Implementing an inventory and monitoring programme for the Department of Conservation s Natural Heritage Management System

Transcription

1 Implementing an inventory and monitoring programme for the Department of Conservation s Natural Heritage Management System

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3 Implementing an inventory and monitoring programme for the Department of Conservation s Natural Heritage Management System INVESTIGATION NO.: DOC4120 Robert B. Allen, Peter J. Bellingham, David M. Forsyth, Catriona J. MacLeod and Elaine F. Wright Landcare Research, PO Box 69040, Lincoln 7640 Landcare Research Contract Report: LC1731 Prepared for: Department of Conservation Planning, Monitoring and Reporting Manager Science and Capability Group Level 1, Moorhouse Avenue Addington, Christchurch 8011 DATE: December 2013

4 Reviewed by: Approved for release by: William G. Lee Scientist Landcare Research Robert B. Allen Science Team Leader Ecosystem Processes Disclaimer: The Department takes no responsibility for the accuracy of the report and the findings and opinions expressed therein. Department of Conservation 2013 This report was produced by Landcare Research New Zealand Ltd for the Department of Conservation. This report was originally published in September 2009 and reissued December 2013.The Department started progressively implementing a national biodiversity monitoring and reporting system in 2011/12. Please note that the implemented system differs in some aspects from that described in the report, including associated costs. All copyright in this report is the property of the Crown and any unauthorised publication, reproduction, or adaptation of this report is a breach of that copyright and illegal.

5 Contents Abstract Overview Introduction What will happen on the ground? How does this programme support the Department? How could the programme be expanded? What are the key interdependencies? Inventory and Monitoring Programme Sampling framework Methods to be used Feasibility of the methods Implementation Training Scheduling Data management Evaluation of costs Pathway to use National and regional reporting of status and trend in ecological integrity Informing prioritisation for resource allocation on conservation lands Evaluating the effectiveness of management and policy An early-warning system Acknowledgements Appendix Person hours and costs per sampling location... 35

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7 Implementing an Inventory and Monitoring programme for the Department of Conservation s Natural Heritage Management System Robert B. Allen 1, Peter J. Bellingham 1, David M. Forsyth 2, Catriona J. MacLeod 1 and Elaine W. Wright 3 1 Landcare Research, PO Box 69040, Lincoln 7640, New Zealand, allenr@landcareresearch.co.nz, bellinghamp@landcareresearch.co.nz, macleodc@landcareresearch.co.nz 2 Arthur Rylah Institute for Environmental Research, Department of Sustainability and Environment, 123 Brown Street, Heidelberg, Victoria 3084, Australia, dave.forsyth@dse.vic.gov.au 3 Department of Conservation, PO Box 13049, Christchurch 8142, New Zealand, ewright@doc.govt.nz Abstract The Department of Conservation (DOC) is the central government organisation charged with conserving the natural and historic heritage of New Zealand on behalf of, and for the benefit of, present and future New Zealanders. DOC needs to know the state of our heritage and whether outcomes are being achieved. Implementation of an inventory and monitoring programme will provide unbiased, repeatable ecological-integrity indicators estimated across all Conservation lands. Indicators are used in many human endeavours to simplify the information needed for decision making and product assurance. Although the indicators adopted in this programme can be applied at multiple scales, within a nested hierarchy, the design we outline has a national focus. Trends in ecological integrity indicators at national and regional scales will be based upon timely, detailed, local measurements that can, where possible, be modelled across all Conservation lands. Five measures, representing three indicators, were chosen by DOC from a potential 41 measures, representing 18 indicators, as vital measures for early implementation in this programme to provide new and objective data with enough detail to address the concerns of DOC, stakeholders, and the New Zealand public. This report presents an outline of the implementation of these five measures: two focus on vegetation persistence and function - (1) Size-class structure of canopy dominants, (2) Representation of plant functional types; one examines a major biotic group - (3) Assemblages of widespread animal species Birds; and two assess threats to ecological integrity - (4) Distribution and abundance of mammal pests considered a threat, and (5) Distribution and abundance of exotic weeds considered a threat. With 1311 sampling locations (i.e. objectively located points on DOC-administered lands with a slope of 65º), implementing all five measures, will cost DOC c. $4.5 million, and utilise 34 FTEs, each year. These are the costs to collect the data, process field samples, and enter the data. This programme will allow DOC to assess ecological integrity and provide an empirical basis for the Department s intervention logic through (a) national and regional reporting of status and 1

8 trend in ecological integrity, (b) informing prioritisation for resource allocation on Conservation lands, (c) evaluating the effectiveness of conservation management and policy, and (d) an early-warning system. The spatially extensive, robustly designed programme outlined will position New Zealand strongly, both nationally and internationally, to report on the effectiveness of biodiversity conservation on public land. Keywords: biodiversity assessment, monitoring, performance measurement, invasive species, pest impacts, bird community structure, plant size-structure, functional traits 2

9 1 Overview 1.1 Introduction Humans are having wide-ranging detrimental effects on biodiversity. 1 Some effects are local or regional, for example those brought about by fire or weed introductions, while others are global, such as those resulting from increasing atmospheric CO 2 concentration. At a national scale, the New Zealand Biodiversity Strategy and successive State of the Environment Reports present a generalised declining trajectory for biodiversity. 2 However relatively few biodiversity components were included in this trajectory, and frequently it is unclear how the rate of decline was determined. It is only known with any confidence that there has been a recent decline in a small proportion of the total biota (e.g. endemic land vertebrates). For most taxa the evidence is anecdotal at best. Even for iconic taxa such as birds there is no large-scale, systematic measure of abundance. Yet a wide range of conservation expenditure is justified on perceived threats to, and negative consequences for, indigenous biodiversity. The Department of Conservation (DOC) is charged with conserving natural and historic heritage on behalf of, and for the benefit of, present and future New Zealanders. DOC is required to know if heritage outcomes are being achieved. Of late there have been efforts to provide clarity around what this means for natural heritage. The desired outcome of conserving natural heritage has been defined as maintaining ecological integrity (see above box) and this now forms the basis for implementing the Natural Heritage Management System (NHMS). 3 However conservation management internationally is bedevilled by an inability to quantify changes in ecological integrity. This is surprising given natural heritage is of enormous environmental, economic, and cultural significance to the New Zealand public. Global concerns mean countries are progressively being required to report on natural heritage (e.g. Convention on Ecological integrity is defined as the full potential of indigenous biotic and abiotic features, natural processes, functioning in sustainable communities, habitats, and landscapes. Components of ecological integrity are: Indigenous dominance (to maintain natural character) Species occupancy (to avoid extinctions) Ecosystem representation (to maintain a full range ). The Department of Conservation is the lead agency for coordinating national reporting on the implementation of the Convention on Biological Diversity Biological Diversity) with implications for trade and value as a global citizen. 4 A useful contrast can be made with reporting required for national carbon accounts (e.g. 1 Vitousek, P.M.; Mooney, H.A.; Lubchenco, J.; Melillo, J.M. 1997: Human domination of Earth s ecosystems. Science 277: Department of Conservation and Ministry for the Environment 2000: New Zealand s biodiversity strategy: our chance to turn the tide. Department of Conservation and Ministry for the Environment, Wellington. 3 Lee, W.G.; McGlone, M.S.; Wright, E.F. 2005: Biodiversity inventory and monitoring: A review of national and international systems and a proposed framework for future biodiversity monitoring by the Department of Conservation. Landcare Research Contract Report LC0405/122, prepared for the Department of Conservation. 4 Scholes, R.J.; Mace, G.M.; Turner, W.; Geller, G.N.; Jürgens, N.; Larigauderie, A.; Muchoney, D.; Walther, B.A.; Mooney, H.A. 2008: Towards a global biodiversity observing system. Science 321:

10 Intergovernmental Panel on Climate Change), as it may foreshadow statistics applied at a national scale to biodiversity reporting (e.g. a Global Biodiversity Observing System). A recent Cabinet paper sets out the Government s expectation of improvements in the quality of information from departments and Crown entities. 5 In 2010/11, the Office of the Auditor General will assess how DOC measures and monitors its performance and provide an annual grading as part of issuing an annual performance opinion. The Inventory and Monitoring Programme outlined here will transform New Zealand s ability to assess biodiversity trends and improve DOC s progress towards the outcomes it seeks to achieve for New Zealanders. This will allow DOC to better meet performance measurement requirements set by the State Services Commission 6 (see diagram below). Those requirements link resource allocation to operational outputs that have impacts leading to a central outcome of ecological integrity. Performance Measurement: Linking resources, outputs, impacts and outcomes This programme allows DOC to assess delivery impacts, as three components of ecological integrity, as well as give reason to planning and intervention logic 7 through: National and regional reporting of status and trend in ecological integrity. This reporting will give unequivocal evidence of what is happening to ecological integrity (and to some degree why) across all Conservation lands. As a consequence, stronger, evidence-based cases can be made for conservation resources. Informing prioritisation for resource allocation on Conservation lands. Providing an objective basis for resource allocation among Conservation lands (e.g. weed control and land acquisition) and selecting the best ecosystems for workforce planning and intensive management. 5 CAB Min (09) 17/ Managing for outcomes What differences are we making? (DOCDM doc) 4

11 Evaluating the effectiveness of conservation management and policy. Complete coverage of Conservation lands will allow the effects of widely applied management regimes (e.g. pest control) to be assessed and to determine whether intensively managed areas more often restore ecological integrity. An early-warning system. Unanticipated trends in ecological integrity may be used to signal management responses or needs for research. For example, systematic avifauna data may have allowed a management response to avert the decline in mohua. The programme will allow more informed and effective planning and policy development, increased agency accountability and hence confidence in, and support for, conservation. Implementation of the programme will provide unbiased, repeatable estimates of ecological integrity indicators for all Conservation lands. An unbiased sample of these lands means complete coverage in a representative way. Changes in Conservation land boundaries through time will alter the sampling universe; however, the use of permanent sampling locations and standardised methods will not only allow statistical advantages from repeat measurements on existing lands but will also allow eventual tracking of changes in ecological integrity on new land acquisitions. Reporting on ecological integrity, and its Do we need indicators? Use is inescapable Widely accepted, e.g. - Nitrates for water pollution - Blood pressure for health risks threats, requires the development of indicators to provide a more systematic approach than is currently available. Indicators are used in many human endeavours to simplify the information needed for decision making and product assurance (e.g. Forest Stewardship Certification 8 ). While managers, policy analysts, and researchers have agonised over selecting indicators for decades, national and international pressures for their use only increase. 9 It is useful if the data underpinning indicators are broadly based with some capacity to adapt and generate new indicators. To rapidly build a capacity to report on ecological integrity will require, where possible, back-calculation of indicators using historical data. Indicators adopted in this report can be applied at many scales, although the sampling design we outline has a national focus and will often be inadequate for meaningful reporting at local scales (e.g. DOC Area Offices) or for uncommon taxa. For example, surveillance monitoring to detect new organisms requires a much more targeted strategy. Sampling intensities defined for field data collection typically allow indicators to be estimated with known levels of precision (usually within 5% of the mean at the 90% confidence interval) over all Conservation land. 10 However, the design will detect major changes at local scales, for example, new taxa that appear on over c. 0.5% of Conservation land or existing taxa that Walpole, M.; Almond, R.E.A.; Besançon, C., et al Tracking progress toward the 2010 biodiversity target and beyond. Science 325: For technical detail see Allen, R.B.; Wright, E.F.; MacLeod, C.J.; Bellingham, P.J.; Forsyth, D.M.; Mason, N.W.H.; Gormley, A.M.; Marburg, A.E.; MacKenzie, D.I.; McKay, M. 2013: Designing an inventory and monitoring programme for the Department of Conservation s Natural Heritage Management System. Landcare Research Contract Report LC1730, prepared for the Department of Conservation, Wellington, New Zealand. 5

12 disappear from down to c. 0.5% of Conservation land. Implementation of these indicators will demonstrate DOC s leadership in quantifying the status of our natural heritage, provide an opportunity to engage with stakeholders from a position of strength, and more generally allow the Department to better connect with the public. Nine principles of monitoring: Define goals Build on the past Don t be preoccupied by current perceptions Ensure comparability Utilise repeat measures Carefully establish baselines Collect interpretive data Ensure long-term commitment Commit to data management The success of this programme will be enhanced by adhering to a set of principles 11 that minimise risks. The willingness to establish and maintain monitoring systems has historically been erratic. Perhaps this is because monitoring systems are often decoupled from the core policy, planning, operational, and reporting functions of organisations. International experience suggests that support for maintaining a monitoring system will be driven in a major way by its demonstrated utility to conservation policy, planning, and management. Therefore, NHMS will only be effective if it is an essential component in DOC s performance measurement and when its results inform and improve conservation management. Effective use will also stem from linking scientific research to the interpretation of indicators and from understanding their implications for management. The Cross Department Research Project Interpreting Terrestrial Biodiversity Indicators exemplifies such a research effort. 1.2 What will happen on the ground? Trends in ecological integrity indicators at national and regional scales will be based upon timely, detailed, local measurements that can, where possible, be modelled across all Conservation lands. Periodic (regular or irregular) measurements will be used to ascertain the extent of compliance with a standard or deviation from desired trends in ecological integrity. The indicators represent the three components of ecological integrity through compositional, structural, or functional characteristics of ecosystems. When sampling ecological integrity indicators, there is also considerable merit in also collecting complementary interpretive data. For example factors that commonly influence ecosystem composition, structure, and function are disturbance, dispersal, time, soil, climate, and herbivory. This programme will specifically collect interpretive data related to invasive species impacts. Five measures (representing three NHMS indicators) were chosen by DOC 12 from a potential 41 measures, representing 18 indicators, as vital measures for early implementation through this programme to provide new and objective data with enough detail to assess conservation performance for DOC, stakeholders, and the public (Table 1). Indicators were selected (by DOC) with high policy relevance and suitability for reporting on components of ecological integrity. Each measure is relatively straightforward to determine in the field and is based 11 Allen, R.B.; Bellingham, P.J.; Wiser, S.K. 2003: Developing a forest biodiversity monitoring approach for New Zealand. New Zealand Journal of Ecology 27: Operationalisation of Vital Measures DOCDM doc. 6

13 upon the collection of consistent data at defined sites and scales. In terms of ecological integrity the field data has a focus on plants and birds. These have critical roles in ecosystems as producers and consumers respectively. The field data will allow: Composition of plant and bird species to be determined. These data will allow changes in bird species assemblages to be quantified (NHMS Measure 5.1.2; Table 1) and represent trends in the richness and diversity of the avifauna. Structure of plant and bird populations to be evaluated. The size-structure of major plant species (Measure 5.1.1) will be used to represent the maintenance of dominant plant species. Function of plant and bird communities to be characterised. Plant species can be pooled by foliage palatability, litter decomposability, or seed dispersal mode to represent functional processes (Measure 5.1.3). Interpretive field data collected by the programme focuses on two measures, exotic weeds and pests, widely thought to threaten ecological integrity 13 and will allow: Distribution and abundance of mammal pests to be evaluated (Measure 2.2.2). For example, the occupancy and abundance of possums through trapping Distribution and abundance of exotic weeds to be evaluated (Measure 2.2.1). This would be done on the same sites that native plant distribution and abundance are measured. In this programme field data are collected with sufficient detail to reliably estimate each measure. The field data can be recollected at relevant time scales (1 10 years) and measures recalculated for reporting and assessing management effectiveness. While some might claim New Zealand has abundant existing ecological data, much of this is qualitative or spatially and temporally limited. Generally there is insufficient detail for the DOC vital indicators or Why do we need new data on ecological integrity? Existing information is historical (e.g. VCM), or Lacks sufficient detail (e.g. EcoSat), or Is spatially incomplete (e.g. LUCAS) underpinning data are out of date. Where current data do exist frequently it is from a subset of Conservation lands. On the other hand, future technological improvements, such as sensor networks, may advance field data collection 14 making this programme more effective and efficient. This programme must remain aware of, and harmonise with, any new technologies adopted. Maps, or spatial representations of measures, could extend observations to give complete coverage of the landscape not only as simple representations for communication with the public, but also to identify areas requiring action and as tools for evidence-based policy. 13 Allen, R.B.; Lee, W.G. (Eds) 2006: Biological invasions in New Zealand. Springer, Heidelberg & Berlin. 14 Rundel, P.W.; Graham, E.A.; Allen, M.F.; Fischer, J.C.; Harmon, T.C. 2009: Environmental sensor networks in ecological research. New Phytologist 182:

14 Spatial representation of these measures for such uses has not so far been undertaken but will only be useful if highly predictive models, with associated errors, can be developed. Table 1. Priority indicators and measures within an inventory monitoring programme to evaluate progress towards maintaining ecological integrity 15 Indicator Measure Match with historical data 16 Objective: Reduce the spread and dominance of exotic/invasive species Exotic weed and pest dominance (Indicator 2.2) Exotic weed and pest dominance (Indicator 2.2) Distribution and abundance of exotic weeds and pests considered a threat Weeds (Measure 2.2.1) Distribution and abundance of exotic weeds and pests considered a threat Pests (Measure 2.2.2) Well matched to historical forest vegetation data and, to a lesser degree, other vegetation data Abundance measures well matched to some recent pest data but not to large amounts of unorganised historical data. Distribution measure (occupancy) is new data 17 Objective: Maintain/restore ecosystem composition Composition (Indicator 5.1) Composition (Indicator 5.1) Composition (Indicator 5.1) Size-class structure of canopy dominants (Measure 5.1.1) Assemblages of widespread animal species Birds (Measure 5.1.2) Representation of plant functional types (Measure 5.1.3) Well matched to historical forest vegetation data but poorly matched to other vegetation data Basic features of historical 5-minute bird count retained to allow for comparisons of the contemporary data with historical data. Well matched to historical forest vegetation data and, to a lesser degree, other vegetation data 1.3 How does this programme support the Department? Current position DOC undertakes the largest amount of biodiversity inventory and monitoring in New Zealand. Most of this is relates to practical, management-focused activity. Monitoring varies widely in scale, objectives, biodiversity indicators measured, time frames to deliver projects, and methods. The challenge for NHMS is to transform these efforts into a standardised system that is responsive to needs across DOC at all management levels. A key component will be line management accountability to ensure the capture, quality, storage, analysis, maintenance, and implementation of monitoring results. A recent review has confirmed previous findings that DOC monitoring projects placed an emphasis on the collection of 15 Lee, W.G.; McGlone, M.S.; Wright, E.F. 2005: Biodiversity Inventory and Monitoring: A review of national and international systems and a proposed framework for future biodiversity monitoring by the Department of Conservation. Landcare Research Contract Report LC0405/122, prepared for the Department of Conservation. 16 Biological invasions are a major cause of indigenous biodiversity loss. 17 Species composition, functional groups, and structural complexity represent aspects of ecosystems. 8

15 monitoring data with little attention paid to data archiving and analysis, and limited presentation and updating of findings Improvements sought The National Biodiversity Monitoring and Reporting System (part of the NHMS) contains three components that are currently under development: National Ecosystems and Species Managed Ecosystems and Threatened Species Reference Sites They can be distinguished by their objectives, scale of operation, type of measures implemented, and target end-users. Each includes indicators, measures, and reporting tools. These three components collectively contribute to measuring ecological integrity. The focus of the National Ecosystems and Species component is to measure and report on the status and trends in ecological integrity at regional and national scales in order to assess progress towards defined outcomes. This means that DOC will monitor across the Conservation estate and not just where management activities are currently undertaken. Aspects of the Lee et al. (2005) 19 framework not addressed in this Inventory and Monitoring Programme, but part of the National Ecosystems and Species component, are focused on the status and trend of selected indicator species. These are chosen using specific criteria and contribute data on status and trend for a small number of species that have been previously reported. 20,21 The selected indicator species information complements that for Managed Threatened Species because it provides data about the status and trend of particular indicator species across their ranges, not just for managed populations. Some factors not directly addressed in this programme but known to influence ecosystems such as disturbance (e.g. fire) are also collected as part of the wider national system. Monitoring of Managed Ecosystems or Managed Threatened Species will include a subset of indicators and measures across managed sites consistent with this programme. Measuring the impacts and outcomes of management outputs, in a way that is compatible with the National Ecosystems and Species component, will be included in development of the optimisation process for Managed Ecosystems or Managed Threatened Species. This will include building upon indicators already in use, as a standard assessment framework, for several management initiatives (e.g. Operation Ark, Mainland Islands, Arawai Kakariki Wetlands). When the programme outlined in this report is combined with Managed Ecosystems or Managed Threatened Species monitoring, DOC will have an integrated platform for assessing status 18 Gautam, M.; Westbrooke, I.; Rohan, M. 2008: Assessment of biodiversity monitoring projects, Department of Conservation. Research and Development, Department of Conservation. 19 Lee, W.G.; McGlone, M.S.; Wright, E.F. 2005: Biodiversity Inventory and Monitoring: A review of national and international systems and a proposed framework for future biodiversity monitoring by the Department of Conservation. Landcare Research Contract Report LC0405/122, prepared for the Department of Conservation

16 and trend in ecological integrity as well as reporting on the effectiveness of management. Further understanding and interpretation is being obtained through intensive monitoring and research at a few Reference Sites. A trade-off between detail and scope or coverage is a practical limitation faced by all monitoring programmes. Using a nested hierarchy (see Figure below) DOC can collect information with different levels of scope and coverage. Tier 1. The lowest level represented in the diagram above is monitoring that has broad spatial and temporal applicability (e.g. National Ecosystems and Species). This level provides geographic and interpretive context for data collected for Managed Ecosystems or Managed Threatened Species (Tier 2 and Tier 3). Tier 2. The middle tier of the diagram indicates enhanced investigation effort that is limited in spatial and temporal extent but focused on management-driven impacts and outputs (Managed Ecosystems or Managed Threatened Species). Tier 3. Monitoring conducted intensively at a few sites (e.g. Waitutu, Eglinton, Craigieburn). These sites are useful for understanding interactions and allowing the development of predictive models. These intensive monitoring areas may become reference sites or benchmarks against which other sites may be compared. Intensive investigations aid in interpreting Tier 1 and Tier 2 data. DOC requires a General Manager, with appropriate accountabilities, to act as an advocate for the National Biodiversity Monitoring and Reporting System. The function would include establishing and delivering the three components, including protocols, training, data curation, monitoring related research and reporting products; and liaising with external parties. This will be to ensure that the system (and this programme) is integrated within the Department s structure and resourced appropriately. 10

17 1.4 How could the programme be expanded? Increased spatial coverage This programme can be a basis for a systematic assessment of biodiversity across the entire New Zealand landscape. By extending the sampling universe to cover all lands, New Zealand will be in a better position for environmental reporting, assessing the status of ecological integrity, and evaluating the effectiveness of conservation management. This will require considerable integration amongst governmental and private parties, involving key agencies such as the Ministry for the Environment who has greater involvement in environmental management on private land. The programme design is also appropriate for, and can readily be modified to, measurement and reporting at local scales by increasing the sampling intensity appropriately. On this basis, existing vegetation plots using the same methodology, where objectively located, may be used to generate the same vegetation measures outlined in this programme for DOC s Managed Ecosystems. Similarly, when locations are being considered for new intensive local reporting, or evaluation of conservation management (be it by, for example, DOC, regional councils, or non-governmental organisations), consistency across as many jurisdictions and scales as possible is desirable to achieve advantages from the measures outlined in this report. Incorporating intensive local samples into national-scale reporting requires appropriate statistical analyses Improved interpretability A high priority is to effectively demonstrate the utility of the programme this will take at least a decade and depend on the use of the indicators in DOC policy, reporting, planning and operational activities. The programme will benefit from expanding the breadth and quality of interpretive data (e.g. climatic variation). Soil fertility is emerging as an important driver of ecosystem composition, structure, and function, including the impacts of invasive species. To partition out the consequences of invasive species management (e.g. pests) it would be useful to have interpretive measures of soil fertility. Given that soil fertility is hugely variable in our mountainous regions at sampling location scales, 22 there is considerable merit in adding soil fertility measurements at sampling locations. Secondarily, there is scope for measuring a wider range of NHMS indicators than considered in this programme. Although the design will be suitable for some of these, such as some biological responses to global change, it is not appropriate for others, for example representation of animal guilds. 1.5 What are the key interdependencies? Evolving international reporting requirements. Measures outlined in this programme, when applied nationally, will markedly improve the country s ability to report on Convention on Biological Diversity (CBD) Goal 1: Promote the conservation of the biological diversity of ecosystems, habitats, and biomes and Goal 6: Control 22 Richardson, S.J.; Allen, R.B.; Doherty, J.E. 2008: Shifts in leaf N:P ratio during resorption reflect soil P in temperate rainforest. Functional Ecology 22:

18 threats from invasive alien species indicators. 23 This programme should be planned to advance CBD reporting. National biodiversity efforts. The programme overlaps with aspirations of the Ministry for the Environment s (MfE) Environmental Performance Indicators (EPI) programme. Some detailed EPI indicators are in use nationally (e.g. trends in water quality indicators using the National River Water Quality Network of 77 sites), but terrestrial, operational EPI national biodiversity indicators are not available. Consequently agencies reporting national biodiversity trends either do so for part of the landscapes (e.g. forests by Ministry of Agriculture and Forestry (MAF)) or use generalised land-cover information (e.g. Statistics New Zealand). Data quality is an issue as consistent standards and methods are not employed, and data are assembled from disparate sources. The overlapping requirements of DOC, MfE, MAF, Statistics New Zealand, Biosecurity New Zealand, and local government agencies need to be harmonised through a co-ordinated effort. Complementary systems. MfE s Land Use Carbon Accounting System (LUCAS) initiative is underway and employs the same sampling framework as recommended in this programme for a national scale in which DOC is a partner. LUCAS collects data for some of the measures at most sampling locations on DOC-administered lands. For vegetation data, at least, it is critical that this programme and LUCAS are consistent and planned accordingly. The National Vegetation Survey Databank serves as the repository for DOC s vegetation data and its development needs to take account of implementing this programme and LUCAS. Interpretive ability. The utility of this programme will be markedly improved by strengthening our interpretive ability of indicators and measures. This involves collecting interpretive data (e.g. the nature and extent of DOC s management activities) and increasing our understanding of those processes influencing indicators and measures (e.g. those emerging from partnered research in the Foundation for Research, Science and Technology funded Outcome Based Investments). Emerging issues. Ecosystem services, in particular carbon has recently emerged as a potential outcome from conservation management, 24 and to some degree is accounted for by LUCAS. While ecological integrity arguably captures the services provided by natural ecosystems these services may be better quantified in DOC s National Monitoring and Reporting System based on additional compositional, structural, or functional characteristics. For example, sampling-location water yield is likely to be modelled, based on measures of species-specific leaf area and water loss characteristics Peltzer, D.A.; Allen, R.B.; Lovett, G.M.; Wardle, D.A.; Whitehead, D. 2010: Effects of biological invasions on forest carbon sequestration. Global Change Biology 16:

19 2 Inventory and Monitoring Programme 2.1 Sampling framework For efficiency all five indicator measures have been integrated to the greatest extent possible in an optimal sampling design for analysis and reporting. 25 The framework for measuring these indicators is regular, unbiased sampling of the New Zealand landscape at the intersections of an 8 8 km grid. This sampling protocol builds upon a national infrastructure established to measure carbon, vegetation structure and biodiversity the LUCAS network of vegetation plots in forests and shrublands. The sampling framework extends the 8 8 km LUCAS grid to all land administered by DOC. As most land administered by DOC is in the South Island 76.3% of the sampling locations are there (see map below). 25 For technical details see: Allen, R.B.; Wright, E.F.; MacLeod, C.J.; Bellingham, P.J.; Forsyth, D.M.; Mason, N.W.H.; Gormley, A.M.; Marburg, A.E.; MacKenzie, D.I.; McKay, M. 2013: Designing an inventory and monitoring programme for the Department of Conservation s Natural Heritage Management System. Landcare Research Contract Report LC1730, prepared for the Department of Conservation, Wellington, New Zealand. 13

20 An example of sampling locations on an 8 8 km grid applied over a section of the central South Island, including land administered by DOC and other tenures (see below). The design and methods for all measures can be applied to highly modified landscapes (land under intensive agriculture, urban areas) as readily as they can for land cover more typically designated for conservation. 14

21 Three indicator measures relating to vegetation characteristics used in this programme are based upon methods widely and consistently used in the past in New Zealand. 26 To maximise use of historical data, a rule when establishing LUCAS vegetation plots was that if there were existing, randomly located, vegetation plots within 1 km of a point on the national 8 8 km grid, the closest plot was used and remeasured, instead of establishing a new plot. The same rule will apply on establishing new sample points for DOC s Inventory and Monitoring programme and additional measures (for mammal pests and common birds) will be made at these pre-established points Stratification The sampling framework entails one primary level of stratification: land administered (or not) by DOC. The stratification boundary will not be fixed over time areas will be added requiring additional sample points and some areas may be lost. For this reason, and others, working to extend the sampling framework across the New Zealand landscape with other agencies, independent of tenure, is desirable. A second level of stratification will be determined by using digital elevation models (DEMs) to assist sampling. Estimates of slope, determined from national-scale DEMs, will be used to exclude 8 8 km grid sampling locations that are likely to be too unsafe to sample. Sampling locations for which DEMS predict slopes >65º will be excluded, although visual inspection 26 Hurst, J.M.; Allen, R.B. 2007: A permanent plot method for monitoring indigenous forests field protocols. Landcare Research, Lincoln. 15

22 (e.g. by helicopter) will also be used to confirm the exclusion of a location en route to an adjacent sampling location. As a consequence, the sampling universe needs to be specified as those lands administered by DOC with slopes 65º. If greater sampling intensities are required to monitor areas of particular interest (e.g. Managed Ecosystems), then a finer scale grid can be set that multiplies simply with the national 8 8 km grid: so that a 4 4 km grid (4 times the sampling intensity within the national framework for a stratum) and a 2 2 km grid (16 times the sampling intensity) are integrated but a 5 5 km grid or a 3 3 km grid are not. Use of finer scale grid-based sampling would be difficult to achieve in some areas of interest to DOC that, by their nature, are attenuated, such as coastal dunes and alluvial terraces. Such areas may be sampled by one of the other components of DOC s National Monitoring and Reporting System. 2.2 Methods to be used A common sampling framework is used for all five indicator measures. A GPS identifies the sample point based upon the 8 8 km national grid. The point is permanently marked and allows for repeated sampling at that point. A m (0.04 ha) area will be demarcated permanently at each location, using metal pegs so that it can be re-located, and vegetation measurements will be made within this fixed plot. Data on mammal pests and common birds are collected within a much larger ( m; 4.84 ha) area, centred on the m vegetation plot, using a design that radiates out from the edges of the central vegetation plot (see diagram below). Plot design for I&M pilot surveys Key: 20 x 20m Vegetation plot 1 x 1m Rabbit quadrat Bird count station 150m Ungulate pellet transect 200m Possum trapping line 16

23 Each sample location will be visited twice in the year of its measurement. Data for the common birds measures will be collected in spring, and data for the vegetation and pest mammal measures will be collected in summer (data for mammal pests can be collected in spring if that proves logistically simpler) Vegetation measures All three vegetation measures will be quantified using the vegetation plots. These measures will capitalise upon decades of investment in data collection, and past vegetation plot measurements will aid interpretation of trends. Weeds This measure will be based on an inventory of the vascular and non-vascular plants found within each plot. The cover and vertical distribution of each plant species will be recorded. The measure is the percentage of vascular and non-vascular plant species within the plot that are exotic. Fine-scale resolution of frequency is gained from replicated subplots. Size-class structure of canopy dominants The size structure of any trees will be determined by measuring their diameters; the size structure of saplings, by counts. Trees and saplings will be measured over the whole plot. Repeated measures of tagged trees will allow long-term determination of population trends. The height and frequency of any seedlings or herbaceous vegetation will be determined from replicated subplots. Plant functional types This measure will be based upon complete inventory of the plants found within the plot, both vascular and non-vascular plants. The measure is the percentages of species within the plot that are assigned to functional types according to (1) susceptibility to introduced herbivores; (2) provision of food sources for birds; and (3) vulnerability to climate change. Complementary ways of interpreting the data are the number of species within functional types or the occurrence of given functional types within different management regimes. The vegetation plots will be measured over summer to obtain a maximum estimate of plant diversity in plots and to minimise seasonal biases. This timing is to ensure that flowering or fruiting material of most plants can be detected for accurate identification. Plots at low altitude northern sites could be measured from late October, whereas high altitude southern sites should not be measured before mid-december. All measurements in any year need to be completed by late March. There are 1254 LUCAS plots in New Zealand s forests and shrublands that use the same methods as this programme. LUCAS plots were measured from 2002 to 2007 and are being remeasured currently, so data on trends in forests and shrublands will soon be available nationally for these vegetation types. Of the 1254 LUCAS plots in forests and shrublands, 874 (69.7%) are on land administered by DOC. About 70% of these plots are suitable for reporting the three vegetation indicator measures. Coverage of land currently administered by DOC will require an additional 433 vegetation plots to be established (although some of these locations are >65 o ) these will primarily sample locations with cover other than forest or shrubland, according to the Land Cover Database. Repeated measurements of the LUCAS plots occur at 5-yearly intervals. This is time interval is adequate to detect change for the three vegetation indicator measures. 17

24 A m vegetation plot being measured in non-woody vegetation is shown above: alpine grasslands, Acheron River catchment, inland Marlborough (Photo: Kate McNutt, DOC) Mammal pests measure This measure will provide spatial and temporal patterns in the abundance and distribution of all deer, feral goats, European rabbits, and brushtail possums (with the potential to add other species such as hares). Deer and feral goats Their abundance will be determined by counting faecal pellets to provide a Faecal Pellet Index (FPI). 27 The FPI has a positive linear relationship with deer abundance. 28 This method has been used widely, over decades, to provide indices of the abundance of deer and, to a lesser extent, feral goats. FPIs will be derived from counts of intact faecal pellets inside 1-m-radius circular plots, along each of four transects. Determination of the distribution of deer and feral goats cannot rely on FPIs because it is difficult to distinguish the faecal pellets of major mammals (i.e. deer, goats, chamois, Himalayan tahr, and feral sheep). Instead distribution will be informed by: expert opinion of 27 Forsyth, D.M. 2005: Protocol for estimating changes in the relative abundance of deer in New Zealand forests using the Faecal Pellet Index (FPI). Landcare Research Contract Report LC0506/027 by Arthur Rylah Institute for Environmental Research for the Department of Conservation. 24 p. 28 Forsyth, D.M.; Barker, R.J.; Morriss, G.; Scroggie, M.P. 2007: Modeling the relationship between fecal pellet indices and deer density. Journal of Wildlife Management 71:

25 DOC staff as to presence/absence around a sampling location; national maps of mammal pests distribution; 29 and helicopter surveys centred on the sampling location. Rabbits The abundance and distribution of rabbits at each sampling location will likewise be estimated using faecal pellet counts in plots. Additional information on rabbit distribution will be obtained from the presence of rabbit pellets in any of the FPI plots at the sampling location. Possums The abundance and distribution of possums will be estimated at each sampling location using the Trap-Catch Index (TCI). This method is in widespread use and was adopted by the National Possum Control Agencies in Trap-lines will be set along the same transects used to derive FPIs. In the first year of measurement, possums will be trapped along the lines over two successive nights, and data from each night s sampling will be kept separate. An evaluation based on inferences from a single night s versus two nights trapping will be made after the first sampling effort with a recommendation about whether reliable possum information can be obtained from one night sampling only. Additional information on possum distribution will be obtained from the presence of possum pellets in any of the FPI plots and rabbit plots at the sampling location. A 5-year frequency of monitoring for deer, feral goats, possums and rabbits is sufficient for reporting purposes. 31 If large increases or decreases in rabbit abundance were expected (e.g. due to introduction of a biocontrol agent) then annual monitoring could be conducted Common-birds measure The species richness, occupancy and abundance of common birds will be estimated using a 10-minute bird count (10MBC). A modified version of the previously widely used 5-minute bird count, 32 our method incorporates a repeated sampling design and distance sampling procedures to allow for more accurate estimates of species richness, occupancy and abundance. Field sampling on the DOC national indicator grid will proceed, in each year, from north to south and east to west to follow the spring season. At each sampling location, 10MBCs will be conducted at five count stations. Each count station will be sampled twice, by two independent observers on the same day. During the first five minutes of the 10MBC, the observer will record within each 1-minute period: species identity, the number of individuals, the cue (auditory/visual) observed, bird behaviour, and distance from the count station to each bird (recorded in fixed distance intervals, see diagram below). This detailed information will be used to calculate estimates of species abundance. For the second five minutes, the observer will record any additional bird species observed (seen or heard) within each minute. 29 Kappers, B.; Smith, L. 2009: New Zealand Biodiversity Data Inventory (BDI) DOC. 30 National Possum Control Agencies 2008: Protocol for possum population monitoring using the trap-catch method. National Possum Control Agencies, Wellington, New Zealand. 34 p. 31 Norbury, G.; Warburton, B.; Webster, R. 2001: Long-term monitoring of mammalian pest abundance in Canterbury. Landcare Research Contract Report LC0001/144, prepared for the Department of Conservation. 62 p. 32 Dawson, D.G.; Bull, P.C. 1975: Counting birds in New Zealand forests. Notornis 22:

26 Estimates of species richness and occupancy derive from repeated sampling. Habitat data will be collected to aid interpretation of the common birds measure. Assessing land cover in relation to a bird count station Key: Bird count station 100m 20 x 20m reduced RECCE plot 11-40m buffer 40m m buffer 2.3 Feasibility of the methods Field experience in sampling vegetation in m LUCAS forest and shrubland plots showed that of 1372 sampling locations nationally, 118 (8.6%) were not sampled (giving 1254 established) either because access to a site was denied or because the site was too steep to be sampled safely (see earlier). A conservative estimate is that 5% of sampling locations in forest and shrubland on public conservation land are too steep to sample vegetation safely, but in grasslands the percentage could well be higher; steep sites with woody vegetation are safer to sample than sites without woody vegetation. It is likely that there will be a higher percentage of sampling locations that are too steep to sample safely for mammal pests and common birds because they are measured at a much larger scale (4.84 ha) than the vegetation measures (0.04 ha). To maintain safety and also ensure that sampling can take place in some locations, the 45º bearing from a vegetation plot edge along which the 150-m deer and goat transects, the 200-m possum trap-lines, and the bird count stations at the end of the possum trap-lines can be moved between 25º and 65º for safety. If parts of the m plot are too steep to work on safely then the vegetation plots can also be offset provided that 75% of the original area is still sampled Vegetation measures The vegetation measurements have been already been widely tested in New Zealand s forests and shrublands. A field assessment of these methods in early 2009 demonstrated that the same measurements can be used in other non-forest vegetation cover types. A three-person field team is required for a full day to collect the data from each vegetation plot. The average time required to measure vegetation plots is 25.4 person hours. Data for the derivation of all three vegetation indicator measures are collected concurrently and this leads to economies. 20

27 From our experience, of the plant taxa distinguished in the field, collections will be needed for up to 45% of the vascular plant species and up to 100% of the non-vascular plant species in every plot measured, so that they can be identified accurately in laboratories. Curation, storage, and identification of this material, together with updating of data sheets, all require consideration in monitoring budgets. A constraint is that there are very few field people with sufficient skills to identify all non-vascular plants Mammal pests measure The techniques used to estimate the distributions and abundances of possums, deer and feral goats have well-established, field-tested existing protocols. Estimating rabbit distribution and abundance is the least costly element of the measure because it takes relatively little time. The cost of estimating deer and feral goat abundance in the 2008/09 field assessment varied among sampling locations according to steepness of the terrain, vegetation type, and the number of pellets encountered. Helicopter-based surveys to determine which ungulate species are present/absent will be conducted during the first year of the programme to determine the distributions of deer and goats at sampling locations. If, after the first year, the information from local experts and databases is defensible (experience to date suggests it is not), then these less costly option will be used Common-birds measure As for the mammal pest measure, steep terrain is a constraint to obtaining data at sampling locations for common birds and it is likely that there will be sampling locations at which it is possible to obtain data for vegetation measures but not for common birds. Dense vegetation can also be a constraint to obtaining accurate data at count stations for use in distance measures, which are used to estimate abundance. This can be overcome, to some degree, by using estimates of distance in fixed classes and this approach can also be used for auditory data. All bird data for a sampling site should be collected in a single day and completed by 1300 hours, with additional habitat information collected at each count station by one observer after completing the bird count. For a 1-day design, to sample all 300 locations that need to be sampled each year, at least 13 teams working nationally would be required, with two bird observers in each team, and with each team visiting three sampling locations per week. Bird survey teams will need to have excellent bird identification skills (sight and especially calls). Automated bird recording devices are currently being considered as an alternative to direct field survey methods for monitoring bird populations and communities. This method has potential advantages: data could be collected simultaneously from a large number of sampling locations for a longer period than direct observation permits, and non-specialist field teams could set up and collect the devices. For the common birds measure, even if software to determine species was developed, processing of the tapes would only quantify two components of the measure (species richness and occupancy) but not abundance. Therefore automated recording devices are not currently recommended for the programme. 21

28 3 Implementation 3.1 Training Field trip planning, management and coordination The field team co-ordinator and his/her support staff need to bring a background in project management. Additional training in team leadership and co-ordination skills should be provided for relevant personnel Field team logistics and operating Prior to the start of each season, all field staff should be briefed on the logistical and operational protocols for field trips. Training should be provided to ensure that field staff have knowledge of protocols for health and safety and risk management. Field staff should also gain first-hand technical experience with handling all the relevant equipment. All field teams should receive training on how to record time-budget and operational data required for logistical planning and budgeting in the future. General protocols for recording and checking data in the field should also be established. Where several field methods are being implemented by one field team, the teams should be given guidelines on how to prioritise their field effort when time-constraints occur (e.g. due to poor weather conditions) Vegetation survey skills The vegetation measures require skills in establishing and measuring permanent m vegetation plots, which are part of DOC s standard operating procedures. These plots are used by LUCAS, and there are many people nationally capable of conducting these measurements to a reasonable standard. Field staff will need to demonstrate competence in making accurate and repeatable measurements of data such as recording plant heights, diameter measurements, counts of stems, cover estimates, and accurate metadata, including estimates of slope, aspect, etc. Accurate identification of plants in the field is a key skill that underpins all vegetation measures. It is also necessary to make high-quality collections that will enable later determination from preserved material. Therefore, each field team needs at least one member with a high level of aptitude in plant taxonomy and the ability to distinguish different vascular plants in the field. Quality assurance audits are needed to ensure that high consistent standards apply across teams in vascular and non-vascular plant taxonomy. DOC needs to convene annual training courses for designated field team members, with some focus on determining plants and giving updates on new systematic treatments, and in particular improving skills in field and laboratory identification of non-vascular plants. There are opportunities for DOC s specialist botanists at Conservancies to raise the standard of field teams identification skills and this can be built into Conservancies annual business plans. 22

29 3.1.4 Bird survey skills The species identification skills required for the bird surveys require a long-term and intensive training programme. Prior to the start of the field season, all bird recorders should attend a refresher course that will focus on key species that people are likely to have problems distinguishing (e.g. finches) and training observers to identify calls from species that have distinct regional dialects (e.g. bellbird). DOC s existing playback system should be developed further to allow training in distance estimation to auditory cues in a range of environments. Observers should also be taught standardised codes for species identity, bird behaviour (flying, movement towards/away from observer), cues (seen/heard) as well as distance measures. Basic skill training in vegetation survey methods for measuring and classifying topography as well as estimating percentage cover for different vegetation layers should also be given Mammal pest survey teams The skills required to conduct the mammal-pest field sampling are relatively straightforward. Someone with demonstrated field skills and who has completed the field operative training course run by Eurotafts International for the National Possum Control Agencies 33 would have the skills required to conduct the possum monitoring and, with an additional day of fieldbased training, should be able to conduct the ungulate and rabbit monitoring. 3.2 Scheduling Prior to implementation of the programme A scoping exercise is necessary to determine the availability of the field skills and personnel required to implement these methods at the national scale. Preliminary surveys, based on a pilot study, indicate that shortages in personnel with the relevant skills for bird, non-vascular and grass species identification are likely to be a problem. Implementation of relevant training schemes to build the skill base required should, therefore, be a priority in the short term, with ongoing training to maintain it Six months prior to field season A work plan should be developed to ensure cost-effective co-ordination of field teams moving among sampling locations. This should include an assessment of access issues (e.g. via private land), feasibility of implementing surveys at each location, as well as specific field gear requirements (e.g. raised possum traps where there is a risk of by-catch). Logistic planning will also be required to determine local service providers (e.g. accommodation and helicopter transport) as well as location-specific operational planning (e.g. maps for navigation and route planning, uploading GPS co-ordinates, data from previous surveys). 33 For further details see: 23

30 Protocols should be developed for health and safety, risk management and other report requirements (e.g. environmental sustainability, by-catch reporting) One month prior to field season The relevant training workshops (for field team leadership, logistics/operating and survey methods) should be run approximately one month prior to the start of the field season. The field teams should then assist with final field team preparations (e.g. field gear, finalising travel/accommodation bookings) Field season The field co-ordinator and his/her support staff will need to oversee the daily logistic requirements of field teams as well as review the work plan at regular intervals in response to any changes (e.g. resulting from adverse weather conditions). During this period, he/she will also need to ensure that data management protocols are maintained Post-field season Field teams should assist with datasheet checking and entry as soon as possible after completing the field season. Any plant or pellet specimens requiring identification should also be processed during this period. Data captured electronically (e.g. GPS co-ordinates and photographs) should also be edited and filed as appropriate. Any reporting requirements (health and safety, environmental sustainability, trap by-catch etc.) should also be met. 3.3 Data management Data recording Waterproof data sheets and protocols should be provided to facilitate efficient and transparent processes for data recording in the field. (Electronic capture of field data is not currently feasible due to problems with battery life and waterproofing, but future technology may well replace field sheets.) Data quality should be maintained by providing appropriate training, particularly where field teams will be required to implement a large number of field methods at a single location on one visit Processing specimens Post-field-trip processing of plant and pellet specimens collected in the field requires specific protocols for labelling, identification, and updating data-sheets (and electronic databases, if appropriate). 24

31 3.3.3 Data storage Both the field sheets and the data they contain need to be captured in electronic databases. Sheets should be scanned (e.g. in portable document format) and archived so that they remain accessible indefinitely. Data captured electronically in the field (including GPS co-ordinates and photographs) will need to be downloaded using systematic protocols to ensure these data are accessible. The vegetation data should be stored in the National Vegetation Survey Databank (as specified in DOC s data archival SOP), with a complementary database for information on processed plant specimens. The bird data could be archived in a modified version of the existing historical 5MBC database. Appropriate databases would need to be developed for the mammal pest data and for storing the operations and logistics data to aid the field season planning process in subsequent years Field survey audit Quality control of field surveys can be achieved through audit. This is a relatively simple task for sessile plants, and based upon remeasurement of a random sample of vegetation plots after the field party has finished (currently conducted on LUCAS plots by DOC on behalf of MfE). For mammal pests and birds, it will be difficult to complete an appropriate audit of field measurements without the field team being aware of an audit. A combination of measurement and recording tests during training and a resurvey of locations using doubleobserver surveys at the time of measurement should be applied. A 10% audit should be undertaken in the first year of the programme and used as a basis for setting audit level and quality standards for subsequent years Data checking Protocols should be in place for data checking both in the field and during the storage process. When the monitoring team returns from a sampling location the data sheets should be checked to ensure that all required fields have been completed. If some required fields have not been completed then the monitoring team must complete them and could require the relevant member of the team returning to the sampling location. Modern databases help minimise the potential for transcription errors (e.g. by constraining input possibilities) and can have customised self-checking and random auditing procedures. The potential for dataentry errors can be further minimised by having data entered by two operators ( doubleentry ) and automatically checking to determine which cells differ (i.e. quality control). Data entry by the field team staff is advantageous, allowing them to see the mistakes that are being made and encouraging them to raise their game Database integration Front-end software, perhaps based in GIS (Geographic Information Systems), should be developed to facilitate efficient access to, and integration of, information from all programme databases and other relevant databases (e.g. historical pest control, pellet count and bird count databases). This should include access to relevant GIS, logistics, and operational information as well as databases providing species names, traits (e.g. palatability for plants, feeding guilds for birds), and land management. 25

32 3.3.7 Documenting changes Any changes to sampling protocols, datasheets and databases must be clearly documented and rules should be established for managing such changes. This is particularly important where back-dating changes may also be required for measuring change in the parameters reported for each measure Database access and use Protocols need to be developed for data access, processing and use, and whether the user is required to cover these costs. Where IMP data are reported in the scientific literature or in technical or contractual reports, protocols for determining whether relevant DOC staff should be included as authors should also be considered Organisational structure An issue with DOC conducting nearly all of the fieldwork would be a lack of capacity to conduct sampling during the relatively short field period. The major problem with DOC outsourcing virtually all of the work is that DOC would not develop capacity/expertise in areas that are critical to the organisation in a wider sense. There is also a risk that DOC would lack ownership of the project at key levels within the organisation if nearly all of the work was outsourced. It is desirable for DOC to have staff at all levels of the organisation involved in delivering the programme. Based on the skills and tasks outlined in the previous section there are a number of programme delivery options DOC could consider, e.g. National-, Regional- or Conservancybased models (or a combination thereof) using DOC staff or a mixture of DOC staff and contractors. Regardless of the option selected, to ensure that the programme is integrated within the Department s structure and resourced appropriately it is essential to have a General Manager (GM) with appropriate accountabilities to establish and have oversight of delivery of all components. The programme would need to have a Level 3 Manager who regularly reports (e.g. quarterly) to his/her respective Senior Management Team (SMT). Such a relationship should help ensure that: (1) the resources required to implement the programme are communicated to the SMT; (2) any major problems in implementation are quickly communicated to the SMT; (3) programme results are communicated annually to the Executive Leadership Team (ELT) by the accountable GM supported by the Level 3 Manager. The Level 3 Manager would have the responsibility and authority to organise the work required to deliver on the agreed objectives and budget. The annual budget should include a target number of sampling locations to be monitored. Key responsibilities suitable for national or regional coordination include: Identifying the field locations to be sampled in any year Administering contracts for fieldwork to be conducted (where required) Managing training for field monitoring teams and auditors Managing the auditing of field monitoring teams 26

33 Ensuring that field sheets are completed before contractors receive final payments (where required); overseeing quality assurance of field data (including entry and curation) Conducting statistical analyses and producing annual reports. Contractors could be used to assist with some of these tasks (e.g. training and data entry) but the overall responsibility for delivering the programme must reside with the delegated Level 3 Manager Key responsibilities suitable for conservancy or area coordination include: Overseeing training of Conservancy/Area staff Conducting random audits of field monitoring teams Liaising with field monitoring teams to ensure access to sampling locations (e.g. with helicopter companies and landholders) Ensuring that field monitoring teams have appropriate permits (e.g. to set possum traps and to land in remote areas) Auditing will require some staff to be fully trained and to travel to the sampling location with the monitoring team to evaluate the standard of data collection and recording Undertaking the field monitoring would be the most labour intensive and expensive component of this project. Multiple monitoring teams would need to operate simultaneously within the field season. There are a number of options for delivery of field monitoring. The preferred option should take account of the skills and scheduling requirements previously described. Given the current DOC organisational structure Conservancy-based teams (using a combination of Conservancy staff and contractors/area staff) supported by Regional or National office may be the most appropriate option. If the option of making use of contractors rather than DOC staff was selected then it may also make data collection standards more enforceable : in particular, we recommend that contractors should be fully paid after the field sheets have been approved and they have passed any random audits. However, this could also be enforced through oversight provided by the Region or National office. Key responsibilities suitable for the field monitoring team leader (or contractor) include: Ensuring that all staff receive the requisite training to undertake the monitoring methods to the required standard Ensuring the required permissions have been gained to undertake the field monitoring at each sampling location (in consultation with Area Office staff) Organising and pay for transport to and from the sampling locations Undertaking the field monitoring to the required standard, including random audits There is a role for co-funding and in-kind contributions from other agencies in the proposed structure. Research institutes can make significant contributions to the analytical methods and interpretation (e.g. via Foundation for Research, Science and Technology funded Outcome- Based Investments). 27

34 Fine -tuning of the organisational structure will be required. Any structure that is adopted should be regularly reviewed to identify and rectify organisational inefficiencies. 3.4 Evaluation of costs Total field costs A programme designed with 1311 sampling locations (i.e. points on DOC-administered lands with a slope of 65 ), which implements all five measures in full, will cost DOC c. $4.5 million per year or c. $22.3 million per 5-year sampling period (see Table 2). Reducing the maximum slope sampled by 10 o for safety does not markedly reduce the number of sampling locations. Without an estimated contribution of $8.4 million per 5-year sampling period from MfE (which covers costs for vegetation measures at LUCAS sampling locations), the total costs would be substantially higher, amounting to $6.2 million per year or $30.7 million per 5-year sampling period. These are the costs to collect the data, process the field samples, and enter the data. Table 2. Summary of total costs for field survey effort (assuming 1311 sampling locations nationally) per 5-year sampling period. These estimates assume that the vegetation survey costs at all LUCAS sampling locations will be covered by an in-kind contribution from MfE. Sampling locations Birds Mammal pests Vegetation NON-LUCAS (number = 397) $1,674,943 $7,335,369 LUCAS (number = 914) $3,856,166 $9,430,652 Total (number = 1311) $5,531,109 $16,766,021 Approximately 25% of the total cost (assuming in-kind contribution from MfE) will be associated with the bird survey effort. Labour costs for the vegetation and mammal pest ground surveys will be similar, although operating costs for the mammal pest surveys will be approximately double those for the vegetation surveys. The higher operating costs for the mammal pest surveys are required for the aerial surveys and transportation of possum trapping gear. We estimate the costs of running training workshops for all field teams at the start of each field season will amount to c. $180,000. Undertaking the bird measurements on all sampling locations, Mammal pests Vegetation on LUCAS sampling locations, and Mammal pests Vegetation on non-lucas sampling locations will require 13.7, 9.9, and 10.4 Full-Time Equivalents (FTE is 1700 hours per year) respectively. This gives a total annual FTE requirement of 34, although this, in part, utilises existing staff. DOC could introduce the programme measures incrementally and use this time to progressively reallocate resources from other activities Clearly the cheapest option would be to measure the non-lucas vegetation plots and obtain three measures for land administered by DOC (see Table 3). The other two measures need to be undertaken at all sampling locations and add considerable cost. 28

35 Table 3. Summary of cumulative costs for field survey effort for 5-year sampling periods. Cumulative costs reflect minimum cost to maximise the number of measures Measure added Number of locations Cumulative cost per 5-year period 3 vegetation measures on non-lucas plots 397 $3,239,123 $647,825 Cumulative cost per year Birds 1311 $8,770,232 $1,754,046 Mammal pests 1311 $22,297,130 $4,459, Field costs per sampling location The primary cost for all the ground surveys will be time taken to travel to and around the sampling location and associated operating costs (Appendix 1). By integrating the mammal pest and vegetation survey effort at each sampling location, rather than implementing these as two independent surveys, we estimate that travel costs will be reduced by c. 40% per sampling location. The additional time required to cover periods of adverse field conditions also represents a significant cost. Based on the LUCAS experience, we anticipate that this will increase the time taken to survey each sampling location by c. 30%. The proportion of time spent collecting data per sampling location will be relatively high for the mammal pest and vegetation survey effort (compared with the bird surveys), because of two major costs: non-vascular plant specimen identification ($2,000) and mammal pest aerial surveys. Logistical support and co-ordination for the field teams will also be relatively high for the mammal pest survey (compared with the bird and vegetation surveys) due to the extra effort required to liaise with local DOC staff (to determine the type of trapping equipment required, e.g. ground v. raised traps) and obtain the relevant access as well as prepare and transport the relevant gear Administrative support and data management costs Additional major costs not included in the budget estimates are project management, administrative support and data management personnel required to implement the IMP. Approximately one FTE will be necessary to carry out the routine data analysis and data processing to produce the relevant reporting measuring using routine algorithms. There are clear opportunities to engage DOC science staff. During the set-up phase, approximately one FTE will be required for database development. 29

36 4 Pathway to use This programme to develop and apply priority indicator measures will allow DOC to report on ecological integrity and strengthen the Department s intervention logic through four key uses. It will be possible to provide the first national assessment of ecological integrity measures, and related threats, at the end of the first measurement with subsequent measurements establishing trajectories of ecological integrity and the effectiveness of DOC s management. Selected examples are demonstrated below using the limited data currently available. The uses DOC makes of this programme will serve as a guide for equivalent regional-level biodiversity assessment, e.g. by regional councils. Not only should regional- and Conservancy-level reporting use the data from this programme, but regional authorities should be supported to use the same methods for more intensive local reporting. 4.1 National and regional reporting of status and trend in ecological integrity The vegetation indicator measures provide a systematic basis for Convention on Biological Diversity, State of the Environment, Montreal Process, and DOC s annual reporting. For example, the Convention on Biological Diversity requires reporting on trends in exotic species so that potentially key targets can be met (control threats from invasive alien species). The early 2009 trial assessment for this programme can address the question How weedy are the landscapes DOC manages? Unbiased sampling on New Zealand s forests shows that they have a low proportion of exotic plants in them (see figure below), comparable with levels of invasion in some North American forests. 34,35 In contrast, the proportion of exotic plants in New Zealand s grasslands is 10 times greater than that in forests, and more than double the proportion in the most invaded grasslands in the western USA. 36 As our knowledge of weed impacts grow reporting can focus on those species capable of transforming ecosystems. 34 Stohlgren, T.J.; Chong, G.W.; Schell, L.D.; Rimar, K.A.; Otsuki, Y.; Lee, M.; Kalkhan, M.A.; Villa, C.A. 2002: Assessing vulnerability to invasion by nonnative plant species at multiple spatial scales. Environmental Management 29: Huebner, C.D.; Morin, R.S.; Zurbriggen, A.; White, R.L.; Moore, A.; Twardus, D. 2009: Patterns of exotic plant invasions in Pennsylvania s Allegheny National Forest using Forest Inventory and Analysis plots. Forest Ecology and Management 257: For further details see: 30

37 The percentage of species exotic in an unbiased national sample from three land-cover classes (6 plots in each class). 4.2 Informing prioritisation for resource allocation on conservation lands The indicator measures generated from this programme can potentially inform DOC s prioritisation for resource allocation nationally and regionally. For example, the current selection of best examples of ecosystems for intensive management is heavily dependent on expert opinion and would be advantaged by objective data. In addition, DOC requires accurate information on the distribution and abundance of mammal pests to determine priority areas for management and, over time, assess the effectiveness of its management. In the current absence of data on deer abundance, opposing claims are made. 37,38 It will be possible to answer the question: how much of the New Zealand landscape has abundant populations of deer? Across trial random sampling locations nationally, deer and feral goats were abundant in at most two (i.e. 11%) locations (see diagram below). Deer were either absent or at very low abundances in over half of the sampling locations and most of these were shrubland or grassland. DOC will be able to answer whether this is a result of its own control efforts or as a result of commercial helicopter hunting in these locations. DOC will also be able to address public concerns about whether it is working to control deer in areas where they are abundant and how much of its current and past research on their 37 NZ Deerstalkers Association 2007: Preservationists scaremongering over big game management Forsyth, D.M.; Barker, R.J.; Morriss, G.; Scroggie, M.P. 2007: Modeling the relationship between fecal pellet indices and deer density. Journal of Wildlife Management 71:

38 effects derives from areas where they are abundant. Unbiased information provided from a national assessment will enable cost-effective control and research on deer impacts. Indices of deer and feral goat abundance from an unbiased national assessment of forests, shrublands, and grasslands (18 points from an 8 8 km grid: ). 4.3 Evaluating the effectiveness of management and policy The programme will provide context to achievements at DOC s intensively managed sites throughout the country and assess whether intensively managed areas often restore ecological integrity. The country has a long history of such assessments particularly through the use of control and treatment areas although their ability to demonstrate management effectiveness has been limited. 39 We believe the spatial and temporal replication from this programme will overcome some of these limitations. For example, there is a widespread perception that regeneration of dominant tree species is failing because of browsing by deer 40 and feral goats, at local and national scales. An unbiased assessment of size structures of forest trees enables evaluation of the maintenance of indigenous dominance, and can focus on species with particular functional attributes, such as species that are highly palatable to deer and goats. 39 Allen, R.B.; Bellingham, P.J.; Wiser, S.K. 2003: Developing a forest biodiversity monitoring approach for New Zealand. New Zealand Journal of Ecology 27: Bain, H. 2007: Wild deer like possums on stilts. Forest and Bird 325:

39 Māhoe is a widespread, highly palatable tree. An unbiased assessment of forests throughout New Zealand provides size structure evidence of continuous regeneration by māhoe (diagram below), and, in fact, by many palatable species. 41 It is highly likely that māhoe populations are being maintained at national scales. Inferences about how forests might regenerate if deer populations were controlled are often drawn from fenced exclosures. Size structures of māhoe outside ungulate exclosures show that, at such local scales, its regeneration is being impeded (see below). However, size structures of māhoe inside exclosures are almost identical to its size structures in forests throughout New Zealand. The reason: exclosures do not sample the landscape in an unbiased way they are likely to have been placed in sites with high deer numbers, which, as described above, may not be common on Conservation lands. Drawing inferences from exclosures about how forests should regenerate nationally needs to be placed within a context of unbiased national assessments. Size structures of the common tree māhoe, which is highly palatable to deer. The black line and data points are derived from unbiased plots in forests nationally. The blue line and data points are from inside fenced deer exclosures nationally and the red line and data points are from areas of forest immediately outside exclosures 41 Petzer, D.A.; Mason, N.W.H. 2009: CDRP Project 3 Milestone 5: Interpret change in indicator based on analyses of existing data. Investigation number Unpublished Landcare Research contract report. 33

40 4.4 An early-warning system Measures also determine unanticipated trends in ecological integrity that may be used to signal management responses or needs for research. The public have a keen interest in the state of the nation s birds. Until now, DOC has reported regularly on the status of populations of endangered endemic species such as kākāpō and takahē, which most members of the public are never likely to see in the wild. There is good evidence that the public are just as interested in assemblages and occupancy of birds with which they are more familiar. 42,43 More species of endemic birds occur in forests than in shrublands or grasslands (diagram below), while the opposite is true for exotic birds. These data do however suggest that extensive reversion of grasslands to shrublands will not only provide services such as increased carbon sequestration but also increased opportunities for endemic and native birds. Measurement of common-bird richness and abundance will also provide the data to allow DOC to answer public debate about whether its intensive management in local areas throughout New Zealand, including use of 1080, results in significant changes in bird species richness and abundance. 44 Numbers of bird species in forest, shrub and grassland on Conservation land. Summarised as endemic, native and exotic species. 42 New Zealand s garden bird survey: 43 RSPB warns of north-south divide for birds, Daily Telegraph newspaper (UK), 21 May 2008: 44 ERMA NZ 2007: The reassessment of 1080: an informal guide to the August 2007 decision by the Environmental Risk Management Authority: 34