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

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1 Extract from Landcare Research Report: Implementing an inventory and monitoring programme for the Department s Natural Heritage Management System Extract: Implementing an inventory and monitoring programme for the Department of Conservation's Natural Heritage Management System This document contains an extract from the report Implementing an inventory and monitoring programme for the Department of Conservation s Natural Heritage Management System, which was produced by Landcare Research New Zealand Ltd for the Department of Conservation. The Department of Conservation has yet to make final implementation decisions on the programme outlined in the report. The full report will be made available in May 2010 after the decisions on the business case for the programme s implementation. DISCLAIMER: The Department takes no responsibility for the accuracy of the report and the findings and opinions expressed therein. 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. Department of Conservation 2009

2 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 W. Wright Landcare Research PO Box 40, Lincoln 7640 New Zealand Landcare Research Contract Report: LC0809/154 PREPARED FOR: General Manager R&D Department of Conservation P.O. Box Wellington DATE: September 2009

3 Contents Abstract Overview What will be delivered? 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 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...31

4 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 Elaine W. Wright 3 and 1 Landcare Research PO Box 40 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 Christchurch 8142 New Zealand ewright@doc.govt.nz 1

5 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 outlined 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. This programme, which involves sampling at 1311 locations, 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 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

6 1. Overview 1.1 WHAT WILL BE DELIVERED? 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 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 ). 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 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. The Department of Conservation is the lead agency for coordinating national reporting on the implementation of the Convention on Biological Diversity 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. Wellington, Department of Conservation and Ministry for the Environment. 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 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:

7 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. Evaluating the effectiveness of conservation management and policy. Complete coverage of Conservation lands will allow the effects of widely applied management 5 CAB Min (09) 17/ Managing for outcomes What differences are we making? (DOCDM doc) 4

8 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 threats, Do we need indicators? Use is inescapable Widely accepted, e.g. - Nitrates for water pollution - Blood pressure for health risks 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 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 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. 2009: Designing an inventory and monitoring programme for the Department of Conservation s Natural Heritage Management System. Landcare Research Contract Report LC0809/153. Prepared for Department of Conservation, Wellington, New Zealand. 5

9 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 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: 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

10 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 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 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) 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. 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. 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:

11 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) 17 Objective: Maintain/restore ecosystem composition 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 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 monitoring data with little attention paid to data archiving and analysis, and limited presentation and updating of findings 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 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. 18 Gautam, M.; Westbrooke, I.; Rohan, M. 2008: Assessment of biodiversity monitoring projects, Department of Conservation. Research and Development, Department of Conservation. 8

12 1.3.2 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 (ie. the NHMS Species and Ecosystems Optimisation projects). 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 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. 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 for the Department of Conservation

13 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. 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 10

14 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,which 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 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 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:

15 Ministry of Agriculture and Forestry (MAF)) or use generalised landcover 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. 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 24 Peltzer, D.A.; Allen, R.B.; Lovett, G.M.; Wardle, D.A.; Whitehead, D. 2009: Effects of biological invasions on forest carbon sequestration. Global Change Biology, in press. 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. 2009: Designing an inventory and monitoring programme for the Department of Conservation s Natural Heritage Management System. Landcare Research Contract Report LC0809/153. Prepared for Department of Conservation, Wellington, New Zealand. 12

16 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). 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. 13

17 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 (e.g. by helicopter) will also be used to confirm the exclusion of a location en route to an 26 Hurst, J.M.; Allen, R.B. 2007: A permanent plot method for monitoring indigenous forests field protocols. Landcare Research, Lincoln. 14

18 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 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). 15

19 2.2.1 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. 16

20 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 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. 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: Kappers, B.; Smith, L. 2009: New Zealand Biodiversity Data Inventory (BDI) DOC. 17

21 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 nights 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. Estimates of species richness and occupancy derive from repeated sampling. Habitat data will be collected to aid interpretation of the common birds measure. 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 for Department of Conservation. 62 p. 32 Dawson, D.G.; Bull, P.C. 1975: Counting birds in New Zealand forests. Notornis 22:

22 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. 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. 19