HELSINKI COMMISSION HELCOM CORESET/TARGREV JAB 6/2012 JOINT ADVISORY BOARD CORESET/TARGREV Sixth Meeting Gothenburg, Sweden, February 2012

Transcription

1 HELSINKI COMMISSION HELCOM CORESET/TARGREV JAB 6/2012 JOINT ADVISORY BOARD CORESET/TARGREV Sixth Meeting Gothenburg, Sweden, February 2012 Agenda Item 4 Activities of the HELCOM CORESET project Document code: 4/3 Date: Submitted by: Secretariat INTERIM REPORT OF THE CORESET PROJECT The interim report of the HELCOM CORESET project The development of a set of core indicators: Interim report of the HELCOM CORESET project was accepted for web publication in Baltic Sea Environment Proceedings by the 36th Meeting of the HELCOM Heads of Delegation (List of Decisions, paragraph 30). The Part A of the report has gone through a professional language revision and a first lay-out version has been produced, whereas the Part B is currently in a language check. This document presents the current version of the parts A and B of the report. The Meeting is invited to take note of the interim report and provide comments to its lay-out. Note by Secretariat: FOR REASONS OF ECONOMY, THE DELEGATES ARE KINDLY REQUESTED TO BRING THEIR OWN COPIES OF THE DOCUMENTS TO THE MEETING Page 1 of 1

2 Baltic Sea Environment Proceedings No. XX A The development of a set of core indicators: Interim report of the HELCOM CORESET project PART A. Description of the selection process Helsinki Commission Baltic Marine Environment Protection Commission

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4 Baltic Sea Environment Proceedings No. XX A Development of a set of core indicators: Interim report of the HELCOM CORESET project PART A. Description of the selection process Helsinki Commission Baltic Marine Environment Protection Commission

5 Helsinki Commission Katajanokanlaituri 6 B Fi Helsinki Finland Editors: Samuli Korpinen and Ulla Li Zweifel For bibliographic purposes this document should be cited as: HELCOM, Development of a set of core indicators: Interim report of the HELCOM CORESET project. PART A. Description of the selection process. Balt. Sea Environ. Proc. No. XXX A Information included in this publication or extracts thereof are free for citing on the condition that the complete reference to this publication is given as stated above. Copyright 2012 by the Baltic Marine Environment Protection Commission Helsinki Commission Language revision: Howard McKee Design and layout: Bitdesign, Vantaa, Finland Photo credits given in the back cover. Photo credits Front cover and back cover: EK / Metsähallitus 2008 and Metsähallitus Page 5, XX. Page 8, XX. Page 9, XX. Page 12, Johanna Kehus. Page 14, Metsähallitus. Page 17, Metsähallitus Page 19, XX. Page 26, XX. Page 30, XX. Page 37, Essi Keskinen / Metsähallitus Page 40, Pekka Lehtonen Page 45, Metsähallitus Page 46, XX. Page 50, XX. Page 55, XX. Page 56, Krause & Hubner. Page 64, Metsähallitus Page 71, XX. Page 73, XX. Page 76, XX. Page 78, XX. Page 79, Reetta Ljunberg. Page 83, XX. Page 84, XX. Page 86, XX. Page 89, Metsähallitus Disclaimer: This publication does not necessarily reflect the views of the Helsinki Commission. This report should not be regarded as final but should be regarded as an important expert input to follow up the implementation of the Baltic Sea Action Plan, including the facilitation of the national implementation of the EU MSFD for those Contracting Parties that are also EU member states, according to the role of HELCOM as a platform for regional coordination. 2 Number of pages: 101

6 Content Executive summary Introduction Background for the HELCOM work on core indicators Objectives of this report What is a core indicator? Framework of the core indicators The need for new principles Common principles of the core indicators and associated targets The CORESET approach to develop core indicators Are the HELCOM BSAP and the EU MSFD compatible? An overview of GES criteria and proposed indicators addressed by the CORESET biodiversity expert group Biological diversity Descriptor Non-indigenous species Descriptor Food webs Descriptor Seafloor integrity Descriptor Differences and similarities between the BSAP biodiversity objectives and the MSFD biodiversity criteria Human-induced eutrophication Hazardous substances An overview of the MSFD GES Descriptor An overview of the MSFD GES Descriptor What is good environmental status for an indicator? Terms and concepts used in the MSFD Comparison with other classification systems Approaches for setting GES boundaries Approach 1: Based on an acceptable deviation from a reference condition Approach 2: Based on an acceptable deviation from a fixed reference point/period Approach 3: Based on an acceptable deviation from a potential state Approach 4: Based on the knowledge of physiological- or population-related limitations Approach 5: Targets based on temporal trends Approach 6: Biological effects on the condition of an organism GES boundary depends on the type of the pressure response Some general comments on target-setting approaches Decisions on GES boundaries by the biodiversity expert group GES boundaries should not be in conflict with existing policy decisions GES boundaries should consider interlinkages between the proposed core indicators GES boundaries are affected by regime shifts Taking natural fluctuation into account when determining GES boundaries Concluding discussions on GES boundaries by the biodiversity expert group Decisions concerning GES boundaries in the hazardous substances expert group The HELCOM CORESET approach for selecting core indicators Structure of the CORESET project Project workshops, meetings and documents

7 5.3 The process for the selection of biodiversity core indicators The functional groups, predominant habitats and key species Use of anthropogenic pressures in the selection of the indicators The influence of monitoring data on indicator selection Categorisation of the biodiversity indicators The process to develop GES boundaries Selection of core indicators for hazardous substances The selection process of the hazardous substances core indicators Decisions on sampling and data conversions for hazardous substances core indicators Core indicators for seafood safety Geographical scales of the core indicators Biodiversity core indicators and targets Proposed core indicators for biodiversity Core indicators for Descriptor 1 (biodiversity) Core indicators for Descriptor 2 (non-indigenous species) Core indicators for Descriptor 4 (food webs) Core indicators for Descriptor 6 (sea-floor integrity) Candidate indicators for the assessments of biodiversity Candidate state indicators for biodiversity Candidate pressure indicators for biodiversity Supplementary indicators to support the core indicators Supplementary biodiversity indicators Supplementary indicators for environmental variability Hazardous substances core indicators Proposed core indicators for hazardous substances Candidate indicators for hazardous substances Supplementary indicators for hazardous substances Eutrophication core indicators and targets Eutrophication core indicators Eutrophication indicators under development Assessment scales for eutrophication core indicators Monitoring needs for the proposed core indicators Existing COMBINE monitoring for the proposed core indicators Other monitoring for the proposed core indicators Identified gaps in the Baltic monitoring Existing monitoring and the selection of core indicators Conclusions References Glossary Annex 1. Pressures impacting functional groups and predominant habitats Annex 2. Qualitative descriptions of GES

8 Executive summary This HELCOM report presents intermediate results and expert advice by the HELCOM CORESET project on the development of core indicators for biodiversity and hazardous substances. The report provides background information, descriptions and justification to the set of proposed core indicators, candidate indicators and supplementary those indicators. The ultimate aim of the core indicators is to enable indicator-based follow-up of the implementation of the HELCOM Baltic Sea Action Plan (BSAP) and facilitation of the implementation of the EU Marine Strategy Framework Directive (MSFD) in those HELCOM Contracting Parties that are also members of the EU. Proposed core indicators will be developed into indicators, as well as to the setting of targets for 5

9 6 operationalised, regularly monitored and updated indicator reports, providing assessment data utilisable in HELCOM assessments, and placed on the HELCOM website. This further development will take place in the further HELCOM CORESET process until June Amongst hundreds of potential indicators, 15 core indicators were proposed for the assessment of biodiversity and 13 for hazardous substances and their effects. In addition, 23 and 4 candidate, and several supplementary indicators were listed for biodiversity and hazardous substances, respectively. The proposed core indicators fill most of the assessment needs arising from the BSAP and MSFD especially for hazardous substances but not all for biodiversity. For example, an obvious gap is the lack of proposals for underwater habitats and several key functional groups and species of the Baltic Sea have only limited representation in the proposed set. Many of these gaps could be filled in by further development of candidate indicators into core indicators. Candidates are indicators that are considered promising but which at this stage were not proposed as core indicators since they did not fulfil all the set criteria. However, several of the candidate indicators are expected to be developed into core indicators during the project and therefore this distinction should not be focused on too much in this report. Eutrophication core indicators have been developed in a separate HELCOM MONAS process and they are only briefly introduced in this report. Several of the proposed biodiversity indicators however also strongly respond to nutrient enrichment or eutrophication effects. The ambitious aim to have a common set of core indicators for biodiversity, hazardous substances and eutrophication in the Baltic Sea is within our reach. This report presents the process for the selection of core indicators and reports the first results from this process. The proposed set of core indicators should be seen as an early outcome of the project, presenting frames for further indicator development, whereas more detailed methodologies for the sampling, analyses and computation of indicator values are partly missing and boundaries for good environmental status are suggested only for some proposed indicators or parts of the Baltic Sea. The HELCOM Baltic Sea Action Plan (BSAP) provides an important starting point for coherent indicator-based approach towards assessing the state of the Baltic environment by defining a common vision for the healthy Baltic Sea divided into four strategic goals that are further specified by a number of ecological objectives. Moreover, the need to follow-up the progress towards the ecological objectives, goals and vision by the use of indicators and associated quantitative targets as was put forward by the BSAP and later the Declaration of the HELCOM Moscow 2010 ministerial meeting provided the basis for the concept of core indicators. The BSAP and the MSFD have a high degree of coherence and in practice the BSAP can be considered a Baltic Sea s regional response to the MSFD also when it comes to assessment needs. The HELCOM CORESET had a starting point that the approaches to be developed for the BSAP should also be applicable for the MSFD. The goals of the hazardous substances and eutrophication segments of the BSAP, supported by their ecological objectives, well match the corresponding qualitative descriptions of good environmental status in the MSFD. The biodiversity goal of the BSAP consists of three ecological objectives at three different levels of ecosystem organisation, while the MSFD defines the good environmental status related to biodiversity more in detail. There are four qualitative descriptors of good environmental status of biodiversity focusing on different aspects of marine biodiversity: Descriptor 1 addressing biodiversity more in general terms, Descriptor 3 on commercial fish stocks, Descriptor 4 focusing on marine food webs and Descriptor 6 addressing seafloor integrity and benthic ecosystems. The MSFD also provides a finer level of detail for defining the good environmental status descriptors, the criteria of descriptors in the European Commission s decision from In practice, the ecological objectives of the BSAP and the criteria of the MSFD are the meeting point providing an important grounding for what core indicators have been proposed. In addition, the lists of indicators for these MSFD criteria have also been used as a starting point for HELCOM s core indicators. The HELCOM CORESET indicator selection process was started by a scrutiny of the assessment requirements arising from the BSAP, MSFD and related

10 documents, including the HELCOM Monitoring and Assessment Strategy. Common principles for the core indicators, their targets and integration methods were created and endorsed at the HELCOM heads of delegation level, which guided the process. These principles included the guidance that each proposed core indicator should have a link to an anthropogenic pressure, it should be backed up by monitoring data or at least a proposal for monitoring, it should have policy relevance and be scientifically justified. The selection process for biodiversity indicators to be proposed as core, candidate or supporting indicators from a large variety of potential indicators was coherently structured. It started by identification of key species, functional groups and predominant habitats and screening of human pressures on those. The following steps included consideration of the common principles and e.g. whether it would be possible to develop a target for the indicator. The selecting of indicators for hazardous substances considered the same common principles but also the availability of thresholds for good environmental status and PBT properties, i.e., persistence in the environment, bioaccumulation in organisms and toxicity. The identified core indicators describing biodiversity included three indicators for marine mammals, two for waterbirds, six for fish and an indicator for both benthic invertebrates and macrophytes. In addition, the CORESET biodiversity expert group developed a core indicator to assess the status of non-indigenous species. In the group of candidate indicators, there are also indicators, which would fill gaps in the assessments of zooplankton abundance, phytoplankton diversity, quality of benthic communities and habitats and abundance of breeding waterbirds. The report proposes nine core indicators for concentrations of hazardous substances, of which eight are EU Priority Substances or on the final revision list of those. In addition, four of the core indicators are also on the list of HELCOM BSAP. The identified core indicators for the effects of hazardous substances are in use in the Baltic Sea, North Sea and Mediterranean. The availability of monitoring data was the only criterion where exceptions were allowed with certain conditions. Recognizing that the HELCOM joint monitoring programmes do not currently cover more than a couple of biodiversity parameters and that only a few hazardous substances parameters are mandatory to monitor for all countries, it was agreed that core indicators could be proposed from outside current monitoring programme under the conditions that the parameter is cost-efficient to monitor, guidelines for the monitoring will be proposed and the monitoring will be established in association with the next HELCOM monitoring revision. The development of core indicators is a process which cannot be completed in a short project. After publishing of this interim expert report, the activities of the project will continue with the aim to have the operational core indicators with full textual reports placed on the HELCOM website by 2012 and the full indicator-based follow-up system of the BSAP ready by the middle of Although environmental indicators are always simplifications of processes going on in the environment, a jointly monitored set of core indicators will form a firm basis for Baltic wide assessments and facilitate understanding of the linkages of anthropogenic pressures and the state of the Baltic Sea. 7

11 1 Introduction Background for the HELCOM work on core indicators In the Baltic Sea Action Plan (BSAP), the Contracting Parties to the Helsinki Convention agreed to periodically evaluate whether the targets of the Action Plan have been met by using indicator-based assessments (HELCOM 2007). The vision of the BSAP a healthy Baltic Sea was built on both ecological and management objectives, leaning on a structured and coherent approach for environmental assessments (Figure 1.1). Three years after the adoption of the BSAP, the HELCOM Moscow Ministerial Meeting of May 2010 reconfirmed HELCOM s assignment related to environmental assessments:

12 this work shall continue to be based on the following common principles: a common understanding of the good environmental status of the Baltic Sea that we want to achieve by 2021, based on the agreed visions, goals and ecological objectives, and jointly constructed quantitative targets and associated indicators as initiated with the HELCOM Baltic Sea Action Plan ; and as practical implementation of the above principles WE DECIDE that core set indicators with quantitative targets shall be developed for each of the segments of the HELCOM Baltic Sea action Plan, while ensuring that the indicators can also be used for the other international monitoring and reporting requirements inter alia the EU Marine Strategy Framework Directive, and that a full indicator-based follow-up system for the implementation of the HELCOM Baltic Sea Action Plan be further developed and placed on the website by 2013 (Moscow Ministerial Declaration). periodic assessments have been elaborated since the early years of the convention (HELCOM 1986, 1990, 1996, 2001, 2003). HELCOM has also established a variety of indicator fact sheets published on the HELCOM website since 2002; however, only the most recent thematic assessments were based on quantitative indicators and environmental targets reflecting good environmental status. The thematic assessments of eutrophication, biodiversity and hazardous substances (HELCOM 2009 a, b, 2010 a) were all based on indicators and their integration through assessment tools. The HELCOM initial holistic assessment of the ecosystem health of the Baltic Sea (HELCOM 2010 c) integrated the thematic assessments and provided a baseline to follow-up the effectiveness of measures under the BSAP. The EU Marine Strategy Framework Directive (MSFD, Anon. 2008) adopted a year after the BSAP reiterated the need for the protection, sustainable management and restoration of the Baltic and other European seas. The directive inter alia specified assessment requirements, listed predominant pressures on marine ecosystems and widened the assessment requirement to include socio-economic impacts. It also defined qualitative descriptors for the good environmental status (GES) of the marine environment. The MSFD stipulates that GES means the environmental status of marine waters where these provide ecologically diverse and dynamic oceans and seas which are clean, healthy and productive within their intrinsic conditions, and the use of the marine environment is at a level that is sustainable thus safeguarding the potential for uses and activities by current and future generations. According to the directive, the determination of good environmental status and the establishment of environmental targets should be developed in a coherent and coordinated manner in the framework of the requirement of regional cooperation (Anon. 2010, see also MSFD, Article 6). Assessments of the environmental status of the Baltic Sea have, however, been carried out already long before the BSAP and the MSFD. HELCOM The thematic and holistic assessments were the first steps towards fully coordinated assessments since they largely relied on commonly agreed data, indicators, environmental targets and assessment methods (see Section 4.1 and Glossary for definition of target in this report). The experience from the assessment work - as well as the need to cost-efficiently focus monitoring and assessment 9

13 Report on the core indicator identification and TARGREV report CORESET HS January Team meetings: GES, data compilation, indicator methodology, draft indicator reports, gaps and specifications of monitoring CORESET JAB February Work in HELCOM Review of core indicators Integration of indicators Assessment methods Dec CORE EUTRO March CORESET BD March MONAS April Decision on core indicators MONAS September Core indicator reports in web Monitoring revision National processes, incl. MSFD, WFD Determination of GES, targets and associated indicators Determination of GES, targets and associated indicators HELCOM 2013 Ministerial meeting: follow up of the BSAP implementation web page ready for indicators Work in Contracting Parties and for the HELCOM 2013 Ministerial Meeting Figure 1.1 Short-term time line of the activities in the development of core indicators to the assessments of the Baltic Sea marine environment. 10 activities - inspired HELCOM to develop a set of core indicators representative for the entire region, and which can be used to evaluate the effectiveness of the implementation of the BSAP. The requirements for the implementation of the MSFD, e.g. regional cooperation among EU Member States sharing a marine region or subregion, provides an additional policy driver to continue the development of regional indicators. The HELCOM CORESET project for the development of core indicators for hazardous substances and biodiversity started in June The work on eutrophication core indicators had begun earlier under HELCOM MONAS and ran parallel to the CORESET project. The tight implementation schedule of the MSFD forced the project to aim at the delivery of preliminary indicators with GES definitions already in September The project, however, runs until June 2013 and is tasked to operationalise the core indicators and prepare an assessment for the forthcoming follow-up meetings of the BSAP. Figure 1.1 presents the expected time line of the HELCOM CORESET activities during Objectives of this report This report is an interim outcome of expert work in the HELCOM CORESET project. It describes the process of selecting core indicators and approaches to develop quantitative boundaries for good environmental status (GES). In addition, the report suggests which indicators could be further developed into core indicators. The indicators are tentatively classified into core indicators, candidate indicators and supplementary indicators although many of them still lack detailed methodology or regionally adapted GES boundaries. The primary objective of this report is to describe the process of developing the selection of core indicators and the justification for their choice. The report: depicts the assessment strategies of the BSAP and MSFD; presents the process of selecting and refuting the indicators; discusses different possibilities for defining the boundary of good environmental status (GES); and identifies gaps - both in terms of knowledge and in meeting the demands of the BSAP and MSFD with the proposed core indicators. The report also aims at

14 facilitating the future work of indicator development and motivating the work towards further improved environmental assessments. The core indicators presented in this report are not yet products that can be utilised by the Contracting Parties; nor do they cover all ecological objectives of the BSAP or descriptors of the MSFD. They represent a frame for indicator selections reflecting impacts of the main anthropogenic pressures on selected key species, functional groups or predominant habitats. Hence, the set of core indicators presented in the report have caveats which the next CORESET activities will focus on. More detailed methodologies for sampling, analyses and indicator calculation, as well as a regionally representative definition of GES for the indicator, will be developed within the project before the core indicators are proposed to be adopted by the HELCOM Contracting Parties. The first part of this report (Part A) focuses on the selection process of the core indicators and only generally presents the identified indicators. The second part (Part B, HELCOM 2012 a) presents the core and candidate indicators, as well as some supplementary indicators in more detail. VISION A healthy Baltic Sea environment, with diverse biological components functioning in balance, resulting in a good ecological status and supporting a wide range of sustainable human economic and social activities GOALS Eutrophication: The Baltic Sea unaffected by eutrophication Hazardous substances: The Baltic Sea life undisturbed by hazardous substances Biodiversity: Favourable conservation status of Baltic Sea biodiversity ECOLOGICAL OBJECTIVES Concentrations of nutrients close to natural levels Concentrations of hazardous substances close to natural levels Natural marine and coastal landscapes Clear water All fish safe to eat Thriving and balanced communities of plants and animals Natural level of algal blooms Healthy wildlife Viable populations of species Natural distribution and occurrence of plants and animals Radioactivity at pre-chernobyl level Natural oxygen levels Figure 1.2. HELCOM s vision for a healthy Baltic Sea. The vision is divided into four goals, subdivided into ecological objectives. Each ecological objective is measured by core indicators. The vision, ecological objectives and core indicators measure the state of the Baltic marine environment. Further, behind each core indicator there are indicators for the underlying pressure(s) ensuring a closer link to human activities. The aims of the maritime activities are not included separately in the status assessments. 11

15 2 What is a core indicator? Framework of the core indicators The HELCOM core indicators are designed so as to enable the follow-up of the effectiveness of the Baltic Sea Action Plan and to measure the progress towards good environmental status of the Baltic Sea, including coastal and transitional waters. Core indicators form the critical set of indicators which are needed to regularly assess the status of the Baltic Sea marine environment against targets that reflect good environmental status. The set of core indicators is based on the HELCOM Baltic Sea Action Plan, where the vision of a healthy Baltic Sea is divided into four strategic

16 goals, each of which is further divided into ecological objectives (Figure 1.1). The full indicatorbased follow-up system is due to be placed on the HELCOM website by The core indicators aim to allow the assessment of the current status and the tracking of progress towards achieving GES. They are designed to measure the distance from the current environmental status of the Baltic Sea to GES and the HELCOM ecological objectives, goals and vision. At the goal level, a number of indicators grouped under the ecological objectives (HELCOM 2009 b, 2010 a) or quality elements (HELCOM 2009 a) are required to assess the status in an integrated and reliable manner. The integration should be made using assessment tools such as the HELCOM assessment tools, which provide a good basis for the thematic and holistic integrations of indicators, even if they are still subject to further improvement. The preliminary core set of eutrophication indicators and their integration with the HELCOM eutrophication assessment tool (HELCOM 2009 a) provides an example of the way how the core indicators can be integrated to provide a thematic assessment over a certain time period. At the vision level, the core indicators should be developed in a coherent manner in such a way that they could all be used for holistic indicator-based assessment, e.g. with the HOLAS assessment tool (HELCOM 2010 c). To date, while the HELCOM thematic assessments have used indicators similar to the concept of core indicators, the maturity of the indicators has varied considerably. For example, the eutrophication indicators were much further developed than many other indicators and have since been developed into a preliminary core set available at: main/. Hazardous substances indicators, on the other hand, were not harmonised over the region but had a more advanced and reliable confidence evaluation than the eutrophication indicators. As the thematic assessment of biodiversity lacked a common and harmonised agreement on indicators and quantitative targets, it only contributed to a pilot indicator-based assessment; for this reason, the results were considered preliminary. The driving policies for developing a set of core indicators are the HELCOM BSAP as well as the EU Marine Strategy Framework Directive (MSFD), which is of importance for those HELCOM Contracting Parties that are EU Member States. One of the objectives of the HELCOM CORESET project is to develop the HELCOM core indicators in such a way as to ensure coherence among them and coherence with the requirements of the MSFD to assess GES, taking account of the GES descriptors and the criteria and indicators for each descriptor contained in the European Commission Decision on criteria and methodological standards on GES (2010/477/EU, Anon. 2010). The descriptors and criteria provide the foundation for defining good environmental status according to the MSFD (Anon. 2010). Chapter 3 of this report describes how HELCOM ecological objectives align with the GES descriptors. Chapters 6, 7 and 8 present the relationships between the identified core indicators and the GES criteria. The core indicators are also linked to other EU directives: the Water Framework Directive (WFD; Anon. 2000) and the Priority Substance Directive (PSD; Anon b). The PSD provides quantitative targets for hazardous substances, while the results of the geographical intercalibration process under the WFD were followed, to a large extent, in setting the quantitative targets of the HELCOM eutrophication core indicators. In addition, the EU Habitats Directive (Anon. 1992) and the Birds Directive (Anon. 2009) provide important frameworks for the development of core indicators and the definition of GES. 2.2 The need for new principles The concept of core indicators implies that the assessment results are comparable across the region and over time, and that the commonly agreed set of indicators can be used in the whole Baltic Sea area. This requirement implicates that the indicators must be based on common principles. A further need for common principles arises from HELCOM s general aim to harmonise assessment procedures for the whole Baltic Sea region and from the EU legislation. This requires coherence, coordination and cooperation within marine regions when developing targets and associated indicators, and when assessing the status of the marine environment. 13

17 14 Although the HELCOM core indicators were primarily developed to assess the effectiveness of the implementation of the Baltic Sea Action Plan, their other objective is to facilitate the work of those Contracting States who are also EU Member States in the implementation of the MSFD. In this role, the core indicators were aligned with the EU MSFD descriptors as defined through criteria and indicators of Commission Decision 2010/477/EU (Anon. 2010). In HELCOM, common principles for core indicators, quantitative targets and assessment methodologies mainly exist on the basis of the previous work to develop common methodological standards. Such activities are: the HELCOM Monitoring and Assessment Strategy (2005); the HELCOM Data and Information Strategy (2005); the HELCOM COMBINE programme and associated COMBINE manual, as well as PLC and MORS-PRO monitoring programmes with associated guidelines; the Indicator Fact Sheet Procedures (2004); the common approaches in the thematic assessments (2006, 2009a, b, 2010a) and the initial holistic assessment (2010b); and the MONAS intersessional work for developing the demonstration set of eutrophication core indicators ( ). The core indicators thus have a good basis in earlier HELCOM decisions and on-going work; however, with the core indicator concept, their principles require common agreement. The new principles can thus be seen as an upgrade of the above-mentioned agreements, aligning the common principles with the national and European standards, and summarizing the whole set of principles in a harmonised way in a single document. 2.3 Common principles of the core indicators and associated targets The common principles for HELCOM core indicators and their quantitative targets are outlined in Tables 2.1 and 2.2. These principles were developed by HELCOM JAB 1/2010 and 2/2011; agreed upon by HELCOM MONAS 14/2011; and endorsed by HOD 35/2011.

18 Table 2.1 Common principles for HELCOM core indicators, recalling HELCOM Monitoring and Assessment Strategy, as well as the HELCOM Data and Information Strategy. 1 Compiled and updated by Contracting Parties. 1 2 Science-based: Each indicator describes a scientifically sound phenomenon. 1 3 Link to anthropogenic pressures: Status indicators should be linked to anthropogenic pressures and indirectly reflect them, where appropriate, and additional pressure indicators are used and they directly reflect anthropogenic pressures and are tightly linked to human activities. 4 Policy response: The indicator measures part of or fully an ecological objective and/or a descriptor of good environmental status. 1 5 Suitability with assessment tools: The indicator can be used with the assessment tools but the assessment tools will be open for modifications as necessary (cf. Table 3). 6 Suitability with BSAP/MSFD, making best use of the synergies with other Directives and according to the HELCOM Monitoring and Assessment Strategy: The indicator reflects a component contained in the HELCOM system of the vision, goals and ecological objectives and/or MSFD descriptor. 7 Qualitative or quantitative with a textual background report: Indicators, either qualitative or quantitative, are numeric, based on measurements or observations and validated models; they must also have a quantitative target level reflecting the lowest boundary of good environmental status. They also contain a textual background report with interpretation of the indicator results. The report should be published on the HELCOM web site and ultimately should take the form of the three-layered indicator report (cf. preliminary core eutrophication indicator reports) with the main page containing a status map and the main message aimed at decision makers; the second page containing trend information, e.g. for different sub-basins; and the third page containing technical background information and information on the confidence of the assessment. 2 8 Baltic Sea wide: The HELCOM indicators should cover the whole sea area. 3 9 Commonly agreed: The finalised indicators and their interpretation are commonly agreed. among the HELCOM Contracting Parties and HELCOM MONAS is the HELCOM body that should approve the publication of the core indicator reports on the HELCOM web page. 10 Frequently monitored and updated: Data underlying the indicators are collected within the HELCOM coordinated monitoring (HELCOM COMBINE, MORS-PRO, PLC) and the indicator reports will be updated preferably annually or at intervals suitable for the measured factor Harmonised methodology: Data in an indicator will be collected using harmonised monitoring, quality assured analytical methods, as well as harmonised assessment tools, according to the relevant HELCOM guidelines or EU standards, such as methodological standards or guidelines for GES under the MSFD to be delivered by the EC, other relevant international standards Confidence evaluation: The indicator and the data must be assessed using common criteria and this confidence evaluation is to be included in the indicator report. 1 Indicator Fact Sheet procedure (HELCOM MONAS 7/2004, paragraph 5.12, LD 9, of the Outcome of the Meeting). 2 Outcome of HELCOM MONAS 12/2009, paragraph Some biological indicators may be spatially limited due distribution limits or sensitivity of species and/or biotopes. Such indicators should be fl exible to include several species, which measure the same phenomenon (e.g. phytobenthos indicator would include eelgrass, bladderwrack, charophytes and other species, e.g. functional indicators). Table 2.2 Common principles for quantitative or qualitative targets of core indicators. 1 Targets need to be developed for each indicator separately. 2 Purpose of the status targets: The target reflects the boundary between GES and sub-ges. The boundary can be based on a specific score (cf. ecological quality ratio, EQS, sensu WFD and also used in HEAT and BEAT) that can be derived through the use of an Acceptable deviation from a Reference condition. 3 Purpose of the pressure targets: The targets reflecting anthropogenic pressures should guide the progress towards achieving good environmental status. 4 Science-based: A target level should be based on best available scientific knowledge. In the absence of data and/ or modelling results, expert judgment based on common criteria should be involved to support the target setting. 1 5 Spatial variability: Target levels can vary among sub-basins or among sites depending on natural conditions. 6 Confidence of the targets must be evaluated by common criteria and included in the general confidence evaluation of the indicator report. 1 Indicator Fact Sheet procedure (HELCOM MONAS 7/2004, paragraph 5.12, LD 9, of the Outcome of the Meeting). 2 Outcome of HELCOM MONAS 12/2009, paragraph Some biological indicators may be spatially limited due distribution limits or sensitivity of species and/or biotopes. Such indicators should be fl exible to include several species, which measure the same phenomenon (e.g. phytobenthos indicator would include eelgrass, bladderwrack, charophytes and other species, e.g. functional indicators). 15

19 HOD 35/2011 also endorsed a set of common principles for assessment methods; however, they are not the subject of this report and are therefore not presented here. 2.4 The CORESET approach to develop core indicators The HELCOM CORESET project focuses on producing a concise set of indicators for biodiversity and hazardous substances. The project also followed the work on the development of eutrophication core indicators carried out under the HELCOM MONAS group and the HELCOM TARGREV project. The HELCOM strategic goal - environmentally friendly maritime activities - was not addressed by HELCOM CORESET. However, certain issues traditionally considered by the HELCOM MARI- TIME group, such as non-indigenous species, were included under the CORESET biodiversity expert group. The project has based its work on the common principles and frameworks of the HELCOM BSAP and the EU MSFD. Figure 2.1 presents the underlying understanding of the role of core indicators in the HELCOM assessment work: environmental data is refined to indicators, and the assessment needs filter a set of core indicators, which give the hard core to marine assessments. All other indicators can be used to support this set of core indicators. ASSESSMENT OF GOOD ENVIRONMENTAL STATUS BIODIVERSITY CORE INDICATORS EUTROPHICATION PRINCIPLES FOR CORE INDICATORS INDICATORS DATA HAZARDOUS SUBSTANCES Figure 2.1 HELCOM core indicators represent a selection of indicators from a wider pool of assessments, indicators and data. The set of core indicators are used to assess the environmental status. They must go through a screening protocol to ensure that the HELCOM common principles for core indicators are fulfilled. 16

20 3 Are the HELCOM BSAP and the EU MSFD compatible? According to the MSFD, the EU Member States are to determine a set of characteristics for good environmental status (GES) based on eleven qualitative descriptors listed in Annex 1 of the MSFD (Table 3.1). The GES Descriptors 1 (biodiversity), 2 (non-indigenous species), 4 (food webs), 6 (sea floor integrity) and partly 3 (commercially exploited fish and shellfish) are all related to the state of the biological diversity. Descriptors 5 (eutrophication), partly 3 and 7-11 (hydrographical changes, hazardous substances, marine litter and energy/ noise) focus on various pressures on the ecosystem. The EC Decision (Anon. 2010) further divides the descriptors to criteria that are mandatory for EU Member States to assess, and indicators that guide the assessment of the criteria. 17

21 Table 3.1 Qualitative descriptors of good environmental status according to the EU Marine Strategy Framework Directive (Annex I). 1 Biological diversity is maintained. The quality and occurrence of habitats and the distribution and abundance of species are in line with prevailing physiographic, geographic and climatic conditions. 2 Non-indigenous species introduced by human activities are at levels that do not adversely alter the ecosystems. 3 Populations of all commercially exploited fish and shellfish are within safe biological limits, exhibiting a population age and size distribution that is indicative of a healthy stock. 4 All elements of the marine food webs, to the extent that they are known, occur at normal abundance and diversity and levels capable of ensuring the long-term abundance of the species and the retention of their full reproductive capacity. 5 Human-induced eutrophication is minimised, especially adverse effects thereof, such as losses in biodiversity, ecosystem degradation, harmful algae blooms and oxygen deficiency in bottom waters. 6 Sea-floor integrity is at a level that ensures that the structure and functions of the ecosystems are safeguarded and benthic ecosystems, in particular, are not adversely affected. 7 Permanent alteration of hydrographical conditions does not adversely affect marine ecosystems. 8 Concentrations of contaminants are at levels not giving rise to pollution effects. 9 Contaminants in fish and other seafood for human consumption do not exceed levels established by Community legislation or other relevant standards Properties and quantities of marine litter do not cause harm to the coastal and marine environment. 11 Introduction of energy, including underwater noise, is at levels that do not adversely affect the marine environment. Compared to the BSAP, the MSFD GES descriptors cover a wider definition of good environmental status than the BSAP ecological objectives. However, as the BSAP segments, particularly biodiversity, and the associated ecological objectives were only loosely defined in the BSAP, there is no critical difference between the two approaches. Because of limited resources and time, the CORESET project only focused on developing core indicators for biodiversity and hazardous substances, and cooperated with the HELCOM group developing eutrophication core indicators as well as ICES. However, it was decided that indicators measuring descriptors outside the scope of the project (e.g. noise or litter) can be included in the set of core indicators only if they directly affect the state of the biodiversity, e.g. impacts of noise on marine mammals. The GES descriptors included in the project were: 1, 2, 4, 6, 8 and 9 (see the descriptors in Table 3.1). However, the indicators related to fish could also be used partly for Descriptor 3. all aspects relevant for the BSAP and MSFD GES are covered as our knowledge increases. It is noted that some indicators suggested in Commission Dec. 2010/477/EU require further development before they can become operational. Baltic Sea Action Plan BSAP vision Goals Ecological objectives Definition of good environmental status in MSFD Article 3 (5) Core indicators Marine Strategy Framework Directive GES Descriptors, Annex I GES criteria (and indicators), EC Decision 18 Although the time constraints and financial limitations of the CORESET project did not allow the development of core indicators for Descriptors 3, 7, 10 and 11, the HELCOM set of core indicators should aim at covering the whole array of MSFD descriptors and criteria in order to reach a holistic view of the ecosystem. In addition, the initial set of core indicators needs to be revisited to ensure that Figure 3.1. Schematic comparison of the assessment requirements of the HELCOM Baltic Sea Action Plan and the EU Marine Strategy Framework Directive.

22 3.1 An overview of GES criteria and proposed indicators addressed by the CORESET biodiversity expert group The biodiversity expert group of the CORESET project was tasked to address Descriptors 1 (Biodiversity), 2 (Non-indigenous species), 4 (Food webs) and 6 (Seafloor integrity). It was also agreed that Descriptor 3 (Commercial fish) should not be developed by the project. However, the project includes indicators based on commercial fish species where they relate to the assessment of the other mentioned descriptors. Descriptor 5 (Eutrophication) is addressed by the HELCOM MONAS intersessional work for eutrophication core indicators (see Chapter 8) whereas biodiversity related indicators for phytoplankton and other ecosystem components affected by eutrophication have been considered in the CORESET project. Coordination was ensured by information exchange between the MONAS group of eutrophication experts, the TARGREV project and the CORESET project. Several of the biodiversity descriptors included in the project overlap in terms of GES criteria. The relation between biodiversity and Descriptors 2, 4 and 6 is thus outlined below Biological diversity Descriptor 1 The MSFD describes in its first GES descriptor how the biodiversity of the marine environment in the EU should look like in 2020: Biological diversity is maintained. The quality and occurrence of habitats and the distribution and abundance of species are in line with prevailing physiographic, geographic and climatic conditions. To describe and assess the marine environment, the MSFD lists physical, chemical and biological characteristics (Annex III Table 1) that shall be taken into account when setting up marine strategies. According to the EC decision on criteria and methodological standards on the GES of marine waters (Anon. 2010), the assessment of biodiversity should be conducted at three ecological levels: species, habitats (including associated communities) and ecosystems. In brief, the document outlines the following tasks: Species: For each region, sub-region or subdivision, a set of relevant species and functional groups should be defined. The assessment at the species level should be based on three criteria: distribution, population size and population condition. The assessment of species should preferentially be linked to an assessment of their habitat. For functional groups of species, the use of the habitat (community) criteria is more appropriate. Habitats: A habitat is defined by addressing both abiotic characteristics and the associated biological community, treating both elements together in the sense of the term biotope. For each region, sub-region, sub-division, a set of habitat types should be defined. The assessment on the habitat level should be based on three criteria; distribution, extent and condition (including that of the associated communities). Ecosystem structure: The level of ecosystem structure should be based on one criterion that considers the composition and relative proportion of ecosystem components. Functional aspects of the ecosystem are also important and are partly addressed by descriptor 4 on food-webs. The proposed indicators of the EC decision for each of the criteria are outlined in Table

23 Table 3.2. Proposed GES criteria and indicators to assess GES Descriptor 1, Biodiversity according to EC document 2010/477/EU (Anon. 2010). Descriptor 1. Biological diversity is maintained. The quality and occurrence of habitats and the distribution and abundance of species are in line with prevailing physiographic, geographic and climatic conditions. Species level GES Criteria Proposed GES indicators 1.1 Species distribution Distributional range Distribution pattern within the latter Area covered by the species (for sessile/benthic species). 1.2 Population size Abundance and/or biomass. 1.3 Population condition Population demographic characteristics: (body size or age class structure, sex ratio, fecundity rates, survival/mortality rates) Population genetic structure. Habitat level 1.4 Habitat distribution Distributional range Distributional pattern. 1.5 Habitat extent Habitat area Habitat volume. 1.6 Habitat condition Condition of the typical species and communities Relative abundance and/or biomass Physical, hydrological and chemical conditions. Ecosystem level 1.7 Ecosystem structure Composition and relative proportions of ecosystem components (habitats and species) Non-indigenous species Descriptor 2 Descriptor 2 (Non-indigenous species) is partly related to biodiversity (Descriptor 1) but can also be considered as a pressure on the native biodiversity. Nonetheless, non-indigenous species play a significant role in terms of the Baltic biodiversity by decreasing, altering or increasing it. Criterion 2.1 (Abundance and state characterisation of nonindigenous species, in particular invasive species) is a biodiversity indicator in a narrow sense, even though its usability in biodiversity assessments can be questionable. Criterion 2.2 (Impacts of nonindigenous species), on the other hand, is a clear pressure indicator for native biodiversity. Table 3.3 presents Descriptor 2 and the relation of its GES criteria with Descriptor 1. Table 3.3. Biodiversity relevant indicators proposed under Descriptor Descriptor 2: Non-indigenous species introduced by human activities are at levels that do not adversely alter the ecosystem GES criteria Proposed GES indicators Relation to biodiversity criteria 2.1 Abundance and state characterisation of non-indigenous species, in particular invasive species. 2.2 Environmental impact of invasive non-indigenous species Trends in abundance, temporal occurrence and spatial distribution in the wild of non-indigenous species, particularly invasive non-indigenous species (notably in risk areas) in relation to the main vectors and pathways of the spreading of such species Ratio between invasive non-indigenous species and native species in some well-studied taxonomic groups (e.g. fish, macroalgae, molluscs) that may provide a measure of change in species composition (e.g. further to the displacement of native species) Impacts of non-indigenous invasive species at the level of species, habitats and ecosystem, where feasible. Not directly applicable. Invasive species might change biodiversity by filling up niches previously not filled by native species in the young Baltic ecosystem. Thus, there is a relation to D1 by describing species and populations. State indicator of non-indigenous species, Pressure indicator on other biodiversity components. Habitat/Community condition (e.g ). Population distribution, size and condition (1.1, 1.2, 1.3). An impact/pressure indicator for native species and communities.

24 3.1.3 Food webs Descriptor 4 The MSFD criteria for food webs (Descriptor 4) are closely related to the criteria of the biodiversity descriptor. The food web descriptor, however, focuses more on functional aspects than the state and structure of species and communities. An exception is criterion 4.3 (Abundance/distribution of key trophic groups and species) which reflect the state of certain components of biodiversity, but also calls for an identification of a set of key trophic groups and species. Table 3.4 presents Descriptor 4 and the relation of its GES criteria with Descriptor 1. Table 3.4. Biodiversity relevant indicators proposed under Descriptor 4. Descriptor 4 Food webs: All elements of the marine food webs to the extent that they are known, occur at normal abundance and diversity, and are at levels capable of ensuring the long-term abundance of the species and the retention of their full reproductive capacity. GES criteria Proposed GES indicators Relation to biodiversity criteria 4.1 Productivity of key species or trophic groups. 4.2 Proportion of selected species at the top of food webs. 4.3 Abundance/ distribution of key trophic groups and species Performance of key predator species Species/Population condition (1.3.1). (mammals, seabirds) using their production per unit biomass (productivity) Large fish (by weight). Species/Population condition (1.3.1) Ecosystem level/ecosystem structure (1.7.1) Abundance trends of functionally important selected key trophic groups/ species. Species/Distribution or Populations size (1.1.2, 1.2.1) and Habitat/Distribution area (1.4.1, 1.4.2, 1.5.1) Seafloor integrity Descriptor 6 Descriptor 6 shares elements with the biodiversity descriptor although it is partly focused on human pressures. Criterion 6.2 (Condition of benthic communities) directly overlaps with indicators under Descriptor 1, particularly criterion 1.6 (Condition of habitats and associated communities), while criterion 6.1 (Extent of seabed disturbance) is linked to the distribution and intensity of human activities, thus reflecting pressures for biodiversity components that depend on the seafloor integrity. Table 3.5 presents Descriptor 6 and the relation of its GES criteria with Descriptor 1. Table 3.5. Biodiversity relevant indicators proposed under Descriptor 6. Descriptor 6 Sea floor integrity: Sea-floor integrity is at a level that ensures that the structure and functions of the ecosystems are safeguarded and benthic ecosystems, in particular, are not adversely affected. GES criteria Proposed GES indicators Relation to biodiversity criteria 6.1 Physical damage, having regard to substrate characteristics. 6.2 Condition of the benthic community. Type, biomass and areal extent of relevant biogenic substrate. Extent of the seabed significantly affected by human activities for the different substrate types. Presence of particularly sensitive and/or tolerant species. Multi-metric indexes assessing benthic community condition and functionality, such as species diversity and species richness as well as the proportion of opportunistic to sensitive species. Proportion of biomass or number of individuals in the macrobenthos above some specified length/size. Parameters describing the characteristics (shape, slope and intercept) of the size spectrum of the benthic community. Habitat distribution (1.4) or extent (1.5). A measure of the impact on the seafloor. Habitat/Community condition (1.6.1, 1.6.2). 21

25 Differences and similarities between the BSAP biodiversity objectives and the MSFD biodiversity criteria The biodiversity goal of the BSAP is to reach a favourable conservation status of the Baltic Sea biodiversity. The expression favourable conservation status stems from the EU Habitats Directive (92/43/EEC) and infers that habitats and species should be likely to exist in a foreseeable future. This goal is in line with Descriptor 1 of the MSFD, which stipulates that biological diversity is maintained. The biodiversity segment of the BSAP is further described through three ecological objectives: Viable populations of species; Thriving and balanced communities of plants and animals; and Natural marine and coastal landscapes. Thus, both the HELCOM BSAP and the EU MSFD recognise that biodiversity must be addressed at different levels. In practice, the different levels addressed by the BSAP cover: Species - including genetic aspects; Communities - including habitat-forming species; and Landscapes including broad-scale abiotic and biotic habitats. In turn, the MSFD addresses biodiversity at the levels of: Species including genetic aspects; Habitats including abiotic characteristics and associated biological communities; and Ecosystem including the composition and relative proportions of habitats and species. The BSAP and the MSFD address biodiversity in similar ways with only minor inconsistencies between the two approaches. The MSFD level related to the extent of habitats is, for example, addressed under landscapes in the BSAP scheme. The MSFD level related to the ecosystem structure is not explicitly addressed in the BSAP, although indicators related to the composition of habitats and species composition are, in practice, addressed under Communities in the HELCOM BSAP scheme. The difference between the two approaches does not hinder the development of individual indicators - biodiversity indicators developed under one framework can be used for the other. Thus, the HELCOM CORESET project has been able to fulfil the demands of both frameworks through one process. In the BSAP, the non-indigenous species (Descriptor 2) have been included under the maritime segment (the management objective No introductions of alien species from ships). In the CORESET project, the JAB decided that it should be addressed under biodiversity (see Section 3.1.2). Descriptors 4 (Food web) and 6 (particularly criterion 6.2 Condition of benthic communities) are not separately mentioned in the HELCOM BSAP. Since the definition of biodiversity in the BSAP is wide, the assessment of these descriptors does not create any conflict between the BSAP and MSFD schemes. 3.2 Human-induced eutrophication GES Descriptor 5 describes the marine environment without human-induced eutrophication: Human-induced eutrophication is minimised, especially adverse effects thereof, such as losses in biodiversity, ecosystem degradation, harmful algal blooms and oxygen deficiency in bottom waters. This Descriptor is comparable to the HELCOM strategic goal for eutrophication: Baltic Sea unaffected by eutrophication, but less strict. The EC decision document divides Descriptor 5 into three themes: 5.1 nutrient levels; 5.2 the direct effects of nutrient enrichment; and 5.3 indirect effects of nutrient enrichment (Anon. 2010). The three criteria are broader than the BSAP ecological objectives (Table 3.6), but are not in conflict with each other. The BSAP ecological objectives can be categorized in the same scheme as the criteria. A practical difference is that the BSAP ecological objectives are detailed enough to be assessed with only one or a couple of indicators.

26 Table 3.6. The MSFD GES criteria for eutrophication and the BSAP ecological objectives for eutrophication. Descriptor 5. Human-induced eutrophication is minimised, especially adverse effects thereof, such as losses in biodiversity, ecosystem degradation, harmful algal blooms and oxygen deficiency in bottom waters GES criteria BSAP ecological objectives 5.1 Nutrient levels. Concentrations of nutrients close to natural levels. 5.2 Direct effects of nutrient enrichment. Natural level of algal blooms. Clear water. 5.3 Indirect effects of nutrient enrichment. Natural distribution and occurrence of plants and animals. Natural oxygen levels. 3.3 Hazardous substances An overview of the MSFD GES Descriptor 8 The MSFD qualitative descriptors for GES include two descriptors (8 and 9) for the status of hazardous substances and their effects (Tables 3.7 and 3.8). Descriptor 8 states that Concentrations of contaminants are at levels not giving rise to pollution effects. The descriptor includes two criteria: the concentrations of contaminants and the effects of contaminants. The EC decision on the GES criteria (Anon. 2010) only includes one broad indicator for the criterion concentrations of contaminants (see Table 3.7). The indicator obviously comprises several substances in different matrices (e.g. water, sediment and biota) and emphasises that the substance indicators should be comparable with the list of Priority Substances under the Water Framework Directive (Anon. 2000) and the subsequent Priority Substances Directive (Anon b), the latter giving environmental quality standards for the priority substances mainly in water. The EC decision further states that other contaminants which are considered significant should also be taken into account. The criterion Effects of contaminants has been given two indicators (see Table 3.7). The first refers to state indicators which measure the effects of contaminants on organisms (e.g. changes in genes, cells, hormonal levels, general health status, reproductive capacity and malformations), populations (decline), habitats (habitat condition) or ecosystem functioning (inter-specific relationships, changes in trophic chain). The second is a pressure indicator, which has a state component referring to the physical effects of polluting incidents An overview of the MSFD GES Descriptor 9 Descriptor 9 states that: Contaminants in fish and other seafood for human consumption do not exceed the levels established by Community legislation or other relevant standards. It considers the hazardous substances from the human point of view - hazardous substances need to be assessed against existing EU food safety standards. Food safety standards are usually based on the dose approach which has been transformed to concentrations, assuming an average consumption of fish or other seafood. The proposed GES indicators for this descriptor are given in Table 3.8. The first indicator in the table is conceptually very wide and comprises two components. The first, actual levels of contaminants detected, looks at individual substance indicators, which can be many; the second, number of contaminants exceeding maximum regulatory levels, summarizes the substance indicators. The second indicator is related to the previous indicator; however, instead of looking at averages, it focuses on the frequency of target exceedances at the substance level. It can thus be seen as a stricter indicator since averages can sometimes hide significant exceedances of safety standards. The GES criteria and the proposed indicators for both descriptors are conceptually wide and, thus, permit regional solutions for the indicator development and target setting. The regionally selected set of substances and targets must be comparable with the list of priority substances and target levels given in the community legislation. This does not hinder developing indicators that give additional information, such as DDTs, PCBs and PFOS, which are of special concern in the Baltic Sea but not included in the current EU legislation. This is spe- 23

27 cifically stated in the EC decision document (Anon. 2010); however, this does not give any inclination of which quantitative targets should be used for such substance indicators. Table 3.7. Relations of hazardous substances GES criteria and GES indicators under Descriptor 8 and the HELCOM BSAP ecological objectives for the hazardous substances. Descriptor 8. Concentrations of contaminants are at levels that do not give rise to pollution effects. GES criteria Proposed GES indicators BSAP ecological objectives 8.1 Concentrations of contaminants Concentration of the above mentioned contaminants measured in the relevant matrix (such as biota, sediment and water) in a way that ensures comparability with the assessments under Directive 2000/60/EC. 8.2 Effects of contaminants Levels of pollution effects on the ecosystem components concerned with regard to the selected biological processes and taxonomic groups where a cause/effect relationship has been established and needs to be monitored Occurrence, origin (where possible), extent of significant acute pollution events (e.g. slicks from oil and oil products) and their impact on biota physically affected by this pollution. Concentrations of hazardous substances at natural levels. Healthy wildlife. Table 3.8. Relations of hazardous substances GES criteria and GES indicators under Descriptor 9 and the HELCOM BSAP ecological objectives for the hazardous substances. Descriptor 9. Contaminants in fish and other seafood for human consumption do not exceed levels established by Community legislation or other relevant standards. GES criteria Proposed GES indicators BSAP ecological objectives 9.1 Levels, number and frequency of contaminants Actual levels of contaminants that have been detected and number of contaminants which have exceeded maximum regulatory levels Frequency of regulatory levels being exceeded. Safe seafood Differences and similarities between the BSAP ecological objectives and Descriptors 8 and 9. The BSAP ecological objective Concentrations of hazardous substances close to natural levels This HELCOM ecological objective is comparable with GES criterion 8.1 of the MSFD (Table 3.8). The BSAP and MSFD define the target setting differently - the BSAP states that the target should be natural levels (e.g. for persistent organic pollutants zero) while the MSFD allows the concentrations to reach a level not causing pollution effects (which is considered equivalent to the environmental quality standards). The quality standards developed for the WFD follow the reasoning of pollution effects, as they are based on visible effects in sensitive organisms. The HELCOM BSAP, however, gave also intermediate targets, which can be seen as equals to environmental quality standards. The thematic assessment of hazardous substances used the environmental quality standards as thresholds to define the boundary between good status and moderate status (HELCOM 2010a). BSAP ecological objective Healthy wildlife The ecological objective Healthy wildlife is covered by GES criterion 8.2, which measures the effects of hazardous substances on wildlife. The EC decision document (Anon. 2010) and the background document for the hazardous substances in the BSAP 5 do not give specific guidance on the targets that should be used in this case; however, it is clear from the descriptor that pollution effects on organisms or biological processes with well- 5 /stc/fi les/krakow2007/hazardoussubstances_ MM2007.pdf

28 established cause-effect relationships to pollutants should be targeted. This is mainly covered by the first indicator of this criterion in the Commission Decision (Anon. 2010). The second indicator calls for measurements of the occurrence, extent and impacts of pollution effects. In the HELCOM BSAP, some management objectives under the maritime segment also reflect the pressures behind the pollution effects. These are Safe maritime traffic without accidental pollution, Minimum sewage pollution from ships and Zero discharges from offshore platforms. BSAP ecological objective All fish safe to eat The BSAP ecological objective and GES Descriptor 9 both encompass the safety of seafood for human consumption. In the BSAP, targets for this ecological objective have used the EU food safety standards. There is, however, a difference between the rationales behind the BSAP and the MSFD: While MSFD considers Descriptor 9 to deal only with human consumption, the BSAP also includes fishfeeding marine predators and thus considers the consumption from the ecosystem point of view. In the HELCOM thematic assessment of hazardous substances, a choice was made to limit indicators under this ecological objective to human consumption because of practical reasons. In the MSFD, the top predators are assessed under Descriptor 8. It should be also noted that the substances under Descriptor 9 are often the same as under Descriptor 8 and the HELCOM ecological objective Concentrations of hazardous substances close to natural levels. The EU food-related target levels are not as strict as the environmental quality standards because food safety targets assume that humans eat seafood only as part of their nutrition while marine predators consume solely seafood and are thus exposed to much higher levels of contaminants. BSAP ecological objective Radioactivity at the pre-chernobyl level Radioactivity has not been explicitly addressed by the MSFD GES descriptors and/or indicators. However, the MSFD makes it clear that radioactivity should be included in the assessment of pressures (i.e. discharges of radioactive substances as in Annex III, Table 2). In the HELCOM indicator system, the cesium-137 indicator measures the ecological objective for radioactivity. The target for radioactivity in the Baltic Sea has been set by the HELCOM MORS group (for cesium-137 in fish). In conclusion, the HELCOM ecological objectives and GES descriptors go almost hand in hand in the case of hazardous substances. All indicators in the HELCOM CORESET project can be developed to benefit both purposes. The difference in the rationales behind the BSAP (close to natural levels) and MSFD targets (no pollution effects) was solved by the expert group in their first and second workshops, where it was decided that the target (defining the boundary for GES) will be set on the basis of the MSFD rationale since the quality standards, in practice, are low enough to help progress towards the BSAP target of natural levels. 25

29 4 What is good environmental status for an indicator? Terms and concepts used in the MSFD The central objective of the MSFD is to achieve or maintain good environmental status (GES) of Europe s marine environment by 2020; further, Article 9 stipulates that GES should be determined in each marine region. The criteria for assessing the extent to which GES is being achieved are those outlined in the EC decision document (Anon. 2010) (see Chapter 3). The MSFD refers to two status classes: GES and the status below GES (sub-ges). Thus, for each indicator that is chosen to reflect GES, a definition of GES must be established in order to use the indicator in practice.

30 The MSFD links the definition of good environmental status to the concept of sustainable use: good environmental status means the environmental status of marine waters where these provide ecologically diverse and dynamic oceans and seas which are clean, healthy and productive within their intrinsic conditions, and the use of the marine environment is at a level that is sustainable, thus safeguarding the potential for uses and activities by current and future generations (Article 3 [5]). The directive does not further define the term sustainable use in practical terms. Furthermore, the MSFD stipulates that a comprehensive set of environmental targets and associated indicators should be established (Article 10), where environmental target means a qualitative or quantitative statement on the desired condition of the different components of, and pressures and impacts on, marine waters in respect of each marine region or subregion (Article 3 [3]). An interpretation of Articles 9 and 10 and the above-mentioned terms is on-going in a WG GES drafting group co-led by Germany, for example, in which several of the HELCOM Contracting Parties are participating. The interpretation was not finalised during the CORESET indicator development. In the HELCOM common principles for core indicators, the boundary between GES/sub-GES should be defined in qualitative and quantitative terms and is referred to as the target for the selected indicators. However, it should be noted that the word target may be misleading under the MSFD referring to Article 10, and in cases where the status is already in GES and aim should be to maintain the current status, which may be above the target level. Therefore, the term GES boundary is used synonymously with environmental target and is the preferred expression when related to state indicators. 4.2 Comparison with other classification systems Environmental assessments aim at giving an evaluation of the state - i.e. whether GES has been reached or not. Preferentially, environmental assessment should also provide information on the direction of change, i.e. whether the state is moving towards or from GES. As indicated above, the MSFD does not define whether a binomial or a more detailed classification should be used, while the EU WFD (Anon. 2000) uses a five-level classification to describe a more detailed status of ecological status in coastal, transitional and inland waters: the acceptable state is described as high and good and the unacceptable classes as moderate, poor and bad (Figure 4.1). The HELCOM thematic assessments have used a similar five-class system. For the chemical status in waters up to 12 nautical miles from the baseline, the WFD uses a two-class system (good chemical status achieved / not achieved). Since the MSFD and WFD overlap in coastal waters, it is important that the interpretation of good status is in agreement between the two directives. The CORESET project has discussed and noted that this is not obviously the case; the WFD defines good status as only slightly deviating from type-specific conditions and communities (2000/60/EC, Annex V, Table 1.2), while the MSFD definition of GES is linked to ecologically diverse and dynamic oceans and seas which are clean, healthy and productive within their intrinsic conditions as well as to sustainable use as presented above. For the time being, however, the project has taken a pragmatic approach and decided that for those indicators that have previously been used in the implementation of the WFD and are now also proposed to be used as core indicators, the GES boundary should be aligned with the good/moderate boundary defined in the WFD. Thus, the range covered by bad, poor and moderate is tentatively considered as representing sub-ges while the lower range limit of good status is considered to reflect the boundary between GES and sub-ges. Likewise, the GES boundary could tentatively be compared to the boundary favourable-unfavourable conservation status used in the Habitats Directive. 27

31 MSFD GES Sub-GES WFD High Good Moderate Poor Bad HD Favourable Unfavourable-Inadequate Unfavourable-Bad Figure 4.1. Status classification in the Marine Strategy Directive (MSFD); the Water Framework Directive (WFD); and the Habitats Directive (HD) and their possible relationship. Note that the MSFD uses the concept Good Environmental Status ; the WFD Good Ecological Status ; and the HD Favourable conservation status. Current HELCOM assessment tools use a similar approach as the WFD for good ecological status. The HELCOM CORESET project drafted qualitative GES boundaries (see Annex 2) to facilitate the development of quantitative targets/ges boundaries for the proposed indicators in accordance with the HELCOM common principles of core indicators, targets and indicator integration methods endorsed by HELCOM HOD 35/2011 (Tables 2.1 and 2.2). 4.3 Approaches for setting GES boundaries Discussions on different approaches to determine the boundary between GES/sub-GES have been given dedicated attention at the CORESET project meetings. The HELCOM Secretariat and a number of experts who participate in the CORESET working teams also attended a Workshop on approaches to determining GES for biodiversity that was held In November 2010 by the OSPAR ICG-COBAM group who coordinate biodiversity aspects of the MSFD within OSPAR. The approaches presented below draw on the discussions and conclusions of these meetings. The approaches setting GES boundaries that have been discussed can be divided into six main categories, of which the five former focus on setting the GES boundary for biodiversity indicators Approach 1: Based on an acceptable deviation from a reference condition In the HELCOM integrated assessment of eutrophication (HELCOM 2009a), the predominant approach to determine good status was to first define a reference condition and second an acceptable deviation from the reference condition which defines the boundary of good/below-good status. This approach is similar to the methods used in the implementation of the WFD that required the establishment of type-specific reference conditions. Ideally, the reference condition should reflect the environmental condition when there is a lack of human pressure or it is very low. The reference condition can be based on, for example: a) existing reference sites or populations that are considered as unimpacted by human pressures; b) historical records that date back to the time when human pressures are considered as being low or absent; or c) the output of modelling to derive the unimpacted state (e.g. modelled by using related variables where the reference condition is known). The main drawback with this approach is the lack of existing unimpacted sites in the Baltic Sea and historical data that date back to the prehuman Unimpacted state Deteriorating state, increasing pressure Reference condition Acceptable deviation GES boundary Figure 4.2. Target setting by a reference condition and an acceptable deviation. The unimpacted state is set on the basis of an existing unimpacted condition or a historic unimpacted condition or a modelled unimpacted condition. 28

32 impact period. During the COBAM GES workshop, this approach was considered as the most robust for target setting related to seabed habitats, while it was not considered an appropriate approach for mammals, fish, birds and pelagic habitats due the lack of historic data or unimpacted areas. Some old hydrographic datasets exist for the Baltic Sea which can, if appropriate, be used as a basis of modelling Approach 2: Based on an acceptable deviation from a fixed reference point/period When it is not feasible to establish a reference condition, the state at a fixed time point or time period can be defined as a reference state to which future assessments should be related to, for example: a) to establish a reference period based on the first years or a selected time period in the existing data series; or b) to establish a reference point based on the current state. As in approach 1, the GES boundary can be derived by defining a certain acceptable deviation from the reference period/point. Since the reference period/point typically stems from a time period when human pressures were already present, the acceptable deviation can be expected to be smaller than when using a reference condition as the starting point. An inherent problem with this approach is that the length of the data series typically varies between organism groups, for example. This may not be a problem when assessing the state of a specific organism group or habitat over time. However, when reference states are derived from different time periods, the GES boundaries for different organism groups and habitats may be incompatible with each other. Nevertheless, the establishment of a reference state at a fixed time point/period was the most commonly used practice in the previous HELCOM pilot studies of biodiversity since relatively long data series (decades) exist for several organism groups. Defining the reference state as the current state is a practical approach; however, it masks previous deteriorations in the range, extent and condition of habitats and species. Therefore, this approach should preferentially be accompanied with other approaches such as the use of other variables extending farther back in time, modelling, or expert judgment. In such a case, the target should be for no further deterioration and, where appropriate and possible, for improvement in the state. However, as some parameters may show improved environmental status at present (e.g. seal health), this approach may be very appropriate. Unimpacted state Deteriorating state, increasing pressure Acceptable deviation Reference GES boundary condition Figure 4.3. Target setting by a reference point/period. The reference point is set as the first point in a data series or as the current time. 29

33 4.3.3 Approach 3: Based on an acceptable deviation from a potential state This type of reference state can be used when an ecological condition, which is required to sustain a certain species or population, is known. The reference state can be based on, for example: a) the potential distribution or range, based on physical and ecological conditions and knowledge of the habitat requirements for the species in question; or b) the potential population size, based on the knowledge of the carrying capacity of the system. The use of the potential range, population, etc. is one of the recommended approaches for establishing reference values as required by the Habitats Directive. For example, a habitat distribution may increase, if existing pressures are reduced or removed. As for approaches 1 and 2, the target (favourable reference value in the Habitats Directive) is established by defining an acceptable deviation from the potential state. Unimpacted state Deteriorating state, increasing pressure Potential state Acceptable deviation GES boundary Figure 4.4. Target setting by a potential state. The potential is based on, for example, the physical and ecological conditions and knowledge of habitat requirements or carrying capacity. 30

34 4.3.4 Approach 4: Based on the knowledge of physiological- or population-related limitations When using indicators that are related to the health of a population or the population size, the targets can potentially be set at known limitations related to these features, for example: a) the average reproduction rate based on the knowledge of healthy populations; b) population size limitations based on the knowledge of sustainable recruitment levels; or c) physiological limits to certain physic-chemical conditions such as hypoxia. This category of targets can be set based on existing knowledge or the modelling of conditions in the absence of significant pressures without defining a reference condition or reference point. This type of target setting has not been widely used in the previous HELCOM assessments. The GES criteria for the Biodiversity descriptor can include targets related to physiology, for example, by including condition among the aspects to be reflected in the indicators (Anon. 2010). The MSFD definition of GES, as linked to sustainable use, also contains the possibility to consider safe biological or precautionary approach limits, for example, as GES boundaries without reference to historic conditions Approach 5: Targets based on temporal trends In many cases, it may be feasible to develop indicators that reflect a change in the environment over a time period; if so, the target may reflect the direction and/or amount of change. As in the previous approaches, the target can be a fixed value (i.e. slope of the change) or a range of values (i.e. a variation of the slope). The advantage of this approach is that trend indicators may be easier to develop and a certain slope of change can be set as a GES boundary on the basis of ecological reasons, political decisions (e.g. the year when GES should be achieved) or for predefined shorter periods (after which the slope will be re-evaluated) such as the MSFD s six-year implementation cycle. The trend-based GES boundaries can also serve as an intermediate approach before exact GES boundaries have been identified and validated. There are, however, at least three disadvantages which should be considered before applying this approach: 1) in order to set a slope, a target point must be set at the end of the temporal scale (see Figure 4.5); 2) the slope target can only be an intermediate target since the change cannot continue forever; and 3) the slope does not explicitly define GES but rather a desired direction towards GES. A practical solution would be to set an intermediate target that could be used to set the slope of the change. Deteriorating state Indicator value Intermediate target years Figure 4.5. Target setting by using slopes of temporal trend curves. The green line reflects progress towards GES; trends below the slope would thus indicate sub-ges and vice versa. 31

35 4.3.6 Approach 6: Biological effects on the condition of an organism GES boundaries can be directly set on the basis of adverse effects of a pressure on individual organisms without using reference conditions and acceptable deviations from it. Although the measurements are made at the organism level, the aim is to follow population-level impacts; for this reason, the approach is highly relevant for target setting in environmental assessments. Even though it is mainly restricted to measure the impacts of hazardous substances, this approach is also applicable to the impacts of noise, marine litter and even changes in the abiotic environment (hydrographical changes, oxygen levels, etc). The target levels in the assessments of hazardous substances follow this approach exclusively. They are based on field and laboratory measurements on the effects of specific substances on viability, reduced reproductive output or other reduced condition of organisms. Such targets include Environmental Quality Standards; specific Quality Standards; Environmental Assessment Criteria; Background Assessment Criteria; and Effect Range Low. This approach also includes targets for indicators that measure the biological effects of hazardous substances. These indicators, however, do not measure the levels of specific substances; rather, they measure the impacts of a substance, substance group or a mixture of substances on an organism. The effects are measured at the enzymatic, sub-cellular, cellular, tissue, organism or population levels. The organism- and populationlevel measurements mainly focus on reproductive failures GES boundary depends on the type of the pressure response The previous approaches in this section focused on the linear responses of an indicator to anthropogenic pressures; however, in the environment, a linear response is only one potential response among several others (e.g. unimodal, exponential and S-type). Furthermore, the use of a single target and thus two status classes is based on an assumption of a unidirectional response. However, good status is not necessarily located at one end of a numeric scale. For sprat (Sprattus sprattus), for example, a small population size may be a sign of intensive fishing, whereas a large population size may be a sign of low predation by cod - also a bad sign from the ecosystem perspective. In this case, GES could be defined as a range with sub-ges located at two ends of the numeric scale. This is potentially relevant for a number of indicators - such as population size, biomass and productivity - that are influenced by both bottom-up and topdown processes. Unimpacted state Deteriorating state, increasing pressure No effects measured No acute, but some chronic effects Some acute and chronic effects Many acute and chronic effects Figure 4.6. Target setting by measuring the effects of a pressure on the condition of an organism. Several of the existing environmental targets have been placed at the level where acute effects do not occur and only few chronic effects are found. The targets are also often set on the basis of their biomagnification in the food chain. GES boundaries Deteriorating state Unimpacted state Deteriorating state Figure 4.7. Bidirectional response of an indicator to environmental pressures. 32

36 4.4 Some general comments on target-setting approaches It should be noted that when the above-mentioned approaches have been applied, for example in the implementation of the WFD, a combination of approaches were used based on a combination of historic data, statistical approaches and modelling. In addition, an element of expert judgement is usually a component in all approaches. A conclusion from the OSPAR ICG-COBAM GES workshop was that expert judgement plays a valuable and useful role in target setting - although care should be taken to make the process transparent. The latter was also emphasized by the CORESET Joint Advisory Board. For the three first approaches, it should be noted that while the use of a reference condition, reference point/periods and potential states are useful when establishing the optimal state under given conditions, it is the acceptable deviation that is the pivotal definition. This is because it is this value that determines the GES boundary, taking into account the natural variability of the parameter while allowing for a sustainable use of the marine environment, as given in the MSFD. One of the principles for the core indicators is that HELCOM s core indicators respond to anthropogenic pressures (Table 2.1). Ideally, therefore, each indicator should have a specific response gradient to a pressure or a mixture of pressures. On this response gradient, a threshold may exist which can be proposed as the boundary between GES and sub-ges. However, in many cases such thresholds cannot be detected and all too often the relation between the pressures and state indicators is not well established. Therefore, more theoretical approaches need to be used in order to find the boundary for GES. When long-term data sets have been available, a statistical approach - taking natural variation into account - has often been used to determine the boundary between good/ below-good status, as in the implementation of the WFD and the recent HELCOM assessments. 4.5 Decisions on GES boundaries by the biodiversity expert group GES boundaries should not be in conflict with existing policy decisions The CORESET project has concluded that it is important that GES boundaries are not in conflict with the existing policy decisions. Of direct relevance for biodiversity is the decision in the Baltic Sea Action Plan (BSAP, HELCOM 2007) where the Contracting Parties to HELCOM have provisionally agreed on nutrient load reduction targets that are linked to an agreement on desirable water transparencies in the different sub-basins of the Baltic Sea. The agreed water transparencies can thus be viewed as the target for GES as regards this parameter/indicator. Good status of water transparency was last met in the Baltic Sea during the 1970s and 1980s. In some sub-basins like the Bothnian Sea and Bothnian Bay, water transparency is at good status even today; for this reason, no BSAP nutrient reduction requirements are targeted to them. In the thematic assessment of eutrophication (HELCOM 2009 a), GES for chlorophyll a and inorganic nutrient concentrations have been specifically defined for the sub-basins. These already agreed definitions of GES may affect several of the indicators discussed in the project, such as the lower depth distribution of macrophytes; the biomass ratio of perennial/opportunistic macrophytes; indicators related to phytoplankton community composition; herbivorous zooplankton; and macrozoobenthic communities. Biomass targets for spawning stock biomass (SSB) of commercially exploited fish species have been set to safeguard a viable population of a fish population, taking into account annual reproductive and growth parameters. The targets for the maximum sustainable yield (MSY) include the aspect of allowable fishing mortality. These policy advice targets for SSB or MSY will influence large zooplankton biomass/abundance and food web related fish indicators, for example. The EU Habitats Directive (HD) (Anon. 1992) requires an assessment of favourable conservation status (FCS) of habitats given in the directive. The 33

37 GES boundaries of core indicators should not be in conflict with FCS thresholds. The EU Birds Directive (Anon. 2009) gives objectives for a number of breeding birds in Special Protection Areas (SPAs). Its assessment scale is currently under preparation and will possibly be in-line with the HD-classification system. The Birds Directive does not define GES - it defines the target to maintain all wild living bird species. Adverse effects from human activities shall be avoided and will be part of programmes of measure GES boundaries should consider interlinkages between the proposed core indicators Several of the proposed core indicators within the CORESET project are interlinked with each other, especially those that are related to abundance, biomass or the productivity of species. For these indicators, it is necessary to analyse whether the proposed definitions of GES are compatible with each other. Ultimately, while the proposed indicators are all linked to each other, examples of obvious interlinkages between indicators discussed during the course of the project are: Zooplankton biomass - affected, for example, by chlorophyll a and size of fish stocks consuming zooplankton; Relative abundance of cyprinids - affected by chlorophyll a and macrozoobenthos abundance/ biomass; Relative abundance of piscivorous fish - affected by the population size of prey stocks and seals and predatory seabirds; Growth rate of populations of marine mammals - affected by the size and quality of fish stocks; and Population abundance of seabirds - affected by the biomass of fish, macrozoobenthos and plants. Eventually, GES of all the core indicators must be calibrated to ensure that they are compatible with each other. At this time point, such evaluation can only be made based on expert evaluation while, optimally, a dedicated modelling effort should be used to address the compatibility between the GES of different indicators. Blubber thickness of marine mammals Fish trophic index Trends in arrival of new NIS Preganancy rate of marine mammals Proportion of large fish Population growth of marine mammals Fish trophic group abundance Copepod biomass White-tailed eagle productivity Fish diversity Biomass of microphageous zpl Abundance of wintering seabirds Fish species abundance Distribution of wintering seabirds Fish mean size Macrozoobenthic indices Abundance of breeding seabirds Depth distribution of macrophytes 34 Figure 4.8. Interlinkages of core indicators, particularly trophic relationships and interlinkages between GES boundaries. Selected candidate indicators have been included (dashed boxes). Although the indicators for non-indigenous species have obvious links to many other indicators, they do not have consequences to GES boundaries.

38 4.5.3 GES boundaries are affected by regime shifts Several studies have indicated pronounced regime shifts in the Baltic Sea ecosystem, i.e. relatively sudden changes in the structure and function of the system (Österblom et al. 2007, Möllmann et al. 2008). Some of these shifts have been linked to human pressures such as eutrophication, fishing and hunting, whereas some are also linked to changes in the climate. If using historical data as a basis for defining GES, data series of different lengths will thus cover different regimes in the Baltic Sea. The ICES Working Group on Integrated Assessment of the Baltic Sea (WGIAB) has analysed long-term data sets from the Baltic Sea and detected a particularly strong period of reorganisation - detectable in all major basins of the Baltic Sea - between 1987 and 1989 (ICES 2011 a). This change has primarily been linked to increases in temperature and decreases in salinity caused by climate-driven changes. These changes have definite implications for biodiversity since the variation in climate affects the intrinsic properties of the sea and thus changes the conditions for proliferation of species and habitats. In this context, it should also be noted that the objective of Descriptor 1 is that the quality and occurrence of habitats and the distribution and abundance of species are in line with the prevailing physiographic, geographic and climate conditions. To avoid this particular problem of non-comparable GES boundaries, the CORESET biodiversity expert group discussed whether it would be possible to determine GES as being set to a specific time period for all indicators (see Section 5.3.2). However, this option was discarded because: 1) the approach would limit use of historical data to the length of the shortest data series, which only dates back to the 1980s for some of the proposed core indicators; 2) different organism groups respond at different temporal and spatial scales, at times with considerable lag; and 3) the impact of different anthropogenic pressures on different components has varied over time. The project discussed the use of a pragmatic approach for taking eventual regime shifts in to account by conditioning the GES boundaries, i.e. to define under which circumstances the proposed GES boundaries are applicable. For example, if the physiological limitation as regards salinity is known for a certain species, the GES can be conditioned by defining within which salinity range the GES applies Taking natural fluctuation into account when determining GES boundaries When determining GES, natural variation has to be taken into account. In the current HELCOM assessment tools, this was considered when setting the acceptable deviation from the defined reference condition. The acceptable deviation is ideally based on dose-response relationships when being set for nutrients and primary producers, for example. As stated, however, the determination of GES is not limited to the use of reference conditions and acceptable deviation - a GES boundary can also be set directly. In fact, for hazardous substances, targets have been set on the basis of various noeffect concentrations. Setting aside the acceptable deviation in setting the GES boundary does not mean, however, that natural variation can be neglected. While a harmonized method to address natural variation should be strived for, it was not possible to explore and conclude this matter during the time course of the CORESET project. The assessment cycles of the BSAP and MSFD should be used to check and, if necessary, re-adjust the GES boundaries with new information on natural variation within the indicator (see Section on regime shifts) Concluding discussions on GES boundaries by the biodiversity expert group In summary, the most important issues discussed and concluded during the CORESET biodiversity expert group meeting were: that it is not possible to decide on one approach for defining boundaries for GES for all core indicators - the approaches will differ between indicators and this is warranted based on both ecological as well as practical considerations; there is a need to consider natural variability when defining the GES boundary; there is a need to consider defining GES as a range rather than a boundary when the response to deteriorating conditions may be bi-directional; 35

39 36 there is a need to align GES boundaries between core indicators to avoid GES conflicts (including ensuring the equivalence of acceptable deviation values across indicators); there is a need to consider regional and temporal differences within an indicator; the GES boundaries should heed and, if suitable, be anchored in existing policy decisions, for example water transparency as agreed in the BSAP or habitat extent as given by the Habitats Directive; and when relevant, it should be considered to condition the GES boundaries, i.e. to re-evaluate them if the intrinsic conditions (e.g. salinity) change above given limits; The proposed GES boundaries for the biodiversity core indicators are presented in Chapter 6; Annex 2; and Part B of this report (HELCOM 2012 a). 4.6 Decisions concerning GES boundaries in the hazardous substances expert group The hazardous substances expert group decided already in the first meeting that it is beyond the capacity of the group to develop new GES boundaries. Instead, the group concentrated on finding existing targets such as Environmental Quality Standards (EQS) or specific Quality Standards (QS) of the WFD, OSPAR Environmental Assessment Criteria (EAC) or Background Assessment Criteria (BAC) and the US Effect Range - Low values (ER-L). Some substances that are relevant for the marine ecosystem do not have EQS targets for preferred matrices (biota and sediment) given by the Priority Substance Directive. In such cases, there are other quantitative targets available. EAC and BAC are quantitative targets developed by OSPAR. Other quantitative targets, for example those used in US EPA and NOAA for marine, coastal or freshwaters (Effect Range - Low), can also be used; however, it should be further studied how applicable they are to the Baltic Sea conditions. The EAC and the US values are based on the lethal doses of hazardous substances for sensitive benthic invertebrates and the use of the precautionary principle. The EQS values are often lower for seawaters than for freshwaters because of a cautionary factor which was applied if there are too few impact studies in marine environment. The group acknowledged the different objectives of the BSAP ecological objective Concentrations of hazardous substances at natural levels and the EU target in the MSFD, which aims at levels not causing pollution effects. It was decided to follow the EU objective since most of the target levels have been developed according to this principle (except BAC). The group established that although the HELCOM BSAP objective is the ultimate aim, they noted that it may be more relevant for metals (natural elements) than for synthetic substances which should have the ultimate level of zero in the environment. When deciding the different targets, the group gave priority to those EQSs that are specifically mentioned in the MSFD and have a legally binding role in the region. The specific Quality Standards (QS), which are equivalent targets in all other matrices except that of an EQS but are not legally binding, were used with a similar preference. Both are currently being developed for many priority substances under the WFD WG-E. The group also closely followed the revision of the list of priority substances in the WFD WG E because some of the selected core indicators were not among the agreed EU priority substances, even though there is a draft revision list of them (see Chapter 5 for further discussion). For these substances, it was decided that the draft EQS/ QS targets will be proposed as provisional GES boundaries, albeit they were not yet agreed in the EU. These will need to be revisited in light of the progress in the EU on developing these EQS/QS and experience gained in their application in the marine environment. There are substances that are highly relevant to the Baltic environment but are not the EU Priority substances list (or on the revision list), such as some polyaromatic hydrocarbons (PAH) and cesium-137. Moreover, because some substances are only water targets available in the current or proposed EQS scheme, EAC or ER-L targets had to be chosen (e.g. DDE in sediment and biota). The selected GES boundaries for the hazardous substances core indicators are presented in Chapter 7.

40 5 The HELCOM CORESET approach for selecting core indicators The selection of the set of core indicators for biodiversity and hazardous substances in the HELCOM CORESET project was a structured process that was initiated by HELCOM Heads of Delegation, coordinated by the Secretariat and carried out by experts working on different indicators. In this section, the structure of the project expert group and the process of selecting the core indicators for the two themes are discussed. 37

41 5.1 Structure of the CORESET project The CORESET project was divided into two work packages: biodiversity and hazardous substances. The HELCOM Contracting Parties nominated experts to both packages to form two expert groups. The task of the hazardous substances group was more straightforward and thus no division into smaller teams was necessary; for biodiversity, however, further grouping was necessary due to the wide scope of the issue. The biodiversity group decided that the development of indicators should be carried out by six teams who would each focus on: 1. Mammals 2. Birds 3. Fish 4. Pelagic habitats (including associated communities) 5. Seabed habitats (including associated communities) 6. Non-indigenous species The reason for organising the biodiversity teams by organism groups and habitats according to Annex III Table 1 (MSFD) rather than the MSFD descriptors is the apparent overlap between several of the MSFD descriptors (see Chapter 3). This structure was therefore considered to provide synergetic effects. It was decided that the teams work should result in a list of candidate indicators to be further discussed during the meetings of the biodiversity expert group. It was also decided that key species and key trophic groups should be defined by the working teams to facilitate the development of indicators, particularly for Descriptor 4 (Food webs), in which several of the proposed criteria and indicators are related to these concepts. Although no separate working team was established for food web indicators, experts from several teams joined in cross-sectoral discussions related to Descriptor 4 during the workshops. The CORESET work was steered by the HELCOM Joint Advisory Board of the CORESET and TARGREV Projects (JAB). HELCOM JAB also functioned as the coordination platform of the regional implementation of the MSFD in the Baltic Sea. At the higher level, the HELCOM Monitoring and Assessment Group (MONAS) and the HELCOM Heads of Delegation (HOD) followed the work and steered or accepted the critical steps of the process. HELCOM Heads of Delegations HELCOM Monitoring and Assessment Group (MONAS) Joint Advisory Board for the HELCOM CORESET and TARGREV Projects (JAB) CORESET biodiversity group CORESET hazardous substances group HELCOM TARGREV project MONAS eutrophication core indicators group Team Marine mammals Team Seabirds Team Fish Team Seabed habitats and communities Team Pelagic habitats and communities Team Non-indigenous species Figure 5.1. Structure of the HELCOM CORESET project and their relation to other HELCOM bodies. 38 Table 5.1. Number of experts in the HELCOM CORESET expert groups on the basis of the participation on meetings. DEN EC EST FIN GER LAT LIT POL RUS SWE Other Total Hazardous substances group Biodiversity group *

42 Coordination with the eutrophication experts developing the core indicators under the HELCOM MONAS was assured by regular information exchange between the two processes. As eutrophication core indicators are in a more advanced stage, the CORESET groups followed their good experience in many cases. The project also followed the scientific work carried out in the HELCOM TARGREV project, which reviews and possibly revises the GES boundaries for the Baltic eutrophication core indicators. The CORESET project also followed the work being carried out in OSPAR ICG-COBAM, OSPAR CEMP and ICES (e.g. WGIAB and SGEH) as well as coordinated discussions of EU Member States in the interpretation of the MSFD (e.g. the document Common understanding of (Initial) Assessment, Determination of Good Environmental Status (GES) & Establishment of Environmental Targets ). In addition, members of the HELCOM ZEN QAI and HELCOM FISH-PRO projects as well as HELCOM SEAL EG have also contributed to the biodiversity groups. 5.2 Project workshops, meetings and documents Although the CORESET project has mainly worked intersessionally, the expert groups had held seven workshops by autumn 2011 (Table 5.2). The hazardous substances group met three times during and a fourth workshop was scheduled for January 2012 to ensure the operationalisation of the core indicators. The biodiversity group organised four workshops during the same period. The focus teams had no obligation to meet separately since many of the participating experts did not have the resources to travel. However, the teams communicated via and met unofficially to exchange views. HELCOM JAB met four times during the indicator development period in The second phase of the project, starting in autumn 2011, will have another series of workshops. One of the key elements in the success of the indicator development was the project documents developed by the project s staff and national experts. Their development was guided by HELCOM JAB and MONAS with the experts providing input both intersessionally and during the workshops. The guidelines and other project documents ensured that the tasks were clear and the products comparable. They also allowed HELCOM JAB, other HELCOM bodies, experts outside the region as well as other interested parties to follow the process and provided material for this report. Table 5.2. Meetings of the HELCOM CORESET project. Time and place Meeting September 2010, Stockholm HELCOM JAB 1/ October 2010, Hamburg HELCOM CORESET HS 1/ November 2010, Helsinki HELCOM CORESET BD 1/ February 2011, Helsinki HELCOM CORESET HS 2/ February 2011, Gothenburg HELCOM CORESET BD 2/ March 2011, Berlin HELCOM JAB 2/ May 1 June 2011, Klaipeda HELCOM CORESET HS 3/ June 2011, Riga HELCOM CORESET BD 3/ June 2011, Warsaw HELCOM JAB 3/ September 2011, Copenhagen HELCOM CORESET BD 4/ October 2011, Vilnius HELCOM JAB 4/ The process for the selection of biodiversity core indicators The identification of a set of core indicators for the Baltic biodiversity followed a coherent and structured process, as agreed during the first expert workshop of the biodiversity expert group. Biodiversity being an object of huge complexity even in the species-poor Baltic Sea was considered a challenging subject. The group based its work on the reports of the MSFD GES Task Groups 1, 2, 4 and 6 (Cochrane et al. 2010, Olenin et al. 2010, Rogers et al. 2010, Rice et al. 2010), the HELCOM common principles of core indicators (see Section 2.3) and the EC decision document (Anon. 2010). They approached the selection of indicators from three aspects: functional groups and predominant habitats, including key species; impacts of anthropogenic pressures on the functional groups and predominant habitats; and the availability of monitoring The functional groups, predominant habitats and key species The functional groups and predominant habitats were first based on the proposals present in the report of the EU MSFD GES Task Group 1 (Cochrane 39

43 et al. 2010) and then adapted to Baltic conditions by the biodiversity group (Tables 5.4 and 5.5). These functional groups and predominant habitats should form the basis of the monitoring and assessment of the status of biodiversity as they are intended to cover the range of biodiversity in the marine regions of the EU member states. The aim is that there should be indicators that can be used to assess the status of each functional group and predominant habitat, and should adequately reflect the relevant GES criteria and the pressures to which they are subject. However, with the limited time of the project, it has not been possible to fully define the range of indicators needed. Nevertheless, in a few cases, single indicators can be applied to several functional groups or habitat types. According to the Commission Decision (Anon. 2010), individual species of fish, mammals and birds are to be assessed at the species or population level, while other biodiversity components should be assessed at the community level in association with their habitat. The latter category includes fish (when strongly associated with seabed habitats), phytoplankton, zooplankton, angiosperms, macroalgae and the invertebrate benthic fauna (cf. MSFD, Table 1 Annex III). The functional groups of fish, mammals and birds can be assessed by using the community criterion (i.e. considering species composition and relative abundance issues within the functional group). The predominant habitats should first be divided into seabed and water column habitats. For the seabed habitats, the TG 1 report (Cochrane et al. 2010) proposes to use coarsely-defined habitat classes which are correlated to the high-level habitat classes of the European EUNIS classification scheme. In the Baltic Sea, the current EUNIS classification is considered unsuitable for MSFD purposes. However, the EUSeaMap project, in collaboration with biotope experts of the Project for Completing the HELCOM Red List of Species and Habitats/Biotopes, has developed a proposal for a Baltic Sea EUNIS classification. The coarse habitat classes from this proposal, which are proposed as the predominant habitat types for MSFD purposes, are shown in Table 5.5 and have been used in the CORESET project. This does not exclude the possibility to further specify more detailed habitat types. The directive has the provision to also assess and report on special habitats such as those on the HELCOM Red List. The pelagic (water column) habitats are simply divided into coastal and offshore waters, using the 1 nautical mile delineation of the WFD to separate the two water types. This simple division is crude and thus a further classification for the Baltic Sea water column should be considered. One possibility is to divide the pelagic realm into photic and non-photic zones or a distinction between above and below the halocline. A further defini- 40

44 tion of pelagic habitats has not been completed within the project. In addition to the identification of functional groups and predominant habitats, Baltic key species were identified. This was seen as significant for two reasons: to select appropriate indicator species for the functional groups and to identify indicator species for Descriptor 4 (Food webs), which particularly calls for such species. The preparation of such a list is also an explicit demand of the GES criteria document (Anon. 2010) which states for Descriptor 1: For each region, subregion or subdivision, taking into account the different species and communities contained in the indicative list in Table 1 of Annex III to Directive 2008/56/EC, it is necessary to draw up a set of relevant species and functional groups. The list of key species, identified in the project, is presented in Table 5.6. The criteria used to assemble the list were: Species and/or groups important to the Baltic Sea ecosystem structure and function in terms of biomass, abundance, productivity, or functional role with emphasis on species/groups with important functional roles. Thus, it is not intended to be a full list of Baltic Sea species but should consider only the most important species/ groups that adhere to these criteria. The list is sorted according to suitable groups as outlined in Descriptor 4, indicator (Anon and Table 3.4). The list is a living document subject to further development. The expert group, however, is aware that at present the list does not properly cover key species in the Kattegat. The GES criteria document also requires that lists of species and functional groups specified in existing community legislation, such as the Birds and Habitats Directive, as well as other listed species should be prepared. Here, the CORESET project refers to the existing HELCOM red list of threatened and/or declining species and biotopes/ habitats in the Baltic Sea area (HELCOM 2007 b); the HELCOM red list of threatened and declining species of lampreys and fishes of the Baltic Sea (HELCOM 2007 c); and the HELCOM red list of marine and coastal biotopes and biotopes complexes of the Baltic Sea, Belt Sea and Kattegat (HELCOM 1998). An update of the red lists of species and biotopes is expected to be finalised in the HELCOM REDLIST project by In the CORESET project, core indicator work focused on key elements of the ecosystem - no indicator was developed for threatened or rare species or biotopes. However, some indicators may be applied to these species and habitats in order to assess their status. Table 5.4. The functional groups in the Baltic Sea which were used as basis for indicator selection. Species groups Functional groups Birds Mammals Fish Coastal pelagic fish feeder Offshore pelagic fish feeder Subtidal offshore benthic feeder Subtidal coastal benthic feeder Subtidal coastal herbivorous feeder Intertidal benthic feeding birds Coastal top predators Toothed whales Seals Pelagic fish Demersal fish Elasmobranchs Coastal fish Anadromous/catadromous fish Table 5.5. Predominant habitats of the Baltic Sea. Habitats are based on a preliminary EUNIS classification developed within the EUSeaMap project in collaboration with biotope experts of the Project for Completing the HELCOM Red List of Species and Habitats/Biotopes. The classification of pelagic habitats was based on Cochrane et al. (2010) and modified for the Baltic Sea environment. Habitat groups Final predominant habitats Seabed habitats Baltic hydrolittoral rock and other hard substrata Baltic hydrolittoral sediment a Baltic infralittoral rock and other hard substrata Baltic infralittoral sediment a Baltic circalittoral rock and other hard substrata Baltic circalittoral sediment Baltic deep sea rock and other hard substrata Baltic deep sea sediment a Pelagic Estuarine water (water column) habitats Coastal water Offshore water 5 Ice-associated marine habitats a) The soft sediment can be further divided into sands and muds, for example. 5 In the TG1 report, the off-the-coast pelagic habitats were defi ned as Shelf water and further as Oceanic water. A class of Low salinity water for the Baltic Sea was also proposed but the meaning of this term is unclear. 41

45 Table 5.6. Key species and functional groups in the Baltic Sea based on criteria specified in Section The content of the list is sorted according to the suitable groups as outlined in Descriptor 4, indicator (Anon. 2010). D criteria: TOP PREDATORS Sub-group: Piscivorous fish Taxon Functional group in the pressure matrix Comment Link to GES criteria (2010/477/EU) Cod, Turbot Marine demersal TAC regulated fisheries , 3.1.1, 3.2.1, 4.1, 4.2.1, Perch, Pike, Pikeperch Coastal demersal Salmon, Sea trout Anadromous TAC regulated fisheries, , 4.2.1, Listed in HD Sub-group: Mammals Harbour porpoise Toothed whales Listed in HD, subject , 4.1.1, of by-catch Grey seal, Ringed seal, Harbour seal Seals Listed in HD, subject , 4.1.1, of by-catch Sub-group: Fish feeding birds Great black-backed gull, Herring gull, Lesserblack-backed gull, Common gull Inshore surface feeder/ scavengers Black-headed gull, Common tern, Arctic tern Inshore surface feeder Terns listed in Annex I, BD Black-throated diver (winter), Red-throated diver (winter), Great crested grebe, Goosander, Razorbill, Common guillemot, Slavonian Grebe (winter) Black guillemot, Cormorant, Great crested Grebe (winter) Offshore pelagic feeder Divers listed in Annex I, BD , , , Inshore pelagic feeder , White-tailed eagle Coastal fish feeder Listed in Annex I, BD , 4.1.1, Table 5.6 continues... D criteria: GROUPS/SPECIES THAT ARE TIGHTLY LINKED TO SPECIFIC GROUPS/SPECIES AT ANOTHER TROPHIC LEVEL Sub-group: Young fish age groups consuming zooplankton Taxon Functional group or habitat in the Comments Link to GES criteria (2010/477/EU) pressure matrix Perch, Pikeperch Coastal demersal , 1.5, 1.6, Cyprinids Coastal benthopelagic , Cod Marine pelagic TAC regulated fisheries , 1.5, 3.1.1, 3.2.1, 4.1, 4.2.1, Flounder Marine demersal TAC regulated fisheries , 4.2.1, Herring, Sprat Marine pelagic TAC regulated fisheries , 4.2.1, 4.3.1, 3.1.1, 3.2.1, 4.1 Sub-group: Adult fish consuming zooplankton Herring, Sprat Marine pelagic TAC regulated fisheries , 3.1.1, 3.2.1, 4.1, 4.2.1, 4.3.1, Sticklebacks Marine pelagic and 1.1, 1.2, 1.3, 1.7 coastal demersal Sub-group: Benthic feeders Cyprinids Coastal benthopelagic , Herring Velvet scoter, Common scoter, Long-tailed duck, Eider, Tufted duck, Greater scaup Marine and coastal benthopelagic , 3.1.1, 3.2.1, 4.1, 4.2.1, Subtidal benthic feeder 1.1, 1.2, 1.3, 4.3.1

46 Sub-group: Prey of benthic feeding fish and birds (soft bottom) Macoma balthica, Monoporeia affinis, Scoloplos armiger, Mytilus spp., Mya arenalis, Hydrobia spp., Cerastoderma spp. Bylgides sarsi Circalittoral sediments and sediments below halocline Sediments below halocline , , Bathyporeia pilosa Infralittoral sand , Table 5.6 continues... D criteria: HABITAT DEFINING GROUPS Taxon Predominat habitat type in the pressure matrix Sub-group: Benthic primary producers Seaweeds Infralittoral rock and other hard substrates Comments e.g. Fucus, Furcellaria, Laminaria Link to GES criteria (2010/477/EU) , Eelgrass, Stoneworts, Pondweed Infralittoral sediments e.g. Zostera, , Potamogeton Sub-group: Filters feeders Blue mussel Infralittoral and circalittoral rock and sand also Biogenic reefs , Table 5.6 continues... D criteria: GROUPS WITH FAST TURNOVER TIMES Taxon Functional group in pressure matrix Sub-group: Carnivorous plankton Selected Cladocerans, Adult Cyclopoida, Zooplankton Jellyfish > 2mm Comments e.g. Cercopagis pengoi, Leptodora kindtii and Bythotrephes longimanus Sub-group: Herbivorous plankton Selected Cladocerans, Calanoida, Rotifers Zooplankton e.g. Bosminidae, Daphniidae, Podonidae Sub-group: Bacterivorous plankton Appendicularia, Rotifers, Juvenile copepods, Small ctenophores Zooplankton e.g. all stages of Mertensia ovum, cydippid stage of Mnemiopsis leidyi Link to GES criteria (2010/477/EU) 1.6.1, 1.6.2, , 1.6.2, , 1.6.2, Sub-group: Pelagic primary producers Cyanobacteria, (nitrogen fixing), Diatoms, Phytoplankton 1.6.1, 1.6.2, Dinoflagellates Flagellates Phytoplankton 1.6.1, 1.6.2, Cyanobacteria, potent. toxic Phytoplankton e.g. Nodularia spumigena, Chrysochromulina polylepis, Prorocentrum minimum, Pseudochattonella farcimen, Karenia mikimotoi, Anabaena lemmermanni, Aphanizomenon flos-aque Sub-group: Bacterioplankton 1.6.1, 1.6.2, Whole community

47 Use of anthropogenic pressures in the selection of the indicators The second criterion for the process was to identify the anthropogenic pressures on the functional groups and predominant habitats. The linkage of a core indicator to a pressure(s) was considered essential, as a principal objective of the core indicators is to measure the effect of human pressures (or mitigation of them) on the ecosystem (see principles in Section 2.3). The use of the pressure-impact relationship to guide indicator selection draws on the proposals by the MSFD TG1 report (Cochrane et al. 2010); the ICES WGECO report (ICES 2010); and concepts laid down in the HELCOM HOLAS report (HELCOM 2010 a, c). The summary of the pressure-impact matrix is presented in Annex 1. The evaluation of impacts of pressures on Baltic Sea functional groups and predominant habitat types was carried out in the six working teams (see project structure in Section 5.1). A specific guiding document for the selection of indicators was produced, which took into account the MSFD GES criteria as well as the common principles of the HELCOM core indicators. Experts were given a list of anthropogenic pressures, sorted according to Annex III, Table 2, of the MSFD, and asked to score the impact of each pressure on each functional group or habitat by a three-level score - low, intermediate, high - and distinguish direct impacts from indirect ones. The pressures perceived as having the highest impacts were identified and the selection of indicator parameters guided by the results of the evaluation. It can be noted that although the expert evaluation of the severity of impacts varied somewhat considerably, when all expert judgements were compared it was still possible for the teams to identify a limited number of pressures as the most severe ones (see Chapter 6). The fish team, which is based on the existing HELCOM FISH PRO project, used a statistical approach to identify the predominant pressures (HELCOM 2012 b). By using a pressure-based approach, the indicators - while primarily describing the state of different ecosystem components - also indicate the impact of pressures on the ecosystem. With a clear link to pressure, they can thus also serve the purpose as indicators to follow up management actions to mitigate the impact of human pressures. With this in mind, the indicator selection focused on identifying indicators that respond to one or a limited number of pressures. However, considering the multiple pressures present in the Baltic Sea and their combined impacts, this ambition has not been possible to follow through for all indicators; as some proposed core indicators have multiple weak underlying pressures, the impacts of some pressures are not adequately measured by any one core indicator (see Chapter 6) The influence of monitoring data on indicator selection One prerequisite of the core indicators, according to the HELCOM common principles, is that they should be frequently monitored using harmonised methods. For this purpose, the project gathered information on existing monitoring in all Contracting Parties (Chapter 9). However, the existing HELCOM monitoring programmes, such as COMBINE, are mainly directed towards monitoring the effects of eutrophication and contaminants. Thus, there is no existing dedicated monitoring programme that widely addresses all components of or all pressures on biodiversity. The availability of the monitoring data was therefore not a ruling criterion in the development of the core indicators for biodiversity. Instead, the principle was interpreted to apply to the operational core indicators after the monitoring programmes had been revised according to the proposed core indicators. Hence, suggestions for the monitoring of the identified core indicators were given, where appropriate. Existing monitoring on certain variables was, however, used to guide the selection process. An example is the proposed indicators for coastal fish, where harmonised monitoring is currently conducted by Estonia, Finland, Latvia, Lithuania and Sweden while being conducted using other methods in the other CPs. The working teams were also given the liberty to develop indicators where there is currently a lack of monitoring if the proposed indicators are considered as central for assessing the state of the biodiversity in the Baltic Sea. The expert group was aware that HELCOM is starting to revise the joint monitoring programme and wanted to be proactive in this matter. The teams were, however, asked to be realistic in their work - if they proposed new monitoring they should also outline a proposal for the revision process.

48 5.3.4 Categorisation of the biodiversity indicators The process to develop core indicators generated an initial list of 45 candidates. The list was presented and discussed during the project s second workshop. At this stage, they were all labelled candidate indicators and thus the teams were encouraged to continue developing almost all of them. The third biodiversity workshop categorised the indicators into candidate and core indicators and also identified a number of supplementary indicators. The following criteria were used to categorise indicators as core indicators: the indicator should clearly represent a GES criterion and the HELCOM common principles for indicators (e.g. link to anthropogenic pressures); the indicator should be well-established or, if new, be tested and documented in a way that allows an external review of the proposal; include proposed GES boundary/boundaries; and monitoring should be in place or a proposal for future monitoring should be formulated. What remained as candidate indicators after this process were considered promising yet not possible to operationalise within the first phase of the CORESET project. It was anticipated, however, that some of the remaining candidate indicators would be reclassified during the second phase of the project and the development work will continue in HELCOM working groups and external projects until and beyond the finalisation of the present report. Indicators which clearly did not fit to the core indicator concept were categorised as supplementary indicators. These were not considered as core indicators but were seen as useful support material for them since they provide data on climatic and hydrographic changes, fluctuations of populations and changes in parameters which reflect human activities The process to develop GES boundaries The final step in the development work was to identify a boundary or range where each indicator is in GES. Different approaches to target setting were described in Chapter 4. Based on discussions and the conclusion in the project, the working teams were given freedom to choose the target setting approach which best suited the available data and type of indicator. As the target setting process varied among the core indicators, it was decided that each core indicator should be substantiated by a background document, including a description of how GES boundaries were established (see Part B of this report (HELCOM 2012a)). During the CORESET process of defining GES boundaries for core indicators, it was also decided to produce qualitative (i.e. narrative) GES boundaries for each core indicator. The benefit of the approach was twofold: 1) to explain the reasoning behind the numeric value to a non-expert; and 2) to facilitate the development of the numeric value. The qualitative GES descriptions are given in Annex Selection of core indicators for hazardous substances The selection process of the hazardous substances core indicators The hazardous substances expert group began its first workshop by agreeing on criteria for the selection of indicators. The group agreed that the selection criteria should be based on needs - at least during the first phase - and not be biased by data availability or solely by existing priority lists. It was also noted that the revision of the HELCOM monitoring programmes was at hand and the selection of core indicators can have a proactive effect on 45

49 that process. The group based its work on the principles of core indicators (see Section 2.3). The selection criteria for the hazardous substances core indicators were: an alarming /increasing levels of the substance in the Baltic; PBT properties (persistence, bioaccumulation, toxicity); management status (banned, regulated, not banned); policy relevance (existing priority lists); the availability of targets; and monitoring status. The expert group screened the list in all the three workshops and eliminated or added indicators as new information became available. In particular, the group discussed the policy relevance of the substances that have been suggested by the WFD WG E to be added to the revision list of the Priority Substances; to date, however, the final decision at the EU level on their inclusion has not been yet made. Nevertheless, the expert group decided that there is no reason not to include them in the core set provided other selection criteria are fulfilled. Except for the two pharmaceutical substances, all the other substances are included in other priority lists as well as the list of EU Priority Substances. Commonly known hazardous substances often consist of several congeners (e.g. PCBs, or PBDEs) or separate substances (e.g. PAHs). As a laboratory s chemical analysis package frequently contains parallel analyses of several congeners or substances at no extra cost, the expert group considered it expedient to include several parameters (i.e. congeners or substances) for a single core indicator. Moreover, the congeners (or closelyrelated substances) often represent different pollution sources and, hence, provide important extra information to the indicator. Most of the individual substances of a group (e.g. PAH) should be assessed against substance-specific targets; however, there are some substance groups for which one target can be used collectively (e.g. dioxins and furans as well as PBDEs). For PCBs, it was agreed that as the congeners 118 and 153 represent the majority of the congeners, the core indicator will be primarily assessed by these two congeners (although concentrations of the ICES 7 congeners (CBs 28, 52, 101, 118, 138, 153, 180) will be shown). HELCOM JAB also tasked the group to include indicators of the effects of hazardous substances in its working programme. The group invited the BONUS+ project BEAST to contribute to the work, and welcomed their offer to choose up to four key indicators with targets and background material. All of the selected core indicators for biological effects had established methods recommended by ICES SGIMC 6 and ICES WGBEC 7. They are already included in other regional monitoring programmes such as OSPAR (on a voluntary basis) or MEDPOL, or used in the national monitoring programmes of 46 6 Study Group for Integrated Monitoring of Contaminants and Biological Effects 7 Working Group on Biological Effects of Contaminants

50 Denmark, Germany and/or Sweden. The following information applies to all listed indicators: sufficient research or monitoring data was available, covering different Baltic Sea sub-regions; Baltic Sea specific Background Assessment Criteria (BAC) have been established for a range of Baltic Sea indicator species (note that BACs for biological effects and for substance concentrations are based on different procedures); biological effects can be assessed against Environment Assessment Criteria (EAC) of response that are indicative of significant harm to the species under investigation (note that BACs for biological effects and for substance concentrations are based on different procedures); monitoring guidelines, including published Standard Operation Protocols (SOPs, e.g. in the ICES TIMES series), are available and widely applied; the costs of analyses are low and samples can be collected during the same sampling campaigns as for the contaminant analyses (mostly using the same target species, size classes, etc.). The impact relationships of organisms or species populations and contaminants are described separately in the core indicator documentation (see Part B of this report, HELCOM 2012 a). Generally, the expert group aimed to cover different contaminant groups by these core indicators; different response levels in organisms; and most mature indicators scientifically. The choice to include the biological effects indicators as core indicators under the hazardous substances group originated from the MSFD and BSAP terminology, although they are very close to the biodiversity indicators in many cases, thereby creating synergies between these two groups of indicators. The expert group also discussed the effects of hazardous substances on top predators (marine mammals and white-tailed eagle) and considered a specific core indicator for these. Although there is extensive material available on this subject, the group decided not to create specific core indicators for top predators since the same substances were already covered by separate indicators in fish, mussels, sediment and water, as it would be difficult to choose which substances should be measured in top predators. It was decided, therefore, that the concentrations of selected substances in top predators will, if available, be shown as supplementary information in the core indicator reports. Moreover, the biodiversity group included the general health indicator of marine mammals in their working programme Decisions on sampling and data conversions for hazardous substances core indicators Monitoring programmes include measurements of hazardous substances from water, sediment, mussels, fish, bird eggs and marine mammals. The multiplity of the sample matrices creates a challenge of compatibility among the data sets and coherence of an indicator. There are probably several reasons for this current situation including chemical properties, historical institutional practices and work sharing, the continuation of long-term data series, preferences of individual scientists and legal obligations. In general, the group was of the opinion that water is unsuitable as a sampling matrix for most of the selected indicator substances. The group also concluded that sediment sampling gives a different message than measurements in biota - the former assesses the state of benthic environment (and hence only a risk for organisms) while the latter assesses the actual concentrations in living organisms. However, since the relevance of the sampling matrix depends on the chemical properties of a compound, sediment sampling can be appropriate for some substances. In order to aim at maximal coherence among countries, marine areas and data sets, the group decided to give priority matrices for the selected substances (Table 5.7). Other matrices can be sampled if no other data is available. The group also wanted to give a message for sampling coherence to the forthcoming revision of the HELCOM monitoring programmes. According to Table 5.7, most substances are to be primarily monitored from biota (or sediment); however, the primary matrix of the pharmaceutical compound EE2 was judged to be water and for the alkylphenols water or sediment. Polyaromatic hydrocarbons cannot be measured from vertebrates (like fish) as they are efficiently degraded; instead, the PAH-metabolite indicator can be used for those compounds in vertebrates. The monitoring of very persistent substances in sediments, in addition to biota, gives additional information to the assessments of hazardous sub- 47

51 48 stances and their effects since sediments, which are generally sinks for many persistent substances, may also act as internal sources to the ecosystem long after the external inputs have ceased. Another discussion point during the process was the sample tissue (in fish samples) and its suitability for assessments against targets. The group acknowledged that as the targets were environmental targets being calculated to prevent the poisoning of higher trophic levels, the targets applied to whole fish. The samples, however, were not taken from homogenised whole fish but from muscle, liver and sometimes bile. The group decided that a pilot study, including a literature review and laboratory experiments, needs to be conducted and the results evaluated in a workshop in The group will produce conversion factors for the data in order to enable coherent assessments with the core indicators. Target setting should be reviewed in light of the workshop results, progress in the EU on developing EQS for biota and sediments and experience gained in the application of those targets in the marine environment. Table 5.7. Sampling matrices to be preferred for core indicator substances. Sampling matrix Substance Water 17-alpha-ethinylestradiol Sediment PAHs, (PBDE, HBCDD, PFOS, PCB, Dioxins) Fish PBDE, HBCDD, PFOS, PCB, Dioxins, PAH meta bolites, metals, cesium- 137, diclofenac Mussel/bivalve PBDE, HBCDD, PFOS, PCB, Dioxins, PAHs, metals, cesium Core indicators for seafood safety As the CORESET expert group had only limited expertise on seafood safety, the development of core indicators for the BSAP ecological objective of safe seafood and the MSFD GES Descriptor 9 was considered incomplete. It was decided that this report will present safety limits from the EU legislation (Anon. 2006) for the selected chemicals as core indicators. The group discussed that it would be cost-efficient to aim at shared monitoring programmes for both indicators of Descriptors 8 and 9. Currently, monitoring is often carried out by different institutes separately. Depending on countries, alignment of the two monitoring approaches may, however, be difficult or not possible due to different requirements under food legislation (sampling of market fish), environmental monitoring (fish from identified sampling/catch location) and different sampling matrices (whole fish, muscle or liver). In such cases, chemical analyses for environment monitoring could be expanded to assess environmental concentrations against food standards. 5.5 Geographical scales of the core indicators Early in the process during the development of core indicators, both expert groups considered geographical scales of the assessment units for the indicators, GES boundaries and integrated assessments. It was apparent that both the size of the assessment units and the scale for which GES boundaries should apply are parameter dependent. For example, highly mobile species (e.g. seals) have a similar GES boundary over the entire sea area for a given parameter; the GES of benthic invertebrate communities, on the other hand, vary along several environmental gradients. It was also agreed that the assessment units for integrated assessments need to be considered already at this stage of the project, even though the assessment methodologies are still not developed. The biodiversity expert group decided that each team should agree on the geographical variability of GES for each core indicator and suggested a relevant size of assessment units for them. The following aspects were to be considered when defining the assessment units for the indicators: a suitable assessment unit for an indicator, based on ecological relevance, i.e. scales of variability in ecosystem components; suitable geographical boundaries within which GES applies to an indicator; and an assessment unit for an integrated assessment. The expert groups noted that the same GES boundary may apply across multiple assessment units. While an indicator can have the same GES boundary for a large area (e.g. a sub-basin), it may, depending on area specific exposures to pressures for instance, be relevant to assess the status of the indicator in smaller areas (e.g. a water type).

52 In order to avoid boundary conflicts among the indicators in the integration phase when producing the assessments, it was decided that the assessment units need to be nested. In order of hierarchy, the highest level (i.e. the largest scale) is the entire Baltic Sea, followed by the sub-basin level and then the levels for offshore and coastal waters of the sub-basins, WFD coastal water types and WFD coastal water bodies. In offshore waters, there is no proposal to divide the basins into smaller units (except for national borders, which should be visible on the assessment maps). This nested boundary setting includes a few hierarchical levels and facilitates the integration of the indicators. The appropriate level of integration would preferably be the smallest scale. Figure 5.1 shows the four levels of the geographical scales nested within each other: the entire Baltic Sea (panel A), the sub-basin level division (panel B) and the division to offshore sea areas and coastal waters (panel C) and the WFD water types inside the 1 nm coastal water boundary (panel C). A The hazardous substances expert group has not yet made any decision on the size of the assessment units; however, they noticed that there are strong gradients from pollution sources and nearby sediment accumulation areas, which supports the differentiation of coastal and offshore waters as assessment units. It was clear, however, that in the integration phase of the hazardous substances core indicators, a decision of the assessment units should be made, otherwise there would be no objective rule of how to combine measurements from point-based sampling sites to an integrated assessment. One option would be to follow the example from the eutrophication core indicators, which are assessed in the coastal waters in the WFD water types (or even water bodies) and in the offshore areas in the offshore sub-basins. B Figure 5.1. Assessment units for the whole Baltic Sea (A); 19 sub-basins (B); and water types of the WFD in coastal waters and 19 sub-basins in offshore waters (C). In panel C, the brown lines represent national borders of Exclusive Economic Zone (EEZ). Key: BBa=Bothnian Bay; Q=Quarck; BS=Bothnian Sea; ÅS=Åland Sea; AS=Archipelago Sea; NBP=Northern Baltic Proper; GF=Gulf of Finland; GR=Gulf of Riga; EBP=Eastern Baltic Proper; WGB=Western Gotland Basin; GG=Gulf of Gdansk; BBs=Bornholm Basin; AB=Arkona Basin; MB=Mecklenburg Bight; KB=Kiel Bight; S=Sound; GB=Great Belt; LB=Little Belt and K=Kattegat. C 49

53 6 Biodiversity core indicators and targets 50 How can a limited set of indicators to assess marine biodiversity be developed one that covers organisms from bacteria to seals, food web interactions on five levels, habitats from the shore to the deepest trenches and all impacted by an array of human activities? The primary limiting factor in such assessments is the available resources for monitoring activities, but also the scientific understanding of interspecific relationships and pressureimpact causalities complicate the development of many potential indicators. The richness of species in the Baltic Sea is relatively low due to its brackish water environment, the young age of the sea basin and the food webs which are characterised by interactions of only a

54 few predominant key species. Because the regional scientific collegium has cooperated for decades to characterise the Baltic biodiversity and human impact on it, the assessment work in the Baltic Sea can be perceived to be somewhat easier than in oceanic environments but it is still a major challenge. The previous chapters of this report described the process of identifying the core indicators for the Baltic Sea. Chapter 2 presented the premises for the HELCOM core indicators while Chapter 3 discussed their objectives - what they should measure. Potential approaches for the quantitative characterisation of good environmental status (GES) for each indicator were given in Chapter 4 and the CORESET process of selecting and developing the core indicators was explained in Chapter 5. This chapter presents the outcome of the HELCOM CORESET indicator development work with specific emphasis on those indicators that were identified as core indicators, i.e. indicators considered as reasonably validated and fully or nearly operational. The chapter also presents examples of numeric targets - the GES boundaries - for the core indicators. At this stage of the project, several of the identified indicators were still considered as candidates because their relation to underlying pressures was still unclear, their applicability to measurement of GES was not proven, or for other reasons. For this reason, the classification of the core and candidate indicators should not be emphasised too much at this stage of the CORESET project. 6.1 Proposed core indicators for biodiversity This section presents the biodiversity related core indicators developed in the HELCOM CORESET project. The proposed indicators are interim expert products that require further development; for example, methodological details and their adjustment to sub-regional conditions. The proposed GES boundaries should be seen as examples provided by the current scientific understanding. The biodiversity core indicators assess the HELCOM BSAP policy goal Favourable conservation status of Baltic Sea biodiversity and the MSFD GES Table 6.1. The proposed core indicators and their potential use as indicators for Descriptors 1, 2, 4 and 6 of the MSFD. The table also presents the primary pressure(s) for these state indicators. Proposed core indicator D1 D2 D4 D6 Primary pressure/driver(s) 1 Blubber thickness of marine mammals X Hazardous substances, disease, removal of prey 2 Pregnancy rates of marine mammals X Hazardous substances 3 Population growth rates of the populations X X Hazardous substances, hunting, disease of marine mammals 4 White-tailed eagle productivity X X Hazardous substances, persecution 5 Abundance of wintering populations of seabirds 6 Distribution of wintering populations of seabirds 7 Fish population abundance X X Species dependent, mainly linked to eutrophication, habitat and prey loss, oil contamination and by-catch X Species dependent, mainly linked to eutrophication, habitat and prey loss, oil contamination and by-catch X X A Functional group dependent, mainly linked to eutrophication or fishing 8 Proportion of large fish in the community X X Fishing 9 Mean metric length of key fish species X Species dependent, mainly linked to fishing 10 Fish community diversity X Eutrophication, fishing, habitat loss 11 Fish community trophic index X X Fishing, eutrophication 12 Abundance of fish key trophic groups X X A Functional group dependent, mainly linked to eutrophication or fishing 13 Multimetric macrozoobenthic indices X X Physical disturbance, hypoxia, eutrophication 14 Lower depth distribution limit of macrophyte species X X Eutrophication 15 Trends in arrival of new non-indigenous species X Reflects the efficiency of management actions to reduce new introductions A The proportion of piscivorous, non-piscivorous fi sh and cyprinids that can be derived from the core indicator. 51

55 Table 6.2. Summary of the anthropogenic pressures with the highest impact on the Baltic Sea biodiversity according to evaluations by the CORESET biodiversity working teams. The success of the HELCOM CORESET project in covering functional groups and main anthropogenic pressures by core indicators is shown by the colouring: green = core indicator(s); orange = candidate indicator(s); red = no indicator. Key: I = State indicator responding to a pressure and displaying its impact; P = Pressure indicator Major functional groups Predominant pressures and habitat types Input of nutrients Input of synthetic and non-synthetic substances Fishing targeted catches Fishing by-catch Hunting Noise Oils spills Introduction of non-indigenous species Mammals (I) (I) (I) (I) Birds (I) (P) (I) (I) Offshore fish (I) Coastal fish (I) (I) (I) Seabed and communities (I) (I/P) (I) Pelagial and communities (I) * * (I/P) Physical disturbance of the seabed * Impacts are indirect and diffi cult to assess through indicators. 52 descriptors for biodiversity, non-indigenous species, food webs and sea-floor integrity. The descriptions and background documentation of all the core indicators are given in Part B of this report (HELCOM 2012 a). Table 6.1 provides a simple overview of the proposed core indicators and how they can be used to assess the different descriptors covered in the project. Even if the redundancy of core indicators between Descriptors 1 and 4, in particular, must be omitted, there are a sufficient number of core indicators to cover most of the GES criteria for both descriptors. The proposed core indicators do not cover the responses of all functional groups or predominant habitats (including associated communities) to the main anthropogenic pressures. Table 6.2 summarises how the indicators, representing different functional groups, are linked to the main pressures identified in the project. In many cases, the indicator development was not finalised as seen by the number of candidate indicators (orange). The table also shows which pressures in the selection process were identified as causing significant impacts but which still lack an indicator at this stage of the project (red) Core indicators for Descriptor 1 (biodiversity) The core indicators for Descriptor 1, which describes the biological diversity of the marine ecosystem at the species, habitat and ecosystem levels, are presented in Tables 6.3 and 6.4. Of the 14 core indicators, eight are related to the species level; five to the habitat level (incl. communities); and one to the ecosystem structure. Despite the relatively high number of indicators, the habitat distribution criterion (1.4) lacks a core indicator (Tables 6.3 and 6.4). This gap will be revisited during the second phase of the project in Further, the genetic structure of populations and habitat distribution patterns are not covered by the set of core indicators mainly due to a lack of information and monitoring. The species distributions are assessed by only one seabird indicator, even though distributional ranges and patterns of several other species should be available. Moreover, the ecosystem structure is only addressed by the trophic index of the coastal fish community - other indicators measuring the ecosystem structure would thus be desirable. From the perspective of major organism groups, mammals, birds and fish are relatively well represented in the set of core indicators (compare to

56 Table 6.3. Proposed core indicators for Descriptor 1 at the species level. The core indicators are shown in their relation to MSFD GES criteria and indicators (EC Decision 477/2010/EU). GES criteria GES indicator Proposed core indicators 1.1 Species distribution Distributional range Birds: Distribution of wintering seabird populations Distribution pattern within No indicator the latter Area covered by sessile/benthic No indicator species 1.2 Population size Abundance and/or biomass Mammals: Population growth rate of marine mammals Fish: Fish population abundance Birds: Abundance of wintering populations of seabirds 1.3 Population condition Population demographic characteristics: (body size or age class structure, sex ratio, fecundity rates, survival/ mortality rates) Population genetic structure No indicator Mammals: Blubber thickness of marine mammals Pregnancy rate of marine mammals Birds: White-tailed eagle productivity Fish: Mean metric length of key fish species Table 6.4. Proposed core indicators for the Descriptor 1, habitat level (including associated communities) and ecosystem level. The core indicators are shown in their relation to MSFD GES criteria and indicators (EC Decision 477/2010/EU). GES criteria GES indicator Proposed core indicators 1.4 Habitat distribution Distributional range No indicator Distributional pattern No indicator 1.5 Habitat extent Habitat area Habitat volume 1.6 Habitat condition Condition of the typical species and communities Relative abundance and/or biomass Physical, hydrological and chemical conditions Seabed communities: Lower depth distribution limit of macrophyte species Seabed communities: Multimetric macrozoobenthic indices (e.g. BQI, MarBIT, DKI, BBI) Fish: Proportion of large fish in the community Fish community diversity Fish: Abundance of fish key trophic groups Water transparency Inorganic N Inorganic P Chl a 1.7 Ecosystem structure Composition and relative proportions of ecosystem components Fish community trophic index Table 5.4). Although the offshore fish populations were not yet adequately covered by this project, they are currently being developed in the project and ICES workshops, for example, and will be the focus (fish indicators) during the second phase of HELCOM CORESET. However, the set still lacks core indicators for breeding seabirds and zooplankton even though they are identified as well-developed candidate indicators (see Section 6.2). Although the core indicators for seabed habitats adequately cover the sediment bottoms at all depth categories, the rocky and hard substrata bottoms (Table 5.5) are only covered in the infralittoral zone with the macrophyte indicator (Table 6.4). The offshore and coastal pelagic habitats currently lack a core indicator. Despite the adequate coverage of MSFD GES criteria, Table 6.2 shows that candidate indicators would fill significant gaps with regard to organism groups and the major pressures that impact them. 53

57 Blubber thickness of marine mammals The blubber thickness of marine mammals indicates the nutritional status and reflects the health condition of the animals. The specific pressures behind the decreased blubber thickness have not been resolved and may involve the synergistic effects of hazardous substances, disease as well as the quality and quantity of available food (fish stocks). Currently, only the blubber thickness of the grey seal has been included as an indicator. Measured in millimetres, the parameter is regularly monitored in Sweden, Finland, Germany and, to some extent, in Poland. The proposed quantitative boundaries for GES have been based on data available at the Swedish Museum of Natural History; the Institute of Marine Research (Norway); the Institute of Zoology, the Zoological Society of London (United Kingdom); and on information gathered through literature reviews. GES is proposed to be the lower 95% CI of the geometric mean of values in the reference period , i.e. GES is based on what is expected to represent healthy populations while taking natural variation into account. Different GES boundaries are proposed for female, male and immature seals. The status assessments should only be based on the data collected during the reproductive season, with hunted or by-caught animals being included but treated separately in the analysis. The geographic scales of assessments should adhere to the management unit for seals as agreed in HELCOM recommendation 27-28/2. The proposed quantitative boundaries are based on a time-series analysis of the pregnancy rates of grey seals in the Baltic Sea area. After a severe decrease in the pregnancy rates during the 1970s-1990s, the grey seal population currently shows no uterine obstructions with pregnancy rates reaching 88% in 4-20 year-old females in The GES boundary is proposed to be set at the lower 95% CI of the period. GES is thus based on the status of what is expected to represent healthy populations as regards pregnancy rates. Only hunted or by-caught animals should be included in the analysis for the status assessments and the geographic scales should adhere to the management unit for seals as agreed in the HELCOM recommendation 27-28/2. Population growth rate of marine mammals The growth rate of the population describes the status of the population s condition. In the case of the Baltic seals and harbour porpoises, a growth rate lower than the intrinsic rate of increase 8 is indicative of the impacts of hazardous substances, hunting, excessive by-catch or disease when the population is far from the carrying capacity. Populations near the carrying capacity will show decreased growth rates due to density dependence in the populations and are then estimated by other means (see below). The indicator is expressed as a % increase of the population per year. The abundance of all seal species is monitored annually in the entire Baltic while data is currently inadequate for harbour porpoises. 54 Pregnancy rates of marine mammals The pregnancy rate describes the reproductive capacity and reflects the health condition of the animals. The decrease in pregnancy rate is mainly linked to the impacts of hazardous substances but could also be linked to infectious agents or starvation. The presence/absence of a foetus or embryo is noted during the pregnancy period of mature females and expressed as a percentage. Currently, only the pregnancy rate of the grey seal has been included. The parameter is regularly monitored in Sweden, Finland, Germany and, to some extent, in Poland. The proposed quantitative boundaries are based on a theoretical analysis of biological constraints and empirical analyses of the growth rates of seals and harbour porpoise populations that have been depleted by hunting. GES boundaries are proposed to be based on two different conditions: 1) When a population is far from the carrying capacity, i.e. the maximum population size of the species that the environment can sustain indefinitely with the available resources, the status should not deviate significantly from its intrinsic rate of increase: the GES boundary is proposed to be set at 4% for harbour porpoises; 10% for grey and ringed seals; 8 he rate at which a population increases in size if there are no densitydependent forces regulating the population is known as the intrinsic rate of increase. (Wikipedia)

58 and 12% for harbour seals. 2) When a population is close to its carrying capacity, GES is proposed to be considered as being met if the decrease of the population is less than 10% over a period of 10 years (similarly to the OSPAR convention EcoQO for seals). The geographic scales of assessments should adhere to the management units for seals as agreed in HELCOM recommendation 27-28/2. The geographic scale for harbour porpoise is the distribution range of each of the separate populations. White-tailed eagle productivity The proposed indicator of the white-tailed eagle population reflects the health status of the population and is based on the brood size (number of eggs per breeding pair) and the breeding success (% successful reproduction of all pairs). Productivity mainly decreases as a response to hazardous substances (for both brood size and breeding success) and persecution and other disturbances (for the breeding success). Productivity is measured as the mean number of nestlings out of all occupied nests. The proposed GES boundary is based on pre-1950s data from Sweden, i.e. based on a time period when the impacts of hazardous substances on the population are perceived as being low. The GES boundary is set at the lower 95% confidence level of the pre-1950s data. The proposed GES boundary for breeding success is 60%, for brood size 1.64 nestlings, and for productivity >1.0 nestlings; the parameters are monitored in all the Baltic Sea countries. The assessment units of the core indicator are the coastal strips (15 km inland) of the Baltic Sea s sub-basins. The proposed GES is tentatively defined as a percent deviation from the mean of the reference period. The current proposal is to use the reference period , which corresponds to the time period of the last coordinated survey and a deviation of 50%. This approach, however, needs to be revisited during the second phase of the CORESER project. Ultimately, GES should be set by modelling the population size based on the GES for eutrophication-related core indicators and empirical data on breeding success and survival rates of the species concerned. The assessment units are the sub-basins of the Baltic Sea. Distribution of wintering populations of seabirds The indicator follows changes in the main distribution area of selected bird species of high numerical and environmental importance, for which sufficient coverage by line transect data is available, such as the Common Eider, Velvet Scoter, Common Scoter and Long-tailed Duck. The distribution is determined from density surface models such as GAMs or GLMs, where the 75th percentile of all the sampled densities during the reference situation is used as the limit for distribution. Time series data can provide information on changes over time and reveal reoccurring spatiotemporal patterns. Combined with data on anthropogenic pressures, naturally driven patterns can be distinguished from pressure-based changes. Pressure-based changes in distribution may occur due to changes in resource quality and availability, habitat loss and disturbances or barriers. The Abundance of wintering populations of seabirds The core indicator for wintering seabird populations measures the abundance of selected species, which have been categorised into functional groups. The indicator can be used either for single species or as an integrated indicator for functional groups or all species. The impacts of pressures on the abundance are species specific; however, the main pressures are the oiling of birds; visual disturbances; altered food availability (i.e. deteriorated habitat conditions); loss of habitat; and by-catch in fisheries. 55

59 distribution is assessed on the scale of the entire Baltic Sea. GES is proposed to be compared to the situation in ; significant negative deviation from this distribution is proposed to reflect a sub-ges condition. Fish population abundance Under this core indicator, several fish stocks in the coastal and offshore waters can be assessed. The offshore stocks are proposed to be assessed by using the MSY B trigger values as GES boundaries; for coastal stocks, however, other GES boundaries need to be used. Currently, ICES has developed MSY B triggers in the Baltic Sea for the western cod stock and three herring stocks. New triggers are also being developed to facilitate the implementation of the EU MSFD. The HELCOM FISH-PRO project has developed the Coastal fish - Species Abundance Index as a core indicator for population assessments. The index estimates the abundance of key fish species in Baltic Sea coastal areas, such as perch (Perca fluviatilis) - a freshwater species that commonly dominates (in terms of numbers) coastal fish communities. As such, areas of good ecological status generally have high populations of perch. The index reflects the integrated effects of recruitment and mortality. Recruitment success is expected to be mainly influenced by climate and the quality of recruitment habitats; mortality, on the other hand, is influenced by anthropogenic pressures, mainly fishing, but also by natural predation by apex predators such as seals, seabirds and fish. The index is currently based on data collected from fishery-independent sampling of coastal fish using passive gears and expressed as relative abundance. Harmonised monitoring is currently conducted in Estonia, Finland, Lithuania, Latvia, and Sweden. Additional data sources, such as commercial catch statistics based on the EU-data collection system and coastal echo sounding, could complement the data if they prove to be of high enough quality to assess the biodiversity of coastal fish communities (for additional fish indicators see Part B of this report, HELCOM 2012 a). The proposed quantitative boundaries for the GES of coastal fish should be based on specific reference data from the sites and sampling methods. If reference data are missing, trends in available data and expert judgements are used to set the GES boundary. Since the temporal and spatial variation 56

60 of coastal fish communities in the Baltic Sea is substantial, the expected targets for GES are typically site specific, depending on the local properties of the ecosystem such as topography and geographical position. The geographic scales of assessment should therefore be within the region of the monitoring area. Proportion of large fish in the community This core indicator follows the community structure by computing the proportion of fish (biomass or individuals) that are large enough to contribute significantly to reproduction and predation. As fishing targets large individual fish, the size structure tends to be bias towards fewer large fish under a heavy fishing pressure. Although there is no established indicator for offshore communities to date, the development work is ongoing (see Section 6.2). For the coastal fish communities, the HELCOM FISH-PRO project has developed the Coastal fish Community Size Index indicator, which reflects the general size structure at the community level and is based on estimates of the abundance of large fish (measured as catch per unit effort). Generally, large piscivorous fish are abundant in coastal communities indicative of good ecological status in the Baltic Sea. The index is expected to mainly reflect changes in fishing mortality at the community level, where low values reflect increased fishing mortality. However, the value of the index may to some extent also be influenced by environmental conditions such as temperature and nutrient status. For monitoring, GES principles and geographical scale, see Coastal Fish - Species Abundance Index. Metric mean length of key fish species The core indicator mean length of the key species is expected to reflect changes in recruitment success as well as in mortality. Low levels may signal the appearance of a strong year class of recruits, decreased top down control in the ecosystem, or high fishing mortality but potentially also density-dependent growth. High levels in the index may signal a high trophic state, but potentially also decreased recruitment success. Because of this, the indicator should be interpreted together with the Fish population abundance. In the coastal community, Coastal fish Species Demographic Index reflects the size structure of key fish species in Baltic Sea coastal areas, such as perch (Perca fluviatilis). The index is based on the metric mean length of the key species, but the metric abundance of large key species could be used as additional information or complement. For monitoring, GES principles and geographical scale, see Coastal Fish - Species Abundance Index. There are no parameters currently developed for offshore fish species. Fish community diversity The indicator reflects biological diversity of fish at the community level and can be based on the Shannon Index. High values reflect high species richness and low dominance of single species, whereas low values reflect the opposite. The index has both an upper and a lower boundary since very high levels of the index potentially also may reflect a decrease in the abundance of a naturally dominating species. In the coastal waters, Coastal Fish Community Diversity Index is based on the Shannon index and has been tested by the HELCOM FISH-PRO project. For monitoring, GES principles and geographical scale, see Coastal Fish - Species Abundance Index. Abundance of fish key trophic groups The indicator measures abundances of trophic groups, being hence a wider estimate of fish abundance in the ecosystem than abundance of single species populations. The indicator has not been developed yet in the offshore waters in the CORESET project, but in the coastal waters the HELCOM FISH-PRO project has tested the Coastal fish Community Abundance Index. The coastal index is based on estimates of the abundance of two different species groups: Abundance of cyprinids and abundance of piscivores, and reflects the integrated effects of recruitment and mortality of the species included in each functional group. Recruitment success is expected to mainly be influenced by the quality and availability of recruitment habitats, climate and eutrophication. Mortality is influenced by fishing, but also natural predation from other animals, 57

61 58 such as seals, seabirds and fish causes variation in the abundance. The two metrics included in the index are expected to differ in their responses to anthropogenic pressure factors; the abundance of cyprinids is expected to show the strongest link to eutrophication and abundance of piscivores the strongest relationship to fishing pressure. Abundance of cyprinids should have an upper and lower boundary since to low levels may reflect a decreased abundance of some naturally dominating cyprinid species. For monitoring, GES principles and geographical scale, see Coastal Fish - Species Abundance Index. Fish community trophic index The index reflects the general trophic structure at the community level and is based on estimates of the proportion of fish at different trophic levels. Alternatively, estimates of the proportion of piscivores in the fish community may be used. The index provides an integrated measure of changes in the trophic state of the fish community. Typically, very low values of the index may reflect high fishing pressure on piscivores and/or domination of species favoured by eutrophic conditions. Since high levels of the index also may reflect a decreased abundance of some naturally dominating non-piscivore species the index has both an upper and a lower boundary. The HELCOM FISH-PRO has tested the Coastal Fish - Community Trophic Index for coastal fish species. For monitoring, GES principles and geographical scale of that approach, see Coastal Fish - Species Abundance Index. Multimetric macrozoobenthic indices In coastal waters, there are several national versions of multimetric macrozoobenthic indices that are used for the implementation of the WFD. All the indices are based on the Benthic Quality Index (BQI) and adapted to local conditions. For example, previous studies show the high dependency of biodiversity indices to the strong salinity gradient in offshore waters of the Baltic Sea (e.g. Zettler et al. 2007). The use of the BQI was ensured by the adjustment to the open sea and salinity conditions by Fleischer & Zettler (2009). The CORESET project proposed to use the species richness indicator (Villnäs & Norkko 2011) in the offshore water areas, until the validity of Benthic Quality Index (BQI) can be ensured in the open sea conditions. This core indicator thereby includes a number of different indices, which are, however, generally based on abundance, sensitivity of species and taxonomic composition of the benthic invertebrate communities. The indicator is a unitless, general disturbance indicator that responds to multiple pressures. Intercalibration has been finalized for some countries in the WFD Baltic GIG (e.g. Carletti & Heiskanen 2009). The GES boundary is the good/moderate boundary as defined in the implementation of the WFD. These boundaries have mainly been determined by first defining a reference condition based on reference sites, historic data or expert judgement. The assessment units in the coastal waters are the water types or water bodies defined in the WFD and, in the offshore waters, the offshore subbasins defined in the HELCOM thematic assessments (HELCOM 2009 a, b). Lower depth distribution limit of macrophyte species The macrophyte indicator reflects the depth distribution of macrophytes which is dependent on water transparency. The indicator value decreases mainly in response to eutrophication, but is also reduced by coastal shipping and other disturbances causing the resuspension of sediments. The indicator has been used in the implementation of the WFD by all Baltic Sea countries except Poland. Intercalibration has taken place in the WFD Baltic GIG. The CORESET project also applied the proposed macrophyte indicator to the offshore areas of the Baltic Sea, even though it only comprises a limited area of offshore reefs. This means that the GES boundaries in the offshore reefs still need to be established. The GES boundary and the assessment units are as in the previous Core indicators for Descriptor 2 (non-indigenous species) MSFD Descriptor 2 requires two kinds of indicators: trends in the abundance of non-indigenous species (NIS) and their impacts (already in the description of the descriptor). Only one core indicator was

62 Table 6.5. Proposed core indicators under Descriptor 2 (Non-indigenous species). GES criteria GES indicator Proposed core indicators 2.1 Abundance and state characterisation of non-indigenous species, in particular invasive species 2.2 Environmental impact of invasive nonindigenous species Trends in abundance Trends in arrival of new non-indigenous species Ratio of invasive non-indigenous No indicator and native species Impacts No indicator proposed for non-indigenous species: trends in the arrival of new species (Table 6.5). The biopollution index that measures the impacts of non-indigenous species on the ecosystem is in its current form, however, considered as a supplementary indicator (Section 6.3). The proposed GES indicator Ratio of invasive non-indigenous and native species is not covered by a core indicator. Trends in the arrival of new non-indigenous species This indicator follows the number of new species in assessment units during six-year assessment periods, and is thus directly related to the management success of the implementation of the IMO Ballast Water Convention and other relevant policies. The indicator reaches GES when no new non-indigenous species have been found in an assessment unit during the assessment period. The indicator is always nulled after the assessment period; however, the cumulative number of new species in the assessment units over longer time periods can be shown as supplementary information. The assessment units of the indicator are the sub-basins divided by national borders and offshore-coastal water boundaries. Although the data of the non-indigenous species are taken from existing monitoring programmes and other sources of information, targeted survey activities are recommended in the vicinity of high-risk areas such as harbours, anchoring areas and intensive ship traffic Core indicators for Descriptor 4 (food webs) As outlined earlier, several of the biodiversity indicators under GES Descriptor 1 of the MSFD are also relevant for Descriptor 4, which describes a functional food web. The indicators related to criterion 4.3 Abundance/distribution of key trophic groups and species, in particular, have a clear overlap with the indicators under Descriptor 1. Table 6.6 presents the proposed core indicators that can be used to assess GES for food webs. Because all these indicators can also be categorised under GES Descriptor 1, the descriptions are given in Section Thus, no food-web specific indicator has been proposed by the project. The proposed core indicators cover all the GES criteria and associated GES indicators for a food web. The indicators do not, however, represent the key species and trophic groups of the ecosystem at an adequate level (see key species in Table 5.6). The set of core indicators for this descriptor lacks benthic species, which play a key role in the food web as prey species, for example; and zooplankton, which would indicate the availability of prey for planktivorous fish. There are, however, candidate indicators suggested by the project, which describe, for Table 6.6. Proposed core indicators for GES Descriptor 4 (Food webs). Note that all of the proposed indicators are also listed under Descriptor 1 (Biodiversity). GES criteria GES indicators Proposed core indicators 4.1 Productivity of key species or trophic groups 4.2 Proportion of selected species at the top of food webs Performance of key predator species using their production per unit biomass. White-tailed eagle productivity Population growth rate of marine mammals Large fish (by weight). Abundance of fish key trophic groups Fish community trophic index 4.3 Abundance/distribution of key trophic groups and species Abundance trends of functionally important selected groups/species. Abundance of wintering seabirds 59

63 example, the size distribution of benthic long-lived invertebrates and the abundance of zooplankton (see Section 6.2). The supplementary indicators for the ratios of different functional groups may also evolve into food web core indicators if further developed and properly tested (see Section 6.3) Core indicators for Descriptor 6 (sea-floor integrity) GES Descriptor 6 describes the condition and extent of benthic habitats and focuses both on the state as well as the impact on and pressure to the seafloor. Among the proposed core indicators, Lower depth distribution limit of macrophyte species and Multimetric macrozoobenthic indices address GES criterion 6.2 Condition of the benthic community (Table 6.7). Because these indicators can also be categorised under GES Descriptor 1, the descriptions are given in Section No core indicator was selected for GES criterion 6.1 Physical damage, having regard to substrate characteristics. This criterion has two GES indicators: the first describes the extent of biogenic substrates and the second the extent of significantly affected seabed. The CORESET project has, however, suggested a candidate indicator for the extent of seabed biotopes significantly affected by the anthropogenic cumulative impact (see Section 6.2.2). In addition, the HELCOM Initial Holistic Assessment contains a chapter that describes the extent of anthropogenic pressures and impacts in the Baltic Sea (HELCOM 2010 a, b); the data layers are published in the HELCOM Data and Map Service ( 6.2 Candidate indicators for the assessments of biodiversity Within the tight time schedule of the HELCOM CORESET project, it was not possible to finalise the selection of all the proposed indicators that had been identified as potentially important for the assessment of the environmental status of the Baltic Sea. These indicators were labelled in this report as candidate indicators and will be readdressed during the second phase of the project. Some of the candidate indicators lack GES boundaries, some have methodological challenges, while others need the data to be compiled and undergo further testing. The CORESET expert group for biodiversity considered it important to continue developing them towards operational core indicators. This section presents the candidate indicators discussed during the CORESET project, while Part B of this report (HELCOM 2012a) contains more detailed descriptions of them Candidate state indicators for biodiversity The candidate biodiversity indicators that could be used to measure the state of the marine biodiversity are listed in Table 6.8. Significant additions to the proposed set of core indicators would be the indicators related to distribution (GES criterion 1.1), breeding waterbirds, zooplankton and phytoplankton, anadromous fish, harbour porpoise and benthic communities. Table 6.7. Proposed core indicators for Descriptor 6 (Sea floor integrity) in relation to the MSFD GES criteria and GES indicators. 60 GES criteria GES indicator Proposed core indicators 6.1 Physical damage, having regard to substrate characteristics 6.2 Condition of the benthic community Type, abundance, biomass and areal extent of the relevant biogenic substrate Extent of the seabed significantly affected by human activities for the different substrate types. No indicator No indicator Presence of particularly sensitive and/or tolerant species. Lower depth distribution limit of specific perennial macrophyte species Multi-metric indexes assessing benthic community condition and functionality, such as species diversity and richness, proportion of opportunistic to sensitive species Proportion of biomass or number of individuals in the macrobenthos above some specified length/size Parameters describing the characteristics (shape, slope and intercept) of the size spectrum of the benthic community. Multimetric macrozoobenthos indicators (BQI, MarBIT, DKI, BBI, ZKI, B) No indicator No indicator

64 Table 6.8. Candidate state indicators for biodiversity. The indicators are related to the MSFD GES descriptors and criteria. MSFD GES descriptors and criteria Descriptor 1 Criterion 1.1 Species distribution Criterion 1.2 Population size Criterion 1.5 Habitat extent Criterion 1.6 Habitat condition Descriptor 4 Criterion 4.1 Productivity of key species or trophic groups Criterion 4.3 Abundance/distribution of key trophic groups and species Descriptor 6 Criterion 6.2 Condition of the benthic community Candidate state indicators Distribution of harbour porpoise Sea trout parr density, quality of spawning habitats (also criterion 1.6) Salmon smolt production capacity Offshore fish populations and communities Blue mussel cover Seasonal succession of functional phytoplankton group Phytoplankton diversity Zooplankton species diversity Cladophora length (also criterion 5.2) Population structure of long-lived macrozoobenthic species (also criterion 4.3) Fatty-acid composition of seals as measure of food intake composition Biomass of copepods Biomass of microphagous mesozooplankton Mean zooplankton size Zooplankton-phytoplankton biomass ratio Abundance of breeding populations of seabirds Offshore fish populations and communities Ratio of perennial and annual macrophytes (also criterion 1.6) Although it may be premature to claim anything concrete regarding the process to finalise the candidate indicators, the salmon and sea trout indicators are currently being developed by ICES WGBAST 9 with several sub-parameters of the indicator already existing. For example, two of the zooplankton indicators are well developed, but their applicability needs to be validated in a wider area; further, the harbour porpoise indicator as well as the phytoplankton indicators are waiting for indepth exploration of data for the GES boundaries. By contrast, there is not even enough background data to start the development work on the fattyacid composition, the macrophyte ratio indicators or the mussel cover indicator (Table 6.8). The perspectives of the other candidate indicators rest somewhere between these extremes. Distribution of harbour porpoise The indicator is intended to measure the geographic distribution of harbour porpoise based on the frequency of registrations per area in a year (e.g. >10 registrations/1,000 km 2 ). There is regular monitoring for the distribution and abundance of harbour porpoise in the south-western Baltic Sea and the current project activities in the Baltic Proper can serve to operationalise the indicator in the near future. However, until a coordinated methodology for the calculation of the indicator is developed it cannot be proposed as a core indicator. The Baltic Proper s harbour porpoise population is currently critically endangered. As an intermediate target, GES may be defined as a positive trend, i.e. an increase in the distribution of the porpoise population between assessment periods. Ultimately, GES is reached when the entire historical range in the Baltic Proper is recolonised. It should be noted, however, that since the abundance of the harbour porpoise in the Baltic Proper is very low at present, it is no longer reliably quantifiable. An indicator based on sightings and recordings of their presence is therefore recommended until the density has recovered sufficiently to allow a reliable estimation of their distribution. 9 ICES Working Group for Baltic Salmon and Sea Trout. 61

65 Fatty-acid composition of seals as a measure of food composition The indicator measures the nutritional status of seals by fatty-acid composition. While there may be multiple pressures behind a change in fatty-acid composition, fishing, the deterioration of habitats of prey species and hazardous substances are perhaps the predominant pressures. However, for a population near its carrying capacity and thus competing for food, this indicator may not be reliable. GES could be estimated from historic data and literature surveys. The assessment unit is the entire Baltic Sea. Sea trout parr density and the quality of spawning habitats Two parameters related to sea trout are proposed: 1) sea trout parr densities of sea trout rivers vs. their theoretical potential densities (%); and 2) the quality of the spawning habitats. The indicator thus responds to both fishing pressure as well as the pressures degrading the quality of spawning habitats. ICES WGBAST is further developing both the parameters. The first parameter is expected to be operational by 2012/2013 and the second by 2013/2014. WGBAST already estimates parr densities in rivers (ICES 2011 b). 62 Abundance of breeding populations of seabirds The indicator includes apriori selected seabird species, which have been categorised into functional groups. The indicator responds to multiple pressures, such as habitat loss, food availability and disturbance. The abundance can be measured on three levels: species, functional groups or all seabirds. In the case of the two latter, an integration method needs to be developed. Although data for the indicator exists, data compilation and the development of the GES boundary require more work. This indicator is predicted to be a very promising candidate for the set of core indicators. Salmon smolt production capacity Three parameters that can be combined into an index are proposed to assess the state of salmon: 1) the survival of smolts in the sea (%); 2) the number of smolts produced annually in a river; and 3) the trend in the number of salmon spawning rivers (%). The indicator responds to fishing pressure - target and non-target - and pressures degrading the quality of spawning habitats. The first two indicators are ready, in principle, for operational use and the results are available in the ICES WGBAST reports (ICES 2011 b). ICES WGBAST will further develop the third parameter, as well as consider ways of combining the three parameters into an index. The outcome of this work is expected to be operational by GES for the index has not been developed; however, HELCOM BSAP includes a target for riverine smolt production capacity of 80%. Offshore fish communities and other fish indicators The CORESET fish indicators have relied on the HELCOM FISH-PRO project, which assesses the status of coastal fish communities. The CORESET biodiversity expert group has, however, also identified additional indicators which are based on other sampling methods and followed the ICES workshops on Descriptor 3 indicators to facilitate the development of core indicators for commercially exploited fish stocks. Offshore fish populations and communities were studied from the Baltic International Trawl Survey (BITS) data. The work will continue with other data sets to develop indicators which are compatible with the coastal fish indicators but comprise different species. The core indicators Abundance of fish key trophic groups and Fish population abundance currently only include sampling by gill nets, where perch and some cyprinids (roach, white bream, etc.) typically form the bulk of the catch. Other data sources, such as coastal trawl surveys, can be used to obtain population level data from a wider group of species. The fish catch data collected under EU Data Collection Regulation 665/2008/EC is also a source which can be used for this indicator. One part of this data, e.g. sampling of predatory species from herring traps, covers all size classes and can be treated here as fishery independent data. The potential indicators from these data sources are Proportion of fish larger than the mean size of first sexual maturation and Mean size at first sexual maturation. These indicators are closely linked to the effects of fishing pressure on fish populations

66 and on population level biodiversity. The testing of these indicators is being carried out in the LIFE+ MARMONI project. GES is anticipated to be based on fishery independent data sources and on the principle that each individual fish should have a chance to spawn at least once before they are targets for effective fishery. Cyprinids, especially bream (Abramis brama), roach (Rutilus rutilus) and white bream (Blicca bjoerkna), have become increasingly abundant in large archipelago areas of the northern Baltic Sea (e.g. in the Gulf of Finland, the Archipelago Sea and the Åland archipelago), mainly due to coastal eutrophication. This indicator is complementary to the core indicator Fish population abundance as regards cyprinid species. It will use sampling methods which give a more reliable estimate of cyprinid abundance, such as horizontal echo-sounding (with trawl or seine samples of the fish) and commercial catches of cyprinids with trap nets and logbook data. The results of these sampling methods, however, would not be directly comparable with the existing gill net monitoring by HELCOM FISH-PRO. Targets could be set as expert judgements, for example a 30-40% reduction in cyprinid biomass in coastal regions where they are very abundant. Ratio of opportunistic and perennial macrophytes The ratio between opportunistic and perennial macrophytes reflects the relative abundance of functionally important groups, with the perennial species often being habitat structuring and sensitive to water quality while the annual species are more tolerant of or even opportunistic in eutrophic conditions. The indicator is based on g dry weight m -2 and expressed as a percentage of the respective type. A shift to a higher percentage of annual macrophytes is primarily considered as a sign of both eutrophication and physical disturbance. The indicator is already applied in the implementation of the WFD in Estonia, Germany and Poland. Assessment units are the WFD water bodies and the GES boundaries that have been developed for specific water types. Cladophora length The length of the green seaweed Cladophora glomerata has been proposed as an indicator of seasonal nitrate availability. Although being primarily a eutrophication indicator, it still provides an easy measure of the condition of hard substratum habitats. It can also be used as an indirect estimate of the state of biodiversity since it also indicates the loss or decreased condition of perennial macroalgae that support diverse communities of associated species. Further validation of the response to nutrient enrichment is needed and is being conducted as part of the ongoing LIFE+ MARMONI project. The indicator is presumed to be low-cost as it is possible to measure from stationary buoys, for example. The GES boundaries can tentatively be based on the response of the length to the nitrate concentrations. Thus, GES boundaries for nitrate concentration will set the GES boundaries for this indicator. Blue mussel cover Blue mussel (Mytilus edulis/trossulus) is an important habitat-forming species in the Baltic Sea and is a food source for benthic feeding birds and fish. Depending on the definition of the methodology (distribution or extent), the indicator based on this species would fulfil GES criteria 1.1 (species distribution); 1.4 (habitat distribution); 1.5 habitat extent; and/or the GES indicator (areal extent of biogenic substrate) - all of which are poorly covered by the currently proposed core indicators. At present, although there is no dedicated monitoring in place, the blue mussel cover in stationary monitoring transects has probably been assessed all around the Baltic Sea. Size distribution of long-lived macrozoobenthic species Long-lived species such as the bivalve molluscs Mytilus edulis/trossulus, Cerastoderma glaucum, Arctica islandica and Macoma balthica, the isopod crustacean Saduria entomon or decapod crustacean species are key species in the benthic community and reflect its condition. The population structure, measured as abundance per size class, is proposed to reflect physical disturbance as well as the indirect effects of eutrophication and selective extraction of species. Continued development of this indicator requires that the response to different pressures as well as the definition of the natural size spectrum be analysed. Although current monitoring in the Baltic Sea does not fully support this 63

67 indicator, with slight modifications in the analyses the proportion of large individuals can be counted. Depending on the scale of the predominant pressure (hypoxia / bottom trawling / dredging), the assessment units can range from WFD water bodies to sub-basins. Biomass of copepods The biomass of copepods primarily reflects the quantity and quality of food for zooplanktivorous fish. As a primary food source for zooplanktivorous fish and efficient consumers of phytoplankton, copepods are central to the ecosystem functioning. The copepod biomass is negatively affected by eutrophication and fishing. The indicator is expressed as mg m -3 or as a percentage of the total mesozooplankton biomass. Monitoring is carried out in all the Baltic Sea countries, albeit with different frequencies and area coverage. The approach for defining GES is based on reference data on zooplanktivorous fish and the identification of time periods when fish growth and population stocks were relatively high. A boundary for GES is set as a threshold mark between acceptable and unacceptable conditions. The geographic scale of assessments is proposed to be based on Baltic Sea sub-basins as defined by HELCOM. Biomass of microphagous mesozooplankton The indicator primarily reflects the trophic state of the ecosystem and increases with increasing eutrophication. It is expressed as mg m -3 or as a percentage of the total mesozooplankton biomass. An increase in the indicator value may also be linked to decreased food availability/quality for zooplanktivorous fish. The biomass of microphagous mesozooplankton is positively affected by eutrophication. The approach for defining GES is based on the reference data of water transparency and/or chlorophyll a and the identification of time periods when these parameters were considered in GES. A boundary for GES is set as a threshold mark between acceptable and unacceptable conditions. The geographic scale of defining GES and conducting current status assessments is proposed to 64

68 be based on Baltic Sea sub-basins as defined by HELCOM and the WFD coastal water types. Zooplankton diversity index Initial testing of the zooplankton diversity index has been conducted. It is a biodiversity-based indicator displaying the ratio between the number of species actually observed in the area and the species number registered in the area in any given year (season), assuming that ratios less than 1 correspond to decreased diversity, and that ratios over 1 indicate an invasion or colonization from nearby areas. Tests showed that the ratio is consistently <1, has been increasing over the last three decades and that it shows a cyclic pattern. Further testing is needed to evaluate the applicability of the indicator. Mean zooplankton size The zooplankton species composition has changed in the Baltic Sea due to climatic fluctuations (e.g. salinity changes), an increase of hypoxic bottom waters (limiting vertical migration) and increased herring and sprat predation. As a general outcome of these changes, the zooplankton size has decreased. The decreased abundance of large-bodied species causes food depletion for predators like herring and sprat as well as for fish-feeding birds (Österblom et al. 2006). GES can be defined from old data series by using weight-at-age measurements of zooplankton-feeding fish species (herring and sprat). As the indicator measures very largescale changes in the Baltic Sea, the assessment units can be sub-basins or even combining some of them to create larger units. Ratio of zooplankton and phytoplankton biomasses One way of measuring the state of the food web in the Baltic Sea is to follow the ratios of trophic levels. By comparing the zooplankton-phytoplankton biomass ratio with fish-related parameters (weight at age, spawning stock biomass, fishing mortality, etc.) over longer time spans, it may be possible to define a ratio where the food web appears to be in GES. As the indicator measures very large-scale changes in the Baltic Sea, the assessment units can be sub-basins or even combining some of them to create larger units. Phytoplankton diversity or evenness Initial testing of the biodiversity-based indicators have been conducted concentrating on the dominant phytoplankton species and their diversity, for example the proportion of the total biomass formed by the most dominant species; the number of species that make up the majority of the total biomass; and an applied Shannon s index based on the most abundant species that together make up >95% of the total biomass. The preliminary testing of the indicators show promise but needs further elaboration. Seasonal succession of functional phytoplankton groups Initial testing of an index based on the seasonal succession of phytoplankton functional groups has been conducted. The proposed index has previously been presented by Devlin et al. (2007) for UK waters. The method is based on first defining reference growth envelopes for functional groups of interest using long-term data or un-impacted sites. The present state is assessed by comparing the present seasonal distribution of each functional group to the reference by use of a normalized score. The index has been tested for diatoms and dinoflagellates in the Baltic Sea area. Further testing is needed to evaluate the appropriateness of the indicator Candidate pressure indicators for biodiversity The GES descriptors for biodiversity, food web and sea floor integrity contain mainly criteria and indicators for the state or impacts on the ecosystem (Anon. 2010). The anthropogenic pressures affecting the state or impacts can be numerous yet only a few have been mentioned in the EC decision document (Anon. 2010). An assessment of individual pressures has, however, advantages which should be heeded. First, a pressure indicator may be easier to develop and monitor than an impact indicator; and second, a pressure indicator is linked to the need for management measures in order to improve the state of the environment. Pressure indicators are, however, always indirect indicators for GES because an increase or decrease of a pressure does not indicate whether GES has been reached for any biodiversity descriptor. 65

69 66 The process that was used to guide the indicator selection (see Section 5.3.2) resulted in an expert evaluation of the pressures perceived to have the highest negative impact on biodiversity. Those pressures identified as predominant are presented in Table 6.2 while the detailed pressure matrices are presented in Annex 1. Many of the pressures are already measured with the spatial accuracy required for developing pressure indicators. Indicators and targets related to inputs of nutrients already exist within HELCOM in the BSAP and are further refined within the HELCOM LOAD group based on the work of the HELCOM TARGREV project. Although indicators related to inputs of synthetic and non-synthetic substances do not currently exist, they are being discussed in other HELCOM working groups or projects (e.g. CORESET HS, COHIBA and HELCOM LOAD) while spatial data is available for some substances. Data on the hunting of seals (and birds) is collected at the national level while data on fishing in terms of catches and efforts of commercial fishery is collected at the EU level. However, there is no spatially-detailed fishing pressure indicator. Oil spills are being monitored in the Baltic Sea by aerial surveillance but the number of oiled birds, for example, is currently not monitored. Thus, the predominant pressures on biodiversity, which are not properly monitored and where indicators are missing, are primarily by-catch in fisheries, noise and the physical disturbance of the seabed. These indicators were the focus for the development of pressure indicators in the biodiversity expert group. By-catch of marine mammals and seabirds The indicator directly reflects the impacts of fishing on marine mammals and seabirds. Fishing is considered as one of the main pressures on seabirds and most likely the most important pressure for harbour porpoises in the Baltic Sea area. The indicator is measured as numbers of individuals by-caught in fishing gear or as a proportion of the population killed annually. According to CORESET experts, the required monitoring to operationalise the indicator is not in place. However, this may be solved if CCTV (closed-circuit television) surveillance systems become mandatory on EU fishing vessels. In addition, the requirements of the MSFD criteria and associated indicators for Descriptors 1 and 4 should lead to additional monitoring efforts of by-catches carried out by the Member States (Anon. 2010). Acceptable by-catch rates must be determined for specific species and subpopulations. A proposed target was already stated in the BSAP - by-catch of harbour porpoise, seals and seabirds should be significantly reduced with the aim of reaching close-to-zero by-catch rates. The assessment units could be HELCOM sub-basins. The indicator can be widened to also include nontarget fish and invertebrate species. Impacts of anthropogenic underwater noise on marine mammals The indicator directly reflects the single and cumulative impacts of anthropogenic underwater noise on marine mammals in the Baltic Sea area such as high-amplitude, low and mid frequency impulsive sounds introduced by different types of sonar, seismic activities, the construction of offshore wind farms or acoustic harassment devices. It also includes low frequency continuous noise generated from shipping, sand and gravel extraction or the operation of offshore wind farms. According to the HELCOM Initial Holistic Assessment, anthropogenic underwater noise is considered as a widespread pressure in the entire Baltic Sea. Underwater noise can be assessed by measurements and modelling based on appropriate propagation models and harmonised noise profiles of the relevant sources. Species-dependent impacts need to be specifically estimated and weighted. According to CORESET experts, the required monitoring to operationalise the indicator is not in place. The requirements of MSFD Descriptor 11 (Anon. 2010) should lead to the basic monitoring of impulsive and continuous sound sources in the marine waters of the Member States and serve as a basis for mapping noise to illustrate the entire soundscape of an area and associated impact zones for different biota of concern. Acceptable noise thresholds should be set to reflect he impact levelss to be avoided. Assessment units are to be determined but the rather quick attenuation of high frequencies should be considered. The indicator can be widened to include other affected marine organisms such as fish or invertebrates. Oiled birds The number of oiled birds is proposed as an indicator to reflect the pressure of oil spills on biota. The

70 oiling of seabirds is a significant pressure on the breeding and particularly wintering populations of seabirds (HELCOM 2009 b). The first step is to identify what type and frequency of monitoring is needed to support the indicator. The indicator would most probably be based on the core indicator Abundance of wintering populations of seabirds - the monitoring effort of the indicator would also produce data for oiled birds. The proportion of oiled birds in the populations would be followed over time and GES would be based on an acceptable mortality rate for the population. Fishing targeted catches Fishing affects offshore and coastal fish communities, seabed habitats and indirectly pelagic plankton communities. The catch data from ICES areas, rectangles or from spatially more detailed VMS-logbook data sets should be used to develop a coherent picture of the extent and intensity of fishing. This indicator is also contained in GES Descriptor 3 (commercially exploited fish stocks) and will most likely be developed by ICES. The indicator could be used in combination with the seabed habitat maps to produce an indicator of significantly affected benthic habitats. Cumulative impacts on benthic habitats The indicator for the anthropogenic cumulative impact on benthic habitats follows the amount of habitat area affected by the physical disturbance of the seabed. The indicator would primarily require spatially-detailed data from dredging, the disposal of dredged matter, bottom trawling fishery and various installation and construction works. Other human activities can be also added to this physical disturbance indicator. This indicator addresses MSFD GES criterion 6.1, which calls for an assessment of anthropogenic impacts on benthic habitats and criterion 1.6 habitat condition. Underlying habitat maps were produced by the EUSeaMap project and the indicator has been tested by the pressure data from the HELCOM HOLAS project, presented in the HELCOM Initial Holistic Assessment (HELCOM 2010 b). GES measures an acceptable proportion of lost or significantly damaged habitats and is suggested to be based on the classification of the EU Habitats Directive. The assessment units would be the sub-basins. Incidentally and non-incidentally killed white-tailed eagles Information on the causes of mortality of the white-tailed eagles is available in many Baltic Sea countries. The indicator would follow the role of technical installations (towers, wind mills, power lines) and persecution in the population development of the species. GES should most likely be on the no increasing trend basis. Assessment units would be the Baltic Sea countries. Inputs of nitrogen and phosphorus The HELCOM BSAP contains a provisional agreement on the annual maximum allowable inputs of nitrogen and phosphorus to the Baltic Sea, and an allocation of the inputs to sub-basins and countries (HELCOM 2007 a, HELCOM 2011). The indicator would be the total amounts of nitrogen and phosphorus draining to the sea areas (division of sub-basins by country borders and WFD catch- Table 6.9. Candidate pressure indicators for biodiversity status outlined by the expert group. MSFD GES descriptors and criteria affected by Candidate pressure indicators the pressure Descriptor 1, criterion 1.2 By-catch of mammals and seabirds Descriptor 4, criterion 4.3 Descriptor 1, criterion 1.1 Impacts of underwater noise on marine mammals Descriptor 1, criterion 1.2 Number of seabirds being oiled annually Descriptor 4, criterion 4.3 Descriptor 1, criterion 1.2 Incidentally and non-incidentally killed white-tailed eagles Descriptor 4, criterion 4.3 Descriptor 1, criteria Cumulative impact on benthic habitats Descriptor 6, criteria Descriptor 1, criteria 1.2, Fishing of targeted catches Descriptor 4, criterion 4.2 Descriptor 1, criteria Inputs of nitrogen and phosphorus Descriptor 6, criterion

71 ment areas). The indicator is the prerequisite for the follow-up of the eutrophication status and is also a significant pressure indicator for biodiversity. Although the nutrient concentrations in seawater can show the pressure for the biodiversity, the input indicator is required to follow management measures to reduce the inputs of nutrients. The inputs of nutrients (both waterborne and airborne) are followed annually by the HELCOM Contracting States. The indicator was not specifically addressed by the CORESET project as its development of the indicator is ongoing in the HELCOM LOAD group. 6.3 Supplementary indicators to support the core indicators The selection process for identifying core indicators identified several parameters which follow changes in the Baltic ecosystem but which were discarded from the final set for several reasons. Some indicators did not clearly reflect anthropogenic pressures - some were redundant to other indicators and for others it was not possible to develop a quantitative threshold to measure GES. Nevertheless, these parameters were considered important to support the assessments made by the core indicators. The supplementary indicators also give valuable information on natural fluctuations in the environment. Some of the candidate indicators (see Section 6.2) can also be operationalised as supplementary indicators until they are further developed into core indicators. Many of the candidates have data in place and they provide useful information for marine status assessments. In this section and in Table 6.10, both the biological and environmental supplementary indicators are presented. The supplementary indicators will have a similar reporting format as the HELCOM Indicator Fact Sheets that are presented on the HELCOM web site. Population Development of Great Cormorant Population Development of White-tailed Sea Eagle Decline of the harbour porpoise (Phocoena phocoena) in the southwestern Baltic Sea The abundance of comb jellies in the northern Baltic Sea Ecosystem regime state in the Baltic Proper, Gulf of Riga, Gulf of Finland, and the Bothnian Sea Ratio of diatoms and dinoflagellates Ratio of autotrophic and heterotrophic organisms Intensity and areal coverage of cyanobacterial blooms Abundance and distribution of non-indigenous invasive species Biopollution index Table Supplementary indicators for biodiversity. Web links to HELCOM Indicator Facts Sheets have been provided, if available. Supplementary biodiversity indicators Objective of the indicator Population Development of Sandwich Tern Porpoise/ ecoregime/ Describes the change in taxonomic group composition, presumably caused by eutrophication. Not applicable for the entire sea area. Describes a change in functional group composition and energy flow in the food web. Not properly tested. Describes effects of phosphorus inputs and internal loading ( CyanobacteriaBloomIndex/) Presents the distribution, abundance and temporal trends of selected invasive non-indigenous species in the assessment units. Estimates the impacts of non-indigenous species on native species, habitats and the ecosystem functioning. See text below. 68

72 Table 6.10 continues Supplementary environment indicators Surface water salinity Near bottom oxygen conditions Sea water acidification The ice season Total and regional Runoff to the Baltic Sea Water Exchange between the Baltic Sea and the North Sea, and conditions in the Deep Basins Hydrography and Oxygen in the Deep Basins Development of the sea surface Temperature in the Baltic Sea in 2009 Wave climate in the Baltic Sea in 2009 Bacterioplankton growth Objective of the indicator Describes environmental conditions caused by climatic variability. Describes condition of the near-bottom habitats caused by climatic variability and nutrient inputs. Describes a temporal change in sea water ph. Describes the extent of sea ice and also reflects a potential threat for ice-breeding seals: ifs2010/en_gb/iceseason/ Exchange/ Supplementary pressure indicators Nitrogen emissions to the air in the Baltic Sea area Emissions from the Baltic Sea shipping in 2009 Atmospheric nitrogen depositions to the Baltic Sea during Spatial distribution of the winter nutrient pool Waterborne inputs of heavy metals to the Baltic Sea Atmospheric deposition of heavy metals on the Baltic Sea Atmospheric deposition of PCDD/Fs on the Baltic Sea Shipping Illegal discharges of oil in the Baltic Sea during 2009 Objective of the indicator Describes anthropogenic pressures for all biota in the form of eutrophication: en_gb/nitrogenemissionsair/ Describes anthropogenic pressures for all biota in the form of contamination and eutrophication: Describes anthropogenic pressures for all biota in the form of eutrophication: en_gb/n_deposition/ Describes anthropogenic pressures for all biota in the form of eutrophication. en_gb/winternutrientpool/ Describes anthropogenic pressures for all biota in the form of contamination: en_gb/waterborne_hm/ Describes anthropogenic pressures for all biota in the form of contamination: en_gb/hm_deposition/ Describes anthropogenic pressures for all biota in the form of contamination: en_gb/pcddf_deposition/ Describes the extent of underwater noise, disturbance for seabirds, vector for non-indigenous species, offshore wastewater and, in shallow areas, seabed disturbance. Describes anthropogenic pressures for all biota, particularly seabirds, in the form of contamination: Supplementary biodiversity indicators The supplementary indicators for biodiversity include HELCOM Indicator Fact Sheets for the abundance of bird populations and the harbour porpoise, and some planktonic indicators. The CORESET expert group for biodiversity found it particularly difficult to develop core indicators for planktonic organisms. In many cases, promising indicators had relevance only in some parts of the Baltic Sea. An example is the ratio of diatoms and dinoflagellates, which has been used in many parts of the world to describe changes in the phytoplankton community. A diatom-dominated community is assumed to reflect an ecosystem in good environmental status and vice versa. In the Baltic 69

73 Sea, however, as this seems to hold true in some sub-basins only, the indicator was thus categorised as a supplementary indicator. Another supplementary-labelled indicator is the ratio of autotrophic to heterotrophic planktonic organisms. Being wider in functional groups than the previous indicator, this indicator may be applicable in a larger area, but it currently lacks proper validation. Hence, it is considered a supplementary indicator until the pressure relationships, the applicability to all sub-basins and the GES boundary can be tested with data. There are very few ways of objectively assessing the impacts of non-indigenous species on native species and biotopes. One of the most transparent methods has been described in Olenin et al. (2007) termed the biopollution index. The index considers five factors for every non-indigenous species: abundance; distribution; impact on species; impact on habitats; and impacts on ecosystem functioning. Each factor has a number of qualitative classes which have been defined clearly with the index value being derived through a combination of the factor classes. As the index value is given only for single species, the overall biopollution of a site is derived through the one-out-all-out approach, where the highest impacting species determines the status. GES is no new impacts by non-indigenous species in an assessment period. The assessment units of the indicator are the sub-basins divided by national borders and the offshorecoastal water boundary. An assessment of impacts is an indicator used in combination with the core indicator following the number of arriving NIS; in cases of no new arrivals, the impact indicator is not used. New baseline studies with the already established NIS should be made regularly to follow the changes in the impacts of NIS in the ecosystem - though not as part of assessing if GES has been met. 70 Cyanobacterial blooms have been measured in the Baltic Sea for several years with two kinds of indicators: the intensity of the blooms and the areal coverage of the blooms. Both indicators respond to phosphorus and are thus linked to an anthropogenic pressure; however, it is difficult to define how often or how widely a bloom can occur while still being considered to be in GES, particularly in the Baltic Sea where cyanobacterial blooms are an intrinsic property of the ecosystem. The abundance and distribution of non-indigenous invasive species (NIS) is an indicator that describes the abundance and further spreading of selected NIS which are known as invasive. Information on the spatial extent and abundance of NIS is relevant for marine status assessments. The expert group decided to define a dirty dozen of NIS in the Baltic Sea and make distribution maps, accompanied by abundance and temporal trend information where available Supplementary indicators for environmental variability The HELCOM Indicator Fact Sheets contain several indicators that do not reflect anthropogenic pressures but describe causes of natural variability in different environmental features. There are, however, indicators describing chemical and physical features in the Baltic Sea. Table 6.10 presents the available supplementary indicators for environmental variability Supplementary pressure indicators for biodiversity The HELCOM Indicator Fact Sheets contain several indicators that measure various anthropogenic pressures, such as maritime activities and emissions or inputs of hazardous substances to the sea. Regarding the inputs of hazardous substances, these could also be listed under Chapter 7, as the aim of the expert group for hazardous substances is to include pressure indicators to the set of core indicators in the future. Table 6.10 presents the available supplementary indicators for anthropogenic pressures. This selection of pressure indicators contains several indicators that should be considered as core indicators, such as inputs of hazardous substances. Currently, however, the Baltic-wide data that are available is so limited that such a development will not likely take place during the project period.

74 7 Hazardous substances core indicators 7.1 Proposed core indicators for hazardous substances The CORESET expert group for hazardous substances identified 13 core indicators for concentrations of hazardous substances and their biological effects (Table 7.1). Each of the core indicators consist of 1-16 parameters (congeners of closely-related substances) that were selected on the basis of their adverse effects to the environment, cost-efficient analyses and available GES boundaries (see Section 5.4.2). The proposed core indicators are interim expert products, which require more scientific work on methodological details, for example. 71

75 Eight of the core indicators measure the BSAP ecological objective referring to the concentrations of hazardous substances; one measures the concentrations of the radioactive substance Cs-137; and four measure the biological effects of hazardous substances. The nine core indicators measuring concentrations cover the most common, widely distributed and harmful substances in the Baltic Sea. Although monitoring them is largely in place or under planning, large gaps have been found. The pharmaceutical substances diclophenac and 17-alpha-ethinylestradiol do not have established monitoring in the region. Moreover, monitoring the coverage of offshore waters needs to be improved for several substances. GES boundaries, defining good environmental status (GES) and the status below GES (sub-ges), have been identified for all of the proposed core indicators. As most of the core indicators are current or proposed EU Priority Substances, their GES boundaries are Environmental Quality Standards (EQS, or specific QS for other matrices). The revision of the Priority Substances is still on-going and all of the EQS-based GES boundaries are therefore provisional. Some GES boundaries are, however, proposed to be the OSPAR Environmental Assessment Criteria (EAC). The selection criteria for each of the core indicators, including policy relevance, environmental impacts (PBT properties), current management and the availability of monitoring are presented in the Table 7.1. Proposed core indicators for hazardous substances in the Baltic Sea. The indicators assess the HELCOM BSAP ecological objectives Concentrations of hazardous substances at natural levels, Radioactivity at pre-chernobyl level and Healthy wildlife as well as the EU MSFD GES Descriptor 8 Concentrations of contaminants are at levels not causing pollution effects. Approaches for the proposed GES boundaries are presented with the numeric boundaries given in Part B of this report (HELCOM 2012 a). Key: EAC = Environment Assessment Criterion; BAC = Background Assessment Criterion; EQS = Environmental Quality Standard; QS = specific Quality Standard. Proposed core indicators Parameters Proposed GES boundaries 1 Polybrominated biphenyl ethers Congeners tribde 28, tetrabde 47, pentabde 99 and 100, hexabde 153 and 154 For biota and sediment, but pending on EU adoption. 2 Hexabromocyclododacene Hexabromocyclododacene (HBCD) Identified EU QS for biota and sediment but pending on EU adoption. 3 Perfluorooctane sulphonate 4 Polychlorinated biphenyls and dioxins and furans 5 Polyaromatic hydrocarbons and their metabolites Perfluorooctane sulphonate (PFOS) CB congeners 28, 52, 101, 118, 138, 153 and 180. WHO-TEQ of dioxins and furans and dioxin-like PCBs The US EPA 16 PAHs in bivalves and sediment and selected metabolites in fish 6 Metals Cadmium (Cd), mercury (Hg) and lead (Pb) Identified EU QS for biota but pending on EU adoption. Dioxins: Identified EU QS for biota but pending on EU adoption. PCBs: tentatively EAC for CB 118 and 153 in biota and sediment until EU QS is adopted. Established OSPAR EACs and established and draft EQSs in mussels and sediment. Proposed EAC for metabolites in fish. Established EU EQS for biota (Hg). Pending EU QS for Cd and Pb in biota and sediment. Effect Range Low for Hg in sediment. 7 Radioactive substances Caesium-137 Established by HELCOM MORS for fish and water. 8 Tributyltin compounds / imposex index Tributyltin and/or imposex index 9 Pharmaceuticals Diclofenac and 17-alpha-ethinylestradiol OSPAR EAC (established for concentrations in mussels and sediment), OSPAR EAC for imposex in mussels and EU QS human health in fish. Identified EU QS for biota and water but pending on EU adoption. 10 General stress indicator Lysosomal membrane stability EACs and BACs established for fish and Mytilus spp. For amphipods under development. 11 General stress indicator Fish disease index Established BACs and EACs for flounder and cod. for fish 12 Genotoxicity indicator Micronucleus induction BACs established for fish and bivalves. EACs under development. 13 Reproductive disorders Malformed embryos of eelpout and amphipods BACs and EACs established for amphipods. Established BACs for fish, but EACs under development. 72

76 descriptions of the core indicators in Part B of this report (HELCOM 2012 a). The no deterioration principle of the Water Framework Directive gives, in addition, the obligation not to allow increased concentrations of the above mentioned substances in biota. This is valid especially for persistent organic pollutants (POP) under the Stockholm Convention (Substances 1-4). This should be ensured with long-term monitoring, even if the tentative GES boundaries may change over time (EQS Directive 2008/105). The four core indicators for biological effects cover responses at the enzymatic, cellular and organism levels. Monitoring is only carried out in few Baltic Sea countries, even though the required knowledge for monitoring is in place in all the countries. When these core indicators are compared with the biodiversity core indicators (e.g. population changes of seabirds and fish or the health status of marine mammals), the overall picture of the state of the ecosystem becomes even clearer. Genotoxicity indicator Genotoxicity is specifically measured by the induction of micronuclei in the cell (MN), which serves as an index of cytogenetic damage during cell divisions, i.e. a lack or damage of the centromere or chromosomal aberrations. The MN test can be applied in a range of species (e.g. bivalves and fish). The indicator of genotoxic effects reflects damage to the genetic material of organisms, which could affect their health and potentially their offspring. The application of cytogenetic assays on ecologically relevant species offers the opportunity to perform early health assessments in relation to exposure to contaminants. The general stress indicator - Lysosomal membrane stability The general stress indicator lysosomal membrane stability (LMS) is a parameter for the integrity of cell membranes and has been tested in various species of mussel and fish from different climate zones. Reduced LMS indicates a response to complex mixtures of chemicals present in water and sediments, point sources of pollution and single pollution events and accidents; it is also a means to discover new hot spots of pollution. LMS is an integrative parameter that also responds to other stressors such as severe nutritional deprivation, severe hyperthermia, prolonged hypoxia, and liver infections associated with high densities of macrophage aggregates. In this respect, LMS may serve as an indicator of individual health status Fish disease index Fish disease index is a general stress indicator for fish. The occurrence of significant changes in the prevalence of externally visible fish diseases can be considered a non-specific and more general indicator of chronic rather than acute environmental stress. 73

77 Table 7.2. Core indicators for seafood safety in the Baltic Sea. The safety limits are taken from EC Regulation 1881/2006 (Anon. 2006). Seafood core indicators Safety limit, representing the GES boundary Polychlorinated biphenyls and dioxins and furans Dioxins and furans: 4 ng kg -1 WHO-TEQ ww muscle Polychlorinated biphenyls (dioxin-like) and dioxins and furans: 8 ng kg -1 WHO-TEQ ww fish muscle; eel: 12 ng kg -1 WHO-TEQ ww. Non-dioxin-like PCBs: 75 μg kg -1 ww muscle; eel 300 μg kg -1 ww; fish liver 200 μg kg -1 ww. Polyaromatic hydrocarbons Benzo[a]pyrene in fish muscle - 2 μg kg -1 ww; crustaceans - 5 μg kg -1 ww; bivalves - 10 μg kg -1 ww. Mercury Fish muscle and crustaceans: 500 μg kg -1 ww; eel, pike and sturgeon: 1,000 μg kg -1 ww; mussel: 2,500 μg kg -1 dw. Cadmium Fish muscle and crustaceans: 50 μg kg - 1 ww; eel: 100 μg kg -1 ww; bivalves: 1,000 μg kg -1 ww. Lead Fish muscle: 300 μg kg -1 ww; crustaceans: 500 μg kg -1 ww; bivalves: 1,500 μg kg -1 ww. Reproductive disorders Reproductive disorders are measured by counting malformed larvae in brood-bearing amphipods or eelpout (Zoarces viviparus) - a fish species giving birth to fully-developed young. The indicator is sensitive to general and point-source pollution from a wide array of contaminants, and thus serves as an indicator for reduced reproductive potential in a contaminated ecosystem, particularly in benthic habitats. The BSAP ecological objective for the seafood safe to eat and the respective GES Descriptor 9 could be measured using the same biota sampled for the purpose of core indicators for the concentrations of hazardous substances in the environment (see Section 5.4.3). GES boundaries for Descriptor 9 are specific targets for human health. As the CORESET expert group had only limited expertise in food safety, the seafood core indicators are only presented provisionally. Table 7.2 presents those core indicators which have safety limits for human consumption under EU legislation. Seafood safety can also be assessed by other safety limits, which are not based on legislation but on research by the European Food Safety Agency, for example. The next step with the seafood core indicators is to identify other safety limits, which can be applied to the selected core indicators (Table 7.1). 7.2 Candidate indicators for hazardous substances The expert group for hazardous substances core indicators withheld a decision to categorise these four indicators as core or supplementary indicators: alkylphenols, vitellogenin induction, Acetylcholin-esterase (AChE) inhibition and EROD/ CYP1A induction (Table 7.3). The group considered the alkylphenols (nonylphenol and octylphenol) a substance group which may potentially have serious impacts in the Baltic environment. The recent HELCOM thematic assessment found high levels of it in sediment (HELCOM 2010 a). Nonylphenol and octylphenol have been listed in the BSAP and the Priority Substance Directive (Anon b). The three indicators for biological effects of hazardous substances vitellogenin induction, AChE inhibition and EROD/CYP1A induction are potentially good indicators for anthropogenic stress. Vitellogenin induction measures the exposure to estrogenic contaminants; AChE inhibition measures the neurotoxic effects; and EROD/ CYP1A induction is sensitive to PAHs, planar PCBs and dioxins. More information is given in the indicator descriptions in Part B of this report (HELCOM 2012 a). 74

78 Table 7.3. Candidate indicators for hazardous substances in the Baltic Sea. Candidate indicators Alkylphenols (nonylphenol and octylphenol) Vitellogenin induction Acetylcholin-esterase inhibition EROD/CYP1A (Ethoxyresorufin-O-deethylase) induction Possible GES boundary and other information EQS for water and QS for biota and sediment. Not established. BACs and EACs under development for Mytilus spp., Macoma balthica, herring, flounder, eelpout and perch. Established BAC for male flounder and eel. Herring BAC and EACs under development. The next steps in the process of validating the candidate indicators as core indicators are to (1) assess their importance in describing the state of the environment in the Baltic Sea, also in their relation to contaminants, (2) develop or validate GES boundaries for them and (3) produce background documentation. In addition to the candidate indicators in Table 7.3, the expert group also discussed the need for an indicator to follow the inputs of hazardous substances to the Baltic Sea. The inputs of lead, mercury and cadmium and, to a lesser extent, nickel, copper and zinc are being monitored by HELCOM Contracting States (e.g. HELCOM 2011). These indicators would show the inputs behind the concentrations found in water, sediment and biota. Thus, they also show the management success in the reduction of releases of heavy metals. However, as there are no targets agreed on these inputs, the trend-based GES targets should be used until the modelling of maximum allowable inputs has been carried out. The inclusion of POPs in this indicator is not yet seen as possible due to very large gaps in the monitoring. Several supplementary indicators that measure the inputs of hazardous substances from different sectors are presented in Section Supplementary indicators for hazardous substances The supplementary indicators for the assessment of hazardous substances are organochlorine pesticides (represented by DDTs, HCHs and HCB), copper and zinc (Table 7.4). In the recent HELCOM thematic assessment (HELCOM 2010 a), DDE (degradation product of DDT) was found at high levels in many sites, whereas HCHs and HCB did not exceed the EU quality standards. As the organochlorine pesticides are banned or strictly managed in the Baltic Sea catchment area and their concentrations are decreasing, the expert group decided to categorise them as supplementary indicators, keeping in mind that their concentrations should be followed regularly in the Baltic Sea. Copper and zinc were recognised as subregionally significant indicators of the state of the environment. Their levels have been increasing in some areas of the Baltic Sea, reflecting changes in their use. These indicators do not have any proposed GES boundaries but temporal trends in biota, sediment and water, and thus should be followed regularly. Table 7.4. Supplementary indicators for hazardous substances in the Baltic Sea. Supplementary indicators Parameters Possible GES boundaries Organochlorine pesticides DDTs, Hexachlorocyclohexanes (HCHs, incl. lindane), hexachloro benzene (HCB) EAC for DDT total in sediment. EAC for DDE in mussel and sediment. EQS for lindane in water and specific QS in sediment and biota. EQS for HCB in biota and QS for water and sediment. Copper Copper (Cu) N.A. Trend-based approach suggested. Zinc Zinc (Zn) N.A. Trend-based approach suggested. 75

79 8 Eutrophication core indicators and targets 76 The HELCOM demonstration set of eutrophication core indicators was presented in the HELCOM Moscow Ministerial Meeting in There are six operational eutrophication core indicators, which are also integrated by the assessment tool HEAT (HELCOM 2009 a). The preliminary core set indicators for eutrophication and the integrated assessment are shown on the HELCOM website: The preliminary core indicators for eutrophication have been developed by intersessional work under HELCOM MONAS and are based on the work of HELCOM EUTRO and EUTRO-PRO. The HELCOM eutrophication core indicators have aimed at quantitative assessments (GES boundaries

80 presented on the HELCOM website); qualitative descriptions of GES are also given in Annex 2 of this report. 8.1 Eutrophication core indicators The eutrophication of the Baltic Sea can be currently assessed by six core indicators: water transparency (Secchi depth); dissolved inorganic nitrogen (DIN); dissolved inorganic phosphorus (DIP); chlorophyll a; multimetric benthic invertebrate community indices; and macrophyte depth distribution. All the core indicators except for the macrophyte indicator are operational and the results are available on the HELCOM website 10. The macrophyte indicator is partly operational but the compilation of data and GES boundaries has not yet been finalised (see Section 6.1.1). The six core indicators measure the causative factors of eutrophication (nutrient levels); the direct effects of the nutrient enrichment (chlorophyll a, water transparency); and the indirect effects of nutrient enrichment (benthic communities and macrophyte depth distribution) (Table 8.1). The six core indicators cover four of the five BSAP ecological objectives; only the objective for oxygen concentration is not covered by the core indicators. The core indicators cover all three GES criteria of the MSFD GES Descriptor 5 (Table 8.1). 8.2 Eutrophication indicators under development The eutrophication experts have also identified and developed other indicators that can be used to assess the direct or indirect effects of nutrient enrichment (Table 8.1). The candidate indicators for direct effects include three indicators that measure the ratios of species sensitive and insensitive to eutrophication, and an indicator to follow Table 8.1. The core indicators to assess eutrophication organised under GES criteria and GES indicators (Anon. 2010). Indicators under development are also shown. GES criteria GES indicators Core indicators Indicators under development 5.1 Nutrient levels Nutrients concentration in the water column. DIN concentration. DIP concentration Nutrient ratios (silica, nitrogen and phosphorus), where appropriate. 5.2 Direct effect of nutrient enrichment. 5.3 Indirect effects of nutrient enrichment Chlorophyll concentration in the water column Water transparency related to increase in suspended algae, where relevant Abundance of opportunistic macroalgae Species shift in floristic composition such as diatom to flagellate ratio; benthic to pelagic shifts; as well as bloom events of nuisance/toxic algal blooms (e.g. cyanobacteria) caused by human activities (5.2.4) Abundance of perennial seaweeds and seagrasses (e.g. fucoids, eelgrass and Neptune grass) adversely impacted by the decrease in water transparency Dissolved oxygen, i.e. changes due to increased organic matter decomposition and size of the area concerned. Chlorophyll a. Water transparency. Biomass ratio of opportunistic and perennial macroalgae Cladophora length. Ratio of diatoms and dinoflagellates. Ratio of autotrophic and heterotrophic organisms. Frequency and coverage of cyanobacterial blooms. Lower depth distribution limit of sensitive macrophyte species Multimetric benthic invertebrate community indices. Oxygen deficiency /BSAP_assessment/eutro/HEAT/en_GB/status/ 77

81 the frequency and coverage of cyanobacterial blooms. All of these, except the indicator for the ratio of perennial and opportunistic macroalgae (see Section 6.2.1), are currently listed as supplementary indicators (see Section 6.3.1). The oxygen deficiency indicator is a candidate indicator for indirect effects and its operationalisation will be implemented in the near future. In offshore areas, it could follow the methodology of the HELCOM TARGREV project (HELCOM 2012 c), while in coastal areas, a recent methodological study by Conley et al. (2011) could be used. In addition, the HELCOM CORESET expert group on biodiversity indicators identified candidate indicators which can be used to assess the effects of eutrophication (see Section 6.2.1). The HELCOM TARGREV project (HELCOM 2012 c) has studied the GES boundaries for the eutrophication core indicators and has also provided expert advice on their validity. The results of the project will be evaluated by the HELCOM eutrophication experts, possibly leading to the re-evaluation of the GES boundaries. 8.3 Assessment scales for eutrophication core indicators The expert group for eutrophication core indicators decided that eutrophication core indicators should be assessed in coastal waters by WFD water types, and in offshore waters by 19 sub-basins. Offshore assessments of the indicators will be made at the sub-basin level (the division used in the recent eutrophication assessment, HELCOM 2009 a). HELCOM HOD 35/2011 endorsed these provisional assessment units for the core eutrophication indicators. As the national water quality assessments under the EU WFD are carried out at the waterbody scale - a unit smaller than water type - this scale must also be heeded in the HELCOM assessment of eutrophication. 78

82 9 Monitoring needs for the proposed core indicators 9.1 Existing COMBINE monitoring for the proposed core indicators The HELCOM COMBINE is a joint programme of all the Contracting States linking nationally monitored parameters in a commonly agreed way. It includes parameters targeted to measure the state and impacts of hazardous substances and eutrophication. There is no monitoring specifically aimed at biodiversity assessments; however, some parameters measuring effects of eutrophication can also be used for the biodiversity core indicators. The biological parameters include: phytoplankton species composition, chlorophyll a and biomass; 79

83 zooplankton species composition, abundance and biomass; macrozoobenthic invertebrate species composition, abundance and biomass; and phytobenthic species composition and depth distribution. The COMBINE parameters for hazardous substances are: mercury, lead, cadmium, copper and zinc; and DDTs, PCBs, HCB and HCHs. The COMBINE parameters for eutrophication are: nitrogen, phosphorus and silicate; water transparency (Secchi depth); and oxygen concentration and hydrogen sulphide. In addition, the COMBINE includes the monitoring of salinity, temperature and current speed and direction. 9.2 Other monitoring for the proposed core indicators The HELCOM Contracting States also monitor parameters which have not been included in the COMBINE programme. The HELCOM FISH-PRO project has continued the monitoring of coastal fish communities since the 1990s, while HELCOM EG SEAL coordinates the monitoring of marine mammals in the Baltic Sea. Although waterbirds are not currently monitored by a joint programme, HELCOM has agreed on joint guidelines to monitor them. The HELCOM EG for cormorants focuses on compiling Baltic-wide data and other information on them. These parameters may have varying sampling methods and analyses, and thus their suitability for common assessments need to be evaluated. Such an evaluation will take place during the next revision of the HELCOM COMBINE. An overview of the existing monitoring of biological parameters that forms the base of the core indicators is given below. Information on specific parameters measured in the Baltic Sea area has also been collected. Some initial consideration as regards future monitoring has been added to the table. Table 9.1. A Summary of biodiversity-related monitoring programmes in the Baltic Sea area. Proposed core indicators: Monitoring programmes Proposed changes to monitoring Mammals Blubber thickness FIN, GER, POL, SWE The sampling and analysis methods have been partly harmonized as a result of expert-level co-operation. They should be formalized as HELCOM manuals. Pregnancy rates FIN, GER, POL, SWE As above Population growth rate EST, FIN, GER, SWE, POL, DEN As above Birds White-tailed eagle productivity All countries Harmonization of methods needed Abundance of wintering populations FIN, GER, LIT, POL, SWE, RUS? Harmonization of methods needed of seabirds Costal fish Fish abundance index Fish size index Fish species demographic index Fish species diversity index Fish community trophic index Seabed All countries. Harmonized monitoring and assessment, collected using fishery independent coastal fish sampling with passive gears, are conducted by Estonia, Finland, Latvia, Lithuania, and Sweden. Harmonization of methods needed. Formalized HELCOM manuals. If proven to serve the needs of assessing biodiversity, additional data such as commercial catch statistics collected within the EU s data collecting framework might be used. Multimetric macozoobenthos indicators Lower depth distribution limit of macrophyte species Pelagial All countries, except RUS All countries, except RUS Harmonization of methods needed Harmonization of methods needed 80 Non-indegenous species: Trends in arrival of new species All countries Targeted screenings in ports

84 Table 9.1 continues Candidate indicators: Monitoring programmes Proposed changes to monitoring Mammals: Distribution of harbour porpoise By-catch of seals and harbour porpoise Fatty-acid composition of seals as measure of food intake composition (D4, new proposal of BD3) Birds: Abundance of breeding populations of seabirds Fish: Salmon smolt production capacity Sea trout parr density Fish indicators using fishery-based data Seabed: DEN, GER, LIT, HELCOM/ ASCOBANS database, SAMBAH project No monitoring No monitoring FIN, GER, SWE, DEN? All countries All countries All countries Regular assessments on densities New monitoring scheme needs to be considered New monitoring scheme needs to be considered Harmonization of methods Ratio of perennial and annual macrophytes EST, DEN, GER, POL Consider to include as parameters in existing monitoring of macrophytes Cladophora length - Consider to include as parameters in existing monitoring of macrophytes Blue mussel cover - New monitoring scheme needs to be considered Population structure of long-lived species Pelagial: All countries, if biomass/abundance ratio can be used. Harmonization of methods Biomass of copepods All countries Zooplankton to be considered as core variable in HELCOM COMBINE Biomass of microphageous mesozooplankton All countries As above Zooplankton diversity index All countries Zooplankton to be considered as core variable in HELCOM COMBINE Phytoplankton diversity or eveness All countries As above Mean zooplankton size (D4, new All countries As above proposal of BD3) Zooplankton:phytoplankton (D4 new proposal of BD3) All countries As above Seasonal succession of functional phytoplankton groups Ferry-line datasets: most subbasins As above Supporting indicators: Monitoring programmes Proposed changes to monitoring Biopollution index All countries Targeted screenings in ports. Diatom:dinoflagellate ratio All countries Zooplankton to be considered as core variable in HELCOM COMBINE Ratio autotrophs: heterotrophs All countries As above Cyanobacterial blooms Remote sensing Harmonization of remote sensing results Abundance of particularly invasive species All countries 81

85 Table 9.2. Monitoring of the proposed core indicators for hazardous substances by the HELCOM Contracting States in biota, sediment and water. Contracting States in parentheses means that only projectbased data exist. Core indicator / substance Biota Sediment Water Polybrominated diphenylethers Hexabromocyclododecane Polychlorinated biphenyls and dioxins Perfluorooctane sulphonate Polyaromatic hydrocarbons Countries Species Countries Countries DEN, FIN, GER, SWE (EST, LAT, LIT, POL) DEN, FIN, SWE (EST, LAT, LIT, POL) DEN, EST, FIN, GER, LIT, POL, SWE (LAT) (DEN, EST,GER, LAT, LIT, POL, SWE) DEN, GER, SWE (FIN, LIT, POL) eelpout, flounder, herring, cod, dab, perch, guillemot herring, cod, guillemot, perch, flounder various species various species mussels, fish (metabolites) FIN, (LIT), SWE FIN, SWE, (LIT) FIN, GER, LIT, POL, RUS, SWE (DEN, FIN, GER, SWE) FIN, LIT, SWE, (RUS) Metals All countries various species All? N.A: Tributyl tin and imposex DEN, FIN, GER, SWE (EST,LAT, LIT, POL) herring, flounder, perch, mussel, snails DEN, FIN, LIT, SWE (LAT, POL) LIT, (EST, LAT) (EST, LAT, LIT, POL) GER, LIT (DEN, FIN, GER, LIT SWE) LIT, (RUS) DEN, GER, LIT Pharmaceuticals only screening only screening only screening Cesium-137 All countries herring, flounder, plaice N.A. All? Lysosomal membrane stability DEN, (FIN, GER, SWE) eelpout, flounder, herring, perch, amphipods, blue mussels Genotoxicity MN (LIT, POL, RUS, SWE) cod, dab, eelpout, flounder, herring, perch, blue mussel, Macoma balthica N.R. N.R. Fish diseases GER, POL, RUS (LIT) cod, flounder N.R. N.R. Reproductive disorders DEN, SWE (GER, RUS) N.R. N.R. eelpout, amphipods N.R. N.R Identified gaps in the Baltic monitoring The CORESET project identified gaps in the current availability of data for the proposed core indicators. For the biodiversity core indicators, the following remarks can be made: Marine mammal core indicators are monitored in the countries where the major parts of the populations occur. Monitoring the harbour porpoise in the Baltic Proper is based on a project only. Seabird monitoring may be adequate in coastal areas, whereas it needs to be strengthened in offshore areas; a minimum five-year monitoring cycle is required to observe changes over time. Fish core indicators are currently described only for a specific coastal fish sampling scheme used in the HELCOM FISH-PRO project (HELCOM 2012 b). Monitoring coastal fish by this method covers some parts of the Baltic coastal zone, with the exception of Russian, German and Danish waters. There are also other sources of data available, even though they have not been tested by the project to date. There are large datasets from research surveys available for the offshore areas, ICES estimates on stocks, national estimates on stocks and fishery data. The project considered that there will be data available for fish indicators once they have been finalised. Benthic macrophytes and macroinvertebrates are monitored in the Baltic Sea, but current monitoring for the EU Water Framework Directive is focused on coastal waters. Zooplankton monitoring is relatively adequate for the proposed indicators, which is mainly targeted to offshore areas. Phytoplankton indicators, which are currently in the testing phase, seem to be dependent on frequent monitoring, such as on ship-of-opportunity sampling. Non-indigenous species are followed through various monitoring programmes, screenings and projects mainly focused on harbour areas and along intensive shipping routes at regular intervals.

86 For hazardous substances, a general remark was made during the project that the sampling methods need to be harmonised, and that and cost-efficiency should be considered when sampling for food safety and environmental authorities. The following more specific remarks were made: PBDE, HBCD and PFOS monitoring does not adequately cover the Baltic Sea marine area. PCBs and dioxins/furans are monitored covering the entire Baltic Sea area. PAHs are monitored in about half of the HELCOM Contracting States, but the monitoring lacks a joint view of the parameters and matrices. Metals cadmium, mercury and lead are being monitored covering the entire Baltic Sea area. Cesium-137 is being monitored adequately in the Baltic Sea. TBT monitoring is not done coherently, but biased to harbours. The pharmaceutical substances diclofenac and EE2 are not monitored anywhere; screenings are carried out in some countries, which shows the need for more frequent monitoring. Core indicators for the biological effects of hazardous substances are only monitored in few areas even though they would provide information of point-source pollution in the vicinity of cities, and also reflect the general degradation of the marine environment. 9.4 Existing monitoring and the selection of core indicators The availability of monitoring from all the Contracting States is one of the common principles for the HELCOM core indicators (Table 2.1). As discussed in Chapter 5, it was possible to disregard this principle in the selection process if a proposal for new monitoring (or a modification of the existing) was proposed. The rationale behind this exception followed the discussion in HELCOM that the revision of the HELCOM joint monitoring requires a study of the core indicators before the revision process can begin. At this stage of the project, most proposals for new or adapted monitoring are incomplete and the finalised proposals may even require a separate process. Nevertheless, several core indicators or candidate indicators were identified which lack proper monitoring data but were nevertheless seen as essential indicators for marine environmental assessments. During its second phase, the CORESET project will continue to develop the identified indicators and draft the proposals for the new or adapted monitoring. 83

87 10 Conclusions 84 The HELCOM CORESET project has made considerable progress in developing a set of indicators to address hazardous substances and biodiversity. In particular, the project has developed a pressure-based approach for the selection of indicators which is in line with MSFD guidelines, and which also renders the indicators suitable for the follow-up of the management measures. This means that while the indicators are mainly related to the state of biodiversity, they respond to human pressures and are thereby linked to the impacts of human activities. In future, a better coverage of pressures and impacts should be envisaged through indicators, in particular where GES is more appropriately tackled through pressure and impact targets than state targets. This

88 would ensure a sufficient link between state and pressure, and enable an assessment of the effectiveness of the measures. CORESET should be revisited to ensure that all aspects of MSFD Descriptors 1-11 are sufficiently covered in order to deliver future ecosystem-based assessments and the evaluation of the progress made towards GES, and to ensure synergies of the indicators across the descriptors. The following results can be highlighted as regards the working process of the biodiversity group: In accordance with the GES criteria document (Anon. 2010), the project has identified a set of predominant habitats, functional groups, and key species in the Baltic Sea. The lists are intended to facilitate the identification of suitable indicators as well as to cross-check that the monitoring efforts cover key components of the Baltic Sea s ecosystem. The lists are living documents that will be further developed. In accordance with the GES criteria document (Anon. 2010) and several guiding documents for the MSFD process (e.g. the EU TG1 report on biodiversity, ICES WGECO 2010 report), the project has assessed the impacts of anthropogenic pressures on Baltic Sea functional groups and habitats as a starting point for indicator selection. This has been based on expert judgements using relatively simple criteria. To increase the reliability in the assessment of impacts, the evidence base should be improved as well as the procedures for expert judgement, including a representative participation of experts. In order to facilitate the development of indicators, information on current monitoring of biological parameters has been compiled which can be used during the revision process of the Baltic Sea monitoring programmes. The proposed set of core indicators was not aimed to include indicators for every functional group or habitat; rather it has been developed into a set of focused indicators avoiding redundancy and omitting indicators with weak evidence of response to human activities. However, the set of core indicators lacks some key functional groups, species and habitats that should be represented in an environmental assessment of the Baltic Sea, such as zooplankton, phytoplankton, harbour porpoise and benthic fauna on hard substrata. These gaps were considered significant and thus candidate indicators have been proposed and presented in this report for each of them. The set of core indicators is considered to cover the HELCOM BSAP ecological objectives well, whereas some GES criteria of the EC decision document (Anon. 2010) are not covered. The spatial distribution of habitats (criterion 1.4) and physical damage to seafloor (criterion 6.1) are not addressed by any core indicator; further, the abundance or distribution of key trophic groups and species (criterion 4.3) are only partly covered by the core indicators. The proposed indicators under Descriptor 4 are duplicated under Descriptor 1 while the project did not propose a specific indicator for food webs. The HELCOM principles for the core indicators and guidance during the CORESET process aimed to develop the core indicators as stand-alone indicators which can be used to assess the state of the marine environment. They were also developed to be used in integrated assessments, where they each assess the state of a part of the ecosystem. The HELCOM assessment tools that were used in the thematic assessments of eutrophication, hazardous substances and biodiversity (HELCOM 2009 a, b, 2010 a), and the HELCOM Initial Holistic Assessment (HELCOM 2010 b) are tools that are able to integrate the core indicators. The tools will be adjusted to apply to the assessment requirements of the MSFD. The applicability of the core indicators depends on the availability of data. All the core indicators have at least some data to support them - data that was also used to propose GES boundaries; however, for several core indicators, the spatial and temporal design of the monitoring programmes need to be improved to ensure Baltic Sea-wide data coverage. For some indicators, no or little monitoring has taken place in the past and it will take some years to build up time series that allow the evaluation of changes in status over time. One of the secondary objectives of the CORESET project was to identify these gaps in the monitoring programmes and, hence, facilitate the revision of the HELCOM monitoring programmes. Recommendations for data requirements for each core indicator have been suggested in the respective descriptions in Part B of this report (HELCOM 2012 a). Often, the regional gaps in data availability have resulted in gaps in the setting of GES boundaries, or validating 85

89 the existing GES boundaries in the area. However, the project also acknowledges financial restrictions in monitoring and gives proposals for the frequency of monitoring. For example, it is noted that the development of new core indicators does not necessarily lead to new monitoring; monitoring can be adjusted to include other parameters and can be performed over longer time intervals. As the CORESET project was not able to finalise or even test all the indicators and GES boundaries by September 2011, it was proposed that the development work of the core indicators will continue to: operationalise the core indicators (i.e. make them applicable for assessment); develop and validate sub-regional GES boundaries; produce detailed guidance documents on how to compute and use the indicators and carry out the assessment; further develop candidate indicators (many of which would fill significant gaps); and ensure data flows to maintain the regional core indicator assessments. The proposed core indicators in this report should thus be considered as provisional until further developed in the continued CORESET process. The project concludes that the development work of the core indicators is typically learning-bydoing, where some indicators, for example, were identified rather easily from existing data sets, while for others the development required much more work than anticipated. Some potential indicators, for instance, were temporarily set aside as candidate indicators because of unexpected difficulties in defining GES boundaries. The project also acknowledged that the GES boundaries for the core indicators depend on prevailing climatic conditions and may require regular revision. In addition, as the scientific basis for setting several of the GES boundaries should be enhanced, all the proposed GES boundaries should be considered as tentative and open for future revision. The proposed set of core indicators is based on the existing anthropogenic pressures and the current understanding of their impacts on the Baltic Sea ecosystem. The future activities and their impacts may result in the need to add new or revise the current core indicators. Such an adaptive management is the prerequisite for all environmental assessments. The vision of a healthy Baltic Sea in the Baltic Sea Action Plan is being assessed regularly as it heads towards 2021; further, the six-year reporting rounds of the Marine Strategy Framework Directive each require an assessment of the state of the marine environment. The regular assessment needs to ensure a comparability of the assessment results over longer time periods, but they also open up possibilities to revisit the indicator selection and the level of GES boundaries. The HELCOM core indicators will be publicly presented on the HELCOM website. Regular updates of assessment results will also ensure a good possibility to follow the state of the environment and review the methodology and data behind the assessments. 86

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92 ICES (2011 a): ICES WGIAB report Report of the ICES/HELCOM Working Group on Integrated Assessments of the Baltic Sea (WGIAB). Available at: reports/ssgrsp/2011/wgiab11.pdf. ICES (2011 b): ICES WGBAST report Report of the Baltic Salmon and Trout Assessment Working Group (WGBAST). Available at: WGBAST/wgbast_2011_final.pdf. Olenin, S., Alemany, F., Cardoso, A.C., Gollasch, S., Goulletquer, P., Lehtiniemi, M. et al. (2010). MSFD Task Group 2 Report. Non-indigenous species. European Commission Joint Research Center and ICES. Available at: Österblom, H., Casini, M., Olsson, O. & Bignert, A. (2006): Fish, Seabirds and trophic cascades in the Baltic Sea. Marine Ecology Progress Series 323: Paine RT (1969) A note on trophic complexity and species diversity. Am Nat 103: Piraino, S., G. Fanelli, F. Boero (2002) Variability of species roles in marine communities: change of paradigms for conservation priorities. Marine Biology 140: Power, M.E., Tilman, D., Estes, J.A., Menge, B.A., Bond, W.J., Scott Mills, L., Daily, G., Castilla, J.C., Lubchenco, J., Paine, R.T. (1996) Challenges in the quest for keystones. Bio- Science 46: Rice, J., Arvanitidis, C., Borja, A., Frid, C., Hiddink, J., Krause, J., Lorance, P. et al. (2010). MSFD. Task Group 6 Report, Seafloor integrity. European Commission Joint Research Center and ICES. Available at: Rogers, S., Casini, M., Cury, P., Heath, M., Irigoien, X., Kuosa, H. et al. (2010) MSFD, Task Group 4 Report, Food webs. European Commission Joint Research Center and ICES. Available at: Villnäs, A. & Norkko, A. (2011): Benthic diversity gradients and shifting baselines: implications for assessing environmental status. Ecological Applications 21: Zettler, M.L., Schiedek, D., Bobertz, B. 2007: Benthic biodiversity indices versus salinity gradient in the southern Baltic Sea. Marine Pollution Bulletin 55:

93 12 Glossary 90 Biological diversity (biodiversity): The variability among living organisms from all sources including, inter alia, terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part; this includes diversity within species, between species and of ecosystems (as used by the Convention on Biological diversity, 1992). Biotope: A habitat and its associated community. Candidate indicators: Indicators discussed in the CORESET project that are considered promising but do not fulfil the selection criteria for core indicators, e.g. in terms of monitoring, or those that require further validation of the GES boundaries. Community: The collection of organisms found at a specific place and time (McCune et al, Analysis of ecological communities 2002). Core indicators: Indicators considered in the HELCOM CORESET project that fulfil the criteria used for indicator selection; and the validation of indicators and proposed GES boundaries that are considered sufficient. Criteria: As used in the Commission s decision on criteria and methodological stands on good environmental status of marine waters (Anon. 2010), criteria refers to an aspect of biodiversity that is used to assess its state and which can be assessed by one or more indicators. Descriptor: MSFD Annex I provides a list of 11 qualitative descriptors which build the basis for the description and determination of GES. The descriptors will be substantiated and specified with the GES criteria of EC decision 2010/477/EU. Ecosystem function: The characteristic exchanges within an ecosystem including energy and nutrient exchanges, decomposition and the production of biomass. Ecosystem health: An ecological system is healthy if it is stable and sustainable, i.e. maintaining its organisation and autonomy over time, and its resilience to stress (Rapport D.J., Costanza, R., McMichael, A.J Assessing ecosystem health). Ecosystem processes: The mechanistic processes, such as decomposition and resource use, that regulate ecosysystem functions. Ecosystem structure: The distribution and composition of species, communities and habitats, and the quantity and distribution of abiotic components. Favourable conservation status (FCS): According to the Habitat Directive (92/43/EEC), conservation status of a natural habitat means the sum of the influences acting on a natural habitat and its typical species that may affect its long-term natural distribution, structure and functions, as well as the longterm survival of its typical species. The conservation status of a natural habitat will be taken as favourable when: - its natural range and areas it covers within the range are stable or increasing; and - the specific structure and functions that are necessary for its long-term maintenance exist, and are likely to continue to exist for the foreseeable future; and - the conservation status of its typical species is favourable. The conservation status of a species means the sum of the influences acting on the species concerned that may affect the long-term distribution and abundance of its populations. The conservation status will be taken as favourable when: - the population dynamics data on the species concerned indicate that it is maintaining itself on a long-term basis as a viable component of its natural habitats; and - the natural range of the species is neither being reduced nor is likely to be reduced for the foreseeable future; and - there is and will probably continue to be a sufficiently large habitat to maintain its populations on a long-term basis. Functional Group; Generally (Wikipedia): In ecology, functional groups are collections of organisms based on morphological, physiological, behavioural, biochemical, environmental responses or on trophic criteria. In MSFD Descriptor 1: In the Task Group 1 report (Cochrane et al. 2010), species groups are called ecotypes or ecological grouping which apply for mobile species such as mammals, birds and fish. The division of ecotypes is given but not justified.

94 In MSFD Descriptor 4: A group of organisms that use the same type of prey (Rogers et al 2010). Good Environmental status (GES): According to the MSFD, Member States should achieve or maintain GES in the marine environment by According to Article 3.5 of the MSFD, GES is defined as: The environmental status of marine waters where these provide ecologically diverse and dynamic oceans and seas which are clean, healthy and productive within their intrinsic conditions, and the use of the marine environment is at a level that is sustainable, thus safeguarding the potential for uses and activities by current and future generations and so forth. Furthermore, GES for biodiversity should be defined according to criteria outlined in document (2010/477/ EU). Habitat: The physical and environmental conditions (e.g. the seabed substratum and associated hydrological and chemical condition) that support a particular biological community or communities (Cochrane et al. 2010). Indicator, state: State indicators give a description of the quantity and quality of physical, biological or chemical phenomena in a certain area. The state of biodiversity can be assessed through, e.g. the abundance, condition, composition and distribution of species and habitats (EEA definition). Indicator, pressure: Pressure indicators describe the release of anthropogenic substances, physical and biological agents, and the use of resources. They measure the factors that cause changes in the state of the environment through actions taken by humans, e.g. nutrient load, by-catch and introduction of non-indigenous species (EEA definition). Key species: Key species refers, in principle, to any species that is important to ecosystem structure and function in whatever form (e.g. biomass, abundance, productivity or functional role) driving ecosystem processes or energy flows (Piraino et al. 2002). Keystone species: A species whose effect on ecosystems is disproportionately large relative to its biomass in the community as a whole (Power et al. 1996). Thus, a keystone species is per definition not an abundant species. The term was originally coined for predators (Paine 1969) but has since become broadened and used for species at other trophic levels as well as ecosystem engineers (as recognised by, e.g. Power et al. 1996). Reference condition / state: A state or condition with no or very little anthropogenic disturbance. Reference condition or reference state is used as an anchor in environmental assessments when defining a baseline (see Target), against which the current state is compared. Reference condition / state is used predominantly in the EU WFD and also in the HELCOM HEAT and BEAT assessment tools. Target: According to Article 3.7 of the MSFD, an environmental target means a (qualitative or) quantitative statement on the desired condition of the different components of, and pressures and impacts on, marine waters. According to Annex IV, #3, an environmental target should reflect the desired condition based on the definition of good environmental status. The target should be measurable and associated indicators should be developed to allow for the follow-up of the implementation of the measures through monitoring and assessment. As used in HELCOM assessments, a Target is more specific and reflects the boundary between GES and sub-ges, sometimes called the baseline. In existing HELCOM assessments, the boundary has been based on a specific score (cf. ecological quality ratio, EQS, sensu WFD and also used in HEAT and BEAT) that has been derived through the use of an Acceptable deviation from a Reference condition. Trophic group: This refers to a category of organisms within a trophic structure, defined according to their mode of feeding (Rogers et al 2010). 91

95 Annex 1. Pressures impacting functional groups and predominant habitats The matrices were filled in by the HELCOM CORESET expert group for biodiversity indicators. Red denotes a significant negative impact; orange an intermediate negative impact; and yellow a low negative impact. Pressures are categorised according to the EU MSFD. Note that low impacts have mostly been left out of the summary tables. The working team for fish indicators made a separate pressure evaluation in the HELCOM thematic assessment of coastal fish communities (HELCOM 2012 b). Table 1. Marine mammals. Microbial pathogens Introductions of non-indigenous species and translocations Selective extraction of species, incl. non-target catches Introduction of non-synthetic compounds Introduction of radioactive substances Introduction of synthetic compounds Changes in salinity regime Changes in thermal regime Inputs of fertilizers Inputs of organic matter Marine litter Underwater noise and electromagnetic fields Abrasion Changes in siltation Selective extraction of non-living resources Sealing Smothering Toothed whales Population distribution Population size Population condition Seals Population distribution Population size Population condition 92

96 Table 2. Seabirds. Note that the definitions and names of functional groups have changed during the project. Microbial pathogens Introductions of non-indigenous species and translocations Selective extraction of species, incl. non-target catches Introduction of non-synthetic compounds Introduction of radioactive substances Introduction of synthetic compounds Changes in salinity regime Changes in thermal regime Inputs of fertilizers Inputs of organic matter Marine litter Noise Abrasion Changes in siltation Selective extraction of non-living resources Sealing Smothering Top predatory birds Species distribution Population size Population condition Subtidal benthic feeders Species distribution Population size Population condition Intertidal benthic feeders Species distribution Population size Population condition Inshore pelagic feeders Species distribution Population size Population condition Inshore surface feeders Species distribution Population size Population condition Offshore pelagic feeders Species distribution Population size Population condition Offshore surface feeders Species distribution Population size Population condition 93

97 Table 3. Pelagic (water column) habitats and associated communities. Microbial pathogens Introductions of non-indigenous species and translocations Selective extraction of species, including incidental non-target catches Introduction of non-synthetic compounds Introduction of radioactive substances Introduction of synthetic compounds Changes in salinity regime Changes in thermal regime Inputs of fertilizers Inputs of organic matter Marine litter Underwater noise and electromagnetic fields Abrasion Changes in siltation Selective extraction of non-living resources Sealing Smothering Zooplankton Estuarine waters Coastal waters Offshore above halocline Offshore below halocline Phytoplankton Estuarine waters Coastal waters Offshore above halocline Pelagic abiotic habitat Estuarine waters Coastal waters Offshore above halocline Offshore below halocline 94

98 Table 4. Benthic habitats and associated communities. Microbial pathogens Introductions of non-indigenous species and translocations Selective extraction of species, incl. non-target catches Introduction of non-synthetic compounds Introduction of radioactive substances Introduction of synthetic compounds Changes in salinity regime Changes in thermal regime Inputs of fertilizers Inputs of organic matter Marine litter Underwater noise and electromagnetic fields Abrasion Changes in siltation Selective extraction of non-living resources Sealing Smothering Hydrolittoral hard substrata Extent Condition of prennial macroalgae Condition of ephemeral macroalgae Condition of zoobenthos Condition of the abiotic habitat Hydrolittoral sediment Extent Condition of macrophytes Condition of zoobenthos Condition of abiotic habitat Infralittoral hard substrata Extent Condition of prennial macroalgae Condition of ephemeral macroalgae Condition of crustacean fauna Condition of mollusc fauna Condition of abiotic habitat Infralittoral sediment Extent Angiosperms and charophytes Perennial macrophytes Infauna Abiotic habitat 95

99 Table 4 continues Microbial pathogens Introductions of non-indigenous species and translocations Selective extraction of species, incl. non-target catches Introduction of non-synthetic compounds Introduction of radioactive substances Introduction of synthetic compounds Changes in salinity regime Changes in thermal regime Inputs of fertilizers Inputs of organic matter Marine litter Underwater noise and electromagnetic fields Abrasion Changes in siltation Selective extraction of non-living resources Sealing Smothering Circalittoral hard substrata Extent Condition of zoobenthos Condition of abiotic habitat Circalittoral sediment Extent Condition of zoobenthos Condition of abiotic habitat Hard substrata under halocline Extent Condition of zoobenthos Condition of abiotic habitat Sediment under halocline Extent Condition of zoobenthos Condition of abiotic habitat 96

100 Annex 2. Qualitative descriptions of GES Qualitative descriptions of Good Environmental Status (GES) of the core indicators and the criteria of the MSFD descriptors. The HELCOM CORESET expert groups were tasked by the Joint Advisory Board of the HELCOM CORESET and TARGREV Projects to develop qualitative in addition to quantitative descriptions for the GES boundaries of the core indicators. This table contains these descriptions and also GES descriptions for some candidate indicators which are close to being finalised (marked by italics). The descriptions were also developed for the criterion level in order to guide the work. These descriptions were primarily developed with the aim to facilitate the development of quantitative GES boundaries. GES criterion 1.1 Species distribution Suggestion for GES description The spatial distribution of populations is in line with physiographic, geographic and climate conditions. Previously lost distribution areas have been restored. Approach for setting the GES boundary Wintering seabirds: Comparison to a reference period in the early 1990s (IBA studies). Harbour porpoise: Based on historic distribution. Description of the GES boundary GES is met when the spatial distribution of wintering seabird populations does not decrease from the baseline level of the early 1990s. State indicator. GES is met when (Intermediate target:) there is an increase in the harbour porpoise distribution or (Ultimate target:) the distribution covers the Baltic Proper (density treshold> ind km 2 ) State indicator. 1.2 Population size 1.3 Population condition The population size of any naturally occurring species of the marine region does not deviate from the natural fluctuations of the population. The population should be in a condition of good health, ensuring the reproduction and long-term viability of the population. Marine mammals: Based on the theoretical analysis of biological constraints and empirical analyses of the growth rate of depleted populations. Wintering seabirds: Reference period. Species abundance index for coastal fish: Based on site-specific reference data. If the reference data are missing, trends in available data and expert judgements are used to assess the status. By-catch of harbour porpoise, seals and water birds: trendbased target. Blubber thickness of mammals: Based on the reference data of a healthy population of grey seals from by-caught and hunted before Pregnancy rate of mammals: Based on the reference data of healthy populations of grey seals in WT-eagle: Based on reference data from the pre-1950s. Species demographic index of coastal fish: Based on site-specific reference data. If the reference data are missing, trends in the available data and expert judgements are used to assess the status. Seals and toothed values: GES is met when the population growth rate of seals and harbour porpoise is close to the intrinsic growth rate of a population undisturbed by human pressures. State indicator. GES is met when the abundance of wintering populations of selected seabird species does not deviate from the state of or , depending on species, more than an acceptable deviation of X% (Definite GES boundary pending on the modelling studies on relations of the environmental targets for eutrophication). State indicator. GES is met when the abundance of a coastal fish species is at an appropriate level to support community functions - including food provisions and trophic state - is based on a reference data set that has been defined as representing GES (or sub-ges ); is defined as a value >X>; and is primarily site-specific. State indicator. The by-catch of harbour porpoise, seals, water birds and non-target fish species has been significantly reduced with the aim to reach by-catch rates close to zero. Pressure indicator. GES is met when the blubber thickness does not deviate from the natural fluctuations of a population defined as representing GES. State indicator. GES is met when the pregnancy rate of female grey seals does not deviate from the natural fluctuations of population defined as representing GES. State indicator. GES is met when the brood size of white-tailed eagle does not show symptoms of pollution effects or poor nutritional status. State indicator. GES is met when the population mean size of a coastal fish species is at an appropriate level to support community functions, including trophic state. It is given as the mean length >X > cm and is primarily site-specific. State indicator. 97

101 GES criterion 1.4 Habitat distribution 1.5 Habitat extent 1.6 Habitat condition 1.7 Eco system structure Suggestion for GES description The distribution of habitats, including habitat-forming species, in the marine region is in line with physiographic, geographic and climate conditions. Previously lost distribution areas have been restored. Habitat extent (areal extent and/or volume) is in line with the prevailing physiographic, geographic and climatic conditions; loss of extent is minimised but accommodates defined levels of sustainable use. The habitat defined by abiotic and biotic parameters is in a condition to be able to support its ecological functions and the diversity of its associated community. Food web elements and habitat extent and conditions guarantee the provision of ecosystem services. Approach for setting the GES boundary Lower depth distribution limit of macrophytes: Several approaches as used in the WFD: generally within natural fluctuations of what has been defined as a type specific reference conditions. Macrozoobenthic indices: Several approaches as used in the WFD. Community size index coastal fish: Based on site-specific reference data. If the reference data are missing, trends in available data and expert judgements are used to assess the status. Community diversity index coastal fish: As above. Community abundance index coastal fish: As above. Biomass of copepods (absolute or relative): GES is based on a reference data set that represents a time period when zooplanktivorous fish growth/condition and fish stocks were relatively high. Biomass of microphagous mesozooplankton (absolute or relative): GES is based on a reference data set that represents a time period when chlorophyll and water transparency complied with GES. Community trophic index coastal fish: Based on site-specific reference data. If the reference data are missing, trends in available data and expert judgements are used to assess the status. Description of the GES boundary GES is met when the lower depth distribution of macrophytes shows only slight signs of disturbance. State indicator. GES is met when the level of diversity and the abundance of invertebrate taxa is only slightly outside the range associated with the type-specific conditions. State indicator. GES is met when the size structure of the fish community is at an appropriate level to support community function, including food provision and resilience. It is given as individuals >X cm and is primarily site-specific. State indicator. GES is met when the diversity of the associated fish community is at an appropriate level to support community function and resilience; is based on the reference data series that has been defined as representing GES; is given as a unitless index value >X>; and is primarily site-specific. State indicator. GES is met when the abundance of cyprinids and piscovores is at an appropriate level to support the community functions and resilience, based on the reference data series that has been defined as representing GES; is given as abundance >X>; and is primarily site-specific. State indicator. GES is met when the copepod biomass is sufficient to support favourable feeding conditions for zooplanktivorous fish. A GES boundary is defined for each sub-basin of the Baltic Sea provided that monitoring data for the area are available. State indicator. GES is met when the biomass of microphagous mesozooplankton does not exceed levels typical for the Baltic Sea unaffected by eutrophication. A GES boundary is defined for each sub-basin and WFD coastal water types. State indicator. Also environmental targets under 5.1 and 5.2. GES is met when the trophic structure of the community is at an appropriate level to support the trophic state, and is based on the reference data series that has been defined as representing GES; is given mean trophic level >X>; and is primarily sitespecific. State indicator. 98

102 GES criterion 2.1 Abundance and characterisation of NIS Suggestion for GES description GES is met when there are no new anthropogenic introductions. Approach for setting the GES boundary N.A. Description of the GES boundary GES is met when the number of new NIS is zero during the assessment period. Pressure indicator. 2.2 Environmental impact of invasive NIS GES is met when further impacts from NIS are minimised, with the ultimate goal of no adverse alterations to the ecosystems. N.A. GES is met when further impacts from NIS are minimised, with the ultimate goal of no adverse alterations to the ecosystems during the assessment period. Pressure indicator. GES criterion 4.1 Productivity of key species trophic groups Suggestion for GES description Approach for setting the GES boundary Marine mammals: Based on the theoretical analysis of biological constraints and empirical analyses of the growth rate of depleted populations. WT-eagle: reference period. Description of the GES boundary Seals and toothed values: GES is met when the population growth rate of seals and harbour porpoise is close to the intrinsic growth rate of a population undisturbed by human pressures. State indicator. White-tailed eagle productivity (the mean number of nestlings out of all occupied nests) is at levels not being affected by hazardous substances, poor prey availability and human disturbance. State indicator. 4.2 Proportion of selected species at top 4.3 Abundance of key trophic groups/species The proportion of predatory species of adequate size is at a level enabling efficient top-down control of the food web. All trophic groups and key species of the marine food webs function in balance. Proportions of fish trophic groups: Based on site-specific reference data. If the reference data are missing, trends in available data and expert judgements are used to assess the status. Fish community trophic index: As above. Biomass of copepods: As under D1. Biomass of microphagous mesozooplankton: As under D1. Proportion of large pikeperch (XXcm), cod (XXcm), perch (XXcm) is XX% of the entire population in the assessment area. State indicator. Proportion of piscivorous fish, non-piscivorous fish and cyprinids are at levels ensuring natural proportions of these trophic groups in the food web in the assessment area. State indicator. [The abundance of wintering bird populations can also be used under 4.2] Fish community trophic index is >XX >. State indicator. Biomass of copepods: As under D1. Biomass of microphagous mesozooplankton: As under D1. 99

103 GES criterion 5.1 Nutrients levels Suggestion for GES description Concentrations of nutrients in the euphotic layer are in line with prevailing physiographic, geographic and climate conditions and not resulting in unacceptable direct or indirect effects of nutrient enrichment Approach for setting the GES boundary Nutrient concentrations: Reference periods and other methods used in WFD. Description of the GES boundary Winter concentrations of DIP, DIN in the 0-10 layer: Acceptable deviation from sub-region specific baseline conditions is < 50%. State indicator. Nutrient inputs: BSAP maximum allowable inputs. Sub-basin specific nutrient loads should be below the maximum allowable annual nutrient inputs for countries as specified in the HELCOM BSAP. Pressure indicator. In the summer-time Secchi depth, the acceptable deviation from sub-region specific baseline conditions is < 25%. State indicator. 5.2 Direct effect of enrichment Clear water and natural levels of algal blooms and growth, not resulting in unacceptable reduced water quality and other indirect effects. Secchi depth: Reference periods and other methods used in WFD. Chlorophyll a: Reference periods and other methods used in WFD. Ratio of opportunistic and perennial macroalgae: Low impacted areas? In the summer-time concentrations of chlorophyll a in the 0-10 m layer, the acceptable deviation from sub-region specific baseline conditions is < 50%. State indicator. Ratio of opportunistic and perennial macroalgae deviate from the sub-region/type specific baseline < XX%. State indicator. 5.3 Indirect effect of enrichment Natural proportions and distribution of plants and animals and no reduction of oxygen concentration. Macrozoobenthic indices: Several approaches in WFD As under D1, 1.6. GES criterion 6.1 Physical damage, substrate characteristics Suggestion for GES description Seabeds, particularly biogenic structures, are in favourable conservation status, providing habitats and resources for associated sessile and mobile species. Approach for setting the GES boundary Physical impacts: Ultimately, the biological effects of impacts; tentatively, a mean cumulative impact. Description of the GES boundary Significant cumulative impacts of physical anthropogenic disturbances on the benthic habitats do not cover more than 15% of the habitat area in the marine region. Pressure indicator. 6.2 Condition of benthic community The benthic community is in a condition to be able to support its ecological functions, species diversity and the abundance of species is in line with physiographic and climatic conditions. Macrozoobenthic indices: Several approaches in WFD. As under D1,

104 GES criterion 8.1 Concentration of contaminants 8.2 Effects of contaminants 9.1 Level, number and frequency of contaminants in seafood Suggestion for GES description Concentrations of contaminants in the most relevant matrix (biological tissue, sediment, water) are at levels not giving rise to pollution effects in sensitive marine organisms, and the health of top predators is safeguarded. Contaminants do not cause unacceptable biological effects at any level of food web, ensuring a healthy wildlife. Human health is not jeopardised by concentrations of contaminants in seafood. Approach for setting the GES boundary All GES boundaries are based on ecotoxicological effect levels and concentrations of POP substances in biota do not increase over time. All GES boundaries are based on the threshold levels of biological effects indicative at different biological levels in relevant important species of the BS ecosystem. All GES boundaries are based on average daily doses, and the effect levels on human health. Description of the GES boundary Concentrations of Priority Substances are below Environmental Quality Standards or respective specific Quality Standard. State indicator. Concentrations of other selected hazardous substances are below other thresholds used by marine conventions (Environmental Assessment Criteria, Background Assessment Criteria or similar). State indicator. Concentrations of persistent organic pollutants in biota do not increase over time. State indicator. The biological effects are below the defined Environmental Assessment Criteria levels for Baltic Sea organisms to assess biological effects. State indicator. The safety levels of EC Regulation 1881/2006 and other food safety legislation have not been exceeded. State indicator. Acknowledged persons contributing to this report: Alexander Antsulevich, Magnus Appelberg, Eero Aro, Britt-Marie Bäcklin, Ulrik Berggreen, Anders Bignert, Mats Blomqvist, Elin Boalt, Maria Boethling, Edgars Bojars, Paulina Brzeska, Anna Brzozowska, Martynas Bučas, David Connor, Darius Daunys, Lars Edler, Ylva Engwall, Vivi Fleming-Lehtinen, Karin Fuerhaupter, Anders Galatius, Anna Gårdmark, Galina Garnaga, Henrik Gislason, Elena Gorokhova, Martin Green, Norman Green, Michael Haarich, Anja Hallikainen, Tero Härkönen, Jenny Hedman, Outi Heikinheimo, Anda Ikauniece, Marie Johansen, Kestutis Joksas, Ulrike Kammann, Kaarina Kauhala, Britta Knefelkamp, Wojchiec Krasniewski, Maria Laamanen, Martin M. Larsen, Maiju Lehtiniemi, Kari Lehtonen, Adam Lejk, Jurate Lesutiene, Wera Leujak, Nicolaj Lindeborgh, Miia Mannerla, Jaakko Mannio, Georg Martin, Monika Michalek-Pogorzelska, Atis Minde, Charlotta Moraeus, Ingo Narberhaus, Stefan Neuenfeldt, Vladimir Nikiforov, Anna Nikolopoulos, Hans Nilsson, Per Nilsson, Tomas Nitzelius, Daniel Oesterwind, Jens Olsson, Marzena Pachur, Rita Poikane, Susanne Ranft, Johnny Reker, Nijole Remeikaite- Nikiene, Manfred Rolke, Anna Roos, Anda Ruskule, Rolf Schneider, Doris Schiedek, Joanna Szlinder- Richert, Peter Sigray, Henrik Skov, Thomas Kirk Sörensen, Solvita Strake, Henrik Svedäng, Norbert Theobald, Diana Vaiciute, Yvenne Walther, Håkan Wennhage, Malin Werner, Johan Wikner, Joachim Voss, Pekka Vuorinen, Agnes Ytreberg, Tamara Zalewska 101

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106 Baltic Sea Environment Proceedings No. XX B Development of a set of core indicators: Interim report of the HELCOM CORESET project. PART B: Descriptions of the indicators Helsinki Commission Baltic Marine Environment Protection Commission

107 Baltic Sea Environment Proceedings No. XX B Development of a set of core indicators: Interim report of the HELCOM CORESET project PART B: Descriptions of the indicators Helsinki Commission Baltic Marine Environment Protection Commission 2

108 Published by: Helsinki Commission Katajanokanlaituri 6 B Fi Helsinki Finland Editors: Samuli Korpinen and Ulla Li Zweifel Authors of the descriptions of core indicators, candidate indicators and supplementary indicators presented in this report: Alexander Antsulevich, Magnus Appelberg, Janina Baršienė, Anders Bignert, Elin Boalt, Stefan Braeger, Katja Broeg, Britt- Marie Bäcklin, David Connor, Vivi Fleming-Lehtinen, Karin Fürhaupter, Anders Galatius, Galina Garnaga, Elena Gorokhova, Martin Green, Michael Haarich, Heidi Hällfors, Martti Hario, Jenny Hedman, Outi Heikinheimo, Björn Helander, Christof Herrmann, Jürgen Herrmann, Tero Härkönen, Marja Isomursu, Günter Kanisch, Mervi Kunnasranta, Thomas Lang, Antti Lappalainen, Martin M. Larsen, Maiju Lehtiniemi, Kari Lehtonen, Jaakko Mannio, Manuel Meidinger, Monika Michalek-Pogorzelska, Charlotta Moraeus, Sven P. Nielsen, Jens Olsson, Rita Poikane, Susanne Ranft, Manfred Rolke, Atso Romakkaniemi, Christina Ruden, Ari Ruuskanen, Rolf Schneider, Doris Schiedek, Henrik Skov, Jakob Strand, Brita Sundelin, Laura Uusitalo, Malin Werner and Stefanie Werner. For bibliographic purposes this document should be cited as: HELCOM, Development of a set of core indicators: Interim report of the HELCOM CORESET project. PART B: Descriptions of the indicators. Balt. Sea Environ. Proc. No. XXX B Information included in this publication or extracts thereof are free for citing on the condition that the complete reference to this publication is given as stated above. Copyright 2012 by the Baltic Marine Environment Protection Commission Helsinki Commission Language revision: XX Design and layout: XX Photo credits given in the back cover. Disclaimer: This report is an expert report of the HELCOM CORESET project on the development of HELCOM core indicators. The report contains the basis for the identification of core indicators to assess the state of the Baltic Sea marine environment in order to follow up the implementation of the Baltic Sea Action Plan and to facilitate the national implementation of the EU MSFD according to the role of HELCOM as a platform for the regional coordination. While the ultimate aim is that the set of core indicators will be measured by all Contracting Parties, the current state of development cannot be regarded as final and needs alteration and extension, for example with respect to the GES boundaries suggested. Number of pages: XX 3

109 Table of Contents 1. Introduction Proposed core indicators for biodiversity Blubber thickness of marine mammals, and Pregnancy rate of marine mammals Population growth rate of marine mammals Productivity of white-tailed eagles Abundance of wintering populations of seabirds Distribution of wintering seabirds Fish population abundance Mean metric length of key fish species Fish community diversity Proportion of large fish individuals in the community Abundance of fish key trophic groups Fish community trophic index Multimetric macrozoobenthic indices Lower depth distribution limit of macrophyte species Trend in the arrival of new non-indigenous species Proposed core indicators for hazardous substances and their effects Poly Brominated Diphenyl ethers (PBDE) Hexabromocyclododecane (HBCD) Perfluorooctane sulphonate (PFOS) Polychlorinated biphenyls and dioxins and furans Polyaromatic hydrocarbons (PAH) Lead, Cadmium and Mercury in fish and shellfish Cesium Tributyltin (TBT) and the imposex index Pharmaceuticals: Diclofenac and 17-alpha-ethinylestradiol Lysosomal membrane stability Fish Disease Index: Micronucleus test A. Reproductive disorders in fish and amphipods: Reproductive success in eelpout B. Reproductive disorders in fish and amphipods: Reproductive success in amphipods Candidate indicators for biodiversity and hazardous substances Distribution of harbour porpoise By-catch of marine mammals and birds Impacts of anthropogenic underwater noise on marine mammals Fatty-acid composition of seals as measure of food composition

110 4.5. Abundance of breeding populations of seabirds Proportion of seabirds being oiled Incidentally and non-incidentally killed white-tailed eagles Status of salmon smolt production, smolt survival and number of spawning rivers Sea trout parr densities of sea trout rivers vs. their theoretical potential densities, and the quality of the spawning habitats Large fish individuals from fishery-based data sources Abundance of Cyprinids in archipelago areas Ratio of opportunistic and perennial macroalgae Cladophora length Size distribution of benthic long-lived species Blue mussel cover Cumulative impact on benthic habitats Biomass of copepods Biomass of microphageous mesozooplankton Zooplankton species diversity Mean zooplankton size Zooplankton-phytoplankton biomass ratio Phytoplankton diversity Seasonal succession of phytoplankton groups Alkylphenols Intersex or vitellogenin induction in male fish Acetylcholinesterase (AChE) EROD/CYP1A induction Supplementary indicators for environmental assessments Summary of all supplementary indicators Ratio of diatoms and dinoflagellates Ratio of aututrophic and heterotrophic organisms Abundance and distribution of non-indigenous invasive species Biopollution level index Organochlorine compounds

111 1. Introduction This report is Part B of the report Development of a set of core indicators: Interim report of the HELCOM CORESET project and its first part describing the process to select core indicators is published as a seprate report (HELCOM ). This report contains interim descriptions of the proposed core indicators, candidate indicators and supplementary indicators by the CORESET project. While the PART A of the report focuses on the description of the selection process of the core indicators, giving only short narrative descriptions of the proposed core indicators, this PART B of the report aims to give more detailed descriptions of the core indicators. The final objective is to use these descriptions as background material for the final core indicator reports that will be placed on HELCOM web site. Presenting interim products of the HELCOM CORESET project, this report should be seen as a milestone report, giving more or less broad frames of core indicators and, in some cases, lacking still essential details of analyses or indicator computations. The selection criteria for the core indicators are given in the PART A of this report, but it can be briefly mentioned that all the core indicators were selected on the basis of the HELCOM common principles for core indicators and targets (endorsed by HELCOM HOD 35/2011), the EC decision document 477/2010/EU 2 and additional selection criteria defined prior the process. The main criteria were that the core indicators must be Baltic wide (including coastal and transitional waters), include a target showing good environmental status, be scientifically sound, reflect or directly measure an anthropogenic pressure, measure a key component of the ecosystem (biodiversity) or a substance with high PBT properties and worrying levels or trends in the sea (hazardous substances). All the selection criteria are given in the main report. However, as the development of the indicators is still on-going, the classification to core and candidate indicators is still provisional. The proposed core indicators for biodiversity are presented in Chapter 2 of this report and Chapter 3 presents the proposed core indicators for hazardous substances. Chapter 4 presents candidate indicators suggested for further development during the project and in Chapter 5 supplementary indicators identified as supportive indicators for environmental assessments are presented. The biodiversity core indicators have a cover page and a background documentation giving scientific support for the selection as well as functionality and GES boundary of the core indicator. The core indicators for hazardous substances and their effects have a documentation presenting the selection criteria for each of the indicators and the proposed GES boundary. The documentations also include information of the monitoring and analyses of the indicators. In addition to core indicators, the report presents candidate indicators which were identified in the project. The HELCOM CORESET was not able to finalize by the autumn 2011 the validation of all the proposed indicators that had been identified as potentially important for assessment of the environmental status of the Baltic Sea. These indicators were labelled as candidate indicators. Some of the candidate indicators lack GES boundaries, some have methodological challenges and others need compilation of data and further testing. The CORESET expert groups considered it important to continue developing them towards operational core indicators. The report presents also some supplementary indicators for environmental assessments. These are quantitative indicators, which did not fulfil the criteria of core indicators, but are a 1 HELCOM, Development of a set of core indicators: Interim report of the HELCOM CORESET project. PART A. Description of the selection process. Balt. Sea Environ. Proc. No. XXX A 2 Commission decision of 1 September 2010 on criteria and methodological standards on good environmental status of marine waters (2010/477/EU). OJ L 232/14,

112 rich source of supporting information. Some of them measure natural fluctuations, caused by climatic variability, while others may have a linkage to anthropogenic pressures but they are not applicable for the entire Baltic Sea or they do not have measurable thresholds, which are required for core indicators. As the HELCOM CORESET project did not focus on developing supplementary indicators, it is clear that only a few of them have been included in this report. 7

113 2. Proposed core indicators for biodiversity Core indicators are those indicators discussed and developed in the HELCOM CORESET project that fulfil HELCOM common principles, endorsed by HELCOM HOD 35/2011, and address the ecological objectives of the HELCOM Baltic Sea Action Plan and the qualitative descriptors and criteria of the EU Marine Strategy Framework Directive and the EC decision document 477/2010/EU. The CORESET expert group on biodiversity has come up with 15 core indicators that will be further developed during the project. The proposed core indicators are also discussed in the PART A of this report. This chapter presents the proposed core indicators for biodiversity including background documentation. Each core indicator has been given a separate section, following the numbering of the summary table. All the core indicators are listed in the summary table below. Table 2.1. Proposed core indicators for biodiversity. 1. Blubber thickness of marine mammals 2. Pregnancy rates of marine mammals 3. Population growth rate of marine mammals 4. White-tailed eagle productivity 5. Abundance of wintering populations of seabirds 6. Distribution of wintering populations of seabirds 7. Fish population abundance 8. Metric mean length of key fish species 9. Fish community diversity 10. Proportion of large fish in the community 11. Abundance of fish key trophic groups 12. Fish community trophic index 13. Multimetric macrozoobenthic indices 14. Lower depth distribution limit of macrophyte species 15. Trends in arrival of new non-indigenous species 8

114 2.1. Blubber thickness of marine mammals, and 2.2. Pregnancy rate of marine mammals 1. Working team: Marine mammal team Authors: Britt-Marie Bäcklin, Charlotta Moraeus, Mervi Kunnasranta and Marja Isomursu Aknowledged persons: Stefan Bräger, Anders Galatius, Britta Knefelkamp, Anna Roos, Ursula Siebert and Stefanie Werner as well as Members of the HELCOM SEAL EG. 2. Name of core indicator Health status measured by blubber thickness and pregnancy rate 3. Unit of the core indicator - millimetre blubber layer, and -% pregnant mature animals 4. Description of proposed indicator Blubber thickness is a commonly used method to describe the nutritional state of marine mammals. The sternum blubber thickness in Baltic seals has been measured, mainly in bycaught seals, since the 1970s. Pregnancy rate in sexually mature female seals during the pregnancy period have been noted since the 1970s in by-caught, and later also in hunted Baltic seals. Blubber thickness and pregnancy rate have also been noted in harbour porpoises. 5. Functional group or habitat type Toothed whales and seals 6. Policy relevance MSFD GES criteria 1.3 (Population condition) of 2010/447/EU HELCOM recommendation on Conservation of seals in the Baltic area 27-28/ HELCOM-Baltic Sea Action Plan: partially addressed in Indicators and targets for monitoring and evaluation of implementation of the Baltic Sea Action Plan (BSAP) under Hazardous Substances. Listed in Annexes II and V of the Habitats Directive. 7. Use of the indicator in previous assessments Harbour porpoises and Seal health monitoring programs, HELCOM indicator fact sheets, ASCOBANS, e.g. in the Jastarnia Plan (2002 & 2009) 8. Link to anthropogenic pressures Fishing causing changes in the food web, ecosystem changes (food web, introduction of pathogens and non-indigenous species), contaminants, climate change, pressure from other anthropogenic activity e.g. underwater noise. 9. Pressure(s) that the indicator reflect Hazardous substances, Biological disturbance, Ecosystem changes, Fishing, Climate change 10. Spatial considerations Assessment should be carried out in accordance to management units defined in HELCOM RECOMMENDATION 27-28/2 i.e. 1) harbour seals in the Kalmarsund region (Sweden);2) Southwestern Baltic harbour seals (Denmark, Germany, Poland, Sweden); 3) Gulf of Bothnia ringed seals (Finland, Sweden); 4) Southwestern Archipelago Sea, Gulf of Finland and Gulf of Riga ringed seals (Finland, Estonia, Latvia, Russia); 5) Baltic Sea grey seals (all Contracting Parties to the Helsinki Convention). 11. Temporal considerations In addition to periodic assessments, the indicators should be followed as time trends 12. Current monitoring Harbour porpoise and seal health monitoring programs, HELCOM indicator fact sheets 13. Proposed or perceived target setting approach with a short justification. Blubber layer in seals: Geometric mean blubber thickness above a reference level (=GES) measured in the species specific pregnancy period (seals) in juvenile and adult (< 21 years) 9

115 Baltic seals. The GES limit will be different between juveniles and adult male and females and between species. The years is used as a reference state for a healthy population. Blubber thickness is also recorded in harbour porpoises, ringed seals and harbour seals; although a low number of mature animals are investigated. More knowledge is needed about the season for measure in harbour porpoises and normal blubber thickness in harbour porpoises, ringed and harbour seals before proposing them as core indicators. Pregnancy rate in seals: per cent females with the presence of a foetus after the delayed implantation period in sexually mature seals (4-20 years old). The pregnancy rate in grey seals in is used as a reference state for a healthy population. The levels that can be considered to represent GES for ringed and harbour seals and harbour porpoises remain to be compiled or investigated. Introduction Several health parameters in marine mammals are investigated in CPs of HELCOM. The significance or cause of some pathological findings remains to be investigated. Furthermore, Baltic countries have different possibilities and access to conduct marine mammal necropsies. Therefore pregnancy rate and blubber thickness have been prioritised to roughly reflect the health in marine mammals since they are routinely measured in several CPs (see monitoring). Agents that are lethal to foetuses or endocrine disrupting causing a decreased pregnancy rate, and also agents or starvation causing a thin blubber layer, could seriously affect the continued existence of the population. Species considered here are; grey seals (Halichoerus grypus), ringed seals (Phoca hispida), harbour seals (Phoca vitulina) and harbour porpoises (Phocoena phocoena). Blubber thickness The thickness of the blubber layer is important for the individual survival in marine mammals and in females also for the survival of their offspring. A seasonal difference in blubber thickness with a decrease during the reproduction, lactating and molting periods in spring and an increasing blubber thickness towards autumn has been described for adult seals in many studies (Nilssen et al., 1997; Sparling et al., 2006; Hauksson, 2007). The mean autumn/winter blubber thickness has decreased significantly in Baltic grey seals since the beginning of 2000s, especially in 1-4 year-old seals from by-catch and hunt (Bäcklin et al., 2010). This decreasing trend has also been observed in young Baltic ringed seals (Kunnasranta et al., 2010). There are also data of blubber thickness in harbour seals and maybe in harbour porpoises that needs to be compiled. There could be several reasons for a thin blubber layer in the autumn/winter season e.g., disease, contaminants, decreased fish stocks and change in diet, or a change in the quality of the diet. The reason for the decreasing trend in blubber thickness in seals is unknown but so far no correlations to disease have been found. Blubber thickness and pregnancy rate are possible to obtain, besides in institutional necropsies, from for example by hunters. By sampling the female reproductive organs (reproductive status), the lower jaw (age determination) and measuring the sternum blubber thickness and reporting the date of death, and sending it to an institute, it should be possible to collect more data than at present. Pregnancy rate During the 1970s and the early half of the 1980s, uterine obstructions causing sterility were commonly found in necropsied Baltic grey and ringed seals (Helle et al. 1976a,b; Olsson 1977;Bergman & Olsson, 1985). Since then, pregnancy rate has increased in examined Baltic grey seals from 9% ( ) to 60% ( ) (Bergman, 1999). In , the pregnancy rate was 88% in 4-20 years old grey seal females. The last case of uterine obstruction in grey seals, investigated in Sweden, was seen in In the 2000s, about 20% of the examined Baltic ringed seals still suffer from uterine obstructions and the 10

116 pregnancy rate of 68% in ringed seals in is therefore probably lower than normal (Helle et al., 2005, Kunnasranta et al.,2010). The most likely candidate responsible for the former low gynaecological health among Baltic seals was high concentrations of polychlorinated biphenyls (PCB) (Helle et al. 1976a, b; Bredhult et al., 2008). There are no observations or reports of uterine obstructions in Baltic harbour seals or harbour porpoises. There are also data of pregnancy rate in harbour seals and in harbour porpoises that needs to be compiled and evaluated. Policy relevance The policy relevance for the indicator health in marine mammals is found in criteria 1.3 (Population condition) of 2010/447/EU, the HELCOM recommendation on Conservation of seals in the Baltic area 27-28/ with the long-term objective of attaining a health status that secures the continued existence of the populations. In the HELCOM-Baltic Sea Action Plan, mammals are partially addressed in Indicators and targets for monitoring and evaluation of implementation of the Baltic Sea Action Plan (BSAP) under Hazardous Substances. The three grey seal species of the Baltic Sea and the harbour porpoises are all protected by the Habitats Directive and listed in its Annexes II and V. Methods to evaluate the core indicators Pregnancy rate Pregnancy rate is measured as the presence or absence of an embryo or foetus in the pregnancy period in mature females (presence of an ovarian Corpus luteum). It is expressed as percentage pregnant females of the number of all mature females (age 4-20 years in seals) investigated during the actual season(s). Grey seals Estimated age-specific birth rates increase steeply from the age of four to six (Hamill & Gosselin, 1995). The birth rates for six year old females in the Northwest Atlantic, British, Norwegian and Baltic populations ranged between 60-91%. In a sample of 526 female grey seals from the Northwest Atlantic, pregnancy rates were estimated from the presence/absence of a foetus. The pregnancy rate for the Northwest Atlantic population was relatively stable at about 90% after the age of six (Hamill & Gosselin, 1995;Harding et al., 2007). In the Baltic grey seal population, the pregnancy rate was 88% in 4-20-year old females in (Fig. 1). This pregnancy rate seems to be normal in 4-20-year old Baltic grey seals and is interpreted as representative of a healthy population (Figs. 1&2). This rate is also close to the pregnancy rate of Northwest Atlantic grey seals older than five years. The pregnancy rate for the 4-5-year old individuals is 65% and for the 6-20-year old individuals is 95.5% among grey seals caught via hunting and as by-catch in in Sweden (Fig. 2). Annually, Sweden does not receive more than 4-13 grey seal females between 4 and 20 years of age in the pregnancy period. 11

117 Pregnancy rates % 40 Pregnant 4-20 years old (N=11) (N=20) (N=565) (N=44) Period Figure 1. Pregnancy rate, mean values and one sided 95% confidence intervals for a proportion, in 4-20-year old female Baltic grey seals (August to reproductive season). Finnish data is included in the period August-February % pregnant years old (N=26) 6-20 years old (N=45) 4-20 years old (N=71) ALL Age Pregnant Figure 2. The pregnancy rate, mean values and one-sided 95% confidence intervals for a proportion, in examined 4-20-year old grey seal females from by-catch or hunt in Sweden , divided into 4-5-year old and 6-20-year old seals. Ringed seals The annual number of investigated 4-20-year old Baltic female ringed seals and Baltic harbour seals (Kalmarsund population) during the pregnancy period is very small. In Figure 3, pregnancy rate of a total number of 19 ringed seals examined is shown. The pregnancy rate in ringed seals was 68% in (but small data!) compared to 84.5% in grey seals. Also, the ringed seals are still suffering from uterine occlusions. Data from harbour seal and harbour porpoise investigations remains to be compiled and evaluated. 12

118 Figure 3. The prevalence of pregnant, and sexually mature (presence of Corpus luteum) females in examined Baltic ringed seals (4 years or older) in Finland and Sweden. Data of prevalence of pregnancies was limited to samples acquired in the implantation period between August to February (Kunnasranta et al.,2010). Blubber thickness In , blubber thickness in seals necropsied at the Swedish Museum of Natural History (SMNH) was only measured ventrally at three sites (sternum, belly and hips, or neck, sternum and hips) between the muscle layer and the skin. Therefore, at SMNH, only the sternum blubber thickness of seals measured today is comparable with earlier data. Two questions have been addressed when evaluating blubber thickness as core indicator; Does the sternum blubber thickness reflect the nutritional status/body condition of the animals? What blubber thickness could be considered to be normal? Investigations of blubber thickness in ringed and grey seals conducted at SMNH and a survey of published data are summarised below LMD-index Ryg et al. (1990) tested a method to estimate the total blubber content of a seal as % of the body weight (LMD-index) in 5 seal species (phocids). The investigation was performed on shot or by-caught seals and the blubber of 132 ringed seals, 8 bearded seals, 38 grey seals, 20 harp seals and 3 harbour seals was measured and weighed. Results showed that % blubber of the body weight was equal to L/M x d, and SE = 3%, where L is body length in meters (nose to tail), M is the body mass in kg, and d is the xiphosternal (a site located dorsally at 60% of the body length from nose) blubber thickness in meters. At SMNH the % blubber of the body weight has been tested using the mathematical expression from Ryg et al. (1990). The calculated results were compared with the real weight of the blubber as % of the body weight in two ringed seals and one grey seal. For these three seals, the calculated LMD-index was similar to the weighed % blubber of the body weight (table 1). The modest experiment also showed that the LMD-index is a good method to calculate % blubber in both ringed and grey seals, if body length, body weight and the xiphosternal blubber thickness are known. 13

119 Table 1. Calculated % blubber (LMD-index) and respective factors used for calculations (from Ryg et al. 1990). Seal Length m Body weight kg Blubber m Blubber weight kg % Blubber of body weight Ringed 1,25 66,3 0,055 30, Ringed 1,08 23,4 0,009 3, Grey 0,98 21,9 0,013 4, Calculated % blubber (LMD) LMD-index and sternum blubber thickness At SMNH, the relation between the sternum blubber thickness and the LMD index (calculated with the xiphosternal blubber thickness) has also been investigated in Baltic ringed and grey seals. The measured sternum blubber thickness was positively correlated with the calculated LMD-index (Fig. 4 & 5). Thus, the results indicate that the sternum blubber thickness is a good indicator for the nutritional status/body condition in ringed and grey seals. Ringed seals LMD-index vs blubber thickness 50% % blubber of body weight 45% 40% 35% 30% 25% 20% 15% 10% 5% R 2 = 0, years May-June (N=21) Males 7-20 years May-June (N=4)i Females 5-13 Years May- June (N=6) Males 5-25 Years October (N=2) 2-3 Years Oct-Jan (N=3) Poly. ( 1-4 years May-June (N=21)) 0% mm blubber thickness sternum Figure 4. Sternum blubber thickness (mm) in Baltic ringed seals from hunt in relation to percentage blubber of the body weight (LMD-index). One - four year olds include both males and females. Most of the animals were shot in the spring (thinnest season). N= number of investigated ringed seals. Bycaught Baltic grey seals 1-20 years old, % LMD-index R 2 = 0, mm sternum blubber thickness 14

120 Figure 5. Sternum blubber thickness (mm) in by-caught Baltic grey seals in relation to percentage blubber of the body weight (LMD-index). Trend line is polynomial. Seasonal changes in blubber thickness To avoid measuring seals that are starved due to natural causes, e.g., poor teeth due to old age, or poor survivors due to young age, it is suggested that only seals between 1-20 years old are included in the assessments of blubber thickness. The blubber layer in mature ringed and grey seals fluctuates with season and is low after the reproductive season. With the intention to measure how well seals have managed to gain blubber after the reproductive season, the measuring period is suggested to be the autumn/winter season. In order to investigate in which month the blubber thickness starts to increase, a mean value was calculated for each month, sex and age class in grey seals from hunt 3. Between August and February (pregnancy period) seems to be the period when the blubber layer is as thickest (Fig.6 & Table 2). The data presented in Fig 6 represent measurements done by the hunters, who were provided with instructions, and the sternum blubber thickness has thereby been measured by different people using different instruments Blubber thickness (mm) years (N=47) 4-20 years females (N=126) 4-20 years males (N=68) 0 April May June July August September October November December Month Figure 6. Mean blubber thickness (mm) ± SD of at least 3 individuals per month in Baltic grey seals from hunt, N= total number of animals measured. Table 2. Number of measured animals each month in Figure 6. Age years/sex April May June July Aug Sept Oct Nov /females 4-20 /males Normal blubber thickness in grey seals Beside Swedish data, data of sternum blubber thickness in grey seals was kindly provided by the UK (P.D. Jepson) and Norway (K.T. Nilssen) and comparisons were made in the pregnancy period 4 of animals examined in and before 2004 (Table 3). It should be noted 3 Since 2001, Swedish hunters have sent the inner organs, lower jaws, a piece of blubber with skin, and data on body length, sternum blubber thickness and date of death from between Baltic grey seals per year. 4 In UK and Norway; March-September and in the Baltic, August-February 15

121 that the available data include animals with different causes of death (stranded, shot or bycaught). Assuming grey seals from hunt represent a fairly random sample from the population; geometric mean 5 blubber thicknesses with confidence intervals were calculated to represent reference levels from Norwegian and Swedish grey seals from hunt (Table 3). Pregnant grey seals, Farne Islands Boyd (1984) made sternum blubber thickness measurements on female grey seals around the time of implantation. The mean ± SEM in females with implantation in progress was 36 ±3.5 mm. For females with a fully implanted embryo it was 46 ± 2.5 mm. These results were based on dissections of 72 shot adult grey seal females; however the number of investigated females was not given for the means. Table 3. Summary of the geometric mean blubber thicknesses and the 95% confidence interval in grey seals from Norway, the UK and Sweden, during the pregnancy period. GM= geometric mean, CI= 95% confidence interval and N= number of grey seals. Country 1-3 years old 5-20 years old or > 170 cm males mm GM mm CI N mm GM mmci N mm GM 5-20 years old or > 170 cm females mm CI Norway hunt ( Sweden hunt ( ) N Sweden & Norway hunt ( ) Sweden by-catch ( ) ) UK stranded ( ) ) no available by-caught 5-20 years old females in during the pregnancy period. Ringed seals The number of investigated ringed seals in the autumn/winter season is rather small but there are some data (Table 4) available in Kunnasranta et al. (2010). The period showing the thickest blubber layer was , but there are only 7 seals from that period. The blubber thickness in harbour seals and harbour porpoises remains to be compiled and evaluated. Table 4. Mean blubber thickness (cm, sternum) in examined 1-3 yr old and 4-20 yr old Baltic ringed seals during spring (January-June) and fall (July-December) in Finland and Sweden (Kunnasranta et al., 2010). 1-3 years old 4-20 years old Period Spring SD N Fall SD N Spring SD N Fall SD N ,54 0,6 5 4,00-1 3,43 1,3 19 5,30 2,3 5 3,96 0,9 12 4,70 0,4 2 3,44 0,9 61 5,94 2,4 5 5 Data is not normally distributed 16

122 ,41 0,8 34 3,94 0,5 7 3,20 1,3 63 5,73 0,9 16 Age determination Age determination in seals is performed by examination of the annual growth pattern (GLGs) in cementum zones in tooth sections (Hewer, 1964). The method is modified for harbour seals (Dietz, R., et al., 1991) and is also used when examining ringed seals and harbour porpoises, however in harbour porposes the annual growth pattern is examined in the dentine. Approach for defining GES Pregnancy rate suggestions Pregnancy rate is measured as presence or absence of a foetus in the pregnancy period in 4-20-year old seals. GES data proposed to be assessed every third year (pooling the data for each 3-year period) for 4-20 years old, and every sixth year pooling the data for each 6- year period, separately for young and adult females. Today s figures suggest that GES in 4-20 years old could be set at the lower limit of the 95% confidence interval i.e at about 80%, referring to the period which is proposed to be defined as representative of a healthy population in Figure 1. Data should also be presented as trends. Whether or not similar GES limit for pregnancy rate can be suggested for harbour seals, ringed seals and harbour porpoises remain to be investigated. Blubber thickness suggestions Blubber thickness is measured at the sternum between the muscle layer and the skin during the season of pregnancy (August-February for grey and ringed seals). Suggested reference levels for GES are the lower limit of the 95% confidence interval for the geometric mean. These have been calculated for 1-3 years old, 5-20 years old males, and 5-20 years old females in Norwegian and Swedish grey seals from hunt in (Table 3). The reason for basing the proposed GES boundary to data from before 2005 is that since this year the available data indicates a trend of decreasing blubber thickness. Suggestion GES boundaries for grey seals during the season of pregnancy from stranded, by-caught or hunted animals (from Table 3). Age class sex GM CI = GES boundary 1-3 years females and males years males years females 37 Data should also be presented as trends in blubber thickness (separated into by-catch, hunt and age classes) with geometrical means and 95% confidence intervals (Fig. 7). Whether the upper or lower limit of the confidence interval or the geometrical mean should be below the GES boundary for assessment of sub GES is to be discussed. Data could probably be presented every third year (i.e. pooling the data for each 3-year period) for grey seals. In the Baltic, the causes of death have been shown to influence the result of the blubber measurements. Stranded seals often show a thin blubber layer (starvation due to disease or old age) and by-caught seals are often thinner than seals received from hunt (Bäcklin et al.,2010, 2011). Therefore, these groups are suggested to be presented separately (Fig.7) since their proportions will influence the GES determination. However, the comparisons of 17

123 data from stranded (exceeding 25 mm), shot or by-caught grey seals from different countries in Table 3, did not reveal big differences (no data from 1-3 year old animals). 1-3 years old Geometric mean mm Hunt (N=51) Bycatch (N=120) GES boundary (N=21) (N=35) (N=74) (N=41) Period Figure 7. The geometric mean blubber thicknesses with 95% confidence interval in four periods in examined 1-3 years old by-caught ( ) and hunted ( ) grey seals in Sweden. All were by-caught or shot between August and February. The proposed GES reference level (26 mm) is shown in blue. N is the number of investigated animals Using proposed GES boundaries for geometric mean blubber thickness, assessment of the period (Fig. 7) reveals that the environmental status is good for the hunted 1-3 years old. The by-caught 1-3 years old geometrical mean is sub GES. GES limits for blubber thickness in ringed seals and harbour seals are still to be considered or investigated as well as for harbour porpoises. Existing monitoring data Health in Baltic marine mammals is investigated in Finland, Lithuania, Poland, Germany, Denmark and Sweden. Table 5. Monitoring information (from CORESET BD, 8 June 2011). Information from several countries is missing. Country Area Coastline Species Month Interval Type of carcass Start of data series Germany Germany Lithuania Sweden Western Baltic Sea Mecklenburg- Western Pomerania Southeastern Baltic sea whole Baltic Sea Hiddensee Westküste Bay of Mecklenburg & Pomeranian Bay, internal lagoons Lithuania coastline Swedish Harbour porpoise Harbour porpoise Grey seal Stranded All always stranded and bycaught All always bycaught,stranded,

124 Sweden Baltic proper Swedish Harbour seal Sweden Sweden Sweden Western Baltic Sea whole Baltic Sea Western Baltic Sea and Baltic proper Swedish Swedish Swedish Harbour seal Ringed seal Harbour porpoise Finland Baltic Sea Finnish Grey seal Finland Baltic Sea Finnish Ringed seal Finland Baltic Sea Finnish Grey seal Finland Baltic Sea Finnish Ringed seal Finland Baltic Sea Finnish Grey seal Finland Baltic Sea Finnish Ringed seal hunt All always bycaught,stranded All always bycaught,stranded, hunt All always bycaught,stranded All always by-caught, stranded April- Decemb er always hunted April- always hunted 2010 Decemb er All always by-caught 1999 All always by-caugh 1999 All sporadic stranded 2010 All sporadic stranded 2010 Weaknesses/gaps The monitoring of Baltic marine mammals started in the 1970s when the seal populations and their health were seriously threatened by especially organochlorine contaminants. The populations have slowly recovered but new contaminants, and threats have revealed. Therefore the knowledge of normal pregnancy rate and blubber thickness is limited in Baltic marine mammals. The point of no return for blubber thickness has not been found in any reports. It seems that the blubber layer in Baltic grey and ringed seals were thicker, but the pregnancy rate was lower, historically. It could then be right to use old (before and early 2000s) data for normal blubber thickness and recent data for normal pregnancy rate. Data from outside the Baltic could be used to determine normal limits but the ecosystem outside the Baltic Sea is different with different opportunities to forage. In the Baltic, grey seals also have a smaller body size than in the northeast Atlantic (UK and Norway) which in turn are smaller than in the northwest Atlantic (McLaren, 1993). The proposed GES boundaries for blubber thickness is partly based on data measured by different Swedish hunters compared to data from by-caught grey seals that have been measured by the SMNH. In order to investigate the accuracy of the blubber thickness measurements made by hunters, an additional measurement on 37 blubber samples was made at the SMNH in 2005, if skin; blubber and muscle layer was visible in the sample. The means of the measurements did not differ significantly (42, 4 ± 9, 6 vs. 42, 2 ± 10, 4) between the hunters and SMNH. This indicates that the mean measurements of blubber thicknesses were comparable (Bäcklin et al., 2011). There is a lack of data, especially for ringed seals. Data from investigations on the western population of harbour seals could probably serve as normal data also for determine GES in the Kalmarsund harbour seal population. It is important to combine population and distribution investigations for the evaluation of the significance of decreased pregnancy rate or mean blubber thickness. 19

125 References Boyd I The relationship between body condition and the timing of implantation in pregnant grey seals (Halichoerus grypus). J Zool., Lond, 203, Bredhult, C., Bäcklin, B-M., Bignert, A., and Olovsson, M Study of the relation between the incidence of uterine leiomyomas and the concentrations of PCB and DDT in Baltic grey seals. Reproductive Toxicology, 25: Bäcklin B-M, Moraeus C, Kunnasranta M, Isomursu M Health assessment in the Baltic grey seal (Halichoerus grypus). HELCOM Indicator Fact Sheets Online. [Date Viewed], Bäcklin B-M, Moraeus C, Roos A, Eklöf E, Lind Y Health and age and sex distributions of Baltic grey seals (Halichoerus grypus) collected from bycatch and hunt in the Gulf of Bothnia. ICES J of Marine Science, 68(1), Dietz, R, Heide-Jorgensen, M-P, Härkönen, T, Teilmann, J, Valentin, N Age determination of european harbour seal, Phoca vitulina L. Sarsia, 76; Hamill M.O. and Gosselin J.F Reproductive rates, age of maturity and age at first birth in Northwest Atlantic grey seals (Halichoerus grypus). Can J. Fish. Aquat.Sci. 52: Harding K., Härkönen T., Helander B. and Karlsson O Status of Baltic grey seals: population assessment and extinction risk. In: Grey seals in the north Atlantic and the Baltic. The North Atlantic Marine Mammal Commission (NAMMCO) vol. 6, 2007, pp ISBN Hauksson, E Growth and reproduction in the Icelandic grey seal (Halichoerus grypus). NAMMCO Scientific Publications, 6: Helle E., Olsson M. & Jensen S. 1976a. DDT and PCB levels and reproduction in ringed seal from the Bothnian Bay. Ambio 5, Helle E., Olsson M. & Jensen S. 1976b. PCB levels correlated with pathological changes in seal uteri. Ambio 5, Helle E Reproductive trends and occurrence of organochlorines and heavy metals in the Baltic seal populations. International Council for Exploration of the Sea (CM papers and reports) E: 37. Helle E, Nyman M, Stenman O Reproductive capacity of grey and ringed seal females in Finland. International conference on Baltic seals, February Helsinki, Finland. Hewer, H.R The Determination of Age, Sexual Maturity, Longevity and a Life-table in the Grey Seal (Halichoerus grypus). Proc. Zool. Soc. Lond 142 (4): Jepson Paul D. Institute of Zoology, Zooligical Soc. of London, Regent s Park, London, NW1 4RY. Kunnasranta M, Isomursu M, Bäcklin B-M, Puntila R, Moraeus C Health assessment in the Baltic ringed seal (Phoca hispida botnica). HELCOM Indicator Fact Sheets Online. [Date Viewed], McLaren I.A Growth in pinnipeds. Biol.Rev. 68:1-79 Nilssen, K, Haug, T., Grotnes, P., and Potelov, V Seasonal variation in body condition of adult Barents Sea harp seals (Phoca groenlandica). Journal of Northwest Atlantic Fishery Science, 22 : Nilssen Kjell T. Institute of Marine Research, Postboks 1870 Nordnes, 5817 Bergen, Norway. Olsson, M., Johnels, A. & Vaz, R DDT and PCB levels in seals from Swedish waters. The occurrence of aborted seal pups. Proc. From the Symposium on the Seal in the BALTIC, June 4-6, 1974, Lidingö, Sweden. SNV Ryg M., Lydersen C., Markussen N Estimating the blubber content of Phocid seals. Can. J. Fish. Aquat. Sci., Vol. 47, Sparling, C., Speakman, J., and Fedak, M Seasonal variation in the metabolic rate and body composition of female grey seals: fat conservation prior to high-cost reproduction in a capital breeder? Journal of Comparative Physiology Biochemical, Systems, and Environmental Physiology, 176:

126 2.3. Population growth rate of marine mammals 1. Working team: Marine mammal team Author: Tero Härkönen Aknowledged persons: Britt-Marie Bäcklin, Stefan Bräger, Anders Galatius, Kaarina Kauhala, Britta Knefelkamp, Charlotta Moraeus, Anna Roos, Ursula Siebert and Stefanie Werner as well as Members of the HELCOM SEAL EG. 2. Name of core indicator Population growth rate of marine mammals 3. Unit of the core indicator Population growth rate (% per year) 4. Description of proposed indicator Marine mammals are top predators of the marine ecosystem and good indicators for the state of the food webs, hazardous substances and direct human disturbance, such as hunting and habitats loss. Deviations from the maximum rate of population growth during the phase of exponential increase are indicative of that the population is reaching its carrying capacity or is affected by human impacts in form of excessive mortality or impaired fertility. Near or in the carrying capacity, the population fluctuates but a continuous decline indicates that the population is not in GES. 5. Functional group or habitat type Seals and toothed whales 6. Policy relevance Descriptor 1, criterion 1.2 Population size Descriptor 4, criterion 4.1 Productivity of key species or trophic groups Descriptor 8, criterion 8.2 Effects of contaminants Marine Strategy Framework Directive, and a number of IGO resolutions (e.g., HELCOM, OSPAR, CMS, ASCOBANS etc.) The Baltic Sea Action Plan provides the following target: By 2015, improved conservation status of species included in the HELCOM lists of threatened and/or declining species and habitats of the Baltic Sea area, with the final target to reach and ensure favourable conservation status of all species 7. Use of the indicator in previous assessments Seal monitoring programs, ASCOBANS, e.g. in the Jastarnia Plan (2002 & 2009). ICES MME: Development of Ecological Quality Objectives (EcoQO:s) 8. Link to anthropogenic pressures The growth rate of the seals and marine mammals has a clear linkage to anthropogenic pressures. 9. Pressure(s) that the indicator reflect Hunting, by-catches of fisheries, environmental pollution 10. Spatial considerations The indicator is expected to vary spatially and among species. The assessment units for the indicator depend on species (HELCOM Recommendation 27-28/2): for grey seal it is the entire Baltic Sea, for ringed seal three areas, for harbour seal two areas and for harbour porpoise there are two populations which should be assessed separately. 11. Temporal considerations Indicators can show long-term trends. Annual counts are required. 12. Current monitoring Monitoring coordinated among Baltic Sea countries 13. Proposed or perceived target setting approach with a short justification. 21

127 Long-term objectives of the 2006 HELCOM seal recommendation: Natural abundance and distribution. Population growth rate should be positive until hampered by natural limitations. Proposal for GES boundary is given below. Introduction Several international initiatives have suggested means to measure the environmental quality of marine ecosystems. The Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR Convention) has been ratified by all North Sea countries. This convention lists a number of Ecological Quality Objectives (EcoQOs) for the North Sea, which were developed in collaboration with the International Council for the Exploration of the Sea (ICES) and aim to define a desirable state for the North Sea. EcoQOs have been developed for some components of the ecosystem, e.g. commercial fish species, threatened and declining species, and marine mammals. An EcoQO is a measure of real environmental quality in relation to a reference level where anthropogenic influence is minimal. The ecological quality elements population trends and utilization of breeding sites, which have been suggested for marine mammal populations, may serve as suitable tools for evaluating current population status. The term population trend is defined for this purpose as a change in abundance of a population, increasing or decreasing within a specified area over a certain number of years. The EU Water Framework Directive (WFD) includes status categories for coastal waters as well as environmental and ecological objectives, whereas the EU Habitats Directive (European Commission, 1992) specifically states that long-term management objectives should not be influenced by socio-economic considerations, although they may be considered during the implementation of management programmes provided the long-term objectives are not compromised. In line with both the OSPAR Convention and the Marine Strategy Framework Directive, the Helsinki Commission (HELCOM) in its HELCOM CORESET project is developing a framework using indicators for the Baltic ecosystem. All seals in Europe are also listed under the EU Habitats Directive Annex II (European Commission, 1992), and member countries are obliged to monitor the status of seal populations. Consequently, the Coreset core indicator Population trend is similar to the EcoQ element with the same name in the ICES and OSPAR frameworks, with the distinction that two latter EcoQ:s include No decline in population size or pup production exceeding 10% over a period up to 10 years for populations minimally affected by anthropogenic impacts. We suggest this condition to be appropriate also for the Coreset indicator Population trend when seal populations are close to natural abundances. The OSPAR and ICES frameworks provide some guidance also for populations far below natural or pristine abundances. Applying the term anthropogenic influence is minimal would imply that a population should grow close to its intrinsic rate of increase when not affected by human activities. The theoretical base for this measure is outlined below and compared with empirical data from seal populations. Approach for defining GES for populations below carrying capacity Long term maximum growth rates in seals The maximum rate of population growth is limited by several factors in grey seals and ringed seals. Females have at most one pup a year, and first parturition occurs at about 5.5 years of age. It is also evident that not all adult females bear a pup each year, especially not young females (Pomeroy et al. 1999, Bäcklin 2011). An additional limitation for the population growth rate is given by the survival of adults. In most seal species the highest measures of adult survival are about , and for grey seals the best estimate available is (Harwood and Prime 1978). An additional constraint is the observation that pup and subadult survival is always found to be lower and more variable compared to adult survival in all studied species of seals (Boulva and McLaren 1979, Boyd et al. 1995, Härkönen et al. 2002). 22

128 These biological constraints impose an upper ceiling of possible rates of long-term population growth for any seal species which can be found by manipulations of the life history matrix. In Fig. 1 we illustrate how fertility and mortality rates known for grey and ringed seals can combine to produce different long-term population growth rates. It is found that growth rates exceeding 10% (λ= 1.10) per year are unlikely in healthy grey seal populations (top stipled line in Fig. 1). Reported values exceeding 10% should be treated sceptically since they imply unrealistic fecundity and longevity rates. Such high growth rates can only occur temporally, and can be caused by e.g. transient age structure effects (Härkönen et al. 1999, Caswell 2000), but are also to be expected in populations influenced by considerable immigration. 1 Annual adult survival 0,95 0,9 0,85 λ=1.10 λ=1.075 λ=1.05 0,8 0,8 0,85 0,9 0,95 1 Annual juvenile survival (0-3 years) Figure 1. Biological constraints delimit the maximum possible rate of increase in populations of grey and ringed seals. The shaded area denotes unlikely combinations of adult and juvenile survival rates. Any given point along the 6 lines shows a combination of adult survival and juvenile survival that produces a given growth rate (λ). The two uppermost lines are for λ = 1.10, the two lines in the middle for λ = 1.075, and the lowest two lines show combinations that result in λ = The stippled lines show combinations of adult and juvenile survival rates given that the mean annual pupping rate is The bold full lines show the possible combinations given that the pupping rate is The upper limit of individual reproductive rate is reflected at the population level, and gives an upper theoretical limit for the population rate of increase (Fig. 1). The mean values of fecundity and mortality will always be lower than the theoretical maximum rate of increase, also for populations which live under favourable conditions. Chance events such as failed fertilisation or early abortions reduce annual pregnancy rates, and in samples of reasonable sizes, mean pregnancy rates rarely reach 0.96 (Boulva and McLaren 1979, Bigg 1969, Härkönen and Heide-Jørgensen 1990). Another factor that will decrease mean pregnancy rates is senescence (Härkönen and Heide-Jørgensen 1990). Further, environmental factors will reduce fecundity and survival rates. The impact from extrinsic factors may occur with different frequency and amplitude. Environmental pollution and high burdens of parasites 23

129 can decrease population-specific long-term averages of fecundity and survival (Bergman 1999), while epizootic outbreaks and excessive hunting have the capacity to drastically reduce population numbers on a more short-term basis (Dietz et al. 1989, Harding and Härkönen 1999, Härkönen et al. 2006). The type of variation in fecundity and survival rates will determine the structure of a population. In a population with a constant rate of increase (thus no temporal variability), the age- and sex-structure quickly reaches a stable distribution, where the frequencies of individuals at each age class are constant. Populations with low juvenile survival typically have steeper age distributions compared to populations with higher juvenile survival rates (Caswell 2001). We have shown the full span of theoretically possible combinations of vital rates at different population growth rates (Fig. 1). It turns out that population growth rate of grey seals can only reach 10% if fertility rates are high (0.95). Harbour seals mature about one year earlier than grey seals and ringed seals, which is why maximum rate of increase in this species is 12-13% per year (Härkönen et al. 2002). Long term maximum growth rates in whales Work carried out under the umbrella of the International Whaling Commission (IWC) have shown that that an appropriate dafault value for the realized annual maximum rate of increase for most whales is about 4% (Best 1992). Similar values have also been estimated for harbour porpoises (Woodley and Read 1991). Empirical evidence With few exceptions, most populations of seals have been severely depleated by hunting during the 20 th century. Detailed historical hunting records for other pinnipeds are available for the Saimaa ringed seal Baltic ringed seal Baltic grey seal and the harbour seal in the Wadden Sea, Kattegat and the Skagerrak. Analyses of these hunting records documented collapses in all populations, which were depleted to about 5-10% of pristine abundances before protective measures were taken. After hunting was banned and protected areas were designated most populations started to increase exponentially. Harbour seal populations outside the Baltic increased by about 12% per year between epizootics in 1988 and 2002, whereas all seal species in the Baltic showed lower increase compared with oceanic populations (Table 1). Regression analyses of time series of abundance data can thus be used to test (ANOVA) if the observed rate of increase in exponentially growing populations deviates significantly from expected values. Table 1. Rates of increase in seal populations depleted by hunting. Grey seals from the UK, Norway, and Iceland are not included here since they have been consistently hunted over the years. Canadian grey seals have life history data similar to harbour seals. Species Area Annual growth Period Reference rate Harbour seal Skagerrak +12% Heide-Jorgensen & Härkönen (1988) Harbour seal Skagerrak +12% Härkönen et al Harbour seal Kattegat +12% Heide-Jorgensen & Härkönen (1988) Harbour seal Kattegat +12% Härkönen et al Harbour seal Baltic + 9% Härkönen & Isakson

130 Harbour seal Wadden Sea +12% Reijnders et al Harbour seal Wadden Sea +12% Wadden Sea Portal Grey seal Baltic +8.5% Karlsson et al Grey seal Canada + 13% Bowen et al 2005 Ringed seal Baltic (BB) +4.5% Härkönen unpublished Proposed GES boundaries The proposed core indicator Population trend is appropriate for marine mammals when used in the OSPAR and ICES contexts. It is feasible in two scenarios of population growth: exponential rate of increase and when the population is close to carrying capacity. A depleted population can evaluated as obtaining GES, when its observed rate of increase doesn t deviate significantly from its intrinsic rate of increase (harbour porpoises 4%, grey and ringed seals 10%, and harbour seals 12%). When populations are close to their carrying capacities, populations obtain GES if the rate of decrease is less than 10% over a period of 10 years as stated in the OSPAR convention. Variances for these maximum estimates are available for all management units, and the statistical analyses can be performed using e.g. ANOVA tests. There is currently not a clear agreement whether the Baltic grey seal population has reached the carrying capacity or not. Existing monitoring data Information derived from national reports to HELCOM CORESET (note that not all countries have reported their monitoring) Country Area/Basin Species Method Noted parameters Germany Kiel Bay & Little Belt, Bay of Mecklenburg Germany Kiel Bay, Bay of Mecklenburg, Southern Baltic Proper Germany Germany Bay of Mecklenburg & Pomeranian Bay, internal lagoons Bay of Mecklenburg & Pomeranian Bay, internal lagoons Lithuania Southern Baltic proper Sweden Baltic Proper, Gulf of Bothnia Finland Gulf of Bothnia, Kvarken, Åland Sea, Archipelago Sea, Gulf of Finland subpopulation Phocoena phocoena western Baltic subpopulation Phocoena phocoena western Baltic Harbour Seal Grey Seal Grey seal Grey seal line transect sampling POD (Porpoise detectors = self-contained submersible data logger for cetacean echolocation clicks) observation of potential haulout sites; collection of accidental sightings observation of actual and potential haul-out or resting sites; collection of accidental sightings Aerial, boat or land of grey seal haulouts Aerial surveys of grey seal haulouts during the molting season in spring Finland Archipelago Sea Grey seal Aerial surveys of grey seal pupping islands during the breeding season in early spring Finland Archipelago Sea, Gulf of Bothnia Baltic ringed seal Aerial surveys of ringed seals during the molting season in n individuals, n pups See method n individuals n individuals n individuals? n individuals n individuals n individuals, n pups n individuals 25

131 Finland Sweden Gulf of Bothnia, and the Quark Gulf of Bothnia and the Quark Baltic ringed seal Baltic ringed seal Sweden Kalmarsund Baltic harbour seal Sweden Kalmarsund Baltic harbour seal Sweden/Denmark Southern Baltic and the Kattegat spring Aerial surveys of ringed seals during the molting season in spring Aerial surveys of ringed seals during the molting season in spring Aerial surveys during moult Landbased pup counts in June and July n individuals n individuals n individuals n pups Harbour seal Aerial surveys during moult n individuals Sampling Monitoring of marine mammal abundance require methods tailored for the different species. Whales and porpoises have usually been surveyed using ship based line transect methodology, where a certain proportion of the sea surface is covered during favourable weather conditions. Large-scale surveys such as SCANS have monitored the abundance of whales in the entire North Sea and adjacent waters (Hammond et al. 2002). This method is appropriate in areas where whale abundance is relatively high, but gives very wide confidence limits in low abundance areas such as the Baltic. The cost in man hours is also very high which is why such surveys only have been repeated about once a decade. Alternative methods in low density areas include submerged hydrophonic devices that record sounds produced by whales. Such devices have been used in the Southern Baltic and an on-going project is deploying sonic equipment elsewhere in the Baltic. This method provides information on the distribution of porpoises but still needs to be evaluated for abundance estimates. Ringed seals are monitored annually in the Bothnian Bay using strip sensus methodology (Härkönen et al. 1998), where more than 13% of the sea ice is covered during peak moulting season in the end of April (20 th of April to the 1 st of May) each year. Such surveys have been conducted since 1988 in the Bothnian Bay, whereas the southern populations in the Archipelago Sea, the Gulf of Finland and the Gulf of Riga and Estonian coastal waters only can be surveyed with this method when ice cover is permitting. Land based surveys of hauled out ringed seals provide complementary information from the Gulf of Finland. Harbour seals in the Kalmarsund, southern Baltic and the Kattegat are surveyed during the peak moulting season in the latter half of August each year. All seal sites are photographed and seals are later counted on the photos. All seal sites are surveyed three times each season, and the mean number hauled out in the two highest counts are used for abundance estimates and trend analyses (Teilmann et al. 2010). Surveys are coordinated between Sweden and Denmark. Grey seals are surveyed in a similar way as harbour seals, where all haul-out sites of seals are photographed and where seals are counted on the photos retrospectively. Surveys are conducted during peak haul-out season in the last week of May and the first week of June. Flights are coordinated among teams from Estonia, Finland and Sweden. Methodology of data analyses All methods except for the sonic method used for harbour porpoises give data on relative abundance since some seals always are submerged. However, since the surveys are standardized, a similar proportion of the seals can be expected to haul out during surveys among years. Consequently, estimates of relative abundance can be used for trend 26

132 analyses, and the growth rate of populations can be estimated with good precision (Teilmann et al. 2010). Using capture/recapture methodology photo-id studies or branded or tagged animals can be used to estimate total abundance. Sub populations are treated separately in the analyses where abundance and trend estimates are given for the following management units: - Ringed seal: The Bothnian Bay including the North Quark, the Archipelago Sea, the Gulf of Finland, Estonian coastal waters including the Gulf of Riga. - Harbour seal: Kalmarsund, the Southern Baltic, and the Kattegat. - Grey seal: The entire Baltic. References Bäcklin, B. M Candidate Indicator: Population health Bergman, A Health condition of the Baltic grey seal (Halichoerus grypus) during two decades. APMIS 107: Best, P. B Increase rates in severely depleted stocks of baleen whales. ICES Journal of Marine Science 50: Bigg, M The harbour seal in British Columbia. Bull. Fish. Res. Bd. Can. 172:1-33. Boulva, J. and McLaren, I.A Biology of the harbor seal, Phoca vitulina, in Eastern Canada. Bull. Fish. Res. Bd. Can. 200, 24 pp. Bowen, W.D., McMillan, J,I and Blanchard, W Reduced rate of increase in grey seals at Sable Island: an estimate of 2004 pup production. Research Document 2005/068 Canadian Science Advisory Secretariat 25 pp. Boyd, I.L., Croxall, J.P., Lunn, N.J. and Reid, K Population demography of Antarctic fur seals: the costs of reproduction and implications for life-histories. J. Anim. Ecol. 64: Caswell, H Matrix population models. Second Edition. Construction, analysis and interpretation. Sinauer Assosiates Incorporated. Sunderland, Mass. USA. Dietz, R., Heide-Jørgensen, M.-P. and Härkönen, T Mass deaths of harbour seals (Phoca vitulina) in Europe. Ambio 18: Heide-Jørgensen, M.-P. and T. Härkönen Rebuilding seal stocks in the Kattegat-Skagerrak. Marine Mammal Science. 4(3): Hammond, P.S. Berggren, P. Benke, H. Borchers, D.L. Collet, A. Heide-Jørgensen, M.P. Heimlich, S. Hiby, A.R. Leopold, M.F. Øien, N Abundance of harbour porpoise and other cetaceans in the North Sea and adjacent waters. Journal of Applied Ecology 39: Harding, K.C. and Härkönen, T.J Development in the Baltic grey seal (Halichoerus grypus) and ringed seal (Phoca hispida) populations during the 20th century. Ambio 28: Härkönen, T. and M.-P. Heide-Jørgensen Comparative life histories of East Atlantic and other harbour seal populations. Ophelia 32 (3): Härkönen, T., O. Stenman, M. Jüssi, I. Jüssi, R. Sagitov, M. Verevkin Population size and distribution of the Baltic ringed seal (Phoca hispida botnica). In: Ringed Seals (Phoca hispida) in the North Atlantic. Edited by C.Lydersen and M.P. Heide-Jørgensen. NAMMCO Scientific Publications, Vol. 1, Härkönen, T, K.C. Harding and S.G. Lunneryd Age and sex specific behaviour in harbour seals leads to biased estimates of vital population parameters. J. Appl. Ecol. 36: Härkönen, T., Harding, K.C. and Heide-Jørgensen, M.-P Rates of increase in age structured populations: A lesson from the European harbour seals. Can. J. Zool. 80: Härkönen, T., R. Dietz, P. Reijnders, J. Teilmann, K. Harding, A. Hall, S. Brasseur, U. Siebert, S. Goodman, P. Jepson, T. Dau Rasmussen, P. Thompson (2006). A review of the 1988 and 2002 phocine distemper virus epidemics in European harbour seals. Diseases of Aquatic Organisms, 68: Härkönen, T. and Isakson, E Historical and current status of harbour seals in the Baltic proper. NAMMCO Sci. Publ. 8: Harwood, J. and Prime, J.H Some factors affecting the size of British grey seal populations. J. Appl. Ecol. 15: Karlsson O & Bäcklin BM (2009) In Swedish: Thin seals in the Baltic Sea. Environmental conditions in Swedish coastal waters, ed Viklund K. The Swedish Environmental Protection Agency. Havet 2009:

133 Pomeroy, P.P., Fedak, M.A., Rothery, P. and Anderson, S Consequences of maternal size for reproductive expenditure and pupping success of grey seals at North Rona, Scotland. J. Anim. Ecol. 68: Reijnders, P.J.H Historical population size of the harbour seal, Phoca vitulina, in the Delta area, SW Netherlands. Hydrobiologica 282/283: Teilmann, J., F. Riget, T. Harkonen Optimising survey design in Scandinavian harbour seals: Population trend as an ecological quality element. ICES Journal of Marine Science, 67: Woodley, TH Read, AJ.(1991) Potential rates of increase of a harbour porpoise (Phocoena phocoena) population subjected to incidental mortality in commercial fisheries. Canadian Journal of Fisheries and Aquatic Sciences. 48:

134 2.4. Productivity of white-tailed eagles 1. Working team: Sea birds Authors: Björn Helander, Christof Herrmann and Anders Bignert 2. Name of core indicator Productivity of white-tailed eagles 3. Unit of the core indicator The mean number of nestlings of at least three weeks of age, out of all occupied nests. 4. Description of proposed indicator The productivity of white-tailed eagle in the coastal zone (15 km zone landwards) of the Baltic Sea is an indicator describing not only biomagnification of contaminants but also persecution, disturbance of nest sites, food availability and availability of suitable nesting sites. Thus, it describes in reproductive terms the growth rate and condition of the population and indirectly indicates the potential for increased abundance. 5. Functional group or habitat type Top predatory birds 6. Policy relevance Descriptor 1, criterion 1.3 Population condition Descriptor 4, criterion 4.1 Productivity of key species or trophic groups 7. Use of the indicator in previous assessments Used in the HELCOM Predatory bird health -indicator. For more detailed descriptions see the Predatory bird health -indicator fact sheet (2009) 8. Link to anthropogenic pressures Scientifically established links to hazardous substances. 9. Pressure(s) that the indicator reflect Directly linked to inputs of synthetic and non-synthetic compounds, disturbance and habitat loss 10. Spatial considerations The parameters should be sampled only from the 15 km coastal zone. Assessment units can be sub-basin wide coastal strips (per country), where an average productivity is calculated. 11. Temporal considerations Frequency: can be updated annually 12. Current monitoring Monitored in Sweden, Germany and in Finland. Data on breeding attempts, breeding success and brood size are collected at as many nests as possible. Early season air surveys are made to find breeding attempts in Sweden. These are later followed up by nest visits to check success and number of young. 13. Proposed or perceived target setting approach with a short justification. Historical data exists that has been used for setting the GES boundary. GES boundary exists for Sweden and can tentatively be used in other areas. 29

135 Introduction The white-tailed sea eagle is a species that faced strong persecution in the 19th and early 20th century causing the population to crash by early 20th century. Protection measures increased the population, but in 1950s the population crashed again because of organic pollutants, mainly DDT, which caused egg-shell changes (including thinning) and, hence, wide-spread failure in reproduction. The white-tailed sea eagle was the first species that signaled the deleterious effects from environmental pollutants in the Baltic Sea. If white-tailed sea eagle reproduction had been monitored earlier during the 20th century, the negative impact of DDT could have been signaled as early as in the 1950s in the Baltic Sea. The sea eagle is the ultimate top predator of the Baltic ecosystem, feeding on fish, sea birds as well as on seals, and is thus strongly exposed to persistent chemicals that magnify in the food web. Reproduction in the Baltic eagle population in the 1970s was reduced to 1/5 of the pre-1950 background level. Following bans of DDT and PCB during the 1970s around the Baltic, eagle productivity began to recover in the 1980s and since the mid-1990s is largely back to pre-1950 levels. The population on the Swedish Baltic coast has increased at 7.8% per year since The improvement in reproduction of the Baltic white-tailed sea eagle populations came no earlier than 10 years after most countries around the Baltic had implemented bans of DDT and PCB. This is a clear reminder of the potentially long-term effects from persistent pollutants. The subsequent recovery, from an 80% reduction in reproductive ability in the 1970s, is nevertheless an important evidence of successful management actions. The core indicator measures the productivity of white-tailed eagle in the coastal zone of different parts of the Baltic Sea thereby describing not only biomagnification of contaminants but also persecution, disturbance of nest sites, food availability and availability of suitable nesting sites. Thus, it describes in reproductive terms the condition of the population and indirectly indicates the potential for increased abundance and distribution. Policy relevance The maintenance of viable populations of species is one of the biodiversity objectives of the HELCOM Baltic Sea Action Plan. EU Birds Directive (79/409/EEC) lists the white-tailed sea eagle in Annex I, binding member states to undertake measures to secure reproduction and survival of the species. The species is listed in the following international conventions: Bern Convention Annex II (strictly protected species), Bonn Convention Annex I and II (conservation of migratory species), Washington Convention (CITES) Annex I (regulating trade). As a top predator in the marine ecosystem, white-tailed sea eagle is also a suitable indicator for the implementation EU Marine Strategy Framework Directive (2008/56/EU), which requires good environmental status (GES) of marine ecosystems by Particularly the following GES criteria apply to this core indicator: - Species distribution (D1.1), - Population size (D 1.2), - Population condition (D 1.3), - Productivity of key species or trophic groups (D 4.1). Monitoring of sea eagle population health as environmental indicator, as well as monitoring of contaminants in eagles and their prey, is recommended in an international Species Action Plan, adopted under the Bern Convention in 2002 (Helander & Stjernberg 2003). Approach for defining GES boundaries 30

136 Definition of GES for the core indicator (productivity) and for the supporting parameters, brood size and breeding success, are based on a Swedish data set during 1850s The reference condition was an average of the parameter values over that time period. The GES boundary sensu EU Marine Strategy Framework Directive was set to the lower 95% confidence limit of the observations during the reference period. The GES boundary is for breeding success 60%, for brood size 1.64 nestlings and for productivity >1.0 nestlings. The observations should be measured as average of the last 5 years. These thresholds are based on data on the 15 km zone of the Swedish Baltic coast (Helander 2003a). 15 km has been widely observed to be the range for foraging among white-tailed sea eagles. The applicability of the proposed GES boundaries to other parts of the Baltic Sea should be validated. The GES boundaries can be tentatively used in Germany (C. Hermann, pers. comm.). Temporal development and current state White-tailed sea eagle reproductive ability is monitored annually by assessing the frequency distribution of occupied eagle nests containing 0, 1, 2 or 3 nestlings (3 being the maximum in this species). Survey techniques and sampling methods are presented in (Helander 1985, 2003a, Helander et al. 2008,). Three indicators of reproductive ability are calculated from these data: productivity, breeding success and nestling brood size. In addition, nutritional condition of nestlings is assessed. The productivity of the white-tailed sea eagle population was chosen as the core indicator to assess the status of the species. Productivity The mean number of nestlings of at least three weeks of age, out of all occupied nests ([n1] + [n2x2] + [n3x3] / [n0] + [n1] + [n2] + [n3]). This indicator combines the breeding success and brood size into a single indicator and assesses the reproductive output of the population. It is a useful indicator in studies on relationships between reproduction and anthropogenic pressures, such as contaminants, persecution and disturbance. It is also a vital parameter in assessments of population status in management perspectives. The productivity has reached GES in Swedish coasts of the Gulf of Bothnia and Central Baltic Proper and in Mecklenburg-Vorpommern in Germany. 31

137 Figure 2. Mean annual productivity of white-tailed sea eagle on the Swedish coast of the Baltic Proper (upper left)and the Gulf of Bothnia (Bothnian Sea and Bothnian Bay), , and in Mecklenburg-Western Pomerania, Germany, (lower). The data set from Germany includes nests that were inspected only from the ground. Reference level given with range based on confidence limits for breeding success and brood size according to Helander (2003a). Whether the reference level, estimated from data from the Swedish Baltic coast, is fully relevant for the German eagle population has not been validated. Breeding success The proportion of nests containing at least one nestling of at least three weeks of age, out of all occupied nests ([n1] + [n2] + [n3] / [n0] + [n1] + [n2] + [n3]). Trends in breeding success of sea eagles on the northern, central and southern Baltic coast over time are presented in Figure 2. As the population has grown over the study period, the number of annually checked pairs has increased: in the Baltic Proper from pairs before 1975 to 176 pairs in 2006, and in the Gulf of Bothnia from around 10 pairs before 1975 (all in the Bothnian Sea) to 89 pairs in 2006 (incl. also the Bothnian Bay, when it was repopulated). Similarly, the number of annually checked pairs in the sample from Mecklenburg-Western Pomerania, Germany, increased from around 75 to 219 between 1973 and Retrospective studies have shown that the breeding success on the whole Swedish Baltic coast decreased from on average about 72% before the 1950s to 47% in and 22% in (Helander 1985, 1994a). Breeding success increased significantly in the Baltic Proper as well as the Gulf of Bothnia from the early 1980s (Figure 3). By the middle to late 1990s, breeding success in both areas was no longer significantly different from the background level. The development in the southern Baltic (Germany) is similar to that in the central Baltic (Sweden, Baltic Proper, see Figure 3), but the breeding success seems to have stabilized at a lower level in Germany. The difference between the German sample and the two Swedish samples, respectively, is statistically significant. Impacts of intraspecific competition in areas with high density of breeding pairs have been 32

138 discussed as a possible reason for the lower breeding success in Mecklenburg-Western Pomerania (Hauff 2009). Figure 3. Breeding success (%) of white-tailed sea eagle on the Swedish coast of the Baltic Proper (upper left) and the Gulf of Bothnia (Bothnian Sea and Bothnian Bay), , and in Mecklenburg-Western Pomerania, Germany, (lower). The blue line included in the set of breeding success data represents a LOESS smoother that explained significantly more than the linear regression line. Reference level with 95% confidence limits is given according to (Helander 2003a). Whether the reference level, estimated from data from the Swedish Baltic coast, is fully relevant for the German eagle population has not been validated. Nestling brood size The mean number of nestlings of at least three weeks of age in nests containing young ([n1] + [n2x2] + [n3x3] / ([n1] + [n2] + [n3]. 33

139 Figure 4. Mean nestling brood size of white-tailed sea eagle on the Swedish coast of the Baltic Proper (upper left) and the Gulf of Bothnia (Bothnian Sea and Bothnian Bay), , and in Mecklenburg-Western Pomerania, Germany, (lower). The data set from Germany includes nests that were inspected only from the ground. Reference level with 95% confidence limits is given according to (Helander 2003a). Whether the reference level, estimated from data from the Swedish Baltic coast, is fully relevant for the German eagle population has not been validated. Based on data from nests inspected by climbing the nest tree, and excluding nests checked only from the ground, nestling brood size is a precise standard. Nestling brood size began to increase in both areas from the 1980s, roughly in synchrony with the increase in breeding success (Figure 2). This is inherent with an improvement in the hatching success of the eggs, affecting both these indicators in parallel. Brood size reached back to the pre reference level in the Baltic Proper in the late 1990s. In the Gulf of Bothnia, however, brood size is still significantly below this reference level. This is mainly due to smaller broods in the southern part of the Bothnian Sea, as illustrated in Figure 4. The current brood size in Germany is lower than in Sweden (Figure 4). During the period , 1.48 nestlings/nest have been recorded in Mecklenburg-Western Pomerania. It 34

140 should be mentioned that this sample includes data from nests only checked from the ground, which results in a certain error due to nestlings not visible from this position. However, this bias does not explain the full difference from the data obtained for Sweden. Data received from ground observations in Germany indicates an underestimation of the real number of nestlings by 11% (Hauff & Wölfel 2002). Using this correction factor for the nests not climbed (about 50% of the total German sample), the corrected brood size for Mecklenburg-Western Pomerania is 1.56, which is still clearly on the low side compared to most coastal records from Sweden (Figure 4, 5). Figure 5. Mean nestling brood size on the Swedish Baltic coastline (15 km zone), counties indicated by letters, and in Mecklenburg-Western Pomerania, (German data corrected for nests checked from the ground). Sample sizes given in brackets. The reference level up to 1950 based on data from the Swedish coast was 1.84, with 95% confidence limits Factors affecting the white-tailed sea eagle reproductive success Abundance, distribution and condition of the white-tailed sea eagle population Productivity Nestling brood size Breeding success Persecution Organic contaminants Food availability Availability of territories (e.g. nest sites) Nest disturbance The productivity of the white-tailed sea eagle is affected by several anthropogenic pressures acting through the nestling brood size (number of nestlings) and the breeding success (success in raising one nestling per pair). 35

141 Monitoring In Sweden, surveys of breeding populations and reproduction, sampling, sample preparation, storage in specimen bank and evaluation of results are carried out by the Department of Contaminant Research at the Swedish Museum of Natural History, Stockholm. Surveys of breeding populations and reproduction of reference freshwater populations are carried out by the Swedish Society for Nature Conservation (Project Sea Eagle), Stockholm. Chemical Analysis is carried out at the Institute of Applied Environmental Research at Stockholm University. In Western Pomerania, Germany, data are collected by voluntary ornithologists, coordinated by the Project group for large bird species under the auspices of the Agency for Environment, Nature Conservation and Geology. The country-wide white-tailed sea eagle data are compiled by Peter Hauff, who submits the annual reports to the mentioned governmental agency. Eagles are presently breeding along the coasts of the whole Baltic Sea, and are monitored in a network of national projects with harmonized methodology. Monitoring of nests is done in all coastal areas of the Baltic Sea with circa 300 nests in Sweden, 300 in Finland and 230 in Germany. There are no large gaps in the monitoring, but the compilation of data has not been done yet, except from Finland, Germany and Sweden. Monitoring of sea eagle reproduction in Sweden is included in the National Environment Monitoring Programme since 1989 as indicator of effects from chemical pollutants. In Finland, the monitoring is done by WWF working group. The first years of the data sets are as follows: in Sweden 1964, in Germany 1973, in Finland Method and frequency of data collection As nests are climbed for assessment of the reproductive parameters, nestlings are also measured (wing chord for estimation of age in days, tarsus width and depth for estimation of sex, see Helander 1981, Helander et al. 2007), and weighed (for nutritional status), sampled (feather and blood), and ringed within an international colour ringing programme, for identifications in the field (Helander 2003b). Dead eggs and shell pieces are collected for measurements, investigation of contents and chemical analyses, for studies on relationships with reproduction. Also shed feathers from adults are collected at all sites and archived. These materials are used in the assessment of other parameters/indicators. Brood size records from nests inspected only from the ground in Germany were corrected by multiplying by a factor 1.11 (Hauff & Wölfel 2002). Methodology of data analyses Simple log-linear regression analysis has been carried out to investigate average changes over time. To check for significant nonlinear trend components, a LOESS smoother was applied and an analysis of variance was used to check whether the smoother explained significantly more than the regression line. Statistical power analyses were used to estimate the minimum annual trend likely to be detected at a statistical power of 80% during a monitoring period of 10 years. To investigate the possible effect of a future reduced sampling scheme, repeated random sampling (5000 times) from 1991 to 2006 in the current database was carried out, simulating a maximum of 50, 25, 20, 15, and 10 records each year. Contingency analysis, using the G-test with Williams correction, a log-likelihood ratio test, was applied for comparisons between geographical regions and time periods. For references see (Helander et al. 2008). 36

142 Gaps and weaknesses Minimum detectable yearly trend (%) for a 10-year monitoring period at a statistical power of 80% has been estimated for Swedish data for different sample sizes, based on random sampling from data collected during (Helander et al. 2008). Minimum detectable trends based on the raw data set between (with a varying annual number of observations) was 1.3% for brood size (Baltic Proper), 2.0% for breeding success (Gulf of Bothnia) and 3.0% for productivity (Gulf of Bothnia). The national survey methods are very similar with the only differences being whether to climb to the nest or survey it from the ground (applying the conversion factor). The reliability of the core indicator can be increased by continuing to develop the GES boundary levels and further studying their linkage to anthropogenic pressures, such as disturbance in the vicinity of nests, wind farms and contaminants. References Hauff, P. & L. Wölfel (2002). Seeadler (Haliaeetus albicilla) in Mecklenburg-Vorpommern im 20. Jahrhundert. Corax, Special Issue 1, Hauff, P. (2009): Zur Geschichte des Seeadlers Haliaeetus albicilla in Deutschland. Denisia 27: 7-18 Helander, B. (1981). Nestling measurements and weights from two white-tailed eagle populations in Sweden. Bird Study 28, Helander, B. (1985). Reproduction of the white-tailed sea eagle Haliaeetus albicilla in Sweden. Holarct. Ecol. 8(3): Helander, B. (1994a). Pre-1954 breeding success and productivity of white-tailed sea eagles Haliaeetus albicilla insweden. In: Raptor Conservation Today. Meyburg, B.-U.& Chancellor, R.D. (eds). WWGBP/The Pica Press, pp Helander, B. (1994b). Productivity in relation to residue levels of DDE in the eggs of white-tailed sea eagles Haliaeetus albicilla in Sweden. Pp in: Meyburg, B.-U. & Chancellor, R.D. (eds.), Raptor Conservation Today.WWGBP/The Pica Press Helander, B. (2003a). The white-tailed Sea Eagle in Sweden reproduction, numbers and trends. In: SEA EAGLE Helander, B., Marquiss, M. and Bowerman, B. (eds). Åtta.45 Tryckeri AB, Stockholm, pp Helander, B. (2003b). The international colour ringing programme adult survival, homing and the expansion of the white-tailed sea eagle in Sweden. In: SEA EAGLE Helander, B., Marquiss, M. and Bowerman, B. (eds). Åtta.45 Tryckeri AB, Stockholm, pp Helander, B., J. Axelsson, H. Borg, K. Holm.& A. Bignert (2009). Ingestion of lead from ammunition and lead concentrations in white-tailed sea eagles (Haliaeetus albicilla) in Sweden. Sci. Tot. Environ. 407: Helander, B., A. Bignert. & L. Asplund (2008). Using Raptors as Environmental Sentinels: Monitoring the White-tailed Sea Eagle (Haliaeetus albicilla) in Sweden. Ambio 37(6): Helander, B., F. Hailer & C. Vila, C. (2007). Morphological and genetic sex identification of white-tailed eagle Haliaeetus albicilla nestlings. J. Ornithol. 148, Helander, B., A. Olsson, A. Bignert, L. Asplund & K. Litzén (2002). The role of DDE, PCB, coplanar PCB and eggshell parameters for reproduction in the white-tailed sea eagle (Haliaeetus albicilla) in Sweden. Ambio 31(5): Helander, B., M. Olsson & L. Reutergårdh (1982). Residue levels of organochlorine and mercury compounds in unhatched eggs and the relationships to breeding success in white-tailed sea eagles Haliaeetus albicilla in Sweden. Holarct. Ecol. 5(4): Helander, B. & T. Stjernberg (eds.) (2003). Action Plan for the conservation of White-tailed Eagle (Haliaeetus albicilla). Recommendation 92/2002, adopted by the Standing Committee of the Bern Convention in Dec., BirdLife International. 51 pp. Henriksson, K., E. Karppanen & M. Helminen (1966). High residue levels of mercury i Finnish white-tailed eagles. Orn. Fenn. 43: Herrmann, C., O. Krone, T. Stjernberg & B. Helander (2009). Population Development of Baltic Bird Species: White-tailed Sea Eagle (Haliaeetus albicilla). HELCOM Indicator Fact Sheets 2009, in press Online., Jensen, S Report on a new chemical hazard. New Scient. 32:

143 Jensen, S., A.G. Johnels, M. Olsson & T. Westermark (1972). The avifauna of Sweden as indicators of environmental contamination with mercury and organochlorine hydrocarbons. Proc. Int. Orn. Congr. 15: Koivusaari, J., I. Nuuja, R. Palokangas & M. Finnlund (1980). Relationships between productivity, eggshell thickness and pollutant contents of addled eggs in the population of white-tailed eagles Haliaeetus albicilla L. in Finland during Environ. Pollut. (Ser. A) 23: Lindberg, P., U. Sellström, L. Häggberg & C.A. De Wit (2004). Higher brominated diphenyl ethers and hexabromocyclododecane found in eggs of peregrine falcons (Falco peregrinus) breeding in Sweden. Environ. Sci. Technol. 38: Nordlöf, U., B. Helander, A. Bignert & L. Asplund (2007). Polybrominated Flame retardants in eggs from Swedish White-Tailed Sea Eagle (Haliaeetus albicilla). Organohalogen Compounds 69:

144 2.5. Abundance of wintering populations of seabirds 1. Working team: Sea birds Authors: Henrik Skov, Martin Green, Susanne Ranft, Martti Hario 2. Name of core indicator Abundance of wintering populations of seabirds 3. Unit of the core indicator A summary index, based on population sizes of selected seabird species 4. Description of proposed indicator Seabirds are important predators in the marine ecosystem. In the wintertime, seabirds aggregate in certain feeding grounds where their abundances can be monitored. The indicator follows the abundance of seabirds in the winter. It follows the birds on three levels: species, functional groups and total abundance. Integration at the group level: Species have been assigned to functional groups where the species abundances are weighted based on population size of respective species. Integration of the all species regardless of their functional groups describes the total abundance of wintering seabirds in an area. With repeated collection of data trends can be calculated over time. 5. Functional group or habitat type Coastal pelagic fish feeder, offshore pelagic fish feeder, Subtidal offshore benthic feeder, Subtidal coastal benthic feeder, Subtidal herbivorous benthic feeder 6. Policy relevance Descriptor 1, criterion 1.2 Population size Descriptor 4, criterion 4.2 Abundance/distribution of key trophic groups and species (Descriptors 5 & 6: indirectly) 7. Use of the indicator in previous assessments None 8. Link to anthropogenic pressures The seabird abundance in the winter is directly impacted by oil spills, by-catch, hunting, displacement by offshore constructions and shipping traffic. It is indirectly impacted by eutrophication and physical disturbance of bottom sediments (through changes in food supplies). 9. Pressure(s) that the indicator reflect Selective extraction of species, introduction of synthetic compounds (oil spills), input of fertilisers and organic matter, abrasion and selective extraction, changes in siltation and thermal regime, other physical disturbance. 10. Spatial considerations Winter concentrations of key species do not occur abundantly in the northern part of the Baltic but are confined to areas in the Baltic proper and southwards. 11. Temporal considerations Monitoring frequency: ideally as often as possible, but at maximum circa every fifth year. 12. Current monitoring Part of international waterfowl monitoring in several member states. Some kind of annual data collection (mainly coastal) is currently being made. Offshore monitoring is being conducted with longer intervals but plans for more regular monitoring (every 3-5 years) exist in at least some member states. 13. Proposed or perceived target setting approach with a short justification. The GES is tentatively defined as a 50% deviation from mean of the reference period of

145 Introduction Water birds are an important part of the marine ecosystem, being predators of fish and benthic fauna and herbivores in coastal areas. Their abundance is supported by the ecosystem productivity, but they also have top-down impacts on their prey species. In the Baltic Sea, majority of waterbird species overwinter in the marine area, aggregating in suitable feeding habitats. Hence, the abundance wintering and breeding populations respond to different pressures and they should be assessed separately. Policy relevance The seabirds have been recognized as a part of the marine ecosystem, and should be included MSFD assessments (Annex III, Table 1). They also fit to the BSAP biodiversity policy goal. In the MSFD, indicator Abundance of wintering populations of seabirds would fit best under the GES descriptor 1 (biodiversity) and descriptor 4 (food web). There is relatively little monitoring of the abundance of wintering seabirds in the offshore areas, but three studies are of key importance: (1) Inventory of Coastal and Marine Important Bird Areas in the Baltic Sea 6, (2) A quantitative method for evaluating the importance of marine areas for conservation of birds 7 and (3) the SOWBAS project s final report 8. Method The indicator is proposed to be based on key seabird species, which have functional significance in the marine ecosystem. They are listed below and sorted under the functional groups of bird species that have been identified in the CORESET project. Species (winter populations) Black-throated diver Gavia arctica Red-throated diver Gavia stellata Great crested grebe Podiceps cristatus Goosander Mergus merganser Red-breasted merganser Mergus serrator Razorbill Alca torda Common guillemot Uria aalge Black guillemot Cepphus grille Velvet scoter Melanitta fusca Common scoter Melanitta nigra Long-tailed duck Clangula hyemalis Eider Somateria mollissima Tufted duck Aythua fuligula Greater scaup Aythua marila Goldeneye Bucephala clangula Mute swan Cygnus olor Mallard Anas platyrhynchos Coot Fulica atra Functional group Coastal pelagic fish feeder Coastal pelagic fish feeder Coastal pelagic fish feeder Coastal pelagic fish feeder Coastal pelagic fish feeder Offshore pelagic fish feeder Offshore pelagic fish feeder Offshore pelagic fish feeder Subtidal offshore benthic feeder Subtidal offshore benthic feeder Subtidal offshore benthic feeder Subtidal offshore benthic feeder Subtidal coastal benthic feeder Subtidal coastal benthic feeder Subtidal coastal benthic feeder Subtidal herbivorous benthic feeder Subtidal herbivorous benthic feeder Subtidal herbivorous benthic feeder All the selected seabird populations are affected by the eutrophication state. In the oligotrophic end of the eutrophication state, the bird populations are limited by the 6 Skov et al. (2000) BirdLife International, Cambridge. 7 Skov et al. (2007) Biological conservation 136: Project funded by the Nordic Council of Ministers: 40

146 availability of food sources, whereas towards eutrophic conditions plant and zoobenthos biomass increases which first benefit seabird populations, but in the extreme end cause decrease in food availability. Oil pollution affects most of the seabirds, oiling feathers and causing hypothermia. Although the number of oil slicks has significantly decreased in the Baltic Sea, oily surface waters still are a significant anthropogenic pressure for seabirds. Estimates of the number of birds oiled are uncertain. By-catch of seabirds in fishing activities is a problem for all fish feeders and benthic divers. Estimates of the number of birds drowned in fishing gear are uncertain. Hunting of seabirds is a significant pressure for some of the selected key species. Particularly, bags of eider and goldeneyes are heavy. Species (wintering population) Black-throated diver Red-throated diver Great crested grebe Goosander Red-breasted merganser Razorbill Common guillemot Black guillemot Velvet scoter Common scoter Long-tailed duck Eider Tufted duck Greater scaup Goldeneye Mute swan Mallard Coot Anthropogenic pressure eutrophication, oil, by-catch eutrophication, oil, by-catch eutrophication, oil, by-catch eutrophication, oil, by-catch eutrophication, oil, by-catch eutrophication, oil, by-catch eutrophication, oil, by-catch eutrophication, oil, by-catch eutrophication, oil, by-catch eutrophication, oil, by-catch eutrophication, oil, by-catch eutrophication, oil, by-catch eutrophication, by-catch eutrophication, by-catch eutrophication, by-catch eutrophication eutrophication eutrophication Because the pressures affecting the selected key seabirds in the winter populations are similar, it is possible to make an index indicator where assessment can be first made on the species level and then functional groups are assessed separately. Finally, an integration of all the species can be made to describe abundance of all wintering seabirds. How this integration will be made is not yet clear. Because the species and functional groups may have different significances in the ecosystem, weighting factors should be considered. They could be based on the conservation value of the Baltic population in the European context or the proportion of the species in the wintering seabird abundance. Approach for defining GES boundaries All the species or functional groups respond to anthropogenic pressures slightly differently, although the pressures behind the change are similar. Therefore the targets, which show the boundary of GES, must be set for each species separately. It is proposed that the GES boundaries are set on the basis of (1) time series data and (2) relation to other indicators (e.g. nutrients, chlorophyll, zoobenthos, plant abundance, fish stocks). The GES boundaries should be given separately for all the sub-basins of the Baltic Sea (see Figure). As defining GES for all of the sub-basins may take time, the first step should be to define GES for those sub-basins which have highest abundance of seabirds in the winter. 41

147 Time series data: it is obvious that there are gaps in the time series datasets of wintering seabirds. The available data sets should be used as far as possible, using also best estimates. Temporal trends should be checked, because they show changes in the environment. Available sources of information are Skov et al. (2000, BirdLife International, Cambridge), Skov et al. (2007, Biological conservation 136: ) and the Final report of the SOWBAS Project funded by the Nordic Council of Ministers ( Relations to other indicators: When assessing GES of the Baltic Sea, there should not be any mismatch between GES of different indicators. For example, the nutrient concentration targets in the Baltic Sea have been agreed in the HELCOM BSAP. Therefore, the seabird GES boundaries should not be set on levels which cannot be reached when nutrient targets have been reached. In addition, competitive interactions between fish feeding birds and large fish affect the target setting. With the current long-term management plan of cod, the cod stocks will increase, which likely affects the food availability for birds. The GES boundaries for birds should not be set too high in such conditions. The policy decisions under different frameworks have possibly conflicting objectives. The Favourable Conservation Status under the Birds Directive may be difficult to reach, if the environment changes to more oligotrophic direction. However, decrease of by-catch, oil pollution and hunting would allow higher bird populations and may mitigate this conflict. Provisional GES boundaries: Until modeling studies have confirmed possible GES boundaries for the selected bird species, it is proposed that provisional GES boundaries are used. The GES is tentatively defined as a 50% deviation from mean of the reference period of (based on available temporal trends in the SOWBAS project). Ultimately, the GES could be set by modelling the population size based on the GES for eutrophication related core indicators, because the abundance of seabirds depends on the trophic state of the ecosystem and the objective of decreasing the eutrophication will affect the seabird populations. Assessment units for the seabird indicators The abundance of wintering seabird populations differs among Baltic sub-basins. Therefore the indicator should be assessed per sub-basin. That means that also the targets must be set for each of the sub-basins. Figure. Sub-basin assessment units in the Baltic Sea (blue lines). 42

148 Sampling and data analyses See SOWBAS final report 9 and Skov et al Gaps and weaknesses The indicator has currently a couple of weaknesses which must be addressed in near future: - not all wintering grounds are covered, - monitoring methods differ between the offshore monitoring and national monitoring practices, - GES boundary is tentative, because of the uncertainty of interlinkages with other GES boundaries. 9 Web link: 43

149 2.6. Distribution of wintering seabirds 1. Working team: Seabirds Authors: Henrik Skov, Susanne Ranft, Martti Hario 2. Name of core indicator Distribution of wintering seabirds 3. Unit of the core indicator Quantitative changes in the main distribution area of seabird species determined from density surface models developed on the basis of line transect survey data in consideration of species specific habitat suitability and sensitivity towards anthropogenic pressures 4. Description of proposed indicator Changes in the main distribution area determined from density surface models like GAMs or GLMs (higher end of the distribution e.g. the 75 th or 90 th percentile of all the sampled densities during the reference situation) are analysed. The indicator consists of well-known species of high numerical and environmental importance only, for which sufficient coverage by line transect data is available, such as Common Eider, Velvet Scoter, Common Scoter and Long-tailed Duck. Time series data can provide information on changes over time and reveal reoccurring spatio-temporal patterns. In combination with data on anthropogenic pressures, naturally driven patterns can then be distinguished from pressure based changes. Pressure based changes in distribution may occur due to changes in resource quality and availability, habitat loss and disturbances or barriers. 5. Functional group or habitat type For the time being the indicator is species specific. 6. Policy relevance Descriptor 1 GES criteria distributional range and distributional pattern of species Biodiversity segment of the BSAP: Objective of natural landscapes and seascapes. 7. Use of the indicator in previous assessments None 8. Link to anthropogenic pressures Directly impacted by: resource depletion (selective extraction of species), habitat loss or deterioration (destructive fishing techniques, construction of artificial structures), temporal or permanent displacement by constructions and ship traffic. Indirectly impacted by: changes in species composition and consequently e.g. resource competition with other bird or non-bird species, changes in resource quality and availability due to contamination by hazardous substances and eutrophication. 9. Pressure(s) that the indicator reflect selective extraction of species, shipping and other physical disturbances, physical damage through dredging and sand/gravel/boulder extraction, nutrient and organic matter enrichment 10. Spatial considerations Areas of suitable habitat to be examined, need to be defined / modelled for each species separately, thereby keeping in mind the naturally occurring spatio-temporal variation, areas at times of sea ice coverage and oxygen depletion should be avoided 11. Temporal considerations Times of highest occurrence, high naturally occurring spatio-temporal variation has to be considered, combination of several observations at varying weather and hydrographical conditions. For waterbirds this would typically mean mid winter. 12. Current monitoring SOWBAS, national monitoring for the identification of SPAs and IBAs, to be included in the HELCOM Waterbird Monitoring 44

150 13. Proposed or perceived target setting approach with a short justification. Deviation from favourable reference value (higher distribution) or deviation from reference state at the beginning of the assessment (the target would be resettlement of areas where anthropogenic pressures lead to avoidance behaviour and no further loss of habitat). Maybe a combination of both approaches. Introduction Seabirds are found across the world s oceans in many different habitats with aggregations occurring over a wide range of spatial and temporal scales (O'Driscoll 1998). The structure and occurrence of aggregations is thereby related to a number of environmental factors, including water temperature and salinity, fluid dynamics, meteorological conditions, food availability and the presence of other marine predators (see e.g. Lewis et al. 2001, Markones et al. 2008). The species-specific effects of these parameters precipitate explicit environmental requirements and dependencies which in combination with the distinct behaviour and biology of the diverse seabird species shape their distributional range and pattern. Thereby, the different species reveal varying distribution patterns ranging from very wide spread to locally concentrated and unpredictable short-term to regular long-term aggregations (BfN 2006, Garthe 2003, Markones et al. 2010, Sonntag et al. 2007). Especially for species with regular long-term aggregations in habituated and predefined localities of specific environmental conditions frequented for breeding, resting or feeding, the availability of suitable and undisturbed habitats is a key factor for the well-being of their population. Anthropogenic pressures, however, decrease the extent of suitable seabird habitats or effect seabird distribution in various other direct or indirect ways (see e.g. Garthe 2003). Human activities such as dredging, sand or gravel extraction as well as the use of destructive fishing techniques or the construction of artificial structures destroy habitats or reduce habitat quality. The latter, in line with shipping, marine wind farms, infrastructure and other physical disturbances, also lead to habitat displacement (Bellebaum et al. 2006, Garthe and Hüppop, 2004, Garthe et al and 2008, Pettersson 2005, Petersen et al. 2006, Sonntag et al. 2007). Marine infrastructures may also act as barriers altering the distributional patterns of bird species at sea (Mendel & Garthe 2010). Fishing or other selective extraction of species influence seabird distribution as resources are being depleted or the species compositions altered leading for example to resource competition with other marine predators (Garthe 1997, Siebert et al., 2009). Furthermore, contamination by hazardous substances and nutrient and organic matter may modify resource availability and quality, therefore indirectly influencing seabird distribution (BfN 2006). With its distinct oceanographic and geographical characteristics the Baltic Sea holds important and unique habitats for breeding and wintering seabird species. The importance of the Baltic as a wintering ground for example can be underlined by the fact that during mild winters over 90% of west-palearctic Long-tailed Ducks and Velvet Scoters overwinter here (Mendel et al. 2008). Changes in distributional patterns of species tied to specific habitats analysed with respect to habitat suitability and anthropogenic pressures should provide information on the environmental status of the species as well as on pressures causing a decline or change in distributional pattern. The authors of the document at hand believe changes in distribution of seabirds to be a suitable indicator for the state of the Baltic Sea marine ecosystem in general and Baltic Sea seabirds in particular. Description of the indicator The indicator is defined as quantitative changes in the main distribution or concentration area of selected species. The main distribution area thereby refers to the higher end of the species specific distribution that is the 75 th percentile. Calculations should be based on time series of line transect data (e.g. 6 yrs) to reduce sample bias which is likely to occur due to e.g. weather conditions. Area of main distribution is determined by application of the 75 th 45

151 percentile on surface density models (e.g. GAMs and GLMs) based on the transect data. Species should be selected based on data availability and accessible background information. Knowledge on their biology, behaviour and seasonal rhythm as well as habitat dependency should be available. Changes in species distribution have to be analysed with respect to habitat suitability and anthropogenic pressures taking into account speciesspecific density thresholds, species-specific pressure sensitivity as well as within- and between-species competition. Time series data may provide information on reoccurring spatio-temporal patterns allowing for a differentiation between naturally driven variation and pressure based changes. Because of its tight linkage to waterbird abundance, this indicator should be used together with the indicator Abundance of wintering populations of waterbirds. For the time being focus shall be put on wintering seabirds. This pays tribute to the important role of the Baltic Sea as wintering area and goes along with the proposed core indicator on wintering seabird abundances. Being among the most abundant and ecologically dominating seabirds wintering in the Baltic Sea the following four species are proposed for the appliance of the presented indicator: Common Eider, Velvet Scoter, Common Scoter and Long-tailed Duck. Other species may be added. For the time being all species should be analysed separately interpreting indicator results on the species level only. In the future, as knowledge improves, the quantitative changes in distribution of several species may be integrated on the level of functional groups. Policy relevance The proposed indicator applies to the MSFD GES criteria 1.1 species distribution and the parameters distributional range (1.1.1) and distributional pattern (1.1.2) listed under descriptor 1. The EC Birds Directive requires special conservation measures for seabird species to ensure their survival and reproduction in their distribution areas. Measures specifically include classifying the most suitable territories as Special Protection Areas. Consequently assessments are required to provide information on the distribution of species for the designation of SPAs as well as ongoing monitoring schemes to detect changes in distribution to adapt management and secure conservation of the target species. The ecological objectives of the Baltic Sea Action Plan (BSAP) currently do not comprise targets and indicators for wintering waterbirds or distribution of waterbirds in general. However, the biodiversity segment of the BSAP includes the objective of natural landscapes and seascapes and the parameter percentage of important migration and wintering areas for birds within the Baltic Sea covered by the BSPAs, Natura 2000 and Emerald sites. This implies knowledge on the distribution of seabird species. Testing of the core indicator and examples from the literature The proposed indicator has not been used as such in the past nor have there been - to the knowledge of the authors - any attempts. However, seabird distribution and density measures have been used for the identification of Important Bird Areas and Special Protected Areas and are integral elements of environmental impact assessments. The underlying studies have detected relations between seabird distribution and anthropogenic activities. Demonstrations of how the 75 percentile of density measures can provide a robust indication of changes in main distribution areas of waterbirds can be found in the recently finished and soon to be published report of the SOWBAS (Status of wintering waterbird populations in the Baltic Sea) project. SOWBAS was launched in 2006 and carried out coordinated surveys of waterbirds in all Baltic waters during The project attempted to fill gaps in knowledge of the status and recent trends in the populations of wintering waterbirds in the Baltic Sea and provides a follow up of the first Baltic wide survey on 46

152 seabird distribution in (Durinck et al. 1994). Compared to the report covering the results from the first census the results from the new SOWBAS report have been achieved through the application of spatial modelling. The maps below demonstrate how percentile distributions (here the 75 percentile) can be used as a means to delineate the higher end of distributions of waterbirds in a region. The examples show comparisons of densities of Long-tailed Ducks wintering in the Bornholm Basin and Pomeranian Bay between the Baltic -wide surveys in and Despite big changes in absolute densities between the two periods the area of high habitat suitability marked by the 75 percentile provides a robust indication of changes in the main distribution pattern within the region between the two periods. 47

153 Figure. Comparisons of habitat suitability and densities of Long-tailed Ducks wintering in the Bornholm Basin and Pomeranian Bay between Baltic -wide surveys in and Source: SOWBAS Report 2011 by courtesy of H. Skov. Approach for defining GES All species respond differently to anthropogenic pressures. Therefore the targets, which show the boundary of GES must be set for each species separately. Based on data availability two different ways of determining GES are proposed. The GES boundary can be set as an acceptable deviation from a favourable reference value that is the potential distribution of a species defined by habitat suitability modelling. A different approach is to set a threshold value for acceptable/ required deviations from a reference state, e.g. as defined at the beginning of the assessment. The target would be resettlement of areas where anthropogenic pressures lead to avoidance behaviour or no further loss of habitat. The high naturally occurring spatio-temporal variations in species distribution (Garthe et al. 2008, Markones & Garthe 2009, Sonntag et al. 2010) have to be considered at all times and detailed spatial statistical analyses have to be developed. Existing monitoring data Currently there is almost a complete lack of internationally co-ordinated monitoring data on waterbirds, especially in offshore areas. Until today there have been only two Baltic wide studies on seabird distribution. In 1992, the first survey (ship transects) covering all major offshore areas was carried out by Ornis Consult (Durinck et al. 1994). This was followed up by international surveys from both aeroplane and ships in In 2006 the SOWBAS (Status of wintering Waterbird populations in the Baltic Sea) project was launched and carried out co-ordinated surveys of waterbirds in all Baltic waters during Other counts of wintering waterbirds in the Baltic Sea stem from the midwinter counts of Wetlands International. These counts generally cover birds of the coastal zone and lagoons, while offshore areas are surveyed only infrequently. In addition there are several national monitoring projects for the identification of IBAs and SPAs as well as regional projects including spatial-assessment of seabirds at sea such as the Baltic LIFE project. Germany, for example, conducts as part of the Seabirds at Sea program since the year 2000 ship- and airplane-based transect surveys assessing the distribution and abundance of seabirds within the German Baltic Sea area. Moreover, the German Federal Agency for Nature Conservation (BfN) commissions since 2009 a seabird monitoring within the framework of Natura 2000 with special focus on the German Exclusive Economic Zone. Additional research includes for example airplane-based transect counts in deep waters of the Baltic Sea (Markones et al. 2010). In depth information on the occurrence and distribution of seabirds in German waters can be found in Garthe (2003), BfN (2006), Mendel et al. (2008), Dries and Garthe (2009), Markones and Garthe (2009) and Sonntag et al. (2006, 2007, 2010). Below examples of the distribution of Common Eiders, Longtailed Ducks, Velvet Scoters and Common Scoters in the German Baltic Sea as of January/ February 2009 are displayed (Markones and Garthe 2009). 48

154 (a) Common Eider (b) Long-tailed Duck (c) Common Scoter (d) Velvet Scoter Figure. Distribution of (a) Common Eiders, (b) Long-tailed Ducks, (c) Velvet Scoters and (d) Common Scoters in the German Baltic Sea January/ February 2009 (airplane-based surveys). Source: Markones and Garthe Sampling It is suggested to include surveys of wintering seabirds with special emphasis on shallow offshore areas into the HELCOM Waterbird Monitoring which should fall under the COMBINE regulations. As a minimum requirement for a Baltic-wide monitoring programme for wintering waterbirds key habitats which may be regarded as holding significant proportions of the European wintering populations should be assessed. Monitoring should take place at times of highest occurrence (mid-winter) following standard procedures. In additional to surveying (principally transect surveying) individual animal tracking could be applied to explore distribution. While the first provides large scale information the latter may provide important additional background information for the interpretation of detected changes in distribution. Habitat association can be inferred by comparing the animal s locations with available habitat within the bird s potential range or directly by use of data loggers providing environmental data on prevailing oceanographic conditions. Moreover, animal tracking delivers high quality information on the individual, such as its activity and status which are important variables aiding in the interpretation of distribution and habitat association. Weaknesses/gaps As pointed out above, besides the naturally occurring spatio-temporal variation, also multiple pressures can be identified as playing an important (either negative or positive) role in the distributions of most species of waterbirds. Teasing out the relative influence of natural determinants and each pressure on the distribution and conservation status of every species requires detailed statistical analyses, which could not be developed within the 49

155 scope of this report. The proposed core indicator requires further work, but can be used tentatively in environmental assessments. In addition, the paper at hand aims at promoting a Baltic wide spatially explicit monitoring of seabirds especially in the offshore areas. References Bellebaum J., A. Diederichs, J. Kube, A. Schulz & G. Nehls (2006). Flucht-und Meidedistanzen überwinternder Seetaucher und Meeresenten gegenüber Schiffen auf See. Ornithologischer Rundbrief Mecklenburg- Vorpommern 45: BfN (2006). Beitrag zum Umweltbericht zur Raumordnung für die deutsche AWZ der Ostsee - Rastvögel Dries H & S. Garthe (2009). Trendanalysen von Seevögeln in den deutschen Meeresgebieten von Nord- und Ostsee; Endbericht für das Bundesamt für Naturschutz Durinck J., H. Skov, F.P. Jensen & S. Pihl (1994). Important marine areas for wintering birds in the Baltic Sea, Ornis Consult Report, Kopenhagen. Garthe S. (1997). Influence of hydrography, fishing activity, and colony location on summer seabird distribution in the south-eastern North Sea. ICES Journal of Marine Science 54: Garthe S. (2003). Erfassung von Rastvögeln in der deutschen AWZ von Nord- und Ostsee; F+E-Vorhaben FKZ: K 1 vom Bundesamt für Naturschutz Garthe S., O. Hüppop (2004). Scaling possible adverse effects of marine wind farms on seabirds: developing and applying a vulnerability index; Journal of Applied Ecology 41, Garthe S., V. Dierschke, T. Weichler & P. Schwemmer (2004). Rastvogelvorkommen und Offshore- Windkraftnutzung. Analyse des Konfliktpotenzials für die deutsche Nord- und Ostsee. Abschlussbericht des Teilprojektes 5 im Rahmen des Verbundvorhabens "Marine Warmblüter in Nord- und Ostsee : Grundlage zur Bewertung von Windkraftanlagen im Offshore Bereich (MINOS)", S Garthe S., N. Markones, P. Schwemmer, N. Sonntag, T. Dierschke, (2008). Zeitlich-räumliche Variabilität der Seevogel-Vorkommen in der deutschen Nord- und Ostsee und ihre Bewertung hinsichtlich der Offshore-Windenergienutzung. Abschlussbericht des Teilprojektes 5 im Rahmen des Verbundvorhabens "MINOS 2 Weiterführende Arbeiten an Seevögeln und Meeressäugern zur Bewertung von Offshore - Windkraftanlagen (MINOSplus). Lewis S., T.N. Sherratt, K.C. Hamer & S. Wanless (2001). Evidence of intra-specific competition for food in a pelagic seabird. Nature 412: Markones N., S. Garthe. (2009). Endbericht für den Werkvertrag Erprobung eines Bund/Länder-Fachvorschlags für das Deutsche Meeresmonitoring von Seevögeln und Schweinswalen als Grundlage für die Erfüllung der Natura Berichtspflichten mit einem Schwerpunkt in der deutschen AWZ von Nord- und Ostsee (FFH-Berichtsperiode ) - Teilvorhaben Seevögel Markones N., S. Garthe, V. Dierschke, S. Adler (2008). Small-scale temporal variability of seabird distribution patterns in the south-east North Sea; in: Wollny-Goerke K., Eskildsen K. (Eds.): Marine mammals and seabirds in front of offshore wind energy;teubner Verlag, Wiesbaden Markones N., N. Sonntag, S. Garthe (2010). Seevogelmonitoring in Nord- und Ostsee: Vogelbeobachtungen auf offenem Meer. Der Falke 57: Mendel B., N. Sonntag, J. Wahl, P. Schwemmer, H. Dries, N. Guse, S. Müller & S. Garthe (2008). Artensteckbriefe von See- und Waservögeln der deutschen Nord- und Ostsee, Verbreitung Ökologie und Empfindlichkeiten gegenüber Eingriffen in ihren marinen Lebensraum. Naturschutz und Biologische Vielfalt 61, Bad Godesberg, 436 S. Mendel B. & S. Garthe (2010). Kumulative Auswirkungen von Offshore-Windkraftnutzung und Schiffsverkehr am Beispiel der Seetaucher in der Deutschen Bucht. In Kenne et al. (Eds): Forschung für ein Integriertes Küstenzonenmanagement: Fallbeispiele Odermündungsregion und Offshore-Windkraft in der Nordsee. Coastline Reports 15: O'Driscoll R.L. (1998). Description of spatial pattern in seabird distribution along line transects using neighbour K statistics. Marine Ecology Progress Series 165: Petersen, I. K., T.K. Christensen, J. Kahlert, M. Desholm & A. D. Fox (2006). Final results of bird studies at the offshore wind farms at Nysted and Horns Rev, Denmark. NERI Report, commissioned by DONG Energy and Vattenfall A/S, DK. Pettersson, J. (2005). The impact of offshore wind farms on bird life in southern Kalmar Sound, Sweden. A final report based on studies Report to the Swedish Energy Agency. Siebert U., P. Schwemmer, N. Guse, S. Garthe (2009). Untersuchungen zum Gesundheitszustand von Seeund Küstenvögeln im Bereich der deutschen Nordsee 50

156 Sonntag N., Mendel B., Garthe S. (2006). Die Verbreitung von See- und Wasservögeln in der deutschen Ostsee im Jahresverlauf. Vogelwarte 44: Sonntag N., B. Mendel, S. Garthe (2007). Erfassung von Meeressäugetieren und Seevögeln in der deutschen AWZ von Ost- und Nordsee (EMSON) - Teilvorhaben Seevögel. F+E Vorhaben FKZ: Bundesamt für Naturschutz Sonntag N, N. Markones, S. Garthe (2010). Marine Säugetiere und Seevögel in der deutschen AWZ von Nordund Ostsee Teilbericht Seevögel. Bundesamt für Naturschutz 51

157 2.7. Fish population abundance 2.8. Mean metric length of key fish species 2.9. Fish community diversity Proportion of large fish individuals in the community Abundance of fish key trophic groups Fish community trophic index Authors and acknowledged persons of the coastal fish indicators: Magnus Appelberg, Jens Olsson, Håkan Wennhage, Antti Lappalainen, Kaj Ådjers, Markus Vetemaa, Outi Heikinheimo, Adam Leijk, Atis Minde, Iwona Psuty and all Members of the HELCOM FISH- PRO project. Introduction This description of core indicators focuses on the work done in the HELCOM FISH-PRO project (HELCOM 2011). The core indicators identified in the HELCOM CORESET project are meant to apply to a wider set of species and methodologies, developed elsewhere (e.g. ICES working groups, LIFE+ project MARMONI, etc) or in the second phase of the CORESET project in Some elements of that work can be seen in Chapter 4 of this report, where candidate indicators are described. Description of coastal fish indicators Indeces for coastal fish were developed for the following biodiversity levels within D1. GES Coastal fish Indeces Proposed core indicators criteria 1.2 Species Abundance Index Fish population abundance 1.3 Species Demographic Index Mean metric length of key fish species 1.6 Community Diversity Index, Community Size Index Fish community diversity, Proportion of large fish individuals in the community 1.6 Community Abundance Index Abundance of fish key trophic groups 1.7 Community Trophic Index Fish communitytrophic index Indices for coastal fish community status estimate changes over time within one monitoring area. The indices can potentially also be used for estimating differences among geographic areas, provided that the same monitoring method is applied in all areas to be compared (HELCOM, 2011). Coastal Fish - Species Abundance Index (D1.2.1) The index estimates the abundance of a key fish species in Baltic Sea coastal areas, such as Perch (Perca fluviatilis). Perch is a freshwater species that commonly dominates quantitatively coastal fish communities in the Baltic Sea (Ådjers et al., 2006). As such, areas of good ecological status generally have strong populations of Perch (Eriksson et al., 2011). The species is a piscivore in the adult stage and an appreciated target for both small scale commercial fisheries and recreational fishing (Swedish Board of Fisheries, 2011). The index reflects the integrated effects of recruitment and mortality. Recruitment success is expected to be mainly influenced by climate and quality of recruitment habitats. Mortality is influenced by fishing, but potentially also by predation from apex predators, such as seals, sea birds and fish. Policy relevance: The index will show if the abundance and productivity of Perch is at appropriate level for supporting coastal ecosystem function, focusing on food provision but 52

158 also reflecting the trophic state. In areas where the index does not signal good environmental status, GES may be achieved by restoration of recruitment habitats, improving water quality or regulating fishing pressure. Coastal Fish - Species Demographic Index (D1.3.1) The index reflects the size structure of a key fish species in Baltic Sea coastal areas, such as Perch (Perca fluviatilis), which was described in the section above. The index is based on the metric mean length of Perch, but the metric abundance of large Perch could be used as additional information or complement. The estimate mean length of Perch is expected to reflect changes in recruitment success as well as in mortality. Low levels may signal the appearance of a strong year class of recruits, decreased top down control in the ecosystem, or high fishing mortality, but potentially also density-dependent growth. High levels in the indicator may signal a high trophic state, but potentially also decreased recruitment success. Because of this, the indicator should be interpreted together with the Species Abundance Index. The estimate abundance of large Perch is calculated as the catch per unit effort of Perch larger than 25 cm. The estimate is expected to provide a more direct measure of fishing mortality on the actual species, as well as of ecosystem health. The index will, however, not be indicative of changes in the younger year-classes of the population. Policy relevance: The index will show if the size structure of Perch is at an appropriate level for supporting coastal ecosystem function, including food provision with a focus on trophic state. In areas where the index does not signal good environmental status, GES may be achieved mainly by regulating fishing pressure. Coastal Fish - Community Diversity Index (D1.6.1) The index reflects biological diversity at the community level and is based on the Shannon Index. High values reflect high species richness and low dominance of single species, whereas low values reflect the opposite. The index has both an upper and a lower boundary since very high levels of the index potentially also may reflect a decrease in the abundance of a naturally dominating species. Policy relevance: The index will indicate whether the biodiversity structure of coastal fish communities is at an appropriate level for supporting coastal ecosystem function, including ecosystem resilience, or not. The index reflects the general state of the fish community. In areas with sub-ges conditions, actions to achieve good ecological status should target the species level. Coastal Fish - Community Size Index (D1.6.1) The index reflects the general size structure at the community level and is based on estimates of the abundance of large fish (measured as catch per unit effort). Depending on the maximum mesh size of the gear, large fish are defined as individuals larger than 30 (Net series) or 40 (Coastal survey nets, Nordic coastal multi-mesh gillnets) cm. Generally, large fish are abundant in coastal communities indicative of good ecological status in the Baltic Sea (Pauly et al. 1998). The index is expected to mainly reflect changes in fishing mortality at the community level, where low values reflect increased fishing mortality. However, the value of the index may to some extent also be influenced by environmental conditions such as temperature and nutrient status. Policy relevance: The index will indicate if the size structure of coastal fish communities is at appropriate level for supporting coastal ecosystem function, including food provision and ecosystem resilience. In areas where the index does not signal good environmental status, GES may be achieved by mainly regulating fishing pressure. Coastal Fish Community Abundance Index (D1.6.2) The index is based on estimates of the abundance of two different functional groups: Abundance of Cyprinids and Abundance of Piscivores, and reflects the integrated effects of 53

159 recruitment and mortality of the species included in each functional group. Recruitment success is expected to mainly be influenced by the quality and availability of recruitment habitats, climate and eutrophication. Mortality is influenced by fishing, but predation from other animals, such as seals, sea birds and fish are also perceivable. The two metrics included in the index are expected to differ in their responses to anthropogenic pressure factors, in that Abundance of Cyprinids is expected to show the strongest link to eutrophication and Abundance of Piscivores the strongest relationship to fishing pressure. Policy relevance: The index will indicate whether or not the abundance and productivity of coastal fish communities is at appropriate level for supporting coastal ecosystem function and resilience, including food provision for man and other marine organisms. In areas where the index does not signal good environmental status, GES may be achieved by restoration of recruitment habitats for piscivores, reduction of nutrient loads, and by regulating mortality of piscivores by reducing fishing pressure and predation from apex predators. Coastal Fish - Community Trophic Index (D1.7.1) The index reflects the general trophic structure at the community level and is based on estimates of the proportion of fish at different trophic levels. Alternatively, estimates of the proportion of piscivores in the fish community may be used. The index provides an integrated measure of changes in the trophic state of the fish community. Typically, very low values of the index may reflect high fishing pressure on piscivores (Pauly et al. 1998) and/or domination of species favoured by eutrophic conditions. Since high levels of the index also may reflect a decreased abundance of some naturally dominating non-piscivore species the index has both an upper and a lower boundary. Policy relevance: The indicator will show if the trophic structure of the coastal fish community is at appropriate level for supporting coastal ecosystem function, including ecosystem resilience. The indicator reflects the general state of the fish community, and is likely to be closely linked to fishing pressure as well as eutrophication. In areas with sub- GES conditions, actions should target the species level. Method(s) used to test the indicators The metrics on which each index is based have previously been used for assessing the state of coastal fish communities in Sweden, Finland, Estonia, Latvia and Lithuania based on data coastal fish monitoring programs (as analyzed within the HELCOM Fish PRO group; HELCOM 2011). The suggested metrics were identified after evaluation of a range of parameters potentially reflecting coastal fish community status. The selection of metrics was based on multivariate analyses (PCA) of monitoring data where the signal strength, biological relevance and redundancy of individual parameters as suggested by Rice and Rochet (2005) were assessed (as analyzed within the HELCOM Fish PRO group; HELCOM 2011). In addition, the biological relevance of the metrics was mainly evaluated based on empirical observations. Relationship to anthropogenic pressures The relationship between metrics and anthropogenic pressures was assessed using a data set covering the Bothnian Bay, Bothnian Sea, Gulf of Finland and the Central Baltic Sea. Samples covered areas with different levels of natural and anthropogenic environmental pressures, and the relationship was analysed using distance-based linear modeling (DISTLM as implemented in PERMANOVA+ of PRIMER v6). The results in combination with expert judgments provided a basis for a preliminary concept of the relationship between the indicators and the pressures Fishing pressure and Eutrophication (see figure). The relationships will, however, be evaluated further. 54

160 Indicators of Ecological Status in Fish Communities FISHING Removing large and often predatory fish EUTROPHICATION Large individuals - - Piscivores - - Cyprinids Mean Trophic Level Piscivore proportion Other considerations In addition to the anthropogenic factors included above, the indices might potentially also be influenced by changes in ambient environmental conditions, such as temperature and salinity levels (Olsson et al., submitted). As such, these effects should be considered in the assessment of coastal fish community status (i.e. Carstenssen, 2007). The suggested approach for achieving this is presented in subsection 8. Approach for defining GES Analyses of the indices with respect to their temporal and spatial variation in the Baltic Sea showed that the expected values (in the absolute sense) are typically site specific, depending on local properties of the ecosystem such as topography and geographical position (as analyzed within the HELCOM Fish PRO group; HELCOM, 2011). Values are also highly dependent on the monitoring method used. This implies that defining a common GES boundary for a larger region should not be attempted, and that the GES boundary rather should be identified separately for each data set. In the suggested approach for achieving this, as presented below, the assessment of the ecological status of coastal fish communities is based on time series data where the state of the assessment period is contrasted against a reference data set. Because the data set does not reach long in the past, the reference data set does not represent necessarily pristine conditions. Definition of the reference data set For analyses of time series, the reference data set is defined by the following criteria - The minimum number of years to be included is at least two times the generation time of the species mainly influencing the index. The total number of years included is maximized based on available data, but does not include the years of the assessment period. - No significant trends of the reference data set are present. - The reference data set is judged by expert opinion in light of prevailing physiographic, geographic and climatic conditions and as either representing GES or sub-ges conditions, based on concurrent trends in the other related indicators or historical information. When a reference data set cannot be defined 55

161 If a reference data set cannot be identified based on the above criteria, trends in the available data are used to assess the environmental status. Prior to the assessment, the available data (not including the assessment period) in combination with other relevant information, is judged by expert opinion as either representing GES or sub-ges conditions. Criteria for GES within the assessment period In case of reference data set representing GES conditions In cases when a reference data set representing GES is used, for GES the median value of the indicator during the assessment period must be above the 5 th (or within the 5 th and the 95 th, depending on the index) percentile of the median distribution of the reference data set. The trend within the assessment period is given as supplementary information. If a reference data set cannot be identified, the long term trend in the whole monitoring data set is analyzed. For GES, the slope must not be significantly negative (or positive depending on the indicator). In case of reference data set representing Sub-GES conditions In cases when a reference data set for sub-ges is used, for GES the median value of the indicator during the assessment period must be above the 99 th percentile of the median distribution of the reference data set. If a reference data set cannot be identified, the long-term trend in the whole monitoring data set is analyzed. For GES, the slope must be significantly positive (or negative depending on the indicator). Proposed GES/subGES boundaries As described in section 2, the anticipated GES/subGES boundaries are data dependent and will be different for different monitoring areas and methods. The suggested approach for defining the GES boundary was described in section 4. Below, examples for GES determination in one area are provided for the indicators described earlier in this document. Kvädöfjärden Species Demographic Index Community Trophic Index Mean Length of Perch GES Mean Trophic Level SUB- SUB- GES SUB- SUB

162 Community Diversity Index Community Size Index Species Diversity Index SUB- SUB- GES Abundance of Large Individ GES SUB-GE Community Abundance Index Abundance of Piscivores GES SUB-GE Abundance of Cyprinids SUB- SUB- GES Out of the five indices outlined above, two indicate GES (Community Trophic Index and Community Size Index), whereas three indicate subges in that the diversity (Community Diversity Index) and demographic characteristics (Species Demographic Index) is above the expected distribution of the reference data set, and the abundance of piscivores (Community Abundance Index) is below the expected distribution. Further testing of the suitability of the boundaries for GES will be elaborated in the nearest future. Existing monitoring data Coastal fish monitoring is performed annually all over the Baltic Sea. The HELCOM Fish PRO Project includes data from monitoring areas in Finland, Estonia, Latvia, Lithuania and Sweden (HELCOM 2011). Coastal fish communities in the Baltic Sea areas of Denmark, Poland and Russia are monitored as well, but were not included in the present evaluation of metrics used for assessing coastal fish community status (as analyzed within the HELCOM Fish PRO group). The longest time series is 22 years, but several were initiated as late as in the 2000s. 57

163 Table 1. Existing monitoring areas of Coastal Fish in the Baltic Sea. Years in parentheses indicates last year of monitoring. Area Country Basin Nordic coastal multi-mesh net Coastal survey nets Net series Råneå Sweden Gulf of Bothnia (2004) Kinnbäcksfjärden Sweden Gulf of Bothnia 2004 Holmön Sweden Gulf of Bothnia Norrbyn Sweden Gulf of Bothnia 2002 Gaviksfjärden Sweden Gulf of Bothnia 2004 Långvindsfjärden Sweden Gulf of Bothnia 2002 Haapasaaret Finland Gulf of Finland 2003 (2008) Kaitvesi Finland Gulf of Bothnia 2005 Helsinki Finland Gulf of Finland 2005 Forsmark Sweden Gulf of Bothnia Finbo Finland Gulf of Bothnia (2008) Kumlinge Finland Gulf of Bothnia 2003 Brunskär Finland Gulf of Bothnia (2004) Tvärminne Finland Gulf of Finland 2005 Lagnö Sweden Baltic Proper 2002 Hiiumaa Estonia Baltic Proper 1991 Asköfjärden Sweden Baltic Proper 2005 Kvädöfjärden Sweden Baltic Proper Vinö Sweden Baltic Proper 1995 Daugavgriva Latvia Gulf of Riga 1995 Jūrkalne Latvia Baltic Proper 1999 Torhamn Sweden Baltic Proper 2002 Curonian lagoon Lithuania Baltic Proper

164 Sampling The coastal fish monitoring takes place in August and reflects trends in species that occur in coastal areas during the warm season of the year. Fishing is performed using survey nets that mainly target demersal and benthopelagic species, but some pelagic species are also captured (HELCOM 2008). Three different monitoring methods are used around the Baltic Sea (HELCOM 2008). In the Baltic Proper, the longest time series data are from monitoring using Net series, which consists of four 30 m long and 1.8 m deep nets. Each net is made up of a single mesh size, 17, 21.5, 25 and 30 (in Latvia also 38) mm (knot to knot), respectively. In the Bothnian Sea, Coastal survey nets are used. These nets are 35 m long, 3 m deep and are composed of five 7 m long panels with mesh sizes 17, 21, 25, 33 and 50mm (knot to knot). In both methods, fishing is repeated three nights at each position. Sampling method using Nordic coastal multi-mesh nets was introduced in 2001 (Appelberg et al. 2003). This gear is 45 m long, 1.8 m deep and is composed of nine mesh sizes (10, 12, 15, 19, 24, 30, 38, 48 and 60 mm, knot to knot). A random depth-stratified sampling design is applied. Typically, 45 positions are distributed over four different depth intervals; 0-3 m, 3-6 m, 6-10 m and m. Each position is fished with one net for one night. A minimum of 10 stations are fished in each depth interval down to 10 meters depth, and a minimum of 5 stations in the deepest depth interval. The method is currently used only in Finland and Sweden, where it is routinely used in all areas established after Monitoring by all methods is performed at fixed stations. The gears are set between and and lifted the next day between and Catches at each station are registered as numbers per species and length group (2,5 or 1 cm), separately for each mesh size (or net). Additionally, wind strength and direction, water temperature, and water transparency measured using a Secchi disc, are routinely monitored during the fishing period. Additional data sources such as commercial catch statistics based on EU-data collection system, coastal echo sounding, etc. might serve as a complement if the data proves to be of enough quality to assess the biodiversity of coastal fish communities. Methodology of data analyses Index computation Species Abundance Index. The indicator is estimated as the catch per unit effort of the key species (i.e. Perch) within the target size range of the gear used. Species Demographic Index. The indicator is estimated as the mean length of all individuals of the key species (i.e. Perch) within the target size range of the gear used and/or the catch per unit effort of all Perca fluviatilis equal to or above 20 cm length. Community Diversity Index. The indicator is the Shannon index calculated based on catch per unit effort of all species targeted by the gear used and within its target size range. Community Size Index. The indicator is the catch per unit effort of individuals equal to or larger than 30 (Net series) or 40 (Coastal survey nets and Nordic coastal multi-mesh nets) cm of all species targeted by the gear used, within its target size range. Community Abundance Index. The index includes measures of catch per unit effort of the groups of Cyprinids and Piscivores, respectively. The group Cyprinids includes all species within the Cyprinidae, and the group piscivores includes all species with a trophic level equal to or higher than 4.0 according to Fish Base ( Community Trophic Index. The index represents the mean trophic level of the community and is based on catch per unit effort of all species targeted by the gear used, within its target size range. The trophic level of each species is based on values from Fish Base ( and the index is calculated as Σ (Trophic level x Relative 59

165 Abundance)species i. As a complement, the proportion of piscivores is used, defining piscivores as species with a mean trophic equal to or above 4, according to Fish Base. Target species and size range In order to only include species and size-groups suited for quantitative sampling by the method, individuals smaller than 12 cm (Nordic Coastal multimesh nets) or 14 cm (Net series, Coastal survey nets), and all small-bodied species (gobies, sticklebacks, butterfish), and species with eel-like body forms (taeniform, anguilliform or filiform shapes) are excluded (HELCOM 2011). Weighting For Nordic Costal multimesh nets, the analyses are based on weighted means of data from all depth strata, in order to account for the depth-stratified sampling design. Corrections For all data sets, the relationship between of the indicators to local temperature and salinity was checked prior to further analyses. If the correlation was significant, further analyses were performed based on the remaining variation (regression residuals). Weaknesses/gaps The current monitoring program does not provide full spatial coverage, and is mainly targeting areas with relatively low levels of direct anthropogenic influence. Currently, methods for extrapolating the results to areas without monitoring are under development. Given the current state of knowledge, it is suggested that the status classifications achieved for monitored areas are extrapolated to areas without monitoring by direct interpolation in combination with expert opinion. Alternatively, additional data sources such as commercial catch statistics based on EU-data collection system, coastal echo sounding, etc. might serve as a complement if the data proves to be of enough quality to assess the biodiversity of coastal fish communities. Extended data collection with a focus on polluted areas is being performed in 2011 and will bring further knowledge on natural environmental factors driving spatial variation in indicator values and the relationship of indicators to anthropogenic pressure factors, such as eutrophication and fishing pressure. References Ådjers, K., Appelberg, M., Eschbaum, R., Lappalainen, A., Minde, A., Repecka, R. and Thoresson, G Trends in coastal fish stocks in the Blaltic Sea. Boreal Environment Research, 11: Appelberg, M., Holmqvist, M. and Forsgren, G An alternative strategy for coastal fish monitoring in the Baltic Sea. ICES Annual Scicence Conferens, Sept. 2003, Tallinn, Estonia. 13 p. Carstensen, J Statistical principles for ecological status classification of Water Framework Directive monitoring data. Marien Pollution Bullentin, 55: 3-15 Eriksson, B. K., Sieben, S., Eklöf, J., Ljunggren, L., Olsson, J., Casini, M., and Bergström, U Effects of altered offshore food webs on coastal ecosystems emphasizes the need for cross-ecosystem management. Ambio, DOI /s HELCOM Assessment on conservation status of coastal fish in the Baltic Sea Submitted to HELCOM MONAS for approval, HELCOM Guidelines for HELCOM coastal fish monitoring sampling methods. Olsson, J., Bergström, L. and Gårdmark, A. Abiotic drivers of coastal fish community change during the last four decades in the Baltic Sea. Submitted manuscript. Pauly, D., Christensen, V., Dalsgaard, J., Froese, R. and Torres Jr., F Fishing down marine food webs. Science, 279: Rice, J.C. and Rochet, M-J A framework for selecting a suite of indicators for fisheries management. ICES Journal of Marine Science, 62: Swedish Board of Fisheries Resurs och Miljööversikt In Swedish. 60

166 2.13. Multimetric macrozoobenthic indices 1. Working team Benthic habitats and associated communities 2. Name of core indicator Multimetric diversity indices of benthic macrofauna communities (B, BBI, BQI, DKI, MarBIT, ZKI) or species richness 3. Unit of the core indicator Unitless (but based on abundance, ind./m 2, data) 4. Description of proposed indicator The indicator shows the diversity of benthic macroinvertebrate communities. The indicator can be calculated by various indices, which all have their own GES boundaries (e.g. relation of sensitive, tolerant species, abundance and taxonomic composition). The indicator describes the condition of the biological component/habitat. The species are sensitive to general contamination of the sediment, physical disturbance and to hypoxic events. It is suggested that the offshore areas of the Baltic Sea are measured by sub-basin wide species richness based on the work by Vilnäs & Norkko (2011), until the applicability of the benthic quality index has been tested. This species richness indicator has also been used as an eutrophication core indicator. 5. Functional group or habitat type all soft sediment habitats (hydrolittoral, infralittoral, circalittoral, below the halocline) 6. Policy relevance Descriptor 1, criterion 1.6 Habitat condition Descriptor 6, criterion 6.2 Condition of the benthic communities BSAP: Ecological objectives Natural distribution and occurrence of plants and animals (Eutrophication) and Thriving communities of plants and animals (Nature conservation) 7. Use of the indicator in previous assessments In the WFD assessments, HELCOM thematic assessments of eutrophication and biodiversity. 8. Link to anthropogenic pressures Faunal communities are adversely affected by the eutrophication, changes in water and sediment quality and hydrographic conditions such as salinity, temperature. Therefore coastal construction works or water outflows affecting hydrography and general decrease in water and sediment quality due to increased eutrophication, turbidity, silt content and input of hazardous substances decrease the species richness of macrozoobenthos at sites. Slight eutrophication improves species richness and diversity, but severe eutrophication reduces diversity, making it therefore difficult to use this indicator for an assessment direct/indirect impact Physical disturbance (due to abrasion, smothering, changes in siltation) reduces the species richness and diversity direct impact Physical loss (due to sealing or selective extraction) reduces the species richness and diversity direct impact Introduction of synthetic compounds (due to ship accidents or harbours) reduces the species richness and diversity direct impact Changes in the hydrological conditions (due to changes in salinity and/or temperature) reduces the species richness and diversity direct impact 9. Pressure(s) that the indicator reflect Input of fertilizers and organic matter, Introduction of synthetic compounds, Introduction of non-synthetic substances and compounds, Introduction of radio-nuclides, Changes in 61

167 siltation, Abrasion, Smothering, Sealing, Selective extraction of seabed resources, Changes in salinity regime, Changes in thermal regime. 10. Spatial considerations Baltic wide but with sub-regional references. 11. Temporal considerations Annual frequency. 12. Current monitoring Monitored by all Contracting States. 13. Proposed or perceived target setting approach with a short justification. Targets (used here for GES boundaries) for the indices in coastal waters have been set by the Contracting Parties under the EU WFD (Baltic GIG). Targets in the offshore have been proposed in Vilnäs & Norkko (2011). Introduction The multimetric macrozoobenthic indices have been developed under the EU Water Framework Directive in the EU Member States. The limitation of these indices is their applicability to national territorial waters only. To fill this gap, HELCOM thematic assessment of eutrophication (HELCOM 2009) presented an offshore indicator for macrozoobenthic invertebrates, which was developed by Villnäs and Norkko (2011). In this brief summary of the macrozoobenthic indices, only references to national work has been given and the second phase of the CORESET project will fully apply these indeces when the outcome of the Baltic wide intercalibration work under the Eu Water Framework Directive has been published. Offshore indicator: sub-basin wide species richness The offshore areas of the Baltic Sea were agreed in the CORESET Biodiversity Expert Group to be provisionally assessed by the indicator, which calculates a sub-basin wide species richness, i.e. gamma diversity. The indicator and its GES boundaries have been described by Villnäs & Norkko (2011) and in the HELCOM core indicator report for eutrophication. The indicator was also used in the HELCOM thematic assessment of eutrophication (HELCOM 2009). The HELCOM TARGREV project has further developed the species richness indicator and linked it to environmental conditions, such as hypoxia. The GES boundaries for the indicator in the sub-basins were set on the basis of historical data and standard deviations from those (Villnäs & Norkko, 2011). Reference values and acceptable deviations for the indicator were based on long-term monitoring data at >200 monitoring stations during 1964iation Data from ~1800 sampling occasions was used. Generally only stations with a depth >40 m were included and anoxic and/or hypoxic periods (<2 ml O 2 /L) were excluded from the data. The reference value for each sub-area was identified as the average of the 10% highest annual average regional diversity values during the monitoring period. Acceptable deviation from reference conditions determines the Goodle deviation from reference conditi critical border between an acceptable and non-acceptable condition of benthic diversity (cf. the EU Water Framework Directive) and it should incorporate natural variation and decadal time-scale fluctuations of species numbers in an area. Based on the long-term data used for identifying reference conditions, the acceptable deviation was defined as the relative standard deviation of average regional diversity in a sub-area per year. An average acceptable deviation for each sub-area was based on data from several years. The highest acceptable deviation allowed was set to 40%. The Gllowed was set tfined by subtracting the acceptable deviation from the reference value. 62

168 The indicator responds mainly to the anthropogenic eutrophication, which causes hypoxia and anoxia in bottom waters (Pearson and Rosenberg 1978, Hyland et al. 2005, Norkko et al. 2006). The indicator reflects the increase in nutrient levels only indirectly and therefore the quantitative relationship to nutrient levels is difficult to ascertain. The relationship has however been found in the Bothnain Bay, where the background concentrations of nutrients are relatively low (HELCOM 2009). Increasing amounts of nutrients were seen to result in a surplus of organic material, leading to large fluctuations in benthic diversity as sensitive, large-sized and long-lived species did not tolerate the altered consitions. At more advanced stages of organic enrichment, the diversity starts to decline. The single strongest factor influencing the benthic diversity is, however, hypoxia. Figure 1. The reference values, good-moderate border and assessment of the offshore macrozoobenthos indicator. Source: HELCOM The national indices and the used sieve size for sampling Finland: Brackish Water Benthic Index BBI (BQI and shannon), 5 pooled Ekman grabs, 0.5 mm sieve. Reference: Perus et al. (2007). Estonia: ZKI (biomass based), 0.25 mm sieve (Anon. 2007) Latvia: BQI, Van Veen, 0.5 mm sieve Lithuania: BQI (and number of species per sample), Van Veen, 0.5 mm sieve Poland: B, 1 mm sieve(?) Germany: MarBit, vanveen, 1 mm sieve, Kautsky frame, 1 mm sieve Denmark: DKI v2 (salinity corrected), Van Veen and Haps, 1 mm sieve Reference: Josefson et al Sweden: Benthic Quality Index BQI, Van Veen, 1 mm sieve Reference: Blomqvist et al. (2007) Intercalibration of the coastal indices in the Baltic GIG An overview of the intercalibration process is described in Carletti and Heiskanen (2009). The report describes all the national methods, gives background information of their responses to anthropogenic pressures, compares them to each other and describes the target setting procedures and the targets themselves. References Anon Report of the Estonian assessment method and the preliminary evaluation of the comparability with methods from other Baltic Sea countries is presented in the Baltic Sea Milestone Report 6. Quality 63

169 element: Benthic Fauna. Version 16 June Rev. 3, 30 March Available at: in folder: GIG Milestone Reports Błeńska M., Osowiecki A., Kraśniewski W., Piątkowska Z., Łysiak-Pastuszak E Macrozoobenthos quality assessment in the Polish Part of the Southern Baltic Sea using a biotic index B. ICES Annual Science Conference Handbook. s Blomqvist, M., Cederwall, H., Leonardsson, K. & Rosenberg, R Bedömningsgrunder för kust och hav. Bentiska evertebrater Rapport till Naturvårdsverket pp. (in Swedish with English summary) Carletti, A. & Heiskanen, A-S. (2009): Water Framework Directive intercalibration technical report. Part 3: Coastal and transitional waters. JRC Scientific and Technical Reports. HELCOM Thematic Assessment of eutrophication. Balt. Sea Envin. Proc. No. 115 B. Available at: Hyland, J., L. Balthis, I. Karakassis, P. Magni, A. Petrov, J. Shine, O. Vestergaard, and R. Warwick Organic carbon content of sediments as an indicator of stress in the marine benthos. Marine Ecology Progress Series 295: Meyer. T-, Reincke, T., Fuerhaupter, K. & Krause, S. (2005) Ostsee-Makrozoobenthos-Klassifiriezungssystem fur die Wasserrahmrichtlinjie. Technical Report. Bericht im Auftrag des Landesamtes fur Natur und Umwelt Schleswig-Hollstein. Norkko, A., R. Rosenberg, S. F. Thrush, and R. B. Whitlatch Scale- and intensity-dependent disturbance determines the magnitude of opportunistic response. Journal of Experimental Marine Biology and Ecology 330: Pearson, T. H., and R. Rosenberg Macrobenthic succession in relation to organic enrichment and pollution of the marine environment. Oceanography and Marine Biology: an Annual Review 16: Perus, J., Bonsdorff, E., Bäck, S., Lax, H-G., Westberg, V. Villnäs, A Zoobenthos as indicator of ecological status in coastal brackish waters: A comparative study from the Baltic Sea. Ambio 36 (2-3): Villnäs, A. & Norkko, A. (2011): Benthic diversity gradients and shifting baselines: implications for assessing environmental status. Ecological Applications 21:

170 2.14. Lower depth distribution limit of macrophyte species 1. Working team Benthic habitats and associated communities 2. Name of core indicator Lower depth distribution limit of macrophyte species 3. Unit of the core indicator m (valid for last specimen or minimum coverage value of 10%) 4. Description of proposed indicator This indicator follows the depth distribution limits (last specimen or minimum coverage value of 10%) of specific sensitive species, which are important for habitat structure (key-species) and perennials with a persistent biomass for a certain time scale adapted to stable conditions (K- Strategy). The indicator describes the condition and abundance of a habitat-forming macrophyte species and indirectly the condition for all the associated flora and fauna. The deeper the macrophyte extends, the larger is the volume of the habitat, thus, supporting more viable populations, having more diverse species assemblages, offering feeding grounds for predators and ensuring enough spawning grounds for pelagic fish. As habitat builders, these macrophyte species are the representative indicators for all species (macrophytes, epifauna, small fish) associated to this kind of habitat/phytal community. The indicator has been established in the coastal waters of the EU Member States, whereas it does not yet contain the offshore waters (reefs) where the GES boundary needs to be estimated. 5. Functional group or habitat type Infralittoral hard substrata Infralittoral sediments 6. Policy relevance Descriptor 1, Criteria 1.5 Habitat extent and 1.6 Habitat condition Descriptor 5, Criterion 5.1 Direct effects of nutrient enrichment Descriptor 6, Criterion 6.1 Kind and size of relevant biogenic substrata BSAP: Ecological objectives Natural distribution and occurrence of plants and animals (Eutrophication) and Thriving communities of plants and animals (Nature conservation) 7. Use of the indicator in previous assessments WFD assessment in Denmark (eelgrass), Estonia (Fucus), Finland (Fucus), Germany (Fucus, eelgrass, charophytes), Lithuania (Furcellaria for coastal and transitional waters along the Baltic coast; Potameids for transitional waters (the Curonian lagoon) and Sweden (several species). The intercalibration of the national indicators was not finalized. Has been used in the HELCOM thematic assessments of eutrophication and biodiversity, but the geographical distribution of the indicator was limited. 8. Link to anthropogenic pressures Reduced water transparency (due to input of fertilizers, organic matter and physical disturbance- increased turbidity) causes a reduced light availability and a reduction in depth distribution of macrophytes indirect impact. Increased nutrient availability increases the abundance of opportunistic algae growing also on perennial algae and overshadowing them. Physical disturbance (due to abrasion, smothering, changes in siltation) reduces the photosynthetic rates of macrophytes resulting in a loss at the lower depth limit (reduction in depth distribution) direct impact. 9. Pressure(s) that the indicator reflect 65

171 Input of fertilizers, Input of organic matter, Changes in siltation, Abrasion, Smothering 10. Spatial considerations Fucus vesiculosus Baltic-wide (except inner Gulf of Finland and the Bothnian Bay). Charophytes: Baltic-wide in sheltered habitats with reduced salinities (lagoons). Furcellaria: Baltic-wide (except inner Gulf of Finland and Northern part of Bothnian Bay). Eelgrass: from Kattegat to Archipelago Sea and mid-gulf of Finland (to mean surface salinity of 6 8 psu), missing from the Polish, Lithuanian and Latvian open coasts. Other angiosperms (Ruppia, Potamogeton): Baltic-wide in sheltered habitats with reduced salinities (lagoons). 11. Temporal considerations Annual data should be aimed at, but less frequent data may be also adequate as the changes in the depth distribution may take years. Harmonization of the sampling method may be required. 12. Current monitoring Part of WFD monitoring in several EU Member States (see 7). 13. Proposed or perceived target setting approach with a short justification. Reference values and classification can be achieved by light models and/or historical data but the direct correlation of the indicator to the pressure can be interfered by biological competition for space. Intercalibration of the targets (here used as GES boundaries) was initiated but not finalized in the EU expert group for Water Framework Directive Baltic GIG. They are based on old data sets (Reference conditions + Acceptable deviations) and expert judgment. Targets for some species have been estimated on the basis of wide datasets in varying environmental conditions. A slow-reacting indicator due to long recovery time of perennials. Introduction The core indicator for macrophytes is an indicator for coastal waters and shallow offshore waters (i.e. offshore reefs). Various macrophyte indicators have been developed under the EU Water Framework Directive, which apply to national territorial waters. The national indicators or indexes cover not only depth distribution parameters but some also include parameters for coverage, species proportions, species richness or densities. In order to have a joint parameter to the set of core indicators, the HELCOM CORESET project decided first to focus on the depth distribution core indicator. This is measured currently by at least 7 of the 9 countries. Because extensive reports are available for the national indicators and methodologies, this short description of the indicator is only referring to them. When the outcome of the Baltic intercalibration work under the EU WFD is published, the national approaches will be presented in detail and differences and similarities in methodologies will be discussed more thoroughly. National approaches to assess macrophytes Danish and German intercalibration of angiosperms is presented in Carletti & Heiskanen Denmark: - Eelgrass depth limit, the depth at the 5% cover (Krause-Jensen et al. 2005) - Total erect macroalgae cover - Number of perennial macroalgae species - Ratio of opportunistic macroalgae (% cover) Estonia: 66

172 - Estonian Phytobenthos Index EPI follows the maximum depth limit of the attached macrovegetation, including bladderwrack. - Proportion of perennial species. Finland: - Bladderwrack lower depth limit Germany: - Lower depth limit of stands of >10% cover (Schories et al. 2006) - BALCOSIS is a multimetric index, which was developed for outer coastal waters (type B3), and includes a parameter for depth distribution (>10% density) (for further description see - ELBO is a composition indicator, which was developed for inner coastal waters, and includes a parameter for depth distribution (Steinhardt et al. 2009). Poland: - a biomass x cover indicator for 18 species (MQAI) (Osowiecki et al. 2010). Latvia: no method Lithuania: - Furcellaria depth limit in the open coast - Potamogeid depth limit in the Curonian lagoon Sweden: - multispecies maximum depth index (maximum depth for 3-9 species) References Krause-Jensen D, Greve TM, Nielsen K Eelgrass as a bioindicator under the Water Framework Directive. Water Resources Management 19: Schories D, Selig U, Schubert H Testung des Klassifizierungsansatzes Mecklenburg-Vorpommern (innere Küstengewässer) unter den Bedingungen Schleswig-Holsteins und Ausdehnung des Ansatzes auf die Außenküste. Küstengewässer-Klassifizierung deutsche Ostsee nach EU-WRRL. Teil A: Äußere Küstengewässer. Steinhardt et al. (2009) The German procedure for the assessment of ecological status in relation to the biological quality element Macroalgae & Angiosperms pursuant to the WFD for inner coastal waters of the Baltic Sea. Rostocker Meeresbiol. Beiträge Heft 22 Osowiecki A., Łysiak-Pastuszak E., Kruk-Dowgiałło L., Brzeska P., Błeńska M., Kraśniewski W., Lewandowski Ł., Krzymiński W An index-based preliminary assessment of the ecological status in the Polish marine areas of the Baltic Sea. Proceedings of the Third International Symposium on Research and management of Eutrophication in Coastal Ecosystems June Nyborg, Denmark. pp

173 2.15. Trend in the arrival of new non-indigenous species 1. Working team: Non-indigenous species Authors: Manfred Rolke, Maiju Lehtiniemi, Malin Werner, Alexader Antsulevich, Monika Michalek-Pogorzelska. Acknowledged persons: Paulina Brzeska, Elena Gorokhova, Bożenna Kaczmaruk and Solvita Strake 2. Name of core indicator Trend in the arrival of new nonindigenous species 3. Unit of the candidate indicator number of new arrivals against a baseline per sixyears assessment period 4. Description of proposed indicator The indicator follows numbers of non-indigenous species found in an assessment area within an assessment period of six years. The indicator requires a baseline study, identifying the number of already arrived non-indigenous species. Every new non-indigenous species (NIS) arriving after the baseline year is counted as a new species. New NIS comprises not only established organisms but all new identified species even if they will not establish (because species which cannot establish stable populations, as also short living introductions, will be regarded as a failed management). New NIS that have already been counted will not be added to the baseline and not be added to the counts of future periods. 5. Functional group or habitat type From phytoplankton to vertebrates. Data sampled from harbours, main shipping lanes and anchoring places and nature conservation areas 6. Policy relevance Descriptor 2 BSAP ecological objective: no new introductions of non-indigenous species. 7. Use of the indicator in previous assessments None 8. Link to anthropogenic pressures Directly impacted by: Ballast water exchange, introductions for mariculture or aquaria, biofouling, unintentional introductions by pleasure boats. 9. Pressure(s) that the indicator reflect The indicator reflects mainly the impact of shipping, but it is difficult to distinguish that from other vectors of NIS. 10. Spatial considerations The information should ideally cover the assessment units (national coastal and offshore waters divided to sub-basins) but at least the sub basins separately and include harbours, main shipping lanes, anchoring places and nature conservation areas 11. Temporal considerations The indicator should be assessed every six years, but data should be collected continuously. 12. Current monitoring The COMBINE biological monitoring can be used as the basis. Gaps should be covered by strengthening the focus on new species identification and by extending the areal coverage as needed, particularly on areas near (or in) harbors, shipping lanes and anchoring sites. 13. Proposed or perceived target setting approach with a short justification. GES boundary refers to the BSAP objective No new introductions and is based on the implementation of the IMO Ballast Water Convention. GES is reached when no new introductions are found per assessment period. 68

174 Introduction Draft Example for German, Swedish and Polish waters - Data must be updated and other countries included The introduction of invasive species into oceanic waters and especially coastal waters is among the four highest risks for our marine environment and can cause extremely severe environmental, economic and public health impacts. These non-indigenous invaders can induce considerable changes in the structure and dynamics of marine ecosystems. They may also hamper the economic use of the sea or even represent a risk for human health. Environmental impacts comprise changes of marine communities changing e.g. the structure of the food web by outcompeting original inhabitants. Economic impacts range from financial losses in fisheries to expenses for cleaning intake or outflow pipes and structures from fouling. Public health impacts may arise from the introduction of microbes or toxic algae. Different vectors are made responsible for human introduced non-indigenous species (NIS). In some cases, NIS have been deliberately introduced for fishing or aquaculture, but most have been brought by ships, which can rapidly transport aquatic animals, plants and algae across the world in their ballast waters and attached to their hulls. A problem for the non-indigenous species issue is that, once a marine organism has been introduced to its new environment, it is nearly impossible to eradicate the unwanted organism, if it has established to the area. The consequence is that assessing a status of an area as bad means that the area will stay in the bad status without the possibility to return to the past condition. Therefore the status of the NIS in the Baltic Sea is described by a trend of the number of new arriving NIS. The number of new species in each assessment unit during a six-year assessment cycle is first of all an indication of the pressure the NIS cause on the native ecosystem, but it is also an indication of management success with the IMO Ballast Water Convention and ballast water treatment and it encourages to take measures against new invaders instead of futile effort or fatalistic inactiveness in view of effects of established ones. The indicator uses primarily species data from the conventional biodiversity monitoring programmes, but also additional information about new arrivals must be gathered, for example, harbours or in the vicinity of main shipping lanes where ships exchange their ballast water or in the vicinity of areas used for aquaculture. The impact on native communities, another indicator requested by MSFD, will be automatically covered by monitoring for other descriptors or for WFD assessment of environmental status. Policy relevance Since the early 90s when the Marine Protection Committee (MEPC) of the International Maritime Organisation (IMO) put the NIS issue on the agenda, the problem got more and more weight in marine environmental protection. In 2004, the Ballast Water Convention was adopted by the IMO. The convention asks for ballast water management procedures to minimize the proliferation of non-indigenous organism with ballast water. Once entered into force every ship has to follow ballast water management procedures. In order to minimize adverse effects of introductions and transfers of marine organisms for aquaculture ICES drafted the ICES Code of Practice on the Introductions and Transfers of Marine Organisms. The Code of Practice summarizes measures and procedures to be taken into account when planning the introduction of non-indigenous species for aquaculture purposes. On the European level, the EC Council Regulation No 708/2007 concerning the use of NIS and locally absent species in aquaculture is based on the ICES Code of Practice. 69

175 With the maritime activities segment of the Baltic Sea Action Plan HELCOM expresses the strategic goal to have maritime activities carried out in an environmental friendly way and that one of the management objectives is to reach No introductions of alien species from ships. In order to prepare the implementation of the Ballast Water Convention a road map was established with the ultimate to ratify the BWM Convention by the HELCOM Contracting States preferably by 2010, but in all cases not later than In the Baltic Sea Action Plan (in the Roadmap towards harmonised implementation and ratification of the 2004 International Convention for Control and Management of Ships Ballast Water and Sediments), the CPs agreed to adjust/extend by 2010 the HELCOM monitoring programmes to obtain reliable data on non-indigenous species in the Baltic Sea, including port areas, in order to gather the necessary data to conduct and/or evaluate and consult risk assessments according to the relevant IMO Guidelines. As a first step, species that pose the major ecological harm and those that can be easily identified and monitored should be covered. The evaluation of any adverse ecological impacts caused by nonindigenous species should form an inherent and mandatory part of the HELCOM monitoring system. The good environmental status (GES) according to the EU Marine Strategy Framework Directive is to be determined on the basis of eleven qualitative descriptors. One of the qualitative descriptors concerns non-indigenous species and describes the GES for this descriptor as Non-indigenous species introduced by human activities are at levels that do not adversely alter the ecosystem. 70

176 Figure 1. Number of non-indigenous species in the assessment units in These values are used as baselines for the indicator; all new introductions during the assessment period are counted in this indicator. The species present in the assessment units have been reported by the experts of HELCOM HABITAT and HELCOM MONAS and HELCOM MARITIME in several occasions during The data spreadsheet is a living document, open for revision. The data is shown in a table in the section Dataset on trends in arrival of non-indigenous species. Temporal trends in arrival of non-indigenous species Figure 1 shows the number of species in each assessment unit in This is the baseline for the assessment period of Figure 2 presents the rate of introductions of NIS to the Baltic Sea starting from the beginning of the 19th century. Altogether 120 nonindigenous species have been found in the Baltic Sea marine environment (excluding terrestrial mammals and waterbirds). In the sections below, rates of introductions in the past and during the assessment period are presented for each country separately. Figure 2. Introductions of non-indigenous species to the Baltic Sea. Source: HELCOM Germany Altogether 23 organisms are known to be introduced in the German Baltic Sea excluding inland waters. Assuming that the influence of man before the industrial revolution (< 1850) can be regarded as negligible, the natural rate of introductions for this area is one and represents a percentage of around 4% of the present total amount of introductions. In the following time until the 1960s of the last century the number of recognized introductions increased only slightly with an average of two (representing 9% of the present total amount). Beginning of the 1970s an appreciable rising of new introductions can be recognized with a maximum of 7 recognized organisms (representing 30% of all introductions). 71

177 Fig. 3: Rates of detected non-indigenous species in the German Baltic Sea for 20-year intervals between 1850 and 2006 (Gollasch and Nehring 2006) Sweden Figure 4 shows the rate of introductions of NIS to Sweden, excluding the west coast (Kattegat and Skagerrak). The introductions have increased greatly during the last four decades. Altogether 39 NIS have been found from the Swedish waters in the Baltic Sea. Fig. 4: Rates of detected non-indigenous species in the Swedish Baltic Sea for 20- year intervals between 1850 and 2010 ( Altogether 39 NIS have been found from the Swedish waters on the Baltic Sea side, excluding Kattegat. Poland Figure 5 shows the rate of introductions of NIS to the Polish marine waters. Altogether 36 NIS have been found from the Polish marine waters. No consistent increase or decrease in the introductions can be seen during the studied time period unless the 72

178 recent increase during the last four decades can be seen as an indication of a new wave of introductions Number of species Number of species 0 < Decades Fig. 5: Rates of detected non-indigenous species in the Polish waters for 20-year intervals between 1850 and 2011 ( Binpas). Altogether 36 NIS have been found. GES and classification method The ultimate goal is to minimize man made introductions of non-indigenous organisms to zero. The boundary between GES and sub-ges is no new introductions of NIS per assessment unit during a six year assessment period. The indicator requires an estimation of the already existing NIS in each area and counts of new introductions. Hence, it is important to distinguish between naturally spreading and anthropogenically introduced species. In reality in some cases it is impossible to distinguish between man-made and natural introductions and therefore all species are first treated as NIS and only species which can be shown to be naturally spreading will be removed from the indicator. The BSAP Roadmap towards harmonised implementation and ratification of the 2004 International Convention for Control and Management of Ships Ballast Water and Sediments (HELCOM 2007, p. 99) presents some advice on this matter (see Introduction above). Systematic studies on NIS introductions are very scarce in the past, especially in the marine area. Therefore, for the purpose of this indicator, reviews and national databases are taken as a basis for an estimation of the baseline (Germany: Gollasch and Nehring 2006, Poland: Binpas data, Sweden: Existing monitoring Data sources are the HELCOM monitoring programme fed by the national monitoring programmes. Proven information provided by other sources such as research institutes can also be used. 73

179 Sampling and data analyses Number of species. All neobiota independent of their state of establishment have to be taken into account. The indicator assesses the entire Baltic Sea: national coastal and offshore waters divided to sub-basins. Currently, the monitoring of coastal and estuarine biodiversity is not structured enough to reliably show the distribution and abundance of several non-indigenous species. As a result of this robustness, assessments must be made on a sub-basin scale. The indicator is assessed by a six year assessment period. Yearly data based on at least two sampling exercises per year for an assessment period of six years. Figure 6. Map of Polish monitoring stations in the Baltic Sea. Strengths and weaknesses of data Strengths: The approach shows promise to give an indication of the success of measurements to minimize the man-made introduction of non-indigenous species. It has harmonized targets in the Baltic Sea. It is a simple measurement. Weaknesses: differences in national data sets, quality problems of old data, geographical and temporal gaps in sampling. Existing data are usually from times where non-indigenous species did not play an important role in the monitoring. Intensified and structured monitoring might identify more non-indigenous species already present in some areas. References Carlton, J.T. (1985). Transoceanic and interoceanic dispersal of coastal marine organisms: the biology of ballast water Oceanogr. Mar. Biol. Ann. Rev. 23: EC, 2007: Council Regulation (EC) No 708/2007 of 11 June 2007 concerning use of alien and locally absent species in aquaculture. Official Journal of the European Union, 17pp EC, 2008: Directive 2008/56/EC of 17 June 2008 establishing a framework for community action in the field of marine environmental policy (Marine Strategy Framework Directive). Official Journal of the European Union, 22pp Gollasch, S. and S. Nehring, 2006: National checklist for aquatic alien species in Germany. Aquatic Invasions 1 (

180 ICES, 2005: ICES CODE of Practice on the Introductions and Tranfers of Marine Organisms 2005, 30pp IMO, 2004: International Convention for the Control and Management of Ships Ballastwater and Sediments, IMO document BMW/Conf/36, 38pp 75

181 3. Proposed core indicators for hazardous substances and their effects This chapter presents the proposed core indicators for hazardous substances and their effects on biota. The CORESET expert group for hazardous substances has come up with 13 core indicators, which will be proposed to be finalized as core indicator reports during the project. All the proposed core indicators have targets that show the boundary for good environmental status (GES). The GES boundaries were primarily selected among the EU environmental quality standards (EQS), but it is good to acknowledge that many of the EQS have not been finalized and accepted in the revision process of EQS and the EU Priority Substances 10. The presented EQS for biota and sediment are, hence, provisional and need to be revisited in light of progress of EQS development in the EU and experience gained in their environmental application. All the proposed core indicators are listed in the summary table below and the following sections will provide descriptions of the proposed core indicators, including background documentation. Each core indicator has been given a separate section, following the numbering of the summary table. Table 3.1. Proposed core indicators for hazardous substances and their effects. Proposed core indicators Parameters 1. Polybrominated biphenyl ethers Congeners 28, 47, 99, 100, 153, Hexabromocyclododacene Hexabromocyclododacene (HBCD) 3. Perfluorooctane sulphonate Perfluorooctane sulphonate (PFOS) 4. Polychlorinated biphenyls and dioxins and furans CB congeners 28, 52, 101, 118, 138, 153 and 180. WHO-TEQ of dioxins and furans and dioxin-like PCBs. 5. Polyaromatic hydrocarbons and their metabolites The US EPA 16 PAHs in bivalves and sediment and selected metabolites in fish. 6. Metals Cadmium (Cd), mercury (Hg) and lead (Pb) 7. Radioactive substances Caesium Tributyltin compounds / imposex index Tributyltin and/or imposex index 9. Pharmaceuticals Diclofenac and 17-alphaethinylestradiol 10. General stress indicator Lysosomal membrane stability 11. General stress indicator for fish Fish disease index 12. Genotoxicity indicator Micronucleus induction 13. Reproductive disorders Malformed embryos of eelpout and amphipods 10 The EQS are developed in the WFD working group E. Draft version are available in the respective folder in CIRCA. 76

182 3.1. Poly Brominated Diphenyl ethers (PBDE) Author: Jaakko Mannio Acknowledged persons: Anders Bignert, Elin Boalt, Anna Brzozowska, Galina Garnaga, Michael Haarich, Jenny Hedman, Ulrike Kamman, Thomas Lang, Martin M. Larsen, Kari Lehtonen, Rita Poikane, Rolf Schneider, Doris Schiedek, Jakob Strand, Joanna Szlinder-Richert, Tamara Zalewska General information 11 General properties (e.g. herbicide, lipophilic, bioaccumulating, persistence, volatile) The polybrominated diphenyl ethers (polybde) are diphenyl ethers with degrees of bromination varying from 2 to 10. Among these polybdes which are mainly used as flame retardants, three are available commercially: pentabde commercial product, octabde commercial product and decabde commercial product. However, these products are all a mixtures of diphenyl ethers as shown in the table hereunder. Therefore, to differentiate pentabde commercial product and octabde commercial product from pentabde substance and octabde substance, respectively, these commercial products will be referred to as c-pentabde and c-octabde in the present fact sheet. All polybde's are hydrophobic or very hydrophobic substances, are very likely to adsorb on particulate matter and not likely to volatilize from water phase. PBDEs have the potential to photodegrade in the environment. Overall, measured BCF values for BDE congeners range from very low values for highly brominated congeners (<5) to very high values for lower brominated congeners (up to (measured value) for tetrabde). Main impacts on the environment and human health Endocrine disrupter (Category 2) for humans, meaning potential for endocrine disruption. In vitro data is indicating potential for endocrine disruption in intact organisms. Also includes effects in-vivo that may, or may not, be ED-mediated. May include structural analyses and metabolic considerations. PBDEs have also been shown to have hormone-disrupting effects, in particular, on estrogen and thyroid hormones. Has been shown to disturb development of the nervous system. Status of a compound on international priority lists and other policy relevance The substances pentabde and octabde have been prioritised through 2 consecutive prioritisation procedures under the WFD: pentabde was prioritised following COMMPS (COmbined Monitoring-based and Modelling-based Priority Setting scheme) procedure in 2001, while octabde has recently been prioritised in the context of the second European Commission proposal for a new list of priority substances, for the reason that it is a PBT (Persistent, Bioaccumulative and Toxic) and a vpvb (very Persistent and very Bioaccumulative) substance. Following this latter prioritisation and the fact that pentabde EQS needed to be revised, it was decided in the WFD procedure to produce a unique fact 11 Points 1-5 mostly from EU/CIRCA WFD /WGE draft dossier 22 Dec

183 sheet reporting a common EQS for all BDE congeners linked to c-pentabde and c- octabde, that is to say tetra- to nona-bde congeners (draft in CIRCA). PBDEs are on the HELCOM BSAP priority list and in the Stockholm Convention Annex A (Elimination). Status of restrictions, bans or use PolyBDE, including pentabde and octabde, are mainly used as flame retardants. The use of pentabde and octabde is however restricted within the EU since August 15, 2004 (Commission regulation (EC) No 552/2009). PentaBDE and OctaBDE are not allowed to be placed on the market as substances, in mixtures or in articles in higher concentration than 0.1% by weight. Furthermore, use of polybdes in electrical and electronic products (E&Es) was restricted even earlier by the Directive 2002/95/EC (RoHS). From June 30, 2008, this directive covers also DecaBDE. This implies that the only permitted use of PBDEs in Europe is now the application of decabde in products other than E&Es. As a result of this new regulation, the majority of the previous use of decabde in the EU is now prohibited (corresponding to ca 80 percent of the total EU use in 2001). It is, however, still possible for industries to apply for exemptions for certain applications under the procedure laid out in article 5 of the RoHS Directive. PentaBDE is now included in Annex A (Elimination) to the Stockholm Convention and should no longer be on the EU market as well as hexabde and heptabde contained in c- octabde. GES boundaries and matrix Existing quantitative targets As for aquatic ecotoxicity, results are available mainly for the commercial mixtures of c- pentabde and c-octabde. The information on individual congener is insufficient to determine the contribution of each compound to the overall toxicity of the mixtures. The lowest NOEC= 0.4 mg kg -1 food is derived from a test in which pregnant rats administered a single dosage of c-pentabde exhibited reduced sperm production in male offspring at adulthood. Considering the data set available, it is proposed to use this worst case value for the determination of the QS biota, sec. pois. The choice of this value based on a mixture of low brominated compounds can be justified by the growing indications that polybde have the tendency to debrominate either in organisms or environmental compartment (pers. comm., POP Review Committee, 2010). WFD WG E draft proposal for Environmental Quality Standards (dossier 22 Dec 2010) Protection objective Unit Value Pelagic community (freshwater) µg.l -1 ] Pelagic community (marine water) µg.l -1 ] Benthic community (freshwater) µg.kg -1 dw] 22.9 µg.l -1 ] Benthic community (marine) µg kg -1 dw] 4.5 µg.l -1 ] Predators (secondary poisoning) µg.kg -1 biota ww] 4 µg kg -1 biota ww 78

184 µg.l -1 ] µg kg -1 biota Human health via consumption oww] fishery products µg.l -1 ] Human health via consumption of water µg.l -1 ] (freshwater) (marine waters) (Critical QS) (freshwater) (marine waters) QS for protection of human health is the critical QS for derivation of an Environmental Quality Standard for the sum of polybrominated diphenyl ethers. The Scientific Committee on Health and Environmental Risks (SCHER) agreed that the sum of all PBDEs is the relevant approach and that the WS for human health is the most critical EQS (SCHER 2011). Kinetic properties of PBDEs indicate that these compounds have dioxin-like, bioaccumulating properties in mammals (de Winter-Sorkina et al., 2006). The methodology for derivation of the threshold level was the same as has been applied to the dioxin 2,3,7,8- TCDD, as proposed by JECFA (Joint expert committee on food additives; JECFA (2002) as quoted in de Winter-Sorkina et al., 2006). The threshold value is derived on the basis of kinetic calculations combined with extrapolation factors. The TLhh of 0.26 ng kg -1 bw d -1 should be used for the derivation of the QS biota, hh. Preferred matrix Biota (e.g. fish and mussels) is the primary matrix and sediment is the secondary matrix. Monitoring the compound Status of monitoring network (geographical and temporal coverage) PBDE Sedime nt profile surface frequen cy (y) Biota species organ stations Frequency (y) Water Stations Frequency (y) Denmark eelpout liver 12 1 flounder liver 5 1 Germany herring liver 1 1 cod liver 1 1 dab liver 1 1 Poland (muscle) (3) project Russia Sweden SGU? 16?? herring muscle cod liver 2 1 guillemot eggs 1 1 Finland 4 >5 herring muscle 4 1 (2 screen) >5 perch muscle 2 1 Estonia (herring + perch) (muscle) (5) project (5 project) Lithuania (9 project) 3 (herring+flounder) (muscle) (2) project 1 1 Latvia (herring + perch) (muscle) (2) project (2 project) 79

185 Gaps in the monitoring of the compound Sweden, Denmark, Finland and Germany have permanent monitoring presently on fish. Germany prepares for monitoring in sediment. Estonia, Latvia, Lithuania and Poland have screening or research data. No information from Russia. Present status assessments Known temporal trends (also from sediment core profiles) A Swedish study found significant increasing trend from the end of 1960s until the end of 1990s followed by a decreasing trend during the last 10 years for BDE47, BDE99 and BDE100 level in the eggs of the guillemots nesting on Stora Karlsö Island west of Gotland. The spatial analysis of BDE levels in herring muscle during do not show any firm geographical differences, except that the levels of BDE47, 99, 100, 153 and 154 in the Southern Baltic Proper seem to be higher than in the other six sites from Skagerrak to Bothnian Bay. In general, BDEs seem to be more evenly distributed in the Swedish marine environment compared to, e.g. PCBs (Bignert et al. 2006). Spatial gradients (incl. sources) The HELCOM thematic assessment of hazardous substances in the Baltic Sea showed that concentrations of the congener BDE-47 (a tetrabde) in fish exceeded the selected threshold (5 µg kg -1 lw) in several parts of the sea area (HELCOM 2010). PentaBDE concentrations in biota (e.g. in herring and seal blubber) are higher in the Baltic Sea compared to the west coast of Sweden in the 1980s. Furthermore, concentrations increased with the age of the fish and were higher in seals than in fish in the Baltic Sea, indicating bioaccumulation and biomagnifications (EU-RAR 2000). In Denmark, the highest contamination with BDEs was found in sediment and mussels close to populated urban areas. The congener BDE47 is both bioconcentrated and biomagnified to a higher degree than any other congeners, whereas the amount of BDE99 decrease at higher trophic levels. The Swedish sediment monitoring programme, covering 16 stations in the coastal and offshore areas of the Baltic Sea, showed that concentrations of BDE47, BDE99 and BDE100 were clearly the highest in the Kattegat, 0,4-0,6 µg/kg dw (BDE209 not reported). The occurrence of BDEs is widespread in the Baltic marine environment. It is probable that current legislative measures (penta- and octabde banned in the EU since 2004) have already decreased penta- and octabde levels in the Baltic Sea. While PentaBDE and octabde do not seem to pose a risk to the marine environment in the Western Baltic Sea, the situation may be different in the eastern part of Baltic Sea. Information on the occurrence of penta-, octa- and decabde in the eastern Baltic Sea (e.g. in biota) and in discharges (e.g. WWTPs) and emissions, especially from eastern HELCOM contracting Parties, is thus greatly needed. More information on the occurrence of penta-, octa- and decabde discharges from e.g., landfills and waste sorting sites is needed from the whole Baltic Sea area. Recommendation DecaBDE is the dominant congener from sources (e.g. WWTPs) and in the Baltic Sea sediments; it can also be found in Baltic Sea fish, although tetrabde is the most dominant congener in biota. Levels of decabde may be increasing because its use has not been restricted. However, because of the environmental problems of decabde and anticipating 80

186 regulatory measures, the European industry has taken voluntary action to reduce releases of decabde. This would be expected to lead over time to decreasing concentrations. PBDEs with smaller molecules are more toxic and bioaccumulative. The biotic and abiotic debromination of highly brominated BDEs, such as decabde, to these smaller forms is a possibility and justifies that monitoring is based on a broad set of congeners. PBDE are recommended to be included as a core indicator. References Bignert, A., Nyberg, E., Asplund, L., Eriksson, U. & Wilander, A Metals and organic hazardous substances in marine biota, trend and spatial monitoring (Metaller och organiska miljögifter i marin biota, trend- och områdesövervakning). 122 p. Swedish Museum of Natural History. EU-RAR European Union Risk assessment on pentabromodiphenyl ether. Final report. European Union Risk assessment report p. European Chemicals Bureau. HELCOM (2010) Hazardous substances in the Baltic Sea An integrated thematic assessment of hazardous substances in the Baltic Sea. Balt. Sea Environ. Proc. No. 120B. Available at: SCHER (2011) Scientific Committee on Health and Environmental Risks. Opinion on "Chemicals and the Water Framework Directive: Draft environmental quality standards". DG Health & Consumer Protection, European Commission. de Winter-Sorkina R., Bakker M.I., Wolterink G. and Zeijlmaker M.J. (2006). Brominated flame retardants: occurrence, dietary intake and risk assessment. RIVM rapport RIVM, Bilthoven, the Netherlands 81

187 3.2. Hexabromocyclododecane (HBCD) Author: Jaakko Mannio Acknowledged persons: Anders Bignert, Elin Boalt, Anna Brzozowska, Galina Garnaga, Michael Haarich, Jenny Hedman, Ulrike Kamman, Thomas Lang, Martin M. Larsen, Kari Lehtonen, Rita Poikane, Rolf Schneider, Doris Schiedek, Jakob Strand, Joanna Szlinder-Richert, Tamara Zalewska General information 12 General properties (e.g. herbicide, lipophilic, bioaccumulating, persistence, volatile) The commercially available brominated flame retardant hexabromocyclododecane (HBCD or HBCDD) is lipophilic, has a high affinity to particulate matter and low water solubility. Depending on the manufacturer and the production method used, technical HBCD consists of 70-95% γ-hbcd and 3-30% of α- and β-hbcd. HBCD has a strong potential to bioaccumulate and biomagnify. Available studies demonstrate that HBCD is well absorbed from the rodent gastro-intestinal tract. Of the three diastereoisomers constituting HBCD, the α-form is much more bioaccumulative than the other forms. HBCD is persistent in air and is subject to long-range transport. HBCD is found to be widespread also in remote regions such as in the Arctic, where concentrations in the atmosphere are elevated. The low volatility of HBCD has been predicted to result in significant sorption to atmospheric particulates, with the potential for subsequent removal by wet and dry deposition. The transport potential of HBCD was considered to be dependent on the longrange transport behaviour of the atmospheric particles to which it sorbs. Main impacts on the environment and human health HBCD is very toxic to aquatic organisms. In mammals, studies have shown reproductive, developmental and behavioral effects with some of the effects being trans-generational and detectable even in unexposed offspring. Besides these effects, data from laboratory studies with Japanese quail and American kestrels indicate that HBCD at environmentally relevant doses could cause eggshell thinning, reduced egg production, reduced egg quality and reduced fitness of hatchlings. Recent advances in the knowledge of HBCD induced toxicity includes a better understanding of the potential of HBCD to interfere with the hypothalamicpituitary-thyroid (HPT) axis, its potential ability to disrupt normal development, to affect the central nervous system, and to induce reproductive and developmental effects. HBCD has been found in human blood, plasma and adipose tissue. The main sources of exposure presently known are contaminated food and dust. For breast feeding children, mothers milk is the main exposure route but HBCD exposure also occurs at early developmental stages as it is transferred across the placenta to the foetus. Human breast milk data from the 1970s to 2000 show that HBCD levels have increased since HBCD was commercially introduced as a brominated flame retardant in the 1980s. Though information on the human toxicity of HBCD is to a great extent lacking, and tissue concentrations found in humans are seemingly low, embryos and infants are vulnerable groups that could be at risk, particularly to the observed neuroendocrine and developmental toxicity of HBCD. 12 Points 1-5 mostly from EU/CIRCA WFD /WGE draft dossier 22 Dec

188 The HELCOM thematic assessment of hazardous substances in the Baltic Sea showed that HBCD exceeds threshold values in several parts of the Baltic Sea and increasing trends have been found in the eggs of common guillemot (HELCOM 2010). Status of a compound on international priority lists and other policy relevance HBCD has attracted attention as a contaminant of concern in several regions, by international environmental forums and academia. In the EU, HBCD has been identified as a Substance of Very High Concern (SVHC), meeting the criteria of a PBT (persistent, bioaccumulative and toxic) substance pursuant to Article 57(d) in the REACH regulation. In December 2009, HBCD was considered by the Executive Body (EB) of the UNECE Convention on Long-Range Transboundary Air Pollution (LRTAP) to meet the criteria for POPs, set out in EB decision 1998/2. It is a substance (group) of specific concern to the Baltic Sea and candidate for revised WFD Priority Substance list. HBCDD is on the HELCOM BSAP priority list. Status of restrictions, bans or use In the EU, HBCD has been identified as a Substance of Very High Concern (SVHC), meeting the criteria of a PBT (persistent, bioaccumulative and toxic) substance pursuant to Article 57(d) in the REACH regulation. In May 2009, HBCD was included in the European Chemicals Agency (ECHA) recommendation list of priority substances to be subject to Authorisation under REACH, based on its hazardous properties, the volumes used and the likelihood of exposure to humans or the environment. A proposal on classification and labeling of HBCD as a possible reprotoxic substance is currently under discussion within the EU (Proposal for Harmonised Classification and Labelling, Based on the CLP Regulation (EC) No 1272/2008, Annex VI, Part 2 Substance Name: Hexabromocyclododecane Version 2, Sep. 2009). GES boundaries and matrix Existing quantitative targets WFD WG E draft proposal for Environmental Quality Standards (dossier 19 Jan 2011). Protection objective Unit Value Pelagic community (freshwater) [µg.l -1 ] 0.31 Pelagic community (marine waters) [µg.l -1 ] Benthic community (freshwater) [µg.kg -1 dw] 860 [µg.l -1 ] Benthic community (marine) [µg.kg -1 dw] 170 [µg.l -1 ] [µg.kg -1 biota ww] 167 (Critical QS) Predators (secondary poisoning) [µg.l (freshwaters) ] (marine waters) Human health via consumption of fishery products Human health via consumption of water [µg.kg -1 biota ww] 6100 [µg.l (fresh and marine ] waters) [µg.l -1 ] 83

189 QS for secondary poisoning is the critical QS for derivation of an Environmental Quality Standard. The Scientific Committee on Health and Environmental Risks (SCHER) agreed that the QS for secondary poisoning of top predators is the most critical EQS (SCHER 2011). Preferred matrix Sediment and biota are preferred. The measured data on HBCD concentration in Baltic Sea water is very scarce and the detection limit has been too high to draw any conclusions (HELCOM 2010). Monitoring the compound Status of monitoring network (geographical and temporal coverage) HBCD Sedime nt profile surface frequen cy (y) Biota species organ stations Frequency (y) Water Stations Frequency (y) Denmark screening screening Germany Poland 3 fish in project (muscle) (2) (2 proj) Russia Sweden SGU? herring muscle cod liver 2 1 guillemot egg 1 1 Finland >5 (pike) (muscle) (3) project (2 screen) >5 Estonia (herring+perch) (muscle) (5) project (5 proj) Lithuania (herring+flounder) (muscle) (2) project 1 1 Latvia (herring+perch) (muscle) (2) project (2 proj) Gaps in the monitoring of the compound Only Sweden has permanent monitoring presently. Denamrk includes HBCD in 2011 in monitoring. Germany does not monitor HBCD in biota, but water monitoring in under development and sediment monitoring in a planning phase. Finland, Estonia, Latvia, Lithuania, Poland and Denmark have screening data. No information from Russia. Present status assessments Known temporal trends (also from sediment core profiles) HBCD is found to be widespread in the global environment, with elevated levels in top predators in the Arctic. In biota, HBCD has been found to bioconcentrate, bioaccumulate and to biomagnify at higher trophic levels. Swedish trend studies show an increase of HBCD in the guillemot eggs until recent years. Its increased presence in the environment is likely attributable to the increased global demand. The general trend is to higher environmental HBCD levels near point sources and urban areas (waste disposal sites including those whose processes include either recycling, landfilling or incineration). 84

190 The Swedish results show that HBCD levels in Baltic Sea fish are generally low and always lower than the estimated PNEC level. (Also the levels in the sediments of the Swedish coastal area are very low compared to the estimated PNEC level (170 µg/kg dw)). A temporal analysis (EU-RAR 2006) showed that HBCD levels in seals in the Baltic Sea have increased. The median levels in the 1980s ranged between 16 and 35 μg/kg lw with a median concentration of 28 μg/kg lw (n=7). In the 1990s, the levels ranged between 34 and 177 g/kg lw with a median of 73 μg/kg lw (n=12). From 2000, data from only one seal are available and has a HBCD concentration of 64 μg/kg lw. However, another study found that the HBCD level in the blubber of 30 grey seals during ranged from μg/kg lw with a mean of 101 μg/kg lw. The results indicate that the HBCD levels in seals have not decreased. Spatial gradients (incl. sources) The spatial analysis of HBCD levels in herring muscle during does not show any firm geographical differences, except that the level in the Southern Baltic Proper seems to be higher than another six sites from Skagerrak to Bothnian Bay. In general, HBCD seems to be more evenly distributed in the Swedish marine environment compared to, e.g. PCBs (Bignert et al. 2006). Recommendation HBCD can commonly be found in fish from the Swedish coastal area of the Baltic Sea. However, the situation may be different in other parts of the Baltic Sea. Thus, information on the occurrence of HBCD in the Baltic Sea (e.g. in biota) and in discharges (e.g. WWTPs, landfills and waste sorting sites) and emissions in the HELCOM countries is greatly needed. The need to include in CORESET is to some extent contradictory: - PBT and HPV substance with limited restrictions in use, high priority or candidate in many lists - but found levels (scarce data) relatively low compared to presented effect levels. HBCD is recommended to be included as a core indicator. References Bignert, A., Nyberg, E., Asplund, L., Eriksson, U. & Wilander, A Metals and organic hazardous substances in marine biota, trend and spatial monitoring (Metaller och organiska miljögifter i marin biota, trend- och områdesövervakning). 122 p. Swedish Museum of Natural History. EU-RAR European Union Risk assessment on hexabromocyclododecane. Draft October European Union Risk assessment report p. European Chemicals Bureau. 85

191 3.3. Perfluorooctane sulphonate (PFOS) Based on the HELCOM Thematic assessment of hazardous substances, chapter on PFOS by Urs Berger and Anders Bignert Acknowledged persons: Elin Boalt, Anna Brzozowska, Galina Garnaga, Michael Haarich, Jenny Hedman, Ulrike Kamman, Thomas Lang, Martin M. Larsen, Kari Lehtonen, Jaakko Mannio, Rita Poikane, Rolf Schneider, Doris Schiedek, Jakob Strand, Joanna Szlinder-Richert, Tamara Zalewska General information General properties Perfluorooctane sulfonic acid (PFOS), perfluoro octanoic acid (PFOA) and other perfluorinated compounds are considered as global environmental contaminants. PFOS and PFOA are chemically and biologically inert and very stable (Poulsen et al. 2005). PFOS meets the P (Persistent) and vp (very Persistent) criteria due to slow degradation. PFOS is also bioaccumulative (B) and toxic (T) (RPA & BRE 2004, OSPAR 2005). PFOA is considered as very persistent (vp) and toxic (T), but not bioaccumulative (Van der Putte et al. 2010). It has a capacity to undergo long-range transport. PFOS related substances and PFOA are members of the larger family of perfluoroalkylated substances (PFAS). Perfluorooctanyl sulfonate compounds are all derivatives of PFOS and can degrade to PFOS, also called as PFOS-related compounds. The abbreviation PFOA is used as a group name for perfluorooctanoic acid and its salts. Some PFOSrelated compounds have been identified (KEMI 2006). PFOS binds to blood proteins and bioaccumulates in the liver and gall bladder unlike most POP compounds, which accumulate into fat (Renner 2001). Some indicative compounds related to use are presented e.g. in HELCOM report on selected hazardous substances (HELCOM 2009). Main impacts on the environment and human health PFOS has been shown to disturb immune system, development and reproduction (encrine disruption) of organisms and influence the lipid metabolism, to reduce weight gain and food consumption. It is also suspected to induce liver necrosis. Status of a compound on international priority lists and other policy relevance PFOS is included in the Stockholm Convention list of POPs, Annex B, which requires the parties to the convention to restrict the production and use of the substance. The HELCOM Baltic Sea Action Plan has the objective of Hazardous substances close to natural levels and PFOS and PFOA are chosen as priority substances under the BSAP. PFOS is included on the revision list of the EU Priority Substances. The EU Marine Strategy Framework Directive requires that contaminants are at levels that do not give rise to pollution effects (GES Descriptor 8). Status of restrictions, bans or use The production and use of perfluorooctane sulfonate (PFOS), one of the major PFA representatives, have been regulated in some countries (e.g., Canada and the EU), but large-scale PFOS production continues in other parts of the world. 86

192 Pathways of PFOS to the Baltic ecosystem Some PFAS have been manufactured for more than five decades. They are applied in industrial processes (e.g., production of fluoropolymers) and in commercial products such as water- and stain-proofing agents and fire-fighting foams, electric and electronic parts, photo imaging, hydraulic fluids and textiles. PFOS is both intentionally produced and an unintended degradation product of related anthropogenic chemicals. PFOS is still produced in several countries. GES boundaries and matrix Existing quantitative targets The threshold values originate from the report of the EU expert group on the review of priority substances. The threshold values are final drafts and should be changed if the final values will change. The threshold value for biota is the Quality Standard for human health via fishery products (9.1 µg kg-1 ww), because it is stricter than the QS for secondary poisoning of predators (33 µg kg-1 ww). The Scientific Committee for Health and Environmental Risks supported this choice of the WFD WG E (SCHER The QS for marine waters is 0.23 µg l-1. Currently, there is no QS for benthic organisms (sediment). Preferred matrix Fish and sediment are appropriate matrixes to be used in the monitoring of PFOS in the Baltic Sea. Instead, water is more appropriate matrix to be used in the monitoring of PFOA. Sediment data is currently not appropriate for the core indicator, because of the lack of a proper threshold value. Monitoring the compound Status of monitoring network (geographical and temporal coverage) Only Sweden has PFOS in the national monitoring programme. Danish monitoring programme will include PFOS in The data in this assessment has been sampled between 2003 and Swedish National Monitoring Programme for biota (years ). HELCOM SCREEN project, data from 2008 (Lilja et al. 2009). Project of the Federal Environmental Agency, Germany. Data from (Theobald et al. 2007). Strand, et al. (2007). DMU (NERI) Rapport 608. Data from Nordic Council of Ministers (NMR) (2004): TemaNord 2004:552. Data from Gaps in the monitoring of the compound There is a need to include PFOS in several CPs monitoring programme. Present status assessments Concentrations and temporal trends of PFOS in the Baltic Sea 87

193 Exponentially increasing concentrations of some PFAs in wildlife have been reported during the 1990s (Holmström et al. 2005). According to the HELCOM thematic assessment of hazardous substances in the Baltic Sea (HELCOM 2010), PFOS concentrations are generally below threshold levels, but frequently exceed them in many parts of the Baltic Sea. The PFOS and PFOA levels in fish and water seem to be similar in different parts of the Baltic Sea. There is not enough data to assess temporal changes in PFOS concentrations in fish. However, the data covers several fish species and blue mussel and can therefore be considered quite exhaustive, whereas the lack of time series inhibits a making of a comprehensive assessment. Assessment of temporal trends of PFOS Figure. Concentration of PFOS in eggs of common guillemot (Uria aalge) from 1968 to The mean annual PFOS value shown as red dot in the figure of the time series is based on pooled samples or mean values of individual samples. Source: HELCOM According to Swedish data on common guillemot eggs, a significant increasing trend is observed for PFOS in guillemot eggs with 7-10% per year (Figure), which is equal to an increase to times higher levels in the early 2000s as compared to the late 1960ties (Bignert et al. 2009). Concentrations in fish exceed the threshold level PFOS levels in fish liver (e.g. herring, perch, pike, eelpout, flounder, eel and cod) exceeded the threshold level for the protection of predators via secondary poisoning (9.1 µg/kg wet weight in prey tissue; see section on targets below) in several areas of the Baltic Sea (HELCOM 2010). Thus, PFOS may cause adverse effects for top predators. One of the highest concentrations was found from the liver of pike (Esox lucius) from the Gulf of Finland (close to Helsinki and Espoo) containing 200 to 550 μg PFOS kg 1 ww, as well as up to 140 μg kg 1 ww of PFOSA, a non-persistent precursor compound of PFOS (Nordic Council of Ministers, 2004). Additional hot spots seem to be the mouth of the river Oder in the Bornholm Basin (coast of Poland; Lilja et al. 2009), the Hanö Bight (Bornholm Basin, coast of Sweden; SEPA, 2006) and the Kattegat (Nordic Council of Ministers, 2004). In all these regions, fish liver values of around 60 µg PFOS kg -1 ww have been observed (perch, cod and eelpout, respectively). In regions less affected by anthropogenic pollution, typical PFOS levels in fish liver were in the range 1 20 μg kg 1 ww. However, for wildlife or general human consumption, whole body or muscle concentrations would be more relevant as food matrices, which so far have 88

194 not been found to exceed the PNEC value for PFOS. Compared to liver, PFOS concentrations in muscle were lower, typically in the range <1 to 5 μg kg 1 ww (Theobald et al. 2007, Berger et al. 2009b). In blue mussels from the Kattegat, Great Belt and the Sound, PFOS was below the detection limit of 0.2 μg kg 1 ww (NERI 2007). The distribution of PFOS in herring liver was found to be quite homogeneous throughout the Baltic Sea (around 10 μg kg 1 ww), which probably is a result of the extraordinary persistence of the compound and its use for more than three decades. A somewhat higher level of 26 μg kg 1 ww was found along the Swedish coast of the Northern Baltic Proper, reflecting the proximity of the city of Stockholm. High concentrations in mammals and birds Marine mammals are considerably higher contaminated with PFOS than marine and freshwater fish, and were found to be the most contaminated of all Nordic biota studied (HELCOM 2010). Several hundreds to one thousand μg kg 1 ww of PFOS have been found in the livers of grey seals (Southern Baltic Proper and Bothnian Sea; Nordic Council of Ministers, 2004), harbour seals (Great Belt and the Sound; Nordic Council of Ministers, 2004) as well as ringed seals (Bothnian Bay; Kannan et al., 2002) (Fig. 2.21). In the eggs of common guillemots (Western Gotland Basin), PFOS concentrations were greater than 1000 μg kg 1 ww (Holmström et al. 2005). OSPAR risk assessment (OSPAR 2005) on marine environment concluded that the major area of concern for PFOS is the secondary poisoning of top predators, such as seals and predatory birds. Concentrations in surface waters Only a few measurements of PFAs in the Baltic Sea surface water exist (Nordic Council of Ministers 2004, Theobald et al., 2007, Lilja et al. 2009). They were mostly performed in potentially affected coastal areas. Perfluoro octanoid acid (PFOA) and PFOS dominated the water samples. Concentrations of PFOA were determined in the range ng l 1 (Little Belt, Kiel Bight, Mecklenburg Bight, Arkona Basin) up to 4 7 ng l 1 (Little Belt, the Sound, coast of Poland, Gulf of Finland). PFOS was found at levels ng l 1 for all locations mentioned, with the exception of single measurements of 2.9 ng l 1 (coast of Poland) and 22 ng l 1 close to Helsinki (Gulf of Finland). Further away from the coast in the Arkona Basin, PFOA and PFOS levels were ng l 1. Concentrations in surface sediments Limited data exist for PFA concentrations in Baltic Sea sediments (Nordic Council of Ministers 2004, SEPA 2006, NERI 2007, Theobald et al. 2007). PFOS and/or PFOA were occasionally detected, but consistently at levels below 1 μg kg 1 dw or ww. The highest levels reported so far have been from the Gulf of Finland close to Helsinki (PFOS 0.9 μg kg 1 ww), close to Stockholm (PFOS 0.6 μg kg 1 ww) and along the coast of Poland (PFOS and PFOA both around 0.6 μg kg 1 dw). In the German Baltic coast, concentrations of PFOS in sediments were on the order of μg/kg dw, those of PFOA μg/kg dw (Theobald et al. 2007). Recommendation PFOS should be included as a core indicator in the Baltic Sea. The substance has high policy relevance, it shows adverse effects in the environment. The core indicator for PFOS requires better geographical coverage in national monitoring programmes and time series data to assess temporal trends. Common HELCOM sampling and analysis procedures should be agreed on. References 89

195 Berger, U., A. Glynn, K. Holmström, M. Berglund, E. Halldin Ankarberg & A. Törnkvist (2009b): Fish consumption as a source of human exposure to perfluorinated alkyl substances in Sweden Analysis of edible fish from Lake Vättern and the Baltic Sea, Chemosphere 76: Bignert, A., Danielsson, S., Nyberg, E., Asplund, L., Eriksson, U., Berger, U. & Haglund, P Comments Concerning the National Swedish Contaminant Monitoring Programme in Marine Biota. Report to the Swedish Environmental Protection Agency, pp. HELCOM Hazardous substances of specific concern to the Baltic Sea Final report of the HAZARDOUS project. Baltic Sea Environment Proceedings No p. Helsinki Commission. HELCOM (2010) Hazardous substances in the Baltic Sea An integrated thematic assessment of hazardous substances in the Baltic Sea. Balt. Sea Environ. Proc. No. 120B. Available at: Holmström, K.E., U. Jarnberg & A. Bignert (2005): Temporal trends of PFOS and PFOA in guillemot eggs from the Baltic Sea, Environmental Science & Technology 39: Holmström, K.E., U. Jarnberg & A. Bignert (2005): Temporal trends of PFOS and PFOA in guillemot eggs from the Baltic Sea, Environmental Science & Technology 39: Kannan, K., S. Corsolini, J. Falandysz, G. Oehme, S. Focardi, J.P. Giesy (2002): Perfluorooctanesulfonate and related fluorinated hydrocarbons in Marine Mammals, Fishes, and Birds from Coasts of the Baltic and the Mediterranean Seas, Environ. Sci. Technol. 36: KEMI Perfluorinated substances and their uses in Sweden. Swedish Chemical Agency (KEMI) Report 7/ p. Lilja, K., K. Norström, M. Remberger, L. Kaj, L. Engelrud, E. Junedahl, T. Viktor & E. Brorström-Lundén (2009): The screening of selected hazardous substances in the eastern Baltic marine environment. IVL, Report B1874. NERI (2007): Danmarks PFAS og organotinforbindelser i punktkilder og det akvatiske miljø, prepared by Strand, J., R. Bossi, O. Sortkjær, F. Landkildehus& M.M. Larsen. (In Danish.) Miljøundersøgelser Rapport 608. Nordic Council of Ministers (NMR) (2004): Perfluorinated Alkylated Substances (PFAS) in the Nordic Environment, prepared by Kallenborn, R., U. Berger & U. Järnberg TemaNord 2004:552, Nordic Council of Ministers, Copenhagen (ISBN , ISSN ). OSPAR 2005 (updated in 2006). OSPAR background document on perfluorooctane sulphonate. 46 p. OSPAR Commission. Poulsen, P., Jensen, A. & Wallström, E More environmentally friendly alternatives to PFOS-compounds and PFOA. Environmental Project No p. Danish Environmental Protection Agency. Renner, R Growing concern over perfluorinated chemicals. Environ. Sci. Technol. 35: 154A-160A. SCHER (2011) Scientific Committee on Health and Environmental Risks. Opinion on "Chemicals and the Water Framework Directive: Draft environmental quality standards". DG Health & Consumer Protection, European Commission. SEPA (2006): Perfluoroalkylated acids and related compounds (PFAS) in the Swedish environment, prepared for Swedish Environment Protection Agency by Järnberg, U., K. Holmström, B. van Bavel & A. Kärrman. Strand, J., Bossi, R., Sortkjær, O., Landkildehus, F. & Larsen, M.M PFAS og organotinforbindelser i punktkilder og det akvatiske miljø (PFAS and organotin compounds in point source effluents and in aquatic environment). In Danish. 49 p. DMU (NERI) Rapport 608. Theobald, N., W. Gerwinski, C. Caliebe & M. Haarich (2007): Entwicklung und Validierung einer Methode zur Bestimmung von poly-fluorierten organischen Substanzen in Meerwasser, Sedimenten und Biota; Untersuchungen zum Vorkommen dieser Schadstoffe in der Nord- und Ostsee, in German, Umweltbundesamt Texte 41/07, ISSN (In German). Van der Putte, I., Murin, M., Van Velthoven, M. & Affourtit, F Analysis of the risks arising from the industrial use of Perfuorooctanoic acid (PFOA) and Ammonium Perfluorooctanoate (APFO) and from their use in consumer articles. Evaluation of the risk reduction measures for potential restrictions on the manufacture, placing on the market and use of PFOA and APFO. 82 p. + annexes. RPS Advies B.V. 90

196 3.4. Polychlorinated biphenyls and dioxins and furans Authors: Elin Boalt, Anders Bignert and Jenny Hedman Acknowledged persons: Anna Brzozowska, Galina Garnaga, Michael Haarich, Ulrike Kamman, Thomas Lang, Martin M. Larsen, Kari Lehtonen, Jaakko Mannio, Rita Poikane, Rolf Schneider, Doris Schiedek, Jakob Strand, Joanna Szlinder-Richert, Tamara Zalewska General information General properties Polychlorinated biphenyls (PCBs) and PCDD/Fs (dioxins) are persistent organic pollutants (POPs) that can cause severe, long-term impacts on wildlife, ecosystems and human health. The substance groups are characterized by low water solubility and low vapor pressure. Due to their persistent and hydrophobic properties, the substances accumulate in sediments and organisms in the aquatic environment. In the environment, dioxins can undergo photolysis, however, they are generally very resistant to chemical and biological degradation. Polychlorinated biphenyls (PCBs) consist of two linked benzene rings with chlorine atoms substituted for one or more hydrogen atoms. Theoretically, 209 congeners are possible, but only around 130 are found in commercial mixtures. Some PCBs are called dioxin-like (dl- PCBs) because they have a structure very similar to that of dioxins and have dioxin-like effects (i.e. four non-ortho substituted PCBs: CB-77, CB-81, CB-126, CB-169, IUPAC and eight mono-ortho substituted: CB-105, CB-118, CB-156, CB-157, CB-167, CB-114, CB-123, CB-189, IUPAC) (Burreau et al. 2006). The name dioxin refers to polychlorinated dibenzop-dioxin (PCDD) and dibenzofuran (PCDF) compounds, i.e two benzene rings with one (furans) or two (dioxins) oxygen bridges and substituted with 1-8 chlorine atoms. Of the 210 possible congeners, the 17 compounds (10 furans, 7 dioxins) substituted in positions 2,3,7,8 are considered to be of toxicological importance. PCBs are synthetic chemicals and do not occur naturally in the environment. Due to their properties, PCBs have been used in a wide variety of manufacturing processes, especially as plasticizers, insulators and flame-retardants. They are widely distributed in the environment through, for example, inappropriate handling of waste material or leakage from transformers, condensers and hydraulic systems. According to some estimates, the total global production of PCBs from 1930 to the ban in most countries by the 1980s has been in the order of 1.5 million tons. PCDD/Fs were never produced intentionally, but they are minor impurities in several chlorinated chemicals (e.g., PCBs, chlorophenols, hexachlorophene, etc.), and are formed in several industrial processes and from most combustion processes, such as municipal waste incineration and small-scale burning under poorly controlled conditions. Formerly, pulp bleaching using chlorine gas was an important source of PCDD/Fs. The PCBs included in this Indicator Information Sheet are the 7 PCB congeners that have been monitored since the beginning of the HELCOM and OSPARCOM monitoring programmes, carefully selected mainly by ICES working groups due to their relatively uncomplicated identification and quantification in gas chromatograms and as they usually contribute a very high proportion of the total PCB content in environmental samples. These are the ICES 7 : CB-28, CB-52, CB-101, CB-118, CB-138, CB-153 and CB-180. Main impacts on the environment and human health 91

197 PCBs and PCDD/Fs can cause a variety of biological and toxicological effects in animals and humans. Most toxic effects are explained by the binding of PCBs and PCDD/Fs to the aryl hydrocarbon (Ah) receptor, however the specific mechanism is not fully understood. Long-term effects of PCBs from human and laboratory mammal studies include increased risk of cancer, infections, reduced cognitive function accompanied by adverse behavioral effects, as well as giving birth to infants of lower than normal birth weight (Carpenter 1998, Carpenter 2006). There are also indications that PCBs are involved in causing reproductive disorders in marine top predators, e.g. seals and bald eagles. PCBs are also assumed, together with p,p -DDE, to cause eggshell thinning and reduced number of offspring in white-tailed sea eagle and uterine leioymas in grey seal (Helander et al 2002, Bäcklin et al. 2010). The most relevant toxic effects of PCDD/Fs are developmental toxicity, carcinogentiy and immunotoxicity. The sensitivity of various species to the toxic effects of PCDD/Fs vary significantly. 2,3,7,8-TCDD is the most toxic and well-studied congener and is used as a reference for all other related chemicals. Each of the 17 relevant congeners is assigned a toxic equivalency factor (TEF), where 2,3,7,8-TCDD equals 1 (Van den Berg et al., 1998; Van den Berg et al., 2006). Dioxin concentrations are commonly reported as toxic or TCDD equivalents (TEQ), which is the sum of the individual congener concentrations multiplied with its specific TEF. The HELCOM thematic assessment of hazardous substances showed that the concentrations of dioxins exceed the thresholds (4 ng kg -1 ww TEQ dioxins, 8 ng kg -1 ww TEQ dioxins + dl-pcbs) in several areas of the Baltic Sea (HELCOM 2010). In the southern parts, it was mainly the dl-pcbs which were on alarming levels. Non-dioxin-like PCBs also exceeded the threshold (0.08 mg kg 1 lipid weight for CB-153) both in the southern and northern sub-basins of the Baltic Sea. Status of a compound on international priority lists and other policy relevance The ICES 7 PCBs are listed as mandatory contaminants that should be analysed and reported within both the OSPARCOM and the HELCOM conventions and are classed as priority POPs under the Stockholm Convention. In the proposed revised guidelines for OSPARCOM (1996) the congeners CB-105 and CB-156 are added to this list. PCBs are not included on the Water Framework Directive (WFD) priority substance lists, but they are in the Marine Strategy Framework Directive (MSFD). Dioxins are included in several international agreements, of which the Stockholm Convention and the Convention on Long Range Transboundary Air are among the most important for the control and reduction of sources to the environment. WHO and FAO have jointly established a maximum tolerable human intake level of dioxins via food, and within the EU there are limit values for dioxins in food and feed stuff (EC, 2006). Several other EU legislations regulate dioxins, e.g. the plan for integrated pollution prevention and control (IPPC) and directives on waste incineration (EC, 2000, 2008). The EU has also adopted a Community Strategy for dioxins, furans and PCBs (EC, 2001). PCDD/Fs are currently not included in the Water Framework Directive but are on the list of substances to be revised for adoption in the near future. HELCOM has listed PCDD/Fs and dl-pcbs as prioritized hazardous substances of specific concern for the Baltic Sea (HELCOM, 2010), like OSPAR on the List of Chemicals for Priority Action (OSPAR, 2010b). Status of restrictions, bans or use The Helsinki Convention (1974, 1992) has recommended special bans and restrictions on transport, trade, handling, use and disposal of PCBs. The Ministerial Declaration from 1998, within HELCOM and the 1995 Declaration of the Fourth international conference of the protection of the North Sea called for measures against toxic, persistent, bioaccumulating substances like PCBs to cease their inputs to the environment completely by the year

198 Under the Stockholm Convention, releases of unintentionally produced by-products listed in Annex C4, including dioxins and dl-pcbs, are subject to continuous minimization with the ultimate goal of elimination where feasible. The main tool for this is a National Action Plan which should cover the source inventories and release estimates as well as plans for release reductions. At the EU level, a Strategy for dioxins and PCBs was adopted in The Strategy includes actions in the area of feed and food contamination and actions related to the environment, including release reduction. Over the past decade, important legislation has been adopted to reduce the emissions of PCDD/Fs, in particular in the areas of waste incineration and integrated pollution prevention and control. Releases of POPs, including dioxins, from industrial installations are mainly regulated by the IPPC Directive and the Waste Incineration Directive, the former requiring Member States to establish permit conditions based on the Best Available Techniques (BAT) for a wide variety of industry sectors, and the latter setting maximum permissible limit values for PCDD/F emissions to air and water from waste incineration. The proper and timely implementation and enforcement of the IPPC Directive remain a key priority in order to ensure the necessary reduction of emissions from major industrial sources. However, at present or in the near future, nonindustrial sources are likely to exceed those from industrial sources (Quass et al., 2004). GES boundaries and matrix Existing quantitative targets PCBs Source Value and description OSPAR EC EAC sediment EAC passive fish EAC mussel BAC sediment BAC fish BAC mussel Proposed MAQ-EQS (marine waters) Proposed AA-EQS biota (marine waters) Food stuff directive CBs µg/kg dw 2.5% TOC. CB-28: 1.7, CB-52: 2.7, CB-101: 3.0, CB- 118:0.6, CB-138: 7.9, CB-153: 40, CB-180: 12. CBs µg/kg lw. CB-28: 64, CB-52: 108, CB-101: 120, CB-118:24, CB- 138: 316, CB-153: 1600, CB-180: 480 CBs µg/kg dw. CB-28: 3.2, CB-52: 5.4, CB-101: 6.0, CB-118:1.2, CB-138: 15.8, CB-153: 80, CB-180: 24 CBs µg/kg dw 2.5% TOC. CB-28:0.22, CB-52: 0.12, CB-101: 0.14, CB-118:0.17, CB-138: 0.15, CB-153: 0.19, CB-180: 0.1 CBs µg/kg ww from CEMP 2008/2009. CB-28: 0.1, CB-52: 0.08, CB- 101: 0.08, CB-118:0.1, CB-138: 0.09, CB-153: 0.1, CB-180: ICES7CBs from ASMO 09/7/3: 1.2. CBs µg/kg dw. CB-28: 0.75, CB-52: 0.75, CB-101: 0.7, CB-118:0.6, CB-138: 0.6, CB-153:0.6, CB-180: µg/l µg/kg ww Sum of CB-28, CB-52, CB-101, CB-138, CB-153 and CB-180 (ICES 6) 75 ng/g ww (with exeptions) Effect Range -Low 93

199 ERL sediment CBs µg/kg dw 2.5% TOC. Total CB: 23 ICES7CBs: 11.5 Water: non-applicable Sediment: OSPAR EAC for CB 118 and 153 PCBs Recommended Biota: OSPAR EAC for CB 118 and 153 GES boundary Seafood: Ʃ6PCBs (28, 52, 101, 138, 153, 180): 75 µg/kg ww. PCDD/Fs and DL-PCBs Source OSPAR (OSPAR, 2010a) EAC sediment EAC fish EAC mussel BAC/BC sediment BAC/BC fish BAC/BC mussel LC sediment Value and description No target levels for PCDD/Fs PCB-118 (dl-pcb): 0.6 ug/kg dw PCB-118 (dl-pcb): 24 ug/kg lw PCB-118 (dl-pcb): 1.2 ug/kg dw PCB-118 (dl-pcb): 0.17 ug/kg dw (BAC) PCB-118 (dl-pcb): 0.6 ug/kg ww (BAC) PCB-118 (dl-pcb): 0.1 ug/kg dw (BAC) PCB-118 (dl-pcb): 0.05 ug/kg dw EC EQS water - Draft EQS water - Draft EQS biota Draft EQS sediment Draft EQS biota Food stuff directive 4.0 ng WHO 98 -TEQ / kg ww (Σ PCDDs+PCDFs) 8.0 ng WHO 98 -TEQ / kg ww (Σ PCDDs+PCDFs+dl-PCBs) Human health is the critical endpoint EQS Biota, Predators (secondary poisoning): 0.23 ng / kg ww (Σ PCDDs+PCDFs) 1.7 ng WHO 98 -TEQ / kg dw (Σ PCDDs+PCDFs+dl-PCBs) Benthic community: 0.85 ng / kg dw (Σ PCDDs+PCDFs) (EC, 2006), 881/2006/EC* Muscle meat of fish and fishery products and products thereof with th exception of eel: 4.0 ng WHO 98 -TEQ / kg ww (Σ PCDDs+PCDFs) 8.0 ng WHO 98 -TEQ / kg ww (Σ PCDDs+PCDFs+dl-PCBs) Muscle meet of eel (Anguilla anguilla) and products thereof: 4.0 ng WHO 98 -TEQ / kg ww (Σ PCDDs+PCDFs) 12.0 ng WHO 98 -TEQ / kg ww (Σ PCDDs+PCDFs+dl-PCBs) Fish liver: 94

200 Canadian Sediment Quality Guidelines PEL sediment Canadian Sediment Quality Guidelines TEL sediment 25.0 ng WHO 98 -TEQ / kg ww (Σ PCDDs+PCDFs+dl-PCBs) Probable Effect Level: 21.5 ng TEQ/ kg dw (PCDD/Fs) Threshold Effect Level: 0.85 ng TEQ/ kg dw (PCDD/Fs) PCDD/Fs Recommended GES boundary Water: non-applicable Sediment: 0.85 ng / kg dw (Σ PCDDs+PCDFs) Biota: 0.23 ng / kg ww (Σ PCDDs+PCDFs) Seafood: Fish muscle: 4.0 ng WHO 98 -TEQ / kg ww (Σ PCDDs+PCDFs), 8.0 ng WHO 98 -TEQ / kg ww (Σ PCDDs+PCDFs+dl-PCBs) * NOTE: This regulation is under amendment and new target levels should be decided during The new levels will be based on the WHO-2005 TEF-values (current levels are based on the WHO-1998 TEFs). The CORESET expert group decided that, due to uncertainties in the target setting on the OSPAR and EU working groups, the PCBs should be assessed by two congeners only: CB- 118 (dioxin like) and 153 (non-dioxin like). Tentatively the OSPAR EACs for these two congeners are suggested to be used. The Scientific Committee on Health and Environmental Risks (SCHER) criticized the derivation of sediment and biota QSs for dioxins (SCHER 2011). Therefore, the GES boundaries for dioxins are seen as tentative until WFD WG E proposes new QSs. Preferred matrix Due to the hydrophobic properties of PCBs and PCDD/Fs, monitoring of very low concentrations in the water column is not appropriate. PCBs and PCDD/Fs accumulate in sediments and biota in the aquatic environment, which are thus preferred matrices for monitoring. E.g. coastal surface sediment and muscle tissue of fat fish (e.g. herring, salmon). For guidance on monitoring strategies, see e.g. the Guidance Document for chemical monitoring under the Water Framework Directive (EC, 2009). Dl-PCBs elicit toxic effects through the Ah receptor and thereby contribute to the TEQ of a sample. Thus, dl-pcbs should be included in the quantitative target level if it is based on total TEQ. Monitoring the compound Status of monitoring network (geographical and temporal coverage) Present status of monitoring network in the Baltic Sea is presented in the table below. Nation Denmark PCBs (ICES 7) Sediments Biota Water PCDD/Fs PCBs (ICES 7) PCDD/Fs Yearly in shellfish (13) and fish (17) Yearly (7 mussels, 17 fish) PCBs (ICES 7) PCDD/Fs 95

201 Germany Yearly Yearly Poland Russia 3 5 years Yearly No regular monitoring, screening Yearly Sweden Yearly Yearly Finland 6-10 years Yearly Estonia Yearly Lithuania Yearly Yearly in fish (State Food (starts and Veterinary 2008) Service) Latvia 2002 Yearly (randomly throughout the year), herring, sprat, salmon (3 sites) Yearly (autumn), herring (3 sites) and guillemot eggs (1 site) Yearly (autumn), herring 4 sites. Surveys, several species, 7 sites ( , ) Yearly in fish (State Food and Veterinary Service) Twice a year yearly (starts 2008) - Gaps in the monitoring of the compound There are no big gaps. Present status assessments Known temporal trends (also from sediment core profiles) As a result of measures taken to reduce discharges of PCBs to the environment, concentrations of PCB, including CB-153 and CB-180, show significant declining trends for herring, perch and blue mussels in several regions surrounding the Baltic Sea. Noteworthy is that few of the presently available data sets have time series long enough (to draw statistical conclusions regarding time trends with an annual change of 5%. In herring, perch, mussel and cod, time series between 14 to 22 years are required to detect such changes (Bignert et al. 2004). Decreasing trends for other PCB congeners, as well as for content of the sum of seven PCBs are also reported for some locations along the Baltic Sea (Bignert et al. 2008, GIOŚ 2007). It is estimated that estimated levels of spcb along the Swedish coast in fish and mussels are decreasing with approximately 5-10% per year since the end of the seventies (Bignert et al. 2008). The analysis of dated slices of laminated sediment cores, however, revealed big regional differences in temporal trends (Schneider and Leipe, 2007). For dioxins, there are few historical sediment data (profiles) from the Baltic Sea and some data are from the late 1980s and thus unable to reveal very recent trends. All the cores, however, show a decline in surface PCDD/F concentrations compared with deeper sediments, with the highest concentrations generally dated back to the 1970s or 1960s in the northern basins, the Baltic Proper and the Kattegat - Danish straits. There is not much information about past or recent trends in PCDD/F concentrations in different fish species and generally the data do not cover past decades. The Swedish Museum of Natural History reported dioxin concentrations in the muscle of small herring collected from 1990 to 2008 at three stations on the Swedish coast that showed no indications of change during that period, but the guillemot egg data showed a major and significant decrease since 1970 (Bignert et al., 2010). Similarly, no decreasing trend of 96

202 PCDD/Fs or dl-pcbs was observed in fish from the southern Baltic Sea during (Szlinder-Richert et al., 2009). Recently, Karl et al (2010) repeated a study on PCDD/F and dl-pcb concentrations i herring from the south and western Baltic Sea (Karl and Ruoff, 2007) and concluded that the TEQ concentrations had not changed between 1999 and Thus, there seems to have been a levelling off of the concentrations in fish from many areas in the Baltic Sea during the last decades. Spatial gradients (incl. sources) The levels of PCBs are about five times higher in the Baltic Sea compared to the North Sea (Mehtonen 2009). Concentrations more than three times above threshold levels in the Baltic Sea were found in the Little Belt, southern parts of the Kattegat, the Sound, the Szczecin Lagoon, southern parts of the Bothnian Sea, and in the Bothnian Bay (HELCOM 2010). In contrast, the concentrations of CB-180 were not found to exceed the threshold level (EAC, mg kg 1 lipid weight) (OSPAR 2009) in any part of the Baltic Sea. The highest concentrations of CB-180 in this assessment were found in the Pomeranian Bay, where concentrations were between and mg kg 1 lipid weight. For dioxins, sediment surveys have revealed some major sediment contamination with dioxins in the River Kymijoki estuary, Finland (Isosaari et al., 2002; Verta et al., 2007) and a more local contamination on the Swedish coast of the Gulf of Bothnia (Sundqvist et al., 2009) originating from local industrial sources. Major data gaps are currently for the southeastern and eastern coastal regions of the Baltic Proper and the southern Gulf of Finland. Numerous recent papers have shown differences in PCDD/F and dl-pcb concentrations in Baltic herring, sprat and salmon between the Baltic Sea basins (e.g., Bignert et al., 2010; Karl et al., 2010). Higher concentrations have been detected in the northern basins where dioxin and dl-pcb levels in herring exceed established maximum limit concentrations for human consumption. Regional variation within a sub-basin has been found in the Swedish coastal region of the Bothnian Sea (Bignert et al., 2007). Since the atmospheric deposition pattern (lowest in the north) is different from concentrations in fish (generally highest in the north), other factors or sources are thus likely to be involved in determining concentrations in fish. The reasons remain unclear, but higher historical PCDD/F discharges from point sources in the northern basins have been suggested. In general, the contribution from the dl-pcbs to the TEQ is substantial and seems to increase the further south in the Baltic region the samples are collected. Recommendation PCBs and PCDD/Fs should be included as a core indicator in the Baltic Sea. The substances have adverse impacts on the environment, they are monitored throughout the entire Baltic Sea area and there are several quantitative targets (i.e. GES boundaries) available. References Bignert, A., Asplund, L., and Wilander, A Comments concerning the national Swedish contaminant monitoring programme in marine biota, Swedish Museum of Natural History, Department of Contaminant Research, Stockholm. Bignert, A., Nyberg, E., Sundqvist, K.L., Wiberg, K., Spatial variation in concentrations and patterns of the PCDD/F and dioxin-like-pcb content in herring from the northern Baltic Sea. J. Environ. Monit. 9, Bignert, A., Danielsson, S., Strandmark, A., Nyberg, E., Asplund, L., Eriksson, U., Berger, U., Wilander, A., and Haglund, P Comments Concerning the National Swedish Contaminant 97

203 Monitoring Programme in Marine Biota. Swedish Museum of Natural History, Department of Contaminant Research, Stockholm. Bignert, A., Danielsson, S., Nyberg, E., Asplund, L., Eriksson, U., Berger, U., A., W., Haglund, P., Comments concerning the national Swedish contaminant monitoring programme in marine biota, Swedish Museum of Natural History, Department of Contaminant Research, Stockholm. Burreau S., Zebühr, Y., Bromar, D., and Ishaq, R Biomagnification of PBDEs and PCBs in food webs from the Baltic Sea and northern Atlantic ocean. Sci. Tot. Environ. 366: Bäcklin, B-M., Madej, A., and Forsberg, M Histolofy of ovaries and uteri and levels of plasma progesterone, ostradiol-17β and oestrone sulphate during the implantation period in mated and gonaotrophin-releasing hormone-treated mink (mustela vison) axposed to polychlorinated biphenlys. J. Appl. Tox. 17: Carpenter, D., Arcaro, K., Bush, B., Niemi, W., Pang, S., and Vakharia, D Human health and chemical mixtures: and overview. Env. Health Persp. 10+: Carpenter, D Polycklorinated biphenlys (PCBs): routes of exposure and effects on human health. Rev. Env. Health. 21, No 1. EC, Directive 2000/76/EC of the European Parliment and of the Council of 4 December 2000 on the incineration of waste. Official Journal of the European Union L 332/91. EC, Community Strategy for Dioxins, Furans and Polychlorinated Biphenyls. Communication from the Commission to the Council, the European Parliment and the Economic and Social Committee 593 final. EC, Commission regulation (EC) No 1881/2006 of 19 December 2006 setting maximum levels for certain contaminants in foodstuffs. Official Journal of the European Union L 364/5. EC, Directive 2008/1/EC of the European Parliment and of the Council of 15 January 2008 concerning integrated pollution prevention and control. Official Journal of the European Union L 24/8. EC, Common implementation strategy for the Water Framework Directive (2000/60/EC), Guidance Document no.19, Guidance on surface water chemical monitoring under the Water Framework Directive. Technical Report Helander, B., Olsson, A., Bignert, A., Asplund, L., Litzén, K The role of DDE, PCB, Coplanar PCB and eggshell parameters for reproduction in the white-tailed se eagle (Haliaeetus albicilla) in Sweden Ambio 31: HELCOM, Implementing HELCOM s objective for hazardous substances, Recommendation 31E/1. HELCOM (2010) Hazardous substances in the Baltic Sea An integrated thematic assessment of hazardous substances in the Baltic Sea. Balt. Sea Environ. Proc. No. 120B. Available at: Helander, B., Olsson, A., Bignert, A., Asplund, L., Litzén, K The role of DDE, PCB, Coplanar PCB and eggshell parameters for reproduction in the white-tailed se eagle (Haliaeetus albicilla) in Sweden Ambio 31: ICES WGBEC. Report Isosaari, P., Kankaanpaa, H., Mattila, J., Kiviranta, H., Verta, M., Salo, S., Vartiainen, T., Spatial distribution and temporal accumulation of polychlorinated dibenzo-p-dioxins, dihenzofurans, and Biphenyls in the Gulf of Finland. Environ. Sci. Technol. 36, Karl, H., Bladt, A., Rottler, H., Ludwigs, R., Mathar, W., Temporal trends of PCDD, PCDF and PCB levels in muscle meat of herring from different fishing grounds of the Baltic Sea and actual data of different fish species from the Western Baltic Sea. Chemosphere 78, Karl, H., Ruoff, U., Dioxins, dioxin-like PCBs and chloroorganic contaminants in herring, Clupea harengus, from different fishing grounds of the Baltic Sea. Chemosphere 67, S90-S95. Mehtonen, J Hazardous substances of specific concern to the Baltic Sea Final report of the Hazardous project. Balt. Sea Environ. Proc. No

204 Olsson, Bignert, Eckhéll, Johnsson Comparison of temporal trends (1940s-1990s) of DDT and PCB in Baltic sediment and biota in relation to eutrophication. Ambio 29(4): OSPAR, 2010a. Agreement on CEMP assessment criteria for the QSR 2010, OSPAR Commission, Ref no OSPAR, 2010b. List of Chemicals for Priority Action, Ref. nr Quass, U., Fermann, M., Broker, G., The European dioxin air emission inventory project - Final results. Chemosphere 54, SCHER (2011) Scientific Committee on Health and Environmental Risks. Opinion on "Chemicals and the Water Framework Directive: Draft environmental quality standards". DG Health & Consumer Protection, European Commission. Schneider, R. and Leipe, T. (2007). Historical and recent contents of PCB and organochlorine pesticides in sediments from Baltic Sea Basins. ICES CM 2007 / I:08, 1-15Sundqvist, K.L., Tysklind, M., Geladi, P., Cato, I., Wiberg, K., Congener fingerprints of tetra- through octa-chlorinated dibenzo-pdioxins and dibenzofurans in Baltic surface sediments and their relations to potential sources. Chemosphere 77, Szlinder-Richert, J., Barska, I., Usydus, Z., Ruczynska, W., Grabic, R., Investigation of PCDD/Fs and dl-pcbs in fish from the southern Baltic Sea during the period. Chemosphere 74, Van den Berg, M., Birnbaum, L., Bosveld, A.T.C., Brunstrom, B., Cook, P., Feeley, M., Giesy, J.P., Hanberg, A., Hasegawa, R., Kennedy, S.W., Kubiak, T., Larsen, J.C., van Leeuwen, F.X.R., Liem, A.K.D., Nolt, C., Peterson, R.E., Poellinger, L., Safe, S., Schrenk, D., Tillitt, D., Tysklind, M., Younes, M., Waern, F., Zacharewski, T., Toxic equivalency factors (TEFs) for PCBs, PCDDs, PCDFs for humans and wildlife. Environ. Health Perspect. 106, Van den Berg, M., Birnbaum, L.S., Denison, M., De Vito, M., Farland, W., Feeley, M., Fiedler, H., Hakansson, H., Hanberg, A., Haws, L., Rose, M., Safe, S., Schrenk, D., Tohyama, C., Tritscher, A., Tuomisto, J., Tysklind, M., Walker, N., Peterson, R.E., The 2005 World Health Organization reevaluation of human and mammalian toxic equivalency factors for dioxins and dioxin-like compounds. Toxicol. Sci. 93, Verta, M., Salo, S., Korhonen, M., Assmuth, T., Kiviranta, H., Koistinen, J., Ruokojarvi, P., Isosaari, P., Bergqvist, P.A., Tysklind, M., Cato, I., Vikelsoe, J., Larsen, M.M., Dioxin concentrations in sediments of the Baltic Sea - A survey of existing data. Chemosphere 67,

205 3.5. Polyaromatic hydrocarbons (PAH) Authors: Galina Garnaga and Rolf Schneider Acknowledged persons: Anders Bignert, Elin Boalt, Anna Brzozowska, Michael Haarich, Jenny Hedman, Ulrike Kamman, Thomas Lang, Martin M. Larsen, Kari Lehtonen, Jaakko Mannio, Rita Poikane, Doris Schiedek, Jakob Strand, Joanna Szlinder-Richert, Tamara Zalewska General information General properties There are 16 PAHs that are recommended as priority pollutants by the U.S. EPA, WFD and MSFD. These PAH compounds include two-ring compounds (naphthalene); three-ring compounds (acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene); fourring compounds (fluoranthene, pyrene, benzo(a)anthracene, chrysene); five-ring compounds (benzo(a)pyrene, benzo(b)fluoranthene, benzo(k)fluoranthene, dibenz(a,h)anthracene); six-ring compounds (indeno(1,2,3-c,d)pyrene, benzo(g,h,i)perylene). Due to their low water solubility and hydrophobic nature, PAHs tend to associate with particulate material. The deposition of these particles in rivers and coastal waters can lead to an accumulation of PAHs in the sediment. PAHs are persistent, especially in anaerobic sediments, with the higher molecular weight PAHs being more persistent than the lower molecular weight compounds (Kennish, 1997; Webster et al., 2003). Bioaccumulation of PAHs from sediments by marine organisms depends, thermodynamically, on the ratio between adsorption capacity of the sediment and absorption capacity of the organism. Different profiles of contaminants have been observed in organisms of different trophic levels. These differences were attributed to a partial biotransformation of the contaminants in the organisms of higher trophic levels (Baumard et al., 1998b). Main impacts on the environment and human health Polycyclic aromatic hydrocarbons (PAHs) are of concern due to their persistence and potential to accumulate in aquatic organisms, particularly invertebrates, such as bivalves and crustaceans. In most vertebrates, PAHs are fairly rapidly metabolized, but they and their toxic intermediates emerging during metabolic degradation can cause deleterious effects in fish. PAH are important environmental contaminants which may lead to increased levels of neoplastic aberrations or tumors in fish liver. Therefore monitoring of PAH and their effects are part of several international environmental programmes. Epoxides originating from the oxidation of PAH by cytochrome P4501A1 may be further oxidised to carcinogenic diolepoxides. These dioleepoxides are known to bind to DNA and/or cause mutations which may lead to cancer. Increased levels of neoplastic aberrations or tumors were found in fish which have been exposed to PAH contaminated sediments. For this reasons PAH contamination in marine ecosystems is a cause for concern. To assess the PAH exposure of fish, concentrations of the main metabolites such as 1-hydroxypyrene, 1-hydroxyphenanthrene and 3-hydroxybenzo(a)pyrene can be determined in bile by HPLC with fluorescence detection (HPLC-F), by synchronous fluorescence scanning, gas chromatography with mass selective detection (GC/MS) and also by UPLC/MS/MS (Bayer et al., 2010; Ariese et al. 2005). PAH metabolites in fish bile 100

206 reflect the exposure of the fish to PAHs via sediment and food usually during the last days depending on the feeding activity. Status of a compound on international priority lists and other policy relevance Anthracene, benzo(a)pyrene, benzo(b)fluoranthene, benzo(g,h,i)perylene, benzo(k)fluoranthene, indeno(1,2,3-cd), pyrene, fluoranthene and naphthalene are identified as priority substances by European Commission (Directive 2008/105/EC). PAHs are included in the OSPAR list of substances of priority action. For US EPA it is the list of 16 priority compounds quoted under 1.1. Relevance of the indicator for describing the developments in the environment Low-molecular-weight PAH compounds, containing two or three rings, are acutely toxic to a broad spectrum of marine organisms. Examples of low-molecular-weight PAHs that tend to be toxic are anthracene, fluorene, naphthalene and phenanthrene. The high-molecularweight PAH compounds, containing four, five, and six rings, are less toxic but have greater carcinogenic potential, e.g. benzo(a)pyrene, dibenz(a,h)anthracene, benzo(b)fluoranthene (Kennish, 1997). While PAHs can be weakly carcinogenic or non-carcinogenic, they can modify the carcinogenic activity of other PAHs in complex mixtures (Marston et al., 2001). Therefore, synergistic effects of PAHs can be larger than the total levels of PAHs would indicate. Higher concentrations of PAHs are also harmful to reproduction of fish and can damage cellular membrane structures (Knutzen, 1995). When PAHs are exposed to sunlight, the mechanism known as phototoxicity is involved, producing reactive and toxic photomodification products (HELCOM, 2010). Anthropogenic PAH sources in the marine environment include the release of crude oil products (petrogenic source) and all types of incomplete combustion of fossil fuels coal, oil and gas or wood and waste incineration (pyrolytic sources) (Neff, 2004). Some PAHs are formed naturally, but the majority of PAHs in the marine environment come from anthropogenic activity. Each source generates a characteristic PAH pattern, enabling distinction of the sources in a sample; concentration relationships of individual PAH compounds can be used to reveal the sources of the PAH compounds (Baumard et al., 1998, Sicre et al.,1987, Yunker et al., 2002). Molecular indices calculated from both sediment and biota showed that pyrolytic sources predominate in the Baltic Sea PAH contamination. However, in the Gulf of Finland and some areas in the western Baltic Sea (Sound, Belt Sea and Kattegat), molecular indices indicated a significant contribution of petrogenic PAHs. This may indicate that atmospheric deposition combined with shipping activities is the main source of PAHs in these areas. The dominance of pyrolytic sources could be surprising in view of the heavy maritime traffic and illegal oil discharges. On the other hand, no reliable information is available on the airborne deposition of PAHs onto Baltic Sea surface waters (Pikkarainen 2004). Status of restrictions, bans or use The maximum levels of benzo(a(pyrene and also a sum of benzo(a)pyrene, benz(a)anthracene, benzo(b)fluoranthene and chrysene are regulated in food stuff according to the Commission Regulation (EC) No 835/2011. There are no other regulations for the production or use of PAHs. GES boundaries and matrix Existing GES boundaries Note: targets based on EQS are subject to changes 101

207 Table 1. Existing targets. Substance GES boundary for biota GES boundary for sediment Dibenz[ah]anthracene ER-L 63.4 µg kg -1 dw GES boundary for water Fluoranthene EAC mussel 110 µg/kg dw (OSPAR 2009) EAC/ERL 600 µg kg-1 dw (OSPAR 2009) EQS: 0.1 µg L -1 Anthracene EAC Mussel 290 µg/kg dw (OSPAR 2009) EAC/ERL 85 µg kg-1 dw (OSPAR 2009) EQS: 0.1 µg L -1 Naphthalene EAC mussel: 340 µg kg-1 dw (OSPAR 2009) EAC/ERL 160 µg kg-1 dw (OSPAR 2009) EQS: 1.2 mg L -1 Benzo[ghi]perylene EAC Mussels 110 µg/kg dw (OSPAR 2009) EAC/ERL 85 µg kg-1 dw (OSPAR 2009) BghiP+I123cdP EQS: µg L-1 Benzo[a]pyrene Benzo[k]fluoranthene Benzo[b]fluoranthene Pyrene EAC Mussels 600 µg kg-1 dw (OSPAR 2009) EAC Mussels 260 µg kg-1 dw (OSPAR 2009 background doc) EAC Mussels 100 µg kg-1 dw (OSPAR 2009) EAC/ERL 430 µg kg-1 dw (OSPAR 2009) EAC/ERL 665 µg kg-1 dw (OSPAR 2009) BaP EQS: 0.05 µg L-1 BbF+BkF EQS: 0.03µg L-1 BbF+BkF EQS: 0.03µg L-1 Fluorene Benz[a]anthracene indeno[1,2,3- cd]pyrene chrysene phenanthrene acenapthylene EAC Mussels 80 µg/kg dw (OSPAR 2009) BAC mussel: 2.4 µg/kg dw (OSPAR 2009) BAC mussel: 8.1 µg/kg dw (OSPAR 2009) EAC Mussels: 1700 µg kg- 1 dw (OSPAR 2009) EAC/ERL 261 µg kg-1 dw (OSPAR 2009) EAC/ERL 240 µg kg-1 dw (OSPAR 2009) EAC/ERL 384 µg kg-1 dw (OSPAR 2009) EAC/ERL 240 µg kg-1 dw (OSPAR 2009) ER-L 44 µg kg -1 dw BghiP+I123cdP EQS: µg L-1 acenapthene ER-L 16 µg kg -1 dw 1-hydroxypyrene 483/909 ng/g[gc-ms] for cod/turbot 1- hydroxyphenanthrene 518/1832 ng/g [GC-MS] for cod/turbot Background response and Assessment Criteria for metabolites EAC and BAC values depend on the metabolite, the fish species as well as on the analytical method used. Both values can be used for the North Sea as well as the Baltic Sea if species fits. The recommended way to calculate BACs is to use the 90th percentile of reference site data. Possible reference sites are Iceland and Barents Sea. Data from additional reference sites may improve the quality of the BAC in future. BACs have been calculated for dab, cod and haddock. In Fig. 1 monitoring results are presented in two colours representing the proportions of the fish above and below the BAC. No EAC values were exceeded. Looking at the values regional differences seems to be much more important than species differences. If BAC should be developed for fish species which prefere more polluted habitats (coast), it could be helpful to use an species independent BAC for fish instead. SGIMC 2010 proposed a joint BAC for three fish species cod dab and haddock. A BAC 102

208 value applicable for more marine fish species would be helpful regarding inter-species evaluation of monitoring data. Even if PAH metabolites are only a marker of exposure, high levels of metabolites can be linked to deleterious effects in fish. EACs have been be identified using results from toxicological experiments linking oil exposure and PAH metabolites in fish with DNA adducts and fitness data (Morton et al., 2010; Skadsheim et al. 2004; Skadsheim et al., 2009), where the latter serves as the effect quantity for the calculation of the EAC presented in Table 2. EAC are available for some fish species only at the moment. More investigations are needed to calculate proper EAC values for Baltic fish species. EACs cannot be easily transferred to other species because they may differ in sensitivity to PAH effects. Table 2. Background Assessment Criteria (BAC) and Environmental Assessment Criteria (EAC) for two PAH metabolites, different fish species and methods. Data partly taken from WKIMC 2009 and SGIMC Biological Effect Fish species BAC [ng/ml] HPLC-F Bile metabolite 1- hydroxypyrene Bile metabolite 1- hydroxyphenanthrene dab 16 EAC [ng/g] GC/MS cod flounder 16 4) haddock 13 dab, cod, haddock 17 turbot 909 halibut 745 dab 3.7 cod flounder 3.7 4) haddock 0.8 dab, cod, haddock 2.4 turbot 1832 halibut 262 Biological Effect Fish species BAC [µg/ml] Synchronuos Fluor. 341/383 Bile metabolites of pyrene-type EAC [µg/ml] Fixed Fluor. 341/383 dab ) cod flounder ) 103

209 haddock ) turbot 29 halibut 22 herring/sprat 16 AC based on 1) halibut, 2) turbot, 3) cod and 4) dab GES boundary for food: Benz(a)Pyrene (fish): 2 μg/kg ww; Benz(a)Pyrene (crustaceans): 2 μg/kg ww; Benz(a)Pyrene (bivalves): 2 μg/kg ww. Quality Assurance of PAH metabolite targets In ICES Times No. 39 there are several methods described and equally recommended. Due to different principles not all of the methods can be compared. BONUS+ project BEAST conducted an intercalibration for PAH metabolites in fish bile in The results showed a good comparability between the participating labs as well as between the analytical methods GC-MS, HPLC-F and synchronous fluorescence scanning. A factor was used to compare synchronous fluorescence to the other two methods mentioned above. Confounding factors The season and the feeding status (freshly filled gall bladder or not) seem to be confounding factors for fish. Normalisation of metabolite concentration to bile pigments (expressed as absorption at 380nm or biliverdin concentration) can help to reduce variation in some data sets (Kammann 2007, Ariese et al. 1997). In other data sets normalisation leads to no advantage. Male and female fish tend to have different levels of PAH metabolites (Vuorinen et al. 2006). Monitoring of the PAHs Status of monitoring network (geographical and temporal coverage) PAHs are monitored mostly in sediments (or in water), but not in mussels (except Denmark and Sweden). In Finland the monitoring of PAHs in sediments it is not coherent regarding sites & frequency, not nearly all sites visited yet. Lithuania analyses only 8 individual PAHs: naphthalene, anthracene, flouranthene, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(a)pyrene, benzo(g,h,i)perylene and indeno(1,2,3-cd)pyrene. PAH metabolites: Baltic countries with regular monitoring of PAH metabolites in fish bile: Germany and Denmark. Baltic countries with pre-monitoring stage of PAH metabolites investigations: Finland, Poland Temporal coverage Temporal trends of PAH concentrations in biota and surface sediments cannot be assessed in the majority of the Baltic Sea area due to temporally and spatially fragmented data sets. In Denmark sediments will be taken according to a rotating sampling scheme, so no temporal trends will be available for sediments. 104

210 Present status assessments Temporal development of PAHs concentrations in sediments and biota Assessment Taking into account data from 1999 to 2008, temporal trends for individual PAHs have been determined using Danish national monitoring data. Benzo(a)pyrene concentrations in mussels from Århus Bight and Sound were characterized by statistically significant decrease, while mussels from Great Belt show temporally relatively constant concentrations. However, it is difficult to detect and interpret temporal variation without long time series and case studies, including examination of environmental condition (HELCOM, 2010). The highest levels of PAHs are observed in lagoon areas (e.g. Szczecin lagoon), in the vicinity of harbours (e.g. port of Copenhagen) or in the accumulation areas (e.g. Arkona Deep or Gdańsk Deep). In general, the concentrations of light molecular weight PAHs like fluoranthene and phenathrene in the Baltic biota and sediments do not exceed the OSPAR toxicity threshold values (OSPAR, 2009) in any of the sub-regions. The heavy molecular weight compound benzo(a)pyrene, which has been shown to be highly toxic, carcinogenic and mutagenic, is below the threshold values both in sediment and bivalves in the whole the sea area. Benzo(g,h,i)perylene is present in high concentrations in the Baltic Sea sediments, often exceeding the threshold values. In bivalves and sediments, it was found to exceed the threshold value in the southern and south-western sea areas. Benzo(b)fluoranthene was found to exceed the threshold values in sediments in all the other basins except Bothnian Sea and Bothnian Bay. However, the threshold value for benzo(b)fluoranthene is not normalized to sediment carbon and therefore the spatial comparison may be misleading due to different sea bed characteristics (HELCOM, 2010). Detectable concentrations of anthracene have been found in fish from Swedish background stations. It has been measured in sediment from the Stockholm area (with concentrations falling inversely with distance from central Stockholm) and homogeneous coastal samples, indicating small local impact. It has also been measured in detectable concentrations in water areas sampled with the use of passive sampling devices. Fluoranthene is frequently present in fish from Swedish background stations, and also found in sediment and sludge. It has been found in all water samples from Sweden taken by means of passive sampling devices, and it is detectable in groundwater samples (Swedish EPA, 2009). Proportion of fish with values < / BAC Figure 1- Hydroxypyren e in bile fluids of dab, flounder and cod caught between 1998 and 2007 categorized by the species overarching BAC of 17 ng/ml. Proportion of single fish per station are categorized in relation to BAC (SGIMC 2010). 105 < 17 ng/ml

211 Clear differences in PAH metabolite concentration in fish bile between the lower contaminated central North Sea and the higher contaminated western Baltic Sea have been detected. In distance of point sources there are no temporal trends detectable in dab and flounder from the North Sea and the western Baltic Sea caught during 1997 and 2004 (Kammann 2007). Lower values than in North Sea (dab, cod, flounder, haddock) and Baltic Sea (flounder, cod, herring, Vuorinen et al., 2006; eelpout) have been detected in Barents Sea (cod) and near Iceland (dab). Higher concentrations are present in fish caught in harbour regions or in coastal areas (eelpout, Kammann and Gercken, 2010). Strengths and weaknesses of data For tracing sources of alkylated versions of PAHs would be preferred over the parent PAHs. E.g. Sweden will include alkylated versions in 2011 in monitoring in order to evaluate whether they should be included in the yearly monitoring program. References Ariese F, Beyer J, Jonsson G, Porte Visa C, Krahn MM (2005) Review of analytical methods for determining metabolites of polycyclic aromatic compounds (PACs) in fish bile. ICES Techniques in Marine Environmental Sciences No. 39 Ariese F, Burgers I, Oudhoff K, Rutten T, Stroomberg G, Vethaak D (1997): Comparison of analytical approaches for PAH metabolites in fish bile samples for marine and estuarine monitoring. Vrije Universiteit Amsterdam, Institut for Environmental Studies. R 97-9, 28 pp Baumard P., Budzinski H., Garrigues P., 1998a. PAHs in Arcahon Bay, France: origin and biomonitoring with caged organisms. Marine Pollution Bulletin, 36 (8): Baumard, P., H. Budzinski & P. Garrigues (1998b): Polycyclic aromatic hydrocarbons in sediments and mussels of the western Mediterranean Sea, Environ. Toxicol. Chem. 17: Beyer J, Jonsson G, Porte C, Krahn MM, Ariese F (2010) Analytical methods for determining metabolites of polycyclic aromatic hydrocarbon (PAH) pollutants in fish bile: A review. Environmental Toxicology and Pharmacology, 30: HELCOM, Hazardous substances in the Baltic Sea An integrated thematic assessment of hazardous substances in the Baltic Sea. Balt. Sea Environ. Proc. No. 120B. Kammann U (2007) PAH metabolites in bile fluids of dab (Limanda limanda) and flounder (Platichthys flesus) spatial distribution and seasonal changes. Environ Sci Pollut Res 14(2) Kammann U, Gercken J (2010) PAK-Metaboliten in Aalmuttern (Zoarces viviparus) aus der Wismar- Bucht. Umweltwiss Schadst Forsch. 22(5): Kennish, M. J., Practical handbook of estuarine and marine pollution. CRC Press marine science series, United States of America, 524 p. Knutzen J., (1995), Effects on marine organisms from polycyclic aromatic hydrocarbons (PAH) and other constituents of waste water from aluminium smelters with examples from Norway. Sci.Total.Environ., 163, pp Marston Ch.P., Pereira C., Ferguson J., Fischer K., Hedstrom O., Dashwood W-M., Baird W., (2001), Effect of a complex environmental mixture from coal tar containing polycyclic aromatic hydrocarbons (PAH) on the tumor initiation, PAH_DNA binding and metabolic activation of carcinogenic PAH in mouse epidermis, Carcinogenesis, 22, pp Morton, C.H., G. Nyhammer, B.E. Grøsvik, V. Makhotin, A. Geffen, S. Boitsov, K.A. Kvestad, A.B. Kjersem, A. Goksøyr, A. Folkvord, J. Klungsøyr, A. Svardal, S. Meier (2010): Development of 106

212 Atlantic cod (Gadus morhua) exposed to produced water during early life stage. I. Effects on embryos, larvae, and juvenile fish. Mar Environ Res 70(5) Neff, J.M. (2004): Bioaccumulation in marine organisms. Effect of contaminants from oil well produced water, Elsevier, Amsterdam, London, Tokio, pp. OSPAR Ecotoxicological Assessment Criteria, 2009 Pikkarainen, A.-L. (2004): Polycyclic aromatic hydrocarbons in Baltic Sea sediments. Polycyclic Aromatic Compounds, 24: Sicre, M. A., J.C. Marty & A. Saliot (1987): Aliphatic and aromatic hydrocarbons in different sized aerosols over the Mediterranean Sea: occurrence and origin. Atmosphere and Environment 21: Skadsheim, A Cod stocks exposed to crude oils: uptake, metabolism and biomarker effects. Technical report AM-2004/005, Akvamiljo, Randaberg, Norway. Skadsheim, A., Sanni, S., Pinturier, L., Moltu, U.-E., Buffagni, M. & Bracco, L Assessing and monitoring long-range-transported hydrocarbons as potential stressors to fish stocks. Deep-Sea Research Part II. Vol. 56, Issues 21-22, pp Swedish EPA, Swedish Pollutant Release and Transfer Register [online: ]. Vuorinen PJ, Keinänen M, Vuontisjärvi H, Baršienė J, Broeg K, Förlin L, Gercken J, Kopecka J, Köhler A, Parkkonen J, Pempkowiak J, Schiedek D (2006): Use of biliary PAH metabolites as a biomarker of pollution in fish from the Baltic Sea. Mar Pollut Bull 53(8-9): Webster L., Twigg M., Megginson C., Walsham P., Packer G., Moffat C., Aliphatic hydrocarbons and polycyclic aromatic hydrocarbons (PAHs) in sediments collected from the 110 mile hole and along a transect from 58o58.32 N 1o10.38 W to the inner Moray Firth, Scotland. Journal of Environmental Monitoring, 5: Yunker, M.B., R.W. Macdonald, R. Vingarzan, R.H. Mitchell, D. Goyette & S. Sylvestre, (2002): PAHs in the Fraser River basin: a critical appraisal of PAHs ratios as indicators of PAH source and composition. Organic Geochemistry 33:

213 3.6. Lead, Cadmium and Mercury in fish and shellfish Author: Martin M. Larsen Acknowledged persons: Anders Bignert, Elin Boalt, Anna Brzozowska, Galina Garnaga, Michael Haarich, Jenny Hedman, Ulrike Kamman, Thomas Lang, Kari Lehtonen, Jaakko Mannio, Rita Poikane, Rolf Schneider, Doris Schiedek, Jakob Strand, Joanna Szlinder-Richert, Tamara Zalewska General information General properties Metals are naturally occurring substances that have been used by humans since the iron age. The metals Cd, Pb and Hg are the most toxic and regulated metals today, and have no biological function. Mercury is bioaccumulated, mainly in its organic form (Methyl-mercury) and due to high evaporation pressure can be transported from soil to the Baltic, and concentrate in the arctic. Main impacts on the environment and human health Lead and mercury have been connected to impaired learning curves for children, even at small dosage. Lead can cause increased blood preasure and cardio-vaskular problems in adults. Acute metal poisoning generally results in vomiting. Long term exposures of high levels of lead and mercury can affect the neurological system. Mercury can lead to birth defects as seen in Minimatta bay among fishermen in a mercury polluted area, and also after ingestion of methylmercury treated corn in Iran. Cadmium is concentrated in the kidney, and can result in impaired kidney function, and cadmium can exchange for calcium in bones and produce bone fractures (Itai-Itai disease). The HELCOM thematic assessment of hazardous substances (HELCOM 2010) showed high concentrations of mercury and cadmium in biota and sediment all over the Baltic Sea. Lead was not assessed. Status of the indicator on international priority lists and other policy relevance Mercury and cadmium are included in the HELCOM Baltic Sea Action Plan. All the three metals are included in the EU WFD (Pb and Cd in water, Hg in biota) and EU shellfish directive in shellfish. Part of EU food directives, limits set in a range of fish species, shellfish and other seafood. In the OSPAR CEMP to be measured on a mandatory basis in fish, shellfish and sediment (OSPAR 2010). Status of restrictions, bans or use All three metals have been used for centuries, but in the last decades have been banned for most uses. Today, cadmiums and mercurys main use is in rechargeable batteries, and for mercury low energy light sources. Main source of all three metals are burning of fossile fuels. The air deposition is mainly long range transport from outside the Baltic Sea catchment area (60-84%). Sources of mercury was use in amalgams for dentist, reduced by installing mercury traps in sinks and generally reducing amalgams in dental works, as electrodes in paper bleaching, in thermometers and mercury switches and a range of other products that have been faced out. Current legal use include batteries and low energy light sources. For lead, the main source was leaded fuels until their ban in Europe in the 1990ies. Both cadmium and lead have hotspots in connection with metal processing 108

214 facilities, and cadmium is coexisting with all zinc ores, and typically present at levels of 0,5-2% in the final products. Weathering of outdoor zinc-products thus leads to cadmium pollution. Current legal use of cadmium includes rechargeable Ni-Cd batteries and for lead car batteries. GES boundaries and matrices Existing quantitative targets e.g. EACs, BACs and food safety standards Metals have been assessed since the beginning of OSPAR and HELCOM conventions, and the OSPAR assessment criteria are available for cadmium, lead and mercury. Table 1. OSPARs assessment criteria for metals, as used in QSR 2010 (OSPAR 2010). Note that the OSPAR criteria currently are under review, with the target to update them by Sediment (µg/kg dry weight) Mussels (µg/kg dry weight) Fish (µg/kg wet weight) BC BAC ERL BC BAC EC BAC ECfood Cd $ Hg Pb $ $: bivalve tissue. Table 2. EUs assessment criteria for metals in WFD (2008/105). AA- EQS Cd / 0.2 Water (µg/l) Mac-EQS AA- EQS Biota (µg/kg wet weight) Mac-EQS AA- EQS Sediment (µg/kg wet weight) Mac- EQS n.a. n.a. n.a. n.a. Hg 0.05 $ n.a. n.a. n.a. Pb 7.2 n.a. n.a. n.a. n.a. n.a. $: If memberstates don t use biota AA-EQS, the water AA-EQS should have the same protection power as the biota AA-EQS. n.a.: Not applicable Table 3. EUs assessment criteria for metals in marine food sources 466/2001. Fish (µg/kg dry weight) Shellfish (mg/kg wet weight) General specific Crab Bivalves Octopus Cd Hg Pb 0,2 0,

215 Shellfish are available in the whole of the HELCOM area, but assessment criteria are based on Mytilus edulis, available in the more saline parts. The GES boundary values for other species should be verified against Mytilus edulis, and it should also be noted that different Mytilus species exists in the Baltic Sea (Mytilus trossulus), that is more adapted to low salinity waters. Other species used for monitoring is Macoma baltica. Preferred matrix Shellfish or sediment for local surveys. Fish for regional surveys Monitoring the parameter Status of monitoring network (geographical and temporal coverage) Mussels have been used world wide as a monitoring organism for metals. In the Baltic Sea, the latest HELCOM assessment indicated that there is a fairly dense grid of monitoring stations for mussels at the shoreline, but very few stations in the open Baltic Sea. HELCOM and OSPAR guidelines for measuring metals in biota and sediment exist. Guideline for monitoring in water is being developed. Quality assurance in form of international workshops and intercalibrations has been organized yearly by QUASIMEME since 1993, with two rounds each year for water, sediment and biota. Gaps in the monitoring of the compound Further studies are needed for establishing the interspecies correlations for mussels. Existing data of sediment cores from the different regions of the Baltic Sea should be evaluated, and used to establish regional background concentrations. Normalization of sediment data to same level of TOC/clay-silt content should be tested. Present status assessments Known temporal trends (also from sediment core profiles) The temporal trends for metals in biota are inconclusive, as there are both areas with increasing trends of mercury and cadmium, and areas with decreasing trends (HELCOM 2010). There are most decreasing trends, though. Spatial gradients (incl. sources) The spatial gradients are mainly linked to different species or sample type (liver/muscle in fish) for biota. In sediments, the highest levels are found in the Bothnian Bay, eastern Gulf of Finland, off the southeast part of Sweden and in the sound. Cadmium patterns is similar, except for low concentrations in The Sound and high Northern Baltic Proper, Western and Eastern Gotland Basins and the Pomeranian Bay. Recommendation Mercury, Cadmium and Lead have high policy relevance, they are well monitored and they have adverse effects on environment and therefore they should become core indicators. References 110

216 HELCOM (2010) Hazardous substances in the Baltic Sea An integrated thematic assessment of hazardous substances in the Baltic Sea. Balt. Sea Environ. Proc. No. 120B. Available at: 111

217 3.7. Cesium-137 Authors: Jürgen Herrmann, Günter Kanisch and Sven P. Nielsen Acknowledged persons: Members of the HELCOM MORS- PRO project As the indicator already exists as a HELCOM Indicator Fact Sheet, it is presented in that format. What are the concentrations of the artificial radionuclide caesium-137 in Baltic Sea herring? Key message Overall, the Cs-137 activity concentrations in herring in the Baltic Sea basins are approaching pre-chernobyl levels. Radioactive fallout over the Baltic Sea from the Fukushima accident in Japan in March 2011 is very small and may not be detectable in seawater and fish. The corresponding radiological risks are estimated to be negligible. 137 Cs concentration above target value 137 Cs concentration below target value Target level = 2.5 Bq/kg National Land Survey, Finland 81/MYY/07 Finnish Environment Institute SYKE, FINLAND 2011 Data source: Helsinki Commission (HELCOM) 112

218 Figure Cs concentrations (in Bq/kg) in herring muscle in , as annual mean values by basin. GES boundary values have been calculated as averages of pre-chernobyl ( ) concentrations. (Note: variable scales in the graphs) Policy relevance The development and use of nuclear power for military and peaceful purposes have resulted in the production of a number of man-made radioactive substances. Explosions of nuclear weapons in the atmosphere distribute radioactive substances in the environment, while underground nuclear explosions release little or no radioactivity into the environment. The routine operations of nuclear power plants give rise to small controlled discharges of radioactive substances, but accidents at nuclear power plants can cause releases of considerable amounts of radioactivity into the environment. Man-made radionuclides of particular concern to man and the environment are 90 Sr and 137 Cs, which are both formed by nuclear fission. A study on worldwide marine radioactivity enables a comparison of levels of anthropogenic radionuclides in Baltic seawater against those in other marine areas of the world. The Baltic Sea has the highest average 137 Cs levels in surface water (IAEA, 2005). Radioactive fallout from the Chernobyl accident in 1986 is the dominating source for 137 Cs in the Baltic Sea. The levels of 137 Cs in the Baltic Sea, both in water and biota, have shown declining trends since the early nineties. Figure 2. Average surface levels of 137 Cs in the world s oceans and seas (estimates for ). Ingestion of 137 Cs in fish is the dominating exposure pathway of humans from man-made radioactivity in the Baltic Sea. Therefore, 137 Cs concentrations in herring are well suited as indicators for man-made radioactivity in the Baltic Sea. Internationally recommended maximum permitted concentrations of 137 Cs in foodstuff are in the range Bq/kg depending on origin of pollution. Reaching one of the ecological objectives given by the BSAP, i.e. radioactivity at pre- Chernobyl level defined by associated GES boundary values, will help to assure healthy wildlife and all fish being safe to eat, both with respect to radiation exposure. Concentrations of radioactivity in marine wildlife in the Baltic Sea have always been low causing negligible risks to wildlife from radiation exposure and to humans from consumption of seafood. HELCOM Monitoring of Radioactive Substances (MORS) projects, and now the HELCOM MORS Expert Group, have been working to implement the Helsinki Convention on matters related to the monitoring and assessment of radioactive substances in the Baltic Sea. This 113

219 work is based on HELCOM Recommendation 26/3 and supports the work of the HELCOM Monitoring and Assessment Group (HELCOM MONAS), by assessing the progress towards the ecological objective Radioactivity at pre-chernobyl level which was defined in the HELCOM Baltic Sea Action Plan (BSAP). This indicator supports the implementation of the EU Marine Strategy Directive (MSFD) Descriptor 9 on contaminants in fish and seafood for human consumption. The work of HELCOM MORS also supports the implementation of the Euratom Treaty, of which all EU Member States are signatories, which requires actions in relation to monitoring and effects of discharges on neighbouring states. Authors HELCOM Monitoring of Radioactive Substances Expert Group Corresponding authors: Jürgen Herrmann, BSH - Federal Maritime and Hydrographic Agency, Germany Günter Kanisch, vti - Johann Heinrich von Thünen-Institute, Germany Sven P. Nielsen - Risoe National Laboratory for Sustainable Energy, DTU, Denmark References HELCOM (2009): Radioactivity in the Baltic Sea, HELCOM thematic assessment. Balt. Sea Environ. Proc. No. 117: 60 pp. HELCOM (2003): Radioactivity in the Baltic Sea Balt. Sea Environ. Proc. No. 85: 102 pp. HELCOM (1995): Radioactivity in the Baltic Sea Balt. Sea Environ. Proc. No. 61: 182 pp. HELCOM (1989): Three years observations of the levels of some radionuclides in the Baltic Sea after the Chernobyl Accident. Balt. Sea Environ. Proc. No. 31: 155 pp. Herrmann, J. & Kanisch, G. (2010): Concentrations of the artificial radionuclide caesium- 137 in Baltic Sea fish and surface waters. HELCOM Indicator Fact Sheets IAEA (2005): Worldwide marine radioactivity studies (WOMARS). Radionuclide levels in oceans and seas. IAEA-TECDOC Laptev G. & O. Voitsekhovitch (2006): Contribution to RER/2/003 report. IAEA RER/2/003 working document. Outola, I. (2010). Total amounts of the artificial radionuclide caesium -137 in Baltic Sea sediments. HELCOM Indicator Fact Sheets UNSCEAR (1996): Sources and effects of ionizing radiation. Report to the General Assembly, with scientific annex. United Nations, New York. Vartti, V-P. (2010): Liquid discharges of Cs-137, Sr-90 and Co-60 into the Baltic Sea from local nuclear installations. HELCOM Indicator Fact Sheets Temporal trends in concentrations of the artificial radionuclide caesium-137 in plaice and flounder muscle as well as sea water in the Baltic Sea basins Key message Overall, the Cs-137 activity concentrations in plaice and flounder muscle, as well as of surface waters, in the Baltic Sea basins are approaching pre-chernobyl levels. Cs-137 is continuously transported from the Baltic Sea to the North Sea via Kattegat. Routine discharges of radioactivity from nuclear power plants into the Baltic Sea area 114

220 are small and only detectable locally. 137 Cs concentration above target value 137 Cs concentration below target value Target level = 2.9 Bq/kg National Land Survey, Finland, 81/MYY/07 Finnish Environment Institute SYKE, FINLAND 2011 Data source: Helsinki Commission (HELCOM) Figure Cs concentrations (in Bq/kg) in plaice and flounder muscle in , as annual mean values by basin. GES boundary values have been calculated as average of pre-chernobyl ( ) concentrations. 115

221 National Land Survey, Finland 81/MYY/07 Finnish Environment Institute SYKE, FINLAND 2011 Data source: Helsinki Commission (HELCOM) Figure Cs concentrations (in Bq/m 3 ) in surface water (sampling depth <=10m) in , as annual mean values by basin. GES boundary values have been calculated as average of pre-chernobyl ( ) concentrations. (Note: variable scales in the graphs) Background The most significant source of artificial radioactivity in the Baltic Sea is fallout from the Chernobyl accident. The direct total input of 137 Cs from Chernobyl to the Baltic Sea was estimated at 4700 TBq. Secondary riverine input from Chernobyl fallout added further 300 TBq of 137 Cs. Other important sources are global fallout from atmospheric nuclear weapons tests performed during the late 1950s and early 1960s and discharges from the nuclear reprocessing plants Sellafield and La Hague, located at the Irish Sea and the English Channel. The latter sources have become of minor radiological importance, due to significant reduction of 137 Cs discharges from Sellafield in the past two decades. 116

222 The Chernobyl accident resulted in the very uneven 137 Cs deposition in the Baltic Sea region with the Bothnian Sea and the Gulf of Finland having been the two most contaminated sea areas. Since 1986, the spatial and vertical distribution of Chernobylderived 137 Cs has changed as a consequence of river discharges, the mixing of water masses, sea currents, and sedimentation processes (Ilus 2007). In the early phase after Chernobyl, 137 Cs concentrations decreased rapidly in the Gulf of Finland and in the Bothnian Sea, while at the same time increasing in the Baltic Proper (Figure 4). Assessment During the period concentrations of 137 Cs have continued to decrease in all regions of the Baltic Sea (Figure 4). The effective half-life of a radioactive contaminant is the time required for its concentrations to decrease by 50% as a result of physical, chemical and biological processes. Half-lives are specific to each radionuclide and each environment where they may occur. Effective half-lives have been calculated for 137 Cs in various parts of the Baltic Sea. Currently, the effective half-lives of 137 Cs in surface water vary from 9 years in the Bothnian Bay to 15 years in the Baltic Proper. The longer residence time of 137 Cs in the Baltic Proper is most likely due to inflows of more contaminated water from the northern part of the Baltic Sea. In the time period following Chernobyl, , the effective half-lives of 137 Cs were much shorter in most contaminated regions: 0.8 years in the Gulf of Finland and 2.5 years in the Bothnian Sea. The shorter effective half-life of 137 Cs in Gulf of Finland as compared to the Bothnian Sea during was probably due to different water exchange and sedimentation processes in these two regions (Ilus et al. 1993). Based on the inventory estimates, the effective half-life of 137 Cs in Baltic seawater during the period has been 9.6 years. With this decay rate, the 137 Cs inventory in the Baltic Sea would reach pre-chernobyl levels (250 TBq) by the year 2020, presuming that the effective half-life will stay constant, and no substantial remobilization of 137 Cs from sediments will occur. Levels of radionuclides in marine biota are linked to the corresponding levels in seawater and sediments, via accumulation through food chains. The complexity of food chains increases with the trophic level of the species considered. Fish, the biota type in the Baltic Sea most important for human consumption, accumulate most of their radionuclides from food, not from water. The biota of the Baltic Sea received the most significant contribution to their radionuclide levels following the Chernobyl accident in 1986, predominantly in the form of 137 Cs and 134 Cs. As shown in Figure 1 (LINK TO 1 st page), concentrations of 137 Cs are continuing to show generally slowly decreasing trends in herring muscle. In the western parts of the Baltic Sea, i.e. the Kattegat, the Sound, the Belt Sea and the Arkona Sea, the values already show levels slightly below the GES boundary of 2.5 Bq kg -1 wet weight. In the remaining Baltic Sea basins, the GES boundary is still exceeded, in the Bothnian Bay and in the Gotland area, by a factor of up to 5. Figure 3 shows the 137 Cs time series for the flat fish group, consisting of flounder (Platichthys flesus), plaice (Pleuronectes platessa) and dab (Limanda limanda), in the western and southern Baltic Sea areas. Samples of fillets/flesh were used for these measurements. At the end of the assessment period, the values were below about 8 Bq kg - 1 wet weight. The ratio 134 Cs/ 137 Cs in Baltic biota agree very well with that of the Chernobyl fallout. High trophic level species, including predators such as cod and pike, have shown the highest 137 Cs levels, but there was some delay in reaching their maximum values after 1986, when compared to trends in seawater. In the long-term, 137 Cs time trends in biota closely follow the trends in seawater. 117

223 Marine biota concentration factors (CF) show clearly that for marine fish species the 137 Cs CF values increase from western Baltic Sea areas to eastern/northern areas, which is explained by the corresponding increase of freshwater contributions to the seawater (HELCOM 2009). Doses The total collective radiation dose from 137 Cs in the Baltic Sea is estimated at 2600 mansv of which about two thirds (1700 mansv) originate from Chernobyl fallout, about one quarter (650 mansv) from fallout from nuclear weapons testing, about 8% (200 mansv) from European reprocessing facilities, and about 0.04% (1 mansv) from nuclear installations bordering the Baltic Sea area. Dose rates and doses from natural radioactivity dominate except for the year 1986 where the individual dose rates from Chernobyl fallout in some regions of the Baltic Sea approached those from natural radioactivity. The maximum annual dose since 1950 to individuals from any critical group in the Baltic Sea area due to 137 Cs is estimated at 0.2 msv y -1, which is below the dose limit of 1 msv y -1 for the exposure of members the public set out in the EU Basic Safety Standards, It is unlikely that any individual has been exposed from marine pathways at a level above this dose limit considering the uncertainties involved in the assessment. Doses to man due to liquid discharges from nuclear power plants in the Baltic Sea area are estimated at or below the levels mentioned in the Basic Safety Standards to be of no regulatory concern (individual dose rate of 10 µsv y -1 and collective dose of 1 mansv). It should be noted that the assumptions made throughout the assessment were chosen to be realistic and not conservative. Consequently, this also applies to the estimated radiation doses to man. References Ilus, E. (2007): The Chernobyl accident and the Baltic Sea. Boreal Environ Research 12:1-10. Ilus, E., Sjöblom, K.L., Ikäheimonen, T.K., Saxén, R. & Klemola, S. (1993): Monitoring of radionuclides in the Barltic Sea in STUK-A103, Helsinki, 35 pp. Relevance of the indicator for describing the developments in the environment The occurrence of man-made radioactive substances in the Baltic Sea has four main causes: 1. During the United States and the Soviet Union carried out atmospheric nuclear weapons tests, which peaked in the 1960s, causing radioactive fallout throughout the northern hemisphere. This pollution is still noticeable in the seas and on land (UNSCEAR, 2000). 2. The accident at the Chernobyl nuclear power plant in 1986 caused heavy pollution in the vicinity of the power plant, and also considerable fallout over the Baltic Sea. 3. The two European facilities for reprocessing of spent nuclear fuel, at Sellafield in the UK and La Hague in France, have both discharged radioactive substances into the sea. Some of this radioactivity has been transported by sea currents to the North Sea, from where a small proportion has entered the Baltic Sea. 4. Authorised discharges of radioactivity into the sea occurring during the routine operation of nuclear installations in the Baltic Sea region (nuclear power plants and nuclear research reactors) have also contributed. Radioactive substances enter the marine environment either as direct fallout from the atmosphere or indirectly as runoff from rivers. Radionuclides may also be discharged 118

224 directly into the ocean as liquid waste or from dumped solid wastes. Some radionuclides will behave conservatively and stay in the water in soluble form, whereas others will be insoluble or adhere to particles and thus, sooner or later, be transferred to marine sediments and marine biota. Conceptual model of the sources, transport and impacts of caesium-137 in the Baltic ecosystem Figure 5. Conceptual model illustrating the sources and pathways of 137 Cs in the Baltic Sea. Levels of radionuclides in marine biota are linked to the corresponding levels in seawater and sediments, via accumulation through food chains. The complexity of food chains increases with the trophic level of the species considered. Fish, the biota type in the Baltic Sea most important for human consumption, accumulate most of their radionuclides from food, not from water. References UNSCEAR (2000): Sources and effects of ionizing radiation, United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) Report to the General Assembly of the United Nations, New York. Technical data on assessing concentrations of artificial radionuclide 137 Cs in biota Data source Data have been collected by the Contracting Parties of HELCOM and submitted to the MORS (Monitoring of Radioactive Substances) database. Description of data 119

225 The data are based on 137 Cs concentrations of a) herring (Clupea harengus L.), b) flounder (Platichthys flesus L.) and plaice (Pleuronectes platessa L.) and c) surface seawater (samples 0-10 m). Analyses have been made either from round fish (without head and entrails) or filets (herring), and for plaice and flounder from filets, only. Concentrations (Bq/kg) have been calculated from wet weight of the samples. Seawater concentrations (Bq/m 3 ) have been analyzed from surface water samples 0-10 m. Data of each media (herring, plaice and flounder and sea water) have been averaged by basin and by year. Spatial and temporal coverage Herring data covers all the areas except Gulf of Riga and the area of Gotland East and West, as there are data only of 2003 and , respectively. There are no data on the Northern Baltic Proper in recent years ( ). In the Sound, Belt and Arkona Sea several years of data are missing ( , , ). Plaice and flounder data are very scarce both temporarily and spatially covering only four sea areas and several years missing. Sampling on plaice and flounder takes place only in some of the countries. Sea water data coverage is almost complete, except the missing years in the Gulf of Riga and in the Archipelago Sea. Methodology and frequency of data collection The average number of biota samples collected annually by the MORS-PRO group through the sampling period was about 110. Over the whole period the numbers of samples collected were 871 for fish, 170 for aquatic plants, and 131 for benthic animals. More detailed information on national monitoring activities are available for Finland, Germany, Lithuania and Poland. Methodology of data analyses More than ten laboratories from the nine countries bordering Baltic Sea have contributed to the monitoring programmes of Baltic Sea by analyzing radionuclides from marine samples. The various analytical methods used in the different laboratories are summarized the HELCOM thematic assessment: Radioactivity in the Baltic Sea, (HELCOM 2009). Strengths and weaknesses of data Quality assurance is a fundamental part of radioanalytical work, needed to confirm the precision and the long-term repeatability of analyses. The radiochemical procedures and counting techniques used by laboratories are well tested, up-to-date, and similar to those used by laboratories worldwide. Eight intercomparisons were organised during the HELCOM MORS-PRO project period ( ) for seawater and sediment samples, and their results are also presented in the HELCOM thematic assessment (HELCOM 2009). The intercomparisons confirm that the data produced by the MORS group is of very good quality and can be considered comparable. Less than five percent of the results were considered outliers GES boundary values and classification method The GES boundaries for 137 Cs concentrations in sea water, sediments and biota have been set at pre-chernobyl levels. Average concentrations of 137 Cs prior the Chernobyl accident have been used as GES boundary values. These are for herring (2.5 Bq/kg), flounder and plaice (2.9 Bq/kg) and seawater (15 Bq/m³). Further work required 120

226 The reported uncertainties in data vary considerably between laboratories. Each laboratory calculates uncertainties in its own particular way, and the harmonization of uncertainty calculations would improve the comparability of the data. References HELCOM (2009): Radioactivity in the Baltic Sea, HELCOM thematic assessment. Balt. Sea Environ. Proc. No. 117: 60 pp. 121

227 3.8 Tributyltin (TBT) and the imposex index Authors: Rita Poikane, Jakob Strand and Martin M. Larsen Acknowledged persons: Anders Bignert, Elin Boalt, Anna Brzozowska, Galina Garnaga, Michael Haarich, Jenny Hedman, Ulrike Kamman, Thomas Lang, Kari Lehtonen, Jaakko Mannio, Rolf Schneider, Doris Schiedek, Joanna Szlinder-Richert, Tamara Zalewska General information General properties Tributyltin compounds (TBT-ion CAS No ( )) belong to organometallic compound (OTC) class. Usually triorgancompounds used as biocide antifoulant paints, agricultural pesticides, molluscicides and wood preservative. TBT compounds are hydrophobic and associate strongly to particles in natural waters and ultimately are deposited in the sediments. Adsorption to organic rich particles (soils and sediments) is stronger than to particles (soils and sediments) of mineral origin. Degradation (photodegradation or biodegradation) of TBTs in environment occurs due to dealkylation and depends on aerobic condition. Degradation of TBT under anaerobic condition may last long time. Half-life of TBTs in natural waters may range from a few days to several weeks but in soils and sediments one to few years. TBTs accumulate in individual organisms often stronger in benthic organisms than in fish. TBT and triphenyltin accumulate in the food web, but a large variance in accumulation potential has been found between species, even within the same trophic level. This is probably due to different abilities to degradate TBT or triphenyltins between the species. Main impacts on the environment and human health TBT compounds are very toxic to aquatic organisms especially to benthic organisms. As a consequence of toxic effects is shell deformation, endocrine disruption and impaired larval recruitment as well as immuno-suppression. TBTs cause endocrine disruption and different types of malformation of the genital system for certain marine and freshwater bivalve and gastropods species at very low concentrations. The process is known as imposex and intersex. For human health high levels of TBT are potential risk to cause endocrine disruption. Several OTCs have negative toxic effects: immumosuppresive, neurotoxicity, hepatoxicity, renal and dermal toxicity, teratogenic and carcinogenic effects. The ecological relevance of imposex and intersex development in marine snails is high because of the links to reproductive disorders. In severe stages, reproductive failure in female snails occurs as they are getting sterile. For instance, sterile female of the red whelk Neptunea antiqua has been found in the Inner Danish waters (Strand 2009). Effects of sterile females on population structures have been shown in other studies of TBT contaminated areas. The HELCOM thematic assessment of hazardous substances (HELCOM 2010) showed that the thresholds for fish (15 µg kg -1 ww), mussels (30 µg kg -1 dw) and sediment (2 µg kg -1 dw) were exceeded all over the Baltic Sea. Status of a compound on international priority lists and other policy relevance The recent environmental issues surrounding tributyltin have been increasing environmental pressures on all butyltin compounds and other OTCs in general. 122

228 TBT is a substance, which is identified on the priority list of the HELCOM Baltic Sea Action Plan. Tributyltin compounds (TBT-ion) are classified as Priority Hazardous substances under the Daughter Directive (2008/105/EC) of the EC Water Framework Directive (2000/60/EC). The EU Marine Strategy Framework Directive (2008/56/EC) refers to the priority substances of the WFD. Progress towards good environmental status will depend on whether pollution is progressively being phased out, i.e. the presence of contaminants in the marine environment and their biological effects are kept within acceptable limits, so as to ensure that there are no significant impacts on or risk to the marine environment. OSPAR supports implementation of EU legislation and measurements of organic tin compounds are included as a part of The Coordinated Environmental Monitoring Programme (CEMP) on a mandatory basis (OSPAR 2010). Imposex, caused by TBT is also part of OSPAR CEMP and therefore are to be measured on a mandatory basis in the North Atlantic region (OSPAR 2010). Status of restrictions, bans or use In accordance with point 20 of Annex XVII to Regulation (EC) No 1907/2006 of the European Parliament and of the Council of 18 December 2006 concerning the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH), establishing a European Chemicals Agency, amending Directive 1999/45/EC and repealing Council Regulation (EEC) No 793/93 and Commission Regulation (EC) No 1488/94 as well as Council Directive 76/769/EEC and Commission Directives 91/155/EEC, 93/67/EEC, 93/105/EC and 2000/21/EC pursuant to Commission Regulation (EC) No 552/2009 of 22 June 2009 amending Regulation (EC) No 1907/2006 of the European Parliament and of the Council on the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) as regards Annex XVII. Organostannic compounds shall not be placed on the market, or used, as substances or in mixtures: 1. where the substance or mixture is acting as biocide in free association paint. 2. where the substance or mixture acts as biocide to prevent the fouling by microorganisms, plants or animals of: (a) all craft irrespective of their length intended for use in marine, coastal, estuarine and inland waterways and lakes; (b) cages, floats, nets and any other appliances or equipment used for fish or shellfish farming; (c) any totally or partly submerged appliance or equipment. 3. where the substance or mixture is intended for use in the treatment of industrial waters. On the global level, the use of TBT in antifouling paints has been banned by the 2001 International Convention on the Control of Harmful Anti-fouling Systems on Ships (AFS convention), which entered fully into force in From 1 January 2008, ships bearing an active TBT coating on their hulls will no longer be allowed in Community ports (782/2003/EC). All Baltic Sea countries except Russian Federation have ratified the Convention. GES boundaries and matrix Existing quantitative targets e.g. EACs, BACs and food safety standards Source OSPAR Value and description 123

229 EAC sediment EAC water EAC mussel BAC/BC sediment BAC/BC water BAC/BC mussel LC/BC mussel EC EQS water Draft EQS water Draft EQS biota Unofficial EQS sediment Unofficial EQS biota Food stuff directive Effect Range -Low ERL sediment Other PNEC WHO (uptake by food) 0.01 ug TBT/kg DW 0.1 ng TBT/L 12 ug TBT/kg DW Zero for man-made compound Zero for man-made compound Zero for man-made compound 1 ug TBT/kg DW 0.2 ng TBT/L (AA) 1.5 ng TBT/L (MAC) 0.02 ug TBT/kg DW 230 ug TBT/kg WW (predators second poisoning) 15.2 ug TBT/kg WW for seafood AA 0.2 ng/l; MAC 1.5 ng/l TBT / 1.0 ng/l TPhT 0.25 ug per kilo of human weight per day RecommendedGES boundaries Water: 0.2 ng/l Sediment: 0.02 ug/kg Biota: 12 ug/kg DW (for mussels) Seafood: 15.2 ug/kg WW for seafood Preferred matrix Water Optional. (low solubility in water, high level of attachment to particles) Sediments Optional. (Could be a co-factor in decreasing biodiversity in areas with low biodiversity) Biota (mussels or gastropoda snails): Preferred. (mussels are sensitive to TBT). Fish (liver) can be used as alternative if molluscs are not present. Biological effects assessment classes for ECOQO on imposex/intersex Assessment classes for N. lapillus and other selected gastropods Assessment class N. lapillus L. littorea N. reticulatus B. undatum N. antiqua Criterion VDSI ISI VDSI PCI VDSI A Level of imposex is close to zero B Level of imposex (~30-~100% of the females have imposex) indicates <0.3 <0.3 <0.3 <0.3 < <2.0 <0.3 <0.3 < <

230 exposure to TBT concentrations below the EAC derived for TBT C Level of imposex indicates exposure to TBT concentrations higher than the EAC derived for TBT <4.0 <0.3 - < < D Reproductive capacity in the gastropod populations is affected as a result of the presence of sterile females, but some reproductively capable females remain <2.0 May occur beyond 4.0 May occur beyond 4.0 May occur beyond 4.0 E Populations are unable to reproduce. The majority, if not all females within the population have been sterilised >2.0 F Populations are absent/expired - Draft 2011 OSPAR background document for TBT. Linking assessment classes between imposex and concentrations of TBT in water, mussels and sediment. Monitoring the compound Status of monitoring network (geographical and temporal coverage) Country Water Sediments Biota Denmark 40 samples per year (rotating sampling scheme) Standard mussel program ~66 samples, shellfish directive ~13 samples, flounder ~12 stations per year. Estonia Screening studies (2008/2009) within HELCOM BSAP project in muscle of Perca fluviatilis and Clupea harrengus. Finland Since 2009 monitoring of organotin compounds is planned and station net is not decided yet. Since 2009 yearly organotin compounds measurements in perches and herrings from

231 Germany Latvia Lithuania Since station in coastal area 8 times per year. Screening of 4 rivers estuaries (2009/2010): 3 largest rivers of the Gulf of Riga, 1 river of the Baltic Proper. Since 2010 national monitoring program: yearly sampling at 4 stations in the coastal area, 2 station in the harbour area and 2 stations in the Curonian Lagoon. Sampling frequency >5yr. Since stations: 5 coastal and 5 open area 2 times per year, since stations all in coastal area every 2-3 years. Screening of 4 rivers estuaries (2009/2010): 3 largest rivers of the Gulf of Riga, 1 river of the Baltic Proper. Planned in national monitoring program from 2011: yearly sampling at 4 stations in the coastal area, 2 station in the harbour area and 3 stations in the Curonian Lagoon. Since 2009 yearly monitoring of TBT in Klaipeda harbour area (several stations) performed by authorities of harbour. sampling areas. Biota since coastal areas 2 times per year. Screening studies (2008/2009) within HELCOM BSAP project in muscle of Perca fluviatilis and Clupea harrengus. Screening studies (2008/2009) within HELCOM BSAP project in muscle of Perca fluviatilis and Clupea harrengus. Poland Data from publications. Data from publications. Russia Sweden Monitored yearly in coastal areas at 13 reference (no local discharges known) stations. Yearly in Hydrobia ulvae at 12 stations (5 geographical regions). Coastal areas. Gaps in the monitoring of the compound Country Denmark Estonia Finland Germany Latvia Lithuania Poland Russia Sweden Gaps Little geographic coverage around Bornholm. Time trend station at Bornholm will be established from 2011 onwards. Sediments will be taken according to a rotating sampling scheme, so no temporal trends will be available for sediments. Sediment profile sites not decided yet. TBT measurements are performed in fish not in mussels. No data about TBT in sediments and in mussels. TBT is not included in monitoring program plan till Monitoring program does not include TBT measurements in biota. Present status assessments Known temporal trends (also from sediment core profiles) Since the EU ban on TBT, temporal trends showed that TBT concentration in sediments decrease as well as in benthic biota and fishes. In some regions TBT concentration remains high but decreasing trend can be expected in a coming years. 126

232 Spatial gradients (incl. sources) Evaluation of spatial gradient in all the Baltic Sea is rather difficult due to the gaps in geographical coverage. Clear spatial gradients have been established in relation to areas with high ship densities, which are in line with that ship traffic is regarded as the main source of TBT in marine environments. Quality Assurance of imposex OSPAR has developed international monitoring guidelines for imposex and intersex in five species of marine snails (OSPAR 2008). An ICES guideline also exists for monitoring intersex in periwinkle (Oehlmann 2004). A detailed method description for imposex in the mud snail Hydrobia can be found in Schulte-Oehlmann et al. (1997) Quality Assurance in form of international workshops and intercalibrations has been organized almost yearly by QUASIMEME since National workshops have also been organized three times in relation to the Danish monitoring program NOVANA. Recommendation TBT measurements in benthic biota should be included as core indicator for the next 8 10 years till next indicator revision. Measurements in sediment and water can support or supplement biota monitoring in areas with little or no target organisms. Imposex and intersex should become core indicators, because they reflect the effects of TBT in sensitive organisms in the marine environment very well. They can be regarded as counterpart of TBT measurements e.g. in water, sediments and biota. A scheme for assessing imposex/intersex and chemical measurements have been described by OSPAR and Strand et al (2006), and can be used to give an overall assessment of the status of TBT contamination. References: HELCOM (2010) Hazardous substances in the Baltic Sea An integrated thematic assessment of hazardous substances in the Baltic Sea. Balt. Sea Environ. Proc. No. 120B. Available at: Oehlmann, J Biological effects of contaminants: Use of intersex in the periwinkle (Littorina littorea) as a biomarker of tributyltin pollution. ICES Techniques in Marine Environmental Sciences (TIMES) No. 37, 22pp. OSPAR (2004). Provisional JAMP Assessment Criteria for TBT Specific Biological Effects. OSPAR agreement OSPAR (2008a). 2007/2008 CEMP Assessment: Trends and concentrations of selected hazardous substances in sediments and trends in TBT-specific biological effects. Assessment and Monitoring Series, OSPAR Commission 2008, 36 pp. OSPAR (2008b). JAMP Guidelines for Contaminant-Specific Biological Effects. Technical Annex 3: TBT-specific biological effects monitoring. OSPAR Agreement OSPAR (2010). OSPAR Coordinated Environmental Monitoring Programme (CEMP). Reference number: Schulte-Oehlmann et al. (1997). Imposex and reproductive failure in Hydrobia ulvae (Gastropoda: Prosobranchia). Marine Biology 128: Strand, J. et al. (2006): TRIBUTYLTIN (TBT) Forekomst og effekter i Skagerrak (in Danish with English summary). Forum Skagerrak II Projektgrupp: Arbejsgruppe WP2 - Miljøfremmede stoffer, affald og oliespild

233 3.9. Pharmaceuticals: Diclofenac and 17-alpha-ethinylestradiol Author: Christina Ruden Acknowledged persons: Anders Bignert, Elin Boalt, Anna Brzozowska, Galina Garnaga, Michael Haarich, Jenny Hedman, Ulrike Kamman, Thomas Lang, Kari Lehtonen, Jaakko Mannio, Rita Poikane, Rolf Schneider, Doris Schiedek, Jakob Strand, Joanna Szlinder-Richert, Tamara Zalewska General information General properties Diclofenac is an active pharmaceutical ingredient belonging to a group called nonsteroidal anti-inflammatory drugs (NSAIDs). It works by reducing hormones that cause inflammation and pain in the body. Diclofenac is sufficiently persistent to pass sewage water treatment plants and reach surface waters (Tixier, C. et al. Environ. Sci. Technol., 2003, 37(6): DOI: /es025834r). In many cases the reduction of diclofenac waste water treatment plants is close to zero, i.e. the same concentration of diclofenac is found in the treated effluent water as in incoming waters. In the aquatic environment, pharmaceuticals have been widely found and Diclofenac is a drug that is detected at high frequency. Zang et al. Chemosphere (8): Diclofenac is bioaccumulating in fish exposed to treated sewage waters (Brown et al. Environmental Toxicology and Pharmacology 24(3)2007: ) 17α-ethinylestradiol (EE2) is an active pharmaceutical ingredient used as a component of combined contraceptives. EE2 is an endocrine disrupter of great concern, with fish feminization induced for concentrations around 1 ng per litre or less. Main impacts on the environment and human health Diclofenac is toxic to the kidneys in fish. NOEC 1 micro gram /liter water (e.g. Schwaiger et al. Aquatic Toxicology 2004, 68: ) Diclofenac in the marine environment is not likely to cause acute toxic effects at environmental concentrations. However chronic effects need cautious consideration. Kidney failure caused by residues of the analgesic and anti-inflammatory drug diclofenac, is considered responsible for a decline by >95% in the population of oriental white-backed vulture, one of the (previously) most common raptors in India and Pakistan (Oaks et al, 2004, Shultz et al, 2004; Reddy et al, 2006; Swan et al, 2006; Cuthbert et al, 2006, 2007). Extensive evidence points to a causal link between exposure to ethinylestradiol and feminization of fish in the environment. These mainly include the following observations: (1) Ethinylestradiol at sub ng/l levels cause both vitellogenin induction (Purdom et al, 1994; Thorpe et al, 2003; Jobling et al, 2003) and intersex/sex-change in fish (Örn et al, 2003; Parrot and Blunt, 2005). (2) Ethinylestradiol up to a few ng/l is found in effluents from waste water treatment plants and water recipients. (3) Fish exposed to waste water treatment plant effluents can bioconcentrate estrogens, including ethinylestradiol, very efficiently as demonstrated by extremely high levels of conjugated metabolites in their bile (Larsson et al. 1999). 128

234 (4) Frogs have been shown to approximately as sensitive as fish to EE2 exposures; 1.7 ng/l resulted in skewed sex ratios of adult frogs and malformations of their gonadal duct system (Pettersson and Berg. Environmental Toxicology and Chemistry (5) Status of a compound on international priority lists and other policy relevance Both are on the draft revision list for EU Priority Substances Status of restrictions, bans or use The use of Diclofenac as a human drug is not restricted. India is phasing out diclofenac because of its impacts on the vulture population. EE2 is not restricted. GES boundaries and matrix Existing quantitative targets Source Diclofenac EE2 EC Draft QS water 0.1 µg L ng L -1 Draft QS biota 1 µg kg -1 ww µg kg -1 ww Draft QS sediment NOEC (open literature) = 1 µg/l LOEC = approximately 1 ng/l Recommended GES boundaries Water: 0.1 µg L -1 Sediment: Biota: 1 µg kg -1 ww Seafood: Water: ng L -1 Sediment: Biota: µg kg -1 ww Seafood: According to SCHER (2011), there is uncertainty in the background material of the EQS and therefore the GES boundary for diclofenac is only tentative. The SCHER opinion on the EE2 supports the WFD WG E proposal (SCHER 2011), but the EQSs are still considered tentative. Preferred matrix Diclofenac can readily be analysed in water and in fish plasma. EE2 can be analyzed in water and in fish plasma. Monitoring the compound Status of monitoring network (geographical and temporal coverage) Diclofenac and EE2 is not monitored anywhere in the Baltic Sea, but it is included at least in the Swedish EPA s screening program. Gaps in the monitoring of the compound There are gaps. Recommendation Diclofenac and EE2 are recommended as core indicators, because of their policy relevance and known adverse effects in environment. 129

235 3.10. Lysosomal membrane stability Author: Katja Broeg, Doris Schiedek and Kari Lehtonen ICES SGEH Biological Effects methods Background Documents for the Baltic Sea region (ICES/OSPAR document from the ICES SGIMC Report 2010, complemented and modified by SGEH 2011 with information relevant for application in the Baltic Sea region) Description of the indicator Lysosomal functional integrity is a generic common target for environmental stressors in all eukaryotic organisms from yeast and protozoans to humans (Cuervo, 2004), that is evolutionarily highly conserved. The stability of lysosomal membranes is a good diagnostic biomarker of individual health status (Allen and Moore, 2004; Broeg et al., 2005; Köhler et al., 1992, Lowe et al., 2006). Dysfunction of lysosomal processes has been mechanistically linked with many aspects of pathology associated with toxicity and degenerative diseases (Cuervo, 2004; Köhler, 2004; Köhler et al., 2002; Moore et al., 2006a, b, Broeg 2010). Lysosomes are known to accumulate many metals and organic xenobiotics. Metals such as copper, cadmium and mercury are known to induce lysosomal destabilisation in mussels (Viarengo et al., 1981, 1985a, b). LMS is strongly correlated with the concentration of PAHs and PCBs in mussel tissue (Cajaraville et al., 2000; Krishnakumar et al., 1994; Moore, 1990; Moore et al., 2006a, b; Viarengo et al., 1992, Strand et al., 2009), as well as organochlorines and PCB congeners in the liver of fish (Köhler et al., 2002, Broeg et al., 1992). LMS of various species of mussel and fish from different climate zones clearly reflect gradients of complex mixtures of chemicals in water and sediments (Da Ros et al., 2002; Pisoni et al, 2004; Schiedek et al., 2006, Barsiene et al., 2006; Sturve et al., 2005), point sources of pollution, single pollution events and accidents (Garmendia et al., 2011; Einsporn et al. 2005; Broeg et al., 2002, Broeg et al., 2008, Nicholson and Lam, 2005) and also serves for the discovery of new Hot Spots of pollution (Bressling, 2006; Moore et. al., 1998; 2004a). LMS can also be used as a prognostic tool, able to predict liver damage and tumour progression in the liver of various fish species (Broeg et al., 1999; Diamant et al., 1999; Köhler et al., 2002; Köhler, 2004, Broeg, 2010). Also hepatopancreatic degeneration in molluscs, coelomocyte damage in earthworms, enhanced protein turnover as a result of radical attack on proteins, and energetic status an indicator of fitness of individuals within a population can be predicted (Allen and Moore, 2004; Kirchin et al., 1992; Köhler et al., 2002; Moore et al., 2004a, 2006a; Nicholson and Lam, 2005; Svendsen and Weeks, 1995; Svendsen et al., 2004). Recently it is tested for its prognostic potential with respect to reproductive disorders in amphipods in the Baltic Sea. For eelpout, this prognostic potential could already been demonstrated. Low membrane stabilities coincided with distinct reproductive disorders that indicated adverse effects at the population level (Broeg and Lehtonen, 2006). Thus, LMS has been adopted by UNEP as part of the first tier of techniques for assessing harmful impact in the Mediterranean Pollution programme (MEDPOL Phase IV) and is also recommended as biomarker to be included into the OSPAR Coordinated Environmental Monitoring Programme (pre-cemp). LMS of blue mussel from the Inner Danish waters and the Danish Belt Sea is part of the Danish monitoring programme NOVANA since 2003 (Strand et al. 2009). It is also under consideration for the Swedish monitoring programme (Granmo, pers. comm.). Methods applied to assess LMS are the Neutral Red Retention test (NRR) on living cells like mussel haemocytes, and the cytochemical test on serial cryostat sections performed from snap-frozen tissue. These methods are described in detail by Moore et al. (2004b). Currently a new method is developed for the assessment of LMS in single tissue sections of small indicator species like amphipods (Broeg and Schatz, in prep.). 130

236 Beside LMS, adverse lysosomal reactions to xenobiotic pollutants include swelling, lipidosis (pathological accumulation of lipid), and lipofuscinosis (pathological accumulation of age/stress pigment) in molluscs but not fish (Köhler et al. 2002; Moore, 1988; Moore et al., 2006a, b; Viarengo et al., 1985a). LMS in blue mussels is correlated with oxygen and nitrogen radical scavenging capacity (TOSC), protein synthesis, scope for growth and larval viability and inversely correlated with DNA damage (incidence of micronuclei), lysosomal swelling, lipidosis and lipofuscinosis (Dailianis et al., 2003; Kalpaxis et al., 2004; Krishnakumar et al., 1994; Moore et al., 2004a, b, 2006a; Regoli, 2000; Ringwood et al., 2004). In fish liver, LMS is strongly correlated with a suppression of the activity of macrophage aggregates, and lipidosis (Broeg et al., 2005). A conceptual mechanistic model has been developed linking lysosomal damage and autophagic dysfunction with injury to cells, tissues and the whole animal; and the complementary use of cell-based bioenergetic computational model of molluscan hepatopancreatic cells that simulates lysosomal and cellular reactions to pollutants has also been demonstrated (Allen and McVeigh, 2004; Lowe, 1988; Moore et al., 2006a, b, c). Various biomarker indices and decision support systems have been developed based on LMS as guiding parameter to interpret the results of other biomarkers (Fig.1) which show bell-shaped responses since it reflects deleterious effects of various classes of contaminants in an integrative linear manner (Dagnino et al., 2007, Broeg et al., 2005, Broeg and Lehtonen, 2006). Fig.1. Progression of biological effects detected on the basis of LMS in individual flounder of the German Bight (Broeg et al., 2005). Confounding factors LMS is an integrative indicator of individual health status and will be affected also by noncontaminant factors such as severe nutritional deprivation, severe hyperthermia, prolonged hypoxia, and liver infections associated with high densities of macrophage aggregates (Moore et al., 1980; Moore et al., 2007, Broeg, 2010). Processing for neutral red retention (NRR) in samples of molluscs adapted to low salinity environments should use either physiological saline adjusted to the equivalent ionic strength or else use ambient filtered seawater. The major confounding factor in respect of biomonitoring is the adverse effect of the final stage of gametogenesis and spawning in mussel, which is a naturally stressful process (Bayne et al., 1978). In general, this period should be avoided anyway for sampling 131

237 purposes, as most physiological processes and related biomarkers are adversely affected (Moore et al., 2004b). However, for fish, spawning has only a minimal effect on LMS and does not mask harmful chemical induced damage to LMS (Köhler, 1990, 1991). Salinity changes didn t provoke significant effects on LMS in flounder (Broeg, unpublished results). Using the cytochemical approach, temperature stress during the tissue incubation at 37 C has to be considered when working with animals from subpolar and polar regions. For these animals, temperature stress leads to a significant decrease of LMS. In this case, temperature during incubation should not be higher than 20 C above the ambient temperature of the sampling location to avoid effects of too severe hyperthermia. Ecological relevance Lysosomal integrity is directly correlated with physiological scope for growth (SFG) and is also mechanistically linked in terms of the processes of protein turnover (Allen and Moore, 2004; Moore et al., 2006a). Ringwood et al. (2004) have also shown that LMS in parent oysters is directly correlated with larval viability. It is also inversely correlated with reproductive disorders in eelpout (Broeg and Lehtonen, 2006). Finally, LMS is directly correlated with diversity of macrobenthic organisms in an investigation in Langesund Fjord in Norway (Moore et al., 2006b), and with parasite species diversity in flounder from the German Bight (Broeg et al., 1999). Quality Assurance Intercalibration exercises for LMS techniques have been carried out in the ICES/UNESCO- IOC-GEEP Bremerhaven Research Workshop, the UNEP-MEDPOL programme, in the framework of the EU-project BEEP and the BONUS+ project BEAST as well as for the neutral red retention method in the GEF Black Sea Environmental Programme (Köhler et al., 1992; Lowe et al., 1992; Moore et al., 1998; Viarengo et al., 2000, BEEP, 2004). The results from these operations indicated that both techniques could be used in the participating laboratories in an effective manner with insignificant inter-laboratory variability. Comparisons of the cytochemical and the neutral red retention techniques have been performed in fish liver (ICES-IOC Bremerhaven Workshop, 1990) and in mussels experimentally exposed to PAHs (Lowe et al., 1995). An AWI/Imare international workshop on Histochemistry of lysosomal disorders as biomarkers in environmental monitoring in Bremerhaven, 2008, demonstrated good correspondence of results obtained by the participants by applying various different assessments by computer assisted image analysis and light microscopy. In 2010, an ICES\OSPAR Workshop on Lysosomal Stability Data Quality and Interpretation (WKLYS) has been held in Alessandria, Italy (ICES, 2010). This workshop concentrated on the NRR. Guidelines for LMS procedures are published as ICES Times Series (Moore et al., 2004b), and in the UNEP/Ramoge biomarker manual (UNEP, 1999). Assessment Criteria Health status thresholds for NRR and cytochemical methods for LMS have been determined from data based on numerous studies (Cajaraville et al., 2000; Moore et al., 2006a, Broeg et al., 2005, Broeg and Lehtonen, 2006). LMS is a biophysical property of the bounding membrane of lysosomes and appears to be largely independent of taxa. In all organisms tested to date, which includes protozoans, annelids (terrestrial and marine), molluscs (freshwater and marine), crustaceans (terrestrial 132

238 and aquatic), echinoderms and fish, the absolute values for measurement of LMS (NRR and cytochemical method) are directly comparable. Furthermore, measurements of this biomarker in animals from climatically and physically diverse terrestrial and aquatic ecosystems also indicate that it is potentially a universal indicator of health status. For the cytochemical method animals are considered to be healthy if the LMS is >20 minutes; stressed but compensating if <20 but >10 minutes and severely stressed and probably exhibiting pathology if <10 minutes (Moore et al., 2006a, Broeg et al., 2005, Broeg and Lehtonen, 2006). Similarly for the NRR method, animals are considered to be healthy if NRR is >120 minutes; stressed but compensating if <120 but >50 minutes and severely stressed and probably exhibiting pathology if <50 minutes (Moore et al., 2006a). The use of different fish species as indicators at identical locations in the Baltic Sea showed species differences with respect to their liver LMS in the following order: Herring < Eelpout < Dab < Flounder. At locations which are higher affected by anthropogenic impact, differences are pronounced. Potential causes are higher fishing stress and high frequencies and intensities of parasite infections in almost all livers of herring and eelpout as confounding factors. Thus, for these species the assessment criteria for the cytochemical test are defined as follows: animals are considered to have no toxically-induced stress if the LMS is >15 minutes; are stressed but compensating if <15 but >8 minutes and are severely stressed and probably exhibiting irreversible toxicopathic alterations if <8 minutes (Broeg et al., in prep.). The following species have been tested as indicator species for LMS in the different regions of the Baltic Sea: Fish Bivalves Amphipods Herring (Clupea harengus), flounder (Platichthys flesus), eelpout (Zoarces viviparus), dab (Limanda limanda). Blue mussel (Mytilus edulis, Mytilus trossulus) Gammarids, Monoporeia affinis Biological effect method (unit, other information) Target species/ tissue/endpoint Lysosomal membrane stability (LMS) (minutes) a. Cytochemical method Herring and eelpout - liver Perch and flounder - liver All other species studied - liver, digestive gland Method modification: Acridine Orange b. In vivo method (Neutral Red Retention test) Amphipods Mytilus spp. haemocytes BAC under development in BEAST EAC under development in BEAST Acknowledgements Research on the application of LMS as a biomarker for the monitoring and assessment of general toxic effects in different Baltic Sea regions and indicator organisms has been funded by the EU Project BEEP Contract n ECK3-CT , and the BONUS+ Project BEAST. 133

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242 3.11. Fish Disease Index: Externally visible fish diseases, macroscopic liver neoplasms and liver histopathology Authors: Thomas Lang, Doris Schiedek & Kari Lehtonen ICES SGEH Biological Effects methods Background Documents for the Baltic Sea region (ICES/OSPAR document from the ICES SGIMC Report 2011, complemented and modified by SGEH 2011 with information relevant for application in the Baltic Sea region) Description of the indicator Diseases of wild marine fish have been studied on a regular basis by many ICES Member Countries for more than two decades. Disease surveys are often integrated with other types of biological and chemical investigations as part of national monitoring programmes aiming at an assessment of the health of the marine environment, in particular in relation to the impact of human activities (Lang, 2002). On an international level, fish disease data have been used for environmental assessments in the framework of the North Sea Task Force and its Quality Status Report (North Sea Task Force, 1993), the OSPAR Quality Status Reports 2000 and 2010 (OSPAR Commission, 2000, 2010a) and in the 3rd and 4th HELCOM assessments (HELCOM, 1996, 2002). Studies on externally visible diseases, macroscopic liver neoplasms and liver histopathology are on the list of techniques for general and contaminant-specific biological effects monitoring as part of the OSPAR pre-cemp (OSPAR, 2010b). In the Baltic Sea, fish diseases have been monitored on a more or less regular basis since the beginning of the 1980s (Lang, 2002). Baltic Sea countries currently carrying out fish disease surveys in the Baltic Sea on an annual basis are Germany (vti Institute of Fisheries Ecology, Cuxhaven), Poland (Sea Fisheries Institute, Gdynia) and Russia (AtlantNIRO, Kaliningrad) (ICES, 2011). While Polish and Russian studies are restricted to national EEZs, the German programme covers larger areas of the southern Baltic Sea, including sampling sites in ICES Subdivision 22, 24, 25 and 26. Other Baltic Sea countries not mentioned have some experience in fish disease monitoring from studies carried out in the 1980s and 1990s, but have stopped regular activities. Most of the regular disease surveys are so far focussed on fish species sampled in offshore areas, with the main target species flounder (Platichthys flesus), cod (Gadus morhua) and, to a lesser extent, herring (Clupea harengus). In the western Baltic Sea, the common dab (Limanda limanda) is another target species. Other common species have been examined on a more irregular basis. A wide and species-dependent range of diseases (incl. some parasite species) is being monitored, with an emphasis on externally visible lesions and parasites. Only in flounder have regular studies on liver pathology (largely related to neoplastic lesions) been included partly (Lang et al., 2006). The methodologies applied largely follow ICES guidelines (Bucke et al., 1996, Feist et al., 2004) which can easily be adapted for other species relevant for fish monitoring in the Baltic Sea. Methodologies and diagnostic criteria involved in the monitoring of contaminant-specific liver neoplasms and liver histopathology have largely been developed based on studies with flatfish species, in Europe mainly dab and flounder, but can also be adapted to other flatfish species (e.g. plaice (Pleuronectes platessa) and also to bottom-dwelling roundfish species, such as viviparous blenny (Zoarces viviparus). New disease trends in Baltic Sea fish species have been reviewed regularly by the ICES Working Group on Pathology and Diseases of Marine Organisms (WGPDMO) and relevant information has partly been incorporated in the HELCOM Periodic Assessments (HELCOM, 1996, 2002). However, compared to the North Sea, fish disease monitoring and 137

243 assessment in the Baltic Sea is less developed and, so far, only few fish disease data from the Baltic Sea have been submitted to the ICES Environmental Databank. In the light of present developments in ICES and in HELCOM, the ICES WGPDMO recommended at its 2007 meeting that Baltic Sea countries running fish disease monitoring programmes in the Baltic Sea make attempts to submit their disease data to the ICES Environmental Databank in order to make them available for integrated assessments, such as those carried out by the ICES/HELCOM Working Group on Integrated Assessment of the Baltic Sea (WGIAB) and as part of the periodic HELCOM assessments (ICES, 2007). In 2005, the ICES Workshop on Fish Disease Monitoring in the Baltic Sea (WKFDM) started to develop an integrative tool for the analysis and assessment of the health status of fish which was later termed Fish Disease Index (FDI) (ICES, 2006a,b). In contrast to previous attempts, largely focusing on the analysis and assessment of changes in prevalence of single diseases, the FDI approach was developed with the primary aim to analyse and assess changes in spatial and temporal patterns in the overall disease status of fish, by summarising information on the prevalence of a variety of common diseases affecting the fish species as well as their severity grades and effects on the host into a robust numerical value calculated for individual fish and, as mean values, for representative samples from a population. The common dab (Limanda limanda) from the North Sea was selected as a model species for the construction of the FDI approach because most existing data are from fish disease surveys with the dab as primary target species. However, the FDI approach is constructed in a way that it can easily be adapted to other fish species for which disease data are available. The development of an analogous FDI approach for Baltic Sea fish species is on the agenda of the ICES Working Group on Pathology and Diseases of Marine Organisms (WGPDMO) and will be finalised during 2011 (ICES, 2011). In first instance, the efforts will focus on flounder and cod, species for which most data are available from national fish disease monitoring in the Baltic Sea. Fish disease surveys and associated FDI data analyses and assessments according to the OSPAR and ICES requirements address four categories of diseases. These categories also are the basis for fish disease monitoring/assessment in the Baltic Sea (see Table 1). Other target species and diseases may be added when more experience and data are available. Table 1. Categories and diseases/lesions for disease monitoring and assessment with Baltic Sea fish species (ICES, 2011; modified) Disease Category Externally visible diseases Macroscopic liver neoplasms Diseases/Lesions Flounder (P. flesus) Cod (G. morhua) Lymphocystis Acute/healing skin ulcerations Acute/healing fin rot/erosion Epidermal hyperplasia/ papilloma Cryptocotyle sp. Lepeophtheirus pectoralis Benign and malignant liver tumours > 2 mm in diameter Acute/healing skin ulcerations Acute/healing fin rot/erosion Skeletal deformities Pseudobranchial swelling Epidermal hyperplasia/papilloma Cryptocotyle lingua Lernaeocera branchialis Benign and malignant liver tumours > 2 mm in diameter Non-specific Non-specific Non-specific 138

244 liver histopathology Contaminantspecific liver histopathology degenerative/regenerative change Inflammatory lesions Parasites Early toxicopathic nonneoplastic lesions Foci of cellular alteration Benign neoplasms Malignant neoplasms degenerative/regenerative change Inflammatory lesions Parasites Early toxicopathic nonneoplastic lesions Foci of cellular alteration Benign neoplasms Malignant neoplasms Confounding factors The multifactorial aetiology of diseases, in this context in particular of externally visible diseases, is generally accepted. Therefore, externally visible diseases have correctly been placed into the general biological effect component of the OSPAR CEMP (OSPAR, 2010b). Most wild fish diseases monitored in past decades are caused by pathogens (viruses, bacteria). However, other endogenous or exogenous factors may be required before the disease develops. One of these factors can be environmental pollution, which may either affect the immune system of the fish in a way that increases its susceptibility to disease, or may alter the number and virulence of pathogens. In addition, contaminants may also cause specific and/or non-specific changes at various levels of biological organisation (molecule, sub-cellular units, cells, tissues, organs) leading to disease without involving pathogens. The occurrence of significant changes in the prevalence of externally visible fish diseases can be considered a non-specific and more general indicator of chronic rather than acute (environmental) stress, and it has been speculated that they might, therefore, be an integrative indicator of the complex changes typically occurring under field conditions rather than a specific marker of effects of single factors. Because of the multifactorial causes of externally visible diseases, the identification of single factors responsible for observed changes in disease prevalence is difficult, and scientific proof of a link between contaminants and externally visible fish diseases is hard to achieve. Nevertheless, there is a consensus that fish disease surveys should continue to be part of national and international environmental monitoring programmes since they can provide valuable information on changes in ecosystem health and may act as an alarm bell, potentially initiating further more specific studies on cause and effect relationships. A thorough statistical analysis of ICES data on externally visible diseases (lymphocystis, epidermal hyperplasia/papilloma, acute/healing skin ulceration) of dab from different North Sea regions, confirmed the multifactorial aetiology of the diseases under study since a number of natural and anthropogenic factors (stock composition, water temperature, salinity, nutrients, contaminants in water, sediments and biota) were found to be significantly related to the long-term temporal changes in disease prevalence recorded. (Lang and Wosniok, 2000; Wosniok et al., 2000). The presence of macroscopic liver neoplasms and of certain types of histopathological liver lesions is a more direct indicator of contaminant effect and has been used for many years in environmental monitoring programmes around the world. Liver neoplasms (either detected macroscopically or by histopathological analysis) are likely to be associated to exposure to carcinogenic contaminants, including PAHs, and are therefore considered appropriate indicators for contaminant-specific biological effects monitoring. The study of liver histopathology (comprises the detection of more lesion categories (non-specific, neoplastic and non-neoplastic toxicopathic lesions), reflecting responses to a wider range of contaminants (including PAHs) but also to other environmental stressors and is, therefore, considered an appropriate indicator for both general and contaminant-specific biological effects monitoring. 139

245 The liver is the main organ involved in the detoxification of xenobiotics and several categories of hepatocellular pathology are now regarded as reliable biomarkers of toxic injury and representative of biological endpoints of contaminant exposure (Myers et al, 1987, 1992, 1998; Stein et al., 1990; Vethaak and Wester, 1996; Stentiford et al., 2003; Feist et al., 2004). The majority of lesions observed in field collected animals have also been induced experimentally in a variety of fish species exposed to carcinogenic compounds, PAHs in particular, providing strong supporting evidence that wild fish exhibiting these lesions could have been exposed to such environmental contaminants. Ecological relevance Fish diseases are considered as ecosystem health indicators, reflecting ecologically relevant effects of environmental stressors at the individual and population levels. As such, they differ from other types of indicators that reflect changes at lower levels of biological organisation (e. g. molecules, cells) and the ecological relevance of which is considered as low or unclear (e. g. biomarkers of exposure to contaminants.) (ICES, 2009b) Fish diseases may act at the individual level by adversely affecting behaviour, growth, reproduction, and survival of affected specimens. Individual effects may lead to ecologically relevant population effects (especially in epidemic situations) and ultimately to biodiversity effects at the community level. Diseases in wild fish may affect aquaculture due to transmission of pathogens. A high prevalence of a conspicuous fish disease may affect fishery profit because fish with prominent disease signs cannot be marketed. Although direct human health effects of diseases affecting wild fish are unlikely (except for a few cases), diseased fish may act as carriers of pathogens that pose a risk to human consumers. Quality Assurance Since the early 1980s, ICES has played a leading role in the initiation and coordination of fish disease surveys and has contributed considerably to the development of standardised methodologies. Through the work of the ICES Working Group on Pathology and Diseases of Marine Organisms (WGPDMO), its offspring, the Sub-Group/Study Group on Statistical Analysis of Fish Disease Data in Marine Stocks (SGFDDS) ( ) and the ICES Secretariat, quality assurance procedures have been implemented at all stages, from sampling of fish to submission of data to the ICES Data Centre and to data assessment. A number of practical ICES sea-going workshops on board research vessels were organised by WGPDMO in 1984 (southern North Sea), 1988 (Kattegat), 1994 (Baltic Sea, co-sponsored by the Baltic Marine Biologists, BMB) and 2005 (Baltic Sea) in order to intercalibrate and standardise methodologies for fish disease surveys (Dethlefsen et al., 1986; ICES, 1989, 2006a; Lang and Mellergaard, 1999) and to prepare guidelines. Whilst first guidelines were focused on externally visible diseases and parasites, WGPDMO developed guidelines for macroscopic and microscopic inspection of flatfish livers for the occurrence of neoplastic lesions at a later stage. Further intercalibration and standardision of methodologies used for studies on liver pathology of flatfish were a major issue of the 1996 ICES Special Meeting on the Use of Liver Pathology of Flatfish for Monitoring Biological Effects of Contaminants (ICES, 1997). This formed the basis from which the quality assurance programme Biological Effects Quality Assurance in Monitoring (BEQUALM) ( developed for the application of liver pathology in biological effects monitoring (see below) (Feist et al., 2004). A fish disease database has been established within the ICES Data Centre, consisting of disease prevalence data of key fish species and accompanying information, submitted by ICES Member Countries. Submission of fish disease data to the ICES Data Centre has been formalised by the introduction of the ICES Environmental Reporting Format designed 140

246 specifically for the purpose. This is used for fish disease, contaminant and biological effects data. The programme includes internal screening procedures for the validation of the data submitted providing further quality assurance. The ICES fish disease database is extended on an annual basis to include data from other species and areas within the OSPAR and HELCOM area as well as data on studies into other types of diseases, e.g. macroscopic liver neoplasms and liver histopathology. To date, the data comprise mainly information from studies on the occurrence of externally visible diseases and macroscopic liver lesions in the common dab (Limanda limanda) and the European flounder (Platichthys flesus) from the North Sea and adjacent areas, including the Baltic Sea, Irish Sea, and the English Channel. In addition, reference data are available from pristine areas, such as waters around Iceland. In total, data on length, sex, and health status of more than individual specimens, some from as early as 1981, have been submitted to ICES, as well as information on sampling characteristics (Wosniok et al., 1999, Lang and Wosniok, 2008). Current ICES WGPDMO activities have focussed on the development and application of statistical techniques for an assessment of disease data with regard to the presence of spatial and temporal trends in the North Sea and western Baltic Sea (Wosniok et al., 1999, Lang and Wosniok, 2008). In a more holistic approach, pilot analyses have been carried out combining the disease data with oceanographic, nutrient, contaminant and fishery data extracted from the ICES Data Centre in order to improve the knowledge about the complex cause-effect relationships between environmental factors and fish diseases (Lang and Wosniok, 2000; Wosniok et al., 2000). These analyses constituted one of the first attempts to combine and analyses ICES data from various sources and can, therefore, be considered as a step towards a more comprehensive integrated assessment. Quality assurance is in place for externally visible diseases, macroscopic liver neoplasms and liver histopathology via the ongoing BEQUALM programme. Regular intercalibration and ring-test exercises are conducted. The basis for QA procedures are provided in two key publications in the ICES TIMES series (Bucke et al., 1996, Feist et al., 2004) and a BEQUALM CD ROM of protocols and diagnostic criteria and reporting requirements for submission of data to ICES. Guidelines on fish disease monitoring in the Baltic Sea have been prepared by ICES (2006a). Assessment Criteria The development of assessment tools for externally visible diseases, macroscopic neoplasms and liver histopathology has been addressed by the ICES Working Group on Pathology and Diseases of Marine Organisms (WGPDMO) (ICES, 2006b, 2007, 2008, 2009a, 2011). Further additions were proposed at the 2009 ICES/OSPAR Workshop on Assessment Criteria for Biological Effects Measurements (WKIMC) (ICES, 2009b) (see further below). For the analysis and assessment of fish disease data, the ICES WGPDMO developed a Fish Disease Index (FDI), using data on diseases of the common dab (Limanda limanda) as a model The aim of this tool is to summarise information on the disease status of individual fish into one robust and easy-to-understand and easy-to-communicate numeric figure. By applying defined assessment criteria and appropriate statistics, the FDI can be used to assess the level and temporal changes in the health status of fish populations and can, thus, serve as a tool for the assessment of the ecosystem health of the marine environment, e.g., related to the effects of anthropogenic and natural stressors. Its design principle allows the FDI to be applied to other species with other sets of diseases. Therefore, the FDI approach is applicable for wider geographical areas, e.g., as part of a convention-wide HELCOM monitoring and assessment programme. For the calculation of the FDI, the following components are required: 141

247 information on the presence or absence of a range of diseases monitored on a regular basis, categorised as externally visible diseases, macroscopic liver neoplasms as well as non-specific and contaminant-specific liver histopathology (see Table 1); for most diseases, data on three severity grades (reflecting a light, medium or severe disease status) are included; disease-specific weighting factors, reflecting the impact of the diseases on the host (assigned based on expert judgements); adjustment factors for effects of size and sex of the fish as well as for season effects. The result of the calculation is a FDI value for individual fish which is scaled in a way that values can range from 0 to 100, with low values representing healthy and high values representing diseased fish. The maximum value of 100 can only be reached in the (purely theoretical and unrealistic) case that a fish is affected by all diseases at their highest severity grades. From the individual FDIs, mean FDIs for a sample from a fish population in a given sampling area can be calculated. Usually a sample in the present sense consists of the data collected in an ICES statistical rectangle during one cruise. All assessment is based on mean FDI values calculated from these samples. Depending on the data available, FDIs can be calculated either for single disease categories or for combinations thereof. The assessment of the mean FDI data considers (a) long-term FDI level changes, (b) FDI trends in the recent five years time window and (c) comparing each FDI to its Background Assessment Criterion (BAC) and Environmental Assessment Criterion (EAC) where these are defined. While assessments (a) and (b) are done on a region-wise basis, global BAC and EAC are used by assessment (c). The assessment approaches (a) and (b) do not apply any global background or reference values or assessment criteria as is often done for chemical contaminants or for biochemical biomarkers. Instead, these assessment approaches use the development of the mean FDI within the geographical units (usually ICES rectangles) over a given period of time, based on which region-specific assessment criteria are defined. The reason for choosing this approach is the known natural regional variability of the disease prevalence (even in areas considered to be pristine), making it implausible to define generally applicable background/reference values that can uniformly be used for all geographical units to be assessed. This approach is based on the availability of disease data over a longer period of time (ideally 10 observations, e.g., in the case of biannual monitoring over a period of five years) for every geographical area to be assessed. The assessment approach (c) ignores the known regional differences and involves globally defined Assessment Criteria (BAC, EAC; see above) with the consequence that withinregion variation might be dominated by general differences in regional levels. However, by applying globally defined Assessment Criteria, the FDI can also be used for exploratory monitoring in areas not studied before or for newly installed fish disease monitoring programmes after some modification. The final products of the assessment procedure are: graphs showing the temporal changes in mean FDI values in a geographical unit over the entire observation period; and maps in which the geographical units assessed are marked with green, yellow or red smiley faces, indicating long-term changes (e.g., comparing the past five years to the preceding five-years period) in health status of the fish population (green: improvement of the health status; yellow: indifferent variation; red: worsening of the health status, reason for concern and motivation for further research on causes), 142

248 maps in which the geographical units assessed are marked with green, yellow or red smiley faces, indicating trends in health status of the fish population during the past five years (green: improvement of the health status; yellow: indifferent variation; red: worsening of the health status, reason for concern and motivation for further research on causes), maps in which the geographical units assessed are marked with green, yellow or red smiley faces, indicating the level of the FDI observed at a defined point in time (green: below the BAC; yellow: between BAC and EAC; red: above the EAC, reason for concern and motivation for further research on causes). The ICES WGPDMO applied the FDI approach and the assessment for the common dab from the North Sea using ICES fish disease data extracted from the ICES Environmental Data Centre twice in 2008 and, using an extended dataset, in 2009 (ICES, 2008, 2009a). The results have been included in the OSPAR QSR 2010 as a case study (OSPAR, 2010). At the 2009 ICES/OSPAR Workshop on Assessment Criteria for Biological Effects Measurements (WKIMC) and the 2011 meeting of the ICES WGPDMO, Background Assessment Criteria (BAC) and Environmental Assessment Criteria (EAC) to be used for externally visible diseases, non-specific liver histopathology, macroscopic liver neoplasms and contaminant-specific liver histopathology in North Sea dab were proposed (ICES, 2009b, 2011). A common strategy was developed for externally visible fish diseases (EVD) and non-specific liver histopathology (NLH), and a modified strategy was developed for macroscopic liver neoplasm (MLN) and contaminant-specific liver histopathology (SLH). Two strategies are needed because the first two categories require an external harm entity that is to be controlled by the EAC, while the last two categories themselves already constitute measures of harm. The approach leading to a BAC for EVD and NLH is guided by the following considerations: No pristine reference area is available from which a BC (background concentration) or a BAC could be obtained and transferred to the ICES area. A certain number of diseases in a population seems inevitable as the vast majority of disease rates from fish disease monitoring samples is larger than zero, i.e. has FDI > 0. This suggests using a lower bound for the mean FDI as BAC (each mean FDI is calculated from data from one cruise, one ICES rectangle). Using the smallest historical positive FDI value produces an unstable BAC estimate. Preferably a small percentile of the FDI distribution should serve as BAC. The FDI value below which only a defined small proportion (e.g. 10%) of all values lies would be used as BAC. A BAC should be derived in this way separately for each species and sex (and the disease category). The BACs obtained are considered valid for the whole area from which the basic data originated. An EAC is the threshold beyond which "unacceptable effects" must be expected. The effect considered for EVD and NLH is the loss in condition factor (CF) that is associated with increasing FDI. Loss in CF is defined as the difference between the mean CF for FDI = 0 and the mean CF for an FDI > 0, expressed as percentage of the mean CF for FDI = 0. The EAC is then defined as that FDI value above which the loss in CF exceeds the acceptable amount (e.g. 10%). The essential point in this approach is that a link was established between a biomarker (fish diseases) and a relevant effect, in this case the loss in condition. Therefore an EAC could be based on loss in condition. With BAC and EAC 143

249 available, the FDI results can be represented in the usual three-colour scheme, also on a map (see above). Deriving BAC and EAC for macroscopic liver neoplasm (MLN) and contaminant-specific liver histopathology (SLH) follows slightly different lines. As macroscopic liver neoplasms are themselves unacceptable effects, there is no need to employ a further effect for determining an EAC. Also, there is no point in defining a BAC, as each effect in the MLN and SLH category is unacceptable. The suitability of these BACs/EACs for fish disease monitoring and assessment in the Baltic Sea will be evaluated in the course of 2011 (prior to the 2012 meeting of ICES WGPDMO) and modifications will be done as required. Acknowledgements Research on the application of the Fish Disease Index (FDI) as indicators for the monitoring and assessment of environmental stressors (incl. contaminants) in the Baltic Sea has partly been funded by the EU Project BEEP Contract n ECK3-CT , and the BONUS+ Project BEAST. References Bucke, D., Vethaak, A. D., Lang, T., and Mellergaard, S Common diseases and parasites of fish in the North Atlantic: Training guide for identification. ICES Techniques in Marine Environmental Sciences, pp. Dethlefsen, V., Egidius, E., and McVicar, A. H Methodology of fish disease surveys. Report of an ICES Sea-going Workshop held on RV Anton Dohrn 3-12 January ICES Cooperative Research Report, pp. Feist, S. W., Lang, T., Stentiford, G. D. and Köhler, A., The use of liver pathology of the European flatfish, dab (Limanda limanda L.) and flounder (Platichthys flesus L.) for monitoring biological effects of contaminants. ICES Techniques in Marine Environmental Science, 28: 47pp. HELCOM Third Periodic Assessment of the State of the Marine Environment of the Baltic Sea, ; Background Document. Baltic Sea Environment Proceedings N0 64 B. 252 pp. HELCOM Environment of the Baltic Sea area Baltic Sea Environment Proceedings N0 82 B. 215 pp. ICES Methodology of fish disease surveys. Report of an ICES Sea-going Workshop held on RV U/F Argos April ICES Cooperative Research Report, pp. ICES Report of the Special Meeting on the Use of Liver Pathology of Flatfish for Monitoring Biological Effects of Contaminants. ICES CM 1997/F:2. 75 pp. ICES ICES Advice %20of%20WKIMON.pdf. ICES. 2006a. Report of the ICES/BSRP Sea-going Workshop on Fish Disease Monitoring in the Baltic Sea (WKFDM). ICES CM 2006, BCC:02, 85 pp. ICES. 2006b. Report of the Working Group on Pathology and Diseases of Marine Organisms (WGPDMO), ICES CM 2006/MCC:01, 104 pp. ICES Report of the Working Group on Pathology and Diseases of Marine Organisms (WGPDMO), ICES CM 2007/MCC:04, 92 pp. ICES Report of the Working Group on Pathology and Diseases of Marine Organisms (WGPDMO), ICES CM 2008/MCC:01, 128 pp. ICES. 2009a. Report of the Working Group on Pathology and Diseases of Marine Organisms (WGPDMO), ICES CM 2009/MCC:01, 111 pp. ICES. 2009b. Report of the ICES/OSPAR Workshop on Assessment Criteria for Biological Effects Measurements (WKIMC), ICES CM 2009/ACOM:50, 133 pp. ICES Report of the Working Group on Pathology and Diseases of Marine Organisms (WGPDMO), ICES CM 2011/SSGHIE:04. Lang, T Fish disease surveys in environmental monitoring: the role of ICES. ICES Marine Science Symposia, 215:

250 Lang, T., and Mellergaard, S The BMB/ICES Sea-Going Workshop 'Fish Diseases and Parasites in the Baltic Sea' introduction and conclusions. ICES Journal of Marine Science, 56: Lang, T., Wosniok, W., Barsiene, J., Broeg, K., Kopecka, J., and Parkkonen, J Liver histopathology in Baltic flounder (Platichthys flesus) as indicator of biological effects of contaminants- Marine Pollution Bulletin 53: Lang, T., and Wosniok, W ICES data for an holistic analysis of fish disease prevalence. In ICES 2000, Report of the ICES Advisory Committee on the Marine Environment, 1999, pp ICES Cooperative Research Report, pp. Lang, T. and Wosniok, W The Fish Disease Index: a method to assess wild fish disease data in the context of marine environmental monitoring. ICES CM 2008/D:01, 13 pp. Myers, M. S., Rhodes, L. D. and McCain, B.B Pathologic anatomy and patterns of occurrence of hepatic neoplasms, putative preneoplastic lesions, and other idiopathic conditions in English sole (Parophyrs vetulus) from Puget Sound, Washington. Journal of the National Cancer Institute 78, Myers, M.S., Olson, O.P., Johnson, L.L., Stehr, C.M., Hom, T., and Varanasi, U Hepatic lesions other than neoplasms in subadult flatfish from Puget Sound, WA: Relationships with indices of contaminant exposure. Mar. Environ. Res. 34, Myers, M.S., Johnson, L.L., Hom, T., Collier, T.K., Stein, J.E., and Varanasi, U Toxicopathic lesions in subadult English sole (Pleuronectes vetulus) from Puget Sound, Washington, USA: Relationships with other biomarkers of contaminant exposure. Marine Environmental Perspectives, 45, North Sea Task Force North Sea Quality Status Report Oslo and Paris Commissions, London. Olsen and Olsen, Fredensborg, Denmark. 132 pp. OSPAR Commission. 2000a. Quality Status Report 2000, OSPAR Commission, London. 136+xiii pp. OSPAR Commission. 2010b. OSPAR Coordinated Environmental Monitoring Programme (CEMP), Reference number pp. OSPAR Commission Quality Status Report 2010, OSPAR Commission, London. 136+xiii pp. Stein, J.E., Reichert, W.L., Nishimito, M., and Varanasi, U Overview of studies on liver carcinogenesis in English sole from Puget Sound; evidence for a xenobiotic chemical etiology, 2, Biochemical studies. Sci. Total Environ. 94, Stentiford, G. D., Longshaw, M., Lyons, B. P., Jones, G., Green, M. and Feist, S. W Histopathological biomarkers in estuarine fish species for the assessment of biological effects of contaminants. Marine Environmental Research 55, Vethaak, A. D. and Wester, P. W Diseases of flounder Platichthys flesus in Dutch coastal and estuarine waters, with particular reference to environmental stress factors. II. Liver histopathology. Dis. Aquat. Orgs., 26, Wosniok, W., Lang, T., Dethlefsen, V., Feist, S. W., McVicar, A. H., Mellergaard, S., and Vethaak, A. D Analysis of ICES long-term data on diseases of North Sea dab (Limanda limanda) in relation to contaminants and other environmental factors. ICES CM 2000/S: pp. Wosniok, W., Lang, T., Vethaak, A. D., des Clers, S., and Mellergaard, S Statistical analysis of fish disease prevalence data from the ICES Environmental Data Centre. In: Report of the ICES Advisory Committee on the Marine Environment, 1998, pp ICES Cooperative Research Report, pp. 145

251 3.12. Micronucleus test Authors: Janina Baršienė, Doris Schiedek and Kari Lehtonen ICES SGEH Biological Effects methods Background Documents for the Baltic Sea region (ICES/OSPAR document from the ICES SGIMC Report 2010, complemented and modified by SGEH 2011 with information relevant for application in the Baltic Sea region) Description of the indicator In environmental genotoxicity indication system, the micronucleus (MN) test has served as an index of cytogenetic damage for over 30 years. MN consists of acentric fragments of chromosomes or whole chromosomes which are not incorporated into daughter nuclei at anaphase. These small nuclei can be formed as a consequence of the lagging of a whole chromosome (aneugenic event) or acentric chromosome fragments (clastogenic event) (Heddle, 1973; Schmid, 1975). A MN arises in cell divisions due to spindle apparatus malfunction, the lack or damage of centromere or chromosomal aberrations (Fenech, 2000). Clastogens induce MN by breaking the double helix of DNA, thereby forming acentric fragments that are unable to adhere to the spindle fibres and integrate in the daughter nuclei, and are thus left out during mitosis. Aneuploidogenic agents are chemicals that prevent the formation of the spindle apparatus during mitosis which can generate not only whole chromatids that are left out of the nuclei, thus forming MN, but also can form multinucleated cells in which each nucleus would contain a different number of chromosomes (Serrano-García and Montero-Montoya, 2001). Furthermore, there are indications that MN additionally may be formed via a nuclear budding mechanism in the interphase. The formation of such type MN reflects in an unequal capacity of the organisms to expel damaged, amplified DNA, failed replicated or improperly condensed DNA, chromosome fragments without telomeres and centromeres from the nucleus (Lindberg et al., 2007). The MN test involves the scoring of the cells which contain one or more MN in the cytoplasm (Schmid, 1975). The assay was first developed as a routine in vivo mutagenicity assay for detecting chromosomal mutations in mammalian studies (Boller and Schmid, 1970; Heddle, 1973). Hooftman and de Raat (1982) were the first, who successfully apply the assay to aquatic species. Since these initial experiments, other studies have validated the detection of MN as a suitable biomarker of genotoxicity in a wide range of both vertebrate and invertebrate species (for review see Chaudhary et al., 2006; Udroiu et al., 2006; Bolognesi and Hayashi, 2011). In fish most studies have applied circulating erythrocytes (blood) cells but can also be sampled from a number of tissues, such as liver, kidney, gill or fin epithelium (Archipchuk, Garanko, 2005; Baršienė et al., 2006a; Rybakovas et al., 2009). The frequency of the observed MN may be considered as a suitable index of accumulated genetic damage during the cell lifespan providing a time integrated response of an organism s exposure to contaminant mixtures. Depending on the life span of each cell type and on their mitotic rate in a particular tissue, the frequency of MN may provide early warning signs of cumulative stress (Bolognesi and Hayashi 2011). As an early warning indicator MN induction was successfully used in studies of environmental genotoxicity in gas (Gorbi et al., 2008) and oil platform zones (Hyland et al., 2008; Rybakovas et al., 2009, Brooks et al., 2011), also after the oil spills (Baršienė et al. 2006b, 2006c; Santos et al., 2010). Environmental genotoxicity levels in organisms from Baltic Sea, North Sea, Mediterranean and Northern Atlantic have been described in indigenous fish and mussel species inhabiting reference and contaminated sites (Wrisberg et al., 1992; Bresler et al., 1999; Baršienė et al., 2004, 2005a, 2006b, 2006c 2008a, 2008b, 2010a; Bagni et al., 2005; Bolognesi et al. 2006a; Magni et al, 2006). The MN test was validated in laboratory with different species after exposure to a large number of various 146

252 chemical agents (Fenech et al., 2003; Bolognesi et al., 2006b; Baršienė, Andreikėnaitė, 2007; Andreikėnaitė, 2010; Bolognesi, Hayashi, 2011). The majority of studies to date have used haemolymph and gill cells of molluscs and peripheral blood cells of fish for the MN analysis (Bolognesi, Hayashi, 2011). There are other studies (albeit limited) available describing the use of other haemopoetic tissues, such as liver, kidney, gills, and also fins (Archipchuk, Garanko, 2005; Baršienė et al., 2006a; Rybakovas et al., 2009). The application of the MN assay to blood samples of fish is particularly attractive as the method is non-destructive, easy to undertake and results in an easy quantifiable number of cells present on the blood smears for microscopic analysis. However, studies must be undertaken to assess the suitability of any species or cell type analyzed. The detected MN frequency in fish erythrocytes is approximately 6-10 times lower than in mussels and clams. The large inter individual variability associated to the low baseline frequency for this biomarker confirming the need for the scoring of a consistent number of cells in an adequate number of animals for each study point. Sampling size in most of studies conducted with mollusc species have been scoring cells per animal (Izquierdo et al. 2003; Hagger et al., 2005; Bolognesi et al., 1996, 2004, 2006a; Magni et al., 2006; Baršienė et al., 2006a, 2006b, 2008b, 2010; Kopecka et al. 2006; Nigro et al., 2006; Schiedek et al. 2006; Francioni et al., 2007; Siu et al., 2008; Koukouzika and Dimitriadis 2005, 2008) and previous reviews have suggested that when using fish erythrocytes at least cells should be scored per animal (Udroiu er al., 2006; Bolognesi et al., 2006a). Previously scorings of fish erythrocytes where used for a MN analysis (Baršienė et al., 2004). Since , the frequency of MN in fish from the Baltic seas was mostly scored in 4000 cells. In stressful heavily polluted zones, the scoring of cells in fish is still recommended. Mussel sampling size in MN assays range from 5 to 20 mussels per site as reported in the literature (Baršienė et al., 2004, 2006c, 2008b; Francioni et al., 2007; Siu et al., 2008). Evidence suggests that a sample size of 10 specimens per site is enough for the assessment of environmental genotoxicity levels and evaluation of the existence of genetic risk zones. In heavily polluted sites, MN analysis in specimens is recommended, due to higher individual variation of the MN frequency. MN analysis in more than 20 mussel or fish specimens shows only a minor change of the MN means (Fig. 1 in Fang et al., 2009; Baršienė et al., unpublished results). Most of the studies have been performed using diagnostic criteria for MN identification developed by several authors (Heddle et al., 1973, 1991; Carrasco et al., 1990; Al-Sabti and Metcalfe, 1995; Fenech, 2000; Fenech et al., 2003): the size of MN is smaller than 1/3 of the main nucleus; MN are round- or ovoid-shaped, non-refractive chromatin bodies located in the cytoplasm of the cell and can therefore be distinguished from artifacts such as staining particles; MN are not connected to the main nuclei and the micronuclear boundary should be distinguishable from the nuclear boundary. 147

253 a) b) c) Fig. 1. Micronuclei in blood erythrocytes of (a) herring (Clupea harrengus),(b) flounder (Platichthys flesus), and (c) in a gill cell of the mussel Mytilus edulis. After sampling and cell smears preparation, slides should be coded. To minimize technical variation, the blind scoring of MN should be performed without knowledge of the origin of the samples. Only cells with intact cellular and nuclear membrane can be scored. Particles with color intensity higher than that of the main nuclei were not counted as MN. The area to be scored should first be examined under low magnification to select the part of the slide showing the highest quality (good staining, non overlapping cells). Scoring of MN should then be undertaken at 1000x magnification. Confounding factors Earlier studies on MN formation in mussels have disclosed a significant influence of environmental and physiological factors (Dixon et al., 2002). Therefore, the role of the confounding factors should be considered prior to the application of MN assay in biomonitoring programs, as well as in description of genetic risk zones, or ecosystem health assessments. Water temperature. MN induction is a cell cycle-related process and depends on water temperature, which is a confounding factor for the mitotic activity in poikilotherm animals. Several studies have demonstrated that baseline frequencies of MN in mussels are related to water temperature (Brunetti et al., 1988, 1992; Kopecka et al., 2006). Baseline frequencies of MN are regarded as the incidence of MN observed in the absence of environmental risk or before exposure to genotoxins (Fenech, 1993). In fish MN frequencies showed also seasonal differences in relation to water temperature with lower MN levels in winter than in autumn (Rybakovas et al., 2009). This was assumed to be an effect of higher mitotic activity and MN formation due to high water temperatures in the autumn (Brunetti et al., 1988). Additionally, it has been reported that increases in water temperature (4-37ºC) can increase the ability of genotoxic compounds to damage DNA (Buschini et al., 2003). Cell type. MN may be seen in any type of cell, both somatic and germinal and thus the micronucleus test can be carried out in any active tissue. Nevertheless there are some limitations using different types of cells, for example, agranular and granular haemocytes in mussels. There are also differences between MN induction level in mussel haemolymph and gill cells, mainly because gills are primary targets for the action of contaminants. The anatomical architecture of the spleen in fish does not allow erythrocytes removal in the spleen (Udroiu et al., 2006), though, in mammals this process go. Salinity. The influence of salinity on the formation of MN was observed in mussels from the Danish coast located in the transitional zone between the Baltic and North Sea. No relationship between salinity and MN frequencies in mussels could be found for mussels from the Wismar Bay and Lithuanian coast. Similar results were found for Macoma balthica 148

254 from the Baltic Sea in the Gulfs of Bothnia, Finland, Riga and in the Lithuanian EZ (Baršienė et al., unpublished data). Individual size. Since the linear regression analysis of animal s length and induction of MN shows that the size could be a confounding factor, sampling of organisms with similar sizes should take place (Baršienė et al., unpublished data). It should also be noted that size is not always indicative of age and therefore age could also potentially affect the response of genotoxicity in the fish. Diet. Results have shown that MN formation was not influenced in mussels who were maintained under simple laboratory conditions without feeding (Baršienė et al., 2006d). Ecological relevance Markers of genotoxic effects reflect damage to genetic material of organisms and thus get a lot of attention (Moore et al. 2004). Different methods have been developed for the detection of both double- and single-strand breaks of DNA, DNA-adducts, MN formation and chromosome aberrations. The assessment of chemical induced genetic damage has been widely utilized to predict the genotoxic, mutagenic and carcinogenic potency of a range of substances, however these investigations have mainly been restricted to humans or mammals (Siu et al. 2004). MN formation indicates chromosomal breaks, known to result in teratogenesis (effects on offspring) in mammals. There is however limited knowledge of relationships between MN formation and effects on offspring in aquatic organisms. With a growing concern over the presence of genotoxins in the aquatic media, the application of cytogenetic assays on ecologically relevant species offers the chance to perform early tests on health in relation to exposure to contaminants. Quality Assurance The MN test showed to be a useful in vivo assay for genotoxicity testing. However, many aspects of its protocol need to be refined, knowledge of confounding factors should be improved and inter-species differences need further investigation. In 2009 an interlaboratory comparison exercise was organised within the framework of the MED POL programme using the mussel M. galloprovincialis as test species. The results are expected by mid Intercalibration of MN analysis in fish was done between experts from NRC and Caspian Akvamiljo laboratories, as well as between NRC experts and the University of Aveiro, Portugal (Santos et al. 2010). It is recommended that these relatively simple interlaboratory collaborations are expanded to include material from all the commonly used indicator species in 2011/12. Assessment Criteria Baseline or background frequency of MN can be defined as incidence of MN observed in the absence of environmental risk or before exposure to genotoxins (Fenech, 1993). In fish, MN frequencies lower than 0.05 has been suggested by Rybakovas et al. (2009) as a reference level in the peripheral blood erythrocytes of the flatfish flounder (Platichthys flesus) and dab (Limanda limanda) and also cod (Gadus morhua) after analyzing 479 specimens from 12 offshore sites in the Baltic Sea. The frequencies of MN in marine species sampled from the Baltic Sea reference sites are summarized in Table

255 Table 1. The reference levels of micronuclei (MN/1000 cells) in Baltic Sea species in situ. Species Tissue Response MN/1000 cells Reference Mytilus edulis Gills 0.37 ± 0.09 Baršienė et al., 2006b Mytilus trossulus Gills 2.07 ± 0.32 Baršienė et al., 2006b; Kopecka et al., 2006 Macoma baltica Gills Baršienė et al., 2008b, unpublished data (NRC, Lithuania) Platichthys flesus Blood 0.15 ± 0.03 Baršienė et al., 2004 erythrocytes Platichthys flesus Blood 0.0 ± 0.0 Kohler, Ellesat, 2008 erythrocytes Platichthys flesus Blood erythrocytes 0.08 ± 0.02 Napierska et al., 2009 Zoarces viviparus Gadus morhua Clupea harengus Scophthalmus maximus Perca fluviatilis Blood erythrocytes Blood, kidney erythrocytes Blood erythrocytes Blood erythrocytes Blood erythrocytes 0.02 ± 0.02 Baršienė et al., unpublished data (NRC, Lithuania) 0.03 ± 0.02 Rybakovas et al., ± 0.03 Baršienė et al., unpublished data (NRC, Lithuania) 0.10 ± 0.04 Baršienė et al., unpublished data (NRC, Lithuania) 0.06 ± 0.02 Baršienė et al., 2005a; Baršienė et al., unpublished data (NRC, Lithuania) Assessment Criteria (AC) have been established by using data available from studies of molluscs and fish in the Baltic Sea (NRC database). The background/threshold level of MN incidences is calculated as the empirical 90% percentile (P90). Until more data becomes available, values should be interpreted from existing national data sets. Note: the values given here are provisional and require further validation when new data becomes available. The 90% percentile (P90) separates the upper 10% of all values in the group from the lower 90%. The rationale for this decision was that elevated MN frequency would lie above the P90 percentile, whereas the majority of values below P90 belong to unexposed, weaklymedium exposed or non-responding adapted individuals. P90 values were calculated for those stations/areas which were considered being reference stations (i.e. no known local sources of contamination or those areas which were not considered unequivocally as reference sites but as those less influenced from human and industrial activity). ACs in bivalves Mytilus edulis, Mytilus trossulus, Macoma balthica (data from MN analysis in 2370 specimens), in fish Limanda limanda, Zoarces viviparus, Platichthys flesus, Gadus morhua and Clupea harengus (data from MN analysis in 3239 specimens) from Baltic Sea have been calculated using NRC (Lithuania) databases (Table 2). Table 2. Assessment criteria of MN frequency levels in bivalve mollusc and fish. BR =Background response; ER = Elevated response; n = number of specimens analysed. Species Size (cm) T (ºC) Region Tissue BR ER n 150

256 Mytilus edulis Baltic Sea Gills <2.50 > Mytilus trossulus Baltic Sea Gills <4.50 > Macoma balthica Baltic Sea Gills <2.90 > Zoarces Baltic Sea Erythrocytes <0.38 > viviparus Limanda Baltic Sea Erythrocytes <0.49 > limanda Platichthys flesus Baltic Sea coastal Erythrocytes <0.29 > Platichthys flesus Baltic Sea offshore Erythrocytes <0.23 > Gadus morhua Baltic Sea Erythrocytes <0.38 > Clupea Baltic Sea Erythrocytes <0.39 > harengus Distribution of indicator species in Baltic Sea subregions MN test has generally been applied to organisms where other biological-effects techniques and contaminant levels are well documented. That is the case for mussels and for certain demersal fish species (as European flounder, dab or Atlantic cod), which are routinely used in biomonitoring programs and assess contamination along western European marine. However, the MN assay may be adapted for alternative sentinel species using site-specific monitoring criteria. When selecting an indicator fish species, consideration must be given to its karyotype as many teleosts are characterised by an elevated number of small chromosomes (Udroiu et al., 2006). Thus, in certain cases MN formed after exposure to clastogenic contaminants will be very small and hard to detect by light microscopy. This can be addressed to a certain extent by using fluorescent staining. After selecting target/suitable species, researchers should also ensure that other factors including age, sex, temperature and diet are similar between the sample groups. If conducting transplantation studies, consideration needs to be given to the cellular turnover rate of the tissue being examined to ensure sufficient cells have gone through cell division. For example, if using blood the regularities of erythropoiesis should be known prior to sampling. Large-scale and long-term studies took place from 2001 to 2010 at the Nature Research Centre (NRC, Lithuania) on MN and other abnormal nuclear formations in different fish and bivalve species inhabiting various sites of the Baltic Sea. These studies revealed the relevance of environmental genotoxicity levels in ecosystem assessments. NRC established a large database on MN and other nuclear abnormalities in 8 fish species and in mussels and clams from the Baltic Sea. Fish and bivalve species were collected from 117 coastal and offshore sites. The following organisms have been tested as the target species for MN test in the different regions of the Baltic Sea: Fish flounder (Platichthys flesus), dab (Limanda limanda, herring (Clupea harengus), eelpout (Zoarces viviparus) plaice (Pleuronectes platessa) Atlantic cod (Gadus morhua) perch (Perca fluviatilis) 151

257 turbot (Scophthalmus maximus, Psetta maxima) Bivalves blue mussels (Mytilus edulis, Mytilus trossulus Baltic clam (Macoma baltica) Amphipods Gammarids Acknowledgements Research on the application of the MN test as a biomarker for the monitoring and assessment of environmental genotoxicity in different Baltic Sea regions and indicator organisms has been funded by the EU Project BEEP, Contract EVK3-CT , BONUS+ Project BEAST and Lithuanian Science Council GENCITOX project MIP References Al-Sabati K, Metcalfe CD. Fish micronuclei for assessing genotoxicity in water. Mutation Research 1995; 323: Andreikėnaitė L Genotoxic and cytotoxic effects of contaminants discharged from the oil platforms in fish and mussels. Summary of doctoral dissertation, 38p.,Vilnius. Arkhipchuk V.V., Garanko N.N Using the nucleolar biomarker and the micronucleus test on in vivo fish fin cells. Ecotoxicology and Environmental Safety. Vol. 62. P Bagni G., Baussant T., Jonsson G., Baršienė J., Mascini M Electrochemical device for the rapid detection of genotoxic compounds in fish bile samples. Analytical Letters, 38: Baršienė J., Andreikėnaitė L Induction of micronuclei and other nuclear abnormalities in blue mussels exposed to crude oil from the North Sea. Ekologija, 53, No 3: Baršienė J., Andreikėnaitė L., Garnaga G., Rybakovas A. 2008b. Genotoxic and cytotoxic effects in bivalve mollusks Macoma balthica and Mytilus edulis from the Baltic Sea. Ekologija, 54: Baršienė J., Bjornstad A., Rybakovas A., Šyvokienė J., Andreikėnaitė L Environmental genotoxicity and cytotoxicity studies in mussels and fish inhabiting northern Atlantic zones impacted by aluminum industry. Ekologija, 56, No 3-4: Baršienė J., Dedonytė V., Rybakovas A., Andreikėnaitė L., Andersen O.K. 2006a. Investigation of micronuclei and other nuclear abnormalities in peripheral blood and kidney of marine fish treated with crude oil. Aquatic Toxicology,78, Supplement 1: S Baršienė J., Dedonytė V., Rybakovas A., Broeg K., Forlin L., Gercken J., Kopecka J., Balk L. 2005a. Environmental mutagenesis in different zones of the Baltic Sea. Acta Zoologica Lituanica, 15: Baršienė J., Lazutka J., Šyvokienė J., Dedonytė V., Rybakovas A., Bjornstad A., Andersen O.K Analysis of micronuclei in blue mussels and fish from the Baltic and the North Seas. Environmental Toxicology, 19: Baršienė J., Lehtonen K., Koehler A., Broeg K., Vuorinen P.J., Lang T., Pempkowiak J., Šyvokienė J., Dedonytė V., Rybakovas A., Repečka R., Vuontisjarvi H., Kopecka J. 2006c. Biomarker responses in flounder (Platichthys flesus) and mussel (Mytilus edulis) in the Klaipėda-Būtingė area (Baltic Sea). Marine Pollution Bulletin, 53: Baršienė J., Rybakovas A. 2006d Cytogenetic and cytotoxic effects in gill cells of the blue mussel Mytilus edulis from the Baltic coast and after 1-3-day maintenance in laboratory. Acta Zoologica Lituanica, 16: Baršienė J., Rybakovas A., Forlin L., Šyvokienė J. 2008a. Environmental genotoxicity studies in mussels and fish from the Goteborg area of the North Sea. Acta Zool. Lituanica, 18: Baršienė J., Schiedek D., Rybakovas A., Šyvokienė J., Kopecka J., Forlin L. 2006b. Cytogenetic and cytotoxic effects in gill cells of the blue mussel Mytilus spp. from different zones of the Baltic Sea. Marine Pollution Bulletin, 53: Boller K., Schmid W Chemische Mutagenese beim Sauger. Das Knochermark des Chinesischen Hamsters als in vivo-test system. Haematologische Befunde nach Behandlung mit Trenimon. Humangenetik, 11, Bolognesi C., Perrone E., Roggieri P., Pampanin D.M., Sciutto A. 2006b. Assessment of micronuclei induction in peripheral erythrocytes of fish exposed to xenobiotics under controlled conditions. Aquatic Toxicology, 78, Supplement 1: S93-S

258 Bolognesi C., Perrone E., Roggieri P., Sciutto A. 2006a. Bioindicators in monitoring long term genotoxic impact of oil spill: Haven case study. Marine Environ. Res., 62: S287-S291.Bolognesi C., Hayashi M Micronucleus assay in aquatic animals. Mutagenesis, 26: Bolognesi C. and Hayashi M Micronucleus assay in aquatic animals. Mutagenesis, 26: Bolognesi C., Frenzilli G., Lasagna C., Perrone E., Roggieri P Genotoxicity biomarkers in Mytilus galloprovincialis: wild versus caged mussels. Mutation Research. 552: Bolognesi C., Rabboni R. and Roggieri P Genotoxicity biomarkers in M. galloprovincialis as indicators of marine pollutants. Comparative Biochemistry and Physiology, 113C, No 2: Bresler V., Bissinger V., Abelson A., Dizer H., Sturm A., Kratke R., Fischelson L., Hansen P.-D Marine mollusks and fish as biomarkers of pollution stress in littoral regions of the Red Sea, Mediterranean Sea and North Sea. Helgoland Marine Research, 53: Brooks S.J., Harman C., Grung M., Farmen E., Ruus A., Vingen S., Godal B.F., Baršienė J., Andreikėnaitė L., Skarphedinsdottir H., Liewenborg B., Sundt R.C Water column monitoring of the biological effects of produced water from the Ekofisk offshore oil installation from 2006 to Journal of Toxicology and Environmental Health, Part A, 74: Brunetti R., Gabriele M., Valerio P. and Fumagalli O The micronucleus test: temporal pattern of the baseline frequency in Mytilus galloprovincialis Lmk. Marine Ecol. Prog. 83: Brunetti R., Majone F., Gola I and Beltrame C The micronucleus test: examples of application to marine ecology. Marine Ecol. Prog., 44: Buschini A, Carboni P, Martino A, Poli P, Rossi C Effects of temperature on baseline and genotoxicantinduced DNA damage in haemocytes of Dreissena polymorpha. Mutatation Research, 537: Carrasco K.R., Tilbury K.L., Myers M.S Assessment of the piscine micronucleus test as an in situ biological indicator of chemical contaminant effects. Canadian Journal Fishery and Aquatic Sciences, 47: Chaudhary, R., Pandy, S., Kushwaha, B., Gaur, K.K., Nagpure, N.S. (2006) Fish micronucleus assay: A sensitive tool for ecogenotoxicity studies. Journal of Ecophysiology and Occupational Health, 6 (3-4): Dixon D.R., Dixon L.R.J., Shillito B., Gwynn J.P Background and induced levels of DNA damage in Pacific deep-sea vent palychaetes: the case for avoidance. Cah. Biol. Marine 43: Fenech M The in vitro micronucleus technique. Mutation Research 455: Fenech M., Chang W.P., Kirsch-Volders M., Holland N., Bonassi S., Zeiger E HUMN project: detailed description of the scoring criteria for the cytokinesis-block micronucleus assay using isolated human lymphocyte cultures. Mutation Research, 534: Fenech, M., 1993, The Cytokinesis-Block Micronucleus Technique: A Detailed Description of the Method and Its Application to Genotoxicity Studies in Human Populations. Mutatation Research, 285, Gorbi S., Lamberti C.V., Notti A., Benedetti M., Fattorini D., Moltedo G., Regoli F An Ecotoxicological protocol with caged mussels, Mytilus galloprovincialis, for monitoring the impact of an offshore platform in the Adriatic sea. Marine Environmental Research, 65: Hagger J.A., Depledge M.H., Galloway T.S Toxicity of tributyltin in the marine mollusc Mytilus edulis. Marine Pollution Bulletin, 51: Heddle J.A A rapid in vivo test for chromosomal damage. Mutation Research, 18: Heddle J.A., Cimino M.C., Hayashi M., Romagna F., Shelby M.D., Tucker J.D., Vanparys Ph. and MacGregor J.T Micronuclei as an index of cytogenetic damage: past, present, and future. Environmental and Molecular Mutagenesis, 18: Hooftman R.N., Raat W.K Induction of nuclear anomalies (micronuclei) in the peripheral blood erythrocytes of an eastern mudminnow Umbra pygmaea by ethyl methanesulphonate. Mutation Research, 104: Hylland K., Tollefsen K.-E., Ruus A., Jonsson G., Sundt R.C., Sanni S., Utvik T.I.R., Johnsen I., Pinturier L., Balk L., Baršienė J., Marigomez I., Feist S.W., Borseth J.F Water column monitoring near oil instalations in the North Sea Marine Pollution Bulletin, 56: Izquierdo J.I., Machado G., Ayllon F., d Amico V.L., Bala L.O., Vallarino E., Elias R., Garcia-Vazquez E Assessing pollution in coastal ecosystems: a preliminary survey using the micronucleus test in the Mytilus edulis. Ecotoxicology and Environmental Safety 55: Köhler A., Ellesat K Nuclear changes in blood, early liver anomalies and hepatocellular cancers in flounder (Platichthys flesus L.) as prognostic indicator for a higher cancer risk? Marine Environmental Research, 66: Kopecka J., Lehtonen K., Baršienė J., Broeg K., Vuorinen P.J., Gercken J., Pempkowiak J Measurements of biomarker levels in flounder (Platichthys flesus) and mussel (Mytilus trossulus) from the Gulf of Gdańsk (southern Baltic). Marine Pollution Bulletin, 53:

259 Koukouzika N., Dimitriadis V.K Multiple biomarker comparison in Mytilus galloprovincialis from the Greece coast: "Lysosomal membrane stability, neutral red retention, micronucleus frequency and stress on stress". Ecotoxicology, 14: Lindberg H.K., Wang X., Järventaus H., Falck G.C.-M., Norppa H., Fenech M Origin of nuclear buds and micronuclei in normal and folate-deprived human lymphocytes. Mutation Research, 617: Magni P., De Falco G., Falugi C., Franzoni M., Monteverde M., Perrone E., Sigro M., Bolognesi C Genotoxicity biomarkers and acetylcholinesterase activity in natural populations of Mytilus galloprovincialis along a pollution gradient in the Gulf of Oristano (Sardinia, western Mediterranean). Environmental Pollution, 142: Nigro M., Falleni A., Del Barga I., Scarcelli V., Lucchesi P., Regoli F., Frenzilli G Cellular biomarkers for monitoring estuarine environments: Transplanted versus native mussels. Aquatic Toxicology, 77: Rybakovas A., Baršienė J., Lang T Environmental genotoxicity and cytotoxicity in the offshore zones of the Baltic and North Seas. Marine Environmental Research, 68: Santos M.M., Sole M., Lima D., Hambach B., Ferreira A.M., Reis-Henriques M.A Validating a multibiomarker approach with the shanny Lipophrys pholis to monitor oil spills in European marine ecosystems. Chemosphere, 81, 6, Schiedek D., Broeg K., Baršienė J., Lehtonen K.K., Gercken J., Pfeifer S., Vuontisjärvi H., Vuorinen P.J., Dedonytė V., Koehler A., Balk L., Schneider R Biomarker responses as indication of contaminant effects in blue mussel (Mytilus edulis) and female eelpout (Zoarces viviparus) from the southwestern Baltic Sea. Marine Pollution Bulletin, 53: Schmid W The micronucleus test. Mutation Research, 31:9 15. Serrano-García L., Montero-Montoya R Micronuclei and chromatid buds are the result of related genotoxic events. Environmental and Molecular Mutagenenesis 38: Siu, W. H. L., J. Cao, R. W. Jack, R. S. S. Wu, B. J. Richardson, L. Xu and P. K. S. Lam Application of the comet and micronucleus assays to the detection of B a P genotoxicity in haemocytes of the greenlipped mussel (Perna viridis). Aquatic Toxicology, 66: Udroiu I The micronucleus test in piscine erythrocytes. Aquatic Toxicology, 79: Wrisberg M.N., Bilbo C.M., Spliid H Induction of micronuclei in hemocytes of Mytilus edulis and statistical analysis. Ecotoxicology and Environmental Safety, 23:

260 3.13 A. Reproductive disorders in fish and amphipods: Reproductive success in eelpout Authors: Jakob Strand, Doris Schiedek and Kari Lehtonen ICES SGEH Biological Effects methods Background Documents for the Baltic Sea region (ICES/OSPAR document from the ICES SGIMC Report 2010, complemented and modified by SGEH 2011 with information relevant for application in the Baltic Sea region) Description of the indicator Eelpout (Zoarces viviparus), also called viviparous blenny, is a benthic fish species that is widely used in ecotoxicological studies and as a bioindicator of local pollution due to its stationary behaviour in coastal marine environment. Eelpout is a recommended fish indicator species for assessing the environmental conditions in the Baltic Sea and eelpout is included in the environmental monitoring programmes of several Baltic States, both in relation to biological effects, contaminants and integrated fish monitoring. For instance, Sweden and Germany have routinely measured contaminant concentrations in eelpout for >15 years, and additional samples are archived in environmental specimen banks allowing retrospective studies on chemical burdens. Similar long time series is also available for some other biomarker studies. The eelpout is viviparous, i.e. there is an internal fertilization of the eggs and the female fish gives birth to fully developed larvae. The eelpout s mode of reproduction (vivipari) enables the study of "reproductive success" on an individual level, and larval developmental disorders can be directly associated with e.g. the health status of the female or body burdens of toxic substances during pregnancy. Different types of abnormal larvae development can be distinguished and be characterised into different groups, i.e. early dead embryos, late dead larvae, growth retarded larvae and deformed larvae, which can be divided into different subgroups of severe gross malformations. Reproductive success in eelpout as a biological effects method is regarded as a general, i.e. non-specific, integrative indicator for impaired fish reproduction, and a significant biological endpoint for assessing potential population-relevant effects. Because the reproductive success in fish is a generic stress indicator; causal agents may, however, only be identified through a combination of chemical analyses of fish tissue and also other biological effects measurements. Several types of hazardous substances such as organochlorines, pesticides, PAH, heavy metals and organometals are known to have the potential to affect embryo and larval development in fish, generally (Bodammer 1993). Several of these substances, which may induce developmental, morphological and/or skeletal anomalies, have also been identified as endocrine disrupting substances (Davis 1997). Reproductive success in eelpout is included in the list of parameters for biological effect monitoring for supporting programme in the HELCOM COMBINE manual for marine monitoring in the coastal zone. Part D. Programme for monitoring of contaminants and their effects (HELCOM 2006). The method is also part of OSPAR pre-cemp and JAMP guideline for general biological effects monitoring (OSPAR 2010). According to the monitoring guideline, the sample size should consist of examinations of individuals of pregnant females of eelpout per station, which should be sampled in the period between October 15 and December

261 There is in some countries restrictions on eelpout fishery that depends on national legislations, e.g. fishing dispensation for catching pregnant females in the autumn is needed in Denmark. National concerns for impact of fishery on local populations and ethical guidelines for humane handling and fish killing should also be considered. In the Baltic Sea region, reproductive success in eelpout is or has been used for monitoring or pre-monitoring investigations at least by labs from Denmark, Sweden, Germany and Poland and as part of integrated fish monitoring, often in combination with contaminant, biomarker studies and/or population studies. Studies in the Baltic Sea has shown that that spatial differences occur with elevated levels of adverse developmental effects of embryo and larvae in eelpout broods have been found in populations living in contaminated areas with effluents from cities and industry. In comparison, only low levels of such effects generally occur in populations living in areas regarded as reference sites (e.g. Vetemaa et al. 1997, Ådjers et al. 2001, Sjölin et al. 2003, Strand et al. 2004, Kalmarweb 2005, Gercken et al. 2006) as shown in Fig. 1. Mean frequency (%) of abnormal larvae Max.-value 90% percentile ---- Median 10% percentile Min.-value Reference sites Not reference sites Reference sites Not reference sites Reference sites Not reference sites Late dead larvae Malformed larvae Retarded larvae Figure 1. Comparison of data distribution of compiled monitoring data on mean frequencies of late dead, malformed and growth retarded larvae in eelpout broods from reference sites and area not regarded as reference sites. The blue dotted line refers to the 90% percentile of data from the reference sites. The red dotted line refers to significantly elevated levels compared to the 90% percentile of the reference sites. Clear temporal developments with up- or down-going trends for the presence of different types of abnormal larvae development have not been established in monitored baseline areas with longer time series. However, some year-to-year variations can occur. Studies of point sources have shown that acute larval mortality also been observed in eelpout exposed to pulp mill effluents (Jacobsson et al. 1986). Skewed sex ratios with significant more males in the eelpout broods have also been found nearby pulp mill effluents indicating effects of endocrine disruption substances (Larsson & Förlin 2002). Confounding factors Other environmental stressors like increased temperature and severe oxygen depletion events may however also affect eelpout reproduction (Veetema 1999, Fagerholm 2002, Strand et al. 2004). There have been some indications that some specific types of abnormal larvae development like early dead embryos and late dead larvae can be induced by severe oxygen events. However, deformed larvae with severe gross malformations, which can be 156

262 distinguished from the other types, seem to be more related to contaminant effects (Strand et al. 2004, Gercken et al. 2006). Ecological relevance The ecological relevance of reproductive success of fish is high, because of the links to reproductive disorders. Population modelling support that elevated levels of abnormal larvae developments also can be important for population sizes. Quality Assurance The methodology for reproductive success is well defined for studies in coastal waters and national guideline exists (Jacobsson et al., 1986; Neuman et al., 1999, Strand & Dahllöf, 2005). An international guideline is in preparation and to be published in the ICES TIMES series. As method quality assurance, some international and national workshops have been held in relation to the monitoring programmes (e.g. BEQUALM 2000). A Baltic workshop has been held in 2009 as part of BONUS+-projects BALCOFISH and BEAST. National workshops in relation to NOVANA monitoring activities have also been held in Denmark (Strand 2005a). Backround response and Assessment Criteria Assessment Criteria for reproductive success in eelpout based on below and above the background response has been proposed by ICES/OSPAR SGIMC The derivation of assessment criteria have been based on data for either late dead larvae or deformed larvae from the Swedish and Danish monitoring programmes from several areas regarded as less polluted reference sites in the Baltic Sea, the Kattegat and the Skagerrak studies, where only low frequencies of abnormal larvae have mainly been found in areas, which were considered as reference sites, if any. Background response values as baseline is based on 90% percentiles have been found to be <1% deformed larvae, <2% late dead larvae and <4% growth retarded larvae, respectively. Alternatively, the background response can also be based on the frequency of broods with >5% abnormal larvae development (Table 1).. Table 1. Background response for the presence of 3 types of abnormal larvae developments in eelpout, i.e. deformed larvae, late dead larvae and growth retarded larvae per station (ICES/OSPAR SGIMC 2010) Type of abnormal larvae development Background response, based on mean frequencies per station Background response, based on frequency of broods with >5% abnormal larvae development Deformed larvae < 1% of all larvae <5% of broods Late dead larvae <2% of all larvae <5% of broods Growth retarded larvae <4% of all larvae - Background response determined as the upper limit is the 90% percentile of response at so-called reference sites. 157

263 Environment Assessment Criteria reflecting the GES boundary are under development. However, these assessment criteria will be revised and evaluated in within the BONUS+ project BALCOFISH, so that the derivation of the background response levels are performed according to the principles recommended by the OSPAR/ICES working group SGIMC. Distribution of indicator species in Baltic Sea subregions The eelpout inhabits coastal waters and is widely distributed and common in almost all subregions of the Baltic Sea. Eelpout occurs also from the White Sea to the southern North Sea. Acknowledgements The BONUS+ project BALCOFISH shall be acknowledged for the progress on the linkage between contaminants, early warning biomarkers and reproductive disorders and also on the developments of assessment criteria and evaluation of the ecological relevance using population modelling. References BEQUALM (2000). Fish Reproductive Success embryo development and survival in viviparous blenny Zoarces viviparus. Biological Effects Quality Assurance in Monitoring Programmes (BEQUALM). BEQUALM Newsletter Blekingekustens Vattenvårdsförbund (2005). Hanöbugten (In Swedish). Bodammer, J.E. (1993). The teratological and pathological effects of contaminants on embryonic and larvae fishes exposed as embryos: a brief review. Am. Fish Soc. Symp. 14: Davis, W.P. (1997). Evidence for developmental and skeletal responses as potential signals of endocrine disrupting compounds in fishes. In Chemically induced alterations in functional development and reproduction of fishes. Edited by Rolland, R.M., Gilbertson, M., Peterson, SETAC Press, Pensacola FL. Fagerholm B (2002). Integrerad fiskövervakning i kustreferensområden, Fjällbacka. Årsrapport för Fiskeriverket, Kustlaboratoriet. Arbetsrapport. 10p. (In Swedish). Gercken J., Förlin L., Andersson J. (2006). Developmental disorders in larvae of eelpout (Zoarces viviparus) from German and Swedish Baltic coastal waters. Mar Pollut Bull. 53(8-9): HELCOM (2006). Manual for Marine Monitoring in the COMBINE Programme of HELCOM. Part D. Programme for monitoring of contaminants and their effects, updated ICES (2004). Recommended techniques for biological monitoring programmes at the national or international level methods for fish. Report of the Working Group on Biological Effects of Contaminants. WGBEC meeting March 2004 Ostend, Belgium. ICES/OSPAR (2010). Report of the Joint ICES/OSPAR Study Group on Integrated Monitoring of Contaminants and Biological Effects (SGIMC), January, Copenhagen, Denmark Jacobsson, A., Neuman, E., Thoresson, G. (1986). The viviparous blenny as an indicator of environmental effects of harmful substances. Ambio 15(4): Kalmarweb (2005). Samordnad kustvattenkontroll i Kalmar län. (In Swedish). Larsson, D.G.J, Förlin, L. (2002). Male-biased sex ratios of fish embryos near a pulp mill: Temporary recovery after a short-term shutdown. Environmental Health Perspective 110(8): Napierska D., Podolska M. (2006). Field studies of eelpout (Zoarces viviparus L.) from Polish coastal waters (southern Baltic Sea). Science of the Total Environment 371: Neuman, E., Sandström, O., Thoresson, G. (1999). Guidelines for coastal fish monitoring. National Board of Fisheries, Institute of Coastal Research, Ôregrund, Sweden, 44p OSPAR (2008). JAMP guidelines for general biological effects monitoring. Technical Annex 10 reproductive success in fish. 158

264 OSPAR (2010). OSPAR Coordinated Environmental Monitoring Programme (CEMP). Reference number: Sjölin, A., Olsson, P., Magnusson, G. (2003). Hälsotillstånd och fortplantning hos tånglake i recipienten til Mörrums bruk hösten Toxicon rapport 8/03. (In Swedish) Strand, J, Dahllöf, I. (2005). Biologisk effektmonitering i fisk. NOVANA teknisk anvisning for marin overvågning, kapitel 6.3. Danmarks Miljøundersøgelser. (In Danish). Strand, J. (2005a). Biologisk effektmonitering i havsnegle og fisk. Marine workshopper Research Note from NERI No. 210, 34p. (In Danish) Strand, J. (2005b). Bioligiske effekter i ålekvabbe og muslinger. Marine områder Status og trends i NOVANA overvågning. Faglig rapport fra DMU. (In Danish). Strand, J., Andersen, L., Dahllöf, I., Korsgaard, B. (2004). Impaired larval development in broods of eelpout (Zoarces viviparus) in Danish coastal waters. Fish Physiology and Biochemistry 30: Vetemaa, M. (1999). Reproduction biology of the viviparous blenny (Zoarces vivparus L.). Rep. Nat. Board Fish. Swed. 2: 81-96, Fiskeriverket, Göteborg, Sweden. Vetemaa, M., Förlin, L., Sandström, O. (1997). Chemical effluent impacts on reproduction and biochemistry in a North Sea population of viviparous blenny (Zoarces viviparus). J. Aquat. Ecosys. Stress Rec. 6: Ådjers, K., Appelberg, M., Eschbaum, R., Lappalainen, A., Lozys, L. (2001). Coastal fish monitoring in Baltic reference areas Kala- ja riistaraportteja 229: 1-14, Helsinki, Finland. Agenda item 3 at the HELCOM MONAS meeting March 2004 in Tallinn, Estonia. 159

265 Summary table for reproductive success in eelpout. Evaluation Criteria Rating Description Recommended indicator species - Eelpout (Zoarces viviparus) Recommended matrix - Pregnant females Recommended sample size per station fish Monitoring guideline (SOP) in place Yes Swedish and Danish monitoring guidelines, ICES guideline in prep. ACs in place, i.e. background response (BaR) and/or EAC Yes BaR <1% for deformed larvae, <2% for dead larvae. EAC under development. QA in place, i.e. ongoing intercalibrations or workshops Yes BALCOFISH/BEAST workshop in 2009, National workshops Ecological relevance of effects for populations High Links to impaired reproduction Persistent damage, not repairable effects Yes Irreversible effects Contaminant sensitive response (Elevated High Coastal waters, point sources effect levels in open waters, coastal waters or only point sources) Contaminant-specific cause-effects response No See below General effect, response to several contaminant groups Yes Can respond to several contaminant groups like metals, OCs, PAH, EDS Stable for confounding factors Medium Depending of the type of abnormal larvae development. The presence of deformed seems most related to contaminants. Applicable indicator species in 1, 2-3 or >3 Yes Eelpout occurs in all Baltic Sea subregions Baltic Sea subregions Already used in monitoring in 1, 2-3 or >3 Yes Sweden, Denmark and Germany countries Available data, spatial coverage in the Baltic Sea - number of countries and stations (<10, 10-20, >20 stations) Medium S: 6-10 stations, DK: st., D: 3 st. Available data, length of time series (<5, 5-10, >10 years) Good S: , DK: , D: Costs of analyses per station, all required individuals (<500, , >1500EUR) High ~2000 EUR per station 160

266 3.13 B. Reproductive disorders in fish and amphipods: Reproductive success in amphipods Authors: Brita Sundelin, Doris Schiedek and Kari Lehtonen ICES SGEH Biological Effects methods Background Documents for the Baltic Sea region (ICES/OSPAR document from the ICES SGIMC Report 2010, complemented and modified by SGEH 2011 with information relevant for application in the Baltic Sea region) Description of the indicator Crustacean amphipods are regularly used in bioassays and laboratory exposure experiments for effects of contaminants. They carry their brood in an egg chamber until hatching and by analyzing the reproduction success we can score the effects of contaminant load in sediment and water. Twenty years of ecotoxicological studies in softbottom microcosms and studies of field populations collected in contaminated industrial areas have demonstrated toxicant-sensitive variables on the embryonic development of the Baltic amphipod species Monoporeia affinis and Pontoporeia femorata (Sundelin 1983, 1984, 1988, 1989, 1998, Eriksson et al., 1996, Eriksson Wiklund et al., 2005) and other amphipod species (Ford et al. 2003a, Sundelin et al. 2008, Bach et al. 2010). When exposed to heavy metals, chlorinated organic compounds, pulp mill effluents or contaminated sediments in bioassays as well as in field studies, the frequency of malformed embryos has been demonstrated to be significantly higher when compared to control microcosms and reference areas (Elmgren et al., 1983, Sundelin, 1983, 1984, 1988, 1989, 1991, Eriksson et al, 1996, Sundelin and Eriksson, 1998, Eriksson Wiklund et al., 2005) suggesting the variable to be a general bioindicator of contaminant effects. Organic contaminants are often associated to lipids. During oogenesis large quantities of lipids are deposited into the developing oocytes (Herring 1974, Harrison, 1990, Harrison, 1997, Wouters et al., 2001, Rosa and Nunes, 2003). These lipids, which consist mostly of monounsaturated fatty acids, are utilized and consumed during embryo development (Morais et al., 2002, Rosa et al., 2003, 2005), potentially leading to toxic effects of lipophilic contaminants increasing during embryogenesis. These effects also arise in low concentrations that do not demonstrably affect the sexual maturation, fertilization rate, fecundity (eggs/female) and rate of embryo development (time to hatching), indicating embryogenesis to be even more sensitive than other variables of the reproduction cycle. All amphipod species show a similar direct embryo development despite differences in sexual behaviour before mating and in duration of embryogenesis that differs, mainly due to ambient temperature (Bregazzi, 1973, Lalitha et al., 1991, McCahon and Pascoe, 1988). Therefore, this similar development allows for a consistent method of staging embryogenesis amongst all amphipod species and any resultant aberrations, which makes them particularly good for biomonitoring reproduction effects in situ. Other embryo aberrations respond to oxygen deficiency, scarcity of food quality and quantity and temperature stress (Eriksson, Wiklund and Sundelin 2001, 2004, Sundelin et al. 2008). Multiple stressors act in concert in the environment and by analysing different types of aberrant embryo development we can discriminate between some of them. The method gives information about health status of the amphipod populations since diseases, parasite infection, sexual maturation in terms of oogenesis in females and sexual development in males and fecundity are scored. Confounding factors Malformed embryos seem to be comparatively insensitive to other environmental stressors but contaminant exposure. However a seven year field study showed a correlation between organic content in the sediment and malformation rate (Eriksson Wiklund and Sundelin 2004). This could likely depend on higher concentrations of contaminants in sediments with higher load of organic content. The same study didn t show any relationship between oxygen concentrations in bottom waters, temperature and malformation rate. A negative 161

267 correlation was found between females carrying a dead brood and the oxygen concentration of the bottom water. Fecundity was positively correlated with the carbon content of the sediment but negatively correlated with the temperature of the bottom water. These results confirm the findings of previous laboratory experiments (Eriksson Wiklund and Sundelin 2001). Undeveloped eggs (undifferentiated eggs) are not correlated to contaminant exposure but seem to occur due to low food resources and possibly to increased temperatures but there are no clear correlations so far (Sundelin et al 2008). To meet the possible confounding factors additional variables i.e. organic content and oxygen in sediment and bottom waters should be measured on sampling stations. Ecological relevance Crustaceans are one of the most abundant invertebrate groups and it is relevant to include them in monitoring activities. Amphipods are regarded as particularly sensitive to contaminant exposure (Conlan 1994). Furthermore amphipods lack pelagic larvae and thus they are comparatively stationary facilitating the linkage between effects and environmental conditions. The deposit-feeding amphipod Monoporeia affinis, and the marine species Pontoporeia femorata are important benthic key stone species in the Swedish fresh and brackish water environment and are efficient bioturbators and important for the oxygenation of the sediment. They are significant food source for several fish species and other macrofauna species (Arrhenius and Hansson, 1993; Aneer, 1975). By analyzing reproduction variables as malformed embryos and other aberrant embryo development we combine the supposedly higher sensitivity of low-organization level biomarkers with the higher relevance attributed to variables giving more direct information on next-generation and population level effects (Sundelin 1983, Tarkpea et al., 1999, Cold and Forbes 2004, Heuvel- Greve et al., 2007, Hutchinson 2007). Quality Assurance Guidelines are available in ICES Techniques in Marine Environmental Sciences (TIMES) no 41. Quality assurance declaration is updated regularly at website at Swedish EPA aden/kust_och_hav/kvalitetsdeklaration_embryonal_vitmarla.pdf. Quality assurance has been practiced during training courses and workshops when different persons analyzing the embryos checked the accordance by examining the same brood. The accordance was between 90 to 97%. Since M. affinis is a glacial relict of fresh water origin occurring in inland waters below the highest coastline and the method has been used and evaluated also in Swedish greater lakes as Lake Vänern and Lake Vättern (Sundelin et al 2008). For method description see Sundelin et al ( Assessment Criteria The reproduction success of the freshwater amphipod Monoporeia affinis and the marine species Pontoporeia femorata in terms of various embryo aberrations have been measured in Baltic proper and Bothnian Sea since an international evaluation in 1993 priorotized the method as one of the most useful for effect monitoring of contaminants in the Baltic. The method has also been used for other amphipod species in coastal waters outside Great Britain, Gulf of Riga, Gulf of Gdansk and in the Belt Sea. The method is used in the Bonus Beast programme as a core biomarker in all areas of the beast programme. All species of amphipods could be analyzed for embryo aberrations and health status. The same protocol and method could be used for all of them (See TIMES 41). Field studies using different species of amphipods inhabiting the same area show a similar background level of malformation rate. However assessment criteria have only recently been developed 162

268 for Monoporeia affinis where there exist a long-term trend series since 1994 in the Bothnian Sea and Baltic proper. Table 1. Assessment criteria for malformed embryos of Monoporeia affinis in the Baltic. Seventeen years data were used for the calculation of background response (<5.7% malformed embryos) and assessment criteria. The limit between good and moderate status was put at a value where all (> 99%) variation in the reference dataset is included. The yearly mean and the the 99th percentile in the reference dataset were estimated by bootstrapping. Three stations with at least 10 gravid females were put as minimum for classifying the status of the area. Status class Malformed embryos% High < 0,029 Good 0,029 < 0,057 Moderate 0,057 < 0,086 Poor 0,086 < 0,114 Bad > 0,114 Distribution of indicator species in Baltic Sea subregions M. affinis occurs in the whole Baltic from northern part of the Bothnian Bay to the Gulf of Gdansk and Gulf of Riga. In the Belt Sea, where salinity is too high for M. affinis only the related species Pontoporeia occurs. The marine related species P. affinis occurs up to the northern Bothnian Sea where it disappears due to lower salinity. The deposit-feeding amphipod Corophium sp.occurs in the whole Baltic. Various gammarid species occur in the whole Baltic but most species are restricted to more shallow areas than M.affinis and P. femorata and live in the seaweed belt. Acknowledgements We acknowledge Anders Bignert at The Swedish Museum of Natural History and Kjell Leonardsson at Umeå University for important support during the calculation of assessment criteria. We also thank the Bonus project BEAST for opportunity to validate the methods for other amphipod species and the dep of Applied Environmental Science (ITM) for facilitating the progress of the work. References Bach, L, Fischer A, Strand J, Local anthropogenic contamination affects the fecundity and reproductive success of an Arctic amphipod. Marine Ecological Progress Series Bregazzi, P. K Embryological development in Tryphosella kergueleni (Miers) and Cheirimedon femoratus (Pfeffer) (Crustacea: Amphipoda). British Antarctic Survey Bulletin, 32: Chapman, P.M., Wang, F., Janssen, C., Persoone, G., and Allen, H. E., Ecotoxicology of metals in aquatic sediments: binding and release, bioavailability, risk assessment and remediation. Canadian Journal of Fisheries and Aquatic Sciences, 55: Cold, A., and Forbes, V Consequences of a short pulse of pesticide exposure for survival and reproduction of Gammarus pulex. Aquatic Toxicology, 67: Conlan, K.E Amphipod crustaceans and environmental disturbance a review. Journal of Natural History, 28: Journal of Natural History, 28: Elmgren, R., Hansson, S., Larsson, U., Sundelin, B., and Boehm, P The "Tsesis" oil spill: Acute and longterm impact on the benthos. Marine Biology, 73,

269 Eriksson, A-K., Sundelin, B., Broman, D., and Näf, C Effects on Monoporeia affinis of HPLC-fractionated extracts of bottom sediments from a pulp mill recipient. In: Environmental fate and effects of pulp and paper mill effluents. Servos et al., (eds) p 69-78, St Lucie Press Florida. Eriksson Wiklund, A-K., and Sundelin, B Impaired reproduction of the amphipods Monoporeia affinis and Pontoporeia femorata as a result of moderate hypoxia and increased temperature. Marine Ecology Progress Series, 171: Eriksson Wiklund, A-K., and Sundelin, B Biomarker sensitivity to temperature and hypoxia- a seven year field study. Marine Ecology Progress Series, 274: Eriksson Wiklund, A-K, Sundelin, B., and Broman, D Toxicity evaluation by using intact sediments and sediment extracts, Marine Pollution Bulletin, 50: Eriksson Wiklund, Sundelin B, Rosa R (2008). Population decline of the amphipod Monoporeia affinis in Northern Europe, consequence of food shortage and competition. J Exp Mar Biol Ecol, 367; Eriksson Wiklund AK., Dahlgren K, Sundelin B, Andersson A. (2009). Effects on benthic production of Climate induced alteration in the pelagic food web. Mar Ecol Prog Ser, 396: Ford, A.T., Fernandes, T.F., Rider, S.A., Read, P.A., Robinson, C.D., and Davies I.M. 2003a. Measuring sublethal impacts of pollution on reproductive output in marine Crustacea. Marine Ecology Progress Series, 265: Gorokhova, E. Löf M, Halldórsson H, Tjärnlund U, Lindström M, Elfwing T, Sundelin (2010). Single and combined effects of hypoxia and contaminated sediments on the amphipod Monoporeia affinis in laboratory toxicity bioassays based on multiple biomarkers. Aquatic Toxicology. van den Heuvel-Greve, M., Postina, J., Jol, J., Kooman, H., Dubbeldam, M., Schipper, C., and Kater, B A chronic bioassay with the estuarine amphipod Corophium volutator: Test method description and confounding factors. Chemosphere, 66: Harrison, K. E The role of nutrition in maturation, reproduction and embryonic development of decapod crustaceans: a review. Journal of Shellfish Research, 9: Harrison, K. E Broodstock nutrition and maturation diets. In Crustacean Nutrition 6. Edited by L. R. D Abrano, D. E. Conklin and D. M. Akiyama. The World Aquaculture Society. Baton Rouge, Louisiana, pp Herring, P. J Size, density and lipid content of some decapod eggs. Deep Sea Research, 21: Hutchinson, T. H Small is useful in endocrine disrupter assessment - four key recommendations for aquatic invertebrate research. Ecotoxicology, 16: Lalitha, M., Shyamasundari, K., and Hanumantha Rao, K Embryological development in Orchestia platensis kroyer (Crustacea:Amphipoda). Uttar Pradesh Journal of Zoology, 11: McCahon, C. P., and Pascoe, D Use of Gammarus pulex (L.) in safety evalutions tests: culture and selections of a sensitive life stage. Ecotoxicology and Environmental Safety, 15: Morais, S., Narciso, L., Calado, R., Nunes, M. L., and Rosa, R Lipid dynamics during the embryonic development of Plesionika martia (Decapoda; Pandalidae), Palaemion serratus and P. elegans (Decapoda; Pandalidae): relation to metabolic consumption. Marine Ecology Progress Series, 242: Rosa, R., and Nunes, M. L Tissue biochemical composition in relation to the reproductive cycle of the deep-sea decapod, Aristeus antennatus in the Portuguese south coast. Journal of the Marine Biological Association of the United Kingdom 83: Rosa, R., Morais, S., Calado, R., Narciso, L., and Nunes, M.L Biochemical changes during the embryonic development of Norway lobster, Nephrops norvegicus. Aquaculture, 221: Rosa, R., Calado, R., Andrade, A. M., Narciso, L., and Nunes, M. L Changes in amino acids and lipids during embryogenesis of European lobster, Homarus gammarus (Crustacea: Decapoda). Comparative Biochemistry and Physiology part B, 140: Sundelin, B Effects of cadmium on Pontoporeia affinis (Crustacea: Amphipoda) in laboratory soft-bottom microcosms. Marine Biology, 74: Sundelin, B Single and combined effects of lead and cadmium on Pontoporeia affinis (Crustacea: Amphipoda) in laboratory soft-bottom microcosms. In: Ecotoxicological testing for the marine environment. G. Persoone, E. Jaspers, and C. Claus (Eds). State University of Ghent and Institute for Marine Scientific Research, Bredene, Belgium. Vol p. Sundelin, B Effects of sulphate pulp mill effluents on soft-bottom organisms - a microcosm study. Water Science and Technology, 20:

270 Sundelin, B Ecological effect assessment of pollutants using Baltic benthic organisms. Thesis, Univ. of Stockholm, Dep. of Zoology Stockholm. Sundelin, B., and Eriksson, A-K Malformations in embryos of the deposit-feeding amphipod Monoporeia affinis in the Baltic Sea. Marine Ecology Progress Series, 171: Sundelin, Rosa R, Eriksson Wiklund A-K (2008). Reproduction disorders in a benthic amphipod, Monoporeia affinis, an effect of low food quality and availability. Aquatic Biology, 2: Swartz, R. C., DeBen, W.A., Sercu, K.A., and Lamberson, J.O Sediment toxicity and the distribution of amphipods in Commencement Bay, Washington USA. Marine Pollution Bulletin, 13: Tarkpea, M., Eklund, B., Linde, M., and Bengtsson, B-E Toxicity of conventional, elemental chlorine-free, and totally chlorine-free kraft-pulp bleaching effluents assessed by short-term lethal and sublethal bioassays. Environmental Toxicology & Chemistry, 18: Wouters, R., C. Molina, P. Lavens, and Calderon, J Lipid composition and vitamin content of wild female Litopenaeus vannamei in different stages of sexual maturation. Aquaculture, 198:

271 4. Candidate indicators for biodiversity and hazardous substances The HELCOM CORESET project identified several indicators which fulfilled the basic criteria to be proposed as core indicators, but that lacked some of the selection criteria, for example, validation of the scientific basis, links to pressures or the GES boundary. These indicators were labelled tentatively as candidate indicators and they will be revisited during the CORESET project. If finalized, the candidate indicators would fill significant gaps in environmental assessments, covering functional groups, anthropogenic pressures or hazardous substances that are not addressed by any of the proposed core indicators. Although many of the candidate indicators require more work, some of them are close to being finalized. This chapter presents the candidate indicators, which were identified in the HELCOM CORESET project. The candidate indictors are listed in the summary table below and then described following the same numbering in separate sections. The summary table also includes expected approaches to define good environmental status for the indicators. Table 4.1. Candidate indicators for biodiversity, hazardous substances and effects of hazardous substances. Candidate indicators Approach to define GES boundary 1. Distribution of harbour porpoise Based on historic reference distribution. 2. By-catch of marine mammals, seabirds and non-target fish 3. Impacts of anthropogenic underwater noise on marine mammals 4. Fatty-acid composition of seals as measure of food composition 5. Abundance of breeding populations of seabirds By-catch close to zero. Deviation from zero can be higher for non-target fish species which have healthy stocks. Mammals and birds should have stricter targets. Modeling of noise intensity and mapping human activities causing noise. Basic scientific research on the fatty-acid composition, describing a balanced species composition of prey species. Defining sub-basin wise reference levels (mean of a selected time window) and a deviation from that. See OSPAR EcoQO. 6. Proportion of oiled seabirds A decreasing trend (see OSPAR EcoQO). 7. Incidentally and non-incidentally killed A decreasing trend. white-tailed eagles 8. Salmon smolt production capacity GES boundary is based on a%-level which allows sustainable exploitation of the stock. The HELCOM proposal for the salmon potential smolt production capacity (PSPC) is 80%. 9. Sea trout parr density GES boundary should be set on a%-level which supports a viable sea trout population in a river, taking into account also the exploitation pressure on the stock. Such target does not currently exist and therefore an interim target may need to be set in order to make initial assessments. The quality of the spawning habitat needs to be assessed on a class scale. 10. Large fish individuals from fisherybased data sources Reference conditions from fishery independent data sets. 11. Abundance of cyprinids in Expert judgment archipelago areas 12. Ratio of opportunistic and Site-specific ratios. Partly established under WFD. perennial macroalgae 166

272 13. Cladophora length Based on experimental data. Under development. 14. Size distribution of benthic longliving species Based on low-impacted conditions (reference areas/periods). 15. Blue mussel cover Long-term means + expert judgement 16. Cumulative impacts on benthic habitats Based on the favourable conservation status of the EU Habitats Directive. 17. Biomass of copepods Based on time periods of good nutritional status of herring. 18. Biomass of microphageous Based on time periods of good water transparency zooplankton 19. Zooplankton species diversity Based on species lists. 20. Mean zooplankton size Long-term means + expert judgement. 21. Zooplankton-phytoplankton Long-term means + expert judgement. biomass ratio 22. Phytoplankton diversity Long-term means + expert judgement. 23. Seasonal succession of functional Long-term means + expert judgement. phytoplankton group 24. Alkylphenols Environmental Quality Standards for nonyl- and octylphenol 25. Vitellogenin induction A level not showing feminization of male fish 26. AChE inhibition BAC established and EAC estimated. 27. EROD/CYP1A induction BAC is under development. 167

273 4.1. Distribution of harbour porpoise 1. Working team: Marine Mammals Author: Stefan Braeger 2. Name of candidate indicator Geographical distribution of the critically endangered Baltic Proper harbour porpoise 3. Unit of the candidate indicator Presence as indicated by the frequency of registrations per area in a year (e.g., >10 registrations/1000km 2 ) 4. Description of proposed indicator The current population size of the Baltic harbour porpoise is extremely small and due to its low abundance no longer reliably quantifiable. Therefore, it appears impracticable to propose the abundance of harbour porpoise as a state indicator or a quantitative target for abundance as a conservation goal. At extremely low densities, such target would be almost impossible and very costly to monitor. The Baltic porpoise population has not only dwindled in numbers to less than 250 reproducing adults (IUCN 2008) but also evacuated large parts of its historic range throughout the Baltic Proper. Therefore, the extent of the distribution range appears to be a suitable proxy for population size assuming that an increasing population would also be likely to expand its range. Annecdotal information on (pre-industrial) porpoise distribution indicates a probably continuous distribution throughout the Baltic Proper, possibly also covering the entire Gulf of Bothnia as well. Therefore, a regular basin-wide presence could serve as proxy for successful population recovery. 5. Functional group or habitat type Harbour Porpoise (a piscivorous top predator) 6. Policy relevance Habitats Directive, Marine Strategy Framework Directive, and national obligations under a number of IGO resolutions (e.g., HELCOM, OSPAR, CMS, ASCOBANS etc.). MSFD Descriptor 1, criterion 1.1 Species distribution. The Baltic Sea Action Plan calls for Abundance, trends, and distribution of Baltic harbour porpoise as preliminary indicator for nature conservation and biodiversity. To achieve a viable population of this species, it provides the following targets: By 2012 spatial/temporal and permanent closures of fisheries of sufficient size/duration are established thorough the Baltic Sea area and By 2015 by-catch of harbour porpoise, seals, water birds and non-target fish species has been significantly reduced with the aim to reach by-catch rates close to zero 7. Use of the indicator in previous assessments ASCOBANS, e.g. in the Jastarnia Plan (2002 & 2009). 8. Link to anthropogenic pressures Directly linked to gillnet fisheries, persistant organic pollutants, underwater noise (e.g., from piledriving, underwater explosions, seismic surveys, military sonar), disturbance from shipping, and habitat destruction (e.g. from gravel extraction, offshore structures, coastal development) among others. 9. Pressure(s) that the indicator reflect Selective extraction of species, including incidental non-target catches, as well as others mentioned and point Spatial considerations Since harbour porpoises are highly migratory mammals, the spatial considerations would be determined by the desired species distribution, e.g. Baltic Proper. 11. Temporal considerations Harbour porpoises live in the Baltic Sea year-round, but have to avoid complete ice cover. The re-colonisation of the entire Baltic Proper cannot rely on immigration from other populations and 168

274 will thus depend on intrinsic population growth from a very low abundance. Therefore, it is likely to take several decades at best. 12. Current monitoring Two aerial surveys of the southwestern part of the Baltic Proper (between southern Sweden and the coast from Darss Ridge to Gdansk) in 1995 and 2002 resulted in best estimates of 599 and 93 porpoises, respectively. Currently, porpoise densities are regarded as too low to make visual surveys any longer viable. Therefore, an ongoing international research project ( SAMBAH ) uses static acoustic monitoring in 300 locations in the Baltic Proper in water depth between 5 and 80 metres and first results regarding the geographical distribution are expected to become available in the year 2014 ( 13. Proposed or perceived target setting approach with a short justification. To measure the success of conservation measures that results in an increase of porpoise distribution range (and by analogy in porpoise numbers), a SAMBAH-like survey should be periodically repeated e.g. every ten years. Additionally, the number of sighted and locally stranded porpoises may provide a useful indicator for the regular presence of porpoises as well as insights into population health. Such information could be based on promotion of new or already existing voluntary reporting schemes such as provided in Poland ( Germany ( Sweden ( r.445.html), and Finland ( Ultimately their entire historical range throughout the Baltic Proper should be recolonised by Baltic harbour porpoises. By then porpoises densities should have recovered sufficiently to allow reliable abundance estimation and the setting of alternative conservation targets. The Baltic Sea Action Plan, for example, also recommends pregnancy rate, fecundity rate, and the occurrence of pathological findings as indicators and targets for the ecological objective By-catch of marine mammals and birds 1. Working team: Marine Mammals Author: Stefasn Braeger 2. Name of candidate indicator Bycatch of marine mammals and birds 3. Unit of the candidate indicator Numbers of individuals bycaught in fishing gear 4. Description of proposed indicator Bycatch in fishing gear is known to be the most important threat to biodiversity and potential disruption of the food web as far as marine mammals in the wider Baltic Sea are concerned. Bycatch is also regarded as one of the main direct anthropogenic pressures on marine diving bird species. It can be measured as number of bycaught porpoises or seals either by a nearcomplete coverage with on-board observers/ CCTV-recording or by examining beached individuals. All net-setting vessels should be monitored since monitoring only a subset of vessels would lead to an estimate with considerable variance. Beached individuals with clear signs of by-catch injuries confirmed by pathological investigations can give indications that bycatch occurred in an area, but it is very difficult to use such data for obtaining total numbers of animals being affected and hence impacts on populations. For healthy mammal populations (with an abundance 80% of a population at carrying capacity) a tolerable bycatch rate may amount to 1.0% (plus another 0.7% anthropogenic take due to other impacts such as pollution, noise etc.) of the local population. For depleted populations such as the critically endangered (according to Hammond et al. 2008) porpoise population of the Baltic Proper and the rapidly decreasing (according to Teilmann et al. 2011) porpiose population of the Belt Sea, bycatch was recommended to be reduced to near zero immedeately (cf. ASCOBANS 2002). For birds it has been shown that present bycatch rates are close to, or 169

275 for some species even exceeding, levels that can be sustained by the populations. 5. Functional group or habitat type Toothed whales, seals and birds (i.e., the piscivorous top predators) 6. Policy relevance Habitats Directive, Marine Strategy Framework Directive, and national obligations under a number of IGO resolutions (e.g., HELCOM, OSPAR, CMS, ASCOBANS, AEWA etc.) The Baltic Sea Action Plan provides the following targets: By 2012 spatial/temporal and permanent closures of fisheries of sufficient size/duration are established thorough the Baltic Sea area and By 2015 by-catch of harbour porpoise, seals, water birds and non-target fish species has been significantly reduced with the aim to reach by-catch rates close to zero 7. Use of the indicator in previous assessments ASCOBANS (2002 & 2009) in the Jastarnia Plan, none for seals and birds. 8. Link to anthropogenic pressures Directly linked to commercial fishery and recreational fishing with gillnets, and to a lesser degree and indirectly (through prey depletion) with other commercial fishery such as pelagic and bottom trawling as well as other coastal stationary gear. 9. Pressure(s) that the indicator reflect Selective extraction of species, including incidental non-target catches 10. Spatial considerations Since harbour porpoises are highly migratory mammals, the spatial considerations would be determined by the desired species distribution, e.g. Baltic-wide. Bycatch of birds is higher in areas where large bird concentrations occur. Such areas, however, are distributed throughout the Baltic. 11. Temporal considerations Harbour porpoises live in many parts of the Baltic Sea year-round, but have to avoid complete ice cover. Therefore, considerations could be less stringent in northern parts of the Baltic Sea in winter during ice-cover. Bird bycatch rates are higher in winter (Oct-April) due to several bird species then occurring in the marine environment in large concentrations. Bycatch, however, does occur all year around, although it affects different species at different times of the year. Areas covered completely by ice do not hold any diving birds and hence have no bycatch in winter. 12. Current monitoring In some rather small parts of the western Baltic Sea, porpoise monitoring is being attempted under EC Regulation 812/2004, however, with insufficient coverage. Furthermore, it is also required under the Habitats Directive. There is no monitoring for bird bycatch so far. 13. Proposed or perceived target setting approach with a short justification. In the Baltic Proper and in the Belt Sea, porpoise bycatch needs to be close to zero to allow recovery of the populations. The anthropogenic removal (including by pollution, ship strike, noise etc.) of more than one porpoise from this entire population has been modeled to thwart recovery from the brink of extinction (Berggren et al. 2002). The target of zero bycatch should be linked to a policy decision, e.g. to close the area for net-setting fisheries for the remainder of the year as soon as more than one harbour porpoise has been caught (cf. NOAA 2010, NZ Minister of Fisheries 2006). For the vulnerable Belt Sea population, an anthropogenic removal of 1% of the total population per year in Danish, Swedish and German waters combined would not allow recovery of the population from a 60% reduction between 1994 and 2005 and jeopardise its continued survival (Teilmann et al. 2011). For birds, levels of of tolerable total anthropogenic removal have been calculated for a few species based on known population sizes and demographic parameters. Such levels can be used to calculate the levels of bycatch that can be sustained by the populations (if knowing other 170

276 sources of anthropogenic mortality as well). GES boundaries could then be set at levels below these to guarantee continued survival of the populations. References: ASCOBANS ( ): ASCOBANS Recovery Plan for Baltic Harbour Porpoises (Jastarnia Plan). Berggren, P., Wade, P.R., Carlström, J. & Read, A.J. (2002): Potential limits to anthropogenic mortality for harbour porpoises in the Baltic region. Biological Conservation 103: Hammond, P.S., Bearzi, G., Bjørge, A., Forney, K., Karczmarski, L., Kasuya, T., Perrin, W.F., Scott, M.D., Wang, J.Y., Wells, R.S. & Wilson, B. (2008): Phocoena phocoena (Baltic Sea subpopulation). IUCN Red List of Threatened Species. NOAA (2010): Harbor Porpoise Take Reduction Plan: New England. NZ Minister of Fisheries (2006): SQU6T Sea Lion Operational Plan: Final Advice Paper. 0B7E928A1B6D/0/squ6t_fap_part1.pdf Teilmann, J., Sveegaard, S. & Dietz, R. (2011): Status of a harbour porpoise population - evidence of population separation and declining abundance. Jastarnia Group 7 Report, Annex Impacts of anthropogenic underwater noise on marine mammals 1. Working team: Marine Mammals Authors: Stefan Braeger & Stefanie Werner 2. Name of candidate indicator Impacts of anthropogenic underwater noise on marine mammals 3. Unit of the candidate indicator Single and cumulative impacts on marine life from highamplitude, low and mid-frequency impulsive sounds and low frequency continuous sound emitted per area and time 4. Description of proposed indicator There is a broad range of physiological or behavioral reaction to noise. Noise presents at least following threats: diversion of attention and disruption of behavior, habituation, masking of important signals, temporary and permanent effects of hearing and injury to other organs, sometimes leading to death. Seals are thought to be more sensitive to certain low frequency sound sources than harbor porpoises, but there are evident gaps in knowledge about their hearing capacities. Noise mapping should be conducted to analyze noise budgets of regional sea areas. Especially high-frequency and mid-frequency SONAR as well as percussive pile-driving during offshore construction and the use of airguns during seismic explorations and explosions during clearing of old ammunition are known to impact marine mammals behaviour severely or cause morphological damage. Shipping is known to be the dominant continuous sound source leading to ever increasing ambient noise levels. Acoustic indicator need to represent all noise components that have impact on marine life. Based on this overall allowable noise budgets can be set up. The indicator should aim on measuring loud, low and mid frequency impulsive sound as well as continuous low frequency sound sources and predict for their single and cumulative effects on marine life. Models need to be applied that allow predicting sources and frequency specific sound levels and sound propagation. Three-dimensional noise (propagation) maps should be produced showing the single and cumulative impact of different noise sources on a species by species basis. Knowing the potential habitat of marine life of concern and the potential impact of noise, it is possible to describe the potential impact on marine life. The species dependent impacts need to be estimated and weighted. Metrics for some of the sound induced effects on marine life are or 171

277 will most likely become available over the next years. It is already possible to determinate impairment of significant life functions. Non permanent auditory injury (Temporal Threshold Shift - TTS) as well as the limited acoustical availability of habitat (masking) can already be expressed in metrics. The question above which needs to be answered is: when do these adaptive responses to an environmental stress, which are within an animals capacity to respond, lead to negative consequences for vital rates and populations. 5. Functional group or habitat type Harbour porpoises, Grey, Harbour and Ringed seals 6. Policy relevance Marine Strategy Framework Directive, Habitats Directive and a number of IGO resolutions (e.g., HELCOM, OSPAR, CMS, ASCOBANS etc.) The Baltic Sea Action Plan provides the following target: By 2015, improved conservation status of species included in the HELCOM lists of threatened and/or declining species and habitats of the Baltic Sea area, with the final target to reach and ensure favourable conservation status of all species 7. Use of the indicator in previous assessments ASCOBANS, e.g. in the Jastarnia Plan (2002 & 2009) 8. Link to anthropogenic pressures Impulsive sound inputs in the Baltic are directly linked with offshore construction of wind farms, use of different types of Sonar, Depth Sounder and Fish Finder, explosions mainly for clearing of old ammunition and the use of Acoustic harassment devises for fishing and scaring of marine mammals during construction periods of wind turbines. Shipping as well as dredging of sand and gravel and the operation of offshore wind farms are related to the introduction of continuous sounds introduction. 9. Pressure(s) that the indicator reflect Anthropogenic underwater noise in the baltic environment. 10. Spatial considerations Sound travels in water about five time faster than in air and absorption is less compared to air. Due to t relatively good transmission underwater, sound acts at considerable spatial scales leading to vast impacted areas (e.g. >1000km² during pile-driving of a wind park) avoided by porpoises for a longer time. Noise of different sources can add up and may lead to synergies. Transmission varies with frequency: low frequency signals typically travel further whereas higher frequencies attenuate more rapidly, therefore fewer individuals might be exposed. Due to the low salinity of the Baltic a considerably lower absorption can be observed compared to other sea areas, which means that the radiated acoustic power travels over broader distances, especially at higher frequencies. 11. Temporal considerations Although each single sound may attenuate rather quickly under water, the total amount appears to increase constantly. Persistence of sound is very variable ships on passage generate continuous sound whereas explosions are very short-term. From late spring to early autumn, harbour porpoises give birth and tend to very young calves that depend completely on the guidance of their mothers. This relationship appears to be particularly sensitive to disturbance by underwater noise. On days with pile driving activities in Nysted percent less grey and harbour seals seeked their resting places than on usual days. A negative correlation was shown between main shipping lanes in the Baltic and harbour porpoise abundance. 12. Current monitoring So far, no monitoring of underwater noise appears to be in place in the Baltic Sea beside of the obligations for construction and operation of offshore wind farms. 13. Proposed or perceived target setting approach with a short justification. The introduction of impulsive and continuous sounds should be measured and modelled in order 172

278 to predict for the cumulative impacts on marine life. Data from aerial and ship-based abundance surveys of marine mammals need to be used for habitat modelling. The sound sources that exceed thresholds that are likely to entail significant impact on marine animals have to be defined and these levels need to be defined in a precautionary way. Maximum sound exposure levels at a certain distance from the sound source for pile driving activities are already in force in Germany, for example, and could become compulsory in all EU waters. Overall allowable noise budgets per area and time need to be defined. The total amount of energy introduced into any area over a standardized time should be generally limited and permitted on a case by case basis with binding mitigation measures in place. To establish the species specific impact as a function of the distribution of noise over time and space the above mentioned steps can be used to create a (threshold) factor as an indicator for the impact of noise. For species of concern, it is therefore necessary to develop a threedimensional (propagation) model that takes account of the duration of noise events. The result of this modeling process would be a map with a grid of related impacts based on the Sound Exposure Level (SEL). The benefit of this approach is the possibility of defining acceptable levels based on scientific estimates. High-frequency sounds, e.g. from depth sounders, fish finders and other SONAR should be limited, especially in shallow coastal areas, to the minimum. The level of underwater noise below 300 Hz is dominated by noise inputs from ships. This noise is broadband and has a maximum level of 50 Hz. It can definitely be correlated with the propeller of a ship. Ship quietening measures need to be identified with the view on how to influence different operational parameters of the ship (e.g. fuel consumption) Fatty-acid composition of seals as measure of food composition This candidate indicator is a measure of food composition and, thus, follows changes in the food web. There is very little data available of the fatty-acid composition in the seals. The data set should be widened and used to determine the fatty-acid composition which indicates good environmental status of food webs. It should also be ensured that the fattyacid composition of studied individuals is not caused by other factors such as illnesses or hazardous substances. This indicator requires basic scientific research until it can be used in environmental assessments Abundance of breeding populations of seabirds 1. Working team: Seabirds 2. Name of candidate indicator Abundance of breeding populations of seabirds 3. Unit of the candidate indicator Species-level: individuals Integrated level: proportion of species above the target 4. Description of proposed indicator Seabirds are significant predators and herbivores of the marine ecosystem. The indicator follows population sizes of pre-selected seabird species, belonging to different functional groups. The indicator follows the OSPAR EcoQO for breeding birds, where each species has a separate reference level and target level but the indicator measures the proportion of species reaching their targets. The indicator should be set separately to different sub-basins of the Baltic Sea, as species abundances and even species composition varies geographically in the Baltic Sea. 173

279 5. Functional group or habitat type Coastal herbivores, coastal benthic feeders, coastal pelagic fish feeders, offshore pelagic fish feeders 6. Policy relevance Descriptor 1, criterion 1.2 Population size Descriptor 4, criterion 4.2 Abundance/distribution of key trophic groups and species (Descriptor 5 & 6: indirectly) 7. Use of the indicator in previous assessments OSPAR EcoQO 8. Link to anthropogenic pressures The breeding seabirds are directly impacted by habitat loss, oil spills, by-catch of fisheries, hunting, displacement by offshore constructions and shipping traffic. Indirect impacts include eutrophication and physical disturbance of bottom sediments (through changes in food supplies). Although eutrophication affects the population only indirectly, it is the most significant factor affecting the abundance of breeding seabirds. 9. Pressure(s) that the indicator reflect Habitat loss, selective extraction of species, introduction of synthetic compounds, input of fertilisers and organic matter, abrasion and selective extraction, changes in siltation and thermal regime, other physical disturbance. 10. Spatial considerations Seabirds breed in all the sub-basins of the Baltic Sea, but the species composition and abundance varies geographically. Therefore, each sub-basin should have an own list of selected indicator species with own reference levels and target levels. The assessments should be made on the sub-basin level. 11. Temporal considerations Frequency: ideally as often as possible, but realistically perhaps every fifth year 12. Current monitoring Monitoring done in all the Contracting States. Measured parameters must be compared and the indicator species agreed and included in the monitoring. 13. Proposed or perceived target setting approach with a short justification. The reference level for each seabird population should be set at a population size that is considered desirable for each individual species within each geographical area. This should be set for each species based on expert judgement of when population levels were subject to low impact by human activities. In the OSPAR EcoQO the target level was set to the level of standard deviation from the reference level. The lower target depended, however, partly on the species; species laying one egg were given stricter target (being more sensitive) than species laying more eggs. The proportion of species reaching their target is the integrated indicator. The target level could be 75% as in the OSPAR EcoQO. Additional indicators for the breeding seabird populations The abundance of breeding seabirds is a good indicator for following long-term changes, whereas it is not feasible for detecting short-term changes. Short-term responses to environmental changes can be better followed by reproductive parameters, such as breeding success or brood size. The OSPAR EcoQO (under development) for the breeding 174

280 success of the kittiwake is an example of such an indicator. It may be used as an indicator for the abundance of sandeel that also serves as a major food source for many other bird, fish and marine mammal species. Sandeel availability may be low because of natural reasons, or through industrial fishing that competes with seabirds. When the breeding success of kittiwake is low over a three-year period, this is likely to be triggered by low abundance of sandeel in coastal areas. The indicator thus shows the status of sandeel and kittiwake populations and the need to reduce industrial fishing. In the Baltic Sea, the availability of data on brood size and breeding success needs to be clarified. The national monitoring programmes to monitor the breeding populations of sea birds can be also used to develop a distribution indicator. The indicator would require sub-basin wise species selection and setting of GES boundaries. In addition, it should be decided which density threshold is used to determine the margin of distribution Proportion of seabirds being oiled 1. Working team Sea birds 2. Name of candidate indicator Proportion of seabirds being oiled 3. Unit of the candidate indicator Number of oiled seabirds per species 4. Description of proposed indicator Proportion of oiled seabirds found in the winter-time population counts are being used for the estimate of this indicator. In addition, proportion of oiled seabirds among those found dead or dying on beaches can be used as an additional information. 5. Functional group or habitat type Mainly offshore benthic feeders and offshore pelagic and surface feeding birds 6. Policy relevance Descriptor 1 Descriptor 4 7. Use of the indicator in previous assessments None 8. Link to anthropogenic pressures Directly linked to oil slicks/oil spills (shipping) 9. Pressure(s) that the indicator reflect oil slicks/oil spills (shipping) 10. Spatial considerations 11. Temporal considerations Frequency: should be updated annually 12. Current monitoring None 13. Proposed or perceived target setting approach with a short justification. A baseline could be set based on the current situation (baseline monitoring needed!) and then the approach adopted by OSPAR could be used. They suggest the following GES boundary The average proportion of oiled birds in all winter months (November to April) should be 20% or less by 2020 and 10% or less by 2030 of the total found dead or dying in 175

281 each of 15 areas of the North Sea over a period of at least 5 years 4.7. Incidentally and non-incidentally killed white-tailed eagles 1. Working team Sea bird team based on the HELCOM Indicator Fact Sheet on health status of white-tailed eagle. 2. Name of candidate indicator Incidentally and non-incidentally killed white-tailed eagles 3. Unit of the candidate indicator Proportion of dead eagles caused by anthropogenic causes 4. Description of proposed indicator Death causes of found dead eagles are estimated for birds handed in to the authorities. 5. Functional group or habitat type Top predatory birds 6. Policy relevance Descriptor 1 Descriptor 4 (Descriptor 8) 7. Use of the indicator in previous assessments Used in the HELCOM Population Development of Baltic Bird Species: White-tailed Sea Eagle (Haliaeetus albicilla) -indicator. For more detailed descriptions see the indicator fact sheet (2009) 8. Link to anthropogenic pressures Directly linked to hunting, persecution, synthetic and non-synthetic compounds, electrocution, collisions with wind turbines. 9. Pressure(s) that the indicator reflect Hunting, persecution, synthetic and non-synthetic compounds, electrocution, collisions with wind turbines. 10. Spatial considerations 11. Temporal considerations Frequency: can be updated annually 12. Current monitoring Monitored in Finland, Sweden, Germany and Denmark. 13. Proposed or perceived target setting approach with a short justification. Historical data exists that can be used as reference data Status of salmon smolt production, smolt survival and number of spawning rivers 1. Working team Author: Atso Romakkaniemi on the basis of work in ICES WGBAST 2. Name of candidate indicator Status of salmon smolt production, smolt survival and number of spawning rivers 3. Unit of the candidate indicator Three parameters: - smolt survival (%) 176

282 - smolt production (individuals) - increase/decrease in number of rivers with natural spawning of salmon (% change from xxxx(2010?) situation) 4. Description of proposed indicator Salmon (Salmo salar) is a big predatory species in the Baltic Sea marine ecosystem. Its abundance is affected not only by commercial fishing but also by the condition of the spawning rivers and the marine ecosystem. When smolts enter the sea, they must have enough suitable food items along their migration paths and they must be able to avoid predation and by-catching in order to survive over the first, critical year. Many of the spawning rivers have been dammed to produce hydroelectricity, and the spawning grounds have in many rivers degraded due to increased siltation and eutrophication (forestry, agriculture). There are also former salmon rivers with few or no migration obstacles; natural reproduction could be re-established especially in these rivers. This indicator is a combination of three parameters, which can be assessed separately and then combined (all or part of them) to give a single measure of the status of salmon. 1) survival of smolts in the sea, (can be also a separate indicator the conditions in marine ecosystem) 2) number of smolt produced annually in a river, and 3) number of salmon rivers (trend in the number of rivers). (The latter two reflect the reproduction of salmon and has a linkage to the marine ecosystem) 5. Functional group or habitat type Anadromous fish 6. Policy relevance Descriptor 1: Criterion 1.1 Species distribution Criterion 1.2 Species abundance Criterion 1.5 Habitat extent BSAP Ecological objective Thriving communities of plants and animals (Nature conservation) 7. Use of the indicator in previous assessments Derived from the ICES salmon assessments. Can be supplemented by the results of MS s monitoring for Habitats Directive, which has not been included in ICES work which focuses only on original stocks. 8. Link to anthropogenic pressures Smolt survival decreases as a result of lack or mismatch of suitable food (invertebrates and prey fish like young herring/sprat/stickleback the abundance of which are affected by human) and commercial fishing (by-catch). The smolt production depends on the number of spawners (affected by fishing) and the quality of the river (damming and degradation of suitable habitats). The number of salmon rivers decreases as a result of damming and degradation of suitable habitats and increases as a result of restoration efforts (improving passage through migration obstacles, measures to improve water quality, flow regimes, physical quality of spawning and nursery habitats). 9. Pressure(s) that the indicator reflect The indicator reflects fishing (commercial and recreational), state of the sea ecosystem (e.g., availability of food for young salmon), river connectivity, siltation (forestry, agriculture) and inputs of nutrients and organic matter (agriculture, waste waters, animal husbandry). 10. Spatial considerations 177

283 Baltic-wide, all rivers of wild or mixed salmon populations. Salmon migrates widely and hence is a part of the Baltic food web all over the basin. 11. Temporal considerations Smolt production and survival may vary annually depending on fishing effort and annual conditions at sea. Indicators describing a specific year become available by the end of May Current monitoring Estimates produced frequently by national research institutes and compiled by ICES working group WGBAST. Smolt survival and smolt production are basically ready for operational use. WGBAST may further develop the number of salmon rivers as an indicators, as well as can consider ways of combining the second and the third indicator; the outcome of this work is expected to be operational by Proposed or perceived target setting approach with a short justification. GES boundary is based on a %-level which allows sustainable exploitation of the stock. The HELCOM proposal for the salmon potential smolt production capacity (PSPC) is 80%. The GES boundary for this indicator could be based on this approach, but requires further development Sea trout parr densities of sea trout rivers vs. their theoretical potential densities, and the quality of the spawning habitats 1. Working team Author: Atso Romakkaniemi on the basis of work in ICES WGBAST 2. Name of candidate indicator Trout parr densities of sea trout rivers vs. their theoretical potential densities, and the quality of the spawning habitats 3. Unit of the candidate indicator % (proportion of parr density reached) and an index for classification of spawning habitats 4. Description of proposed indicator Sea trout (Salmo trutta) is a big predatory species in the Baltic Sea marine ecosystem. Its abundance is affected by fishing and the condition of the spawning rivers. Many of the spawning rivers have been dammed to produce hydroelectricity and the spawning grounds have in many rivers degraded due to migration obstacles and increased siltation and eutrophication (forestry, agriculture). This indicator is a combination of two parameters. The first one follows the realized parr densities of trout in rivers as a percentage of the estimated, theoretical maximum densities. This parameter serves as an overall response to the quality of the spawning grounds and the adjacent sea and the fishing pressures. The second parameter estimates the quality of the spawning habitat in the spawning rivers. This latter parameter is still under the development. The data for the indicators is compiled by national research institutes and the indicators would be calculated in the ICES WGBAST. WGBAST is further developing both indicators. The first indicator it is expected to be operational by 2012/2013 and the latter one by 2013/ Functional group or habitat type Anadromous fish 6. Policy relevance Descriptor 1: Criterion 1.1 Species distribution 178

284 Criterion 1.2 Species abundance Criterion 1.5 Habitat extent BSAP Ecological objective Thriving communities of plants and animals (Nature conservation) 7. Use of the indicator in previous assessments In ICES assessments 8. Link to anthropogenic pressures The parr densities in sea trout rivers decrease as a result of decreased quality of the spawning habitat or adjacent sea or due to increasing fishing pressure. 9. Pressure(s) that the indicator reflect The indicator reflects fishing pressure, siltation (forestry, agriculture), inputs of nutrients and organic matter (agriculture, waste waters, animal husbandry), and river connectivity. 10. Spatial considerations Baltic-wide. Sea trout does not migrate as widely as salmon and therefore the quality of the spawning rivers has a more direct connection to the adjacent sub-basin. 11. Temporal considerations The indicator responds to the river condition and therefore may respond slowly to management measures. Among the smallest rivers, annual variation in river flow is a driving force in annual variation of parr densities. 12. Current monitoring Estimates produced frequently by national research institutes and complied by ICES WGBAST. 13. Proposed or perceived target setting approach with a short justification. GES boundary should be set on a%-level which supports a viable sea trout population in a river, taking into account also the exploitation pressure on the stock. Such a target does not currently exist and therefore an interim target may need to be set in order to make initial assessments. The quality of the spawning habitat needs to be assessed on a class scale. The criteria for the classification are not yet ready Large fish individuals from fishery-based data sources 1. Working team MARMONI Life project (Antti Lappalainen et al.) 2. Name of candidate indicator Large fish individuals (complement) 3. Unit of the candidate indicator Proportion of large fish individuals in fish populations. Mean size of sexual maturation. 4. Description of proposed indicator The original core indicator Large fish individuals is monitored in HELCOM FISH project by gill nets. Perch and some Cyprinids typically form the bulk of the catch. Other data sources, such as coastal trawl surveys, can be used in order to get population level data from a wider group of species The fish catch data collected under the EU Data Collection Regulation is also a source which can be used for this indicator. A part of this data, e.g sampling of predatory species from herring traps, covers all size classes and can be treated here as fishery independent data. These data can be used e.g. to calculate: 179

285 1) Proportion of fish larger than the mean size of first sexual maturation 2) mean size at first sexual maturation These issues (1 and 2) are closely linked to effects of fishing pressure on fish populations and on population level biodiversity. In the Marmoni project, Finland (FGFRI) will shortly evaluate the usability of the fishery data (EU Data Collection regulation) and national trawl survey data for this kind of indicators. This work will be focused on pike-perch. In Estonia (EMI), there are long time series of trawling survey data, which might be used to assess the effects of fishery on pike-perch stocks. The usability of coastal commercial catch data to monitor the state of coastal fish stocks will be evaluated out, too. Latvia has long time series of trawling survey data, too, and the data will be evaluated in the Marmoni project. 10. Spatial considerations Valid in the entire Baltic Sea. 11. Temporal considerations 12. Current monitoring Fishery dependent data (catch samples from commercial fishery) is collected by all countries under the EU Data Collection Regulation. Trawling surveys are also carried out in several countries around the Baltic Sea. 13. Proposed or perceived target setting approach with a short justification. GES boundaries not set yet. Reference conditions could be based on fishery independent monitoring results from earlier time period(s). There is also a general principle that every fish individual should have a chance to spawn at least once before they are targets for effective fishery Abundance of Cyprinids in archipelago areas 1. Working team Finnish Game and Fisheries Research Institute (Lappalainen, Lilja and Heikinheimo) 2. Name of candidate indicator Abundance of Cyprinids in archipelago areas 3. Unit of the candidate indicator biomass (kg/ha) or catch per unit effort 4. Description of proposed indicator Cyprinids, especially bream (Abramis brama), roach (Rutilus rutilus) and white bream (Blicca bjoerkna) have become increasingly abundant in large archipelago areas of the northern Baltic Sea (e.g. in the Gulf of Finland, Archipelago Sea and the Åland archipelago). The main reason for the increased abundance is the coastal eutrophication favouring the reproduction of cyprinids in the inner archipelago, but the warm springs and low salinity may have contributed. Similar development has widely been reported from eutrophied lakes. The present high abundance of Cyprinids likely tends to maintain the eutrophic conditions in the archipelago areas thorough the effects on food webs and by increasing the leaking of nutrients from soft bottoms. The high amount of Cyprinids in the gill-net and trap net catch in the Finnish coastal areas has also been regarded as a problem for coastal commercial fishery and a bulk of the catches have been discarded. A high abundance of cyprinids also indicates a biased fish community structure, which may indicate less than good environmental status under the GES Descriptor 1. The relative abundance of Cyprinids has so far been monitored by multi-mesh gill-nets at 180

286 certain study areas especially in Sweden, but also in some study areas in Finland, Estonia and Lithuania. In both of the Finnish study areas, located in the Gulf of Finland, Cyprinids have formed over half of the total catches. There is relatively high temporal and spatial variation in the gill-net monitoring catches and it seems that this survey method underestimates the abundance of bream and white bream, which are the species mostly benefiting of coastal eutrophication. Gill-net monitoring could be seen here as one tool for an overall screening and more thorough assessments should be considered in areas where the abundance of Cyprinids is evidently high. There are approaches and survey methods which could be used for more detailed assessments of Cyprinid abundance. Horizontal echo-sounding (with trawl or seine samples of the fish) is a promising method to survey large shallow areas and produce even speciesspecific biomass estimates for the most common species. This method is under development and testing at the moment. Commercial fishery on Cyprinids with trap nets could offer a possibility to use the log-book data (and regular sampling of the catch) to calculate catches per unit of effort (CPUEs) which could be reliable indexes of Cyprinid abundance. The results of these sampling methods would not be directly comparable with the existing gill net monitoring by HELCOM FISH. However, these methods could be used to get a finer assessment of Cyprinid populations in specific coastal areas, where effects of human pressures, e.g. eutrophication, on coastal fish communities are evident. Proper data on historical reference conditions does not exist. GES boundaries could be set as expert judgements, e.g % reduction in Cyprinid biomass in coastal regions where Cyprinids are at present very abundant. 5. Functional group or habitat type Cyprinids 6. Policy relevance Descriptor 1: Criteria 1.2 and 1.3 Population size, population condition Descriptor 1: Criterion 1.6 Habitat condition (Condition of the typical species and communities, Relative abundance and/or biomass) Descriptor 5: Criterion 5.3 Indirect effects of nutrient enrichment BSAP: Ecological objectives Natural distribution and occurrence of plants and animals 10. Spatial considerations Valid in archipelago areas and lagoons. Applicability of the indicator in other kinds of areas should be validated. 11. Temporal considerations Sampling should be made outside spawning season. Timing of sampling/survey is important as Cyprinids have some feeding and spawning migration (aggregation) patterns. Timing should be adjusted locally/regionally. 12. Current monitoring No current monitoring. The methods are under development. 13. Proposed or perceived target setting approach with a short justification. GES boundaries are not set yet. GES boundary can be set by expert judgment Ratio of opportunistic and perennial macroalgae 1. Working team: Benthic habitats and associated communities Author: Karin Furhaupter 2. Name of candidate indicator Biomass relation perennials/opportunists 3. Unit of the candidate indicator % (based on g DW m -2 values) 181

287 4. Description of proposed indicator The candidate core indicator for the Biomass relation of perennial and opportunist macrophytes is an indicator which is used by Germany, Denmark, Poland and Estonia in the WFD assessment. The indicator has not been further developed in the CORESET project and it has not been tested in the northern Baltic Sea, e.g. in Finland and Sweden. Moreover, there seem to be differences in the monitoring procedures among the countries using it. The indicator basically follows the biomass relation between K- and r-species. K-species are habitat-structuring, perennial species (usually key-species) with a persistent biomass for a certain time scale adapted to stable conditions. R-species are fast growing small, tiny species adapted to instable conditions and opportunistic responses to, e.g. nutrient availability. This is indicator for the relation of most important functional groups and for the habitat condition. 5. Functional group or habitat type Hydrolittoral and infralittoral hard substrata and/or sediments 6. Policy relevance Descriptor 1, criterion 1.6 Habitat condition Descriptor 5, criterion 5.2 Direct effect of nutrient enrichment Descriptor 6, criterion 6.2 Condition of benthic communities BSAP: Ecological objectives Natural distribution and occurrence of plants and animals (Eutrophication) and Thriving communities of plants and animals (Nature conservation) 7. Use of the indicator in previous assessments WFD assessment in Estonia and Germany (not in the hydrolittoral zone in Germany) and Poland (only for infralittoral sediments) 8. Link to anthropogenic pressures The indicator reflects a shift from perennial species (macroalgae and angiosperms) towards opportunistic species as a consequence of - increased nutrients causing rapid growth of opportunistic species, which overgrow and displace perennial vegetation direct impact - increased nutrients and increased amounts of organic matter and silt preventing the attachment of perennial species direct/indirect impact - increased physical disturbance (due to abrasion, extraction, dredging) favouring opportunistic species, which are adopted to instable conditions resulting in a displacement of perennials direct impact - changes in salinity and thermal regime favouring growth of opportunistic species resulting in a displacement of perennials direct impact 9. Pressure(s) that the indicator reflect Input of fertilizers, changes in siltation, Abrasion, Smothering, Changes in salinity regime, Changes in thermal regime. 10. Spatial considerations Baltic-wide but eventually with sub-basin specific and even site-specific GES boundaries 11. Temporal considerations Timing of measurement is important (adjusted to local conditions). Harmonization of the sampling method may be required (time of sampling, depth, species lists, variables measured, etc.). Frequency of monitoring not necessarily high as change in perennial macroalgae is slow. 12. Current monitoring Part of WFD monitoring in several member states (see 7.) and in several national monitoring programs. 13. Proposed or perceived target setting approach with a short justification. Difficult definition of reference values, as historical data are more or less only qualitatively 182

288 available. Use of current WFD values, expert judgement and ecological models. Modelling approaches should be used, based on abundance ratios along a water quality gradient. The GES boundaries will be site-specific. A fast reacting indicator due to high productivity of opportunists Cladophora length 1. Working team: Benthic habitats and associated communities Author: Ari Ruuskanen 2. Name of candidate indicator Length of Cladophora glomerata 3. Unit of the candidate indicator mm 4. Description of proposed indicator Several macroalgal species of the ephemeral life cycle are efficient in assimilating nutrients from the surrounding sea water. They use the nutrients in their growth, which can be measured in the length or biomass of the filaments. Especially nitrate has been found to be the limiting nutrient for the ephemeral macroalgae. The length/biomass of ephemeral macroalgae is an indicator for long term nutrient availability. Nutrient concentrations fluctuate widely in the sea water, which affects their reliability as an indicator. As the algae assimilate nutrients over the whole growing season, they indicate the total availability of nutrients over a longer time period. The use of this indicator relies on prior work for length/biomass nitrate correlation in laboratory conditions as well as in marine environment. Such experimental work is going on in Finland in the summer As a result, response curves for the use of the indicator will be published. The indicator will first apply to Cladophora glomerata, a dominant species all over the Baltic Sea, but other species can be included at later stages. There are scientific studies of the use of color as an indicator of the nitrate concentration in C. glomerata. The use of colour as a supporting or alternative parameter need to be studied. The indicator will not require costly monitoring as the data can be collected without diving from shores, navigational buoys and other man-made structures. The indicator will be developed also in the LIFE+ MARMONI project. 5. Functional group or habitat type Hydrolittoral and infralittoral hard substrata and/or sediments (large stones, other structures). 6. Policy relevance Descriptor 1, criterion 1.6 Habitat condition Descriptor 5, criterion 5.2 Direct effect of nutrient enrichment Descriptor 6, criterion 6.2 Condition of the benthic community BSAP: Ecological objectives Natural distribution and occurrence of plants and animals (Eutrophication) and Thriving communities of plants and animals (Nature conservation) 7. Use of the indicator in previous assessments Not 8. Link to anthropogenic pressures The indicator reflects the response of ephemeral (opportunistic) macroalgae to increased nitrate availability. Nutrients cause rapid growth of opportunistic species, which can also overgrow and displace perennial vegetation. 9. Pressure(s) that the indicator reflect Input of fertilizers (Waterborne discharges of nitrogen, atmospheric deposition of nitrogen; aquaculture) and ship traffic. 183

289 10. Spatial considerations Baltic-wide but eventually with region-specific GES boundary values 11. Temporal considerations Monitoring in the end of growing season. Timing of measurement is important. 12. Current monitoring Not, but could be included in the current field monitoring with low extra expenses. 13. Proposed or perceived target setting approach with a short justification. Does not require historical reference conditions. GES boundary will be set on the basis of the response of the alga length/biomass to the nitrate concentrations. Thus, the target for nitrate concentration in water determines the boundary between GES and sub-ges. This target has been already established for coastal water types under the EU WFD and for open sea areas in HELCOM EUTRO PRO. Classification requires the use of a response curve, which relates the length or biomass measurement to nitrate levels (and status classes) and wave action of study site. GES boundaries (response curves) require regional validation (at least on main basin level) Size distribution of benthic long-lived species 1. Working team: Benthic habitats and associated communities Author: Karin Furhaupter 2. Name of candidate indicator Size distribution of benthic long-lived species (e.g. Cerastoderma, Macoma or Saduria) 3. Unit of the candidate indicator Ind./size class 4. Description of proposed indicator The population structure (abundance per size class) of specific, long-lived species like bivalves or Saduria or decapod crustaceans, which are key-species of different communities or target species of other ecosystem components (e.g. birds). The indicator describes the condition (functionality) and abundance of the biological component. Population structure of food web and community key species is an indicator for the whole habitat condition. 5. Functional group or habitat type Infralittoral, circalittoral infauna communities (eventually also sediments below the halocline) 6. Policy relevance Descriptor 1, criterion 1.6 Habitat condition Descriptor 4, criterion 4.3 Abundance/distribution of key trophic groups and species Descriptor 6, criterion 6.2 Condition of the benthic communities BSAP: Viable populations of species 7. Use of the indicator in previous assessments Not. 8. Link to anthropogenic pressures Population structure of bivalves is affected by changes in the food web due to selective extraction of target species, including incidental non-target species direct/indirect impact Population structure of bivalves is affected by eutrophication. The proportion of small individuals increases under strong predation by cyprinid fish, which have increased in 184

290 abundance due to eutrophication of Baltic Sea. Population structure of bivalves is affected by physical damage/disturbance as adult species got lost and recruitment success is reduced Population structure of bivalves is affected by changes in hydrography as reproduction and recruitment is dependent of specific T and S values 9. Pressure(s) that the indicator reflect Selective extraction of species, Input of fertilizers, Changes in siltation, Abrasion, Smothering, Changes in salinity regime, Changes in thermal regime 10. Spatial considerations Cerastoderma glaucum Baltic-wide but eventually with region-specific reference values; C. edule only in subregions (Western Baltic) Mya arenaria: from Kattegat to Bottnian Sea (to mean bottom salinity of 6 psu) Macoma balthica: from Kattegat to Nordic Baltic Proper/Gulf of Finnland (to mean bottom salinity of 8 psu) Saduria: from Kattegat to Bothnian Sea (to mean bottom salinity of 6 psu) 11. Temporal considerations Frequency: every 2 years sufficient due to slow recruitment Harmonization of the sampling method may be required. 12. Current monitoring Only monitored in specific scientific surveys? Or: can the national benthos monitoring be used to derive the size distribution? 13. Proposed or perceived target setting approach with a short justification. GES boundaries should be set on the basis of known size distribution in low-impact conditions (reference sites, reference times) Blue mussel cover 1. Working team: Benthic habitats and associated communities Author: Karin Furhaupter 2. Name of candidate indicator Blue mussel cover 3. Unit of the candidate indicator % cover 4. Description of proposed indicator Coverage of blue mussels on hard and soft bottom along the depth gradient. The indicator describes the abundance and extent of the biological component/community with blue mussels as the habitat forming key-species. 5. Functional group or habitat type Infralittoral, circalittoral hard substrata Infralittoral, circalittoral sediments 6. Policy relevance Descriptor 1, criterion 1.5 Habitat extent Descriptor 6, criterion 6.1 Habitat size of biogenic substrata BSAP: Nature conservation and biodiversity Thriving and balanced communities of plants and animals and Natural distribution and occurrence of plants and animals 7. Use of the indicator in previous assessments 8. Link to anthropogenic pressures Introduction of synthetic compounds (due to oils spill, ship accidents) causes a habitat loss 185

291 direct impact Sealing (due to harbours, coastal defence structures, bridges and coastal dams, wind farms) causes a loss of habitat area (but blue mussels accept artificial solid substrates quite well!) Selective extraction (due to dredging and sand/gravel/boulder extraction) causes habitat loss direct impact Physical damage (due to abrasion, smothering or change in siltation) causes habitat loss - direct impact 9. Pressure(s) that the indicator reflect Introduction of synthetic compounds, Sealing, Smothering, Abrasion, Selective extraction 10. Spatial considerations from Kattegat to Bothnian Sea (to mean bottom salinity of 6 psu) 11. Temporal considerations The cover should be measured at the time of yearly maximum (if applicable). Regular monitoring, but not necessarily annually. 12. Current monitoring Currently not monitored, but datasets are available. 13. Proposed or perceived target setting approach with a short justification. Difficult definition of reference values, as historical data are more or less only partly available. GES boundary could be based on long-term means and expert judgement. Also trend-based GES boundary could be used. High natural variability especially at shallow sites due to varying reproduction success and high predator pressure (ducks, sea stars) Cumulative impact on benthic habitats 1. Working team: Authors: Manuel Meidinger and Samuli Korpinen Acknowledged persons: David Connor, Maria Laamanen, Hans Nilsson and Johnny Reker 2. Name of candidate indicator: Cumulative impact on benthic habitats 3. Unit of the candidate indicator Percentage 4. Description of proposed indicator The indicator measures the proportion of a benthic habitat being significantly impacted by a cumulative impact of anthropogenic disturbances. The indicator gives a result for each habitat type. The habitat data is based on the recent benthic habitat model of the EUSeaMap project and data sets on anthropogenic impacts are from the HELCOM Initial Holistic Assessment. The indicator relies on reliable habitat and pressure data, but also on - estimates of the weights of each pressure in the cumulative impact score, - definition of a significant cumulative impact, and - acceptable proportion of a habitat type being significantly disturbed. 5. Functional group or habitat type: All predominant benthic habitats, defined by depth zones and substrate type 6. Policy relevance MSFD Descriptor 1 (Biodiversity), Criterion 1.6 Habitat condition MSFD Descriptor 6 (Seafloor integrity), Criterion 6.1 Extent of habitats being impacted. BSAP Ecological Objective: Natural marine landscapes. 186

292 7. Use of the indicator in previous assessments None 8. Link to anthropogenic pressures Directly impacted by physical disturbance pressures on the seabed. 9. Pressure(s) that the indicator reflect Directly impacted by bottom trawling, dredging, extraction of sand and gravel (etc), disposal of dredged material (etc), shipping in shallow water, installation of wind farms, piers, platforms, bridges, dams, cables and pipelines, coastal erosion defence structures and replenishment of beaches. Also large salinity and temperature changes caused by waste water treatment plants and nuclear power plants (and other industry) disturb the seabed habitats. 10. Spatial considerations The index is Baltic wide, but can be calculated to smaller areas, e.g. sub-basins. The tool has no spatial limits, but the limitations arise from the data reliability. 11. Temporal considerations Human activities being slowly changing in larger spatial scales, the indicator can be updated every three years. 12. Current monitoring The data on pressures is compiled from different sources. 13. Proposed or perceived target setting approach with a short justification. Under the EU Habitats Directive a threshold of 25% is being used to classify a habitat type to Bad conservation status. Using this threshold as a basis, a threshold of 15% or less is being proposed for this indicator. Policy relevance of the indicator The HELCOM Baltic Sea Action Plan (BSAP) and the EU Marine Strategy Framework Directive (MSFD) both require an assessment of the state of the habitats and the intensity and distribution of anthropogenic pressures impacting them. Particularly, the MSFD calls for an improved understanding and management of pressures and impacts arising from human activities and ultimately aims at reducing them. This should lead to improved state of the ecosystem and hence enhanced resilience of marine ecosystems to counteract natural and human induced changes whilst ensuring the sustainable use of ecosystem goods and services. The MSFD requires Member States to put in place measures to achieve or maintain Good Environmental Status (GES) in the marine environment by 2020 at the latest. To reach this overall goal Member States must develop and implement marine strategies. The marine strategies must include an assessment of pressures and impacts and develop environmental targets and associated indicators. These environmental targets and associated indicators should help to guide the progress towards achieving and maintaining GES. The BSAP ecological objectives, relevant for benthic habitats, state that the distribution and extent of marine landscapes must be natural and species communities must be thriving and balanced. Although the BSAP does not mention habitats or biotopes separately, the landscape and community-level objectives together set the standard for GES of marine habitats. In the MSFD, the GES of the benthic habitats is particularly assessed with the qualitative descriptor 6 Sea-floor integrity is at a level that ensures that the structure and functions of the ecosystems are safeguarded and benthic ecosystems, in particular, are not adversely affected. The objective of the descriptor is that human pressures on the seabed do not 187

293 hinder the ecosystem components to retain their natural diversity, productivity and dynamic ecological processes, having regard to ecosystem resilience. The descriptor and particularly its criterion 6.1 require an assessment of the extent of significant impacts on benthic habitats. A proposal for an approach to assess anthropogenic impacts on benthic habitats Selection of data The benthic habitats used in this indicator were based on the modeling work of the EUSeaMap project, which modeled over 200 biotopes (EUNIS level 4) for the Baltic Sea, based on substrate type, depth zone, salinity and bottom energy. Because the use of over 200 biotopes is cumbersome, the first testing of the indicator was done with 18 biotopes describing substrate type and depth zone (and combining the other parameters). More detailed habitat types can also be used, for example, in national or sub-regional assessments. The 18 benthic biotopes are described below. Infralittoral Circalittoral Deep sea mud & sandy mud mud & sandy mud mud & sandy mud sand & sandy mud sand & sandy mud sand & sandy mud coarse sediment coarse sediment coarse sediment mixed sediment mixed sediment mixed sediment till till till bedrock & boulders bedrock & boulders bedrock & boulders The project selected twelve physical pressures, which pose direct disturbance on seabed. The selected pressures were shipping in shallow water (<15 m), dredging and sand extraction, disposal of dredged matter, waste water treatment plants, bridges and dams, oil rigs, coastal defense structures, coastal nuclear power plants, cables and pipelines, wind farms, bathing sites and bottom-trawling fishery. They were selected from the HELCOM Data and Map Service ( where all the pressure data is visible and downloadable. The pressures are also visible in the HELCOM background report for the Baltic Sea Impact Index 13. The coarseness of some of the pressure data sets was estimated to cause bias in the outcome of the indicator, but they were included in order to finalize the testing of the approach. Most of the anthropogenic pressures had quantitative intensities based on the underlying human activities; some used areal coverage of the activity or amount of material being moved, while some were limited to the presence-absence scale. As there are no or very few data sets available where the actual pressure has been measured, the intensities were proxies for pressures. More reliable proxies or more direct measurements are needed in future assessments. The intensity scales were log-transformed and normalized to 0-1 scale to have similar scales for all the twelve pressures. Estimating impacts Each pressure has individual impacts on the different habitats. These impacts are difficult to objectively measure (at least for all pressures) and therefore expert judgment was used to estimate the magnitude of the impact. These weighting scores are presented in the

294 background report to the HELCOM Baltic Sea Impact Index 13. The normalized pressures were multiplied by the weighting scores and then summed up for every benthic habitat type. This cumulative impact was used as a measure for the total human impact on each of the habitats. Cumulative impacts were calculated for 276 m x 276 m squares over the entire Baltic Sea region. The weighting scores naturally limit the number of habitats being included in the assessment. For every new habitat type, twelve more weighting scores must be developed. Benchmarking of individual or total impacts to unacceptable or acceptable levels is a task that remains to be done in the Baltic Sea. Until that has been accomplished, the HELCOM CORESET project used the mean cumulative impact of the entire Baltic Sea as the level to represent significant impacts. In practice, the mean impact means that there are either several low impacts present in the site or one heavy impact. Such an approximation was seen rough but still applicable as a first step towards more detailed assessments of cumulative human impacts. Classification of Impacts The candidate indicator uses four different impact categories (not impacted, low impact, medium impact and high impact) to describe the cumulative impacts using mean and standard deviation to define class boundaries. The border between low and medium was defined as significant impact. Technical details of the data handling and the GIS procedures are given in the section Technical data below (some information still missing). Category Cumulative impact score Not impacted 0 Low impact Medium impact High impact 0 < Mean Mean Mean + standard deviation Mean + stdev max. cumulative impact score Approaches to set the GES boundary for the condition of benthic habitats The HELCOM core indicators for BSAP and MSFD assessments have quantitative targets which define the boundary between GES and sub-ges. The MSFD GES criterion 6.1 of the EC Decision 477/2010/EU calls for an indicator to measure Extent of the seabed significantly affected by human activities for the different substrate types. This means that two thresholds must be defined: - the level of significant impact (a precondition for the next definition) and - the level for GES, i.e. the proportion of benthic habitats which is not significantly affected. The first definition requires a thorough investigation of the impacts of different pressures on benthic habitats (which depend on the habitat type). If aiming at perfection, one should also estimate the significance of synergistic impacts. At present, this information is not available and the CORESET project suggests using mean cumulative impact to denote significant impact (see also text above). The second definition may be hard to set by ecological means. All anthropogenic impacts degrade the habitat quality and it may be difficult to find sudden drops in the habitat quality along the pressure-state response curves. Another approach would be so-called assessment of the ecological coherence which measures the size, number and 189

295 connectivity of areas and which has been previously used for assessments of MPA networks (see HELCOM and publications of the EU BALANCE project 15 ). A practical solution is to select a basis which is also used in the EU Habitats Directive. Under the directive a habitat which has 25% of area significantly impacted is classified to Unfavourable - Bad status. In this indicator we can assume that 15% of the habitat area is allowed to be significantly impacted and still be in good environmental status, allowing some human use of the marine environment. Technical data Metadata This is an indicator to estimate the cumulative impact of anthropogenic pressures on benthic habitats. It measures the amount of each habitat type being significantly impacted by cumulative impacts. The indicator is targeted to be used in the HELCOM biodiversity assessments and to assess the EU MSFD GES criteria 1.6 and 6.1. Description of data: Metadata and the maps of each of the pressure data layers are available in the HELCOM Data and Map Service ( The benthic habitats are from the EUSeaMap project: Data source: EUSeaMap (raster, cell size/resolution 276m) Relevant anthropogenic (physical) pressure data from prior projects (HELCOM HOLAS) were selected: Dredging, Dumping, Windfarms, Oil rigs, cables and pipelines, coastal defense structures, bridges and dams, bathing sites, coastal shipping <15m water depth, nuclear power plants, bottom trawling, municipal waste water treatment plants MWWTPs Geographical coverage: All regions of the Baltic Sea, whereas the data quality varies among data regions and data layers. Temporal coverage: The pressure data is from period , biased towards Exact years are available in pressure metadata. Methodology and frequency of data collection: See HELCOM Data and Map Service. Methodology of data analyses: The main tool used for data preparation and analyses are version ArcGIS with Spatial Analyst extension. In case the original pressure layers had point or polyline feature characteristics they were converted to polygon shapefiles using an individual buffer for each pressure layer: particularly 190

296 o shipping in shallow water (<15 m) average monthly shipping density in 2008 o dredging and sand extraction, disposal of dredged matter both with buffers of 2000m o waste water treatment plants with buffer of 100m o bridges and dams with buffer of 100m o coastal defense structures with buffer of 100m o coastal nuclear power plants with buffer of 1000m o cables and pipelines with buffer of 50m o wind farms and oil rigs original polygon shapefile o bathing sites with buffer of 500m o bottom-trawling fishery ICES rectangles Then the individual pressure layers were converted to raster format with a cell size of 276m. Each individual pressure layer was log-transformed, normalized to 0-1 scale, multiplied by the corresponding expert judgment weighting score for each benthic habitat and summed up. The weighting scores are from the HELCOM background report 13. Six cumulative impact score rasters have been produced for each biozone (infralittoral, circalittoral, deep sea) and were then clipped with the corresponding habitat shapefile and sub-basin shapefile. Weaknesses of the indicator: - coarseness of pressure data sets - reliability of the habitat model - artefacts in the map - weighting of pressures - benchmarking the impacts Examples of the use of the indicator The indicator was tested in the HELCOM Secretariat by using 12 pressure data layers from the HELCOM HOLAS project, 18 benthic habitats from the EUSeaMap project and tentative GES boundary of 15% of acceptable proportion being impacted. Figure 1 shows the cumulative impacts on six infralittoral benthic habitats on a continuous scale. In Figure 2, the cumulative impacts are divided to four status classes (not impacted, low, intermediate and high) by using the mean cumulative impact as the boundary between low and intermediate and standard deviations to define the other two boundaries. Figure 3 shows the same result as proportions of the total habitat area. 191

297 Figure 1. Map showing the cumulative anthropogenic impacts on six selected infralittoral habitats on a Baltic Sea wide scale. 192

298 Figure 2. Extent of infralittoral habitats with classified impact categories on a Baltic Sea wide scale. Figure 3. Percentage wise proportion of impact classes for infralittoral habitats on a Baltic Sea wide scale Biomass of copepods 1. Working team: Zooplankton (ZEN) Authors: Elena Gorokhova and Maiju Lehtiniemi Acknowledged persons: Lutz Postel 2. Name of candidate indicator: Biomass of copepods 3. Unit of the candidate indicator mg/m 3 4. Description of proposed indicator Copepod biomass is calculated using abundance and individual weights. Alternatively (or in addition), contribution of copepod biomass to total mesozooplankton biomass may be used. The indicator reflects composition of zooplankton community and food availability for zooplanktivorous fish. This is a state indicator. 5. Functional group or habitat type: Zooplankton/plankton 6. Policy relevance 193

299 MSFD Descriptor 1 (Biodiversity), Criteria Relative abundance and or biomass. BSAP Ecological Objective: Viable populalation of species, Target: By 2021 all elements of the marine food webs, to the extent that they are known, occur at natural and robust abundance and diversity. 7. Use of the indicator in previous assessments Used as preliminary indicators in offshore BEAT cases 8. Link to anthropogenic pressures Directly impacted by climatic changes, altered predation, introduction of synthetic compounds and invasive species (via predation). Indirectly impacted by eutrophication. 9. Pressure(s) that the indicator reflect Negative impacts are expected with increased predation pressure and changes in food web structure. Both positive and negative responses can result from changes in thermal regime and salinity. 10. Spatial considerations The index is strictly area-specific, possibly limited to the open sea areas in the Baltic proper, western Gulf of Finland and southern Baltic. Consistent sampling stations and methods, species identification and biomass calculation methods should be used for estimating and interpreting trends. 11. Temporal considerations Averaged over growth season. In areas where seasonal monitoring data are available, the assessment could be done on a seasonal basis. 12. Current monitoring National monitoring programmes, HELCOM (reported variable) 13. Proposed or perceived target setting approach with a short justification. The applicability and targets should be tested and validated for specific areas. The long term data or data from areas not affected by changes in fish community structure and abundance must be provided by national labs to serve for target setting. A discussion regarding development of common target setting approach and analogous indices for areas where copepods are not dominant species is needed Biomass of microphageous mesozooplankton 1. Working team: Zooplankton (ZEN) Author: Elena Gorokhova and Lutz Postel Acknowledged persons: Maiju Lehtiniemi 1. Working team: Zooplankton (ZEN) 2. Name of candidate indicator: Biomass of microphagous mesozooplankton 3. Unit of the candidate indicator mg/m 3 4. Description of proposed indicator Biomass is calculated using abundance of microphagous feeders present in mesozooplankton community and their individual weights. Alternatively (or in addition), contribution of microphagous biomass to total mesozooplankton biomass can be used. The indicator reflects composition of zooplankton community and availability of small-sized phytoplankton and bacterioplankton, the increase in the latter is commonly observed with increasing eutrophication. It also negatively related to food availability for zooplanktivorous 194

300 fish. 5. Functional group or habitat type: Zooplankton/plankton 6. Policy relevance MSFD Descriptor 1 (Biodiversity), Criteria Relative abundance and or biomass. BSAP Ecological Objective: Viable population of species, Target: By 2021 all elements of the marine food webs, to the extent that they are known, occur at natural and robust abundance and diversity. 7. Use of the indicator in previous assessments None 8. Link to anthropogenic pressures Directly impacted by (1) fisheries (through predation), (2) changes in thermal regime and salinity, (3) introduction of synthetic compounds and (4) invasive species (via predation) Indirectly impacted by (1) eutrophication (through changes in food abundance and size spectra), and (2) commercial fisheries (through changes in pelagic food webs), 9. Pressure(s) that the indicator reflect Eutrophication increases abundance and productivity of small-sized phytoplankton and bacterioplankton, which stimulates production and standing stocks of microphagous species. In addition, increased biomass of microphagous species implies decreased food quality and availability for fish. 10. Spatial considerations The index is strictly area-specific, possibly limited to the areas generally dominated by crustacean zooplankton, such as open sea areas in the Baltic proper, western Gulf of Finland and southern Baltic. 11. Temporal considerations Averaged over growth season. In areas where seasonal monitoring data are available, the assessment could be done on a seasonal basis. 12. Current monitoring National monitoring programmes, HELCOM (reported variable). 13. Proposed or perceived target setting approach with a short justification. The applicability and targets should be tested and validated for specific areas. The long term data or data from relatively pristine areas must be provided by national labs to serve for target setting. A discussion regarding development of common target setting approach is needed Zooplankton species diversity 1. Working team: Zooplankton (ZEN) Author: Elena Gorokhova Acknowledged persons: Maiju Lehtiniemi, Lutz Postel 1. Working team: Zooplankton (ZEN) 2. Name of candidate indicator: Zooplankton species diversity 3. Unit of the candidate indicator unitless 4. Description of proposed indicator 195

301 Using long term species lists for different subregions of the Baltic Sea, area-specific species diversity index is calculated as a ratio between the number of species actually observed in the area and species number registered in the area. The indicator reflects changes in taxonomic diversity in the area and therefore could be used as a general indicator of zooplankton species diversity. Potentially could be also used for indication of bioinvasions, both in planktonic and benthic communities if meroplankton is included in zooplankton community analysis. 5. Functional group or habitat type: Zooplankton/plankton 6. Policy relevance MSFD Descriptor 1 (Biodiversity), Criterion 1.6 Habitat condition BSAP Ecological Objective: Viable population of species, Target: By 2021 all elements of the marine food webs, to the extent that they are known, occur at natural and robust abundance and diversity. 7. Use of the indicator in previous assessments None 8. Link to anthropogenic pressures Directly impacted by: climatic changes, introduction of synthetic compounds and invasive species. 9. Pressure(s) that the indicator reflect Directly impacted by: introduction of invasive species, both positively by adding new species and negatively by eliminating native species via predation/competition (very rare cases). Other pressures are (1) changes in thermal regime, ph and salinity (can cause both expansion of species from neighbouring areas and disappearance of existing species from the area, and (2) introduction of synthetic compounds, with possible local effects in areas situated close to municipal and industrial effluents. 10. Spatial considerations The index is strictly area-specific. Consistent sampling stations and methods, and species identification should be used for estimating and interpreting trends. Annual assessment. In areas where seasonal monitoring data are available, the assessment could be done on a seasonal basis. 12. Current monitoring National monitoring programmes, HELCOM 13. Proposed or perceived target setting approach with a short justification. The applicability should be tested and validated for specific areas. The GES boundary is 1, i.e. no change in biodiversity. Consequently, ratios <1 correspond to decreased diversity, =1 is no change, >1 means either invasion or colonization from neighboring areas. The long term species list must be provided by national labs Mean zooplankton size The indicator was meant to follow long-term changes in the zooplankton size as a response to changes in food web (predation pressure) and eutrophication (hypoxia, altered phytoplankton species composition). Larger zooplankton size indicates a better state of the environment. No description of the indicator is available, but see the indicator for copepod biomass for some discussion (below). 196

302 4.21. Zooplankton-phytoplankton biomass ratio The indicator was meant to follow long-term changes in the biomass ratio of zooplankton and phytoplankton as a response to changes in food web (predation pressure) and eutrophication (hypoxia, nutrient availability). Bias to zooplankton indicates stronger topdown control and hence a better functioning food web (piscivorous fish controlling planktivorous fish, releasing zooplankton from high predation. No description of the indicator is available but see the indicator for copepod biomass for some discussion (below). Description and testing of zooplankton indicators: Introduction In aquatic ecosystems, changes in species composition and abundance of small, rapidly reproducing organisms, such as plankton, have been considered among the earliest and sensitive ecosystem responses to anthropogenic stress (Schindler 1987). Zooplankton are integral to aquatic productivity, serving as primary consumers of nutrient-driven primary producers, and as prey for fish. Despite their potential as indicators of environmental changes and their fundamental role in the energy transfer and nutrient cycling in aquatic ecosystems, zooplankton assemblages have not been widely used as indicators of ecosystem condition (Stemberger and Lazorchak 1994), and zooplankton is not included as a relevant quality element for the assessment of ecological status within Water Framework Directive. Nevertheless, changes in primary productivity and physical conditions due to eutrophication and warming and the consequent reorganization of zooplankton communities have been documented worldwide, albeit, more often in freshwater than in marine systems. In the Baltic Sea, alterations in fish stocks and regime shifts received a particular attention as driving forces behind changes in zooplankton (Casini et al. 2009). Here, we consider a possibility of using zooplankton as indicators for eutrophication and fish feeding conditions. With respect to eutrophication, it has been suggested that with increasing nutrient enrichment of water bodies, total zooplankton biomass increases (Hanson and Peters 1984), mean size decreases (Pace 1986), and relative abundance of calanoids generally decrease, while small-bodied cyclopoids, cladocerans, rotifers, copepod nauplii, and ciliates increase (Brook 1969; Pace and Orcutt 1981). With respect to fish feeding conditions, the following properties of zooplankton assemblages are usually associated with good food availability: high absolute or relative abundance of large-bodied copepods and low contribution of small zooplankters. Description of proposed indicators Copepod biomass (CB; mg/m 3 ) zooplankton-as-food indicator; calculated using abundance and individual weights. Alternatively (or in addition), contribution of copepod biomass to total mesozooplankton biomass (CB%) may be used. This is a state indicator; reflects composition of zooplankton community and food availability for zooplanktivorous fish. In the Baltic Sea, copepods contribute substantially to the diet on zooplanktivorous fish, such as sprat and young herring, and fish body condition and weight-at-age (WAA) have been reported to correlate positively to abundance/biomass of copepods (Cardinale et al. 2002, Ronkkonen et al. 2004). Copepods included here are mostly herbivores, therefore, this indicator would be indirectly impacted by eutrophication (via changes in primary productivity and phytoplankton composition), whereas direct impacts are expected from climatic changes, predation, introduction of synthetic compounds (at point sources) and invasive species (via predation). Both positive and negative responses can result from changes in thermal regime and salinity. Microphagous mesozooplankton biomass (MMB; mg/m 3 ) eutrophication indicator; calculated using abundance of microphagous feeders present in mesozooplankton 197

303 community and their individual weights. Alternatively (or in addition), contribution of microphagous biomass to total mesozooplankton biomass (MMB%) can be used. The indicator reflects composition of zooplankton community and availability of small-sized phytoplankton and bacterioplankton. The increase in the latter is commonly observed with increasing eutrophication that favors growth of smallest primary producers. This provides a high food supply for grazers capable of efficient filtration of small particles; these grazers are usually also small. MMB and MMB% are also negatively related to food availability for zooplanktivorous fish as increased proportion of microphagous species, at least to some extent, implies a reciprocal trend in large copepods that have low efficiency for filtration of small algae. This indicator is directly impacted by eutrophication (through changes in food abundance and size spectra), changes in thermal regime and salinity, introduction of synthetic compounds (at point sources) and invasive species (via predation). Impacted by commercial fisheries, both indirectly (through changes in pelagic food webs) and directly (via predation by fish larvae). Policy relevance for zooplankton indicators MSFD Descriptor 1 (Biodiversity): - Criterion 1.2 Population size; Indicator Population abundance and/or biomass, as appropriate; - Criterion 1.6 Habitat condition; Indicator Relative abundance and/or biomass; - Criterion 1.7 Ecosystem structure; Indicator Composition and relative proportions of ecosystem components (habitats and species) MSFD Descriptor 4 (Food webs): - Criterion 4.3 Abundance/distribution of key trophic groups/species; Indicator Abundance trends of functionally important selected groups/species; BSAP Ecological Objective: Viable population of species. Methods used to test the indicators See provisional guidelines for a specific description of zooplankton indicator testing procedure. The approach is based on examining zooplankton time series in relation to: the time series on zooplanktivorous fish growth (WAA, or condition) and fish stocks from relevant ICES subdivision(s) to identify time periods when fish growth and fish stocks were relatively high (e.g., Rahikainen and Stephenson 2004) when setting GES boundary for CB (CB%); the existing GES values for water transparency or chlorophyll values (e.g., figs and 2.20 in HELCOM, 2009) when setting GES boundary for MMB (MMB%). In the example below, the testing was done using coastal zooplankton data from the northern Baltic proper (ICES subdivision 29); the data are from Swedish national monitoring conducted by Stockholm University collected and analyzed according to HELCOM guidelines (HELCOM 1988). Approach for defining GES Data analysis and definition of GES boundary To establish baselines and acceptable variability for specific indicators, trends and reference periods were evaluated using indicator Control Chart (Manley 2001; Guthrie et al. 2005). For CB% and MMB%, mean values and 95% confidence intervals (CI) were used. 198

304 As these variables are non-normally distributed, standard deviation (SD) was calculated using transformed values and then back-transformed to arrive to the upper and lower 95% limits of CI. In the context of GES for CB (CB%), upper limit is not relevant, whereas lower limit is not relevant for MMB (MMB%). Thus, GES boundary for CB (CB%) is the lower 95% CI limit, and for MMB (MMB%), it is the upper 95% CI limit. These values are set as threshold values which mark the boundary between acceptable and unacceptable conditions, i.e. CB (CB%) should not decline below its GES boundary, whereas MMB (MMB%) should not increase above its GES boundary. GES boundary for CB% For the data set analyzed, the most easy interpretable results were obtained with CB%. The GES boundary was estimated to be 73% based on the reference period , when herring and sprat stocks were relatively stable and had high WAA and body condition. This reference period was selected based on the data presented by Rahikainen & Stephenson (2004) and Casini et al. (2006). See Annex 5a for details. Fig. 1. Long-term changes in copepod contribution to the total mesozooplankton biomass (CB%) in the Askö area, northern Baltic proper ( ; average summer values, n=6). According to the trend observed, CB% >73% indicate good feeding conditions for zooplanktivorous fish (green area). CB% reference period CB% mean GES boundary: lower 95% CI Year GES boundary for MMB% For the data set analyzed, the most easy interpretable results were obtained with MMB%. The GES boundary estimated was 22% based on the reference period , when water transparency complied with GES levels (various HELCOM documents; this period might need refining). Fig. 2. Long-term changes in microphagous zooplankton contribution to the total mesozooplankton biomass (MMB%) in the Askö area, northern Baltic proper ( ; average summer values, n=6). According to the trend observed, MMB% <22% correspond to water quality in GES (green area). MMB% reference period MMB% Year GES boundary: upper 95% CI mean Notes for the GES boundary The copepod biomass is an indicator of fish feeding conditions and, accordingly, the reference period is selected on the basis of the fish growth status. As we know, moderate eutrophication is actually beneficial for fish nutrition, and therefore, it is not surprising that highest growth of zooplanktivorous fish coincides with some (but not the highest!) eutrophication (expressed as Chl a or Secchi depth). It would be against the theoretical expectations to observe the best feeding conditions in an oligotrophic system. The example that is used in this example is for a relatively pristine area (Askö) and in ties the Secchi and Chl values were in a better status than in the next 20 years. Therefore, 199

305 the highest copepod biomass did not coincide with the heavy eutrophication. One has to remember that all reference periods should be area-specific. Existing monitoring data Zooplankton data required for this analysis are collected on a regular basis within national and HELCOM monitoring programs. Laboratories that follow HELCOM methodology for sampling and sample analysis, should possess all data necessary for indicator development and use. Depending on the sampling frequency, a specific period for zooplankton stocks should be considered and used consistently; this period may vary between different areas/countries/laboratories, because sampling frequency is not uniform. Unfortunately, in some areas, sampling coverage is low and not all sea areas are equally well represented (see also Weaknesses and Concerns). Data interpretation A dialogue with experts (and data holders) responsible for establishing GES values for eutrophication and fish stocks would greatly facilitate selection of the reference periods for zooplankton indicators and estimating GES boundaries. Although the empirical relationships between zooplankton abundance and eutrophication status are common in scientific literature, the underlying mechanisms are not well understood. For zooplankton indices to have relevance to management, it is necessary to postulate and test (through research and/or data analysis) hypotheses that explain the response of zooplankton to water quality. Similarly, it is necessary to identify fish species individually or feeding groups for which the zooplankton-as-food indicator is relevant. It is also necessary to include other aspects of habitat quality, particularly for coastal fish, and the zooplankton-as-food indicator can serve as one element in a more comprehensive index of habitat condition. Zooplankton communities include herbivores, predators and omnivores, i.e. organisms with different trophic roles in the food web, but from an ecological viewpoint, all of them are intermediate players, i.e., subject to bottom-up pressures as well as top-down demand. Therefore, zooplankton information is most useful within the framework of a broader, multitrophic-level monitoring providing indicators of ecosystem functioning (i.e., MSFD Descriptor 4). Weaknesses and Concerns Presently, we do not have a good overview on south-north and east-west variability in zooplankton community structure, population stocks and seasonal fluctuations in the Baltic Sea. This complicates development of indicators applicable in different areas and may further hamper between-area comparisons; Due to difference in zooplankton compositions between the Baltic Sea areas, some modifications may be required for taxa composition in each specific indicator; Data are generally noisy, owing to multiple factors affecting zooplankton growth and mortality; Different sampling/analysis methods might have been used in different labs in previous years resulting in either over- or underestimations of specific zooplankton groups/species. If 200

306 these methodological difference are not corrected for, the long-term data might be of little use; Poor spatial coverage, and, in some areas, poor frequency of sampling; Biomass calculation is not based on actual measurements of individual weight/size, but a fixed value, whereas seasonal and spatial variability of individual body size is well recognized in all zooplankton groups; Strong confounding effects of salinity and temperature that may obscure relationships between the indicators and relevant pressures. Provisional guidelines for testing zooplankton-based indicators proposed within CORESET Biodiversity group The indicators proposed were: Zooplankton Species Diversity (ZSD); Copepod Biomass (CB, CB%); Microphagous mesozooplankton biomass (MMB, MMB%); Additional indicators that appeared as promising during testing using datasets from a coastal area in the northern Baltic proper and discussions at Coreset Biodiversity meeting (15-17/6, Riga) were: Mean zooplankter size (MeanSize) calculated as a ratio between total mesozooplankton biomass and abundance. Note: only species/groups that are included consistently in zooplankton assessment should be used. The rationale is that as eutrophication favors small-bodied forms that are more competitive in feeding on nano- and picoplankton. Zooplankton/phytoplankton ratio; this is a food web indicator of trophic transfer efficiency. The rationale is that higher grazing efficiency implies less losses in the food webs, less energy and nutrients going via microbial loops, and, consequently, more energy transferred to the higher trophic levels, i.e. fish. Again, only species/groups that are included consistently in phyto- and zooplankton assessment should be used. To start on the evaluating procedure, obtain the following background information: Step 1: Relevant for your area (=your ICES subdivision) time series on zooplanktivorous fish growth (weight-at-age, commonly abbreviated as WAA, or condition) and fish stocks. This is needed to identify a time period when fish growth was high and fish stocks were relatively high (for example, Rahikainen M, Stephenson RL Consequences of growth variation in northern Baltic herring for assessment and management. ICES Journal of Marine Science 61: , see pdf attached). Consult your fish-colleagues for data location and interpretation if necessary. The time period should span at least 5-7 consecutive years; 201

307 Step 2: Relevant for your area time series for water transparency or chlorophyll values (see, for example, figs and 2.20 in HELCOM, Eutrophication in the Baltic Sea An integrated thematic assessment of the effects of nutrient enrichment and eutrophication in the Baltic Sea region. Balt. Sea Environ. Proc. No. 115B, available at for download; and/or other relevant data or assessments). This is needed to identify a reference period when eutrophication levels were below or at currently accepted targets. Consult your colleagues involved in Water Framework Directive activities for data location and interpretation if necessary. The time period should span at least 5-7 consecutive years. Step 3: Prepare a list of species/groups routinely identified in zooplankton samples (if unavoidable, use groups that are pooled in a consistent manner) to calculate ZSD values as a ratio between the number of species observed in a given year (or season if the assessment is done on a seasonal basis) and the total number of species ever observed in routine zooplankton monitoring in this area. This is a proxy for species richness. Step 4: Prepare available time series or data published in various reports for each of the main indicators (ZSD, CB, CB%, MMB and MMB%) and additional indicators (MeanSize, Zooplankton/Phytoplankton ratio): a. Pay particular attention to the data availability for the periods of the high fish growth conditions and acceptable eutrophication levels indentified from the time series for these background data; b. Note that both absolute biomass (mg/m 3 ; CB and MMB) and relative (proportion or percentage of the indicator group in the total mesozooplankton biomass; CB% and MMB%) will be needed; c. When calculating CB and CB%, include all copepodites stages of copepods; d. When calculating MMB and MMB%, include only holoplankton (i.e., no benthic larvae); most relevant being the following species/groups: i. rotifers, ii. appendicularians, iii. small (<20 mm) ctenophores, iv. small cladocerans feeding mostly on nanoplankton (e.g., Bosmina maritima, Penilia avirostris), v. pelagic harpacticoids, vi. Nauplii of all copepod species and tintinnids can be included if assessment of their abundance follows the same methodological guidelines for the entire dataset. Step 5: To establish baselines and acceptable variability for specific indicators, evaluate trends using indicator Control Chart (see presentation at Coreset BD meeting by Johan Wikner, Status Assessment Control Diagram attached; consult also various statistical books, e.g., Manley, F.J.M Statistics for environmental science and management, 1th ed. Chapman and Hall/CRC, New York: McGraw-Hill Book Company). For CB% and MMB%, we used mean and 95% confidence interval (CI). Please, remember that percentages are not normally distributed by definition and use an appropriate transformation to calculate CI. 202

308 Example to illustrate the workflow: Testing CB% as an indicator of fish feeding conditions in a coastal area of the northern Baltic proper a. Based on Fig. 2 in Rahikainen & Stephenson (2004) and Casini et al. (2006), the reference period (=high growth in zooplanktivorous fish) in this area (ICES subdivision 29) occurred in ; b. Time trend for CB%, with calculated mean for the reference period and target value set at lower 95% CI limit (Fig. 1). Observe that for values expressed as percentage, SD is calculated using arcsin sqrt transformed values and then backtransformed to represent upper and lower CI limits; c. The GES boundary value for CB% it is set as a threshold value, which mark the boundary between acceptable and unacceptable conditions, i.e. CB (CB%) should not decline below its GES boundary value. d. Evaluation of the indicator trend: Since 1995, CB% is generally below its target (i.e. GES boundary) value, indicating poor nutritional conditions for zooplanktivorous fish. The decline from the baseline (mean value) started in early 1990-ties and particularly low values were observed in the late 1990-ties - early 2000-ties, which correspond well with fish condition index in this area (Casini et al. 2006). Thus, we conclude that indicator performs reasonably well. References Brooks, J.L Eutrophication and changes in the composition of the zooplankton. In Eutrophication: causes, consequences, correctives. National Academy of Sciences, Washington, D.C. pp Cardinale M, Casini M, Arrhenius F (2002) The influence of biotic and abiotic factors on the growth of sprat (Sprattus sprattus) in the Baltic Sea. Aquat. Liv. Res.: Casini M, Cardinale M, Hjelm J (2006) Inter-annual variation in herring, Clupea harengus, and sprat,sprattus sprattus, condition in the central Baltic Sea: what gives the tune?. Oikos 112: Casini M, Hjelm J, Molinero JC, Lövgren J, Cardinale M, Bartolino V, Belgrano A, Kornilovs G (2009) Trophic cascades promote threshold-like shifts in pelagic marine ecosystems. Proc. Natl. Acad. Sci. USA 106: Guthrie B, Love T, Fahey T, Morris A, Sullivan F Control, compare and communicate: designing control charts to summarise efficiently data from multiple quality indicators. Qual. Saf. Health Care 2005;14: Hanson, J.M., and Peters, R.H Empirical prediction of zooplankton and profundal macrobenthos biomass in lakes. Can. J. Fish. Aquat. Sci. 41: HELCOM (1988) Guidelines for the Baltic monitoring programme for the third stage. Part D. Biological determinants. Baltic Sea Environment Proceedings 27D: HELCOM, Eutrophication in the Baltic Sea An integrated thematic assessment of the effects of nutrient enrichment and eutrophication in the Baltic Sea region. Balt. Sea Environ. Proc. No. 115B. Manley, F.J.M Statistics for environmental science and management, 1th ed. Chapman and Hall/CRC, New York: McGraw-Hill Book Company. Pace, M.L An empirical analysis of zooplankton community size structure across lake trophic gradients. Limnol. Oceanogr. 31: Pace, M.L., and Orcutt, J.D., Jr The relative importance of protozoans, rotifers and crustaceans in freshwater zooplankton community. Limnol. Oceanogr. 26: Rahikainen M, Stephenson RL Consequences of growth variation in northern Baltic herring for assessment and management. ICES Journal of Marine Science 61: , 203

309 Ronkkonen S, Ojaveer E, Raid T, Viitasalo M (2004) Long-term changes in Baltic herring (Clupea harengus membras) growth in the Gulf of Finland. Canadian Journal of Fisheries and Aquatic Sciences 61: Schindler, D.W Detecting ecosystem responses to anthropogenic stress. Can. J. Fish. Aquat. Sci. 44(Suppl.1): Sládecek,V Rotifers as indicators of water quality. Hydrobiologia, 100: Stemberger, R.S., and Lazorchak, J.M Zooplankton assemblage responses to disturbance gradients. Can. J. Fish. Aquat. Sci. 51: Phytoplankton diversity 1. Working team: Pelagic (phytoplankton) Authors: Vivi Fleming-Lehtinen, Laura Uusitalo and Heidi Hällfors Acknowledged persons: Seija Hällfors, Andres Jaanus and Lauri London 2. Name of candidate indicator Phytoplankton diversity 3. Unit of the candidate indicator unitless diversity index 4. Description of proposed indicator The indicator describes phytoplankton species diversity by an applied Shannon diversity index. It shows changes in the phytoplankton species composition as a result of the eutrophication of the marine environment. Initial testing has been conducted concentrating on dominant phytoplankton species and their diversity by an applied Shannon's index based on the most abundant species that together make up >95% of the total biomass. Since the occurrence of rare species in the samples is random and uncertain, excluding these species from the indicator enhances its robustness. The preliminary testing of the indicators show promise but needs further elaboration. SYKE continues to develop the indicator in the LIFE+ MARMONI project. Indicator depends on monitoring on the number and abundance of phytoplankton species on species level or as close to species level as possible. 5. Functional group or habitat type Pelagic habitats 6. Policy relevance Descriptor 1, criterion 1.6 Habitat condition. 7. Use of the indicator in previous assessments Not 8. Link to anthropogenic pressures The linkage to eutrophication has been established. Eutrophication alters the abiotic condition of the pelagic habitat (bottom-up driven changes). 9. Pressure(s) that the indicator reflect Inputs of nitrogen and phosphorus (all sources and forms). 10. Spatial considerations The indicator can be used in the sub-basin level, following changes in large scale. 204

310 11. Temporal considerations Requires weekly/biweekly monitoring and is therefore restricted to ship-of-opportunity samples. 12. Current monitoring Monitored along a few shipping lanes in the Baltic Sea. 13. Proposed or perceived target setting approach with a short justification. The GES boundary should be set on the basis of historical data and diversity results in lowimpacted areas Seasonal succession of phytoplankton groups 1. Working team: Pelagic (phytoplankton) Author: Andres Jaanus 2. Name of candidate indicator Seasonal succession of phytoplankton groups 3. Unit of the candidate indicator unitless index 4. Description of proposed indicator The seasonal succession of phytoplankton functional groups is an index which has previously been presented by Devlin et al. (2007) for UK waters. The method is based on firstly defining reference growth envelopes for functional groups of interest using long-term data or unimpacted sites. Present state is assessed by comparing the present seasonal distribution of each functional group (Phytoplankton counts are averaged over months, and monthly mean and standard deviations calculated for each functional group) to the reference by use of a normalized score (Z score). Monthly Z score establishes comparable seasonal distributions for each functional group for a sampling year. A positive Z score indicates that the observation is greater than the mean and a negative score indicates the observation is less than the mean. The index has been tested for diatoms and dinoflagellates in the Baltic Sea area. Further testing is needed to evaluate the appropriateness of the indicator. 5. Functional group or habitat type Pelagic habitats 6. Policy relevance Descriptor 1, criterion 1.6 Habitat condition. 7. Use of the indicator in previous assessments Not 8. Link to anthropogenic pressures The linkage to eutrophication has been established. Eutrophication alters the abiotic condition of the pelagic habitat (bottom-up driven changes). 9. Pressure(s) that the indicator reflect Inputs of nitrogen and phosphorus (all sources and forms). 10. Spatial considerations The indicator can be used in the sub-basin level, following changes in large scale. 11. Temporal considerations Requires weekly/biweekly monitoring and is therefore restricted to ship-of-opportunity samples. 12. Current monitoring 205

311 Monitored along a few shipping lanes in the Baltic Sea. 13. Proposed or perceived target setting approach with a short justification. Reference growth envelopes should be established from long-term data or data from lowimpacted sites Alkylphenols 1. Name of candidate indicator Alkylphenols: nonylphenol and octyphenol 2. Preferred matrix Herring and perch muscle, cod liver (lipid + fresh + LW%). Bivalve soft tissue (dry + fresh + DW%). 3. Description of proposed indicator Nonylphenol and octylphenol are toxic and possibly bioaccumulating in mussels. According to the thematic assessment of hazardous substances (HELCOM 2010), nonylphenol exceeded EQS only in the southern parts of the Baltic Sea and only in sediment samples. Octylphenol exceeded the EQS also in the Northern Baltic Proper, but only in the sediments. The CORESET expert group for hazardous substances indicators noticed the lack of high concentrations in biota and noticed that more information should be compiled before alkylphenols could be proposed as core indicators. 4. Policy relevance Nonylphenol and octylphenol are both listed under the HELCOM BSAP and under the EU Priority Substances. Descriptor 8, criterion 8.1 of the MSFD. BSAP, ecological objective Concentrations of hazardous substances close to natural levels. 5. Use of the indicator in previous assessments Thematic assessment of hazardous substances (HELCOM 2010). 6. Current monitoring Monitored by Denmark, Germany and Sweden. 7. Proposed or perceived target setting approach with a short justification. Environmental Quality Standards Intersex or vitellogenin induction in male fish The candidate indicator for measuring the estrogenic activity and its effects is developed by the BONUS+ project BEAST. This report lacks a proper documentation for the indicator. Table 1. Overview of the use, monitoring, cause-effect relationships, assessment criteria and available guidance. Used by OSPAR CEMP or pre- CEMP MEDPOL 1) Used in national monitoring programmes in Baltic Sea countries 2) Research monitoring data available Studied in large Baltic Sea research projects Biological Indication (BI) Cause/effect (C/E) relationship Availability of AC specific for the Baltic Sea (for detailes see Table 1 Monitoring Guidelines, other important info QA 206

312 Method costs (High-Medium- Low) ICES TIMES 31 QA NO Low costs 2) DE, SE, DK BEEP BEAST BALCOFISH BI exposure to estrogenic contaminants BAC, EAC under development (BEAST) Abbreviations BAC Background Assessment Criteria EAC Environmental Assessment Criteria (concentrations above which there is concern that negative effects might be observed in marine organisms. EAC describes the direct linkage to adverse health effects of the individuals) AC Numerical Assessment Criteria QA Quality Assurance measures CEMP guidelines, quality assurance and assessment tools are in place - monitoring of the component is mandatory for OSPAR contracting parties pre-cemp agreed to be included as components of the CEMP, guidelines, QA tools and/or assessment tools are currently not all in place. Monitoring of the components is voluntary Country codes: DK-Denmark, EE-Estonia, FI-Finland, DE-Germany, LV-Latvia, LT-Lithuania, PL- Poland, RU-Russia, SE-Sweden Acetylcholinesterase (AChE) General information General properties The analysis of acetylcholinesterase (AChE; EC ) activity and its inhibition in marine organisms has been shown to be a highly suitable method for assessing exposure to neurotoxic contaminants in aquatic environments. AChE activity method is applicable to a wide range of species and has the advantage of detecting and quantifying exposure to neurotoxic substances without a detailed knowledge of the contaminants present. AChE activity is a typical biomarker that can be used in in vitro bioassays and field applications. Main impacts on the environment and human health AChE has traditionally been used as a specific biomarker of exposure to organophosphate and carbamate pesticides. More recently, its responsiveness has been demonstrated to various other groups of chemicals present in the marine environment including heavy metals, detergents and hydrocarbons. Its usefulness as a general indicator of pollution stress in mussels from the Baltic Sea has been shown within the EU-BEEP project. AChE inhibition mostly agreed well with the studied pollution gradients, especially in mussels. Seasonal differences in activity were notable in flounder, eelpout and mussels, possibly resulting from variations in the occurrence of affecting substances (e.g., pesticides from river input or run-off from agricultural sources) during the year. Additional field studies and laboratory experiments showed that AChE in Baltic mussels is influenced by temperature and salinity, while also salinity has an effect on the uptake (and therefore on toxicity) of substances (Lehtonen et al., 2006). Status of a compound on international priority lists and other policy relevance 207

313 OSPAR pre-cemp, MED POL Phase IV (2º Tier). ICES SGIMC has recommended AChE in molluscs as biomarker to be included into the OSPAR Coordinated Environmental Monitoring Programme (pre-cemp). AChE has been adopted by UNEP as part of the second tier of techniques for assessing harmful impact in the Mediterranean Pollution programme (MEDPOL Phase IV). GES boundaries and matrix The existence of extremely low thresholds for induction of inhibitory effects on AChE suggests that detection is possible after exposure to low concentrations of insecticides (0.1 to 1 µgl-1; ICES, 2010). Standardisation of the sampling strategy and regular intercalibration exercises on specific organisms are still necessary before using AChE in routine pollution monitoring. No formal quality assurance programmes are currently run within the BEQUALM programme but one major intercalibration exercise was carried out during the BEEP project. Baseline levels of AChE in different marine species have been estimated from results derived from in the Atlantic Ocean, the Mediterranean and the Baltic Sea (Table 1; ICES, 2010) and ongoing studies within Bonus+ BEAST. Generally it has been accepted that 20% reduction in AChE activity in fish and invertebrates indicates exposure to neurotoxic compounds. Depression in AChE activity more than 20% up to 50% indicates sublethal impact. In the field, several species have baseline AChE activities within the same order of magnitude among different studies/measurements (Table 1; ICES, 2010,). However, differences between sea areas and seasons are obvious, with values activity values in Mytilus spp. varying from 25 to 54 nmol min mg protein. (ICES, 2010). Therefore Baltic Sea specific data have been collected which are presently assessed as part of Bonus+ BEAST activities. Preferred matrix Fish muscle, bivalve gills Monitoring the compound Status of monitoring network (geographical and temporal coverage) Suitability of AChE in bivlaves and fish has been tested during the EU-BEEP project; AChE is also a core biomarker within Bonus+ BEAST field activities in different Baltic Sea sub regions. Gaps in the monitoring of the compound Spatial gaps for the Baltic Sea have been identified which are presently filled in within the Bonus+ BEAST project. Present status assessments Known temporal trends Under investigation in Bonus+ BEAST, results will be available during Spatial gradients Under investigation in Bonus+ BEAST, results will be available during

314 Recommendation AChE should become a CORE indicator to be used in a future integrated chemical and biological effects monitoring and assessment programme in the HELCOM region. AChE is a good indicator for direct neurotoxic effects caused, e.g., by organophosphate and carbamate pesticides (specific exposure) also in brackish-water systems. It seems also to indicate general toxicity, often following a similar pattern to LMS (Lehtonen et al., 2006). When applying AChE activity as a biomarker of contaminant effects in the Baltic Sea, local abiotic factors and seasonal differences have to be considered. Results obtained within Bonus+ BEAST will further support suitability of AChE and also provide data needed to develop appropriate assessment criteria for the Baltic Sea. AChE inhibition can be used for integrated biomarker approach. References: ICES Report of the Joint ICES/OSPAR Study Group on Integrated Monitoring of Contaminants and Biological Effects (SGIMC), January, Copenhagen, Denmark. ICES CM 2010/ACOM: pp. Lehtonen, K.K., D. Schiedek, A. Köhler, T. Lang, P.J. Vuorinen, L. Förlin, J. Baršiene, J. Pempkowiak & J. Gercken (2006): The BEEP project in the Baltic Sea: overview of results and outline for a regional biological effects monitoring strategy. Marine Pollution Bulletin 53: Table 1. Overview of the use, monitoring, cause-effect relationships, assessment criteria and available guidance. Used by 1) Used in national OSPAR, CEMP monitoring or pre-cemp programmes in or MEDPOL Baltic Sea countries MEDPOL (2º Tier) 2) Research monitoring data available 2) FI, LV, DE, SE BEEP BEAST Studied in large Baltic Sea research projects Biological Indication (BI) Cause/effect (C/E) relationship Availability of AC specific for the Baltic Sea (for details see Table 1 BI neurotoxic BAC and EAC effects, early warning C/E YES Monitoring Guidelines, other important info Method costs (High-Medium- Low) ICES SGIMC 2010 QA YES Low costs Table 2. Numerical Assessment Criteria (AC) for Baltic Sea organisms to assess biological effects. Values for Background Assessment Criteria (BAC) and Environmental Assessment Criteria (EAC) are given where available or relevant. Full details of AC and how they have been derived can be found in the ICES SGIMC 2010, SGIMC 2011 and WKIMC 2009 reports on the ICES website and in the SGEH Background Documents for the individual biological effects methods. NOTE: All missing information will soon be available from the output of the ongoing projects mentioned. Biological effect method (unit, other information) Target species/ tissue/endpoint BAC Acetylcholinesterase activity Mytilus spp. under development (Finnish and and EAC under development (Finnish and German 209

315 (AChE) [nmol/min/mg protein] - gill tissue German seasonal data;, cf. OSPAR temperature corrected values Macoma balthica - muscle tissue (foot) Herring - muscle tissue Flounder - muscle tissue Eelpout - muscle tissue Perch - muscle tissue under development (Finnish seasonal data) under development (BEAST data) Seasonal BAC values under development (BEEP, BEAST and Polish data) Seasonal BAC values under development (BEEP & BEAST data) under development (BEEP data) Seasonal BAC values seasonal data;, cf. OSPAR temperature corrected values) 0.7 x BAC 0.7 x BAC (cf. OSPAR AC) Seasonal BAC values 0.7 x BAC (cf. OSPAR AC) Seasonal BAC values 0.7 x BAC (cf. OSPAR AC) Seasonal BAC values 0.7 x BAC (cf. OSPAR AC) Seasonal BAC values EROD/CYP1A induction The candidate indicator for measuring the Ethoxyresorufin-O-deethylase (EROD) activity is developed by the BONUS+ project BEAST. This report lacks a proper documentation for the indicator, but information provided by the BEAST project has been compiled. Table 1. Overview of the use, monitoring, cause-effect relationships, assessment criteria and available guidance. Country codes: DK-Denmark, EE-Estonia, FI-Finland, DE-Germany, LV-Latvia, LT- Lithuania, PL-Poland, RU-Russia, SE-Sweden. Used by OSPAR, CEMP or pre-cemp or MEDPOL 1) Used in national monitoring programmes in Baltic Sea countries Studied in large Baltic Sea research projects Biological Indication (BI) Cause/effect (C/E) relationship Availability of AC specific for the Baltic Sea (for detailes see Table 2 Monitoring Guidelines, other important info Method costs (High-Medium-Low) 2) Research monitoring data available pre-cemp 1) DK, SE, 2) PL, FI, Pl, EE BEEP BEAST BI to Ah-receptor active chemicals such as PAH, planar PCB, and dioxins BAC, under development (BEAST) EAC not yet available ICES TIMES 13 and 23 QA-YES Low costs Abbreviations BAC Background Assessment Criteria EAC Environmental Assessment Criteria (concentrations above which there is concern that negative effects might be observed in marine organisms. EAC describes the direct linkage to adverse health effects of the individuals) AC Numerical Assessment Criteria QA Quality Assurance measures 210

316 CEMP guidelines, quality assurance and assessment tools are in place - monitoring of the component is mandatory for OSPAR contracting parties pre-cemp agreed to be included as components of the CEMP, guidelines, QA tools and/or assessment tools are currently not all in place. Monitoring of the components is voluntary Table 2. Numerical Assessment Criteria (AC) for Baltic Sea organisms to assess biological effects. Values for Background Assessment Criteria (BAC) and Environmental Assessment Criteria (EAC) are given where available or relevant. Full details of AC and how they have been derived can be found in the ICES SGIMC 2010, SGIMC 2011 and WKIMC 2009 reports on the ICES website and in the SGEH Background Documents for the individual biological effects methods. NOTE: All missing information will soon be available from the output of the ongoing projects mentioned. Biological effect method (unit, other information) Ethoxyresorufin-O-deethylase activity (EROD) [pmol/min/mg protein] pmol/min/ mg S9 protein *pmol/min/ mg microsomal protein Target species/ tissue/endpoint BAC EAC Flounder (male) 24 not yet available Eelpout 10 (Belt Sea data) not yet available Herring under development BEAST not yet available 211

317 5. Supplementary indicators for environmental assessments The HELCOM CORESET project identified a number of supplementary indicators, which were not included in the core set, because they either did not fulfil the HELCOM principles for core indicators or they were considered as redundant. Some supplementary indicators can fulfil some of the strict requirements of the core indicators, including the requirement for a quantitative GES boundary, while others can be more descriptive indicators, for example, describing temporal development of parameters that are not linked or weakly linked to anthropogenic pressures. Nevertheless, the supplementary indicators provide valuable information for environmental assessments. Their role is to support the core indicators and provide information of causative factors behind status assessments Summary of all supplementary indicators The supplementary indicators are listed in the summary table below with a short description or a web link to HELCOM Indicator Fact Sheets. Indicators without a web link are further described in this chapter below. Table 5.1. Supplementary indicators. Web links to HELCOM Indicator Facts Sheets have been provided, if available. Supplementary biodiversity indicators Objective of the indicator 1. Population Development of Sandwich Tern andwichtern/ 2. Population Development of Great Cormorant 3. Population Development of Whitetailed Sea Eagle 4. Decline of the harbour porpoise (Phocoena phocoena) in the southwestern Baltic Sea 5. The abundance of comb jellies in the northern Baltic Sea 6. Ecosystem regime state in the Baltic Proper, Gulf of Riga, Gulf of Finland, and the Bothnian Sea ormorant/ White-tailedSeaEagle/ arbourporpoise/ ombjellies/ n_gb/ecoregime/ 7. Ratio of diatoms and dinoflagellates Describes the change in taxonomic group composition, presumably caused by eutrophication. Not applicable for the entire sea area. See text below. 8. Ratio of autotrophic and heterotrophic organisms 9. Intensity and areal coverage of cyanobacterial blooms Describes a change in functional group composition and energy flow in the food web. Not properly tested. See text below. Describes effects of phosphorus inputs and internal loading ( Cyanobacterial_blooms/, n_gb/cyanobacteriabloomindex/) 10. Abundance and distribution of non- Presents the distribution, abundance and temporal trends of selected invasive non-indigenous species in the assessment 212

318 indigenous invasive species units. 11. Biopollution index Minor impact from newly arrived species. See text below. Supplementary indicators for the status Objective of the indicator of hazardous substances 12. Organochlorine pesticides Includes DDTs, HCB and HCHs (incl. lindane). Separate description below. 13. Copper in biota, sediment and water Concentrations of Cu have increased in some areas of the Baltic Sea (see HELCOM 2010). Monitoring is done by several HELCOM Contracting States. 14. Zinc in biota, sediment and water Concentrations of Zn have increased in some areas of the Baltic Sea (see HELCOM 2010). Monitoring is done by several HELCOM Contracting States. Supplementary environment indicators Objective of the indicator 15. Surface water salinity Describes environmental conditions caused by climatic variability. 16. Near bottom oxygen conditions Describes condition of the near-bottom habitats caused by climatic variability and nutrient inputs. 17. Sea water acidification Describes a temporal change in sea water ph. To be published as Indicator Fact Sheet in The ice season Describes the extent of sea ice and reflects also a potential threat for ice-breeding seals: eseason/ 19. Total and regional Runoff to the Baltic Sea unoff/ 20. Water Exchange between the Baltic Sea and the North Sea, and conditions in the Deep Basins 21. Hydrography and Oxygen in the Deep Basins WaterExchange/ ydrographyoxygendeepbasins/ 22. Development of Sea Surface Temperature in the Baltic Sea in easurfacetemperature/ 23. Wave climate in the Baltic Sea aveclimate2009/ 24. Bacterioplankton growth acterioplankton/ Supplementary pressure indicators 25. Nitrogen emissions to the air in the Baltic Sea area 26. Emissions from the Baltic Sea shipping in 2009 Objective of the indicator Describe anthropogenic pressures for all biota in the form of eutrophication: itrogenemissionsair/ Describe anthropogenic pressures for all biota in the form of contamination and eutrophication: hipemissions/ 213

319 27. Atmospheric nitrogen depositions to the Baltic Sea during Spatial distribution of the winter nutrient pool 29. Waterborne inputs of heavy metals to the Baltic Sea 30. Atmospheric deposition of heavy metals on the Baltic Sea 31. Atmospheric deposition of PCDD/Fs on the Baltic Sea Describe anthropogenic pressures for all biota in the form of eutrophication: _deposition/ Describe anthropogenic pressures for all biota in the form of eutrophication /en_GB/WinterNutrientPool/ Describe anthropogenic pressures for all biota in the form of contamination: aterborne_hm/ Describe anthropogenic pressures for all biota in the form of contamination: m_deposition/ Describe anthropogenic pressures for all biota in the form of contamination: 2010/en_GB/pcddf_deposition/ 32. Shipping Describes the extent of underwater noise, disturbance for sea birds, vector for non-indigenous species, offshore wastewater and, in shallow areas, seabed disturbance. 33. Illegal discharges of oil in the Baltic Sea during 2009 Describe anthropogenic pressures for all biota, particularly seabirds, in the form of contamination: egaldischarges/ 5.2. Ratio of diatoms and dinoflagellates It has been widely suggested that the ratio of diatoms and dinoflagellates indicates environmental change in marine ecosystems. Most often changes in that ratio have been contributed to eutrophication or climatic changes. The same factors have been suggested to have caused the increase of dinoflagellates in the Baltic Sea spring bloom over the last decades, both in the northern Baltic Sea (Jaanus et al. 2006, Kremp et al. 2008, Olli & trunov 2010), as well as in the central and southern parts (Wasmund & Uhlig 2003, Alheit et al. 2005). Klais et al. (2011) however concluded that on the time scale of previous four decades there has been no visible Baltic Sea wide trend in the ratio, but that the role of dinoflagellates has increased in the Gulf of Finland and the Gulf of Bothnia, where also eutrophication process has taken place at the same time. At the moment, the indicator for the ratio of diatoms and dinoflagellates is seen by the CORESET project as a supplementary indicator and its applicability to indicate anthropogenic eutrophication in different areas of the region should be tested. References Alheit J, Möllmann C, Dutz J, Kornilovs G, Loewe P, et al. (2005) Synchronous ecological regime shifts in the central Baltic and the North Sea in the late 1980s. ICES Journal of Marine Science 62: Jaanus A, Hajdu S, Kaitala S, Andersson A, Kaljurand K, et al. (2006) Distribution patterns of isomorphic coldwater dinoflagellates (Scrippsiella/Woloszynskia complex) causing 'red tides' in the Baltic Sea. Hydrobiologia 554: Klais R, Tamminen T, Kremp A, Spilling K, Olli K (2011) Decadal-Scale Changes of Dinoflagellates and Diatoms in the Anomalous Baltic Sea Spring Bloom. PLoS ONE 6(6): e doi: /journal.pone Kremp A, Tamminen T, Spilling K (2008) Dinoflagellate bloom formation in natural assemblages with diatoms: nutrient competition and growth strategies in Baltic spring phytoplankton. Aquatic Microbial Ecology 50: Olli K, Trunov K (2010) Abundance and distribution of vernal bloom dinoflagellate cysts in the Gulf of Finland and Gulf of Riga (the Baltic Sea). Deep-Sea Research II 57:

320 Wasmund N, Uhlig S (2003) Phytoplankton trends in the Baltic Sea. ICES Journal of Marine Science 60: Ratio of aututrophic and heterotrophic organisms This indicator is based on the same rationale than the previous one: Increasing eutrophication reduces the ratio of autotrophic to heterotrophic processes. This indicator requires more consideration Abundance and distribution of non-indigenous invasive species The supplementary indicators for the distribution and abundance of selected invasive nonindigenous species are under development. The indicators will show the distribution map on the basis of the best available information, abundance map and graphs of the temporal changes of species. No text has been finalized for this report. The first NIS species selected to be worked on are the zebra mussel (Dreissena polymorpha) and the fish hook water flea Cercopagis pengoi Biopollution level index 1. Working team: Non-indigenous species Authors: Maiju Lehtiniemi, Manfred Rolke, Malin Werner and Alexander Antsulevich 2. Name of the indicator Biopollution level index 3. Unit of the indicator An index based on the number, abundance, distribution and impacts of non-indigenous species on native communities, habitats and ecosystem functioning 4. Description of proposed indicator Biological pollution (magnitude of bioinvasion impacts) is defined as the impact of nonindigenous species (NIS) on ecological quality and includes (but is not confined to) the genetic alteration within populations, the deterioration or modification of habitats, the spreading of pathogens and parasites, competition with and replacement of native species. The BPL method (Olenin et al., 2007) takes into account the abundance and distribution range (ADR) of NIS in relation to native biota and aggregates data on the magnitude of the impacts in three categories: 1) impacts on native communities, 2) habitats and, 3) ecosystem functioning. ADR varies within five classes, ranking a NIS from low abundance in a few localities (A) to occurrence in high numbers in all localities (E). After ADR is established, three categories of impacts are considered, whose magnitude is ranked on five levels ranging from no impact (0) to massive impact (4) based on qualitative changes in an invaded ecosystem. The theoretical justification uses several well established ecological concepts, e.g. key species, type specific communities, habitat alteration, fragmentation and loss, functional groups, food web shift, etc. BPL aggregates the results of the assessment into five categories: No bioinvasion impact, Weak, Moderate, Strong and Massive. 5. Functional group or habitat type All non-indigenous species 6. Policy relevance Descriptor 2 (Descriptor 1 & 4: indirectly) 7. Use of the indicator in previous assessments None 8. Link to anthropogenic pressures 215

321 Directly impacted by: Introductions of new species e.g. from shipping, intentional stocking to aquaculture purposes or aquaria. 9. Pressure(s) that the indicator reflect Shipping activities (untreated ballast water, hull fouling) 10. Spatial considerations The indicator should be estimated for specific areas (e.g. sub-basins or assessment units consisting of national coastal and offshore waters) but can be generalized for larger areas as well. 11. Temporal considerations The indicator will be assessed every six years, but data collection is continuous. 12. Current monitoring The monitoring of NISs is rare in the Baltic Sea as such. However, in other biological monitoring programs (in the open sea and in coastal areas) e.g. in COMBINE program, NIS are often observed and counted, which gives a certain level of data for the indicator. Nevertheless it would be important to increase monitoring in specific less monitored habitats. The most problematic is to get information on the impacts of NIS, which is not currently monitored. The data on impacts have to be searched from the literature. 13. Proposed or perceived target setting approach with a short justification. The goal is to minimize human mediated introductions of non-indigenous species. GES boundary for non-indigenous species should be 'no new introductions'. For the indicator in question the GES boundary should be 'No new non-indigenous species with known impacts'. This means that when an assessment is made only the species, which have been introduced after the previous assessment will be taken into account. Introduction Introductions of non-indigenous species (NIS) in the Baltic Sea are increasing. In order to prevent new harmful introductions all human mediated introductions should be prevented. Not all introduced species are harmful, thus biopollution level index, which takes into account impacts of introduced species, gives a good overall view on the situation in the area in question concerning non-indigenous species. Biopollution level index needs to be calculated if new introductions have happened meaning that 'trend in arrival indicator' have shown an increase during the six year assessment period. Furthermore, non-indigenenous species with a BPL<1 should be re-evaluated in every assessment period. The impacts of non-indigenous species The introduction of non-indigenous species is among the four largest threats to marine environment. They can have severe ecological, economic and public health impacts. NIS can induce considerable changes in the structure and dynamics of marine ecosystems. They may also hamper the economic use of the sea or even represent a risk for human health. Ecological impacts include changes in habitats and communities and alterations in food web functioning, even losses of native species can occur in extreme cases. Economic impacts range from financial losses in fisheries to expenses for cleaning intake or outflow pipes of industries and structures from fouling. Public health impacts may arise from the introduction of microbes or toxic algae. Due to the fact that only a minority of non-indigenous species (NIS) are invasive i.e. have a potential to cause negative impacts on the environment, the plain high numbers of introduced species do not provide sufficient basis for the assessment of biopollution i.e. effects non-indigenous species have on the ecosystem. Hence, the NIS need to be analysed and classified according to the magnitude of their impacts on the environment and 216

322 biodiversity. In this regard, those NIS which cause most harm on the environment and/or humans are most important, and not only in terms of assessing the current and changing status of the ecosystems (requirements from the WFD and MSFD), but also in terms of the marine management perspective in order to facilitate strong move towards implementation of the ecosystem based approach. One method for this is the Biopollution Level Index (BPL, Olenin et al. 2007). The proposed method has species-approach and considers each NIS separately, based on its impact on community, habitat or ecosystem levels. According to this method, the biopollution calculation is based on abundance and distribution range of the non-indigenous species under consideration and the magnitude of their impacts on native species, communities, habitats and ecosystem functioning. Index may get values from 0 (no biopollution) to 4 (massive biopollution). The method has been tested in the Baltic Sea with all known nonindigenous species recorded (Zaiko et al. 2011) as well as for a specific case of the dinoflagellate (Prorocentrum minimum) (Olenina et al. 2010). Policy relevance Since the early 1990's when the Marine Protection Committee (MEPC) of the International Maritime Organisation (IMO) put the issue on the agenda, the problem became more and more important for marine environmental protection. In 2004 the Ballast water Convention was adopted by the IMO. The convention requires ballast water management procedures to minimize the proliferation of non-indigenous species via ballast water and sediment. Once entered into force every ship has to treat its ballast waters unless exemption is given based on risk analysis. In order to minimize adverse effects of introductions and transfers of marine organisms for aquaculture ICES drafted the 'ICES Code of Practice on the Introductions and Transfers of Marine Organisms'. The Code of practice summarizes measures and procedures to be taken into account when planning the introduction of NIS for aquaculture purposes. On the European level the EC Council Regulation No 708/2007 concerning the use of nonindigenous and locally absent species in aquaculture is based on the ICES Code of Practice. With the maritime activities segment of the Baltic Sea Action Plan HELCOM expresses the strategic goal to have maritime activities carried out in an environmental friendly way and that one of the management objectives is to reach No introductions of alien species from ships. In order to prepare the implementation of the Ballast Water Convention a road map has been established with the ultimate to ratify the BWM Convention by the HELCOM Contracting States preferably by 2010, but in all cases not later than The EU Marine Strategy Framework Directive in order to maintain or achieve good environmental status in the marine environment established a framework for Member states. The good environmental status shall be determined on the basis of qualitative descriptors. One of the qualitative descriptors concerns non-indigenous species stating 'Non-indigenous species introduced by human activities are at levels that do not adversely alter the ecosystem.' Biopollution Level index has been reviewed by the EU MSFD good environmental status task group 2 on non-indigenous species and is seen as a straight-forward and practical way of assessing impacts of the NIS and their potential to become invasive. BPL index is also viewed as a practical solution for the Ballast Water Management efforts to distinguish between species which pose a threat on regional voyages and which should therefore be taken into account in Risk Assessments done for IMO BWM Convention when considering if a certain ship route may get an exemption from ballast water treatment procedures. 217

323 Biopollution Level assessment has presently been performed only once. Thus there are no temporal trends yet available concerning this indicator. Assessment This assessment is a baseline assessment, since the target for next assessments is to estimate impacts of new introduced species. Good Environmental Status is met when further impacts from NIS are minimized, with the ultimate goal of no adverse alterations to the ecosystems during the assessment period.the baseline assessment was performed for nine Baltic sub-regions. It revealed that documented ecological impact is only known for 43 NIS, which is less than 50% of the species registered in the sea. The highest biopollution (BPL = 3, strong impact) occurs in coastal lagoons, inlets and gulfs, and the moderate biopollution (BPL = 2) in the open sea areas (Fig. 1). None of the Baltic sub-regions got low impact classifications (BPL = 0 or 1) indicating that invasive species with recognized impacts are established in all areas. The most widely distributed species, observed nearly all around the Baltic Sea were Marenzelleria spp., Potamopyrgus antipodarum, Eriocheir sinensis, Cercopagis pengoi, Mya arenaria and Balanus improvisus. However, their magnitude of impact (BPL) differed between different sub-regions of the sea (Fig. 2). For seven species (Neogobius melanostomus, Obesogammarus crassus, Pontogammarus robustoides, Dreissena polymorpha, Gammarus tigrinus, Balanus improvisus and Cercopagis pengoi) high biopollution level (BPL = 3) was defined in one or more analyzed subregions. None of the analyzed species got the maximum biopollution level (BPL = 4). 218

324 Fig. 1. Biopollution level in the assessed sub-regions in the Baltic Sea (lighter regions have BPL = 2 moderate biopollution, darker BPL = 3 strong biopollution). Numbers in parentheses indicate the number of impacting non-indigenous species in an assessment unit (with BPL>0). BPL may get values from 0 to