Development of a OSPAR Common Set Biodiversity Indicators

Development of a OSPAR common set biodiversity indicators

Version: 18 January 2013

Prepared by the OSPAR Intersessional Correspondence Group on the Coordination of Biodiversity Assessment and Monitoring (ICG-COBAM) for the OSPAR Biodiversity Committee, 2013.

Disclaimer This is a living document that builds on the OSPAR MSFD Advice Manual on Biodiversity and reflects the state of discussion at expert level at the time of its drafting. The document is of a non-binding nature and aims at facilitating coordination between the EU Member States that are parties to the OSPAR Convention, with regard to the development of common biodiversity indicators for MSFD Descriptors 1, 2, 4 and 6. It does not prejudice the on going decision-making processes in Contracting Parties and their final conclusions on reporting under the MSFD. The document will be further developed by ICG-COBAM in the coming meeting cycle to support on going implementation of the Directive.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Contents

Part A. Process for selecting indicators ...... 3 1. Introduction ...... 3 1.1 What are common indicators? ...... 3 1.2 Role of the Intersessional Correspondence Group for the Coordination of Biodiversity Assessment and Monitoring (ICG-COBAM) ...... 4 2. Process of selecting common biodiversity indicators ...... 5 2.1 Expert groups ...... 5 2.2 Steps taken by expert groups ...... 6 3. Proposed indicators for endorsement as OSPAR common biodiversity indicators ...... 9 4. Overview of indicators and gap analysis ...... 11 4.1 MSFD criteria and proposed common biodiversity indicators ...... 11 4.2 Pressures and proposed common biodiversity indicators ...... 15 4.3 EcoQOs and proposed common biodiversity indicators ...... 20 4.4 Results of the Questionaire to Contracting Parties ...... 21 5. Monitoring ...... 23 6. Next steps ...... 27 References ...... 27 PART B. Abstracts of proposed common biodiversity indicators ...... 27 PART C. Technical specifications of common biodiversity indicators ...... 43

Part A is intended to explain how the indicators have been selected and how they, as a set, address the needs for assessing biodiversity aspects of the MSFD and OSPAR's Strategy, Part B is intended to communicate the basis and purpose of each indicator, and Part C describes in detail the indicators, their level of development, and their application in environmental assessments.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Part A. Process for selecting indicators 1. Introduction

The first implementation cycle of the Marine Strategy Framework Directive (MSFD) requires EU Member States to develop a marine strategy that includes: 1) reporting current environmental status, determining characteristics of good environmental status (GES) and establishing environmental targets and associated indicators by 15 July 2012; 2) establishing monitoring programmes to assess environmental status by 15 July 2014; and 3) developing programmes of measures by 2015 that should be implemented by 2016, with the overarching aim to achieve GES in the marine waters of EU member states by 2020.

The MSFD stipulates that strategies that relate to the same marine region or sub-region need to be coherent, coordinated, and have common approaches where possible. This is to ensure that Member States work together to implement each stage of the Directive in order to ensure comparability across Europe and coherence across marine regions. OSPAR is the main platform for coordinating the MSFD implementation process within the North-East Atlantic region. To facilitate the 2012 reporting requirements OSPAR has provided a framework for the development of coordinated environmental targets and indicators and developed ‘Advice documents’ for a majority of the 11 MSFD descriptors that should be considered when determining GES, including for the biodiversity descriptors 1, 2, 4 and 6.

To support OSPAR Contracting Parties with the continued implementation of the MSFD, the OSPAR Joint Assessment and Monitoring Programme is to be updated by 2014. A structure for coordinated monitoring and assessment is already more or less present for several MSFD Descriptors (D) e.g. for D5 Eutrophication (e.g. OSPAR Comprehensive Procedure) and for D8 Hazardous Substances (e.g. EU WFD, OSPAR CEMP). OSPAR Ecological Quality Objectives (EcoQOs), currently only applicable to the North Sea, can also be directly used to fulfil some of the criteria for determining GES for biodiversity that are outlined in the Commission Decision on criteria and methodological standards on good environmental status (2010/477/EC). Still, operational indicators and targets for biodiversity are generally less developed than for other MSFD descriptors and the development of coordinated biodiversity monitoring in accordance with the MSFD requires that EU Member States agree on what needs to be monitored and how. For OSPAR Contracting Parties this is defined firstly through identification of a common set of indicators and their application. This includes identifying: the parameters to measure, the spatial and temporal monitoring requirements needed to support the indicators, and defining the baselines and GES-boundaries/targets that are needed to assess the indicators.

1.1 What are common indicators?

The Biodiversity Committee in 2012 requested ICG-COBAM “based on the prioritised suite of common indicators, make progress on their definition and operational implementation in monitoring programmes for 2014, delivering an initial set to BDC 2013”. This initial set of common biodiversity indicators has been developed to enable an assessment of the state of the North-East-Atlantic marine environment and to measure progress towards the achievement of good environmental status. It comprises state, pressure and impact indicators, covers all major groups of ecosystem components, and aims to address the biodiversity requirements of the EU MSFD, in particular covering the EU COM decision on criteria and methodological standards. It is intended to provide a regional basis for national biodiversity monitoring and assessment activities under the MSFD, and under analogous policies for Non-EU Contracting Parties.

Article 5 of the EU MSFD requires that all elements of the national marine strategies are regionally coherent and coordinated. In the North East Atlantic, this is largely delivered through OSPAR as the relevant Regional Sea Convention (Art. 6). A basic and key item of regionally coherent strategies are common assessment

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development methods and common indicators. OSPAR is consequently aiming to commonly agree upon a set of indicators for application by all OSPAR Contracting Parties.

However, considering the wide variety of marine ecosystems within the OSPAR area, a set of common indicators should be considered as providing a framework for harmonized assessments, as several biodiversity indicators will require flexibility in their operationalization, depending on the differing characteristics of each sub-region. Thus, in some cases the implementation of common indicators will need to be tailored to those habitats and species characterising the marine waters of Contracting Parties and/or to the particular pressures in those waters. Other indicators targeted on specific ecosystem components (such as sea turtles) may have a spatially limited applicability due to natural distribution limits of species and/or habitat types. Taking such flexibility into account, it is the view of ICG-COBAM that the set of common indicators should be considered and applied as a whole across the OSPAR area by all Contracting Parties. In this sense they are considered complimentary to each other and aim to represent all major components of biodiversity and all main pressures from human activities.

The concept of commonality in assessments is not a new one to OSPAR. OSPAR has a long tradition in developing common methodological standards e.g. Coordinated Environmental Monitoring Programme (CEMP) and the development of a set of common “Ecological Quality Objectives” (EcoQOs). All existing, biodiversity-relevant EcoQOs have been included as a basis in the proposed set of biodiversity indicators presented in this document.

In view of the spectacular spectrum of biodiversity components present in the OSPAR area and the vast geographic scales covered, the proposed set of biodiversity indicators is considered a concise set that will need careful regular verification of its representativity to enable reliable assessments of the state of the NE Atlantic. Regular revisions of the set of indicators and also of the methods of single indicators (including GES boundaries/targets), will also be necessary to reflect e.g. changing climate conditions and progress in scientific understanding and technological developments.

Furthermore, in order to address specific ecological characteristics of Contracting Party waters and/or additional national policy requirements some additional specific indicators may be needed to complement the set of common indicators,

1.2 Role of the Intersessional Correspondence Group for the Coordination of Biodiversity Assessment and Monitoring (ICG-COBAM)

ICG-COBAM is responsible for developing OSPAR's biodiversity assessment and monitoring work under the guidance of the Biodiversity Committee (BDC). In addition to MSFD D1 (biodiversity), ICG-COBAM also considers descriptors that are related to biodiversity i.e. D2 (non-indigenous species), D4 (food webs) and D6 (sea floor integrity). ICG-COBAM also addresses the adaptation and development of EcoQOs and development of monitoring programmes for species and habitats on the OSPAR List (2008-6 OSPAR).

Existing OSPAR advice on biodiversity assessment

In 2012, a preliminary suite of common biodiversity indicators was presented in the OSPAR MSFD Advice Manual on Biodiversity (OSPAR 2012a). The preliminary suite was founded on the results of an OSPAR workshop on MSFD biodiversity descriptors that was organised and hosted by the Netherlands in Amsterdam in November 2011 (OSPAR 2012b). The Amsterdam workshop focused on identifying commonalities between Contracting Parties in terms of indicators and GES-boundaries/targets that they were considering for reporting under MSFD articles 9 and 10 for D 1, 2, 4 and 6. The workshop was attended by 66 participants covering both technical and policy experts from nine Contracting Parties (OSPAR 2012b).

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development The national lists of preliminary indicators that were submitted before the workshop collectively included >400 indicator proposals. There was however a great deal of overlap between indicators proposed by different Contracting Parties. The lists were scrutinised for duplication and similar indicators were merged. This exercise was undertaken during the workshop, as well as during the subsequent meeting of ICG- COBAM (ICG-COBAM 3/2011, Madrid). Through expert discussions some indicators were also excluded due to e.g. restricted geographic applicability or inconsistency with MSFD criteria. The resulting collated list included 41 indicators that formed the preliminary suite of common indicators included in the OSPAR’s MSFD Advice Manual on Biodiversity. This list did not however include proposed indicators for pelagic habitats or food webs since these indicators were few, less advanced at that time, and expertise to consider them at the workshop was limited.

The Advice Manual also includes descriptions of different approaches to defining GES and on how to set quantitative GES boundaries/targets for D1, 2, 4 and 6, building upon the results of an OSPAR workshop hosted by the Netherlands in Utrecht in November 20101.

The Advice Manual also includes definitions and interpretation of terms used in the MSFD2. The reader of this document is referred to the Advice Manual for definitions of terms if not specified here (Annex 8.2 Terminology).

Work of ICG-COBAM in 2012/2013

The Terms of Reference (ToRs) for ICG-COBAM for the meeting cycle 2012/2013 were agreed by BDC 2012. The ToRs include a list of steps including the following central issues for further development of biodiversity assessment and monitoring:

- refine the list of common indicators as provided in the Advice Manual - make progress on their technical definition and operational implementation in monitoring - contribute to the discussion on agreeing a set of ecological assessment areas. The work being undertaken should result in the delivery of an initial set of OSPAR common biodiversity indicators to BDC 2013.

2. Process of selecting common biodiversity indicators

The outcome of the Advice Manual forms the basis for refinement and selection of biodiversity indicators that may be suitable for common application across the OSPAR area. Among the preliminary suite of 41 biodiversity indicators included in the Advice Manual, a number of indicators needed further examination and considerable development work before becoming operational. This section outlines the process of further refinement of the initial set of indicators, which has resulted in a list of proposed common biodiversity indicators, and their further development.

2.1 Expert groups

To progress the selection and technical development of biodiversity indicators so that they are fully operational, expert groups on different ecosystem components were established within the framework of ICG-COBAM as presented in Table 1.

1 Report of the OSPAR/MSFD workshop on approaches to determining GES for biodiversity, November 2010 (http://www.ospar.org/documents/dbase/publications/p00553_ges4bio_workshop%20report_final.pdf)

2 The ICG-COBAM definition of MSFD assessment terms has later been included in a modified version in the EU WG GES ‘common understanding document’.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development

Table 1. Expert groups and national nominations, as of January 2013.

Group BE DE DK ES FR IE NL NO PT SE UK

Birds X Deputy X X X X X X LEAD

Mammals LEAD X X X X X X Deputy and Reptiles

Fish and X X X LEAD X X X Cephalopods

Non- X X X X X X X X LEAD Indigenous Species

Benthic X LEAD Deputy X X X X X X Habitats

Pelagic X X X X X LEAD Habitats

Food webs NN X X LEAD X X X

Deputy

A coordinator was nominated to lead the work of each expert group, with the assistance of a deputy lead. The work of the expert groups is guided by ToRs formulated by ICG-COBAM (see Annex 3, COBAM (2) 2012 Summary Record). National experts were nominated to the groups by the OSPAR Biodiversity Committee Head of Delegation following BDC 2012. The expert groups started working in the period April- September 2012. Some expert groups have convened meetings while most of the work was carried out through correspondence, supported by OSPAR's online collaboration tool, Basecamp. Reports and outcomes of the expert work are filed and discussed using Basecamp.

2.2 Steps taken by expert groups

Proposals and development of indicators have been carried out in an iterative way with the following steps carried out by experts:

Expert assessment of sensitivity of the preliminary indicators to pressures

Each expert group have assessed the response of the indicators to the following pressures: physical loss (permanent change), physical damage (reversible change), hydrological changes, contaminants, nutrients, noise and litter, non-indigenous species, selective extraction of species, and climate change. The assessment categorized the sensitivity into low, medium and high. The assessment also indicates if the indicator could respond to single or multiple pressures (see section 4, Table 5).

Definition of criteria for further selection of common indicators (ICG-COBAM 2/2012)

In view of ICG-COBAM, “common indicators” are intended to contribute to coherent implementation of the MSFD in the North East Atlantic region. They are recommended to be used in assessments across the OSPAR area and MSFD region and sub-regions, inferring that all Contracting Parties should monitor the parameters or metrics underpinning those indicators (see section 1.1, What are common indicators?).

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development For further selection of common indicators a set of criteria has been agreed upon. The application of the criteria should inter alia help to define a minimum required set of indicators to fulfil the MSFD as regards D1, D2, D4 and D6.

Criteria for proposed OSPAR common biodiversity indicators (as agreed by ICG-COBAM 2/2012) are presented in Table 2. These criteria have later been adopted as joint OSPAR criteria for the development of common indicators (Annex 5, CoG (2) 2012 Summary Record).

In COBAM the criteria have been used to guide the selection process. In a few cases, indicators that did not meet all of these criteria were still selected. Where this has occurred clear justification for their selection has been provided. The outcome of assessing the indicators versus these criteria is presented for each indicator (see Part C, Technical specification).

Table 2. Criteria for selecting OSPAR common biodiversity indicators.

Sensitive to significant and specific pressures: Specific refers to the response of an indicator to a single pressure. This enables the use of state indicators to identify pressures and aids the identification of appropriate management measures.

Significant refers to selecting indicators that respond to pressures with known or potential threat to the functional group or habitat in question. This will help to direct monitoring efforts towards detecting impacts of predominate threats.

Relevant for development of management measures: An indicator relevant for management informs on the pressure and supports the development of management measures. The response time is also relevant and typically refers to the time that has elapsed between measures taken and response of an indicator.

Practicable: The consideration of practicability includes methodological aspects of the measurement and assessment, costs of monitoring, whether the indicators can be based on existing monitoring, and whether one and the same monitoring effort can be used as a basis for several different indicators.

Applicable across the region/sub-region: Common indicators should be applicable across the OSPAR area, acknowledging that in some cases regional specification of the indicator may be necessary to take into account relevant species and habitats.

Representative: As a set the indicators should respond to the MSFD requirements (criteria and indicators of 2010/477/EU) and enable a representative state assessment of all important ecosystem components.

Degree of consensus among Contracting Parties: Degree of consensus among Contracting Parties refers to whether the indicator is already being applied by Contracting Parties. This criterion should be used as a complementary criterion. High consensus supports the inclusion of an indicator as a common indicator. Low consensus should on the other hand not be used as an exclusive argument for excluding an indicator if it fits the other criteria.

Inventory of indicators reported by Contracting Parties to the EU

The proposed common indicators are based on the inventory of indicators compiled at the Amsterdam workshop in 2011. Thus, consensus among Contracting Parties has been the basis of selection of indicators in ICG-COBAM from the outset. However, since the inventory compiled at that time represented preliminary

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development information from Contracting Parties, it was considered necessary to repeat the inventory before presenting the proposed set of indicators to BDC. In order to provide timely information to BDC 2013, this was done using a simplified inventory where Contracting Parties were asked to reply to two questions related to the indicators: 1) whether the proposed common biodiversity indicators were included in the October 2012 reporting to the EU and 2) if they find the “non-reported” indicators useful as part of a region-wide set of common indicators. For results see Part C, Technical specifications (Section 2 – Appropriateness of the indicator), and section 4.4. The inventory also included a third question related to existing monitoring in relation to the proposed common indicators (see section 5, Monitoring).

Categorization of proposed common indicators into core and candidate indicators (ICG-COBAM 3/2012)

Indicators fulfilling the criteria in table 2 were designated as core or candidate indicators depending on their stage of development. The stage of development is separated into two phases: 1) method development and 2) operationalization. At ICG-COBAM 3/2012 the following definitions were agreed.

1) Method development encompasses: defining monitoring parameters and indicator metrics, defining species/habitats and applicability of the indicator to different sub-regions, determining appropriate assessment area and monitoring frequency.

2) Operationalization encompasses: defining baseline and GES-boundary/target, data flows, a protocol for status assessment, and reporting.

For an indicator to be considered as fully operational, both phases must be completed.

Indicators are designated as “core” if method development will be completed by mid-2013, and there are good prospects that operational aspects will work in at least one sub-region by this time. Indicators where method development is not foreseen to be ready by mid 2013 were designated as “candidates”.

ICG-COBAM also identified “specific indicators”. These are indicators with potentially high relevance for assessing environmental status but with restricted applicability across the OSPAR area, such as an indicator for species/habitats with restricted distribution within the OSPAR area. This type of indicator is not included in the current list of proposed common indicators.

Technical specification of indicators

It was agreed at COBAM (2) 2012 that a technical specification was required for each indicator. The technical specifications outline the stage of development and detail the components which are necessary to develop (see Part C, Technical specification). Several of the technical specifications presented at this time need further elaboration since most indicators are not yet operational. When completed, they are expected to contribute to a handbook on assessment of OSPAR common indicators.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development 3. Proposed indicators for endorsement as OSPAR common biodiversity indicators The process and steps outlined above have produced a list of 24 core indicators. In addition, the list includes 15 candidate indicators. This list of core and candidate indicators should be considered collectively as the OSPAR common set biodiversity indicators, and consequently taken forward for further development and operationalization. It should be noted that the list may not be comprehensive, consequently the list should be regularly reviewed. Tables 3.1-3.7 Proposed set of OSPAR common biodiversity indicators.

*Previous code: refers to numbering in OSPAR’s MSFD Advice Manual on Biodiversity.

Table 3.1 MAMMALS

Code Previous Indicator Category code* M-1 31&33 Distributional range and pattern of grey and harbour seal haul-outs and breeding colonies Core

M-2 32&34 Distributional range and pattern of cetaceans species regularly present Core

M-3 35 Abundance of grey and harbour seal at haul-out sites & within breeding colonies Core

M-4 36 Abundance at the relevant temporal scale of cetacean species regularly present Core

M-5 37 Harbour seal and Grey seal pup production Core

M-6 38&39 Numbers of individuals within species being bycaught in relation to population Core

Table 3.2 BIRDS

Code Previous Indicator Category code* B-1 25 Species-specific trends in relative abundance of non-breeding and breeding marine bird Core species B-2 26 Annual breeding success of kittiwake Core

B-3 27 Breeding success/failure of marine birds Core

B-4 29 Non-native/invasive mammal presence on island seabird colonies Core

B-5 28 Mortality of marine birds from fishing (bycatch) and aquaculture Candidate

B-6 24 Distributional pattern of breeding and non-breeding marine birds Core

Table 3.3 FISH AND CEPHALOPODS

Code Previous Indicator Category code* FC-1 17 Population abundance/biomass of a suite of selected species Core

FC-2 20 OSPAR EcoQO for proportion of large fish (LFI) Core

FC-3 22 Mean maximum length of demersal fish and elasmobranchs Core

FC-4 18 By-catch rates of Chondrichthyes Candidate

FC-5 21 Conservation status of elasmobranch and demersal bony-fish species (IUCN) Candidate

FC-6 19 Proportion of mature fish in the populations of all species sampled adequately in international Candidate and national fish surveys

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Code Previous Indicator Category code* FC-7 15 Distributional range of a suite of selected species Candidate

FC-8 16 Distributional pattern within range of a suite of selected species Candidate

Table 3.4 BENTHIC HABITATS

Code Previous Indicator Category code* BH-1 4 Typical species composition Core

BH-2 7 Multi-metric indices Core

BH-3 11a/11b Physical damage of predominant and special habitats Candidate

BH-4 11b Area of habitat loss Candidate

BH-5 12 Size-frequency distribution of bivalve or other sensitive/indicator species Candidate

Table 3.5 PELAGIC HABITATS

Code Previous Indicator Category code*

PH-1 NA Changes of plankton functional types (life form) index Ratio Core

PH-2 NA Plankton biomass and/or abundance Core

PH-3 NA Changes in biodiversity index (s) Core

Table 3.6 FOOD WEBS

Number Previous Indicator Category code* FW-1 NA Reproductive success of marine birds in relation to food availability Core

FW-2 NA Production of phytoplankton Core

FW-3 NA Size composition in fish communities (LFI) Core

FW-4 NA Changes in average trophic level of marine predators (cf MTI) Core

FW-5 NA Change of plankton functional types (life form) index Ratio between: Gelatinous zooplankton Core & Fish larvae, Copepods & Phytoplankton; Holoplankton & Meroplankton FW-6 NA Biomass, species composition and spatial distribution of zooplankton Candidate

FW-7 NA Fish biomass and abundance of dietary functional groups Candidate

FW-8 NA Changes in average faunal biomass per trophic level (Biomass Trophic Spectrum) Candidate

FW-9 NA Ecological Network Analysis indicator (e.g. trophic efficiency, flow diversity) Candidate

Table 3.7 NON-INDIGENOUS SPECIES

Number Previous Indicator Category code* NIS-1 41 Pathways management measures Candidate

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development NIS-2 40 Rate of new introductions of NIS (per defined period) Candidate

4. Overview of indicators and gap analysis

This section provides an overview of the proposed common biodiversity indicators versus different requirements and requests of the EC and OSPAR, namely: the MSFD, the link to human pressures, and the relationship to OSPAR EcoQOs. It also presents an overview of the outcome of the Questionnaire to Contracting Parties.

4.1 MSFD criteria and proposed common biodiversity indicators

The EU Commission Decision document on criteria and methodological standards on GES (2010/477/EU) defines a number of criteria and proposed indicators to assess GES. In relation to the requirements of this decision, the proposed OSPAR common biodiversity indicators can be summarized as follows (Tables 4.1- 4.6).

D1 Species level

The proposed indicators include seals, cetaceans, birds as well as fish and cephalopods, and thereby fulfil the MSFD in terms of the major species groups (excepting turtles) to be included in an assessment of GES (SEC 2011) (Table 4.1).

Table 4.1. Descriptor 1, proposed common indicators for species vs MSFD criteria and indicators.

Core indicators. Candidate indicators. Codes refer to indicators as presented in Tables 3.1-3.7.

GES Criteria Proposed EC GES indicators taceans Seals Ce birds Marine and Fish cephalopods

1.1.1 Distributional range M-1 M-2 FC-7

1.1 Species distribution 1.1.2 Distribution pattern within the latter M-1 M-2 B-6 FC-8

1.1.3 Area covered by the species* NA NA NA NA

FC-1 1.2 Population size 1.2.1 Abundance and/or biomass M-3 M-4 B-1 FC-4 B-2, M-5 3, 4 1.3.1 Population demographics M-6 FC-6 1.3 Population M-6 condition B-5 1.3.2 Population genetic structure

* NA. Not applicable since sessile species are covered under habitats.

There are no indicators proposed to assess the population genetic structure (1.3.2). This partly reflects that genetic studies are generally conducted as research projects rather than part of national or regional monitoring programmes.

In order to complete the assessment of environmental status, candidate indicators for fish and cephalopods, in particular the indicators for distributional range and pattern, need further development.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development D1 Habitat level

Both, the state of benthic and pelagic habitats are represented through indicators that mainly reflect the condition of associated communities (Table 4.2). Proposed indicators cover benthic communities, demersal fish, and pelagic (zooplankton and phytoplankton) communities.

Table 4.2. Descriptor 1, proposed common indicators for habitats vs MSFD criteria and indicators.

Core indicators. Candidate indicators. Codes refer to indicators as presented in Tables 3.1-3.7.

GES Criteria Proposed GES indicators es Benthic habitats Benthic Benthic communities fish Demersal communiti habitats Pelagic Plankton communities

PH-1 1.4.1 Distributional range PH-3 1.4 Habitat distribution PH-1 1.4.2 Distributional pattern PH-3 1.5.1 Habitat area BH-4 1.5 Habitat extent 1.5.2 Habitat volume BH-1 FC-2 1.6.1 Condition of the typical species BH-2 FC-3 PH-1

and communities BH3- PH-3 FC-5 1.6 Habitat condition BH5 1.6.2 Relative abundance and/or BH-2 PH-2 biomass

1.6.3 Physical, hydrological and

chemical conditions

An obvious gap is the poor representation of indicators related to the distribution of benthic and pelagic habitats (criterion 1.4). For benthic habitats, extent was considered the more significant criterion (covered by the indicator Area of habitat loss, BH-4). For benthic habitats, such indicators are generally considered to be specific for different sub-regions. Common indicators related to physical damage (BH-3) and habitat loss (BH-4) are also included under D4. The condition criterion (1.6) is well covered with indicators for both benthic and pelagic habitats (via their communities).

For pelagic habitats, the distribution and extent of the physicochemical environment is central for explaining and interpreting the distribution and abundance/biomass of pelagic species and communities. However, whilst some data, such as temperature and salinity, are needed for the interpretation of assessment results, it is not considered as purposeful to define GES for climate-dependent variables which cannot be practically managed on a regional scale. Also, GES for e.g. nutrients are assumed to be determined through the development of indicators for D5 (eutrophication).

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development

D1 Ecosystem level

To assess the relationship between ecosystem components, there are five proposed indicators (Table 4.3). They are also included as pelagic habitats and food webs (D4) indicators i.e. there is no exclusive indicator proposed to assess this criterion.

Table 4.3. Descriptor 1, proposed common indicators for ecosystem level vs MSFD criteria and indicators.

Core indicators. Candidate indicators. Codes refer to indicators as presented in Table 3.1-3.7.

1.7.1 Composition and relative PH-1, PH-3, FW-4 1.7 Ecosystem structure proportions of ecosystem components (habitats and species) FW-8, FW-9

D2 Non-indigenous species

At present, only two candidate indicators are proposed, both of which are related to the state of NIS (Table 4.4). There are no proposed indicators related to impacts of NIS. No standardized or commonly accepted method to measure the impacts of non-indigenous species is present and more research is needed to develop an indicator

Table 4.4. Descriptor 2, proposed common indicators for NIS vs MSFD criteria and indicators.

Core indicators. Candidate indicators. Codes refer to indicators as presented in Tables 3.1-3.7.

GES criteria Proposed GES indicators NIS

2.1 Abundance and state characterisation of non- 2.1.1 Trends in abundance, temporal NIS-1 indigenous species, in occurrence and spatial distribution … NIS-2 particular invasive species

2.2.1 Ratio between invasive non- indigenous species and native 2.2 Environmental impact species… of invasive non- indigenous species 2.2.2 Impacts of non-indigenous

invasive species …

D4 Food webs

In order to assess GES for food webs, it is important to have a whole food web overview. Proposed food web indicators currently cover marine birds, fish, zooplankton and phytoplankton (Table 4.5). However, indicators related to the functioning of the benthic environments and the microbial loop are missing.

Benthic processes influence energy flows and nutrient cycling within the trophic chain, and thus indicators based on the structure (abundance and diversity) and processes (production and metabolism) of benthic groups can help to describe trophic functioning.

The microbial loop complements the classical food web since it recycles dissolved organic matter/nutrients and energy back into the food web. Hence, changes in the functional and structural characteristics of the microbial loop might have implications for the functioning of the entire food web.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development It should be noted that three of the proposed indicators overlap with proposed indicators for D1, ecosystem level.

Table 4.5. Descriptor 4, proposed common indicators for food webs vs MSFD criteria and indicators.

Core indicators. Candidate indicators. Codes refer to indicators as presented in Tables 3.1-3.7.

GES criteria Proposed GES indicators

specific

- Non Mammals Birds Fish Zooplankton Phytoplankton

4.1 Productivity of key 4.1.1 Performance of key predator FW-1 FW-2* species/trophic groups species 4.2 Proportion of 4.2.1 Large fish (by weight) FW-3 selected species …

FW-4 FW-5 4.3 Abundance/ 4.3.1 Abundance trends of functionally distribution of key FW-7 FW-5 important selected groups/species. FW-8 FW-6 trophic groups/species FW-9 * Belongs to criterion 4.1 but not indicator 4.1.1 which is linked to predator species

D6 Seafloor integrity

The proposed indicators for D6 overlap with proposed indicators for D1 for benthic habitats and communities (Table 4.6). The two indicators related to physical damage and to loss of habitats refer to both predominant and special habitat types and have been categorised as candidate indicators (BH-3 and BH-4). They should be prioritized for urgent further development since they reflect the impact of physical disturbance which is typically the most widespread and significant pressure affecting benthic habitats. Altogether, the proposed set of five indicators, if adequately operationalized, covers well the two COM decision criteria for D6.

Table 4.6. Descriptor 6, proposed common indicators for sea-floor integrity vs MSFD criteria and indicators.

Core indicators. Candidate indicators. Codes refer to indicators as presented in Tables 3.1-3.7.

GES criteria Proposed GES indicators Habitats Communities

6.1.1 Type, biomass and areal extent of BH-4 6.1 Physical damage, relevant biogenic substrate. having regard to substrate characteristics 6.1.2 Extent of the seabed significantly BH-3 BH-3 affected by human activities. BH-4 BH-4

6.2.1 Presence of particularly sensitive BH-1 and/or tolerant species.

6.2.2 Multi-metric indexes assessing BH-2 6.2 Condition of the benthic community condition … benthic community 6.2.3 Proportion of biomass or number of BH-5 individuals .. above some length/size. 6.2.4 Parameters describing the...size BH-5 spectrum of the benthic community.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development

4.2 Pressures and proposed common biodiversity indicators

The Commission Decision (2010/477/EU) underlines the usefulness of considering human pressures when defining suitable indicators for assessing GES.

An optimal indicator has a well-established causal-link to a specific pressure, thereby instantly guiding the measures needed to alleviate indications of a sub-GES condition. In reality, causal-links are often poorly known and biodiversity components are often subject to many pressures, including climate change, which obscures interpretation of assessment results. Still, some general links between proposed common biodiversity indicators and pressures can be outlined.

Table 5 shows the evaluation of COBAM expert groups on the specificity and response of proposed indicators to the major pressures outlined in MFSD Annex III, table 2. Firstly and importantly, it is apparent from table 5 that all pressures are to some extent reflected through the set of common indicators. Thus, unsustainable human pressure on the marine environment should be picked up by one or more of the indicators included in the set. Secondly, some indicators are highly specific, in particular those related to selective extraction of species, by-catch, and introduction of non-indigenous species.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Table 5. Pressures vs proposed common biodiversity indicators. The tables show the potential sensitivity of the proposed indicators to various groups of pressures. It does not reflect whether the biodiversity component concerned as such responds to the given pressure although this is strongly interdependent. The different estimated levels of sensitivity are given in colours:

High Medium Low Not applicable

Indicator

indigenous indigenous - Code Specificiy loss Physical damage Physical changes Hydrological Contaminants Nutrients litter and Noise Non speices extraction Selective change Climate

M-1 Distributional range and pattern of grey and Non-specific -responds to multiple harbour seal haul-outs and breeding colonies pressure M-2 Distributional range and pattern of cetaceans Non-specific –responds to multiple species regularly present pressures M-3 Abundance of grey and harbour seal at haul-out Non-specific –responds to multiple sites & within breeding colonies pressures M-4 Abundance at the relevant temporal scale of Non-specific –responds to multiple cetacean species regularly present pressures M-5 Harbour seal and Grey seal pup production Non-specific –responds to multiple pressures M-6 Numbers of individuals within species being by- High – caught in relation to population by-catch in fisheries B-1 Species-specific trends in relative abundance Non-specific –responds to multiple marine bird species pressures B-2 Annual breeding success of kittiwake High - Sensitive to changes in prey availability. B-3 (also Breeding success/failure of marine birds High - Sensitive to changes in prey FW-1) availability. B-4 Non-native/invasive mammal presence on island High - Terrestrial pressure with impact

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OSPAR Commission BDC 13/4/2-Rev.2-E

Indicator

indigenous indigenous - Code Specificiy loss Physical damage Physical changes Hydrological Contaminants Nutrients litter and Noise Non speices extraction Selective change Climate seabird colonies on seabirds B-5 Mortality of marine birds from fishing (bycatch) High- by-catch in fisheries and aquaculture B-6 Distributional pattern of breeding and non- Low - Distribution is strongly driven by breeding marine birds climate FC-1 Population abundance/biomass of a suite of High - selective extraction of species selected species FC-2 OSPAR EcoQO for proportion of large fish (LFI) High - selective extraction of species (also FW- 3) FC-3 Mean maximum length of demersal fish and High - selective extraction of species elasmobranchs FC-4 By-catch rates of Chondrichthyes High - selective extraction of species

FC-5 Conservation status of elasmobranch and High - selective extraction of species demersal bony-fish species (IUCN)

FC-6 Proportion of mature fish in the populations of all Response to pressures not well species sampled adequately in fish surveys understood FC-7 Distributional range of a suite of selected species Non-specific -responds to multiple pressure FC-8 Distributional pattern within range of a suite of Non-specific -responds to multiple selected species pressure BH-1 Typical species composition Depends on choice of species and habitats BH-2 Multi-metric indices Potentially high. WFD indices primarily respond to eutrophication

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OSPAR Commission BDC 13/4/2-Rev.2-E

Indicator

indigenous indigenous - Code Specificiy loss Physical damage Physical changes Hydrological Contaminants Nutrients litter and Noise Non speices extraction Selective change Climate

BH-3 Physical damage of predominant and special High - physical damage habitats BH-4 Area of habitat loss High - physical damage and loss BH-5 Size-frequency distribution of bivalve or other High - physical pressures sensitive/indicator species PH-1 Changes of plankton functional types (life form) Non-specific -responds to multiple index Ratio (pelagic) pressure PH-2 Plankton biomass and/or abundance Non-specific -responds to multiple pressure PH-3 Changes in biodiversity index(s) Non-specific -responds to multiple pressure FW-2 Production of phytoplankton Medium – responds mainly to input of nutrients FW-4 Changes in average trophic level of marine High – Selective extraction of species predators (cf MTI) FW-5 Change of plankton functional types (life form) Non-specific – responds to multiple index Ratio (food webs) pressures FW-6 Biomass, species composition and spatial Non-specific – responds to multiple distribution of zooplankton pressures FW-7 Fish biomass and abundance of dietary Medium – responds mainly to selective functional groups extraction FW-8 Changes in average faunal biomass per trophic Medium – responds mainly to selective level (Biomass Trophic Spectrum) extraction, response to other pressures not well understood FW-9 Ecological Network Analysis indicator (e.g. Response to pressures not well trophic efficiency, flow diversity) understood

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OSPAR Commission BDC 13/4/2-Rev.2-E

Indicator

indigenous indigenous - Code Specificiy loss Physical damage Physical changes Hydrological Contaminants Nutrients litter and Noise Non speices extraction Selective change Climate

NIS-1 Pathways management measures High - NIS NIS-2 Rate of new introductions of NIS (per defined High - NIS period)

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OSPAR Commission BDC 13/4/2-Rev.2-E 4.3 EcoQOs and proposed common biodiversity indicators

The relationship between the OSPAR EcoQOs, agreed or under development for the North Sea, and the here proposed biodiversity indicators is shown in Table 6. There is overall a high take up of the EcoQOs in the proposed set of biodiversity indicators, although some have been modified to better suit the needs of the MSFD.

Table 6. EcoQOS vs proposed common biodiversity indicators.

Topic (from May 2012 EcoQO (2010 report) Lead Compatible proposed COBAM indicator CoG meeting) CP

Spawning stock Maintain the spawning stock biomass NO No biomass of commercial above precautionary reference points species in the North for commercial fish stocks agreed by Sea the competent authority for fisheries management.

Healthy Seal Population There should be no decline in harbour UK Assessment supported by indicator: Abundance of grey and (harbour seals) seal population size within any of harbour seal at haul-out sites & within breeding colonies (M-3). eleven sub-units of the North Sea.

Healthy Seal Population There should be no decline in pup UK Assessment supported by indicator: Abundance at the relevant (grey seals) production of grey seals within any of temporal scale of cetacean species regularly present (M-4). nine sub-units of the North Sea.

Bycatch of Harbour Annual by-catch of harbour porpoises UK Assessment supported by indicator: Numbers of individuals Porpoises in the North should be reduced to below 1.7% of within species being bycaught in relation to population (M-6). Sea the best population estimate.

Local sand eel NN Assessment supported by indicator: Annual breeding success availability to black- of kittiwake (B-2). Note: The target setting approach suggested legged kittiwakes by COBAM takes into account climate impacts on sandeel availability, and produces a more effective target for identifying anthropogenic impacts, than the approach proposed for the EcoQO.

Seabird population DE Assessment supported by indicator: Species-specific trends in trends as an index of relative abundance of non-breeding and breeding marine bird seabird community species in all functional groups (B-1). health

Breeding success of NN Estimates of guillemot breeding success can be addressed by guillemots the indicator: Breeding success/failure of marine birds (B-3).

Proportion of large fish At least 30% of fish (by weight) should NO OSPAR EcoQO for proportion of large fish: for selected in the fish community be greater than 40 cm in length species from the International Bottom Trawl Survey (FC-2). (LFI)

Density of sensitive Under development NN Addressed In part (species composition) by the typical species (fragile) species indicator (BH-1).

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Quality and extent of Under development NN Potentially supported by several proposed COBAM indicators. Species

Quality and extent of Under development NO Potentially supported by several proposed COBAM indicators. Habitats

4.4 Results of the Questionaire to Contracting Parties

As explained in section 1, the origin of the list of indicators proposed by ICG-COBAM was an inventory of indicators in use or under development by Contracting Parties in order to fulfil the MSFD Art. 8-10 reporting requirements in 2012. This inventory was compiled at the OSPAR Workshop on common indicators held in Amsterdam in 2011. In order to compare the indicator proposals further developed in ICG-COBAM expert groups with the indicators effectively used by Contracting Parties for MSFD reporting in 2012, the inventory was repeated before presenting the proposed set of indicators to BDC. The following simplified inventory was performed in which Contracting Parties were asked to reply to two questions related to the indicators (used in Part C, Technical specification, to demonstrate coherence of views between Contracting Parties):

1) Which of the possible common indicators have been reported to the EC/are in use? (No/Yes/Yes with modification). 2) Would you regard this indicator useful as part of a region-wide common set for future assessments? (Yes/Yes but caveats apply/Not applicable/No). The inventory also included a third question related to existing monitoring in relation to the proposed common indicators (see section 5, Monitoring, for a more detailed presentation of results):

3) Is current monitoring capable of supporting the indicator? (Yes/Partly/No/Not applicable)

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Table 7. Results of a simplified inventory to ascertain reporting of proposed common indicators by OSPAR Contracting Parties. Key: >61% % of affirmative responses from CPs (e.g. yes, partly, yes with modifications, yes with caveats) 31-60% % of affirmative responses from CPs (e.g. yes, partly, yes with modifications, yes with caveats) <30% % of affirmative responses from CPs (e.g. yes, partly, yes with modifications, yes with caveats)

modified the the indicator wide common set for for set common wide - future assessments, assessments, future perhaps with caveats with perhaps indicator either as is, or or is, as either indicator Q2: CPs that regard this this regard that Q2: CPs Q3: Monitoring is at least least at is Q3: Monitoring partly sufficient to support support to sufficient partly indicator useful as part of part as useful indicator region Indicators Category the /using reporting Q1: CPs N=9 N=8 N=7 Marine mammals

Distributional range and pattern of grey and harbour seal haul-outs M-1 Core 7 7 5 and breeding colonies Distributional range and pattern of cetaceans species regularly M-2 Core 8 8 5 present Abundance of grey and harbour seal at haul-out sites & within M-3 Core 7 7 5 breeding colonies Abundance at the relevant temporal scale of cetacean species M-4 Core 8 8 6 regularly present M-5 Harbour seal and Grey seal pup production Core 7 7 4 Numbers of individuals within species being bycaught in relation to M-6 Core 7 7 5 population Birds

Species-specific trends in relative abundance of non-breeding and B-1 Core 8 8 7 breeding marine bird species B-2 Annual breeding success of kittiwake Core 5 5 2 B-3 Breeding success/failure of marine birds Core 8 8 5 B-4 Non-native/invasive mammal presence on island seabird colonies Core 5 5 1 B-5 Mortality of marine birds from fishing (bycatch) and aquaculture Candidate 8 8 2 B-6 Distributional pattern of breeding and non-breeding marine birds Candidate 7 7 5 Fish

FC-1 Population abundance/ biomass of a suite of selected species Core 7 7 6 FC-2 OSPAR EcoQO for proportion of large fish (LFI) Core 7 7 6 FC-3 Mean maximum length of demersal fish and elasmobranchs Core 7 7 6 FC-4 By-catch rates of Chondrichthyes Candidate 7 7 6 Conservation status of elasmobranch and demersal bony-fish FC-5 Candidate 5 5 5 species (IUCN) Proportion of mature fish in the populations of all species sampled FC-6 Candidate 8 8 5 adequately in international and national fish surveys FC-7 Distributional range of a suite of selected species Candidate 8 8 6 FC-8 Distributional pattern within range of a suite of selected species Candidate 7 7 6 Benthic Habitats

BH-1 Typical species composition Core 8 8 6 BH-2 Multi-metric indices Core 8 8 7 BH-3 Physical damage of predominant and special habitats Candidate 8 8 6

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PH-1 Change of plankton functional types (life form) index Ratio Core 5 5 6 PH-2 Plankton biomass and/or abundance Core 7 7 7 PH-3 Changes in biodiversity index(s) Core 4 4 6 Food webs

FW-1 Reproductive success of marine birds in relation to food availability Core 8 8 4 FW-2 Production of phytoplankton Core 7 7 6 FW-3 Size distribution in fish communities (LFI) Core 8 8 8 FW-4 Changes in average trophic level of marine predators (cf. MTI) Core 8 8 4 Change of plankton functional types (life form) index Ratio FW-5 between: Gelatinous zooplankton & Fish larvae, Copepods & Core 5 5 4 Phytoplankton; Holoplankton & Meroplankton Biomass, species composition and spatial distribution of FW-6 Candidate 6 6 6 zooplankton FW-7 Fish biomass and abundance of dietary functional groups Candidate 7 7 7 Changes in average faunal biomass per trophic level (Biomass FW-8 Candidate 5 5 2 Trophic Spectrum) Ecological Network Analysis Indicator (e.g. trophic efficiency, flow FW-9 Candidate 3 3 1 diversity) NIS NIS-1 Pathways management measures Candidate 8 8 2 NIS-2 Rate of new introductions of NIS (per defined period) Candidate 8 8 5

5. Monitoring

To support the revision of OSPAR JAMP and guide the development of monitoring programmes to fulfil MSFD article 11, one of the important next steps of ICG-COBAM in 2013 is to identify the needed monitoring to support the proposed OSPAR common biodiversity indicators (see section 6, Next steps). To get a preliminary overview of existing monitoring, ICG-COBAM included a question related to monitoring in the questionnaire presented in section 4.4, asking Contracting Parties to indicate whether current monitoring is capable of supporting the proposed common indicators. In this section the detailed response to this question is presented.

Although the questionnaire only provides a crude overview, giving no detailed information on needed or existing monitoring, it indicates that the majority of proposed common indicators are at least partly covered by existing monitoring programmes. This is particularly the case for indicators related to mammals, birds and

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fish while indicators related to habitats and food webs at least in some countries would require modified and/or new monitoring efforts. Briefly the results show the following (see Table 8).

 Mammals: Most Contracting Parties already monitor or partly monitor the needed parameters to support the proposed common indicators. This is particularly the case for Contracting Parties for which grey and harbour seals are relevant species while regular monitoring of cetaceans is less well covered.

 Birds: All countries are to some extent monitoring seabirds. Current monitoring is particularly supporting indicators related to abundance, breeding success, and distribution for seabirds while e.g. mortality through by-catch and presence of non-native mammals on seabird colonies is at present monitored by only a limited number of Contracting Parties.

 Fish: All countries are fully or partly conducting monitoring to support proposed common indicators. This can largely be explained by already ongoing regular scientific surveys, often regionally coordinated by ICES.

 Benthic habitats: Most countries are to some extent conducting monitoring of the benthic communities and habitats. However, the indication of “partly monitored” by most countries reflects the difficulty in clearly replying to this question until the indicators have been further developed, the particular habitats specified, and the necessary monitoring has been identified.

 Pelagic habitats: All except one country already monitor the planktonic groups included in the proposed common indicators, although not necessarily at the required spatial scale or temporal frequency.

 Food webs: This group of indicators, which includes several organism groups, shows a disparate result. Most countries are at least partly conducting the needed monitoring, except for the proposed ecosystem-based indicators, such as the Biomass Trophic Spectrum (FW-8) and Ecological Network Analysis Indicator (FW-9), both candidate indicators. In general, comprehensive datasets on the feeding ecology of many of the key species in marine food webs are insufficient and coordinated surveys across trophic levels are needed.

 NIS: Most countries are at least partly monitoring the appearance of non-indigenous species. However, the modification of current monitoring is likely to be needed for most countries to support the proposed indicators.

In terms of developing future joint OSPAR monitoring programmes for biodiversity, it is the ambition of COBAM to propose, as far as possible, integrated and cost-efficient monitoring schemes. Already at this stage it should be noted that several of the proposed indicators can be based on the same monitoring effort. This is the case for e.g. indicators related to distribution, abundance and pup production of seals (M-1, 3 and 5), all indicators using data on bird abundance and breeding success (B-1, B-2, B-3 and B-6), the abundance of fish species and the proposed fish community indicators (FC-1, FC-2 and FC-3), indicators related to the condition of benthic habitats (BH-1, 2, 5), and for those food web indicators that overlap with the species/habitat indicators (e.g. FW-1 and B3; FW-3 and FC-2; FW-5 and PH1) and possibly the ecosystem-based indicators, FW-8 and FW-9. With regards to the pelagic indicators, Also, the UK-funded

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Continuous Plankton Recorder survey monitors phyto- and zooplankton communities (PH 1 and PH 3) and phytoplankton biomass (PH2) at the European scale.

Table 8. Results of questionnaire Q3: Is current monitoring capable of supporting the indicator? Numbers within each cell reflects the number of responses from Contracting Parties (n=7). N/A: not applicable e.g. species not present in waters of a Contracting Party.

Code Indicator Category Yes Partly No N/A Marine mammals M-1 Distributional range and pattern of grey and harbour seal haul-outs and Core 3 2 0 2 breeding colonies M-2 Distributional range and pattern of cetaceans species regularly present Core 2 3 2 0 M-3 Abundance of grey and harbour seal at haul-out sites & within breeding Core 3 2 0 2 colonies M-4 Abundance at the relevant temporal scale of cetacean species regularly Core 2 4 1 0 present M-5 Harbour seal and Grey seal pup production Core 3 1 1 2 M-6 Numbers of individuals within species being bycaught in relation to population Core 2 3 2 0 Birds B-1 Species-specific trends in relative abundance of non-breeding and breeding Core 3 4 0 0 marine bird species B-2 Annual breeding success of kittiwake Core 1 1 1 4 B-3 Breeding success/failure of marine birds Core 2 3 2 0 B-4 Non-native/invasive mammal presence on island seabird colonies Core 0 1 5 1 B-5 Mortality of marine birds from fishing (bycatch) and aquaculture Candidate 0 2 5 0 B-6 Distributional pattern of breeding and non-breeding marine birds Core 2 3 2 0 Fish FC-1 Population abundance/ biomass of a suite of selected species Core 5 1 0 0 FC-2 OSPAR EcoQO for proportion of large fish (LFI) Core 4 2 0 0 FC-3 Mean maximum length of demersal fish and elasmobranchs Core 3 3 0 0 FC-4 By-catch rates of Chondrichthyes Candidate 3 3 0 0 FC-5 Conservation status of elasmobranch and demersal bony-fish species (IUCN) Candidate 2 3 0 0 FC-6 Proportion of mature fish in the populations of all species sampled adequately Candidate 3 2 0 0 in international and national fish surveys FC-7 Distributional range of a suite of selected species Candidate 3 3 0 0 FC-8 Distributional pattern within range of a suite of selected species Candidate 3 3 0 0 Benthic Habitats BH-1 Typical species composition Core 0 6 1 0 BH-2 Multi-metric indices Core 1 6 0 0 BH-3 Physical damage of predominant and special habitats Candidate 0 6 1 0 BH-4 Area of habitat loss Candidate 1 5 1 0 BH-5 Size-frequency distribution of bivalve or other sensitive/indicator species Candidate 0 5 2 0 Pelagic Habitats

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Code Indicator Category Yes Partly No N/A PH-1 Change of plankton functional types (life form) index Ratio Core 1 5 1 0 PH-2 Plankton biomass and/or abundance Core 3 4 0 0 PH-3 Changes in biodiversity index(s) Core 1 5 1 0 Food webs FW-1 Reproductive success of marine birds in relation to food availability Core 0 4 2 0 FW-2 Production of phytoplankton Core 1 6 0 0 FW-3 Size distribution in fish communities (LFI) Core 6 2 0 0 FW-4 Changes in average trophic level of marine predators (cf. MTI) Core 2 2 2 0 FW-5 Change of plankton functional types (life form) index Ratio between: Core 0 4 2 0 Gelatinous zooplankton & Fish larvae, Copepods & Phytoplankton; Holoplankton & Meroplankton FW-6 Biomass, species composition and spatial distribution of zooplankton Candidate 2 4 1 0 FW-7 Fish biomass and abundance of dietary functional groups Candidate 3 4 0 0 FW-8 Changes in average faunal biomass per trophic level (Biomass Trophic Candidate 1 1 5 0 Spectrum) FW-9 Ecological Network Analysis Indicator (e.g. trophic efficiency, flow diversity) Candidate 1 0 4 0 NIS NIS-1 Pathways management measures Candidate 1 1 5 0 NIS-2 Rate of new introductions of NIS (per defined period) Candidate 1 4 3 0

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development

6. Next steps The proposed common OSPAR biodiversity indicators are at present at very different stages of development: some indicators such as existing EcoQOs for fish and birds are already well developed or soon to be finalised while other indicators require substantial development work (see Part C, Technical specifications).

It is expected that the finalisation of the method development for the 24 proposed core indicators will take place by mid-2013, given that resources and experts are allocated to the task. The remaining steps of method development differ between indicators but include e.g. to identify ecosystem components (species/habitats) to populate the indicator and to define suitable assessment scales. The next phase of development of core indicators, i.e. the operalization of indicators, further requires the definition of GES, assessment protocols, and reporting procedures. At this time point only the OSPAR EcoQO for proportion of large fish (FC-2) can be identified as fully operational and only in the North Sea region. However, several other indicators are already partly operational. For instance, the Typical Species Composition indicator (BH-1) is already in use in Germany for habitat types under the Habitats Directive.

Although operalization of indicators should be progressed immediately it should be noted that this level of development, in terms of MSFD requirements, is not required until preparation of the 2018 status reporting. For the 15 indicators currently categorized as ‘candidates’, the stage of development is variable and in some cases dedicated research projects will be required for their continued development. Other candidate indicators are more advanced but further discussions are needed regarding technical aspects of the work they will therefore not be ready by mid-2013. Thus, continued development will differ between indicators and different modes of working need to be explored.

In the proposed ToRs of 2013/2014, ICG-COBAM proposes to focus the continued work on: - finalizing the method development of core indicators by mid-2013, - defining the necessary monitoring requirements to support the core indicators by end-2013, - continue development of prioritized candidate indicators.

To achieve this, different ways of working will be explored including collaboration with ICES working groups, where this is appropriate (e.g. birds, mammals, fish and food webs) as well as requesting Contracting Parties to act as task lead for the development of indicators that need substantial development work. Details to proposed continued work is found in proposed draft ToRs for COBAM 2013/2014 (BDC 13/4/1.Add1) and in the COBAM report to BDC 2013 (BDC 13/4/1). References 2008-6 OSPAR. List of Threatened and/or declining Species and Habitats (http://www.ospar.org/documents/DBASE/DECRECS/Agreements/08- 06e_OSPAR%20List%20species%20and%20habitats.doc) 2010/477/EU. Commission decision of 1 September 2010 on criteria and methodological standards on good environmental status of marine waters. OSPAR 2012a MSFD Advice Manual and Background Document on Biodiversity. A living document - Version 3.2 of 5 March 2012. OSPAR 2012b. Biodiversity series. Report of the OSPAR workshop on MSFD biodiversity descriptors: comparison of targets and associated indicators.

SEC(2011) 1255 final 2011. European Commission. COMMISSION STAFF WORKING PAPER. Relationship between the initial assessment of marine waters and the criteria for good environmental status.

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PART B: Abstracts of proposed common biodiversity indicators

Mammals

Code Previous Indicator Category code*

M-1 31&33 Distributional range and pattern of grey and harbour seal haul-outs and breeding colonies Core

M-2 32&34 Distributional range and pattern of cetaceans species regularly present Core

M-3 35 Abundance of grey and harbour seal at haul-out sites & within breeding colonies Core

M-4 36 Abundance at the relevant temporal scale of cetacean species regularly present Core

M-5 37 Harbour seal and Grey seal pup production Core

M-6 38&39 Numbers of individuals within species being bycaught in relation to population Core

M-1. Distributional range and pattern of grey and harbour seal haul-outs and breeding colonies (Core) Marine mammals, including harbour and grey seals, are top predators, and comprise an important part of biodiversity (Descriptor 1). As harbour and grey seal are taken up under the Habitats Directive (annex II), their distributional range and pattern comprises a key aspect for securing and achieving GES according to the MSFD. As there are many human activities which can affect the distributional range and pattern of seal colonies and haul-out sites, these should be monitored to identify trends, and if necessary for the appropriate measures to be taken. Although the baseline should be based on historical data, these are not available everywhere. Moreover, the historical distributional range and pattern of haul-out sites and colonies is a situation that cannot realistically be restored, given for instance coastal developments and tourism. Climatic changes and outbreaks of PDV may have important consequences. Therefore a modern baseline will have to be used. The target, “No decrease with regard to the baseline beyond natural variability”, will have to be set for every Management Unit (MU). There is a clear overlap between the monitoring for distributional range and pattern and the monitoring of pup production and population size of hauled out seals. The same monitoring, already partly implemented, will be used to undertake both analyses.

M-2. Distributional range and pattern of cetacean species regularly present (Core) Cetaceans are top predators, and comprise an important part of biodiversity (Descriptor 1). As they are taken up under the Habitats Directive, their distribution comprises a key aspect for securing and achieving GES. Many human activities can affect the distribution of cetaceans, and monitoring may elucidate cause-effect relationships. Since it is very expensive and logistically impractical to monitor all cetaceans, only harbour porpoise, (coastal) bottlenose dolphin, common dolphin, white-beaked dolphin and minke whale are proposed for core indicators. Historical data are usually not available at the appropriate spatial and temporal scales, and the historical situation cannot realistically be restored in most cases. Climatic changes may have important consequences. It is therefore likely that a modern baseline will have to be utilised. The target: (“No decrease with regard to the baseline beyond natural variability”) will have to be set at the appropriate temporal and spatial scale. The distribution of cetaceans can be monitored using a variety of techniques. Since the monitoring of

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distribution and abundance overlaps, the same monitoring approaches, already partly implemented, will be used to undertake both analyses. Strandings data may yield useful additional information, the investigation of stranded cetaceans or cetaceans found or bycaught at sea and returned to port possibly contributing information about human pressures as well as important life history information. A transboundary approach to the collection, collation and analysis of data will be required.

M-3. Abundance of harbour and grey seals at haul-out sites & within breeding colonies (Core) Marine mammals, including seals, are top predators, and comprise an important part of biodiversity (Descriptor 1). As harbour and grey seal are taken up under the Habitats Directive, their abundance, at the relevant spatial and temporal scale, comprises a key aspect for securing and achieving GES according to the MSFD. Existing OSPAR EcoQO’s deal with grey seal pup production (which can be scaled up to provide abundance estimates) and the population size of harbour seals (estimated from haul out counts). The historical abundance of seals at haul-out sites and colonies is a situation that cannot realistically be restored, given for instance large-scale coastal developments and tourism. Climatic changes and outbreaks of PDV (limited to harbour seals) may have important consequences. A modern baseline will therefore have to be used, such as a favourable reference situation (Habitats Directive) for abundance at the different Management Units (MUs), or the level at which growth rates are levelling off due to natural causes. The proposed target, to be set for every MU, is: “No statistically significant decrease with regard to the baseline beyond natural variability”. Identifying trends in colonies near the edge of the range of harbour and grey seals will be especially important, as will movements of seals between MUs. In most parts of the distributional range of the harbour and grey seal, there is sufficient monitoring at haul-out sites and/or breeding colonies. This monitoring takes place in combination with the monitoring of the indicators M-1 (distributional range and pattern) and M-5 (pup production). Although no straightforward link exists between the abundance of seals and human activities, a number of human activities may lie at the basis of trends and changes in abundance. The monitoring of the indicator serves as to trigger the investigation of possible cause-effect relationships as a basis for measures.

M-4. Abundance at the relevant temporal scale of cetacean species regularly present (Core)

Cetaceans are top predators, comprising an important part of biodiversity. Their abundance, at the relevant temporal and spatial scale, comprises a key aspect for securing and achieving GES. The cetacean species for use as a core indicator under OSPAR are shelf species for which objectives are set in other fora, and/or for which bycatch need to be assessed (harbour porpoise, (coastal) bottlenose dolphin and common dolphin), and minke whale (as a species of baleen whale with different ecological and life history characteristics) and white-beaked dolphin (as a species restricted to the north-Atlantic). Historical baseline data are usually not available at the appropriate spatial and temporal scale, and the historical abundance of many cetacean species cannot realistically be restored. For each species and area targets need to be set. Targets can be defined as “no deterioration from current state”, and “an improvement towards the reference state where feasible”. For harbour porpoise, minke whale, white-beaked dolphin and common dolphin the more detailed target can be defined as: “No statistically significant decrease with regard to the baseline beyond natural variability“. For coastal bottlenose dolphins it could be “Maintenance of the current levels of the populations where stable, and where feasible and relevant, an increase in numbers”. A recovery in areas where it was known to occur up to the 20th century is not realistic in the short or medium term. Monitoring and assessment of the indicator is partly in place, as it is required under other fora. It can be combined with monitoring to assess changes in distribution. While there is no pre-defined link between the abundance of cetaceans and human activities, the objective should be to detect trends, in particular negative ones, in the abundance of cetacean populations.

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M-5. Harbour seal and Grey seal pup production (Core) Marine mammals are top predators, and comprise an important part of biodiversity (Descriptor 1). As harbour and grey seal are taken up under the Habitats Directive, their population condition comprises a key aspect for securing and achieving GES according to the MSFD. “Fecundity rate of harbour seal and grey seal (pup production)”, at the relevant temporal scale, and for each geographically defined Management Unit (MU), can serve as an indicator for population condition. Grey seal population estimates are often based on pup counts (number of pups per colony vs. the size of the colony). In contrast, estimating pup production of harbour seals can be extremely difficult in some areas. Historical data on the abundance of seals is not available everywhere, and can in some locations not realistically be restored. Data on pup production is usually also unavailable, but it can indicate shrinking or increasing populations. It is likely that a modern baseline will have to be utilized, such as average pup production in the first decade of the 21st century per MU. This level can then be related to increasing or decreasing population sizes, with appropriate targets. The target is “No statistically significant deviation from long-term variation / no decline of ≥10% at each Management Unit”. While an existing OSPAR EcoQO deals with grey seal pup production, there is not an equivalent to harbour seal pup production. Climatic changes and PDV outbreaks (for harbour seals) may have important consequences. The monitoring required takes place in combination with the monitoring for the indicators M-1 (distributional range and pattern) and M-3 (abundance). While there is sufficient monitoring at most breeding colonies for grey seals, it will not be possible to cover all MUs for harbour seals. While there is usually no straightforward link between a human activity and pup production, there are multiple pressures, and changes and trends are important to be able to detect cause-effect relationships, where necessary to be followed by appropriate measures.

M-6. Mortality rate of seals and cetaceans due to bycatch (Core)

Marine mammals are usually slowly reproducing, and a high human-induced mortality can have serious and long-term implications. An important source of such mortality is bycatch in fishing gear. As an indicator, the numbers of individuals of the relevant species (harbour porpoise, common dolphin, (coastal) bottlenose dolphin, striped dolphin, harbour seal and grey seal) being bycaught are set against population estimates (indicators 35 and 36). Bycatch monitoring is already in place for a number of fisheries and regions under the Habitats Directive, ASCOBANS and fisheries regulations, but it is clear that at present it provides only a very patchy overview of bycatch due to low and uneven sampling coverage. Difficulties exist in both measuring bycatch and assessing population size in a sufficiently high degree of accuracy to draw conclusions, and in combining data originating from different regions for an overall assessment of GES. An additional source of information could be strandings, which not only provide demographic data for populations, but can also be used to detect changes in the causes of death. As the maximum population growth rates differ in marine mammals, different targets will be needed. The suggested target is “The annual bycatch rate of [marine mammal species] is reduced to below levels that are expected to allow conservation objectives to be met”. Current targets for cetaceans are based on a simple percentage of the best population estimate, but other approaches have been shown to perform better. An alternative for the target is the use of the current bycatch rate (as numbers of animals) as the baseline and aim for it to be reduced in future years. Given the high mobility of marine mammals, and the distributional range of populations, assessments will necessarily need to be made on a wide scale (population range or management regions).

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Marine Birds

Code Previous Indicator Category code*

B-1 25 Species-specific trends in relative abundance of non-breeding and breeding marine bird Core species

B-2 26 Annual breeding success of kittiwake Core

B-3 27 Breeding success/failure of marine birds Core

B-4 29 Non-native/invasive mammal presence on island seabird colonies Core

B-5 28 Mortality of marine birds from fishing (bycatch) and aquaculture Candidate

B-6 24 Distributional pattern of breeding and non-breeding marine birds Core

B-1 Species-specific trends in relative abundance of non-breeding and breeding marine birds (Core)

This indicator describes changes in relative abundance of breeding and non-breeding marine birds, i.e. birds relying on marine food resources. Birds are a highly visible component of marine ecosystems. Collectively, these species represent a variety of feeding guilds, from herbivores to top predators. Due to the long life span of these species, abundance changes slowly and is sensitive to a variety of pressures. The indicator is based on annual sample counts of breeding or non-breeding birds, derived using a variety of well- established techniques. Current monitoring can deliver the data for the indicator in some countries and for some species groups; in other cases additional monitoring is needed. A baseline abundance should be set for each species based on expert judgement, to reflect a situation with limited human impact. The indicator is derived from annual indices of relative abundance of each species (absolute abundance as a percentage of the baseline). The indicator for each species should be more than 70% or 80% of the baseline, depending on life history (the higher threshold being applied to those species with a slower recovery rate). The overall target is that 75% of species should be above their individual species-specific thresholds.

B-2 Annual breeding success of kittiwake (Core)

This indicator reflects the breeding performance of a pelagic seabird species, the black-legged kittiwake, documented to be highly sensitive to fisheries-induced changes in availability of forage fish such as sandeels, herring or sprat. Kittiwakes form a key component of cliff-breeding seabird communities in the northeast Atlantic, and monitoring their breeding success (chicks produced per breeding pair) is easy, cost- efficient and already in place in most areas. Their food availability is also strongly affected by climate variation. The target setting approach takes account of this by comparing annual breeding success to a baseline that predicts what annual breeding success should be if in line with prevailing climatic conditions. The baseline is derived from a regression analysis of past measures of annual breeding success and local mean sea-surface temperature (SST) in the period most important for the production of the local prey species. Any significant negative deviation from the baseline will indicate a detrimental anthropogenic impact other than climate change, but further assessment will be needed to identify the actual cause (e.g. fisheries, predation or disturbance).

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B-3 Breeding success/failure of marine bird species (Core)

The indicator describes breeding success which in turn describes population condition and reflects habitat condition and the effects of pressures such as availability, human disturbance, predation by invasive species and contaminants..

Birds are a highly visible component of marine ecosystems. Collectively, these species represent a variety of feeding guilds, from herbivores to top predators. Measurements of abundance alone do not provide a warning system sensitive at the short time scale because most of the species involved are long-lived. The indicator complements the indicator on annual breeding success of kittiwake, in order to keep a watching- brief on the population condition of other species and to include regions where the Kittiwake does not breed.

The indicator for colonial breeders is derived from a measurement of annual colony failure rate e.g. the percentage of colonies failing per year, per species. A metric for non-colonial breeders needs to be developed.

Breeding success of marine birds is monitored at a selection of sites for a number of species throughout the NE Atlantic. Further work is needed to determine if the development of this indicator at the sub-regional scale will be restricted by lack of monitoring or data availability.

The target for each species should be based on a threshold for the annual percentage of sites experiencing breeding failure.

B-4 Non-native/invasive mammal presence on island seabird colonies (Core)

The indicator describes the level of impact of predation by non-native (e.g. brown rat, American mink, domestic cat) or invasive native mammals (e.g. fox, hedgehog) on marine birds that are breeding on inshore and offshore islands. The introduction of both native and non-native mammals on to previously mammal- free islands has a substantial negative impact on ground-nesting marine birds, by reducing breeding success and breeding numbers and in some cases, causing colony extinction. Some of the largest colonies of seabirds in the NE Atlantic are on mammal-free islands.

This indicator is derived from observations of the presence or absence of mammals on islands “units” (a single island or an archipelago) where marine birds currently breed or are likely to do so. Each unit should have a low chance of invasion or reinvasion. There are currently no known co-ordinated monitoring schemes in the NE Atlantic.

The GES Target should be: No non-native or invasive-native mammal species on islands that are already free of such species. The proportion of islands where non-native or invasive-native mammal species are present or having a significant impact, should be decreasing.

The aim of the indicator is to inform management that will reduce the pressure on seabird populations. The corresponding operational (management) target should be: Minimise the risk of invasion by non-native mammals on all islands, where this has not already occurred (including islands from where mammals have been eradicated); and eliminate detrimental impacts caused by mammals at a prioritised list of islands.

B-5 Mortality of marine birds from fishing (bycatch) and aquaculture (Candidate)

The indicator measures mortality from birds being accidentally killed by fishing operations (e.g. gillnets and long-lines) and in aquaculture structures. The indicator is important as marine birds are long-lived and are slow to reproduce. Therefore any extra mortality can have serious impacts on the populations reducing the possibilities to reach a GES under other criteria for marine birds. The target for the indicator should be that

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the estimated mortality as a result of fishing bycatch and aquaculture entanglement should not exceed levels that would prevent targets for 1.2 population size from being achieved. Currently there is no systematic monitoring of seabird bycatch for the NE Atlantic. Monitoring of bycatch by Member States and Regional Fisheries Management Organizations (RFMO) should follow recommendations in the recently published European wide National Plan of Action (EU-PoA) from the European Commission.

B-6 Distributional pattern of breeding and non-breeding marine birds (Core)

The indicator describes changes in the distribution pattern of seabirds. Changes in the distribution may occur independently of changes in abundance and thus reflect the condition of populations of key species. The indicator includes colony breeding terns, gulls and cormorant as well as breeding and non-breeding waterbirds (seaducks, divers and shorebirds). Non-breeding seabirds from offshore areas are not included due to their highly dynamic distribution patterns.

On land changes in the distribution pattern of breeding sites may be caused by disturbance and habitat loss but also changes in food supply. At sea marine bird distribution is affected by activities such as wind farms, dredging and aggregate extraction. The indicator is based on spatial monitoring units, which will have to be defined. Depending on the scale of chosen monitoring units, most countries have monitoring scheme which could supply data for breeding birds. The availability of data for non-breeding birds is restricted to fewer countries. The target is that no major shifts or shrinkage in the range of marine birds in 75% of species monitored, i.e. that the majority of species maintains its distributional pattern.

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Fish and Cephalopods

Code Previous Indicator Category code*

FC-1 17 Population abundance/ biomass of a suite of selected species Core

FC-2 20 OSPAR EcoQO for proportion of large fish (LFI) Core

FC-3 22 Mean maximum length of demersal fish and elasmobranchs Core

FC-4 18 By-catch rates of Chondrichthyes Candidate Any references cited in the abstracts can be found in the associated technical specifications

FC-1 Population abundance/ biomass of a suite of selected species (Core)

The population abundance/ biomass indicator measures the size of the catchable proportion of fish populations by survey. The indicator can either be weight based, which gives a measure of biomass, or numbers based which gives a measure of abundance. Biomass and abundance indices are in most cases relative and require surveys to be conducted at regular intervals (eg annually), in the same area, in the same season and with a standard gear. The indicators are sensitive to fishing, but also to environmental conditions. There are currently extensive surveys conducted across the OSPAR region to measure the abundance/biomass of commercial fish. Some of these surveys such as demersal fish trawl surveys also provide abundance and biomass on non commercial fish species. There are however certain functional groups and subregions that are not adequately covered by current monitoring programmes.

FC-2 OSPAR EcoQO for proportion of large fish (Core)

The proportion of large fish indictor (LFI) is a size based indicator to measure the proportion of large fish by weight in the assemblage, reflecting the size structure and life history composition of the fish community. Size based indicators are considered suitable to measure the effects of fishing on the fishing community as they are responsive to fishing impacts. The LFI takes no account of species identity but rather that of individual size and provides a measure of the relative composition in terms of size of individuals making up the community. The LFI was developed as an OSPAR EcoQO for fish community structure in relation to the impacts of fishing (Greenstreet et al. 2011). Data for this indicator comes from scientific fisheries surveys which sample the whole fish community and the methods require that surveys are conducted at regular intervals (annually) in the same area with a standard gear. Targets are set according to the principle that the fish community is moving towards recovery from fishing. The LFI is part of the indicator suite that member states have to report on under the data collection framework directive to evaluate the effects of fishing on the ecosystem (2010/93/EU). Currently, the most important data source for the LFI is fisheries groundfish surveys which are conducted as part of the ICES international bottom trawl survey programme in the North Sea, the Celtic Seas, Bay of Biscay and Iberia.

FC-3 Mean Maximum Length of demersal fish and elasmobranchs (MML) Core

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the relative composition of species within the community. The MML does not reflect any change in size structure of individual populations. Data for this indicator comes from scientific fisheries surveys which sample the whole fish community and the methods require that surveys are conducted at regular intervals (annually) in the same area with a standard gear. Targets are set according to the principle that the fish community is moving towards recovery from fishing. The MML is part of the indicator suite that member states have to report on under the data collection framework directive to evaluate the effects of fishing on the ecosystem (2010/93/EU). Currently, the most important data source for the MML is fisheries groundfish surveys which are conducted as part of the ICES international bottom trawl survey programme in the North Sea, the Celtic Seas, Bay of Biscay and Iberia.

FC-4 Bycatch rates of Chondrichthyes (Candidate)

The bycatch rate of chondrichthyes is a pressure indicator, which measures the degree of bycatch of Chondrichthyes in commercial fisheries. Chondrichthyes are cartilaginous fishes and include elasmobranchs (sharks, rays and skates) and chimaeras. Due to their life history traits of large body sizes, slow growth rates and low fecundity, chondrichthyes are particularly vulnerable to the impacts of overfishing (Dulvy and Reynolds, 2002; Reynolds, et al. 2001). Data for this indicator comes from scientific observer programmes onboard fishing vessels which quantify the bycatch of Chondrichthyes in commercial fisheries. It is envisaged that the indicator would be implemented based on a risk assessment, which identifies the fishing metiers which pose high risk to the sustainability of Chondrichthyes species. There are a number of scientific fisheries observer programmes within the OSPAR area under national and European legislations (such as data collection framework and deep-water access scheme); however there is no dedicated programme currently in place for this indicator. The target is to reduce the bycatch in cartilaginous fishes. The possibility to develop species specific bycatch targets needs to be further explored.

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Benthic Habitats

Code Previous Indicator Category code*

BH-1 4 Typical species composition Core

BH-2 7 Multi-metric indices Core

BH-3 11a/11b Physical damage of predominant and special habitats Candidate

BH-4 11b Area of habitat loss Candidate

BH-5 12 Size-frequency distribution of bivalve or other sensitive/indicator species Candidate

BH-1. Typical species composition (Core)

The indicator reflects the condition of benthic habitats by assessing either the integrity of the typical species composition within the associated community or the state of selected sensitive species. While the first rather unspecifically describes the condition of the community, the latter might be directly linked to a single pressure such as eutrophication. Typical species lists are commonly used in most national monitoring and assessment systems (e.g. according to the Habitats Directive Art. 17 reporting), but still have to be adapted and extended to the special requirements of the MSFD. The assessment is generally based on the simple presence of the species but potentially also on quantitative values like abundance, biomass or coverage which are usually generated in most monitoring programs. If simple species lists are used, the divergence from the full list may be interpreted as a degree of degradation leading to the target to maintain a substantial ratio of typical species of all regarded communities.

BH-2. Multi-metric indices (core)

Diversity indices and species richness indices as well as sensitivity/tolerance species classification systems are since long used to assess the qualitative state of benthic communities. The development of multi-metric indices, combining these indices and classifications, was made mandatory by the EU Water Framework Directive (WFD). Here, the different indices used are presented and a new MMI is proposed. The latter has not yet been fully endorsed by the expert team, however, the proposal to BDC is the use of an MMI (this or similar concept) as such. The proposed MMI contains a diversity indicator (e.g. Shannon index or Simpson index), a species richness indicator (e.g. the number of species, Margalef d) and an indicator for the proportions of sensitive, tolerant and opportunistic species of the benthic community (e.g. AMBI or the Infaunal Trophic Index (ITI)). This metric is expected to give a useful integrated quality score of the condition and functionality of the infaunal benthic community. The proposed MMI responds well to the pressure of among others oxygen depletion by organic matter, sand extraction and hydrodynamic pressure, as demonstrated in transitional waters. Pressure-impact validation of the MMI setup with physical pressures (e.g. fisheries) is an important point of attention. The collection of quantitative pressure data and the construction of a suitable pressure index is a key step in the pressure-impact validation of this MMI. The current monitoring is mostly adequate for the use of this MMI, because it is estimated that most countries use box core sampling.

BH-3. Physical damage of predominant and special habitats (Candidate)

This indicator aims to address the most important pressures to sea floor habitats in the OSPAR area which are those causing physical damage. It is an area-related indicator closely linked to condition elements. It is being designed to assess predominant as well as special habitat types and regarded particularly useful to

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target larger sea areas with relatively low effort. It builds upon two types of information, i) the distribution and sensitivity of a particular habitat type and ii) the distribution and intensity of human activities potentially causing physical damage, such as mobile bottom contacting fisheries, sediment extraction or offshore constructions. Although the proposed approach is mainly focused on physical pressures, habitat damage caused by other pressures such as eutrophication, hazardous substances etc, could also be accommodated within this approach, as long as information on habitat sensitivities and pressures information are available. Data for this indicator could be mainly derived from activity data sources such as EIAs and VMS data, and potentially from the Data Collection Framework (DCF). It is envisaged that some data collection and analysis for the testing and validation of this indicator could be required, in particular to improve the confidence of the approach

BH-4. Area of habitat loss (Candidate)

Components of this indicator (some special habitats) are transferable from the assessment of habitat area according to the requirements of the Habitats Directive. For predominant habitats in the wider sea area the indicator addresses the highest impact on benthic habitats caused by human activities: total functional loss and physical loss of area by building upon two types of information, i) the distribution and sensitivity of a particular habitat type and ii) the distribution of human activities that might lead to a loss of area (e.g. harbour construction, coastal protection, offshore constructions, sediment extraction).

Overall the indicator is partially developed. It originates from merged proposals from the OSPAR ICG-MSFD Workshop (Amsterdam, November 2011) and fulfils indicator 1.5.1 of the EU COM decision. A large part of this indicator is dependent on pressure data that is, in principle, already available, rather than on practical sampling and direct state assessments, the costs for monitoring low risk (predominant and certain special) habitats is therefore foreseen as relatively low. However, additional monitoring effort may be needed for some special habitat types.

BH-5. Size-frequency distribution of bivalves or other sensitive/indicator species in the community (Candidate)

Under natural conditions, populations of large species consist of different size-classes representing different age-groups. The natural balance between the large and small individuals within the population of a single species can be affected by anthropogenic influences such as physical disturbance, e.g. bottom trawling or sand extraction. Large, long-lived bivalves are in general regarded to be the most sensitive group to bottom- trawling within the soft-bottom communities. The basic parameter is the number per size (class). The condition of the population is assessed by comparing the actual and a (modelled) natural population structure with the latter serving as reference state. This indicator is currently not part of any regular European monitoring programme. However, it is principally considered possible to collect the relevant data using the samples taken within the framework of most standard benthos monitoring programmes as long as the species involved occur in adequate densities.

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Pelagic Habitats

Code Previous Indicator Category code*

PH-1 NA Changes of plankton functional types (life form) index Ratio Core

PH-2 NA Plankton biomass and/or abundance Core

PH-3 NA Changes in biodiversity index (s) Core

PH-1. Microplankton Community Index (Core)

This indicator is based on plankton lifeforms (functional groups), which can be used to assess plankton community response to pressures. The relative changes between different pairs of plankton lifeforms are linked to different pressures. The pairs of lifeforms have been chosen based on their ecological importance and responsiveness to anthropogenic pressures. This approach is taxonomically flexible and can be used with most plankton monitoring datasets.

PH-2. Plankton Biomass and/or abundance (Core)

The plankton biomass/abundance indicator provides information on the amount of phytoplankton and zooplankton production in an ecosystem. These indicators are measured different ways throughout and between contracting parties.

PH-3. Biodiversity Indices (Core)

Biodiversity indices are based on the description of diversity, species richness, evenness, or dominance. The advantage of these indices is that they allow an accurate description of the pelagic assemblages and also the direct comparison of communities that have few or no species in common. These indices are required for detailed qualitative assessment of biodiversity, in complement of others indices. Moreover, some of them are able to describe the impacts of water pollution on biotic communities, which often affect only the structure of the assemblages or the abundance of a single or few species, and not the biomass or the ratio between functional or size groups. However these indices require standard observation methods based on microscopy and a high level of expertise in taxonomic identification (which is very time consuming) because the sensitivity values are assigned at species level.

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Food webs

Number Previous Indicator Category code*

FW-1 NA Reproductive success of marine birds in relation to food availability Core

FW-2 NA Production of phytoplankton Core

FW-3 NA Size composition in fish communities (LFI) Core

FW-4 NA Changes in average trophic level of marine predators (cf MTI) Core

FW-5 NA Change of plankton functional types (life form) index Ratio between: Gelatinous zooplankton Core & Fish larvae, Copepods & Phytoplankton; Holoplankton & Meroplankton

FW-6 NA Biomass, species composition and spatial distribution of zooplankton Candidate

FW-7 NA Fish biomass and abundance of dietary functional groups Candidate

FW-8 NA Changes in average faunal biomass per trophic level (Biomass Trophic Spectrum) Candidate

FW-9 NA Ecological Network Analysis indicator (e.g. trophic efficiency, flow diversity) Candidate

FW-1 Reproductive success of marine birds in relation to food availability (Core) Top predators, such as marine birds and mammals, can be highly sensitive to changes in the abundance and diversity of their primary prey, as a result of fishing, bycatch and climate change. The indicator describes the annual mean breeding success (no. chicks fledged per pair) of marine bird species/ trophic guilds in relation to food availability. It is intended to complement another proposed indicator on annual breeding success of kittiwakes in relation to sandeel availability (under 1.3.1), in order to keep a watching-brief on the population condition of other species. Breeding success is monitored at colonies of a number of species (e.g. 10 species in the Wadden Sea) belonging to different trophic guilds (e.g. herbivorous and carnivorous benthivores, deep diver piscivores, etc.) throughout the NE Atlantic. Further work is needed to determine if the development of this indicator at the sub-regional scale will be restricted by lack of monitoring or data availability. Information on the availability of prey and knowledge on prey consumption will be needed to assign species to their respective feeding or trophic guilds so that the indicator can be further developed in a food web context. Further development of this indicator is currently underway in the ICES Working Group on Seabird Ecology.

FW-2 Productivity of phytoplankton (Core) Phytoplankton groups have fast turnover rates and therefore respond rapidly to anthropogenic pressures e.g. waste water discharge, agricultural practices, etc. Primary production is an essential parameter to assess food web functioning and to evaluate the potential impacts of bottom-up pressures on higher trophic levels of the food web. Moreover, considering primary production at different size ranges could provide information on the energy flow between different parts of the food web. Other parameters, such as chlorophyll biomass and oxygen concentration could be used in addition to primary production so that the impacts of pressures could be more easily interpreted. As an indicator of habitat quality, target values have been established, however, further work is needed to establish appropriate targets in a food web context. Upper limits of primary production will be set on an annual basis and on the basis of seasonal events (type spring bloom). The indicator is practicable since the metrics could be collected during existing monitoring programmes and therefore, additional costs for monitoring will be minimal.

FW-3 Size distribution in fish communities (e.g. Large Fish Indicator) (Core)

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Since large-bodied species tend to be more vulnerable to fishing, a size based measure such as the Large Fish Indicator (LFI), can be used as an indicator of fishing pressure. As a target, the LFI states that the proportion (by weight) of fish greater than a specific size caught during routine demersal fish surveys (e.g. the ICES International Bottom Trawl Survey) should reach or exceed the reference level. By “Large Fish Indicator” we denote the specific definition of the OSPAR EcoQO in the North Sea and its extensions to other regions. However, adaptations of the indicator to stronger reflect system-level properties of food webs are still needed. For example, inclusion of pelagic species is desirable and inclusion of non-fish species, as conventionally done for the MTI, should be considered. Current implementations focus on demersal habitats, ideally, however, data for this metric should come from scientific fisheries surveys which sample the entire fish community. Additional information on trophic structure will be needed to interpret the LFI in a food web context. Information on the trophic structure of the fish community can be obtained by assigning fish species within a food web to their respective feeding or trophic guilds and monitor their relative changes in biomass (cfr. Trophic Guild Indicator; ICES, 2012; see Case study in Part C.

FW-4 Changes in average trophic level of marine predators (e.g. Marine Trophic Index) (Core) The Marine Trophic Index (MTI) addresses issues related to food web integrity, ecosystem functioning, and biodiversity loss. This indicator has been used worldwide to assess the ecosystem impacts of fishing and demonstrates the now well known “Fishing down marine food web” phenomena, a major fishing-induced shift in marine ecosystems. It has been formally adopted as an indicator of biodiversity by the European Environment Agency coordinating work in the Streamlining Biodiversity Indicators in Europe process (SEBI). Whereas the indicator 4.3.1. is suggested to relate to a single group/species, biomass could be considered over several trophic levels simultaneously. The MTI is an example of such an ecosystem-based indicator. It is usually calculated for the exploitable fraction of the ecosystem (i.e., invertebrates, fish, marine mammals) and provides the mean trophic level of predators present. In order to establish trophic relationships so that trophic levels can be estimated more accurately, data on species feeding habits is urgently needed across trophic groups, and this is especially true for species at lower trophic levels. Further regionalisation of the indicator is needed and for this purpose, the use of case studies with long-time series data across regions will help to identify a reference level and interpret potential deviations.

FW-5 Change of plankton functional types (Core) The use of functional groups is often favoured over indicator species since indices of species abundance are frequently subject to large inter-annual variation, often due to natural physical dynamics rather than anthropogenic stressors. To define GES for food webs, life-form pairs of plankton can be selected to provide an indication of changes in: (1) the transfer of energy from primary to secondary producers, e.g. phytoplankton and copepods ratio; (2) the pathway of energy flow and top predators, e.g. gelatinous zooplankton and fish larvae ratio; and (3) benthic/ pelagic coupling, e.g. holoplankton and meroplankton ratio. In contrast to taxonomical indicators, life-form indicators will be more easily extrapolated across regions, however, some regional adaptation in the selection of pairs will be necessary. Target setting is currently under development. Long-term time-series as well as high frequency monitoring of plankton will be needed, particularly in habitats considerably influenced by anthropogenic pressures. Routine assessment on gelatinous zooplankton will need to be established across the OSPAR region.

FW-6 Biomass, species composition and spatial distribution of zooplankton (Candidate) Long-term changes in the biomass, species composition and size structure of zooplankton communities can be used to indicate environmentally driven changes in the pelagic system, and the possible impact of anthropogenic pressures such as nutrient enrichment and oil spills. Currently, this indicator is partly implemented by HELCOM but will need further testing and development to become operational across the OSPAR region. Further research will be necessary to understand the responses of zooplankton to changes in water quality and the effects of these responses on higher trophic levels. This indicator will need a trend based target. Long-term time-series as well as high frequency monitoring of plankton will be needed,

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particularly in habitats considerably influenced by anthropogenic pressures. The frequency of sampling should be monthly or preferable bi-weekly during the productive season. Microzooplankton and gelatinous zooplankton are generally undersampled groups across the OSPAR region.

FW-7: Fish biomass and abundance of dietary functional groups (Candidate) Changes in the biomass of fish through time describe abundance trends of a functionally important biodiversity component. Furthermore, by coupling fish biomass with primary production, information on trophic efficiency can be derived in addition to the direct impacts of multiple pressures on food web components, for example, the effects of nutrient inputs via phytoplankton and selective extraction via fish biomass. Whilst the conceptual development of this indicator is underway, further work is needed to make this indicator operational. The biomass of fish can be calculated from abundance data from existing scientific surveys. Partitioning such data according to functional/dietary groups eases their statistical and ecological interpretation. However, currently comprehensive datasets on the feeding ecology of many of the key species in marine food webs are insufficient and there is a need to coordinate data collection across trophic levels over a large spatial and temporal extent.

FW-8 Changes in average faunal biomass per trophic level (Biomass Trophic Spectrum) (Candidate) Total biomass within one or more trophic levels is often correlated with the rate or level of ecosystem function. The Biomass Trophic Spectrum (BTS) is an example of an ecosystem indicator that represents the distribution of the biomass of all trophic levels equal to or higher than 2, i.e. marine mammals, fish and invertebrates, as a function of trophic level. Theoretical simulations and empirical analyses of specific case studies have shown that anthropogenic impacts from fishing leads to a decrease in the abundance of high trophic levels and in some cases to an increase in low trophic levels abundance. Further development will be needed to understand the responsiveness of the indicator to pressures other than fishing. An important advantage of this indicator is that the proposed concept is transferable across OSPAR regions, however, mean trophic levels of species will need to be estimated on a regional/sub-regional scale. Currently, comprehensive datasets on the feeding ecology of many of the key species in marine food webs are insufficient, and this is especially true for species at lower trophic levels. In order to advance the development of food web indicators in general, there is a need to coordinate data collection across trophic levels over a large spatial and temporal extent.

FW-9: Ecological Network Analysis Indicator (e.g. flow diversity) (Candidate) Flow diversity determines diversity and evenness of flows between food web compartments and thus measures its structure and energy flows as a whole. An important advantage of this indicator is that it can be used as a link between food web characteristics and habitat diversity. For a given food web, high flow diversity might represent a stable status of an ecosystem. It is not defined yet from which point on a given food web becomes destabilized and thus will be sensitive to perturbations. We can assume that if top predators are only dependent on a single food source that this would be an alarming situation. The food web should be characterized in terms of biomass of the particular compartments and it is necessary to know the food spectra of the different species forming the food web. The flow diversity index can then be derived from ecological network analysis and is calculated from the routine of this modelling. Further development will be needed to make this indicator operational in a management context. The target setting method will likely be directional or trend based. Data on all trophic levels will be necessary to feed the model so coordinated data collection across trophic levels over a large spatial and temporal extent is needed. Monitoring locations should reflect the relevant types of habitats and climate regimes in the respective region.

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Non-indigenous species

Number Previous code* Indicator Category

NIS-1 41 Pathways management measures Candidate

NIS-2 40 Rate of new introductions of NIS (per defined period) Candidate NIS-1: Pathways management measures (Candidate) The pathway management indicator aims to reduce the risk of the introduction of new NIS through management of pathways and vectors of introduction, with the effectiveness of the applied management measured as a rate of introduction of new NIS (non-indigenous species) into managed areas. There is currently limited management and monitoring for NIS undertaken by member states and further work is required to develop appropriate indicators. A risk based approach to identify locations where NIS are most likely to be introduced is recommended to provide guidance on where management strategies and surveillance are targeted. Management strategies for high risk pathways and methods by which management effort can be quantified need to be developed. Monitoring for the absence/presence of new NIS in the high risk locations will provide a rate of introduction that can then be compared to the level of effort implemented under the management strategies.

Requirements for further development of the pathway management indicator include:  Identification of high risk locations.  Development of management strategies at high risk locations and methodology to quantify.  Development of monitoring programmes at high risk locations.  Methodology to compare management effort with rate of introduction to determine GES.

NIS-2: Rate of new introductions of NIS (per defined period) (Candidate) The trend indicator for non-indigenous species aims at reflecting the rate of increase or decrease in new introductions of non-indigenous species through anthropogenic activities. The development of the trend indicator is based on two complimentary activities. The first activity is creating an understanding about the technical development methodology to define the appropriate indicator parameters, and the monitoring strategies for recording the numbers, occurrences and the spatial distribution of new introductions. The second activity is focused on our understanding of the operational process of the trend indicator. This includes defining the operational limits and the reference situations for the indicator. Knowledge of the baseline values and the (trend-based) targets for reflecting the desired Good environmental status (GES) are of crucial importance. The trend indicator is based on monitoring data and could become operational after two years of consistent monitoring in the designated areas. The seasonal variability determines the monitoring frequency while the number of import vectors determines the type and the number of monitoring points in the areas. The annual monitoring costs should be limited and may not exceed 100.000 Euros for the entire coastline.

Requirements for developing a common trend indicator for the Non-indigenous Species include the following activities:  Assess all import vectors present in the area,  Select at least two monitoring areas for each vector,  Review the type and the extent of the present monitoring strategy, and  Developed (if required) a new monitoring protocols for non-indigenous species per area

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PART C: Technical specification of proposed common biodiversity indicators

Mammals

Code Previous Indicator Category code* M-1 31&33 Distributional range and pattern of grey and harbour seal haul-outs and breeding colonies Core

M-2 32&34 Distributional range and pattern of cetaceans species regularly present Core

M-3 35 Abundance of grey and harbour seal at haul-out sites & within breeding colonies Core

M-4 36 Abundance at the relevant temporal scale of cetacean species regularly present Core

M-5 37 Harbour seal and Grey seal pup production Core

M-6 38&39 Numbers of individuals within species being bycaught in relation to population Core

Draft OSPAR Common Indicators: marine mammals (M-1)

Distributional range and pattern of grey and harbour seal haul-outs and breeding colonies

1. Indicator “Distributional range and pattern of grey and harbour seal haul-outs and breeding colonies”. 2. Reasoning for the development of this indicator Marine mammals, including harbour and grey seals, are top predators, and comprise an important part of biodiversity (Descriptor 1). As harbour and grey seal are taken up under the Habitats Directive (Annex II), their distributional range and pattern comprises a key aspect for securing and achieving GES according to the MSFD. Number of CPs reporting/using the indicator (n=9) : 7 Consensus among CPs on usefulness as part of a region wide set (n=8): 7 3. Parameter/metric “Distribution and number of harbour and grey seal haul-outs and breeding colonies”. Since in certain areas seals alternate among vast numbers of sites depending on weather conditions and the season, range may be used instead of number of haul-outs and breeding colonies. 4. Baseline and reference level There are baseline data on historical distribution and range for many populations of harbour and grey seals. Most current populations of harbour seal have distributions coinciding with historical distributions. However, grey seals were extirpated in the Wadden Sea in the early Middle Ages, in the Skagerrak in the 1750’s and in the Kattegat in the 1930, indicating that setting a historic baseline is not straightforward. Moreover, the historical distributional range and pattern of haul-out sites and colonies is a situation that cannot realistically be restored, given for instance coastal developments and tourism. Climatic changes may have important consequences. It is therefore likely that a modern baseline will have to be utilized, such as a favourable reference situation (Habitats Directive) or maximum range derived from surveys performed during the last decade.

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5. Target setting The proposed target is: “No decrease with regard to the baseline beyond natural variability, and where possible restoration towards favourable reference conditions”. This target should be set for every Management Unit (MU; see further). MUs should not be specifically listed in the target, thus avoiding the need to rewrite or update the wording of the indicator as new information on populations comes to light. Identifying trends near the edge of the range of harbour and grey seals will be especially important, and movements of seals between MUs (immigration and emigration) need to be taken account of. 6. Spatial scope For monitoring the EcoQO’s on seals, the North Sea has been subdivided into different MUs, which include stretches of coastline with presumed major exchanges of animals between the colonies, and with a coordinated monitoring scheme in place. A subdivision into MUs should be made for the whole range of both species, with indications of current and former occupancy. Genetic criteria for setting MUs in harbour seals are available, and where appropriate other evidence that suggests demographic differences should be utilised. The widespread use of telemetry may provide for more information on foraging range and distribution. 7. Monitoring requirements Existing OSPAR EcoQO’s cover grey seal pup production and population size of hauled out harbour seals, but there is clearly an overlap with the distributional range, and an overlap between range and distributional pattern. The same monitoring will be used to undertake both analyses. Monitoring of distributional range and pattern is well covered in most areas. This monitoring, at seal haul-out sites and at colonies, is predominantly targeted at elucidating trends in abundance (indicator M-3) and for monitoring pup production (indicator M-5). In the Wadden Sea the monitoring and management under the Trilateral Monitoring and Assessment Programme and Wadden Sea Plan (Trilateral Seal Agreement; CMS) are well established over recent decades, and support the indicators and targets for harbour seals, and (although not under CMS) also the ones for grey seals. Similar work has also been ongoing in the UK over a similar time frame. 8. Appropriateness of the indicator There is usually no straightforward link between the parameter and human activities. It is generally possible to detect deterioration or improvement of the distribution of harbour and grey seal by monitoring their presence on existing (and former) breeding colonies or haul-out sites. When recording changes, it is necessary to assess and interpret these, in order to discriminate natural vs. human-induced changes. Fundamental knowledge of behaviour and health of individuals from undisturbed areas is required for this discrimination. Changes and trends may reveal a cause-effect relationship. Changes due to climate change and epizootics, not directly related to a human activity, may be important. 9. Reporting Given that most populations have a transboundary distribution, and that shifts between colonies and haul-out sites can occur, agreements have to be made on monitoring and reporting in order to be able to make an assessment. 10. Costs As the monitoring is coastal in nature, costs are limited. It is already partly in place: the monitoring for the indicators M-1 (distributional pattern), M-3 (abundance) and M-5 (pup production) can be combined. 11. Further work

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Future steps are similar for the parameters M-1 (distributional pattern), M-3 (abundance) and M-5 (pup production). 1) Compilation of existing data on the distributional range and pattern. 2) Subdivision of the area (beyond the North Sea) into MUs, and a revision of the North Sea MUs. 3) Development of a baseline for each MU. 4) Development of a standardized monitoring methodology, or alternatively a mechanism for standardizing data post collection. 5) Development of an assessment tool. Literature OSPAR, 2009. Evaluation of the OSPAR system of Ecological Quality Objectives for the North Sea (update 2010). OSPAR Biodiversity Series, 406.

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Draft OSPAR Common Indicators: marine mammals (M-2) Distributional range and pattern of cetacean species regularly present

1. Indicator

“Distributional range (1.1.1) and distributional pattern within range (1.1.2)”.

The cetacean species for use as a core indicator under OSPAR are limited to the following continental shelf species: harbour porpoise, coastal and offshore bottlenose dolphins, white-beaked dolphin and minke whale. Common dolphin are considered representative of the wider European waters (i.e. both off and on the continental shelf). It should also be noted that bottlenose dolphins can be divided into two types. There are well known small resident coastal groups (possibly to be divided into different Management Units) and a much larger number of animals in groups that are wide ranging both inshore and offshore.

2. Reasoning for the development of this indicator

Marine mammals, including cetaceans, are top predators, and comprise an important part of biodiversity (Descriptor 1). As all cetacean species are taken up under the Habitats Directive (annex II and/or IV), their distribution comprises a key aspect for securing and achieving GES according to the MSFD.

The distribution of cetaceans can be monitored using a variety of techniques (e.g. visual surveys from vessels and planes; towed hydrophone arrays; static acoustic monitoring; mark-recapture techniques using photo-identification). With the possible exception of some coastal bottlenose dolphin populations, cetaceans are generally mobile over large spatial and temporal scales. For example, there was a significant southerly shift in the North Sea harbour porpoise population between the two SCANS surveys (1994 and 2005). Assessments therefore need to be undertaken at an appropriate scale and it should be noted that expansions in range are far easier to detect than contractions. A good understanding of natural movement patterns (e.g. seasonal patterns) is required prior to any deterioration or expansion being detected and links made with anthropogenic activities.

Because of the scale required for assessments, a transboundary approach to the collection, collation and analysis of data will be required. Such an approach has also been suggested for Favourable Conservation Status assessments for the Habitats Directive.

Number of CPs reporting/using the indicator (n=9) : 8 Consensus among CPs on usefulness as part of a region wide set (n=8): 8 3. Parameter/metric

“Distributional range of cetacean species regularly present and distributional pattern at the relevant temporal scale of cetacean species regularly present.”

There is a very clear overlap between distributional range (1.1.1) and distributional pattern within range (1.1.2). The same monitoring will be used to undertake both analyses. An assessment of distribution, including trends over time, is required as part of the Favourable Conservation Status (FCS) assessments for

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the Habitats Directive (as short term and long term trends)3.

4. Baseline and reference level

Although the baseline should be based on historical data, these are not available at the appropriate spatial and temporal scale. Moreover, the historical distributional range and pattern of many cetacean species (i.e. pre-commercial hunting) cannot realistically be restored (assuming it has contracted, which is unknown for many species) as today’s marine environment is very different. Climatic changes may have important consequences. It is likely that a modern baseline will have to be utilised, such as that provided through the Joint Cetacean Protocol (JCP) analyses, or to use FCS, although for the latter option international coordination is needed, as FCS is now set at geographical scales that are, for most species, not suitable for an overall assessment of the population.

For the harbour porpoise, there have been important distributional shifts in the North Sea during the last decades.

For the coastal bottlenose dolphin, many populations are small, and some estuaries that historically contained populations no longer do so (e.g. Humber an Thames Estuaries, UK); in other locations (e.g. the Sado Estuary, Portugal), populations are endangered. The relationship between inshore and offshore populations is not well known, and the much larger offshore populations are relatively poorly known.

White beaked dolphins occur over a large part of the European continental shelf, including the North Sea, but are rare in the Irish Sea, Celtic Sea, Channel and Bay of Biscay, and around the Iberian Peninsula.

Minke whales are widely distributed in European shelf waters, particularly along the Atlantic seaboard and in the northern and central North Sea.

For common dolphins, there are large seasonal movements in the population on and off the continental shelf, whilst in some areas the possibility of inshore and offshore populations has been suggested. For this species, as with bottlenose dolphin, it is essential that assessments include consideration of the species off the continental shelf.

5. Target setting

The proposed target is “Maintain populations in a healthy state, with no decrease in population size with regard to the baseline (beyond natural variability) and restore populations, where deteriorated due to anthropogenic influences, to a healthy state”. Some difficulties can be encountered here, because there is usually no straightforward link between the distributional range and pattern, and human activities. Although the baseline for each species considered should be based on historical data, these are generally not available at the appropriate spatial and temporal scale.

6. Spatial scope

The geographical scope of the indicator is species dependent. With the exception of coastal bottlenose dolphin populations, cetacean populations cover large spatial scales often extending beyond European North Atlantic waters for example. Assessments therefore need to be undertaken at an appropriate scale and a good understanding of natural variability and patterns of movement is required prior to any decline or increase in population size being detected and links made with anthropogenic activities. Management Units

3 In the 2007 FCS assessments, this was undertaken on a country by country basis which led to an unsatisfactory standard of assessment at the European North Atlantic scale (ICES, 2009). For the 2013 FCS assessments, a greater emphasis has been placed on the need for a transboundary approach (European Commission, 2011), although it seems unlikely that this will occur.

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for cetacean species, also to be used in indicator M-4 (Abundance) and M-6 (bycatch) assessments, have been defined by ASCOBANS (Evans & Teilmann, 2009) and further reviewed by ICES (2012).

7. Monitoring requirements

The objective of the monitoring should be to detect trends, in particular negative ones, in the distributional range and pattern, due to human pressures. Human pressures are diverse: some human activities remove individuals directly from the population (e.g. bycatch). Other pressures degrade condition and health of animals (e.g. contaminants, food depletion), or displace populations towards habitats of poorer quality (disturbance by noise, habitat modification). Monitoring is undertaken through a variety of approaches and by many different organisations. There are large scale international surveys such as SCANS and CODA that occur at a decadal scale, annual national surveys that occur in the waters of some Member States and, at a more localised scale, there are various surveys undertaken by the state, academic institutions and/or non-governmental organisations.

A mechanism, the JCP, is being developed that can bring these diverse datasets together at the NW European Atlantic scale. Effort-related cetacean sightings data from all major data source types are included4. These data, collected between 1979 and 2010, represent the largest NW European cetacean sightings resource ever collated. It is recognised, however, that there remain some significant datasets missing such as the annual national monitoring undertaken by some Member States.

It is expected that the JCP will deliver information on the distribution, relative abundance and population trends of the more regularly occurring cetacean species occurring in northwest-European waters. A preliminary phase of the project, covering the Irish Sea and west coast of Scotland, was completed in 2011 (Paxton et al., 2011), and the final phase of the project, covering north-west European waters, will be published in 2013.

Strandings data represent to date the most extensive and long-term source of demographic data for a number of cetacean populations (at least in areas where strandings occur). Strandings data are currently clearly underexploited and rarely analysed at an international level. They could yield useful supplementary information about trends in the distributional range and pattern of cetaceans. In addition, the investigation of stranded cetaceans (or cetacean carcasses found at sea or bycaught and returned to port) can yield information of causes of death, and as such potentially contribute information about human pressures as well as provide data on a number of life history parameters. Coverage needs to be reliable, and biological and pathological investigations need to be standardised.

The monitoring and assessment undertaken for distributional range and pattern of cetaceans, will be made in combination with indicator M-4 (abundance).

8. Appropriateness of the indicator

In most cases it is difficult to find a straightforward link between the distribution and distributional range of cetaceans and human activities. There are multiple pressures, and climate change is also a factor influencing abundance and distribution. However, as top predators and animals well known and of general public concern, changes in distribution and abundance are important, and should be assessed against changes in human activities and climate change to detect cause-effect relationships, where necessary followed by the appropriate measures.

4 E.g. SCANS I & II, CODA, European Seabirds at Sea (ESAS), data from the Sea Watch Foundation (SWF) and other non- governmental organisations, as well as the industry (e.g. in relation to potential renewable energy installations)

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9. Reporting

Given that populations have a transboundary distribution (except for coastal bottlenose dolphins), agreements have to be made on monitoring and reporting in order to be able to make an assessment.

10. Costs

Monitoring distribution and distributional range of cetacean can range from fairly cheap (monitoring of an inshore population with a limited range) to very expensive (monitoring of an offshore population distributed over a large area); however, part of the monitoring is in place (in a combination of indicator M-2, M-4 and M-6), while new resources are needed, e.g. for large scale decadal surveys and more comprehensive annual surveillance (see also indicator M-4).

11. Further work

Future steps are similar for the indicators M-2 (distributional range and pattern) and M-4 (abundance).

1) Compilation of existing data on the distributional range. This has already begun through the JCP, although international agreement is required that this represents the best way forward. Should such an agreement be obtained, then the JCP will need to be extended to include as many national datasets as possible.

2) Development of a baseline for each species.

3) Development of a standardized monitoring methodology, and mechanisms for standardizing data post collection where different methods are used. Development of a system to utilise strandings data.

4) Development of an assessment tool.

Literature

European Commission, 2011. Assessment and reporting under Article 17 of the Habitats Directive Explanatory Notes & Guidelines for the period 2007-2012. Available at: http://circa.europa.eu/Public/irc/env/monnat/library?l=/habitats_reporting/reporting_2007- 2012/reporting_guidelines&vm=detailed&sb=Title

Evans, P.G.H. & Teilmann, J., 2009. ASCOBANS/HELCOM Small Cetacean Population Structure Workshop. ASCOBANS, Bonn, Germany, 141 pp.

ICES, 2009. Report of the Working Group on Marine Mammal Ecology (WGMME), February 2–6 2009, Vigo, Spain. ICES CM 2009/ACOM:21. 129 pp.

ICES, 2012. Report of the Working Group on Marine Mammal Ecology (WGMME), March, 2012.

Paxton, C.G.M. , M. Mackenzie, M.L Burt, E. Rexstad & Thomas, L., 2011. Phase II Data Analysis of Joint Cetacean Protocol Data Resource. Report to Joint Nature Conservation Committee, Contract number C11-0207-0421. Available at: http://jncc.defra.gov.uk/pdf/JCP_Phase_II_report.pdf

Paxton, C.G.M. & Thomas, L., 2010. Phase One Data Analysis of Joint Cetacean Protocol Data. Available at: http://jncc.defra.gov.uk/pdf/JCP_Phase_1_Analysis.pdf

Thomas, L., 2009. Potential Use of Joint Cetacean Protocol Data for Determining Changes in Species’ Range and Abundance: Exploratory Analysis of Southern Irish Sea Data. Available at: http://jncc.defra.gov.uk/pdf/JCP_Prelim_Analysis.pdf

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Draft OSPAR Common Indicators: marine mammals (M-3)

Abundance of harbour and grey seals at haul-out sites & within breeding colonies

1. Indicator

Abundance of harbour and grey seals

2. Reasoning for the development of this indicator

Marine mammals, including seals, are top predators, and comprise an important part of biodiversity (Descriptor 1). As harbour and grey seal are taken up under the Habitats Directive (annex II), their abundance comprises a key aspect for securing and achieving GES according to the MSFD.

Number of CPs reporting/using the indicator (n=9) : 7 Consensus among CPs on usefulness as part of a region wide set (n=8): 7 3. Parameter/metric

“Abundance, at the appropriate spatial and temporal scale, of harbour and grey seal at haul-out sites and/or within breeding colonies (as appropriate)”.

Existing OSPAR EcoQO’s encompass grey seal pup production (which is scaled up to provide abundance estimates) and the population size of harbour seals (estimated from haul out counts), but the monitoring for this indicator would also yield the necessary information for indicator M-1 (distributional range and pattern). In the Baltic grey seals are surveyed during moult in a similar way as harbour seals.

4. Baseline and reference level

Although the baseline should derive from historical data, these are not available everywhere. Moreover, the historical abundance of seals at haul-out sites and colonies is a situation that cannot realistically be restored, given for instance large-scale coastal developments and tourism. Climatic changes and outbreaks of PDV may have important consequences. It is therefore likely that a modern baseline will have to be used, such as a favourable reference situation for abundance at the different Management Units (MUs), as defined in the Favourable Conservation Status assessments under the Habitats Directive or maximum counts in the last decade. However, as different countries have set different baselines, there might be a need for a more coherent definition. Baselines could be set to the level at which population growth rates are levelling off due to natural causes, with a need to decide a time period over which this is measured.

5. Target setting

The proposed target is: “Maintain populations in a healthy state, with no decrease in population size with regard to the baseline (beyond natural variability) and restore populations, where deteriorated due to anthropogenic influences, to a healthy state“.

This target should be set for every Management Unit (MU). MUs should not be specifically listed in the target (as is the case now in the OSPAR EcoQO), thus avoiding the need to rewrite or update the wording of the indicator as new information on populations comes to light. Identifying trends in colonies near the edge of the range of harbour and grey seals will be especially important, as will movements of seals between MUs (immigration and emigration).

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6. Spatial scope

For monitoring the EcoQO’s on seals, the North Sea has been subdivided into different monitoring areas. A subdivision of the European populations into MUs should be made for the whole range of both species, with indications of current and former abundance (or alternatively a favourable reference situation). While population estimates are made at the MU level through combining site level estimates, movements between Management Units need to be taken into account.

7. Monitoring requirements

It is possible to detect changes in abundance of harbour seals from haul-out counts and for grey seals from pup counts and, where this is not possible, from moult counts. In most parts of the distributional range of the harbour and grey seal, there is sufficient monitoring at haul-out sites and/or breeding colonies. This monitoring takes place in combination with the monitoring of the parameters 31 (distributional range), 33 (distributional pattern) and 37 (pup production). However, some MUs are monitored annually, whereas UK and Norwegian harbour seal MUs are monitored every fifth year.

In the Wadden Sea, the monitoring and management under the Trilateral Monitoring and Assessment Programme and Wadden Sea Plan (Trilateral Seal Agreement; CMS) are well established over the last decades, and support the indicators and targets for harbour seals, and (although not under CMS) also the ones for grey seals. Similar work has also been ongoing in the UK over a similar time frame.

8. Appropriateness of the indicator

Although no straightforward link exists between the abundance of seals and human activities, a number of human activities may lie at the basis of trends and changes in abundance. The monitoring of the indicator serves as to trigger the investigation of possible cause-effect relationships as a basis for measures. Changes due to epizootics might be important. For example, Phocine Distemper Virus (PDV) has caused past declines in European harbour seal populations, with the first and most significant outbreak in 1988 and the second in 2002. Also, there have been recent increases in the grey seal populations, and climate change may have important consequences for both species.

9. Reporting

Given that most populations have a transboundary distribution, and that shifts between colonies and haul-out sites can occur, agreements have to be made on monitoring and reporting in order to be able to make an assessment.

10. Costs

Costs should be relatively low, given that seal colonies are inshore. The monitoring should be combined with the monitoring for indicators M-1 (distributional range and pattern) and M-5 (pup production).

11. Further work

Future steps are similar for the indicators M-1 (distributional range and pattern) and M-5 (pup production).

1) There needs to be a subdivision of the whole area into Management Units in which monitoring needs to be coordinated.

2) Existing data for an agreed time period within each Management Unit need to be compiled.

3) Movements between Management Units need to be assessed.

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4) Baselines for each Management Unit need to be developed.

5) A standardized monitoring methodology and time frame needs to be agreed, or alternatively a mechanism for standardizing data post collection.

6) An assessment tool needs to be developed.

Literature

OSPAR, 2009. Evaluation of the OSPAR system of Ecological Quality Objectives for the North Sea (update 2010). OSPAR Biodiversity Series, 406.

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Draft OSPAR Common Indicators: marine mammals (M-4)

Abundance at the relevant temporal scale of cetacean species regularly present

1. Indicator

“Abundance, at the relevant temporal scale, of cetacean species regularly present”.

The cetacean species for use as a core indicator under OSPAR are limited to the following continental shelf species: harbour porpoise, bottlenose dolphin, white-beaked dolphin and minke whale. Common dolphin are considered representative of the wider European waters (i.e. both off and on the continental shelf). It should also be noted that bottlenose dolphins can be divided into two types. There are well known small resident coastal groups (possibly to be divided into different Management Units) and groups, comprising much more animals, that are wide ranging both inshore and offshore.

2. Reasoning for the development of this indicator

Marine mammals, including cetaceans, are top predators, and comprise an important part of biodiversity (Descriptor 1). As cetaceans are taken up under the Habitats Directive (annex IV), their abundance (criterion 1.2.) comprises a key aspect for securing and achieving GES according to the MSFD. However, as it is not feasible to monitor all cetaceans, which include uncommon, widely-dispersed and oceanic species, the indicator is limited to the population size of Management Units of a number of shelf species for which objectives were set or measures proposed in the framework of OSPAR, ASCOBANS, EC fishery regulations and the Habitats Directive (Annex II).

The monitoring and assessment of the indicator is partly in place, with monitoring already required under the Habitats Directive and fisheries legislation (Regulation 812/2004 and Data Collection Regulation).

Number of CPs reporting/using the indicator (n=9) : 8 Consensus among CPs on usefulness as part of a region wide set (n=8): 8 3. Parameter/metric

“Abundance of cetacean species regularly present at the relevant temporal and spatial scale“.

The same monitoring used to assess changes in cetacean abundance will be used to assess changes in distribution. An assessment of abundance, including trends over time, is required as part of the Favourable Conservation Status (FSC) assessments for the Habitats Directive5.

4. Baseline and reference level

Although the baseline should derive from historical (i.e. pre-1900) data, these are not available at the appropriate spatial and temporal scale. Moreover, the historical abundance of many cetacean species is unknown and cannot realistically be restored (where it is known to have declined) as today’s marine environment is very different. Climatic changes may have important consequences. A modern baseline has to be utilised for the species considered, such as that provided through the SCANS/CODA surveys.

5 In the 2007 FCS assessments, this was undertaken on a country by country basis which led to an unsatisfactory standard of assessment at the European North Atlantic scale (ICES, 2009). For the 2013 FCS assessments, a greater emphasis has been placed on the need for a transboundary approach (European Commission, 2011), although this is unlikely to occur.

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Management Units (MUs), population distribution, and/or stock structure needs to be agreed upon for all relevant species.

5. Target setting

For coastal bottlenose dolphins it could be “Maintenance of the current levels of the populations where stable, and where feasible and relevant, an increase in numbers”. A recovery in areas where it was known to occur up to the 20th century might not be realistic in the short or medium term, given the life history parameters of bottlenose dolphins, with a slow reproduction. However, as several of the estuaries they occupied in the past are now much cleaner than they were, and fish are returning to them (e.g. Thames and Clyde estuaries), it is possible that they return to colonise these areas within a few decades.

For cetacean populations with a relatively small range, FCS could also be used.

6. Spatial scope

The geographical scope of the indicator is species dependent. With the exception of some coastal bottlenose dolphins, cetacean populations cover large spatial scales often extending beyond European North Atlantic waters for example. Assessments therefore need to be undertaken at an appropriate scale and a good understanding of natural variability and patterns of movement is required prior to any decline or increase in population size being detected and links made with anthropogenic activities. MUs for cetacean species, also to be used in indicator M-6 (bycatch) assessments, have been defined by ASCOBANS (Evans & Teilmann, 2009) and further reviewed by ICES (2012).

7. Monitoring requirements

The abundance of cetaceans can be monitored using a variety of techniques (e.g. visual surveys from vessels and planes, towed hydrophone arrays, static acoustic monitoring devices). Because of the scale required for assessments, a transboundary approach to the techniques used, and the collection, collation and analysis of data will be required. Also strandings data can be useful as a supplementary measure to assess trends in the distribution and abundance of cetaceans6.

The objective of the monitoring should be to detect trends, in particular negative ones, in the abundance of cetacean populations due to human pressures. As cetacean monitoring is costly, the frequency at which data should be collected shall depend on the species monitored; it can be yearly and with a high resolution for species with a limited range (coastal bottlenose dolphin, harbour porpoise, white-beaked dolphin) up to decadal and with a coarse resolution for species widely-distributed offshore. The area surveyed should make an interpolation at non-visited locations possible within an acceptable confidence interval, making it possible to detect changes.

Monitoring is undertaken through a variety of approaches and involving many different organisations.

6 Strandings data represent to date the most extensive and long-term source of demographic data for a number of cetacean populations (at least in areas where strandings occur). Although they cannot yield an absolute figure for abundance, they can be interpreted to provide for a relative indication of local and temporal variations in coastal abundance. Strandings data are currently clearly underexploited and rarely analysed at an international level. They could potentially yield useful information about trends in the distribution and local changes in relative occurrence of cetaceans. In addition, the investigation of stranded cetaceans can yield information on a number of life history parameters, and on causes of death, and therefore provide some indications about human pressures.

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There have been large scale international surveys such as SCANS and CODA, annual national surveys in the waters of some Member States and, at a more localised scale, various surveys undertaken by the state, academic institutions and/or non-governmental organisations7. For the monitoring of this indicator, a coordinated combination of these types of survey will be required.

Since part of the monitoring is used to set baselines against which to set bycatch limits or trends, boundaries for Management Units need to be defined8.

8. Appropriateness of the indicator

There is usually no straightforward link between the abundance of cetaceans and human activities. There are multiple pressures, and climate change is an additional factor influencing abundance and distribution. However, as top predators and animals general public concern, changes in distribution and abundance are important, and should be assessed against changes in human activities and climate change to detect cause-effect relationships, where necessary followed by the appropriate measures.

9. Reporting

Given that populations have a transboundary distribution (except for some coastal bottlenose dolphins), agreements have to be made on monitoring and reporting in order to be able to make an assessment.

10. Costs

Cetacean monitoring can range from fairly cheap (monitoring of an inshore population with a limited range) to very expensive (monitoring of an offshore population distributed over a large area). Part of the monitoring is in place (in a combination of indicator M-2, M-4 and M-6), while new resources are needed, e.g. for annual surveillance and large scale decadal surveys (see also indicator M-2).

11. Further work

Work has begun on several subjects, but further work and/or agreement is needed on:

1) A compilation of existing data on abundance. This has already begun through the JCP, but it is recognised that a number of significant national datasets are missing. International agreement will be required to determine whether this is the best mechanism for generating transboundary assessments.

7 A mechanism, the Joint Cetacean Protocol, is being developed that can bring these disparate datasets together at the NW European Atlantic scale (JCP, Paxton et al, 2011, see http://jncc.defra.gov.uk/page-5657). Effort-related cetacean sightings data from all major data sources are included e.g. SCANS I & II, CODA, European Seabirds at Sea (ESAS), SeaWatch Foundation (SWF) and other non-governmental organisations, as well as industry (e.g. in relation to potential renewable energy installations in UK waters). These data, collected between 1979 and 2010, represent the largest NW European cetacean sightings resource ever collated. It is recognised, however, that there are some significant datasets missing such as the annual national monitoring undertaken by some States. It is expected that the JCP will deliver information on the distribution, relative abundance and population trends of the more regularly occurring cetacean species occurring in NW European waters. A preliminary phase of the project, covering the Irish Sea and west coast of Scotland, was recently been completed (Paxton et al., 2011). This work was used to refine the modelling techniques that had been developed in earlier projects (Thomas, 2009; Paxton & Thomas, 2010; Paxton et al., 2011). A final analysis of north-west European waters will be published in 2013.

8 Information on defining such boundaries has been collected by among others ICES WGMME, ASCOBANS, OSPAR and HELCOM. ASCOBANS (2009) held a workshop of specialists to focus upon defining Management Units for the regular small cetacean species. ICES WGMME (2012) has also made an overview of, and advised on, appropriate boundaries for harbour porpoise, common dolphin, bottlenose dolphin (including inshore and offshore populations), white-beaked dolphin, white-sided dolphin and minke whale.

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2) An agreement on definitions for Management regions, population distribution, and/or stock structure for each relevant species against which to assess trends in abundance.

3) The development of a baseline for the Management region, population or stock of each species.

4) The development of a standardized monitoring methodology, or alternatively a mechanism for standardizing data post collection. Although progress has been made, both effort-related monitoring of cetaceans and analytical procedures need further refinement and standardisation.

5) The development of an assessment tool.

Literature

Evans P.G.H. & Teilmann, J., 2009. ASCOBANS/HELCOM Small Cetacean Population Structure Workshop. ASCOBANS, Bonn, Germany, 141 pp.

ICES, 2009. Report of the Working Group on Marine Mammal Ecology (WGMME), February 2–6 2009, Vigo, Spain. ICES CM 2009/ACOM:21. 129 pp.

ICES, 2012. Report of the Working Group on Marine Mammal Ecology (WGMME), March, 2012.

Paxton, C. & Thomas, L., 2010. Phase One Data Analysis of Joint Cetacean Protocol Data. Available at: http://jncc.defra.gov.uk/pdf/JCP_Phase_1_Analysis.pdf

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Draft OSPAR Common Indicators: marine mammals (M-5)

Harbour seal and Grey seal pup production

1. Indicator

“Fecundity rate of harbour seal and grey seal (pup production)”.

2. Reasoning for the development of this indicator

Marine mammals, including harbour and grey seals, are top predators, and comprise an important part of biodiversity (Descriptor 1). As harbour and grey seal are taken up under the Habitats Directive (annex II), their population condition comprises a key aspect for securing and achieving GES according to the MSFD.

Grey seals form breeding aggregations at traditional, remote colonies, with females often returning to the same location on the breeding colony to give birth to their single pups. In addition, some females exhibit philopatry, i.e. returning to breed at their natal site. It is for these reasons that grey seal population estimates are based on pup counts. In contrast, harbour seals do not aggregate into discrete colonies to breed. The females appear to move away from larger groups to give birth and raise their new-born pups in very small groups, returning to form larger groups when the pup is sufficiently old. The dispersed nature of the breeding groups and the fact that pups are able to swim within hours of birth contrive to make estimating pup production of harbour seals extremely difficult in some areas. It is for this reason that population estimates for harbour seals are undertaken during their annual moult when groups tend to be larger than at other times of the year and numbers at many haul-out sites appear to be at a maximum. However, in some areas(the Wadden Sea and limited rocky shore areas such as the Kalmarsund in Sweden), counts are made during the breeding season for harbour seals.

Number of CPs reporting/using the indicator (n=9) : 7 Consensus among CPs on usefulness as part of a region wide set (n=8): 7 3. Parameter/metric

“Harbour seal and grey seal pup production in each Management Unit” (number of pups per colony vs. the size of the colony, integrated over the Management Unit; MU).

4. Baseline and reference level

Although the baseline should derive from historical data, these are not available everywhere. Moreover, the historical distributional range of breeding sites and colonies is a situation that cannot realistically be restored, given for instance coastal developments and tourism, and climatic changes may have important consequences. It is therefore likely that a modern baseline will have to be utilized, such as average pup production in the last decade per MU.

5. Target setting

The target is “No statistically significant long-term average decline of ≥10% at each Management Unit”.

While an existing OSPAR EcoQO deals with grey seal pup production, there is not an equivalent to harbour seal pup production.

6. Spatial scope

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The North Sea has been subdivided into different MUs (respectively nine and eleven for grey and harbour seal). A subdivision into MUs should be made for the entire range of both species.

7. Monitoring requirements

The monitoring required takes place in combination with the monitoring for the indicators M-1 (distributional range and pattern) and M-3 (abundance). There is sufficient monitoring at breeding colonies for grey seals. In contrast, for harbour seals it will not be possible to cover all MUs, as it is much more difficult to count harbour seal pups. Harbour seal counts are undertaken during the breeding season in the Wadden Sea, but in the UK pup production for harbour seals has only been monitored at two colonies (Moray Firth and Wash Estuary). In the Wadden Sea, the monitoring and management under the Trilateral Monitoring and Assessment Programme and Wadden Sea Plan (Trilateral Seal Agreement; CMS) are well established since a few decades, and support the indicators and targets for harbour seals, and (although not under CMS) also the ones for grey seals.

8. Appropriateness of the indicator

There is usually no straightforward link between a human activity and pup production. There are multiple pressures, such as disturbance, coastal engineering works and pollution. However, changes and trends are important to detect cause-effect relationships between pup production and a certain human activity, where necessary to be followed by appropriate measures.

9. Reporting

Given that some Management Units are transboundary, and that shifts may occur between adjacent colonies, agreements have to be made on the appropriate time scale of monitoring and reporting in order to be able to make an assessment.

10. Costs

As the monitoring is coastal in nature, costs are limited; the monitoring can be combined with the monitoring for the indicators M-1 (distributional range and pattern) and M-3 (abundance).

11. Further work

Future steps are similar for the indicators M-1 (distributional range and pattern) and M-3 (abundance).

1) Compilation of existing data on pup counts and production estimates.

2) Subdivision of the area (beyond the North Sea) into MUs (already exists for the UK, with further refining needed in e.g. the Irish Sea). Assessment in all MUs will not be possible for harbour seal.

3) Development of a baseline for each MU (where possible).

4) Development of a standardized monitoring methodology, or alternatively, a mechanism for standardizing data post collection.

5) Agreement on time scale for monitoring and development of an assessment tool.

Literature

OSPAR, 2009. Evaluation of the OSPAR system of Ecological Quality Objectives for the North Sea (update 2010). OSPAR Biodiversity Series, 406.

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Draft OSPAR Common Indicators: marine mammals (M-6)

Mortality rate of seals and cetaceans due to bycatch

1. Indicator

The indicator is “mortality rate due to bycatch”.

2. Reasoning for the development of this indicator

Marine mammals are usually slowly reproducing, and a high human-induced mortality, on top of natural mortality, can have serious and long-term implications for the population. An important source of human induced mortality that can be singled out is bycatch in fishing gear. While the number of animals bycaught is clearly pressure related, there is a link with a state of the population (population size - indicators 35 and 36).

For cetaceans, the Habitats Directive requires that incidental capture or killing is monitored, and that it should not have a significant negative impact on the species. Therefore the setting of limits for bycatch of cetaceans can be considered as a key aspect in achieving GES according to the MSFD. It has been agreed that bycatch targets can also be set for pinnipeds, as bycatch also occurs in these marine mammals. As the maximum population growth rates differ in marine mammals, different targets will be needed. Given the high mobility of marine mammals, and the distributional range of populations, assessments will necessarily need to be made on a wide scale (population range or management regions). Difficulties exist in both measuring bycatch and population size in a sufficiently high degree of accuracy to draw conclusions, and in combining data originating from different regions for an overall assessment of GES.

Number of CPs reporting/using the indicator (n=9) : 7 Consensus among CPs on usefulness as part of a region wide set (n=8): 7 3. Parameter/metric

“Numbers of individuals being bycaught in relation to population estimates”, set for each population range or Management Unit (MU).

4. Baseline and reference level

Although some historical bycatch estimates exist, the current levels of bycatch vs. the population estimates (baseline), and a trend-based target can be used.

5. Target setting

The target “The annual bycatch rate of [marine mammal species] is reduced to below levels that are expected to allow conservation objectives to be met” may require different approaches for different species. Obvious species for which the target could/should be set, as bycatch exists, are harbour seal, grey seal, harbour porpoise, short beaked common dolphin, bottlenose dolphin and striped dolphin. There are regional differences in the species to be selected. One target accepted for harbour porpoises (existing OSPAR EcoQO) is less than 1.7% of the best population estimate. For other species, such as the common dolphin, the population against which the target should be set is not straightforward. For seals it may be set against a measure of the regional population size, as there is a fairly good knowledge of the number of seals at haul- out sites and breeding colonies. Good information might also be available for coastal bottlenose dolphins.

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However, there has been much debate about the use of a simple fraction of the best population estimate. The harbour porpoise bycatch limit reference point of 1.7% is derived from work undertaken by a working group convened by the International Whaling Commission and ASCOBANS (IWC, 2000). A very simple deterministic population dynamics model was used, which assumed a “biological” population with independent population dynamics. If this management target is to be applied to management regions for harbour porpoise, the animals living in the areas defined by these regions are assumed to have more or less independent dynamics (which is clearly not the case in the European North Atlantic). Where the population dynamics are not independent, the management targets calculated on the basis of biological populations are unlikely to be appropriate. An alternative to such an approach is the bycatch management procedures developed under the SCANS-II and CODA projects (Winship, 2009).

An alternative for the parameter (bycatch rate vs the population size) is the use of the current bycatch rate (in numbers of animals) as the baseline and aim for it to be reduced in future years. This would mean that no information is required on the population size, but have the disadvantage that there is no link with the population state.

6. Spatial scope

Management Units (MUs) for cetacean species, also to be used in indicator M-4 (abundance) assessments, have been defined by ASCOBANS (Evans & Teilmann, 2009) and further refined by ICES (2012). For the purpose of the assessment of bycatch percentages, MUs should be refined with ICES (fishery) rectangles, in order to produce more accurate bycatch estimates and relate it to the scale of the human activities concerned.

7. Monitoring requirements

The 1.7% limit for the harbour porpoise is widely accepted, but may be too high to meet ASCOBANS conservation objectives. The OSPAR EcoQO for harbour porpoise in the North Sea has a similar target and there is a requirement for monitoring bycatch of cetaceans in fisheries legislation (e.g. Regulation 812/2004; Data Collection Regulation) and Article 12 of the Habitats Directive. Monitoring of marine mammal population size is diverse, with parts of some populations being regularly monitored on a regional scale (e.g. seals at colonies) and with other populations only monitored in approximately decadal large scale surveys (e.g. SCANS surveys for harbour porpoises and common dolphins), yielding population estimates for one season only.

In 2008, the International Council for the Exploration of the Sea (ICES) Working Group on Marine Mammal Ecology tried to evaluate progress to date with the harbour porpoise bycatch EcoQO on a North Sea wide basis (ICES, 2008b). It was quickly apparent that many of the fisheries suspected to have the highest bycatch levels are conducted without bycatch observer programmes as these are not a requirement of Regulation 812/2004. Subsequently, ICES Working Group on Bycatch of Protected Species has tried to evaluate the impact of fisheries bycatch annually.

Extrapolated estimates of total bycatch in EU waters in 2009 (based on EC/812/2004 national reports) were available for striped dolphins (about 870), for common dolphins (around 1500), for bottlenose dolphins (10) and for harbour porpoises (about 1100) (ICES 2011). It is clear that these totals provide only a very patchy overview of total cetacean by-catches within European waters due to low and uneven sampling coverage (ICES, 2011). Reductions in bycatch should be considered as a target that will contribute to GES, but it is currently not possible to evaluate whether the indicator will provide an accurate assessment of GES. However, data collation techniques are continually improving and coverage of the relevant fisheries sectors has been increasing.

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Problems in monitoring are the scale of assessment (marine mammal population distributions are wider than national waters), monitoring of bycatch is undertaken using different methodologies and to different standards, and, in some Member States, bycatch can occur in the recreational or part-time fishery sector, which is considerably harder to monitor.

A source of information, currently underexploited, are strandings. These not only provide demographic data for cetacean populations, but can also be used to detect changes in the causes of death within some degree of confidence, certainly with species for which sufficient numbers wash ashore. Although absolute estimates should be treated with caution, trends are likely to be informative, and a good coverage and a standardised methodology is needed.

8. Appropriateness of the indicator

Bycatch is considered as one of the major anthropogenic threats to marine mammals. It is easy to understand and quantify (although the methods for quantification are not straightforward), and there is a clear link with human activities (different fishing metiers). The target set should indicate the level at which, in the absence of other important human-induced threats, conservation objectives will be met.

9. Reporting

The proposed target means that knowledge is required both on bycatch and on the population size, both spatially and temporally, and within appropriate confidence values. This poses problems, as has been demonstrated by ICES (2010). With the available data on bycatch of harbour porpoises it was not possible to conclude whether or not more than 1.7% of the population had been bycaught during the most recent years. Estimates of bycatch were made on the basis of the number of fishing days per fisherman, the landings in relevant fisheries, and on board observer schemes. Currently, observer schemes are not required in all relevant fisheries according to the fisheries legislation. There is an obligation under the Habitats Directive to monitor bycatch, but it has to date not been enforced by the European Commission, and obligations exist under the CFP.

10. Costs

Both monitoring marine mammal abundance (indicators 35 and 36) and bycatch rates can be expensive, especially where a high coverage of fisheries through independent observers on board is required. Cheaper methods exist, such as the use of camera systems on board, or a voluntary reporting scheme by fishermen.

11. Further work

There is clearly a lack of information on aspects of this indicator, although information is slowly improving. Concerning the population sizes of the marine mammals, and the assessment scale, the lack of information and proposed future steps are described in the summaries of the indicators M-3 and M-4 (Abundance). Concerning bycatch, the following aspects should be further developed through linkages with appropriate fora:

1) Discussion about the use of a simple fraction of the best population estimate, or alternatively the bycatch management procedure developed under SCANS-II and CODA. Conservation objectives still need to be specified and agreed.

2) Define MU/region against which to set the target for all species, or refinement of the MU, aligning them with ICES rectangles.

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3) Once the mechanism for determining the bycatch level has been agreed, develop target levels for relevant species.

4) Development of a baseline for each population or Management Unit.

5) Development of a standardized monitoring methodology for bycatch or alternatively a mechanism for standardizing data post collection. This is currently being progressed through WGBYC.

6) Investigation of the use of stranded animals to derive information on trends in causes of mortality.

7) Development of an assessment tool. This is currently being progressed through WGBYC.

Literature

CODA, 2009. Cetacean Offshore Distribution and Abundance in the European Atlantic. Report available from http://biology.st-andrews.ac.uk/coda/.

Evans, P.G.H. & Teilmann, J., 2009. ASCOBANS/HELCOM Small Cetacean Population Structure Workshop. ASCOBANS, Bonn, Germany, 141 pp.

ICES, 2008. Report of the Working Group on Marine Mammal Ecology (WGMME), February 25-29 2008, St. Andrews, UK. ICES CM 2008/ACOM: 44. 83 pp.

ICES, 2010. ICES Advice on the EC request on cetacean bycatch Regulation 812/2004, Item 3. ICES Special Request Advice, Copenhagen, October 2010.

ICES, 2011. Report of the Working Group for Bycatch of Protected Species (WGBYC), February 1-4 2011, Copenhagen Denmark. ICES CM 2011/ACOM:26. 75 pp.

ICES, 2012. Report of the Working Group on Marine Mammal Ecology (WGMME), March, 2012.

IWC, 2000. Report of the IWC-ASCOBANS Working Group on harbour porpoises. Journal of Cetacean Research & Management 2 (supplement): 297-305. IWC (2004). Report of the Scientific Committee. Journal of Cetacean Research & Management (supplement) 6: pp12-13; 88-89; 171-183.

SCANS-II, 2008. Small Cetaceans in the European Atlantic and North Sea. Final report to the European Commission LIFE Nature programme on project LIFE04NAT/GB/000245. Report available from http://biology.st-andrews.ac.uk/scans2/

Winship, A.J., 2009. Estimating the impact of bycatch and calculating bycatch limits to achieve conservation objectives as applied to harbour porpoise in the North Sea. PhD thesis, University of St Andrews, UK. Available from: http://research-repository.st-andrews.ac.uk/handle/10023/715.

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Marine Birds

Code Previous Indicator Category code* B-1 25 Species-specific trends in relative abundance of non-breeding and breeding marine bird Core species B-2 26 Annual breeding success of kittiwake Core

B-3 27 Breeding success/failure of marine birds Core

B-4 29 Non-native/invasive mammal presence on island seabird colonies Core

B-5 28 Mortality of marine birds from fishing (bycatch) and aquaculture Candidate

B-6 24 Distributional pattern of breeding and non-breeding marine birds Core

Species-specific trends in relative abundance of non-breeding and breeding marine birds

1. Indicator

Name: Species-specific trends in relative abundance of non-breeding and breeding marine birds

Code: B-1 (25)

Proposed to BDC 2013 as: Core

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components attributed (species/habitat types) Yes

Applicability to sub-regions Yes

Assessment scales Yes

Monitoring parameter Yes

Monitoring frequency Yes

2. Appropriateness of the indicator

Biodiversity component: Marine Birds

MSFD criterion: 1.2 Population Size

MSFD indicator: 1.2.1 Population abundance

Number of CPs Consensus among Relevance to reporting/using CPs on usefulness Sensitivity to management Applicable the indicator as part of a region specific pressures measures Practicable across region (n=9) wide set (n=8)

Low Low Target & indicator adopted Yes 8 8

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Non-specific – as an EcoQO on seabird indicator of state that population trends can be responds to multiple applied to other species. pressures At sea monitoring increase needed.

This indicator is constructed from information on marine bird species, which at some point in their annual lifecycle, are reliant on coastal and offshore areas under the jurisdiction of MSFD. These areas compose non-estuarine shores below HAT, including coastal lagoons and saltmarsh; inshore non-transitional waters and offshore waters.

In this context, ‘marine birds’ include the following taxonomic groups that are commonly aggregated as ‘waterbirds’ and ‘seabirds’:

Waterbirds: shorebirds (order Charadriiformes); ducks, geese and swans (Anseriformes); divers (Gaviiformes); and grebes (Podicipediformes);

Seabirds: petrels and shearwaters (Procellariiformes); gannets and cormorants (Pelecaniformes); skuas, gulls, terns and auks (Charadriiformes).

Shorebirds, some duck species and some gulls feed on benthic invertebrates in soft inter-tidal sediments and on rocky shores. Geese mostly graze on exposed eelgrass beds (i.e. Zostera spp.). Diving duck species feed on invertebrate benthos in shallow inshore waters. All other marine birds, including some gulls, spend the majority of their lives at sea, feeding on prey living within the water column (i.e. plankton, fish and squid) or picking detritus from the surface. Divers, piscivorous ducks, grebes, cormorants, gulls and terns tend to be confined to inshore waters; whereas petrels, shearwaters, gannets, skuas and auks venture much further offshore and beyond the shelf-break.

The indicator and its target are derived from the OSPAR EcoQO on Seabird population trends as an index of seabird community health. The EcoQO on seabird population trends was adopted by OSPAR’s Biodiversity Committee (BDC) in 2012 (see OSPAR 2012). When adopting the EcoQO on seabird population trends, the OSPAR BDC agreed that it, along with the other EcoQOs, should be taken forward as part of the implementation of the EC Marine Strategy Framework Directive (MSFD) (OSPAR 2012). Subsequently, OSPAR’s ICG-COBAM identified the EcoQO as an appropriate target for assessing the achievement of Good Environmental Status (GES) under MSFD.

The indicators for the EcoQO were intra-specific trends in abundance. Abundance is used as an indicator of seabird community health because:

• Abundance is measured widely and relatively easily

• a good indicator of long-term changes in seabird community structure

• likely to change slowly under ‘natural’ conditions, so rapid changes in their numbers might indicate human-induced impacts, thereby providing a cue for immediate management actions

The EcoQO has so far been applied only to trends in breeding numbers of colonial-breeding seabird species. In the context of MSFD, abundance indicators could be constructed from time-series data of other groups of marine birds and from data collected at sea.

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3. Parameter/metric

This indicator is generated using time-series of annual estimates of abundance of individual species. The indicator metric is relative abundance: Annual abundance as a percentage of the baseline.

Species –specific indicators have so far been generated for

a) 13 species of breeding seabird in the Celtic Seas (ICES 2010, 2011),

b) 16 species of breeding seabird in the Greater North Sea (ICES 2011),

c) seven species of non-breeding shorebirds (i.e. in non-estuarine intertidal areas outside the breeding season) in each of the UK parts of the Celtic Seas and Greater North Sea (Humphreys et al. 2012).

The breeding seabird indicator could be constructed for other sub-regions. ICES (2008) noted that there were sufficient data from colonies in the Azores to construct an indicator, but further data collation was required in the Bay of Biscay.

The non-breeding shorebird indicator, so far developed only for the UK, could easily be applied to other countries and should be expanded to other seasons. For instance, the Wadden Sea is of minor importance for wintering shorebirds, but of eminent importance for spring staging and moult. Separate indicators may be required for wintering, staging and moulting birds using inter-tidal areas. Furthermore, such an indicator would benefit from the inclusion of other waterbirds that use inter-tidal areas (e.g. Brent Goose, Wigeon, Pintail) – which could also be inserted into an additional indicator.

Humphreys et al. (2012), constructed an indicator of coastal-breeding waterbirds in the UK (i.e. species of waterbird (incl. Shorebirds) breeding close to the shoreline and dependant on intertidal and inshore areas for feeding), but data proved sufficient to include just one species – Oystercatcher (Ostralegus haematopus). The inclusion of data from other countries could expand the indicator to more species, e.g. Avocet, Ringed Plover, Kentish Plover, Redshank and Common eider.

Indicators could be generated for non-breeding ducks, divers and grebes (i.e. in inshore waters outside the breeding season) and seabirds at sea (i.e. seabird species in inshore and offshore waters throughout the year). Considerable development of such indicators is required. Similar work is being undertaken by HELCOM and a preliminary trend analysis has been conducted on time-series data from German waters (Garthe, unpubl.). Such indicators may give an early warning of declines in some breeding populations.

4. Baseline and Reference level

The baseline for each species, should be set at a population size that is considered desirable for each individual species within each geographical area. Baselines should be set as follows:

a) At a point in the past when, based on expert judgement, anthropogenic impacts are likely to have been relatively minimal compared to the rest of the time-series; the baseline needs to reflect prevailing climatic conditions. It may prove difficult to set a baseline that meets both critera.

b) The mean value of the time series. This method carries the risk of a shifting baseline e.g. if a population is in long-term decline, the baseline will also decline as time goes on - so much so that target may eventually be met, without the population recovering.

c) Where no previous data are available: set baseline at the start of the new time-series and amend in due course - see (a) and (b).

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It is preferable to set baselines objectively (i.e. (a) or (b)) than arbitrarily (i.e. (c)). Option (a) potentially provides the most objective baseline, but the limited length of the time-series available may mean some assumptions are made in setting them. A set of criteria for setting baselines in the past would help to steer and standardise expert judgement.

5. Target setting

The criterion level target for Population Size (1.2) should be identical to the EcoQO on seabird population trends: ‘Changes in abundance of marine birds should be within individual target levels in 75% of species monitored’.

Humphreys et al (2012) recommended a target threshold of 75% for non-breeding shorebirds and coastal breeding waterbirds in the UK because it is comparable to the thresholds used for shorebirds by the WeBS Alerts system (http://www.bto.org/volunteer-surveys/webs/publications/webs-alerts).

The supporting targets attached to each species-specific indicator of trends in relative abundance are set on the magnitude of change relative to baselines: species-specific annual breeding abundance should be more than 80% of the baseline for species that lay one egg, or more than 70% of the baseline for species that lay more than one egg (ICES 2008, 2010, 2011).

These different lower thresholds were set according to the resilience of populations to decline. These species-target thresholds could be changed or set individually for each of the species-specific trends.

An upper target threshold has previously been applied to indicators of the EcoQO on seabird population trends (ICES 2008, 2010, 2011), so that annual abundance should not be greater than 130% of the baseline. This upper threshold was used to flag-up potentially disruptive increases in some species that might impact on other species. However, this may mean that the EcoQO or GES is not achieved if some species recover to levels in excess of the baseline, without having a detrimental impact on other species. It appears that GES is not clearly indicated by the upper threshold, but it could provide a useful trigger for action (research and/or management).

When reporting on the annual results of the species-specific indicators, species that have exceeded 130% of the baseline, should be highlighted as shown in Table 1.

6. Spatial scope

The EcoQO on Seabird population trends was adopted in 2012 (OSPAR 2012). The indicator for the EcoQO has so far been constructed from trends in the numbers of seabirds at breeding colonies within the Celtic Seas (ICES 2008, 2010, 2011) and the Greater North Sea (ICES 2011). Further work is required to collate breeding seabird data in the Bay of Biscay and to construct the indicator for there and also for Macaronesia.

The Waddensea should not be considered as ‘transitional waters’ and its populations of marine birds should be included in the assessment for MSFD because of its ecological connections with the Greater North Sea sub-region. The Waddensea could be assessed as a sub-division of the Greater North Sea.

For indicators of non-breeding bird abundance (e.g. during winter, staging or moulting), the scale of assessment needs to be larger than the sub-region i.e. region or flyway. For some species there may need to a combined assessment across regional borders e.g. between North Sea and Baltic. More work is needed to define the appropriate assessment scale for each species. This work should benefit from the increasing amount of evidence on bird migration routes, obtained from tagging studies.

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7. Monitoring requirements

The frequency at which data should be collected, annually

For colonies and other breeding sites: Walsh et. al. (1995); Koffijberg et. al. (2011) - for Wadden Sea.

For at-sea aerial and boat-based line transect surveys (Camphuysen et al. 2004 )

Who is responsible for the monitoring, National Monitoring Schemes

Minimal required amount of monitoring locations. Depends on species and the inherent variability in trends between locations, and the magnitude of change that needs to be detected with statistical confidence.

Does the required monitoring already exist? Most countries in the region conduct annual monitoring of abundance of marine birds at breeding sites and of shorebirds in intertidal areas. Monitoring in some countries may need to be expanded to construct a robust indicator.

Monitoring of marine bird abundance at sea is currently confined to certain parts of the Greater North Sea. The UK is currently scoping a monitoring scheme for inshore and offshore waters

8. Reporting

The indicator should be updated as frequently as possible - annually is preferable. The assessments of the indicator against its target should be conducted and reported annually also. This will enable management measures to be instigated to restore GES before the state of indicator declines too much, which may save considerable resources. Annual reports would also enable the effectiveness of the management measures to be frequently assessed and adjusted if required.

Data collected by CPs, need to be collated centrally (probably at a sub-regional scale), pooled and then analysed to produce annual species specific indices of relative abundance. The assessment can then be conducted and based on the resultant sub-regional trends. ICES WGSE can be used to provide an expert review of the assessment and make recommendations for management and provide any amendments to the analytical and assessment process.

Issues that need to be resolved to build s sub-regional collation and reporting process:

i. Need to nominate data custodians and analysts – could be one CP per sub-region. Different CPs could be nominated for different indicators.

ii. Need to draft agreements on data sharing and address any issues around data ownership.

iii. Need to agree on a format for data submission.

iv. Need to resolve how and where data will be stored.

Figure 1 shows how the trends and target assessment for individual species indicators can be presented. Figure 2 provides an example of a sub-regional assessment of the criterion target for population size. Table 1 shows how the species specific assessments in the different sub-regions can be presented side by side and visually interpreted via a traffic light system.

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9. Resources needed

Most countries in the region conduct annual monitoring of abundance of marine birds on land i.e. counts of birds or pairs at breeding sites and counts of shorebirds in intertidal areas or when roosting above high water. Monitoring of non-breeding shorebirds in the Greater North Sea and Celtic Seas is concentrated in transitional waters, so additional monitoring of non-estuarine coasts may be required to construct the indicator for these species. Monitoring of breeding abundance of marine birds is conducted in all countries in the region and as part of nationally co-ordinated schemes with central data storage mechanisms (e.g. national databases), in all countries except Portugal and Sweden (North Sea coastline). Most countries monitor a sample of their colonies, with some but not all counted annually. Periodically, all colonies may be surveyed as part of a census. The intensity of monitoring (i.e. number of colonies and frequency) varies depending on species. Further work is required to determine if sufficient data are collected by each country to construct indicators for relevant species in each sub-region. Monitoring in some countries may need to be expanded to construct a robust indicator.

Monitoring breeding abundance is more straightforward in some species than others, so species-specific methods have been designed and are widely used (see e.g. Walsh et al. 1995). Generally, monitoring is conducted by the number of nests, pairs or individuals within an entire colony or specially selected sub- sections or plots. This requires one or two observers visiting a colony several times during the breeding season (i.e. usually May-Aug, but varies with species). Resources required for these visits are dependent on how remote the colony is i.e. colonies on uninhabited remote offshore islands are more expensive to monitor than colonies on mainland coasts. Monitoring costs in most countries are minimised by using volunteer observers, but professional observers are sometimes used to monitor some colonies – usually those on remote offshore islands. Hence, monitoring costs will vary between countries depending on the number of colonies to be monitored, the accessibility of these colonies and on how much of the monitoring can be done by volunteers. During colony visits, data on breeding success for common indicator B-3 (Breeding success/failure of marine bird species) can be collected. Monitoring costs for both indicators are not necessarily additive.

Monitoring of marine bird abundance at sea is currently confined to certain parts of the Greater North Sea i.e. the waters of DE, BE, DK, NL, SE, (FR?) and NO. The UK is currently scoping a monitoring scheme for inshore and offshore waters. Numbers of birds at sea are either counted from ships or from the fixed-winged aircraft. Surveys need to be conducted by professional observers, rather than volunteers. Costs for ship- time and flight-time can be reduced by sharing the platform with other marine biological surveys (e.g. benthic surveys or cetacean surveys). There is potentially scope for neighbouring countries to share survey platforms.

Both aerial and ship-based surveys count numbers of birds in a sample of the survey area i.e. along transects. There are European-wide standards for collecting these data (Camphuysen et al. 2004). These data are used to construct maps of bird density across the survey area. An area may need to be repeatedly surveyed in a single year to capture seasonal variation in bird abundance. These bird density maps can be used for some species to construct the common indicator B-6 (Distributional pattern of breeding and non- breeding marine birds) Monitoring costs for both indicators are not necessarily additive.

For all indicators of marine bird abundance, a centrally funded annual analysis and collation is required: There is a need to nominate data custodians and analysts. This could be one CP per sub-region or a coordinating group for an ecological unit such as the Wadden Sea. The European Seabirds at Sea Database (Reid & Camphuysen 1998) potentially provides a mechanism to collate and store data on at–sea bird abundance.

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10. Further work

i. Construct indicators for Bay of Biscay and Macaronesia derived from time-series data on numbers of seabirds at breeding colonies.

ii. Investigate the feasibility of constructing, for each sub-region, indicators of the abundance of: i. coastal-breeding waterbirds; ii. non-breeding waterbirds; iii. seabirds at sea; and iv. non-breeding shorebirds.

iii. Construct new indicators for bird groups and sub-regions where data is available. The development of indicators for marine birds at-sea in the NE Atlantic can learn from ongoing work by HELCOM and the Marmoni project that are constructing such indicators in the Baltic. Some preliminary indicators have been constructed on at-sea data from German waters in the North Sea. A larger funded project may be required.

iv. Development of baselines – objective baselines, set at time when anthropogenic impacts on the population were thought to be relatively minimal, are preferable to arbitrary baselines e.g. set at the beginning of a time series. A set of criteria is required to steer and standardise expert judgement.

v. Spatial scale – what is the most useful scale to aggregate data for assessment of each of the abundance indicators and their targets?

vi. Presentation of assessment results for breeding Marine Birds and inter-tidal non-breeding birds: How to define whether an indicator is decreasing, increasing or stable (see Table 1).

vii. Functional groups definition of inshore/offshore: these need to be reassessed as new indicators are constructed. Are the existing functional groups appropriate or are alternatives required.

viii. Co-ordinate across CPs within each sub-region, the collation of data, trend analysis, assessment against targets and reporting.

References

Camphuysen C.J., Fox A.D., Leopold M.F., & Petersen I.K., 2004. Towards standardised seabirds at sea census techniques in connection with environmental impact assessments for offshore wind farms in the U.K.: a comparison of ship and aerial sampling methods for marine birds, and their applicability to offshore wind farm assessments (PDF, 2.7 mb), NIOZ report to COWRIE (BAM – 02-2002), Texel, 37pp.

Humphreys E M, Risely K, Austin G E, Johnston A & Burton N H K 2012. Development of MSFD Indicators, Baselines and Targets for Population Size and Distribution of Marine Birds in the UK. BTO Research Report No. 626

ICES. 2008. Report of the Workshop on Seabird Ecological Quality Indicator, 8–9 March 2008, Lisbon, Portugal. ICES CM 2008/LRC:06. 60 pp.

ICES. 2010. Report of the Working Group on Seabird Ecology (WGSE). 15–19 March 2010, Copenhagen. ICES CM 2010/SSGEF:10. 81 pp.

ICES. 2011. Report of the Working Group on Seabird Ecology (WGSE). 1–4 November 2011, Madeira, Portugal. ICES CM 2011/SSGEF:07. 77 pp.

OSPAR Commission 2012. Summary Record of the Meeting of the Biodiversity Committee (BDC) in Brest: 13-17 February 2012. OSPAR Convention for the Protection of the Marine Environment of the North-East Atlantic, BDC 12/8/1-E.

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Reid JB & Camphuysen C.J. 1998. The European Seabirds at Sea database. Biol. Cons. Fauna 102: 291.

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Annual breeding success of kittiwake

1. Indicator

Name: Annual breeding success of kittiwake

Code: B-2 (26)

Proposed to BDC 2013 as: Core

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components attributed (species/habitat types) Yes

Applicability to sub-regions Yes

Assessment scales Yes

Monitoring parameter Yes

Monitoring frequency Yes

2. Appropriateness of the indicator

Biodiversity component: Marine Birds

MSFD criterion: 1.3 Population Condition

MSFD indicator: Population demographic characteristics (1.3.1)

Number of CPs Consensus among Sensitivity to reporting/using CPs on usefulness specific Relevance to Applicable the indicator as part of a region pressures management measures Practicable across region (n=9) wide set (n=8)

High - High Data on kittiwake Yes in those 5 5 Sensitive to breeding success sub-regions Depends on cause of (high where the changes in widely available. where changes to prey availability kittiwake occurs) prey Existing long term kittiwake (if fishing -high; if climate- availability. monitoring through breed low). most of range.

This indicator is constructed from data on annual mean breeding success (no. chicks fledged per pair) at colonies of black-legged kittiwake (Rissa tridactyla) throughout most of its range within the Celtic Seas and Greater North Sea. The indicator uses data on black-legged kittiwake because, it is sensitive to changes in food availability (Furness & Tasker 2000) and because there is good evidence in the Greater North Sea that they are negatively affected by fishing (Frederiksen et al. 2004, 2007, 2008).

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An indicator and target on kittiwake breeding success has previously been proposed for the draft EcoQO on Local sandeel availability to Black-legged kittiwakes. The EcoQO has not been adopted because it failed to distinguish between changes in sandeel availability that were an impact of fishing from those that resulted from variation in prevailing climatic conditions.

The new indicator, proposed here, uses the regression of past measures of annual breeding success and local mean sea-surface temperature in late winter of the previous (SST-1), to predict what annual breeding success should be if it is ‘in line with prevailing...climatic conditions’ (see Fig 1). The premise of the indicator is that any statistically significant negative deviation may indicate a detrimental anthropogenic impact, other than any climate change impacts.

The indicator is based on previous work by Frederiksen et al. (2004, 2007), which found kittiwake breeding success at seven colonies along the North Sea coast of the UK to be significantly negatively correlated with local mean sea-surface temperature two winters previously (SST-1). The relationship is thought to be related to larval sandeel survival and the subsequent availability of 1 year-class (1-group) sandeels for kittiwakes to rear their chicks on. In an area of eastern Britain, adjacent to the seven colonies above, where sandeel fishing occurred during 1991-98 and has been banned since 2000, there was a significant negative effect of the presence of fishing, as shown by the red line in Fig. 1.

Figure 1: Stylised version of the relationship between kittiwake breeding success and SST two winters previously (from Frederiksen et al. 2004, 2007). The diagram also demonstrates how targets may be set.

In developing this indicator for the UK, Cook et al. (2012) found there to be a statistically significant negative relationship between annual breeding success and SST-1 at 29 colonies in the Greater North Sea. But they failed to find a significant relationship at 10 colonies in the Celtic Seas. Lauria et al. (2012) also found no long-term (1986-2007) effects of spring SST-1 on kittiwake breeding success in the Celtic Sea. The relationship between breeding success and SST will vary across the distributional range in relation to the spatial variation in the main prey of breeding kittiwakes. Thus, the SST time lag giving the best relationship is likely to reflect the time lapse between the key period of survival of 0-group fish (e.g. late winter/early spring in sandeels and herring) and the time at which the fish (most often 0- or 1-group) is later used as chick food by the kittiwakes.

Caution needs to be given when interpreting the cause of low annual breeding success compared to what the relationship with SST would predict. While in some UK North Sea colonies there is good evidence for an impact of fishing, poor success at colonies in Shetland and in Norway has resulted increased pressure from natural predators (i.e. Great skua and white-tailed sea-eagle respectively).

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Further analysis of data from throughout the Kittiwakes breeding range in the Region is required to determine full applicability of this indicator across its range. There should be scope for a dynamic regional adjustment in indicator and target design.

3. Parameter/metric

Annual mean breeding success (no. offspring per pair ) of kittiwake at sampled colonies.

The indicator is constructed from a time-series of annual estimates of breeding success at a sample of colonies. Not all the colonies in the sample will have been observed every year in the times-series. Missing annual observations can be predicted by models. These models are more accurate if they take into account spatial variation in temporal trends in breeding success. Dabam et al (2012) produced separate models for UK colonies in the Celtic Seas, the Northern Isles and the Greater North Sea (except the Northern Isles).They constructed indicators from Kittiwake breeding success data collected in the UK by the Seabird Monitoring Programme (SMP) for the period 1986 – 2010 at 29 colonies in the Greater North sea and at 10 colonies in the Celtic seas.

4. Baseline and Reference level

The baseline is the curve predicted by the regression of SST and annual breeding success during previous years. Baseline breeding success for UK waters was calculated by Dabam et al. (2012) using a mixed-effect General Linear Model with observed annual breeding success as the response variable and SST and colony as random effects, to take into account differences in the relationship between breeding success and SST at each colony. Dabam et al, (2012) calculated separate baselines for each sub-region: Celtic Seas and the Greater North Sea.

There are currently insufficient data from UK Celtic Sea colonies to produce a robust baseline model as described above, perhaps because the diet of kittiwakes in this area differs from that in the Greater North Sea. As an interim measure, an alternative model should be used for the Celtic Seas: a mixed-effect GLM with annual breeding success as the response variable, SST as a fixed effect and colony as random effect. The relationship between BS and SST was fitted as a single fixed slope, i.e. assuming differences in the relationship between the two variables were primarily due to sampling variability and that the same relationship underlies variation in BS at all colonies.

5. Target setting

The supporting target applied to each colony is:

Annual breeding success is not significantly different, statistically, from the level expected in the prevailing climatic conditions in five years out of six.

In order to achieve the supporting target, breeding success at a colony should be equal to or higher than the lower 95% confidence limit around the baseline relationship between BS and SST (see above), in at least five years in each six year MSFD reporting cycle. Allowing the target to be missed in one year out of six will take into account natural stochastic events that may depress breeding success (e.g. heavy rainfall).

The criterion level target applied to a sub-region or other large spatial unit, is also:

Annual breeding success is not significantly different, statistically, from the level expected in the prevailing climatic conditions (defined by local sea-surface temperature in late winter of the previous i.e. SST-1) in five years out of six.

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For GES to be achieved according to this target, supporting targets for colony-specific breeding success should be achieved in at least five years in each six year MSFD reporting cycle, at a specified percentage of colonies (see below).

Dadam et al. (2012) calculated the threshold for the proportion of colonies achieving supporting targets for breeding success each year is one, minus the expected failure rate occurring by chance. The expected failure rate was calculated separately for each sub-region, using a generalised linear model using failure/success to meet the target as the response variable, and year and site as covariates, specifying the distribution family as binomial. Dadam et al. (2012) proposed a target of ≥ 93% of UK colonies in the Greater North Sea reaching targets for kittiwake breeding success. They suggested an interim target of ≥ 96% of colonies in the Celtic Seas, but note the statistical model used to calculate colony targets for breeding success is not as robust as that for the Greater North Sea, possibly because trophic relationships with 1- group fish is less important in the Celtic Sea. Nevertheless, Lauria et al. (2012) found no effects of 0-group herring, spring NAO or spring SST in the previous year on kittiwake breeding success in the Celtic Sea during 1986-2007.

6. Spatial scope

This indicator is constructed from data on annual mean breeding success (no. chicks fledged per pair) at colonies of black-legged kittiwake (Rissa tridactyla) throughout most of its range within the Celtic Seas and Greater North Sea. Further analysis of data from throughout the Kittiwakes breeding range in the Region is required to determine full applicability of this indicator across its range. There should be scope for a dynamic regional adjustment in indicator and target design.

7. Monitoring requirements

The frequency at which data should be collected, annually

The monitoring method, Walsh et. al. 1995; EcoQO on Kittiwake Breeding Success

Who is responsible for the monitoring, National Monitoring Schemes

Number required could be provided following further analysis of Minimal required amount of monitoring locations. existing data (see Dabam et al. 2012)

Does the required monitoring already exist? There is probably sufficient monitoring for indicators in OSPAR III.

In OSPAR II monitoring is currently restricted to UK and France, but should be initiated in DK, DE (Helgoland) and Norway.

Good data also exists for OSPAR I, but the most relevant countries here (Norway, Iceland and Russia) have not yet adopted the MSFD.

8. Reporting

The targets for this indicator could be assessed annually. Data needs to be collated centrally from CPs (at least at a sub-regional scale) and then analysed to produce indices, which can then be assessed against targets.

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Dadam et al. (2012) suggested a way of presenting the results of each annual assessment – see Fig. 2.

9. Resources needed

Development of this indicator outside the UK may be possible because monitoring of breeding success occurs throughout most of the kittiwakes breeding range. The robustness of the indicators produced from available monitoring data will depend on the completeness of time-series at each colony. Dadam et al (2012) used power analysis to determine the number of colonies and number of annual observations required to create robust indicators from data collected in UK waters. This information can be used to inform where additional survey effort may need to be targeted in the future.

There is probably sufficient monitoring for indicators in OSPAR III. In OSPAR II monitoring is currently restricted to UK and France, but should be initiated in Denmark, Germany (Helgoland) and Norway. Good data also exists for OSPAR I, but the most relevant countries here (Norway, Iceland and Russia) have not yet adopted the MSFD.

Monitoring breeding success of kittiwakes is straightforward because unlike some colonial seabird species, kittiwake build a substantial nest, in which the young remain until they fledge. Monitoring methods are well established in the region where the kittiwake breeding success is monitored (see e.g. Walsh et al. 1995). Monitoring is conducted by observing a sample of nests within a colony and recording progress from laying, hatching and fledging. This requires one or two observers visiting a colony several times during the breeding season (i.e. usually May-July). Resources required for these visits are dependent on how remote the colony is i.e. colonies on uninhabited remote offshore islands are more expensive to monitor than colonies on mainland coasts. Monitoring costs in most countries are minimised by using volunteer observers, but professional observers are sometimes used to monitor some colonies – usually those on remote offshore islands. Hence, monitoring costs will vary between countries depending on the number of colonies to be monitored, the accessibility of these colonies and on how much of the monitoring can be done by volunteers.

A centrally funded annual analysis and collation is required: There is a need to nominate data custodians and analysts. This could be one CP per sub-region.

10. Further work

The UK has recently completed a study which shows that in UK waters at least, the proposed indicator and target-setting approach described above can provide a robust indicator of kittiwake breeding success that takes climate effects into account and is much more likely to detect anthropogenic impacts than the proposed EcoQO on Local sandeel availability to Black-legged kittiwakes. The next step in its development is to determine if the indicator and target setting approach can be applied to data collected at kittiwake colonies elsewhere in its range in the MSFD and OSPAR areas.

a. Consider approaches to target setting recommended by Dadam et al. 2012.

b. Further analysis of UK data incorporating data from France and Republic of Ireland, by CPs to determine colony-specific baselines and targets.

c. Aggregate colony assessments to regional sea scale, adopting a more relevant ecosystem-scale divisioning than reflected by the OSPAR sub-regions.

d. Co-ordinate across CPs within each sub-region, the collation of data, trend analysis, assessment against targets and reporting.

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e. Initiate monitoring of kittiwake breeding success at colonies in Denmark, on Helgoland (Germany’s only colony) and in southern Norway.

References

Dadam D., Cook A.S.C.P. & Robinson R.A. 2012. Development of MSFD Indicators, Baselines and Target for the Annual Breeding Success of Kittiwakes in the UK. BTO Research Report No. 616. The British Trust for Ornithology, UK.

Frederiksen M., Wanless S., Harris M.P., Rothery P., Wilson L.J. (2004). The role of industrial fisheries and oceanographic change in the decline of North Sea black-legged kittiwakes. J. Appl. Ecol. 41: 1129–1139

Frederiksen M., Wright P.J., Harris M.P., Mavor R.A., Heubeck M., Wanless S. 2005. Regional patterns of kittiwake Rissa tridactyla breeding success are related to variability in sandeel recruitment. Mar. Ecol. Prog. Ser. 300: 201–211

Frederiksen, M., Mavor, R.A. & Wanless, S. 2007. Seabirds as environmental indicators: the advantages of combining data sets. Mar. Ecol. Prog. Ser. 352: 205–211.

Frederiksen, M., Jensen, H., Daunt, F., Mavor, R.A. & Wanless, S. 2008. Differential effects of a local industrial sand lance fishery on seabird breeding performance. Ecol. Appl. 18: 701–710.

Furness R.W. & Tasker M.L. 2000. Seabird-fishery interactions: quantifying the sensitivity of seabirds to reductions in sandeel abundance, and identification of key areas for sensitive seabirds in the North Sea. Mar. Ecol. Prog. Ser. 202: 253–264.

Lauria V., Attrill M.J., Pinnegar J.K., Brown A., Edwards M. & Votier S.C. 2012. Influence of climate change and trophic coupling across four trophic levels in the Celtic Sea. PLoS ONE 7(10): e47408.

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Figure 2. Good Environmental Status (GES) indicator in 2009. The map shows that GES was not met in 2009 as three colonies (red background) in the Great North Sea sub-region did not meet the predicted breeding success (green background) in 2009; the threshold, based on results from the random-slope model, was two colonies failing by chance. The pie charts indicate the proportion of years that the predicted breeding success was achieved (white) or not achieved (black) per each colony from 1991 to 2010. Colonies in the Celtic Sea could not be considered because the model did not reliably fit the data from that sub-region. From Dadam et al. (2012).

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Breeding success/failure of marine bird species

1. Indicator

Name: Breeding success/failure of marine bird species

Code: B-3 (27)

Proposed to BDC 2013 as: Core

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components Partially attributed (species/habitat types)

Applicability to sub-regions Yes

Assessment scales Yes

Monitoring parameter Yes

Monitoring frequency Yes

2. Appropriateness of the indicator

Biodiversity component: Marine Birds

MSFD criterion: 1.3 Population Condition

MSFD indicator: Population demographic characteristics (1.3.1)

Number of CPs Consensus among reporting/using CPs on usefulness Relevance to Applicable the indicator as part of a region Sensitivity to specific management across (n=9) wide set (n=8) pressures measures Practicable region

High - Sensitive to High Depends on cause Data on breeding Yes 8 8 changes in prey of changes to prey success for some availability, human availability (if fishing - species widely disturbance, high; if climate-low). available; for contaminants and other species High for human predation. only available for disturbance, parts of sub- contaminants* and regions (e.g. predation Wadden Sea). (*in combination with TMAP-monitoring of contaminants in bird eggs)

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The indicator is intended to complement another proposed core common indicator on annual breeding success of kittiwake (B-2), in order to keep a watching-brief on the population condition of other species and to include areas or sub-regions where the Kittiwake does not breed.

The indicator provides links to a number of pressures on breeding bird populations including food availability, human disturbance, contaminants and predation by invasive species (especially on islands).

Spatially the indicator is widely applicable for some species e.g. Common and Arctic Terns. Other species will be restricted to sub-regions and divisions thereof.

There are strong links to management, especially with regard to food availability, human disturbance and predation.

3. Parameter/metric

‘Annual colony failure rate’ i.e. the percentage of colonies failing per year, per species (from Cook et al. 2012).

Cook et al. (2012) considered a colony to have failed if the annual mean breeding success was 0.1 chicks fledged per nest or less. The appropriateness of their definition of colony failure needs further assessment. Although it flags up extreme breeding failure, it is not clear if this would exclude relatively poor breeding years for some areas and for some species.

The indicator is to be derived from data on annual mean breeding success (no. chicks fledged per pair) of marine bird species at colonies and in survey plots throughout the NE Atlantic. A separate indicator should be constructed for each species in each sub-region. Depending in species and area, the parameter may be derived from data hatching success (i.e. number of eggs hatched per pair).

In this context, ‘marine birds’ include the following taxonomic groups that are commonly aggregated as ‘waterbirds’ and ‘seabirds’:

a. Waterbirds: shorebirds (order Charadriiformes); ducks, geese and swans (Anseriformes); divers (Gaviiformes); and grebes (Podicipediformes);

b. Seabirds: petrels and shearwaters (Procellariiformes); gannets and cormorants (Pelecaniformes); skuas, gulls, terns and auks (Charadriiformes).

Species selected for this indicator should be sensitive to changes in pressures such as anthropogenic impacts on their food supply, predation by non-indigenous species, disturbance and contaminants - see Furness & Tasker (2000) who applied criteria to identify the most sensitive seabird species (Table 1) and Koffijberg et al. (2011) who identified species for the Wadden Sea (Table 2).

The indicators for each species are constructed from a time-series of annual estimates of breeding success at a sample of colonies. Not all the colonies in the sample will have been observed every year in the times- series. Missing annual observations can be predicted by models: Cook et al. (2012) used a Generalised Linear Model (GLM) framework with a binomial error structure. Breeding success for each colony in each year was calculated, and where this value was below 0.1 chicks per nest, the colony was assessed as having failed in that year. Breeding success or failure was modelled in relation to year and site, to account for the fact that. The coefficient for each year was then taken to represent the probability of breeding failure occurring at any given site within that calendar year. Year was fitted as a fixed effect factor, rather than a random effect so that the coefficients would not be constrained to follow a normal distribution.

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These models were used to estimate the annual colony failure rate (i.e. proportion of colonies in a sample that had annual breeding success of 0.1 or less chicks fledged per pair ) for each of 17 species during 1986- 2010 (data from UK Seabird Monitoring Programme). Of these 17 species, five were selected for the indicator for the Greater North Sea (Kittiwake, Little Tern, Sandwich Tern, Common Tern and Arctic Tern) and eight for the Celtic seas indicator (Kittiwake, Common and Arctic Terns [both subject to improved monitoring], Lesser Black-backed Gull and Herring Gull), on the basis of a) sufficient data to construct a robust failure rate model that accurately predicted observed failure rates; and of b) high or moderate sensitivity to reductions in sandeel abundance, as quantified by Furness & Tasker (2000) (Table 1). Arctic skua was omitted from the Greater North Sea indicator because of its limited distribution in this sub-region.

4. Baseline and Reference level

Complex baseline data for species, colonies and divisions of sub-regions are available.

5. Setting of GES boundaries / targets

The target proposed by the UK for the indicator is:

Criterion level target (1.3): Widespread seabird colony breeding failures should occur rarely in other species that are sensitive to changes in food availability.

The criterion target will be assessed on the basis of the number of species achieving species specific supporting targets: The annual percentage of colonies experiencing breeding failure does not exceed the mean percentage of colonies failing over the preceding 15 years, or 5%, whichever value is greater, in more than three years out of six.

The aim of the target is to ensure that only a small proportion of colonies fail per year, probably due to local problems, rather than any large scale anthropogenic impact. The aim of the target of 3 years out of six is to ensure that the cumulative effect of successive failures does not have a significant impact on recruitment into the regional population. Cook et al. (2012) tested various target thresholds on each species indicator of annual colony failure rate. They found that some species e.g. terns, experience breeding failure on a regular basis, others e.g. auks, rarely fail to breed. The threshold of the 15-year mean breeding failure rate was appropriate for species that regularly failed to breed, while a fixed threshold of 5% was appropriate for highlighting failures in species that rarely fail.

Further work is required to investigate how applicable these targets are to other species and other areas in the NE Atlantic Targets for other species and possibly for other ecological units or divisions of sub-regions would need to be developed.

6. Spatial scope

Breeding success of seabirds is monitored at colonies of a number of species throughout the NE Atlantic (see ICES 2007). Further work is needed to determine if the development of this indicator at the sub-regional scale will be restricted by lack of monitoring or data availability.

Hatching and fledging success is monitored for a selection of species breeding on soft coasts and islands e.g. in the Wadden Sea region. Monitoring is carried out on survey plots in colonies and for non-colony breeding shorebirds. Further work is needed to develop this indicator at the sub-regional scale.

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7. Monitoring requirements

The frequency at which data should be collected, annually

The monitoring method, Walsh et. al. 1995; for Wadden Sea Koffijberg et. Al. 2011

Who is responsible for the monitoring, National Monitoring Schemes.

For the Wadden Sea: the Trilateral Monitoring and Assessment Programme (TMAP)

Minimal required amount of monitoring locations. number required could be provided following further analysis of existing data

Does the required monitoring already exist? Most countries in the region collect breeding productivity data on marine bird species. Further work required to determine if sufficient data are collected by each country to construct indicators for relevant species in each sub-region.

8. Reporting

Targets can be updated on an annual basis. Cook et al. (2012) suggested a colour-coded alerts system, which enables an early warning that targets may not be met in subsequent years and may enable pre- emptive measures to be applied.

Breeding failure Alerts coding (see Table 2, from Cook et al. 2012):

“red alert” when target is exceeded in four or more of the preceding six years;

“amber alert” when target is exceeded in three of the preceding six years;

"green alert" when target is exceeded in less than three years of the preceding six.

Because of uncertainties with the definition of breeding failure (see above) “green” would not necessarily mean that breeding success is sustainable for the given species. Further work is necessary to make this system more robust.

Data needs to be collated centrally from CPs (at least at a sub-regional scale) and then analysed to produce indices, which can then be assessed against targets.

9. Resources needed

Most countries in the region collect breeding productivity data on marine bird species. Several countries have nationally co-ordinated monitoring schemes and national databases. Further work required to determine if sufficient data are collected by each country to construct indicators for relevant species in each sub-region. Monitoring in some countries may need to be expanded to construct a robust indicator.

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fledging. This requires one or two observers visiting a colony several times during the breeding season (i.e. usually May-Aug, but varies with species). Resources required for these visits are dependent on how remote the colony is i.e. colonies on uninhabited remote offshore islands are more expensive to monitor than colonies on mainland coasts. Monitoring costs in most countries are minimised by using volunteer observers, but professional observers are sometimes used to monitor some colonies – usually those on remote offshore islands. Hence, monitoring costs will vary between countries depending on the number of colonies to be monitored, the accessibility of these colonies and on how much of the monitoring can be done by volunteers.

A centrally funded annual analysis and collation is required: There is a need to nominate data custodians and analysts. This could be one CP per sub-region or a coordinating group for an ecological unit such as the Wadden Sea.

11. Further work

The COBAM expert group needs to consider further whether the TMAP approach for the Wadden Sea sub- region and the approaches to target setting recommended by Cook et al. 2012 can be amended in order to represent GES and whether they can they be applied elsewhere in the NE Atlantic. Specifically, they need to consider further the following issues:

i. Is breeding failure universally defined as 0.1 chicks per pair, or by some other threshold – perhaps bespoke to particular species or breeding areas.

ii. Are the methods recommended by Cook et al (2012) for defining target thresholds for percentage of colonies failing, applicable across species and breeding areas.

iii. Are the targets for this indicator aimed at representing GES or simply means of flagging-up areas of concern that may require for further action (e.g. management measures or further research).

iv. Should the indicator include just sensitive species or all species?

Assuming the indicator and targets are considered worthwhile developing for the rest of the NE Atlantic, the following tasks are required before the indicator can become operational:

f. Selection of constituent species

g. Further data analysis by CPs to determine baselines and targets.

h. Aggregate colony assessments to regional sea scale.

i. Co-ordinate across CPs within each sub-region, the collation of data, trend analysis, assessment against targets and reporting.

References

Cook A.S.C.P., Ross-Smith V.H. & Robinson R.A. 2012. Development of MSFD Indicators, Baselines and Target for Seabird Breeding Failure Occurrence in the UK. BTO Research Report No. 615. The British Trust for Ornithology, UK.

Furness RW and ML Tasker 2000. Seabird-fishery interactions: quantifying the sensitivity of seabirds to reductions in sandeel abundance, and identification of key areas for sensitive seabirds in the North Sea. Marine Ecology Progress Series 202: 253–264.

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ICES. 2007. Report of the Working Group on Seabird Ecology (WGSE), 19–23 March 2007, Barcelona, Spain. ICES CM 2007/LRC:05. 123 pp.

Koffijberg, K., Stefan Schrader & Veit Hennig 2011: Monitoring Breeding Success of Coastal Breeding Birds in the Wadden Sea – Methodological Guidelines and Field Manual. Joint Monitoring Group for Breeding Birds Common Wadden Sea Secretariat April 2011.Thyen, S., P.H. Becker, K.-M. Exo, B. Hälterlein, H. Hötker & P. Südbeck, 1998: Monitoring breeding success of coastal birds. Final report of the pilot studies 1996-1997. Wadden Sea Ecosystem Ecosystem No. 8. Common Wadden Sea Secretariat, Wilhelmshaven, Germany.

Willems, F., R. Oosterhuis, L. Dijksen, R.K.H. Kats & B.J. Ens, 2005: Broedsucces van kustbroedvogels in de Waddenzee 2005. Sovon-onderzoeksrapport 2005/07. SOVON, Beek-Ubbergen.

Walsh, P.M., Halley, D.J., Harris, M.P., del Nevo, A., Sim, I.M.W., & Tasker, M.L. 1995. Seabird monitoring handbook for Britain and Ireland. Published by JNCC / RSPB / ITE / Seabird Group, Peterborough.

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Table 1: Assessment of species sensitivity (1 = most sensitive, 17 = least sensitive) to anthropogenic activities affecting food supply (taken from Furness & Tasker 2000). Red = sensitive, amber = intermediate, green = non-sensitive.

Species Sensitivity rank

Arctic Tern (Sterna paradisaea) 1

Little Tern (Sternula albifrons) 2

Common Tern (Sterna hirundo) 3

Sandwich Tern (Sterna sandvicensis) 4

Kittiwake (Rissa tridactyla) 5

Arctic Skua (Stercorarius parasiticus) 6

Great Skua (Stercorarius skua) 7

Atlantic Puffin (Fratercula arctica) 7

Razorbill (Alca torda) 9

Lesser Black-backed Gull (Larus fuscus) 10

Herring Gull (Larus argentatus) 10

Great Black-backed Gull (Larus marinus) 12

Common Guillemot (Uria aalge) 13

Shag (Phalacrocorax aristotelis) 14

Great Cormorant (Phalacrocorax carbo) 15

Fulmar (Fulmarus glacialis) 15

Northern Gannet (Morus bassanus) 17

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Table 2. Selection and priority setting of species to be included in a TMAP monitoring scheme for breeding success in the Wadden Sea.

High priority species: Medium priority species Low priority species

High importance Wadden Sea As important as high priority Not typical for Wadden Sea species, but practical Habitat specialist Species too rare or breeding implementation difficult, or too locally Food specialist sensitive species (disturbance risk) Practical implementation Link with management difficult or sensitive species (disturbance risk)

Eurasian Spoonbill3 Hen Harrier Great Cormorant

Common Eider23 Great Ringed Plover Shelduck

Oystercatcher123 Kentish Plover Red-breasted Merganser

Avocet12 Northern Lapwing Dunlin

Black-headed Gull12 Black-tailed Godwit Ruff

Lesser Black-backed Gull1 Eurasian Curlew Common Snipe

Herring Gull12 Common Redshank(1) Turnstone

Sandwich Tern3 Little Tern Mediterranean Gull

Common Tern12 Short-eared Owl Little Gull

Arctic Tern Common Gull

Great Black-backed Gull

Gull-billed Tern

1 included in trilateral pilot 1996-97, Common Redshank left out for practical reasons (Exo et al. 1996)

2 included in monitoring scheme Dutch Wadden Sea 2005-2007 (Willems et al. 2005)

3 proposed to be included in Integrated Population Monitoring Dutch Wadden Sea (Reneerkens et al. 2005)

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Table 3 Assessment of breeding failure indicator against the target the percentage of colonies failing in more than three out of the previous six years for the Greater North sea and Celtic Seas sub-regions (UK data only) does not exceed the mean percentage failing over the preceding 15 years or 5 %, whichever is higher. Green indicates that target has been met or exceeded, Amber indicates that target has not been met in three out of the previous six years and Red indicates that target has not been met in four or more of the past six years. Species taken forward as indicators in each region highlighted in red boxes. From Cook et al. 2012. Little TernLittle Cormorant Guillemot Kittiwake Sandwich Razorbill

Common Common Northern Gannet Atlantic Fulmar Herring backed backed Lesser Puffin Black Black Arctic Arctic Shag Skua Sku Great Great Great Tern Tern Tern Gull Gull Gull 2

a 1 1 1 1 1 1 1 2 2

- - 2

2 2

2 1 2 1

GREATER NORTH SEA (UK ONLY)

2001 RED RED AMBER AMBER GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN 2002 RED RED AMBER GREEN GREEN AMBER GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN 2003 RED RED AMBER GREEN AMBER AMBER GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN 2004 RED RED RED GREEN AMBER AMBER GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN 2005 RED RED RED GREEN AMBER RED GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN AMBER GREEN 2006 RED RED RED GREEN AMBER RED GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN RED GREEN 2007 RED RED RED AMBER AMBER RED GREEN GREEN AMBER GREEN GREEN GREEN GREEN GREEN GREEN RED GREEN 2008 RED RED RED RED RED RED GREEN GREEN RED GREEN GREEN GREEN GREEN AMBER GREEN RED GREEN 2009 RED RED RED RED AMBER RED GREEN GREEN RED GREEN GREEN AMBER GREEN RED GREEN RED GREEN 2010 RED RED RED RED AMBER AMBER GREEN GREEN RED GREEN GREEN RED GREEN AMBER GREEN RED GREEN CELTIC SEAS (UK ONLY) 2001 GREEN GREEN GREEN GREEN GREEN NA NA GREEN GREEN AMBER RED GREEN GREEN GREEN GREEN GREEN GREEN 2002 GREEN GREEN GREEN GREEN GREEN NA NA GREEN GREEN AMBER RED GREEN GREEN GREEN GREEN GREEN GREEN 2003 GREEN GREEN GREEN GREEN GREEN NA NA GREEN GREEN GREEN RED GREEN GREEN GREEN GREEN GREEN GREEN 2004 GREEN GREEN GREEN GREEN GREEN NA NA GREEN GREEN GREEN AMBER GREEN GREEN GREEN GREEN GREEN GREEN 2005 GREEN GREEN GREEN GREEN GREEN NA NA GREEN GREEN AMBER RED AMBER GREEN AMBER GREEN GREEN GREEN 2006 GREEN GREEN GREEN GREEN GREEN NA NA GREEN GREEN AMBER RED RED GREEN RED GREEN GREEN GREEN 2007 GREEN GREEN GREEN GREEN AMBER NA NA GREEN GREEN AMBER RED RED GREEN AMBER GREEN GREEN GREEN 2008 GREEN GREEN GREEN GREEN RED GREEN GREEN GREEN GREEN AMBER RED RED AMBER AMBER AMBER GREEN GREEN 2009 GREEN GREEN GREEN AMBER RED GREEN GREEN GREEN GREEN RED RED RED AMBER AMBER RED GREEN GREEN 2010 GREEN GREEN GREEN RED RED NA NA GREEN GREEN AMBER RED RED AMBER GREEN RED GREEN GREEN

1 target is the percentage of colonies failing in more than three out of the previous six years does not exceed the mean percentage failing over the preceding 15 years 2 target is no more than 5 % of colonies failing in more than three out of the previous six years.

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OSPAR Commission BDC 13/4/2 Add.1-E

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OSPAR Commission BDC 13/4/2 Add.1-E Non-native/invasive mammal presence on island seabird colonies

1. Indicator

Name: Non-native/invasive mammal presence on island seabird colonies

Code: B-4 (29)

Proposed to BDC 2013 as: Core

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components Yes attributed (species/habitat types)

Applicability to sub-regions Yes

Assessment scales Yes

Monitoring parameter Yes

Monitoring frequency Yes

2. Appropriateness of the indicator

Biodiversity component: Marine Birds

MSFD criterion: 1.3 Population Condition

MSFD indicator: Population demographic characteristics (1.3.1)

Consensus Number of CPs among CPs on reporting/using usefulness as Sensitivity to Relevance to management Applicable the indicator part of a region specific pressures measures Practicable across region (n=9) wide set (n=8)

High - Terrestrial High Easy to measure Yes 5 5 pressure with impact presence/absence Effective management on seabirds of mammals measures well established

This indicator is derived from observations of the presence or absence of non-native or invasive mammal species on key island seabird colonies. The aim of the indicator is to inform management that will reduce the pressure on seabird populations from depredation by non-native or invasive mammals. This pressure is not addressed by indicators or targets under Descriptor 2 on Non-indigenous species.

Seabirds that nest on the ground are vulnerable to their eggs and young and themselves being killed by terrestrial mammals. Most inshore and offshore islands would be naturally free of mammals, but with human intervention (both intentional and unintentional), many such islands have been invaded by both native species (e.g. fox Vulpes vulpes) and non-native species (e.g. brown rat Rattus norwegicus, Amercian mink Neovison vison, domestic cat Felis catus). There is comprehensive evidence from around the world that the introduction of both native and non-native mammals on to previously mammal-free islands has a substantial

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development negative impact on ground-nesting seabirds, by reducing breeding success, by reducing breeding numbers and in some cases, causing colony extinction. Some of the largest colonies of seabirds in the NE Atlantic are on mammal-free islands. The populations of species that are most vulnerable to mammal predation: shearwaters and petrels (Procellariiformes), gulls (Laridae), terns (Sternidae) and Atlantic puffin (Fratercula arctica), black guillemot (Cepphus gryle) and groundnesting shorebirds and waterfowl tend to be aggregated on a relatively small number of mammal-free islands. This clumping makes their populations vulnerable to other small-scale impacts (e.g. from oil spills or local fish-stock collapse).

3. Parameter/metric

Number of island seabird colonies where non-native or invasive-native mammal species are present.

4. Baseline and Reference level

5. Target setting

The target on invasive mammals (see below), if met through eradication and quarantine measures, should make targets for population size (1.2) and species distribution (1.1) easier to attain, by directly removing a pressure and by creating more habitat than is currently available to breeding seabirds.

The GES Target: No non-native or invasive-native mammal species on islands that are already free of such species. The proportion of islands where non-native or invasive-native mammal species are present or having a significant impact, should be decreasing.

In order to achieve this target, CPs should include in their programme of measures, the following Operational (Management) Target: Minimise the risk of invasion by non-native mammals on all island seabird colonies, where this has not already occurred (including islands from where mammals have been eradicated); and eliminate detrimental impacts caused by mammals at a prioritised list of island seabird colonies.

The ‘islands’ referred to in the above targets must meet both criteria:

a. Be current, past or potential marine bird breeding sites.

b. Be individual islands or groups of islands that are at least 2km from adjacent mainland or other islands.

Criterion b) is necessary to prevent invasion or reinvasion from Amercian Mink. Employing mammal control or eradication measures on islands that could easily be reinvaded by mink, would be a waste of resources. Further details in Ratcliffe et al. 2009.

6. Spatial scope

NE Atlantic, but can be assessed at any smaller scale.

7. Monitoring requirements

Monitoring of mammal presence/absence required at all island colonies thought to be free of invasive non- native or native mammals, in conjunction with biosecurity measures to minimise risk of invasion. Subsequent monitoring at any other island colony where mammals are eradicated.

A list of islands to be monitored needs to be compiled by each CP – see criteria for island selection in section 5 above. In countries such Denmark, Sweden and Norway, compiling such a list could be a daunting

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development excercise. The use of GIS and teh application of a 2km buffer as suggested above, would greatly speed up teh process and greatly narrow down the number of islands to be included in this indicator.

In the UK, for example, many of the islands that could be potentially included in this indicator are designated as protected areas under existing national and international legislation (e.g. as Special Protection Areas under the Birds Directive). As a consequence, these sites are already under active management, which would make the introduction of mammal monitoring for this indicator a realistic proposition. Likewise the introduction of quarantine measures to prevent mammal invasion could be implemented as part of existing management plans, and is already done so at some sites. The eradication of mammals from islands would require a more substantial input of resources, though many such schemes have been successfully implemented around Europe.

The frequency at which data should be Frequently (e.g. annually) on islands with high risk of invasion by mammals or collected where mammals are already present

The monitoring method Surveys of mammals on or near to colonies concurrent with quarantine or eradication measures

Who is responsible for the monitoring, National Monitoring schemes

Minimal required amount of monitoring All identified island units locations.

Does the required monitoring already exist? No.

8. Reporting

At a local scale the indicator should be updated as frequently as possible - annually is preferable in areas where predator-free bird colonies have a high risk of invasion from mammals. There needs to be a close link between reporting the results of monitoring mammal presence and absence and the instigation of control measures. This will prevent mammals from becoming established on an island and having a significant impact on the resident birds. Prompt control measures following mammal invasion will save substantial resources in the long-term, which would be required to eradicate and established population of e.g. brown rats. Frequent monitoring of a site during and after control measures have been instigated, will enable the effectiveness of the management measures to be assessed and adjusted if required.

At a national or sub-regional scale assessments can be reported less frequently, e.g. every 6 years, to be in line with MSFD and Birds Directive reporting requirements. This level of reporting will provide an update on the scale of the extent of the pressure from non-native/invasive mammals in the region and report on the progress of large scale management strategies employed to mitigate the pressure.

9. Resources required

These will be unclear until a CP has identified how many ‘island’ units are to be included in its indicator.

Monitoring mammal presence is straight forward (e.g. placement of chew sticks and traps, observation of tracks and signs) but requires regular visits to islands. Resources required for these visits are dependent on the accessibility of the islands and on how much of the monitoring can be done by volunteers.

10. Further work

a. CPs to conduct GIS analysis to select ‘islands’ for inclusion in the indicator.

b. Coordination across CPs for reporting against the target.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development References

Capizzi D, Baccetti N & Sposimo P 2010. Prioritizing rat eradication on islands by cost and effectiveness to protect nesting seabirds. Biological Conservation 143 (2010) 1716–1727.

Ratcliffe N, Mitchell I, Varnham K, Verboven N & Higson P 2009. How to prioritize rat management for the benefit of petrels: a case study of the UK, Channel Islands and Isle of Man. Ibis (2009), 151, 699–708.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development

Mortality of marine birds from fishing (bycatch) and aquaculture

1. Indicator

Name: Mortality of marine birds from fishing (bycatch) and aquaculture

Code: B-5 (28)

Proposed to BDC 2013 as: Candidate

State of methodological development:

Development step Defined

Indicator metrics No

Ecosystem components Yes attributed (species/habitat types)

Applicability to sub-regions Yes

Assessment scales No

Monitoring parameter Yes

Monitoring frequency Yes

2. Appropriateness of the indicator

Biodiversity component: Marine Birds

MSFD criterion: 1.3 Population Condition

MSFD indicator: Population demographic characteristics (1.3.1)

Consensus among CPs on Number of CPs usefulness as reporting/using part of a Sensitivity to Relevance to Applicable the indicator region wide specific pressures management measures Practicable across region (n=9) set (n=8)

High- High No systematic Yes 8 8 monitoring at by-catch in fisheries Impacts can be reduced present through management measures

This indicator focuses on an impact of commercial fishing activities that is not addressed by indicators or targets under any of the other Descriptors. Mortality from birds being accidentally caught on longlines or trapped in other commercial fishing gear (e.g. gill nets) or in aquaculture structures (e.g. fish cages) could reduce the chance of achieving GES under other criteria for marine birds (e.g. 1.2 Population Size).

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Marine birds are long-lived and slow to reproduce, therefore any increase in adult mortality would make targets for population size more difficult to attain. Adult survival rates of marine birds are difficult to measure. In the absence of an effective indicator and target for survival rates, it would make sense to set a target against what could be a major anthropogenic cause of adult mortality in marine birds.

A comprehensive review of seabird bycatch from longlining and from other fisheries in the North Atlantic (ICES 2008, 2011) found evidence of substantial numbers of seabirds being killed. There have been notably high numbers of northern fulmar (Fulmarus glacialis) and great shearwater (Puffinus gravis) caught and killed by longlining in the NE Atlantic. There has been a moderate to high frequency of capture of species notable for their high conservation concern: sooty shearwater (Puffinus griseus), Cory’s shearwater (Calonectris diomedea) and black‐legged kittiwake (Rissa tridactyla). Species that forage by pursuit-diving (e.g. auks and cormorants) are most at risk from being caught and killed by gill nets and other fixed gear including aquaculture structures.

The lack of systematic monitoring of seabird bycatch on commercial vessels (spatial and frequency) makes it impossible to assess the extent of the impact on seabird populations at a regional/sub-regional scale (ICES 2008, 2011). Given that there are tried and tested measures to reduce seabird bycatch (for longlining at least), ICG-COBAM considered that an indicator of seabird bycatch would usefully inform such management and contribute to the achievement of GES re. seabird populations.

The European Commission has recently published details of a European wide National Plan of Action for reducing incidental catches of seabirds in fishing gears. This indicator should be developed as part of the implementation of the Euro PoA.

3. Parameter/metric

Number of birds caught of each species

4. Baseline and Reference level

To be determined, once data are available

5. Target setting

The target proposed is: Estimated mortality as a result of fishing bycatch and aquaculture entanglement does not exceed levels that would prevent targets for 1.2 population size from being achieved.

This target follows the approach applied to a similar target for harbour porpoise bycatch that is currently operational under the Habitats Directive and ASCOBANS, and is proposed as a GES target for marine mammals under criterion 1.3.

6. Spatial scope

To be determined. Worth noting that MSFD is restricted to MS waters, but the EU-PoA on seabird bycatch covers external waters also.

7. Monitoring requirements

The EU-PoA makes the following recommendations to Member States and Regional Fisheries Management Organisations (RFMO) for bycatch monitoring schemes:

a. Ensure that observers routinely deployed on vessels operating inexternal waters accurately record seabird bycatch.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development b. Ensure that observer data is routinely submitted to the Secretariat of the respective RFMO and the Commission to facilitate analysis of observer programme data

c. Establish a standard reporting format for recording seabird bycatch on a voluntary basis and to maintain a database of seabird bycatch in EU fisheries based on the information supplied by MS COM in conjunction with ICES.

d. Consider the feasibility of incorporating the monitoring of seabirds under the new DCF

The COBAM bird expert group recommends the following for a monitoring scheme under MSFD:

The frequency at which data should be collected, annually

The monitoring method, Observation on board fishing vessels according to requirements of the EU-PoA

Who is responsible for the monitoring, According to EU-PoA

Minimal required amount of monitoring locations. ?

Does the required monitoring already exist? There is currently no systematic monitoring of seabird bycatch in the NE Atlantic, but some countries do record some seabird bycatch in their waters.

8. Reporting

Reporting should follow the same cycle as required by the EU- PoA on seabird bycatch.

The Commission would carry out a full review and evaluation of the EU-PoA after the fourth report (eight years) of implementation and update the EU-PoA accordingly. This review would be timed to coincide with the obligation under the MSFD to reach GES for marine ecosystems by 2020.

Under Article 12 of the Birds Directive Member States must report every three years on the implementation of national provisions taken under the Directive. Where relevant, Member States could also use these reports as a data source (e.g. seabird population estimates) for use in evaluating the effectiveness of the PoA.

9. Resources required

The resources required to set up national bycatch monitoring schemes for this indicator, will be covered by those deployed by CPs to meet teh requirements of the EU-PoA on seabird bycatch.

11. Further work

a. Development of this indicator should be conducted as part of EU-PoA on seabird bycatch.

b. The first step is for CPs to scope out and instigate systematic monitoring of seabird bycatch in their waters. Some CPs do systematically monitor commercial vessels for marine mammal bycatch and there could be scope to adapt or expand such schemes to more effectively monitor seabird bycatch.

c. Population modelling is required to set targets on the level of acceptable mortality from bycatch and aquaculture. Need to know the providence of birds being caught.

d. Once monitoring schemes are up and running and targets have been set, there needs to be coordination across CPs within each sub-region, to collate bycatch data, conduct assessments against targets and report results.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development References

ICES. 2008. Report of the Working Group on Seabird Ecology (WGSE), 10-14 March 2008, Lisbon, Portugal. ICES CM 2008/LRC:05. 99 pp.

ICES. 2011. Report of the Working Group on Seabird Ecology (WGSE), 1–4 November 2011, Madeira, Portugal. ICES CM 2011/SSGEF:07. 87 pp.

COM(2012) 665 final Brussels, 16.11.2012 Communication from the Commission to the European Parliament and the Council; Action Plan for reducing incidental catches of seabirds in fishing gears

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Distributional pattern of breeding and non-breeding marine birds

1. Indicator

Name: Distributional pattern of breeding and non-breeding marine birds

Code: B-6 (24)

Proposed to BDC 2013 as: Core

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components Yes attributed (species/habitat types)

Applicability to sub-regions Yes

Assessment scales Yes

Monitoring parameter Yes

Monitoring frequency Yes

2. Appropriateness of the indicator

Biodiversity component: Marine Birds

MSFD criterion: 1.1 Species Distribution

MSFD indicator: 1.1.2 Distributional Pattern

Consensus among Relevance to Applicable Number of CPs CPs on usefulness Sensitivity to specific management across reporting/using as part of a region pressures measures Practicable region the indicator (n=9) wide set (n=8)

Low Low Monitoring of Yes 7 7 shorebirds and seabird Distribution is strongly colonies conducted driven by climate; throughout most of NE changes caused by Atlantic. Increase of at- human impacts may be sea monitoring needed obscured.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development The indicator on distributional pattern of marine birds will provide important supplementary information to the assessment of abundance of marine birds (common indicator B-1) because the distribution pattern might change due to pressures, while overall population size may remains unchanged. Changes in the distributional pattern of species that use shallow inshore areas could be useful to assess displacement due to activities such as offshore renewables (e.g.wind farms), or dredging, or aggregate extraction. Changes in distributional pattern may make populations of marine birds more vulnerable to pressures: for instance, if colonial-nesting species become concentrated into a small number of breeding colonies, local pressures may cause impacts at population scale.

This indicator is confined to those species of marine birds that tend to aggregate in inshore areas or at onshore breeding or roosting sites, for which distributional pattern can be accurately measured and is likely to provide an indication of anthropogenic impacts. The indicator is derived from information on colonial- breeding terns, gulls and cormorants; easily defined inshore aggregations of seaduck, divers and possibly grebes; as well as breeding and non-breeding shorebirds.

Distributional patterns of marine birds in offshore areas are not useful as indicators because they exhibit strong short-term variability due to numerous factors, especially weather. Distributional patterns of species that nest at a relatively small number of very large colonies e.g. auks, would not be a useful indicator because impacts would be reflected by decreases in abundance long before any changes in distributional pattern would become evident.

3. Parameter/metric

The parameter used to construct species-specific indicators of distributional pattern, should be the number of spatial sampling units where the species is either present or absent.

Spatial sampling unit may vary in size between different surveys. Humphreys et al (2012) use the number of occupied tetrads (2km*2km squares) to construct indicators from UK census data for non-breeding shorebirds. Tetrads are also used by breeding bird Atlas surveys in Britain and Ireland. But in Germany, for example, breeding bird atlas data are collected using a grid size of roughly 5km x 5km. Variation in sample unit size is not a problem as long as the same unit is used for particular country or area in which change in distributional range is being measured (see section on target-setting).

Further work is needed to develop metrics and determine appropriate sampling units for all relevant bird groups throughout the NE Atlantic region. For example the indicator for shorebirds along open stretches of coast in the UK (Humphreys et al. 2012) may not be appropriate for shorebirds foraging on large mudflats (e.g. Wadden Sea), where monitoring is largely restricted to counts at high tide roosts. Metrics have yet to be derived for data on the at-sea distribution of marine birds.

4. Baseline and Reference level

Each supporting target will be set against a baseline distributional pattern:

a) where data are available: set baseline at a point in the past when anthropogenic impacts are likely to have been relatively minimal compared to the rest of the time-series; the baseline needs to reflect prevailing climatic conditions. It may prove difficult to set a baseline that meets both critera.

b) where no previous data are available: set baseline at the start of the new time-series and amend in due course - see (a)..

5. Target setting

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development The criterion-level target for Species Distribution (1.1) should be no major shifts or shrinkage in the range of marine birds in 75% of species monitored.

The extent of a major shift or shrinkage in distribution of each species is defined by whether or not supporting targets for both distributional pattern are both met.

Humphreys et al (2012) proposed the following supporting target relating to shrinkage: the distributional range (as measured by percentage occupancy ) in an area should not decrease, with statistical significance by x% or more; . where change in percentage occupancy is calculated as shown in Box 1; and the statistical significance of the change in percentage occupancy was obtained using a generalized linear model with binomial response variable and a logit error distribution to test the null hypothesis: there is no difference in the proportion of tetrads occupied in the baseline survey period compared to the subsequent survey period.

Note that the value of x in the above target needs to reflect the percentage occupancy of the species concerned. For example, if a species occupied only 10% of an area, a significant change in occupancy would be less than 10%. Conversely, if a species occupied 90% of an area, a significant change in occupancy may be much larger, eg, 20%.

Box 1. Calculation of change in percentage occupancy for distributional pattern (from Humphreys et al. 2012):

STEP 1 – calculate percentage occupancy, where

Percentage occupancy = 100 * (number of spatial units occupied by species x / number of spatial units in assessment area).

STEP 2 – calculate change in percentage occupancy between baseline period A and subsequent period B; where

Change in percentage occupancy = percentage occupancy A – percentage occupancy B

Example:

Number of spatial units (e.g. 2km x 2km tetrads) in assessment area = 560

Number of tetrads occupied in survey period A= 40 = (40/560) = 7%

Number of unit area occupied in survey period B = 28 = (28/560) = 5%

Therefore the change in percentage occupancy = -2%

The change in percentage occupancy (in Box 1) does not necessarily detect a shift in distribution where the overall percentage occupancy of the assessment areas remains unchanged. A shift in distribution could be detected by an alternative metric, shown in Box 2.

Box 2. Metric to detect a shift in distribution

Shift Index = (2*(A&B))/(A+B), where ‘A’ is the number of spatial units (e.g. tetrads or sites) occupied by species x during the baseline period A, and ‘B’ is the number of units occupied in the subsequent period of interest, and ‘A&B’ is the number of units occupied in both periods.

If Shift Index = 0, there has been a complete shift in distribution.

If Shift Index = 1, there has been no shift in distribution, i.e. the same sites are occupied in both periods.

The Shift Index in Box 2, would be affected by overall changes in occupancy (see Box 1), which is undesirable. It should be possible to correct for this effect, perhaps by dividing by the maximum value

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development possible given the overall change in occupancy. Suitable target values for such a metric requires further thought.

6. Spatial scope

Initially, the indicator is likely to be constructed from data that has been collected throughout the NE Atlantic on non-breeding shorebirds, breeding colonies of seabirds and coastal-breeding waterbirds. Indicators of waterbirds and seabirds at sea are likely to be more restricted, given that monitoring is currently confined to certain parts of the Greater North Sea i.e. the waters of DE, BE, DK, NL, SE, FR? and NO.

The supporting targets for each species should be assessed at a large scale to detect significant population level changes in distribution. As an example, of those scales tested in the UK by Humphreys et al. (2012) the following should be appropriate: Sub-regional (i.e. Celtic Seas and Greater North Sea), or country parts of each subregion (e.g.lish north sea coast), or alternatively, national marine planning policy areas if these exist (as suggested by Humphreys et al 2012, but not tested).

To provide a watching brief on potential local anthropogenic impacts on distribution, parallel assessment should be undertaken at smaller scales within each country, e.g. local administrative areas. These parallel assessments should not be used to assess achievement of GES but should be used to inform local measures and provide an early warning of potential population level impacts.

7. Monitoring requirements

The frequency at which data should be collected, at least once every two reporting periods

For colonies and other breeding sites: Walsh et. al. (1995); Koffijberg et. al. (2011) - for Wadden Sea.

For at-sea aerial and boat-based line transect surveys (Camphuysen et al. 2004 )

Who is responsible for the monitoring, National Monitoring Schemes

Minimal required amount of monitoring locations. total coverage within assessment areas

Does the required monitoring already exist? Censuses of breeding marine birds have been conducted in Denmark, UK, Republic of Ireland, France, Belgium, the Netherlands, Germany and Spain; but not in Norway.

Monitoring of marine bird abundance at sea inshore is currently confined to certain parts of the Greater North Sea. The UK is currently scoping a monitoring scheme for inshore waters

8. Reporting

The indicator is unlikely to be fully updated during each six year reporting cycle for MSFD, because monitoring of some species in some areas is very labour and resource intensive and is unlikely to be carried out more frequently than once every 10 years. However, where monitoring is carried out more frequently it may be possible to update the indicator and assessments for species in these areas every six years or more frequently.

There are no details yet on how data will be collated analysed and disseminated. The first step will be to be trial the collation and assessment of a single species indicator to scope the level of co-ordination required. The key question is whether or not raw data from each country needs to be pooled prior to construction and assessment of the indicator.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development 9. Resources needed

Most countries in the region conduct annual monitoring of abundance of marine birds on land i.e. counts of birds or pairs at breeding sites and counts of shorebirds in intertidal areas or when roosting above high water. Monitoring of non-breeding shorebirds in the Greater North Sea and Celtic Seas is concentrated in transitional waters, so additional monitoring of non-estuarine coasts may be required to construct the indicator for these species. Monitoring of breeding abundance of marine birds is conducted in all countries in the region and as part of nationally co-ordinated schemes with central data storage mechanisms (e.g. national databases), in all countries except Portugal and Sweden (North Sea coastline). Most countries monitor a sample of their colonies, with some but not all counted annually. Data from these annual samples of colonies will be used to construct the common indicator B-1 (Species-specific trends in relative abundance of non-breeding and breeding marine birds). The indicator for distribution of breeding marine birds will require all colonies to be surveyed periodically as part of a census. Censuses of breeding seabirds have been conducted once in Denmark and more than once in the UK, Republic of Ireland, France, Belgium, the Netherlands, Germany and Spain. Such censuses have never been conducted in Norway

Breeding censuses use the same methods used for monitoring breeding abundance. Survey methods are more straightforward in some species than others, so species-specific methods have been designed and are widely used (see e.g. Walsh et al. 1995). Each census will require a periodic additional input of resources to survey those colonies not included in the annual monitoring programme. The cost of each census will therefore be additional to the cost of annual monitoring of breeding abundance for indicator B-1 (Species- specific trends in relative abundance of non-breeding and breeding marine birds). The size of this additional resource is dependant on the number of additional colonies to be surveyed, the accessibility of these colonies and on how much of the monitoring can be done by volunteers.

Monitoring of marine bird abundance at sea inshore is currently confined to certain parts of the Greater North Sea i.e. the waters of DE, BE, DK, NL, SE, (FR?) and NO. The UK is currently scoping a monitoring scheme for inshore waters. Numbers of birds at sea are either counted from ships or from the fixed-winged aircraft. Surveys need to be conducted by professional observers, rather than volunteers. Costs for ship-time and flight-time can be reduced by sharing the platform with other marine biological surveys (e.g. benthic surveys or cetacean surveys). There is potentially scope for neighbouring countries to share survey platforms.

Both aerial and ship-based surveys count numbers of birds in a sample of the survey area i.e. along transects. There are European-wide standards for collecting these data (Camphuysen et al. 2004). These data are used to construct maps of bird density across the survey area. An area may need to be repeatedly surveyed in a single year to capture seasonal variation in bird abundance. These bird density maps can be used for some species to construct the common indicator B-1 (Distributional pattern of breeding and non- breeding marine birds) Monitoring costs for both indicators are not necessarily additive.

10. Further work a) Further consider recommendations for metrics and target-setting given above.

b) Select constituent species.

c) Agree on how to measure the distributional pattern of seabirds and waterbirds at-sea.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development d) Select baseline range for each species.

e) Define target range for each species (i.e. supporting target).

f) Compile a plan for co-ordination of data collation, analysis, assessment and reporting across CPs.

References Camphuysen C.J., Fox A.D., Leopold M.F., & Petersen I.K., 2004. Towards standardised seabirds at sea census techniques in connection with environmental impact assessments for offshore wind farms in the U.K.: a comparison of ship and aerial sampling methods for marine birds, and their applicability to offshore wind farm assessments (PDF, 2.7 mb), NIOZ report to COWRIE (BAM – 02-2002), Texel, 37pp. Humphreys E M, Risely K, Austin G E, Johnston A & Burton N H K 2012. Development of MSFD Indicators, Baselines and Targets for Population Size and Distribution of Marine Birds in the UK. BTO Research Report No. 626 Reid JB & Camphuysen C.J. 1998. The European Seabirds at Sea database. Biol. Cons. Fauna 102: 291.

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Fish and Cephalopods

Code Previous Indicator Category code* FC-1 17 Population abundance/ biomass of a suite of selected species Core

FC-2 20 OSPAR EcoQO for proportion of large fish (LFI) Core

FC-3 22 Mean maximum length of demersal fish and elasmobranchs Core

FC-4 18 By-catch rates of Chondrichthyes Candidate

FC-1 Population abundance/ biomass of a suite of selected species

INDICATOR

Name: Population abundance/ biomass of a suite of selected species

Code: FC-1

Proposed to BDC 2013 as: Core indicator

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components Partially attributed (species/habitat types)

Applicability to sub-regions Yes

Assessment scales No

Monitoring parameter Yes

Monitoring frequency Yes

APPROPRIATENESS OF THE INDICATOR

BIODIVERSITY COMPONENT: Fish and Cephalopods

DESCRIPTOR: Biodiversity

CRITERION: 1.2 Population size

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development INDICATOR: Population abundance/ biomass of a suite of selected species (1.2.1)

Sensitivity to Relevance to Practicable Applicable Number of CPs Consensus among specific pressures management across region reporting/using CPs on usefulness as measures the indicator part of a region wide (n=9) set (n=8)

High - selective High – quick Existing monitoring Yes 7 7 extraction of species response for some species, additional monitoring needed

The indicator is regarded as appropriate as it fulfils the following criteria for selecting OSPAR common biodiversity indicators: The indicator is simple to measure and specific. Abundance/biomass indicators can be spatially applied and the necessary data that feeds into these indicators are already collected widely across the OSPAR region. The indicator also benefits from being easily communicated to the wider public as the concept of the indicator is easy to understand. The indicator is sensitive to particular human pressures (such as selective extraction of species) but it also fluctuates due to natural variability. This is a weakness as it can hamper to responsiveness to management measure.

PARAMETER/METRIC:

Abundance:

NPUE is the total number of individuals of a species caught per survey station and standardised per unit of effort, either trawling hours or distance towed. Log transformation can be applied to improve the signal-to- noise ratio.

Catch Weight:

WPUE is the total weight of a species caught per station on a survey standardised per unit of effort, either trawling hours or distance towed. If catch weights are not recorded, they can be estimated from numbers at length-weight conversions for each species using the allometric formula:

W=a*(length)b where a and b are constants for each species, the first being a scaling factor for units, the second being a factor relating to change of shape with increasing size (Froese, 2006). a and b parameters can be either estimated from the survey or obtained from external sources, eg fishbase.

Since abundance indicators give equal weight to all ages of the population (depending on catchability), abundance is sensitive to large recruitment pulses, which can result in high interannual variability. Biomass is less influenced by varying recruitment from year to year as more weight is given to the older, larger individuals of a population. This means that biomass time series tend to display less noise than those for abundance indices (Cotter et al. 2009).

BASELINE AND REFERENCE LEVEL

The baseline should reflect historical condition where overall exploitation is considered to be sustainable and populations are considered to display a satisfactory age composition. If this cannot be evaluated, the long- term mean could be used as an alternative.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development SETTING OF GES BOUNDARIES/TARGETS

Fish abundance and biomass are expected to decrease in exploited populations (Beverton and Holt, 1957), and this applies to target and non target species that are taken as by-catch and are exposed to similar impacts. Some non-target species can increase in abundance because of lower predation by depleted target predator species (Rochet and Trenkel, 2003). Species specific targets need be developed that relate to reference conditions and should incorporate natural variability. Where reference levels are not known due to the absence of appropriate time series, trend targets can be set. The trend in population abundance/ biomass should alter in a predictable specified direction towards community recovery.

SPATIAL SCOPE

This indicator should be applied at the sub regional level or at the survey level. Appropriate aggregation methods across surveys within subregions still need to be developed. In some cases, smaller spatial scales need to be used, depending on stock structure.

MONITORING REQUIREMENTS

Data for this indicator comes from scientific fisheries surveys which provide a measure of the abundance or biomass of fish species and can include among others, trawl, acoustic, egg and underwater TV surveys. To compute the indicator, surveys need to be conducted at regular intervals (annually) in the same area with a standard gear. There are currently extensive surveys conducted across the OSPAR region to measure the abundance/biomass of commercial fish. These surveys are funded nationally and as part of the data collection framework directive. For demersal fish, the most important data source for this indicator is fisheries groundfish surveys which are conducted as part of the ICES international bottom trawl survey programme (IBTS) in the North Sea, the Celtic Seas, Bay of Biscay and Iberia (see figure 1). For pelagic fish there are a series of acoustic surveys (such as International blue whiting acoustic surveys) and egg surveys (such as MEGS- international mackerel and horse mackerel egg surveys).

REPORTING

The raw sampling data for demersal fish from the IBTS surveys are uploaded into the ICES DATRAS data base and can be used for indicator calculation. Abundance and biomass indicators of selected commercial species are also housed in the DATRAS data base. There are several ICES survey working groups which are used for the reporting and publishing of other species abundance indicators such as WGNAPES and WGMEGS. Most of the species which are reported on are commercial species. There is potential for developing more reporting of non commercial species through ICES working groups such as WGBIODIV.

RESOURCES NEEDED

The costs for this indicator are estimated to be high, but are primarily met under existing national programmes and the data collection framework. Current monitoring requirements are covered under the DCF and a gap analysis would be necessary to identify any selected species or ecosystems that are not covered. Reporting, data analysis and development as well as assessment could be carried out within the ICES framework. It is assumed that management measures would relate to fisheries and come under the CFP.

FURTHER WORK

1. Species selection:

The criteria for selecting species need to be agreed and a species list needs to be developed on a regional basis, taking catchability of different surveys into account.

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The metric of the indicator needs to be further refined and agreed among CPs who are sharing MSFD subregions. This relates to whether biomass or abundance should be used, what standardisation procedures are applied (by hour or distance trawled) and how station data is aggregated. In order to ensure transparency and repeatability of the indicator, step by step calculation methods should be specified as ‘pseudo-code’, or flow diagrams including defined data clearing routines applied to central datasets (such as ICES’ DATRAS database), and a defined list of biological parameters used in the calculations (such as a and b LW parameters).

3. Target setting:

The method of target setting and trend detection should be agreed. Species-specific targets and baselines need to be given further consideration.

REFERENCES

Beverton, R. J. H., and Holt, S. J. 1957. On the dynamics of exploited fish populations. Fishery Investigations, Series II, 19. Her Majesty’s Stationery Office, London. 533 pp.

Cotter J., Mesnil B., Witthames P., Parker-Humphreys M. (2009), Notes on nine biological indicators estimable from trawl surveys with an illustrative assessment for North Sea cod. Aquat. Living Resour. 22, 135–153.

Froese R (2006). Cube law, condition factor and weight-length relationships: history, meta-analysis and recommendations. Journal of Applied Ichthyology, 22(4): 241–253.

Rochet, M. J., and Trenkel, V. M. (2003). Which community indicators can measure the impact of fishing? A review and proposals Canadian Journal of Fisheries and Aquatic Sciences, 60: 86-99.

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OSPAR EcoQO for proportion of large fish

INDICATOR

Name: OSPAR EcoQO for proportion of large fish

Code: FC-2

Proposed to BDC 2013 as: Core indicator

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components Partially attributed (species/habitat types)

Applicability to sub-regions Yes

Assessment scales No

Monitoring parameter Yes

Monitoring frequency Yes

APPROPRIATENESS OF THE INDICATOR

BIODIVERSITY COMPONENT: Fish and Cephalopods

DESCRIPTOR: Biodiversity (1) Foodwebs (4)

CRITERION: 1.6 Habitat condition, 1.7.1 Composition and relative proportions of ecosystem components (habitats and species); 4.2. Proportion of selected species at the top of food webs

INDICATOR: Condition of the typical species and communities (1.6.1), Large fish (by weight) (4.2.1)

Sensitivit Relevance to Practicable Applicable Number of CPs Consensus among CPs y to management reporting/using on usefulness as part of

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High - High - but time ECO QO and operational Yes - except 7 7 selective lag in response, in the North Sea, part of Region V (no extraction up to a decade the DCF for all regións. bottom trawl of species or more Existing monitoring in surveys) other regions, additional effort required for regional adaptation

The large fish indicator is an OSPAR EcoQO in the North Sea. The LFI is part of the indicator suite that member states have to report on under the data collection framework directive to evaluate the effects of fishing on the ecosystem (2010/93/EU). The indicator is regarded as appropriate as it fulfils the following criteria for selecting OSPAR common biodiversity indicators:

It is sensitive to a particular human pressure (selective extraction of species), it can be accurately determined; it is specific and simple to measure. The indicator also benefits from being easily communicated to the wider public as the concept of the indicator is easy to understand. The LFI can be spatially applied and the necessary data that feeds into this indicator is already collected widely across the OSPAR region. There is still a question mark on how responsive the indicator is to management measures. There is a known lag period for this indicator with an estimated time period of several decades (Fung et al. 2012).

PARAMETER/METRIC

According to SEC (2008), the proportion of large fish is calculated as:

W40cm P40cm  where W>40cm is the weight of fish greater than 40 cm in length and WTotal is the total weight WTotal of all fish in the sample. Weights estimated from numbers at length for each species using the allometric formula:

W=a*(length)b where a and b are constants for each species, the first being a scaling factor for units, the second being a factor relating to change of shape with increasing size. a and b parameters can be either estimated from the survey or obtained from external sources, eg fishbase. The indicator is survey specific. The “large” fish threshold needs to be set at a level that decreases the noise around the trend caused by e.g. recruitment effects while maintaining the indicators’ sensitivity. The OSPAR EcoQO is based on the North Sea IBTS data and defines the size threshold of 40 cm.

BASELINE AND REFERENCE LEVEL

The baseline should reflect historical condition where overall exploitation was considered to be sustainable. A reference levels has been specified for the North Sea IBTS surveys and is 0.3 of the fish community by weight to be larger than 40cm (Greenstreet et al. 2011), and this has been adopted as the OSPAR EcoQO for the North Sea fish community. A reference level has been proposed for the West Coast Ground Fish Survey (WCGFS), which is for 0.4 of the fish community by weight to be larger than 50cm (Shepherd et al. 2011), however the WCGFS was discontinued in 2004.

SETTING OF GES BOUNDARIES/TARGETS

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development For each region the proportion (by weight) of fish greater than a specific size in length caught during routine demersal fish surveys (e.g. the ICES International Bottom Trawl Survey) should be greater than a defined target. This target needs to be survey specific, and relate to reference conditions and should incorporate natural variability. Where reference levels are not known due to the absence of appropriate time series, trend targets can be set. The trend in LFI should alter in a predictable specified direction towards community recovery.

SPATIAL SCOPE

This indicator should be applied at the sub regional level or at the survey level. Appropriate aggregation methods across surveys within subregions still need to be developed. Depending on management units, smaller spatial scales might be required in some sub-regions.

MONITORING REQUIREMENTS

Data for this indicator comes from scientific fisheries surveys which sample the whole fish community and the methods require that surveys are conducted at regular intervals (annually) in the same area with a standard gear. Currently, the most important data source for the LFI is fisheries groundfish surveys which are conducted as part of the ICES international bottom trawl survey programme in the North Sea, the Celtic Seas, Bay of Biscay and Iberia.

REPORTING

The LFI is part of the indicators that member states have to collect for the data collection framework. The raw data from the IBTS surveys are uploaded into the ICES DATRAS data base and can be used for indicator calculation. Several ICES working groups and STECF have evaluated this indicator based on contributions from member states, but there is currently no formal reporting structure where every member states supplies the results of this indictor on a regular basis. There is potential for developing a more formal reporting structure through ICES or the regional databases which will form part of the new Data Collection framework (ref).

REQUIRED RESOURCES

The resource implications for this indicator are estimated to be high, but are primarily met under the national programmes and the Data collection framework. Current monitoring requirements are covered under the DCF and a gap analysis would be necessary to identify any subregions or ecosystems that are not adequately covered. Reporting, data analysis and development as well as assessment could be carried out within the ICES framework under WGBIODIV, WGECO or regional ecosystem assessment working groups. It is assumed that management measures would relate to fisheries and come under the CFP.

FURTHER WORK

1. Application across regions:

The trans-regional applicability of the LFI still needs to be demonstrated. Whereas the LFI has been validated in the North Sea, contrasting results have been obtained in some ecosystems, e.g. for the southern part of the Bay of Biscay. Calculations of the LFI in other parts of European waters, e.g. Northern part of Bay of Biscay, West Scotland and the Baltic, are currently being carried out by the European Scientific Technical and Economic Committee for Fisheries (STECF). Further development of the indicator is also taking place within ICES working groups (WGECO).

2. Survey selection:

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3. Careful consideration will need to be given on the selection of species to include in the analysis. Selection criteria should include survey catchability, ecological significance and purpose of indicators (ie as a biodiversity indicator or a foodweb indicator). Pelagic species are excluded from the biodiversity indicator but might be included as part of a foodweb indicator.

4. Metric development

The metric of the indicator needs to be further refined and agreed among CPs who are sharing MSFD subregions. In order to ensure transparency and repeatability of the indicator, step by step calculation methods should be specified as ‘pseudo-code’, or flow diagrams including defined data clearing routines applied to central datasets (such as ICES’ DATRAS database), and a defined list of biological parameters used in the calculations (such as a and b parameters).

5. Target setting:

Targets need to be established for each marine region relative to a region specific reference period, and dependent on the species composition included in the indicator calculation. If used as a food web metric, pelagic species may be included - thus new targets will need to be established. The feasibility of aggregating across surveys needs to be evaluated.

REFERENCES

EU, 2010. COMMISSION DECISION of 18 December 2009 adopting a multiannual Community programme for the collection, management and use of data in the fisheries sector for the period 2011-2013 (2010/93/EU).

Fung, T., Farnsworth, K. D., Reid, D. G., Rossberg, A. G., 2012. Recent data suggest no further recovery in North Sea Large Fish Indicator. ICES Journal of Marine Science 69 (2), 235–239.

Greenstreet, S. P. R., Rogers, S. I., Rice, J. C., Piet, G. J., Guirey, E. J., Fraser, H. M. & Fryer, R. J.

2011 Development of the EcoQO for the North Sea fish community. ICES Journal of Marine

Science 68, 1-11.

Kerr, S. R. & Dickie, L. M. 2001 The biomass spectrum: a predator prey theory of aquatic production. New York: Columbia University Press.

SEC 2008: Commission staff working document. Accompanying the document Communication from the Commission to the Council and the European Parliament. The role of the CFP in implementing an ecosystem approach to marine management [COM(2008)187 final].

Shephard, S., Reid, D. G. & Greenstreet, S. P. R. 2011 Interpreting the large fish indicator for the Celtic Sea. ICES Journal of Marine Science 68, 1963-1972.

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MEAN MAXIMUM LENGTH OF DEMERSAL FISH AND ELASMOBRANCHS (MML)

INDICATOR

Name: Mean Maximum Length of demersal fish and elasmobranchs (MML)

Code: FC-3

Proposed to BDC 2013 as: Core indicator

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components Partially attributed (species/habitat types)

Applicability to sub-regions Yes

Assessment scales No

Monitoring parameter Yes

Monitoring frequency Yes

The mean maximum length indicator (MML) is a size based indicator to measure the life history composition of the fish community. Size based indicators are considered suitable to measure the effects of fishing on the fishing community as they are responsive to fishing impacts. This indicator uses species’ Lmax as a proxy for life-history characteristics and measures the potential size of species making up the community. The MML indicator is the average Linf (or Lmax) of fish making up the sampled community and provides a measure of the relative composition of species within the community. The MML does not reflect any change in size structure of individual populations. Data for this indicator comes from scientific fisheries surveys which sample the whole fish community and the methods require that surveys are conducted at regular intervals (annually) in the same area with a standard gear. Targets are set according to the principle that the fish community is moving towards recovery from fishing. The MML is part of the indicator suite that member states have to report on under the data collection framework directive to evaluate the effects of fishing on the ecosystem (2010/93/EU). Currently, the most important data source for the MML is fisheries groundfish surveys which are conducted as part of the ICES international bottom trawl survey programme in the North Sea, the Celtic Seas, Bay of Biscay and Iberia.

APPROPRIATENESS OF THE INDICATOR

BIODIVERSITY COMPONENT: Fish and Cephalopods

DESCRIPTOR: Biodiversity (1)

CRITERION: 1.6 Habitat condition, 1.7.1 Composition and relative proportions of ecosystem components (habitats and species; 4.2.

INDICATOR: Condition of the typical species and communities (1.6.1)

Sensitivity Relevance to Practicable Applicable Number of CPs Consensus among CPs

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High - High - but time lag in Operational in Yes - except 7 7 selective repsonse. principle as as part Region V (no extraction of Complements LFI FC- of the bottom trawl species 2 requirements surveys) under the DCF. Targets still have to be further developed

The MML is sensitive to a particular human pressure (selective extraction of species), it can be accurately determined; it is specific and simple to measure. The MML can be spatially applied and the necessary data that feeds into this indicator is already collected widely across the OSPAR region. There is still a question mark on how responsive the indicator is to management measures. There is a known lag period for this indicator.

PARAMETER/METRIC

According to SEC (2008), the mean maximum length is calculated as:

max   max j j )( NNLL j where Lmax j is the maximum length obtained by species j, Nj is the number of individuals of species j and N is the total number of individuals. Asymptotic total length (Linf) is used where available, otherwise the maximum recorded total length (Lmax) can be used.

BASELINE AND REFERENCE LEVEL

The reference state is a fish community which is sustainably fished. The baseline should reflect historical condition where overall exploitation is considered to be sustainable (in the medium to longterm).

SETTING OF GES BOUNDARIES/TARGETS

Target setting should be either trend based whereby the MML should alter in a predictable specified direction towards community recovery or be based on reference levels as described above and incorporate natural variability.

SPATIAL SCOPE

This indicator should be applied at the sub regional level or at the survey level. Appropriate aggregation methods across surveys within subregions still need to be developed.

MONITORING REQUIREMENTS

Data for this indicator comes from scientific fisheries surveys which sample the whole fish community and the methods require that surveys are conducted at regular intervals (annually) in the same area with a standard gear. Currently, the most important data source for the MML is the fisheries groundfish surveys which are conducted as part of the ICES international bottom trawl survey programme in the North Sea, the Celtic Seas, Bay of Biscay and Iberia (see figure 1).

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The MML is part of the indicators that member states have to collect for the data collection framework. The raw data from IBTS surveys are uploaded into the ICES DATRAS data base and can be used for indicator calculation. Several ICES working groups and STECF have evaluated this indicator based on contributions from member states, but there is currently no formal reporting structure where every member states supplies the results of this indictor on a regular basis. There is potential for developing a more formal reporting structure through ICES or the regional databases which will form part of the new Data Collection framework.

RESOURCES REQUIRED

The resource implications for this indicator are estimated to be high, but are primariliy met under the Data collection framework. Current monitoring requirements are covered under the DCF and a gap analysis would be necessary to identify any subregions or ecosystems that are not covered. Reporting, data analysis and development as well as assessment could be carried out within the ICES framework under WGBIODIV, WGECO or regional ecosystem assessment working groups. It is assumed that management measures would relate to fisheries and come under the CFP.

FURTHER WORK

1. Survey selection:

CPs need to agree on the survey(s) to be used in different subregions. This indicator should be calculated using species, length and abundance survey data that have been collected from the largest proportion of the marine region over the longest available time period.

2. Metric development

biological parameters used in the calculations (such as Linf). The methods of aggregation across surveys should be evaluated and further developed if feasible.

3. The method of target setting or trend setting should be agreed.

REFERENCES

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BYCATCH RATES OF CHONDRICHTHYES

1. Indicator

Name: Bycatch rates of Chondrichthyes

Code: FC-4

Proposed to BDC 2013 as: Candidate indicator

State of methodological development:

Development step Defined

Indicator metrics No

Ecosystem components Partially attributed (species/habitat types)

Applicability to sub-regions Yes

Assessment scales No

Monitoring parameter No

Monitoring frequency No

The bycatch rate of chondrichthyes is a pressure indicator, which measures the degree of bycatch of Chondrichthyes in commercial fisheries. Chondrichthyes are cartilaginous fishes and include elasmobranchs (sharks, rays and skates) and chimaeras. Due to their life history traits of large body sizes, slow growth rates and low fecundity, chondrichthyes are particularly vulnerable to the impacts of overfishing (Dulvy and Reynolds, 2002; Reynolds, et al. 2001). Data for this indicator comes from scientific observer programmes onboard fishing vessels which quantify the bycatch of Chondrichthyes in commercial fisheries. It is envisaged that the indicator would be implemented based on a risk assessment, which identifies the fishing metiers which pose high risk to the sustainability of Chondrichthyes species. There are a number of scientific fisheries observer programmes within the OSPAR area under national and European legislations (such as data collection framework and deepwater access scheme); however there is no dedicated programme currently in place for this indicator. The target is to reduce the bycatch in cartilaginous fishes. The possibility to develop species specific bycatch targets needs to be further explored.

2. Appropriateness of the indicator

BIODIVERSITY COMPONENT: Fish and Cephalopods

DESCRIPTOR: Biodiversity

CRITERION: 1.2 Population size

INDICATOR: Population abundance and/or biomass, as appropriate (1.2.1)

Sensitivity Relevance to Practicable Applicable Number of CPs Consensus among to specific management reporting/using the CPs on usefulness

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High - High Some existing Yes, should be 7 7 selective monitoring but based on risk extraction of not systematic assessment species across region?

The indicator is regarded as appropriate as it fulfils the following criteria for selecting OSPAR common biodiversity indicators: It is sensitive to a particular human pressure (selective extraction of species), it can be accurately determined; it is specific and simple to measure. The indicator also benefits from being easily communicated to the wider public as the concept of the indicator is easy to understand. Bycatch of chondrythes indicator can be spatially applied and can target high risk fisheries. One of the main reasons why this indicator is proposed as an indicator, is the gap in abundance monitoring of some chondrichthyes such as deepwater and pelagic sharks. This indicator is however a pressure indicator and not a state indicator and there are problems in interpreting this indicator when it is not accompanied by a state indicator.

PARAMETER/METRIC:

Bycatch rate:

The number of individuals or the weight of a species caught per unit effort within a commercial fishery. The indicator should include bycatch of specimen that would either be landed or discarded. The information collected for this indicator should include whether the specimen caught is dead or alive. Fisheries should be grouped by gear or métier such as deepwater longlining, pelagic trawl etc., to assess risk of different sectors.

BASELINE AND REFERENCE LEVEL

Ideally species/stock specific reference levels are calculated which reflect longterm sustainability of the population.

SETTING OF GES BOUNDARIES / TARGETS

The target is to reduce the bycatch rate in cartilaginous fishes. The possibility to develop species specific bycatch targets needs to be further explored.

SPATIAL SCOPE

It is envisaged that a risk approach is applied and that the indicator is implemented in fisheries which pose a high risk to the sustainablility of chondrichthyes populations. The spatial scope will relate to the spatial distribution of high risk fisheries.

MONITORING REQUIREMENTS

This indicator requires a scientific monitoring programmes onboard commercial fishing vessels. There are currently different monitoring programmes in operation based on national and European legislation (such as the DCF and the deepwater access scheme) but it has to be evaluated if they would be adequate to provide data for this indicator.

REPORTING

It still needs to be evaluated whether the reporting obligations and reporting structures under existing European and national legislations are adequate to feed into this indicator. It also needs to be further evaluated, what role certain ICES working groups (such as WGEF and WGBYCATCH) can play in compiling and reporting on national data sets.

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The resource implications for this indicator are estimated to be high, but are primarily met under existing national programmes and the data collection framework. Some monitoring are covered under the DCF and a risk analysis would be necessary to identify if fisheries that are identified as posing a high risk to chondrythes are accompanied by observer programmes which provide adequate spatial and temporal coverage. Reporting, data analysis and development as well as assessment could be carried out within the ICES framework. It is assumed that management measures would relate to fisheries and come under the CFP.

FUTURE STEPS NECESSARY

1. Species selection:

There needs to be an agreement which species should be included in this indicator, ie whether bycatch of all Chondrichthyes should be monitored or whether there should be a selection of species depending on agreed criteria. These criteria could include whether species are listed, species have 0 TACs or other restricted management measures in place. Consideration should be given to extending the bycatch indicator to other vulnerable species, particularly those not covered by other monitoring programmes.

2. Risk assessment and monitoring: A risk analysis needs to be carried out to identify the fishing metiers which pose the highest risk to identified species. There needs to be an evaluation of whether current monitoring programmes and their reporting structures are adequate to cover the relevant fishing sectors or whether increased sampling is required.

3. Target setting:

The method of target setting should be agreed. Species-specific targets and baselines need to be given further consideration.

References:

Dulvy, N.K. and J. D. Reynolds (2002) ,Predicting Extinction Vulnerability in Skates. Conservation Biology Volume: 16, Issue: 2, Pages: 440-450.

EC (43/2009), Council regulation (EC) No 43/2009 of 16 January 2009 fixing for 2009 the fishing opportunities and associated conditions for certain fish stocks and groups of fish stocks, applicable in Community waters and, for Community vessels, in waters where catch limitations are required.

EC (1288/2009), Council regulation (EC) No 1288/2009 of 27 November 2009 establishing transitional technical measures from 1 January 2010 to 30 June 2011.

EC (43/2012), Council regulation (EU) No 43/2012 of 17 January 2012 fixing for 2012 the fishing opportunities available to EU vessels for certain fish stocks and groups of fish stocks which are not subject to international negotiations or agreements.

EC (1225/2010), Council regulation (EU) No 1225/2010 of 13 December 2010 fixing for 2011 and 2012 the fishing opportunities for EU vessels for fish stocks of certain deep-sea fish species

Reynolds, J. D., S. Jennings, and N. K. Dulvy. 2001. Life histories of fishes and population responses to exploitation. Pages 147–168 in J. D. Reynolds, G. M. Mace, K. H. Redford, and J. G. Robinson, editors. Conservation of exploited species. Cambridge University Press, Cambridge, United Kingdom.

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Fig. 1) Distribution of the national groundfish surveys that are part of the ICES International bottom trawl survey (from ICES IBTSWG 2012).

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Benthic Habitats

Code Previous Indicator Category code* BH-1 4 Typical species composition Core

BH-2 7 Multi-metric indices Candidate

BH-3 11a/11b Physical damage of predominant and special habitats Candidate

BH-4 11b Area of habitat loss Candidate

BH-5 12 Size-frequency distribution of bivalve or other sensitive/indicator species Candidate

Typical species composition

1. Indicator

Name: Typical species composition

Code: BH-1

Proposed to BDC 2013 as: Core indicator

State of methodological development:

Development step Defined

Indicator metrics Partially

Ecosystem components attributed (species/habitat types) Partially

Applicability to sub-regions Yes

Assessment scales Partially

Monitoring parameter Partially

Monitoring frequency Partially

The concept of “typical species” (TS) emerges from the Habitats Directive (HD, Dir 92/43/EEC), which in Article 1 relates the conservation status of natural habitats to their long-term natural distribution, structure and functions, as well as the long-term persistence of their typical species within the territory. The assessment of TS is required by the technical guidance of the Commission9, which assumes that typical species should be at a Favourable Conservation Status (FCS) as a condition for their habitat to be in favourable conservation status (FCS). Although the Directive uses the term ‘typical species’ it neither provides a definition of this term, nor gives a list of typical species per habitat type. It is left to member states to define lists of TS and to set targets for their presence.

Typical species composition comprises both macrozoobenthos and macrophytes, depending on the type of habitat (i.e. macrophytes not in deeper aphotic waters). For the latter, various composition-based indicators have been developed for use in the European Water Framework Directive (WFD) e.g. WELLS et al. (2007). Also within this context, two approaches have been used: the use of typical species lists and the distribution

9 Assessment and reporting under Article 17 of the Habitats Directive. Explanatory Notes & Guidelines for the period 2007-2012. ETC on Biological Diversity. April 2011.

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2. Appropriateness of the indicator

Biodiversity component: Benthic Habitats

MSFD criterion: Condition of benthic community (6.2)

MSFD indicator: Proportion of biomass/number of individuals above specified length/ size (6.2.3)

Sensitivity to Relevance to Practicable Applicable Number of CPs Consensus among CPs specific pressures management across region reporting/using on usefulness as part of measures the indicator a region wide set (n=8) (n=9)

High High Yes Yes 8 8

Two different targets are covered under this indicator, which are (1) its implementation as a state condition indicator by using an unweighted list of typical species of the habitat’s communities and (2) its implementation as a specific pressure indicator by including pressure-sensitive species. As this encompasses the use of different methodological approaches, this indicator should be considered as a general concept, covering different specific indicators.

3. Parameter/metric

The selection of the relevant parameter and the development of metrics strongly depend on the selected habitat and its relationship to pressures. It has to be highlighted that the natural variability of species composition in space and time has to be considered when further developing the indicator. As the species composition is the main parameter of this indicator, the use of EUNIS level 3 habitat types is not the appropriate level for further development and later assessment, as the typical species lists need to relate to more specific habitat types (e.g. EUNIS level 5 or 6).

For [unspecific] state condition indicators, a simple species list per habitat forms an appropriate parameter. The species inventories may differ locally even if the habitat is similar (e.g., sandbanks). The list of typical (and possibly character) species has therefore to be defined per habitat type with respect to a particular geographic area (bioregion10); it should be updated every six years. Species included within these lists should contain two aspects:

 state reflection (by listing habitat-typical species of the community)

 pressure reflection (by including species specifically sensitive to the pressures to which the habitat is subjected)

Long-living species and species with high structuring or functional value for the community should preferably be included, but the typical species list can also contain small and short-living species if they characteristically occur in the habitat under natural conditions.

10 See OSPAR Advice Manual biodiversity guidance on use of suitable bioregions within each subregion.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development For the second suggested approach (density, condition or proportion of pressure sensitive species) the same framework requirements (habitat specificity, regional differences) have to be considered. The form of a possible parameter follows indicator “size-frequency distribution” respectively if condition of the population structure is the selected parameter. Density estimations are calculated as numbers (quantitative or semi- quantitative) per surface unit or covered area (in %). In some cases, both the biomass per area and the condition of the population structure considering the size spectrum of the species might be combined in a metric.

4. Baseline and Reference level

For baseline setting (following OSPAR, 2011), the use of method C (current state) might be inappropriate if the habitats actually underlie high human pressure and no reference sites are available. Use of method B (past state) may be most appropriate as the definition of a reference state of North Sea habitats is problematic at best.

5. Setting of GES boundaries / targets

The general target is to reach a ratio of typical and/or character species similar to baseline conditions defined with method B (see above) of all regarded communities.

In case of using habitat specific species lists this might be implemented by setting a certain percentage value to define GES. This cut-off value has to be habitat-specific and regionally adapted in view of the natural variability of species composition by habitat type and bioregion; the list also needs to be adapted to the sampling [effort and] methodology to be used (e.g. video, grab). Therefore, the importance of exact descriptions for the used methodologies to ensure comparability and reproducibility has to be stressed. Also for verification of comparability, biogeographic regions with common species compositions in same habitats have to be identified in advance.

6. Spatial scope

This indicator is applicable in all regions. Typical species lists have to be developed on a sub-regional scale (or bioregion within each subregion) for each biotope.

7. Monitoring requirements

Since this indicator is in part derived from the Habitats Directive, the selection of typical species has been already done by several MS for listed habitat types in order to fulfil the assessment requirements under the HD (e.g. BENSETTITI et al., 2004, KRAUSE et al., 2008, ARMONIES 2010, RACHOR & NEHMER 2004). Additionally, the coastal area out to 1 nautical mile offshore is already covered under the WFD in the EU countries. Therefore, the indicator is available for major parts of certain macrophyte-dominated habitats within these areas and are already covered by monitoring and assessed using appropriate metrics (see e.g. Wells et al. 2007; Indicator “multimetric indicators”). Elsewhere in other extensive broad habitat types in certain regions there may be development work required (e.g. circalittoral reef).

The required methods and effort strongly depend on the habitat type (and selected species) to be addressed. Large attached epibenthic species on hard substrates are preferably monitored using optical, non-destructive methods such as underwater-video. Endobenthic communities are sampled using standardized grabs or corers which are in commonly use in marine monitoring programs. Large mobile species might be caught using dredges or beam-trawls. Sampling design and treatment should be in accordance with international (e.g. ICES) or national guidelines.

8. Reporting

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9. Resources needed

The list of required resources largely overlaps with that of indicators BH-5 and BH-2. It includes:

- Research Vessels, suited to work from sublittoral to bathyal, depending on subregion;

- Adequate equipment (box core samplers, grabs, dredges, underwater camera systems etc) for sample collection from intertidal to bathyal;

- Laboratory infrastructure to analyse samples (e.g. microscopes, scales).

Qualified personnel, in particular experienced taxonomists, are required for both field and lab work to guarantee for quality in sampling accuracy, consistency in the data over time, meaningful data analyses and interpretation of the results

10. Further work

The following steps are essential for operationalization:

1. finalize overview of existing regional or MS projects and species lists and check for consistency within biogeographical regions

2. identify typical and character species for remaining habitats / biogeographical regions, initialize regional projects and re-evaluate species lists in six-year periods

3. identification / definition of baselines for habitats and biogeographical regions

4. clear description of required sampling methodologies and effort

5. definition of GES

6. Identification of indicator groups relevant to specific major broad habitat types where manageable pressures exist.

References

Armonies, W. 2010. Analyse des Vorkommens und der Verbreitung des nach §30 BNatSchG geschützten Biotoptyps “Artenreiche Kies-, Grobsand- und Schillgründe“. 14 pp. + Anhänge.

Bensettiti, F, Bioret, F., Roland, J., Lacoste, J.-P. et al. 2004. Connaissance et gestion des habitats et des espèces d’intérêt communautaire – Tome 2: Habitats côtiers. Cahiers d’ habitats Natura 2000, La Documentation Française ISBN : 2-11-005192-2.

Krause, J., von Drachenfels, O., Ellwanger, G., Farke, H., Fleet, D. M., Gemperlein, J., Heinicke, K., Herrmann, C., Klugkist, H., Lenschow, U., Michalczyk, C., Narberhaus, I., Schröder, E., Stock, M. & Zscheile, K. (2008): Bewertungsschemata für die Meeres- und Küstenlebensraumtypen der FFHRichtlinie - 11er Lebensraumtypen: Meeresgewässer und Gezeitenzonen. http://www.bfn.de/0316_ak_marin.html

OSPAR (2011). Advice document on GES 1, 2, 4 and 6 – Biodiversity (ICG-MSFD(4) 11/2/3 –E). Meeting of the Intersessional Correspondence Group for the Implementation of the Marine Strategy Framework Directive (ICG-MSFD) Madrid: 13-14 December 2011

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Salzwedel, H., Rachor, E., Gerdes, D., 1985. Benthic macrofauna communities in the German Bight. Veröff. Inst: Meeresforsch. Bremerh., 20, 199-267.

Wells, E., Wood, P., Wilkinson, M., Scanlan, C., 2007. The use of macroalgae species richness and composition on intertidal rocky seashores in the assessment of ecological quality under the European Water Framework Directive. Marine Pollution Bulletin, 55, 151-161.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development MULTI-METRIC INDEX (MMI)

1. Indicator

Name: Multi-metric index (MMI)

Code: BH-2

Proposed to BDC 2013 as: Core indicator

State of methodological development:

Development step Defined

Indicator metrics Partly

Ecosystem components attributed (species/habitat types) Benthic Habitats11

Applicability to sub-regions Yes

Assessment scales No

Monitoring parameters Partly

Monitoring frequency Partly

The use of diversity indices (e.g. Shannon-Index, Simpson-Index), species richness indices (e.g. number of species, Margalef d) and of sensitivity/tolerance classification (e.g. AMBI, BQI, ITI) has a long tradition in assessment the quality state of benthic communities. The development of multi-metric indices, combining these indices and classification, was enhanced by the European Water Framework Directive (WFD). Following Annex V of the WFD, multi-metric indices for macrophyte (macroalgae and angiosperms) and benthic invertebrate fauna must consider diversity and abundance as well as the relative proportions of disturbance-sensitive, tolerant and opportunistic taxa. These multi-metrics have been well-developed for macroalgae, angiosperms and soft-bottom macrofauna benthic communities, in all cases restricted to coastal and transitional waters. The currently available MMIs (cf. Annex I) were then mostly developed for WFD purposes and have a strong focus on:

a) transitional water and coastal habitats (both benthic macrofauna and macrophytes)

b) indicating eutrophication, micropollutants and dredging/dumping as key pressures

Most of the MMI indicators currently in place were developed under this focus, have been published in scientific journals, have been approved by the Commission (COM Dec 2008/915/CE) and are already operational in the River-Basin Management plans and the WFD monitoring programs. A second set of new indicators (for example BEQI-2, RICQI and BOPA) are expected to be added to the existing ones when the results of the 2nd intercalibration exercise (finished by December 2012) will be published as a COM Decision for WFD12. Annex I shows a summary description of the existing WFD multi-metric indices.

The generic MMI indicator is explicit in the indicator 6.2.2 of the Commission Decision on GES (2010), and partly implicit in indicators 1.6.1, 1.6.2 and 6.2.1, but further framework development is needed for an MMI generally suitable for MSFD/OSPAR purposes. It should include a necessary flexibility to take into account

11 Currently operational for WFD quality elements macrozoobenthos and coastal angiosperms and macro-algae.

2 The new COM Decision is expected to be approved in the beginnings of 2013.

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The generic MMI indicator design will be differentiated for the three quality elements, which are combined in this indicator document, namely macrozoobenthos (all regions), macrofytes (coastal regions) and macroalgae (coastal regions).

2. Appropriateness of the indicator

Biodiversity component: Benthic habitats

MSFD criterion: 1.6 (habitat condition) and 6.2 (Condition of benthic communities)

MSFD indicator: 6.2.2 (“Multi-metric indexes assessing benthic community condition and functionality, such as species diversity and richness, proportion of opportunistic to sensitive species”)

The assessment of habitat condition by MMI is a basic and integrative tool in benthos ecology. Monitoring methodologies are well developed and widespread used in national monitoring, but still has to be adapted to the special requirements of the MSFD.

In the table below, the proposed MMI is compared with the OSPAR criteria for selecting common biodiversity indicators.

Sensitivity to Relevance to Practicable Applicable Number of CPs Consensus specific pressures management across region reporting/using the among CPs on measures indicator (n=9) usefulness as part of a region wide set (n=8)

+ ? (a) +? + + 8 8 (b)

+? Partially

(a) Sensitivity demonstrated to pollution, eutrophication and dredging/dumping. Still to be further adapted to indicate physical pressures.

(b) Consensus has been achieved under the WFD umbrella. Still to be agreed under the MSFD perspective.

3. Parameter/metric

Several specific MMIs have already been developed and operationalized, in particular to fulfill WFD requirements. They are all well methodologically defined, at least for the monitoring of the basic parameters: species composition and abundances. The way to combine these parameters in diversity indices and sensitivity/tolerance classification is more heterogeneous, depending on the issue (pressure type), habitat types or sub-region. For unspecific condition indicators, a simple species list and respective abundances per habitat forms an appropriate basis of monitoring parameter. It has to be taken into account that species communities may differ locally even if the habitat is similar (e.g. sandbanks). Attention has to be paid to the fact that species lists depend on the expertness of taxonomists in the monitoring teams. Different results could be caused by uneven taxonomic expertise in the teams that could mask the real differences in environmental status. The set-up of the relevant metric also has to be habitat specific and might be (further) developed by each Member State with respect to their (sub-)regional reference values. Overlap with metrics used in the indicator “Typical species composition” should be avoided, although a coherence and optimization should be made for monitoring data (common parameters). Abundances estimates (density) are calculated as numbers (preferably quantitative; or semi-quantitative) per surface unit or covered area (in %).

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Recently, some MMIs have been developed, including alternative component (e.g. foraminifera, Schönfeld et al., 2012) or parameters, according to new technologies. For example, Sediment Profile Images (SPI) provides exclusive in situ views of the sediment-water interface and subsurface sediments (Diaz and Treffy, 2006; Rhoads and Cande 1971). This technique can constitute a useful tool to assess sediment features and the activity of benthic organisms (Nilsson and Rosenberg, 1997), optimized for offshore cohesive sediments. SPI has been successfully used to detect benthic habitat changes (Rumohr and Schomann, 1992), including: organic enrichment (Karakassis et al., 2002; Labrune et al., 2012), benthic hypoxia (Nilsson and Rosenberg, 2000), and physical disturbance (Rosenberg et al., 2003). Other works like testing sensitivity of MMI to fishing impacts have been recently published (Juan and Demestre, 2012). The SPI method will be tested for the pressure monitoring of fisheries and other human pressures on the sea floor. Pressure data are necessary to validate the benthos MMI results.

A first Dutch proposal to be tested under the MSFD perspective is an MMI consisting of three parameters: i) Species richness (number of species per area unit); ii) Species diversity (Shannon index); and iii) a parameter for the proportion of sensitive, tolerant and opportunistic species, the Infaunal Trophic Index (ITI) or the AMBI. See the background document of Van Loon and Heslenfeld (2012) for more details. This proposal will be discussed in the experts group.

4. Baseline and Reference level

For the OSPAR/MSFD MMI, both for benthic macrophyte and macrofauna, the following baseline and target setting methods are recommended (OSPAR’s MSDF Advice Manual on Biodiversity, 2012):

a. Baseline setting: Method A; reference state, with negligible impacts

b. Target setting: Method 3; target set as deviation from the baseline.

5. Setting of GES boundaries / targets

The setting of the relevant quantitative target may vary, depending on the diversity, species richness and sensitive/tolerant/opportunistic species indicators used in each MMI. It has to be highlighted that the natural variability of species composition in space and time has to be considered when further developing the MMI indicator. Further development should include inter-calibration test of the range of values at a (sub-)regional scale, in order to validate a standardized Ecological Quality Ratio (EQR) or equivalent threshold to discriminate the GES/ no GES, including (sub-)regional reference values. The EUNIS habitat classification system will be used as one of the tools for the (sub-)regional habitat classifications for application of the MMI.

6. Spatial scope

The MMI indicator is conceptually applicable in all sub-regions and all type of habitats, and potentially more sensitive to changes due to anthropogenic pressure than the “typical species composition” indicator. Further discussions in the OSPAR benthic habitat expert group and expert consultation are needed to progress on the selection of ecologically relevant habitats for MMI assessments. The (often limited) data availability may restrict the number of habitats which can be assessed with sufficient statistical confidence at present.

7. Monitoring requirements

The spatial and temporal planning of the monitoring (assessment area, sampling locations, sampling and reporting frequencies) depends of MMI metrics, habitat types, exposure to pressure and (sub-)regional

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It is recommended to use the ISO method for marine soft-bottom macrofauna (ISO, 2011) as an advisory document for national benthos monitoring.

8. Reporting

Reporting process depends deeply on the temporal planning of the monitoring, and the temporal planning of the overall assessment itself. At least one reporting every six years should be warranted for all the habitats to which this indicator is applied. The possibility of reporting or assessing with a higher frequency is still to be discussed.

9. Resources needed

A coarse estimation of the resources needed is the following:

- Vessels, suitable to work from sublittoral to bathyal

- Scuba diving sampling to infralittoral

- Adequate equipment (box core samplers, grabs, dredges etc) for sampling collection from intertidal to bathyal

- Laboratory infrastructure to analyse samples

- Qualified personnel to data processing, analysis and interpretation. Taxonomy skills are very determinant

The possibilities of integrating the coastal WFD monitoring into the MSFD monitoring should be further explored, in order to optimize the resources allocation. Nevertheless, it must be acknowledged that the sampling surface covered by WFD is a very low proportion of the total marine waters covered by MSFD (this proportion is different depending on the CP). This means that additional resources are needed to operationalize this indicator. Sediment-profile-imagery could be a cost-effective tool to assess disturbance- impact in large areas.

10. Further work

The following steps are essential for methodological development:

1. Overview of existing regional or national monitoring for the relevant parameters and MMI development projects. Check for consistency and optimization within biogeographical regions.

2. Selection of an essential set of indices for use in the MMI’s for benthos, angiosperms and macro-algae - by the benthic habitats expert group - based on available literature, data and expert judgement.

3. Test the sensitivity of every MMI to every pressure, with special concern to physical pressures.

4. To obtain classifications of species based on response to every pressure. Many indices need this information. Obviously species sensitivity classifications may be different among indicators, pressures and regions.

5. Clear description of required sampling methodologies and effort

Afterwards, the final operationalisation should include:

5. Identification / definition of baselines for the respective habitats and biogeographical regions.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development 6. inter-calibration test of the range of values at a (sub-)regional scale, and validation of a standardized Ecological Quality Ratio (EQR) or equivalent threshold to discriminate the GES/ no GES, including (sub-)regional specificities. It is proposed to construct a common dataset with the contracting parties sharing a same assessment area and methodology, consisting of both benthos data and pressure data. Furthermore, it is proposed to use a common pressure index setup.

7. Target setting. To be performed in the OSAPR benthic habitats expert group and in COBAM.

References: A.R. Boon, A. Gittenberger and W.M.G.M. van Loon, 2011, Review of Marine Benthic Indicators and Metrics for the WFD and design of an optimized BEQI, Deltares, report nr 1203801-000. Bermejo, R., Vergara, J.J. Hernández, I., 2012. Application and reassessment of the reduced species list index for macroalgae to assess the ecological status under the Water Framework Directive in the Atlantic coast of Southern Spain. Ecol. Ind., 12: 46-57. Borja, A., Josefson, A.B., Miles, A., Muxika, I., Olsgard, F., Phillips, G., Rodríguez, J.G., Rygg, B. 2007. An approach to the intercalibration of benthic ecological status assessment in the North Atlantic ecoregion, according to the European Water Framework Directive. c: 42-52. Dauvin, J.C., T. Ruellet (2007) Polychaete/amphipod ratio revisited: Implementation of the Water Framework Directive in European marine waters. Marine Pollution Bulletin, 55(1-6), 215-224. Diaz, R.J., Trefry, J.H., 2006. Comparison of sediment profile image data with profiles of oxygen and Eh from sediment cores. Journal of Marine Systems 62(3-4) 164-172.Helcom 2010. Towards a tool for quantifying anthropogenic pressures and potential impacts on the Baltic Sea marine environment. BSEP 125. Díez, I., M. Bustamante, A. Santolaria, J. Tajadura, N. Muguerza, A. Borja, I. Muxika, J.I. Saiz-Salinas, J.M. Gorostiaga, 2012. Development of a tool for assessing the ecological quality status of intertidal coastal rocky assemblages, within Atlantic Iberian coasts. Ecol. Ind. 12: 58-71. ISO 16665:2011, Water quality - Guidelines for quantitative sampling and sample processing of marine soft-bottom macrofauna Josefson, A.B., Blomqvist, M., Hansen, JLS, Rosenberg, R., Rygg, B. 2009. Assessment of marine benthic quality change in gradients of disturbance: Comparison of different Scandinavian multi-metric indices. Mar. Poll. Bull. 58: 1263–1277 Juan S de, Demestre M (2012). A Trawl Disturbance Indicator to quantify large scale fishing impact on benthic ecosystems. Ecological Indicators, 18, 183-190 Juanes, J.A., Guinda, X., Puente, A., Revilla, J.A. 2008. Macroalgae, a suitable indicator of the ecological status of coastal rocky communities in the NE Atlantic. Ecol. Ind, 8: 351-359 Karakassis I., Tsapakis M., Smith C.J., Rumohr H. (2002). Fish farming impacts in the Mediterranean studied through sediment profiling imagery. Marine Ecology Progress Series 227:125-133. Krause-Jensen, D., Sagert, S., Schubert, H., Boström, Ch. 2008. Empirical relationships linking distribution and abundance of marine vegetation to eutrophication Ecol. Ind. 8: 515-529 Labrune C., Romero-Ramirez A., Amouroux J.M., Duchêne J.C., Desmalades M., Escoubeyrou K., Buscail R., Gremare A. (2012). Comparison of ecological quality indices based on benthic macrofauna and sediment profile images : a case study along an organic enrichment gradient of the Rhône River. Ecological indicators, 12 : 133-142. Muxika, I., Borja, A., Bald, J. 2007. Using historical data, expert judgement and multivariate analysis in assessing reference conditions and benthic ecological status, according to the European Water Framework Directive. Mar. Poll. Bull., 55: 16-29 Neto J.M., Gaspar, R., Pereira, L., Marques, J.C., 2012. Marine Macroalgae Assessment Tool (MarMAT) for intertidal rocky shores. Quality assessment under the scope of the European Water Framework Directive Ecol. Ind 19: 39-47

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Nilsson H.C., Rosenberg R. (1997). Benthic habitat quality assessment of an oxygen stressed fjord by surface and sediment profile images. Journal of Marine Systems 11:249-264. Nilsson H.C., Rosenberg R. (2000). Succession in marine benthic habitats and fauna in response to oxygen deficiency: analysed by sediment profile-imaging and by grab samples. Marine Ecology Progress Series 197:139-149. Rhoads, D.C., Cande S ., 1971. Sediment profile camera for in situ study of organism-sediment relations. Limnol Oceanogr 16:110-114 Rumohr H., Schomann H. (1992). REMOTS sediment profiles around an exploratory drilling rig in the southern North Sea. Marine Ecology Progress Series 91:303-311. Rosenberg R., Nilsson H.C., Grémare A., Amouroux J.M. (2003) Effects of demersal trawling on marine sedimentary habitats analysed by sediment profile imagery. Journal of Experimental Marine Biology and Ecology 285-286: 465-477. Scanlan, C.M., Foden, J., Wells, E., Best, M.A. 2007: The monitoring of opportunistic macroalgal blooms for the water framework directive Marine Poll. Bull., 55: 162-171 Schönfeld J., Alve E., Geslin E., Jorissen F., Korsun S., Spezzaferri S. and FOBIMO (2012) The FOBIMO (FOraminiferal BIo-MOnitoring) initiative—Towards a standardised protocol for soft-bottom benthic foraminiferal monitoring studies Marine Micropaleontology, 94/95 . pp. 1-13. Teixeira, H., Neto, J.M. Patrício, J., Veríssimo, H., Pinto, R., Salas, F., Marques, J.C. 2009. Quality assessment of benthic macroinvertebrates under the scope of WFD using BAT, the Benthic Assessment Tool Marine Poll. Bull., 58: 1477-1486 Van Hoey, G., Drent, J., Ysebaert, T., Herman, P. 2007, The Benthic Ecosystem Quality Index (BEQI), intercalibration and assessment of Dutch coastal and transitional waters for the Water Framework Directive, Final report, NIOO. Van Loon, W., Verschoor, A.J., Gittenberger, A. 2012. Benthic Ecosystem Quality Index 2: Design and Calibration of the BEQI-2 WFD metric for marine benthos in transitional waters. Report, RWS Waterdienst, 35 pp Van Loon, W.M.G.M. and P. Heslenfeld, Proposal for a multi-metric index for OSPAR and MSFD, 2012. Wells, E, Wilkinson, M., Wood, P., Scanlan, C. 2007. The use of macroalgal species richness and composition on intertidal rocky seashores in the assessment of ecological quality under the European Water Framework Directive. Mar Poll Bull 55: 151-161

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development ANNEX I: Summary description of the existing (mostly WFD) multi-metrics indices.

COASTAL MACROALGAE INDICATOR CP APPLYING BRIEF DESCRIPTION AND REFERENCES for WFD RSL IE, UK, NO, ES “Reduced species list” is an indicator that includes 5 components: species richness (from a reduced list of between 68 and 70 species) /proportion of Rhodophyta/ proportion of Chlorophyta/ proportion of opportunistic species/ratio of perennial to annual forms. Wells et al. 2007: Mar. Pollution. Bull. 55: 151–161. Recently adapted to Southern Spain (Bermejo et al, 2012: Ecol. Ind, 12: 46-57) CFR ES “Quality of rocky bottoms”. This indicator includes: percentage cover of characteristic macroalgae/ macroalgae population richness / percentage cover of opportunistic species. (Juanes et al, 2008. Ecol. Ind, 8: 351-359) p-MarMAT PT “Portuguese marine macroalgae assessment tool”. This indicator contemplates all the components of the RSL method, including an additional parameter of % coverage of opportunistic species. Neto et al. 2011, Ecol. Ind: in press. MAB IE, UK, DE “Macroalgae blooming”, which measures 5 components: % cover of algae from the intertidal area / total extent of algal blooms/ biomass of algae/ biomass of algae over the affected bloom area/ presence of entrained algae. Scanlan et al, 2007: Marine Poll. Bull., 55: 162-171 RICQI ES “Rocky Intertidal Community Quality Index”. It includes: ESS: ecological status similarity, PC: presence of Cystoseira; Morphologically Complex Algae; Species Richness and Faunal cover. Díez I., M. et al 2012. Ecol. Ind, 12: 58-71

Subtidal algae NO, SE, DK This indicator incorporates: depth extension of selected perennial macroalgae species / cover of macroalgae along depth gradients / macroalgae composition in rocky littoral and sublittoral zones (based on the integration of multiple parameters). Krause‐Jensen et al, 2008. Ecol. Indicat. 8: 515‐529

COASTAL ANGIOSPERMS INDICATOR CP APPLYING BRIEF DESCRIPTION AND REFERENCES Intertidal Zostera UK, IE, NL Multimetric indicator for Zostera communities. It includes three parameters: 1: DE (only bed Species composition; 2. Seagrass abundance (acreage/bed extent) and 3. extent), FR Seagrass abundance (coverage/density) BENTHIC INVERTEBRATE FAUNA INDICATOR CP APPLYING BRIEF DESCRIPTION AND REFERENCES BEQI BE Benthic ecosystem quality index. Indicators included: density, biomass, species richness, species composition changes (Van Hoeij et al., 2007. Report NIOO/NIOZ). BEQI-2 NL Benthic ecosystem quality index 2. Indicators included: species richness, Shannon index and AMBI; univariate calibration (Van Loon et al., Report, 2011) M-AMBI ES, FR, DE Multimetric-AMBI: Species richness, Shannon diversity, and AMBI, multi-variate calibration (Muxika et al., Marine Poll. Bull., 2007. Mar. Poll. Bull., 55: 16-29). IQI IE, UK Infaunal quality index (IQI) is comprised of three indicators: species richness, Simpson diversity and AMBI (Borja et al., Marine Poll. Bull., 2007) NQI NO Norwegian quality index: includes SN-diversity, total abundance and AMBI (Josefson et al., Marine Poll. Bull., 2009). P-BAT PT Portuguese benthic assessment tool. Indicators included: Margalef species richness, Shannon diversity and AMBI (Teixeira et al., Marine Poll. Bull., 2009). BQI SE Benthic Quality index. Indicators included: species richness and total abundance (Josefson et al., 2009). DKI DK Danish quality index. Indicators included: AMBI, Shannon’s diversity, total abundance and species richness (Josefson et al., Marine Poll. Bull., 2009). BOPA ES Benthic Opportunistic Annelida Amphipoda Index /Benthic Opportunistic Polychaete Amphipoda Index. It uses the ratio between opportunistic polychaete and amphipods frequencies. Dauvin, J.C., T. Ruellet, 2007. Mar. Pollut. Bull, 55(1-6), 215-224. BHQ SE Benthic Habitat Quality index. Used in analyze of sediment profile image. Tested against organic enrichment, oxygen deficiency, physical disturbance (e.g. trawl fishery). Nilsson H.C. and Rosenberg R., 1997. Marine System, 11, 249-264.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development

Physical13 damage of predominant and special habitats

1. Indicator

Name: Physical damage of predominant and special habitats

Code: BH-3 (11a/11b)

Proposed to BDC 2013 as: Candidate indicator

State of methodological development:

Development step Defined

Indicator metrics Partially

Ecosystem components attributed (species/predominant or special habitat types) Partially

Applicability to sub-regions Yes

Assessment scales No

Monitoring parameter Partially

Monitoring frequency No

This indicator aims to address those pressures which cause physical damage to seafloor habitats in the OSPAR area. It is being designed to assess predominant as well as special habitat types and is regarded as particularly useful to target larger sea areas with relatively low effort. The indicator will build upon two types of information, i) the distribution and sensitivity of habitats and ii) the distribution and intensity of human activities that potentially cause physical damage, such as mobile bottom gear fisheries, sediment extraction and offshore constructions.

Although the proposed approach is mainly focused on physical pressures, habitat damage caused by other pressures such as eutrophication, hazardous substances etc, could also be accommodated within this approach, as long as information on habitat sensitivities and pressures information are available. In order to provide an overall assessment of habitat damage the indicator will ultimately need to accommodate all significant pressures operating over the habitats under assessment.

There are three potential options for the analysis of this information (with an alternative to combine or partially combine these three options): i) sampling and assessment in representative areas with subsequent extrapolation; ii) an impact modeling approach that is under development; and iii) a vulnerability assessment approach, also under development. The pressure data is principally available from EIAs and ongoing environmental monitoring for approved plans and projects and from VMS and logbooks for bottom fisheries.

In principle, any habitat type may be assessed on the basis of this indicator through the processing of spatial pressure data.

2. Appropriateness of the indicator

Biodiversity component: Benthic habitats

13 The current proposal is mainly focused around physical damage. However, the approach could be adapted to included a wider range of pressures such as eutrophication

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development MSFD criterion: 1.6 (habitat condition) and 6.1 (Physical damage, having regard to substrate characteristics)

MSFD indicator: 6.1.1 Condition of the typical species and communities;1.6.3 Physical, hydrological and chemical conditions and 6.1.2 Extent of the seabed significantly affected by human activities for the different substrate types

Number of CPs Consensus among Number of CPs Consensus Number of CPs Consensus reporting/using CPs on usefulness reporting/using among CPs on reporting/using the among CPs on the indicator (n=9) as part of a region the indicator usefulness as indicator (n=9) usefulness as part wide set (n=8) (n=9) part of a region of a region wide wide set (n=8) set (n=8)

High* High Yes** Yes 8 8

*mainly for physical damage, but maybe for others too, e.g. eutrophication.

**additional monitoring will be needed in particular for predominant habitats. Potential costs around validation and testing of approach.

Under the MSFD (Annex III, table 1), the habitat types fall into two groups: ‘special habitat types’ and ‘predominant habitat types’. Predominant habitat types, generally defined by abiotic characteristics, are widely occurring and broadly-defined habitat types (e.g. shelf sublittoral sand or mud) that are typically not covered by other legislation. In general, each predominant habitat type includes various biological communities, and in some cases also includes special habitats. The ‘special’ habitats refer to those listed by the EC Habitats Directive, and those on the OSPAR list of threatened and/or declining species and habitats and other international convention lists.

The most important pressures to consider for the majority of benthic habitat types in the OSPAR area are physical pressures arising from a variety of human activities e.g. fisheries, sediment extraction, offshore and coastal constructions and dumping. This indicator is particularly relevant for GES-Descriptor 6, which is defined as “sea-floor integrity at a level that ensures that the structure and functions of the ecosystems are safeguarded and benthic ecosystems, in particular, are not adversely affected”, i.e. human pressures on the seabed may not hinder the ecosystem components to retain their natural diversity, productivity and dynamic ecological processes, having regard to ecosystem resilience. Outputs from this indicator are also needed to assess the criterion 1.6 habitat condition from Descriptor 1 ”Biological Diversity”, in particular to capture habitat damage caused by other pressures such eutrophication and hazardous substances.

The indicator proposed here is an area-related indicator closely linked to condition elements. There are three potential options (with an alternative to combine or partially combine these three options), to undertake this condition assessment:

i. the use of selected condition indicators with any sampling and assessment to take place in a restricted number of stations in representative areas with subsequent extrapolation up to a larger area of the same habitat type (presumably experiencing the same pressures);

ii. modelling the impact by using sensitivity maps in combination with the spatial data of pressure intensities (with appropriate ground truthing);

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development iii. the use of a vulnerability assessment to evaluate the area of habitat being damaged by anthropogenic activity using a combination of sensitivty assessments and exposure to pressures using a semi-automated GIS approach.

The vulnerability assessment approach will be mainly based on indirect evidence, although, subject to availability, the assessment of damage should be supported and validated by direct evidence to calibrate the approach and improve the confidence of the results.

The key term of this indicator is damage (=temporary and/or reversible change of a habitat due to pressures). For further terminology please refer to the OSPAR MSFD Advice Manual on Biodiversity (OSPAR 2011a) or the Annex of the WG GES Common understanding document14.

This indicator is, in principle, applicable to all kinds of predominant and special habitat types across the North-East Atlantic region and it is considered to be highly sensitive to physical pressures. Consequently there is a clear link to considering activities causing physical pressures, such as mobile bottom gear fisheries, in the establishment of management measures.

This indicator primarily corresponds to criterion 6.1 (indicator 6.1.2) of the EU COM decision. Since it will be largely built on the modeling of available spatial pressure data, it is deemed to be highly cost efficient and will require only minimal monitoring activities in the field. There is a high degree of consensus between OSPAR contracting parties on the necessity of this indicator.

3. Parameter/metric

The parameter/metric of this indicator is the surface area of damaged habitat. The mapping of abiotic (e.g. sediment, depth range) and biotic parameters (abundance and/or biomass of macrozoobenthos) at the required scale and resolution, in particular in terms of habitat classification (EUNIS level) would be necessary to assess damaged areas of predominant and special habitats. EUNIS level 3 maps are already available in EUSeaMap and MESH Atlantic. Direct evidence from sampling is expensive and not always practical and should therefore be regarded as supplementary in most areas. The requirements for direct evidence should be linked to the confidence in the assessments and the requirements to validate initial results. For the assessment of predominant habitat types, by definition the more widespread habitat types of the seabed, it is therefore suggested to use cumulative impact data derived from our knowledge of the pressures arising from human activities as a main framework for the assessment of habitat extent and quality. This can assessed using a vulnerability assessment approach combining the information and data from sensitivity assessments and pressure information. Sensitivity is defined as the degree to which a species or habitat responds to a particular pressure, taking into consideration the resistance (tolerance) of a habitat or species to a pressure and the time it would take to recover (resilience) (Tillin et al, 2010). A habitat is considered to be vulnerable when it is exposed to a pressure (from human activity) to which it is sensitive. The degree to which the feature is vulnerable is dependent on the degree of sensitivity and the level of exposure to the pressure (Tyler-Walters, 2001; Tillin et al, 2010). When the intensity of the pressure causes sufficient change in the condition of the habitat and its community (which can be determined by use of the condition indicators) the habitat can be said to be impacted (damaged).

Any data relating to habitat damage arising from projects requiring licensing procedures, EIAs and ongoing environmental monitoring (e.g. wind farm constructions, sediment extraction), should be readily available to CPs. For habitat damage caused by other activities, including fishing, a range of activity data sources are also available, including VMS and logbook data from fishing vessels using mobile bottom fishing gears. The

14 See latest version at https://circabc.europa.eu/faces/jsp/extension/wai/navigation/container.jsp

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development sensitivity assessment could be done using a sensitivity matrix which contains information on habitat sensitivities assessed in relation to a multitude of pressure intensities or benchmarks, such as developed by Tillin et al (2010).

In general terms, the following steps should be included as part of the indicator’s assessment process:

i. Generate maps of predominant marine habitats in each CP’s sea area(s) at the relevant Eunis level

ii. Overlap with spatial and temporal pressure intensity data (e.g. VMS data for fisheries, activity data from approved plans and projects)

iii. Deduce impacts from either

a. known pressure/impact relationships, using reference sites and risk-based monitoring of selected stations (linked to condition indicators)

b. impact models (such as in Schröder et al. 2008)

c. a vulnerability assessment approach

iv. Determine whether the threshold value has been reached (proportion of lost or damaged area, related to total area of the habitat, beyond which GES is no longer reached).

For the vulnerability assessment approach, the process for the combination and analysis of all data layers and information could be undertaken using a semi-automated GIS approach similar to the approach developed for the assessment of the structure and functions parameter for Annex I Reef and Annex I Sandbanks in offshore waters under the reporting for Habitats Directive Article 17 (JNCC report).

4. Baseline and Reference level

For each habitat type a baseline of the area and degree of damage has to be determined, as well as the natural extent of the habitat type. The preliminary target described below will need to be reconsidered when baselines are elaborated.

From the baseline setting method recommended in OSPAR’s MSFD Advice Manual on Biodiversity (OSPAR, 2011a), option 1 (reference state) is recommended as the preferred approach to setting baselines for benthic habitats. To establish a baseline for this indicator, it is expected that information on the natural extent of the habitat (based for example on historical data) and the current extent of damage (based on modeling or direct evidence or combination of both) will be needed. Information from the area of habitat loss is also relevant to inform the baselines for this indicator. Where possible, information could be gathered using historical maps/data, including current extent of permanent constructions and modified habitats, and/or using information from undisturbed states within some Marine Protected Areas or areas with a very low level of disturbance. The work undertaken by Hill et al. (2012) provides recommendations on methods for determining reference conditions for benthic marine habitats of the North-East Atlantic which are relevant for this work. If the determination of reference state is not possible, then expert judgement should be used giving particular consideration to the current state.

The approach for developing baselines should be applicable to all habitat types if possible as the methodologies will have to be standardized.

5. Setting of GES boundaries / targets

Further discussion will be needed to ascertain the targets / GES boundaries applicable to this indicator. It is recommended that the target should be a deviation from a specified given baseline as defined in the common implementation strategy guidance (European Commission, 2012) This indicator is closely linked to

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development the area of habitat loss indicator. Therefore the GES boundary for habitat damage could take into account the proportion of area already lost for a particular habitat by decreasing the targets of allowed damage.

Quantitative or qualitative targets based on the options above will require further discussion amongst experts and at a policy level. A proposal was put forward by the experts of the Amsterdam OSPAR workshop, which suggested setting a target of 15% of the baseline value (OSPAR 2011b). This target level was similarly proposed by HELCOM and is originally derived from the OSPAR ‘Texel-Faial’ criteria. For special habitats a target of 5% or less was recommended by experts at a previous workshop in Hambugh. Under the Habitats Directive if more than 25% of the extent of the habitat is damaged (specific structures and functions including typical species) it is classed as ‘Unfavourable-Bad’. However, further discussions will be needed to consider the feasibility and application of a percentage as a target value, in particular regarding assessment scales and the aggregation of the information. Moreover, a set percentage criteria might not be applicable to all habitat types or geographical scales.

Additionally, a careful consideration of the level of resolution of the assessment and consideration of habitats of specific importance within predominant habitats (such as spawning or feeding grounds for mobile species) is recommended when applying, further developing or revising this indicator.

6. Spatial scope

This indicator is applicable to all sub-regions and habitat types. The scale and resolution of the indicator and the aggregation of results for assessments will require further discussion. If the target is applied to a bioregion (e.g. one of the five areas in the North Sea), each CP could undertake its own assessments to inform the contribution to the bioregional target.

7. Monitoring requirements

This indicator is currently under development. Some data collection will be necessary under option i in order to undertake sampling and assessment in a restricted number of stations for further analysis and extrapolation to a larger area. For options ii and iii, the data for this indicator could be mainly derived from activity data sources such as EIAs and VMS data. Additional information may be gathered from the Data Collection Framework (DCF) which may also be relevant for this indicator. A risk-based approach should be applied for any additional monitoring effort to collect data on physical damage.

It is envisaged that some data collection and analysis for the testing and validation of this indicator could be required, in particular to improve the confidence of the approach. Some of the proposals for integrated monitoring programmes under WKECES 2012 which aim to provide wider ecosystem information using ecosystem surveys fundamentally based on fisheries observations, could be useful to validate some of the outputs from this indicator, and/or to collect data to improve the sensitivity and vulnerability information.

8. Reporting

(to be developed)

9. Resources needed

As this indicator is largely dependent on pressure data that is, in principle already available, rather than on practical sampling and direct state assessments, the costs are foreseen to be low, although further data collection to improve our knowledge of location and extent of habitats, sensitivity information and pressures will be necessary to refine and update the methodology and increase confidence in outputs.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development It is envisaged that most of the costs will be associated with the manipulation and analysis of data. Existing monitoring programmes could capture relevant data and existing data collection networks such as DCF should be useful to provide information.

Further cost considerations will be taken when the conceptual development is matured.

10. Further work

In principle, the indicator “Physical damage of predominant and special habitats” is highly recommended to be taken further. Furthermore, at the Hamburg workshop, the benthic habitats expert group emphasized the strong potential of this indicator and ranked it highest among the list of indicators to be submitted and developed as part of the list of OSPAR core indicators. However, an exact methodology and an appropriate assessment scale needs yet to be identified.

The following main steps are necessary for operationalization (please note that some steps might not be needed if a vulnerability approach is used):

i. define damage (e.g. in difference to disturbance and considering natural variability)

ii. define vulnerability/resilience for all predominant and special habitat types, taking into account their different communities, in relation to physical pressures and other pressures

iii. select a condition indicator/index which reacts sensitively to physical pressures to be used for the assessment of vulnerability

iv. define the linkage between habitat area and condition of its community e.g. either using condition indicators resulting from a sampling of representative sub-areas and/or by modelling the impact by using sensitivity maps

v. agree on a simple and pragmatic model for the use of a sensitivity matrix for analysing generalized pressure/impact relations for the wider predominant habitat types and define qualitative GES on the basis of these results

vi. identify quality baselines for physical damage using reference areas where possible

vii. identify area baselines for each predominant habitat type (historical characteristics are probably only applicable for offshore habitat types)

viii. further develop criteria for the risk based approach to monitoring and develop harmonized sampling instructions

ix. determine the appropriate assessment scales in detail, e.g. by taking into account predominant habitats on EUNIS level 5 or 6. If necessary these data can later be aggregated to EUNIS level 3 for reporting;

x. develop standardized data flows for spatial pressure data

To further develop this indicator, as a first step, a workshop focusing on the definition and the assessment of vulnerability/sensitivity of habitats and to identify appropriate spatial pressure/impact models should be initiated.

References:

European Commission. 2012. Guidance for 2012 reporting under the Marine Strategy Framework Directive, using the MSFD database tool. Version 1.0. DG Environment, Brussels. pp164.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development JNCC report: Method for assessing the structures and functions parameter of Favourable Conservation Status for Annex I Reefs and Sandbanks in UK offshore waters (in prep)

Hill, J.M., Earnshaw, S., Burke, C. and Gallyot,J., 2012. Reviewing and Recommending Methods for Determining Reference Conditions for Marine Benthic Habitats in the North-East Atlantic Region, JNCC Report 464, ISBN 0963 8091

OSPAR 2011a: Advice document on GES 1, 2, 4 and 6 – Biodiversity (ICG-MSFD(4) 11/2/3 –E). Meeting of the Intersessional Correspondence Group for the Implementation of the Marine Strategy Framework Directive (ICG-MSFD) Madrid: 13-14 December 2011

OSPAR 2011b: Report of the OSPAR workshop on MSFD biodiversity descriptors: comparison of targets and associated indicators („Amsterdam workshop“).

Schröder A., Gutow L, Gusky M (2008) FishPact - Auswirkungen von Grundschleppnetzfischereien sowie von Sand- und Kiesabbauvorhaben auf die Meeresbodenstruktur und das Benthos in den Schutzgebieten der deutschen AWZ der Nordsee. Report to BfN: http://www.bfn.de/habitatmare/de/downloads/berichte/Auswirkungen_von_Grundschleppnetzfischerei.p df

Tillin, H.M., Hull, S.C. and Tyler-Walters, H. (2010). Development of a sensitivity matrix (pressures- MCZ/MPA features). Report to the Department of Environment, Food and Rural Affairs from ABPMer, Southampton and the Marine Life Information Network (MarLIN) Plymouth: Marine Biological Association of the UK. Defra Contract No. MB0102 Task 3A, Report No. 22.

Tyler-Walters, H., Hiscock, K., Lear, D.B. and Jackson, A. (2001). Identifying species and ecosystem sensitivities. Report to the Department for Environment, Food and Rural Affairs from the Marine Life Information Network (MarLIN), Marine Biological Association of the united Kingdom, Plymouth. Contract CW0826 [Final Report].

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Area of Habitat Loss

1. Indicator

Name: Area of Habitat Loss (predominant and special habitat types)

Code: BH-4 (11b/3a)

Proposed to BDC 2013 as: Candidate indicator

State of methodological development:

Development step Defined

Indicator metrics Partially

Ecosystem components attributed (species/habitat types) Partially

Applicability to sub-regions Yes

Assessment scales Partially

Monitoring parameter Partially

Monitoring frequency No

The proposed indicator assesses the proportion of the area of habitats that are permanently or for a long- lasting period lost due to anthropogenic pressures. In principle, any habitat type may be assessed on the basis of this indicator through the processing of spatial construction and other pressure data and the compilation of modeled habitat, interpolated habitat or directly measured habitat extent. The MSFD GES criterion linked to this indicator is habitat extent, as measured by the area of seabed covered by each of the habitat types.

2. Appropriateness of the indicator

Biodiversity component: Benthic habitats

MSFD criterion: 1.5 (habitat extent) and 6.1 (Physical damage, having regard to substrate characteristics)

MSFD indicator: 1.5.1 (habitat area) and 6.1.2 (Extent of the seabed significantly affected by human activities for the different substrate types)

Sensitivity to Relevance to Practicable Applicable Number of CPs Consensus among CPs specific pressures management across region reporting/using the on usefulness as part of measures indicator (n=9) a region wide set (n=8)

High* High Yes** Yes 8 8

*mainly for sealing by offshore and coastal constructions, sediment extraction, dumping, but maybe for others too, e.g. demersal fisheries causing physical damage to complex habitats.

**additional monitoring will be needed in particular for predominant habitats. Potential costs around validation and testing of approach. Habitats Directive monitoring should cover most monitoring needs for special habitats but some additional monitoring may be needed for OSPAR priortity marine habitats that are not otherwise covered.

Under the MSFD (Annex III, table 1), the habitat types fall into two groups: ‘special habitat types’ and ‘predominant habitat types’. Predominant habitat types are generally defined by abiotic characteristics, are

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development widely occurring and broadly defined (e.g. shelf sublittoral sand or mud) and are typically not covered by other legislation. In general, each predominant habitat includes various biological communities, and in some cases also includes special habitats. The ‘special’ habitats refer, at least, to those listed by the EC Habitats Directive and the OSPAR list of threatened and/or declining species and habitats. For some of these special habitats, it is more appropriate to measure their extent directly because of high risk to their status coupled with low resolution or absent pressure data which precludes a model/mapping assessment.

Listed habitat types according to the EU Habitat Directive (Annex I):

1110 Sandbanks which are slightly covered by sea water all the time, 1120 Posidonia beds, [1130 Estuaries], 1140 Mudflats and sandflats not covered by seawater at low tide 1150 Coastal lagoons 1160 Large shallow inlets and bays, 1170 Reefs, 1180 Submarine structures made by leaking gases

OSPAR habitat types (list of threatened and/or declining species and habitats):

Carbonate mounds Coral Gardens Cymodocea meadows Deep-sea sponge aggregations Intertidal Mytilus edulis beds on mixed and sandy sediments Intertidal mudflats Littoral chalk communities Lophelia pertusa reefs Maerl beds Modiolus modiolus (horse mussel) beds Oceanic ridges with hydrothermal vents/fields Ostrea edulis beds Sabellaria spinulosa reefs Seamounts Sea-pen and burrowing megafauna communities Zostera beds Special habitats are described according to their main abiotic and/or biological characteristics. “Sea-pen and burrowing megafauna communities”, for example, are defined by their biological characteristics coupled with their soft mud substrate. “Reefs”, however, may either be of abiotic rock or of biogenic origin (e.g. Mytilus spp., Modiolus sp., Sabellaria spp.) and saline lagoons are entirely physiographic features. Some of these differences result in different sensitivities of special habitats to changes in their extent (area).

The indicator is in principle applicable to all kinds of predominant and special habitat types across the North- East Atlantic region and it is considered to be highly sensitive to physical pressures. In most cases (2 below) the indicator will be largely built on the modelling of habitats and available construction footprint and spatial pressure data; this is cost efficient because it minimises monitoring activities in the field.

In special habitats which are defined by long-lived habitat-bio-engineering species, such as reefs of the cold- water coral (Lophelia pertusa) or horse mussels (Modiolus modiolus), changes in the extent of the habitat are likely to be due to anthropogenic physical influences such as bottom-trawl fisheries, (OSPAR 2010;

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Roberts et al., 2000; Lindenbaum et al. 2008; Strain et al. 2012). Loss of extent of habitat is of most concern for these biogenically-defined habitats (including others such as seagrass beds; Godet et al., 2008; 2009) and typically less of an issue for physically-defined special habitats such as rock reef or large shallow inlets and bays, because these are typically less spatially sensitive and have a greater natural extent. A regional risk-based approach should seek to prioritise those listed habitats that need active, regular monitoring programmes to collect the necessary additional data to that derived from desk-based studies. Nevertheless all listed and predominant habitat types need to be assessed.

The key term of this indicator is loss (= permanent loss or change of habitat-type due to pressures). In order to assess the area of loss, information on the actual area of these habitats is also needed, analogous to the area parameter of the Habitats Directive Art. 17 reporting requirements (special habitats). For further terminology refer to the OSPAR advice document (OSPAR 2011a) or the Annex of the WG GES Common understanding document (Ref?).

This indicator is an area related indicator, closely linked to condition elements i.e. if a habitat condition is sufficiently poor and irrecoverable, it is lost. There are three options for this assessment identified:

(1) the use of condition indicators and a representative sampling and assessment in a restricted number of areas with subsequent extrapolation into the larger area (predominant and certain special habitats15)

(2) modelling habitats and mapping against impacts using sensitivity maps in combination with construction footprint data and spatial pressure intensity data. It may also be possible to combine options 1 & 2.

(3) Direct monitoring of particular (special and also threatened16) habitats

3. Parameter/metric

The parameter/metric is the surface area of lost predominant or special habitat. This is based on the mapping of abiotic parameters (e.g. sediment, depth range) for predominant habitats and also biotic parameters (key species, habitat-forming species, communities) for higher level special habitats. It is suggested to largely use cumulative impact data derived from knowledge of construction and other anthropogenic pressures. As most human activities causing habitat loss are projects requiring licensing procedures and EIAs (e.g. wind farm constructions, sediment extraction) the data should be available to MSs. Also for habitat damage caused by other activities, including fishing, a range of activity data is available, including VMS for larger fishing vessels that undertake bottom trawling. On the basis of these data it should then be decided on a case by case basis, applying a risk based approach, where to focus monitoring/sampling efforts to validate (2 above), extrapolate (1 above) or measure (3 above) habitat area.

Mapping of habitats in targeted areas of a subregion (e.g. North Sea) is the basis of this indicator. Consistent scales and methods will be necessary for mapping a given ‘special habitat’ in a subregion. The time of sampling should be synchronised for a subregion so as to standardize the influence of seasonal, interannual or climate-related changes on results (e.g. Kröncke et al. 2011, Kröncke, 2011).

In general terms, the following steps should be part of the indicator’s assessment:

1. Generate maps of predominant marine habitats (EUNIS level 3) in each MS’s marine areas

2. Generate maps of special habitats in each MS’s marine areas

15 Often ‘geographic’ special habitats like ‘large shallow inlets and bays’

16 Often biogenic habitats

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development 3. Attribute a specific sensitivity/vulnerability to physical pressures to each habitat

4. Collate construction footprint data for sealed habitats and apply spatial and temporal pressure intensity data (e.g. VMS data for fisheries, activity data from approved plans and projects)

5. If vulnerabilities are addressed in 1-4, deduce impacts from either

a. known pressure/impact relationships, using reference sites and risk based monitoring of selected stations (link to condition indicators)

b. mapping construction footprints and impact models (with ground truthing)

6. If vulnerabilities are not addressed in 1-4 (as may be the case for certain special habitats) derive measures of habitat extent (in keeping with Habitats Directive requirements)

7. Determine whether the target is reached (proportion of lost or damaged area, related to total area of a predominant habitat, above which GES is not achieved).

Since “special habitats” include rare habitat types, the investigation method must be chosen carefully. Non- invasive surveys (e.g. side scan sonar, video) or models (to be validated by optimized sampling) may be necessary to select the most appropriate sampling strategy. Intervals of 3-6 years are probably appropriate.

4. Baseline and Reference level

From the baseline setting method recommended in OSPAR’s MSFD Advice Manual on Biodiversity (OSPAR, 2011a), option 1 (reference condition/reference state) is recommended as the preferred approach to setting baselines for benthic habitats. Where possible, the reference conditions should be determined e.g. using historical maps/data, modelling results (and maybe important for some special habitats that have historically declined. The work undertaken by Hill et al. (2012) provides recommendations on methods for determining reference conditions for benthic marine habitats of the North-East Atlantic which are relevant for this work. If the determination of reference conditions is not possible, then expert judgement should be used giving particular consideration to the current state.

5. Setting of GES boundaries / targets

As a target value, the experts of the Amsterdam OSPAR workshop advised that the damaged or lost area per habitat, (predominant habitats) should be below GES (i.e. unacceptable impact / loss / unsustainable use), as defined by condition and extent indicators and it must not exceed 15% of the baseline value. This target level was similarly proposed by HELCOM and is originally derived from the OSPAR ‘Texel-Faial’ criteria. For special habitats the OSPAR ICG-MSFD Workshop (Amsterdam, November 2011): “Stable or increasing and not smaller than baseline value”. This target is derived from the EU guidance for the assessment of conservation status under the Habitats Directive where a 5% tolerance has generally been adopted by MSs to represent ‘stable’. However, in some cases a more stringent <1% tolerance has been attached to the maintenance of habitat extent.

The Hamburg workshop of the benthic habitats expert team discussed the percentage target intensively. Even though a majority was in favour of a quantitative target, there was concern by several experts that targets were unacceptably high. It must therefore be explored if a lower value is appropriate. This could possibly be done by interfacing the areas of constructions/coastal defence, etc. with e.g. the EUSeaMap (aggregated to the predominant habitat types).

Coastal habitats are likely to be most altered/ sealed already whereas offshore habitats have currently only very small areas built on. It should therefore be considered whether to set targets for different habitat groups.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development The definition of baselines interacts with targets for this indicator - e.g. in cases where 15 % loss has already occurred due to land claims in the past the baseline could be set at a current state or historic and this, coupled with the ambition of the target would determine whether GES is achieved.

For some special habitats that have historically been reduced the target should be that the area increases towards the size of the baseline (i.e. towards reference conditions), within a certain time interval, recognising that recolonisation of formerly occupied areas may not occur due to changes in environmental or climatic conditions.

Consideration of specific habitats of importance within predominant habitats (such as spawning or feeding grounds for mobile species) is recommended when applying/further developing or revising this indicator.

6. Spatial scope

The reference region should follow the OSPAR guidance manual which splits the subregion according to biogeographic subareas as a basis for assessment e.g. subdivisions of the North Sea (OSPAR 2011). This will reflect changes in biological character of each habitat type across the NE Atlantic and its subregions.

Each contracting party should assess each predominant habitat across their national maritime waters. However, it is recommended to assess on a smaller scale if they belong to different biogeographical sub- regions or differences in pressure intensity are obvious between sub-basins.

7. Monitoring requirements

The indicator is currently under development. The data for this indicator should mainly be derived from activity data sources such as EIAs and VMS data. A risk-based approach will identify additional monitoring effort required for certain habitat types and keep the monitoring effort cost effective. Currently we are not aware of any regular European monitoring programme measuring predominant habitats.

Sediment and macrozoobenthos mappings from benthos monitoring programmes in several contracting parties (e.g. DAAN & MULDER 2005) represent good approaches for estimating the location and size of predominant habitats from which to extrapolate. Elsewhere modelled benthic maps now exist (EUSeaMap and MESH) as an accurate starting point.

The effort and/or expense of a full monitoring programme (including condition parameters) for special habitat types can be assessed as moderate to high depending on the number and area of the listed habitats. The use of non-invasive methods or models may reduce the effort and/or expense on a long-term basis but these cannot comprehensively address extent and condition parameters.

An approach using historic habitat and activity data to assess the risk of loss/damage will focuss active sampling/monitoring on high risk areas. Measuring the extent of many high-risk special habitats, for example, has required targeted survey using hydroacoustics, drop down video or ground-truthed aerial imagery in specific areas with high resolution (e.g. Lindenbaum et al., 2008; Roberts et al. 2000; Godet et al. 2008; 2009). Some MSs have implemented a comprehensive monitoring programme for the Habitats Directive reporting (e.g. Germany) but comprehensive coverage was not available for all OSPAR MSs and would be expensive for those MSs with extensive national resources. Current monitoring will be reconsidered soon by Member States under the MSFD Art. 11 and OSPAR will take a coordinating role for the North-east Atlantic region.

The required methods and effort strongly depend on the specific habitat and selected species. Large attached epibenthic species on hard substrates are preferably monitored using optical, non-destructive methods such as underwater-video. Infaunal communities are sampled using standardized grabs or corers

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development commonly used in marine monitoring-programs. Sampling design and treatment should be in accordance with international or national guidelines.

8. Reporting

(to be developed)

9. Resources needed

A large part of this indicator is dependent on pressure data that is – in principle – already available, rather than on practical sampling and direct state assessments, the costs for monitoring low risk (predominant and certain special) habitats is foreseen to be relatively low. It is envisaged that further data collection on habitat extent and mapping will be needed.

Monitoring special habitats at risk is expected to be largely covered under ongoing Habitats Directive and OSPAR initiatives. However, since these have not been intercalibrated to the extent of, for example, WFD, there may be additional special habitat monitoring required to achieve consistency across MSs for MSFD.

Further cost considerations emerge as the conceptual development for this indicator matures.

10. Further work

In principle, the indicator “Area of habitat loss” is highly recommended to be taken further. Also the Hamburg workshop of the benthic habitats expert group emphasized the strong potential of this indicator and ranked it highest among the list of indicators to be submitted and developed as OSPAR core indicators. However, an exact methodology and an appropriate assessment scale has yet to be identified.

The following main steps are necessary for operationalization:

1. define vulnerability/resilience for all predominant and special habitat types, taking into account their different communities, in relation to physical pressures

2. agree on a simple and pragmatic model for analysing generalized pressure/impact relations for the wider predominant habitat types and define qualitative GES on the basis of these results

3. identify area baselines for each predominant and special habitat type. Location and extent of special habitats will need to consider historic records using OSPAR habitat distribution data as foundation

4. further develop criteria for the risk based approach to monitoring and develop harmonized sampling instructions where appropriate

5. Development of common computing methodologies, sampling concepts and mapping instructions for the subregion, specifying the accuracy (spatial resolution or grid) of the determination of area a priori;

6. determine the appropriate assessment scales in detail, e.g. by taking into account predominant habitats on EUNIS level 5 or 6. If necessary these data can later be aggregated to EUNIS level 3 for reporting;

7. develop standardized data flows for spatial pressure data

8. Further development of assessment categories and GES boundaries, including consideration of current boundaries used for Habitats Directive reporting, WFD Hydromorphology Tool and OSPAR listing. Rephrasing of target as to cover the mentioned group 1 and 2 habitat types.

9. Research GES baselines for habitats types that cannot be inferred from contemporary records of pressure or construction (environmental envelope analysis etc)

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development 10. Agree harmonised sampling, cartographic, data collation and GIS protocols.

References:

COUNCIL Of EUROPEAN COMMUNITIES (1992) COUNCIL DIRECTIVE 92/43/EEC on the conservation of natural habitats and of wild fauna and flora.

Daan, N. & M. Mulder (2005) The macrobenthic fauna in the Dutch sector of the North Sea in 2004 and a comparison with previous data. - NIOZ-rapports 2005-3.

Godet L., Fournier J., Van Katwijk M., Olivier F., Retière C. & Le Mao P., 2008. Before and after wasting disease in common eelgrass Zostera marina along the French Atlantic coasts: a general overview and first accurate mapping. Diseases of Aquatic Organisms 79: 249–255

Godet, L., Fournier, J., Toupoint, N., Olivier, F., 2009. Mapping and monitoring intertidal benthic habitats: a review of techniques and a proposal for a new visual methodology for the European coasts. Progress in Physical Geography 33 (3), 378–402

Kröncke, I. (2011) Changes in Dogger Bank macrofauna communities in the 20th century caused by fishing and climate. - Estuar. Coastal Shelf Sci. 94: 234-245.

Kröncke, I., H. Reiss, J. D. Eggleton, J. Aldridge, M. J. N. Bergman, S. Cochrane, J. A. Craeymeersch, S. Degraer, N. Desroy, J.-M. Dewarumez, G. C. A. Duineveld, K. Essink, Hillewaert, M. S. S. Lavaleye, A. Moll, S. Nehring, R. Newell, E. Oug, T. Pohlmann, E. Rachor, M. Robertson, H. Rumohr, M. Schratzberger, R. Smith, E. Vanden Berghe, J. Vam Dalfsen, G. Vam Hoey, M. Vincx, W. Willems & H. L. Rees (2011) Changes in North Sea macrofauna communities and species distribution between 1986 and 2000. - Estuar. Coast. Shelf. Sci. 94: 1-15.

Künitzer, A., D. J. Basford, J. A. Craeymeersch, J.-M. Dewarumez, J. Dörjes, G. C. A. Duineveld, A. Eleftheriou, C. H. R. Heip, P. Herman, P. Kingston, U. Niermann, E. Rachor, H. Rumohr & P. A. W. J. De Wilde (1992) The benthic infauna of the North Sea: Species distribution and assemblages. - ICES Journal of Marine Science 49: 127-143.

Lindenbaum, C., Bennell, J.D., Rees, E.I.S., McClean, D., Cook W., Wheeler, A.J., & Sanderson, W.G. (2008). Small-scale variation within a Modiolus modiolus (Mollusca: Bivalvia) reef in the Irish Sea: I. Seabed mapping and reef morphology. Journal of the Marine Biological Association of the UK, 88(1), 133-141.

OSPAR (2008) OSPAR List of Threatened and/or Declining Species and Habitats. - OSPAR Agreement 2008-6.

OSPAR 2011b: Report of the OSPAR workshop on MSFD biodiversity descriptors: comparison of targets and associated indicators („Amsterdam workshop“).

Roberts, J.M., Harvey, S.M., Lamont, P.A. & Gage, J.A., 2000. Seabed photography, environmental assessment and evidence for deep-water trawling on the continental margin west of the Hebrides. Hydrobiologia 44, 173-183.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Robinson, K.A., Mackie, A.S.Y., Lindenbaum, C., Darbyshire, T., van Landeghem, K.J.J., & Sanderson, W.G. (2012). Southern Irish Sea Habitats, with focus on a horse-mussel (Modiolus modiolus) bioherm. In Seafloor geomorphology as benthic habitat, P.T. Harris & E.K. Blake (eds), Elsevier, London, 523 – 537.

Strain EMA, Allcock AL, Goodwin C, Maggs CA, Picton BE, Roberts D (2012). The long-term impacts of fisheries on epifaunal assemblage function and structure, in a Special Area of Conservation. Journal of Sea Research 67: 58-68.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Size-frequency distribution of bivalve or other sensitive/indicator species

1. Indicator

Name: Size-frequency distribution of bivalve or other sensitive/indicator species

Code: BH-5

Proposed to BDC 2013 as: Candidate indicator

State of methodological development:

Development step Defined

Indicator metrics No

Ecosystem components attributed (species/habitat types) Partially

Applicability to sub-regions Yes

Assessment scales No

Monitoring parameter Yes

Monitoring frequency Partially

Benthic communities typically consist of a mixture of long-living and short-living species. The short-living species are usually small with low individual biomass, whilst the long-living species can reach much bigger sizes and higher individual biomass. Under natural conditions, populations of large species consist of different size-classes representing different age-groups.

The natural balance between both (1) the large and small species within the community and (2) the large and small specimens within the population of a single species can be affected by anthropogenic influences such as physical disturbance (e.g. caused by bottom trawling or sediment extraction) (BASSET et al. 2012, HIDDINK et al., 2006, PEARSON & ROSENBERG, 1978; TYLER-WALTERS et al., 2009).

In current asssessments of benthic habitat condition a clear focus has been put on the community-based approach as summarized for the impact of beam-trawl fisheries in the North Sea by LENGKEEK & BOURMA (2010) and more generally in RICE et al. (2011). Based on the size spectrum within the community, conclusions can be drawn on the dynamics of the community, its productivity (QUEIROS et al., 2006) and partially on the structure of food-webs (BLANCHARD et al., 2009). But this approach (size distribution within community) integrates over several anthropogenic influences, as most pressures affect the linkage between productivity and mortality rate in comparable ways (RICE et al., 2011).

The impact of human pressure on the size-frequency distribution of single species has been mainly described for fish species. Regional studies on macrobenthic invertebrates are rare. AMARO et al (2003) and WITBAARD & BERGMANN (2003) detected bottom-trawling to be a potential reason for unbalanced population structure of bivalve species (Mya truncata and Arctica islandica respectively) in the Frisian front. Large bivalves are in general regarded to be the most sensitive group of benthic species to bottom-trawling within the soft-bottom communities, whereas species of large, mobile gastropods, echinoderms and especially decapods might benefit from temporal physical disturbance (RUMOHR & KUJAWSKI, 2000).

As the community-based approach is (1) partly covered by other indicators (typical species composition, multimetric indices), (2) is partly related to descriptor 4 (food webs) and (3) is to a lesser extent directly

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development linked to physical disturbance of the seafloor, only the approach dealing with the population structure of single indicative species is followed here.

2. Appropriateness of the indicator

Biodiversity component: Benthic Habitats

MSFD criterion: Condition of benthic community (6.2)

MSFD indicator: Proportion of biomass/number of individuals above specified length/ size (6.2.3)

High High Yes Yes 7 7

The proposed indicator is a condition indicator with direct linkage to area-related physical pressures such as bottom-trawling and substrate extraction which are considered to be the most important pressures for the majority of benthic habitat types in the OSPAR area. It is therefore relevant for both “predominant” and “special” habitats according to MSFD,

This indicator is particularly relevant for GES-Descriptor 6, which is defined as “sea-floor integrity at a level that ensures that the structure and functions of the ecosystems are safeguarded and benthic ecosystems, in particular, are not adversely affected”, i.e. human pressures on the seabed may not hinder the ecosystem components to retain their natural diversity, productivity and dynamic ecological processes, having regard to ecosystem resilience. It is the only proposed condition targeted benthic habitats indicator with a focussed sensitivity to physical disturbance and is therefore most suitable not only for regular state assessment but also for monitoring of the success of measures. The targeted species may be collected during benthos monitoring that is performed for other purposes, in such cases little additional monitoring effort is assumed.

3. Parameter/metric

The basic parameter is the number of individuals per size class. A possible modification is the use of biomass instead of size, as both parameters are in general strongly correlated. Use of biomass is preferable if measuring the size of the specimens might be an important source of error. It is recommended to use the full size/ biomass spectra instead of concentrating on a ratio of individuals /biomass above specified length/ size, as information on the full state of the population and a potential recovery might be lost by ignoring smaller size/ biomass classes.

In principle, length-frequency distributions can only be determined using species that survive sampling relatively undamaged and are present in adequate (representative) numbers within a habitat. In taxonomic terms, crustaceans, molluscs and echinoderms are suitable, but bivalve species are preferred due to their high sensitivity to physical disturbance. However, a careful selection of species is essential and a variety of species should be selected to improve the relevance and reliability of the results.

The proposed metric would be a comparison of the current population structure with a (theoretical) natural population structure resulting in a value for the “degree of naturalness” of the population structure. No such metric is known for marine benthic species.

4. Baseline and Reference level

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Baselines have not yet been defined and will depend on the habitat type in focus, however, the use of reference state as a baseline is regarded to be the most appropriate approach. The reference level is a natural population structure of the selected species with a defined proportion of small (young), medium-sized and large (old) individuals. This reference not only strongly depends on the species, but also on parameters with high spatial variability like spawning success, growth rate and mortality. Therefore this natural population structure will in most cases have to be modelled.

5. Setting of GES boundaries / targets

GES boundaries and targets have not yet been defined as the baselines are still unknown. The suggested target is to reach a high degree of naturalness of the population structure represented by a natural length- frequency distribution of all sensitive or indicator species. These target values have to be defined separately for each species and most probably per sub-region. However, natural variability in the population structure (e.g. due to predation, irregularities in reproduction or natural physical disturbance) has to be considered when formulating the final target.

6. Spatial scope

The index is in general applicable to all regions, but reference values have to be defined for populations sharing the same growth rate, mortality and recruitment success and so should be set for each subregion (and possibly more locally).

7. Monitoring requirements

This indicator is with the exception of a few fishery relevant species (e.g. Nephrops norvegicus, Pecten maximus) currently not part of most regular European monitoring programmes. However it is possible to record this parameter using the samples taken within the framework of many standard benthic monitoring programmes as long as the species involved occur in an adequate density. To reach this prerequisite, it may be necessary to expand the sampling scope. The additional effort and expense for implementation of size- based benthos parameters is likely to be low, even though additional time is needed for size/ biomass measurements.

When working with size-based metrics, one has to take into account that they are less suitable for an annual assessment, but rather lead to suitable results for management on a time scale of > 5 years (JENNINGS & DULVY, 2005). Although this statement is based on the application of such metrics to fish communities, it principally applies to benthic marine communities as well.

8. Reporting

(to be developed)

9. Resources needed

Principally, the required resources for data aquisition for this indicator are rather extensive:

- Research Vessels, suit to work from sublittoral to bathyal

- Scuba diving sampling to infralittoral

- Adequate equipment (box core samplers, grabs, dredges etc) for sampling collection from intertidal to bathyal

- Laboratory infrastructure to analyse samples (e.g. microscopes, scales)

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Qualified staff is required for both field and laboratory work to fulfil the requirements of quality management in sampling accuracy, data processing, analysis and interpretation.

However, in practice, the requirements for this indicator highly overlap with the needs for the proposed indicators BH-1 (Typical species composition) and BH-2 (Multimetric indices). Therefore, little additional effort arising from measuring/weighting the individual specimens of the target species is assumed for most habitats (see also under ch. 7, Monitoring requirements).

10. Further work

The following steps are essential for operationalization:

1. Selection of suitable target species. Recommended selection criteria include:

- sensitive to (physical) disturbances

- of frequent occurrence

- high maximum age, reflected significantly by size

- historical data on natural state and natural variability are available.

2. A separate reference length-frequency distribution (baseline) has to be established for each of the species (historical data, comparative data from undisturbed areas, expert judgements). Alternatively, a natural population structure has to be modelled (because of current lack of reference sites) for development of GES distributions.

3. Measuring the size of the relevant species has to be included into the ongoing monitoring program to start the creation of a suitable database.

4. The statistical comparison between the reference size distribution and the current size distribution has to be operationalized (development of the metric).

5. Setting a cut-off value to define an acceptable deviation from the natural size-distribution.

References:

Amaro, T., Duineveld, G, Bergman, M., Witbaard, M. 2003. Growth variations in the bivalve Mya truncata: a tool to trace changes in the Frisian Front macrofauna (southern North Sea)? Helgoland Marine Research 57:132–138.

Basset. A., Barbone, E., Borja, A., Brucet, S., Pinna, M., Quintana, X.D, Reizopoulou, S., Rosati, I., Simboura, N. 2012. A benthic macroinvertebrate size spectra index for implementing the Water Framework Directive in coastal lagoons in Mediterranean and Black Sea ecoregions. Ecological Indicators 12: 72-83.

Hiddink, J.G., Jennings, S., Kaiser, M.J. 2006. Indicators of the ecological impact of bottom-trawl disturbance on seabed communities. Ecosystems 9: 1190-1199.

Jennings, S. & Dulvy, N.K. 2005. Reference points and reference directions for size-based indicators of community structure. ICES J. Mar. Sci 62 : 397-404.

Lengkeek, W. & Bourma, S. 2010. Impact of beam trawl fisheries in the North Sea – A summary of 55 publications. Report of the Bureau Waardenburg bv on behalf of Stichting de Noordzee and Greenpeace Nederland, 44 pp.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development OSPAR 2011. Advice document on GES 1, 2, 4 and 6 – Biodiversity (ICG-MSFD(4) 11/2/3 –E). Meeting of the Intersessional Correspondence Group for the Implementation of the Marine Strategy Framework Directive (ICG-MSFD) Madrid: 13-14 December 2011.

Pearson, T. H. & R. Rosenberg, 1978. Macrobenthic succession in relation to organic enrichment and pollution of the marine environment. – Oceanogr. Mar. Biol. Annu. Rev. 16: 229-311.

Queiros, A.M., Hiddink, J.G., Kaiser, M.J., Hinz, H., 2006. Effects of chronic bottom trawling disturbance on benthic biomass, production and size spectra in different habitats. Journal of Experimental Marine Biology and Ecology 335, 91–103.

Rice et al., 2011: Indicators for seafloor integrity under the European Marine Strategy Framework Directive. – Ecological indicators 12: 174-184.

Rumohr, H., and Kujawski, T. 2000. The impact of trawl fishery on the epifauna of the southern North Sea. – ICES Journal of Marine Science, 57: 1389–1394.

Tyler-Walters, H., Rogers S. I., Marshall C.E., Hiscock K. 2009. A method to assess the sensitivity of sedimentary communities to fishing activities. Aquatic Conserv: Mar. Freshw. Ecosyst. 19: 285–300.

Witbaard R., Bergman M. 2003. The distribution and population structure of the bivalve Arctica islandica L. in the North Sea: what possible factors are involved? Journal of Sea Res 340: 1–15.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Pelagic Habitats

Code Previous Indicator Category code* PH-1 NA Changes of plankton functional types (life form) index Ratio Core

PH-2 NA Plankton biomass and/or abundance Core

PH-3 NA Changes in biodiversity index (s) Core

Microplankton Community Index (MCI) 1. Indicator Name: Microplankton Community Index (MCI) Code: PH-1 / FW-5

Proposed to BDC 2013 as: Core indicator

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components attributed (species/habitat types) Pelagic habitats

Applicability to sub-regions yes

Assessment scales regional

Monitoring parameter Plankton abundance or biomass (per taxa)

Monitoring frequency Monthly

[Further review from other CPs desired]

2. Appropriateness of the indicator

Biodiversity component: Pelagic Habitats

MSFD criterion: Distributional range (1.4.1) Distributional pattern (1.4.2) Condition of the typical species and communities (1.6.1) Composition and relative proportions of ecosystem components (habitats and species (1.7.1) Abundance trends of selected groups/species (4.3.1) Multi-metric indexes assessing benthic community condition and functionality (6.2.2.

Also used to inform D2, D3, D5. MSFD indicator: yes Already developed but not operational yet. Will be fully operational for the UK in Sept 2014.

Sensitivity to Relevance to Practicable Applicable Number of CPs Consensus among specific pressures management across region reporting/using the CPs on usefulness measures indicator (n=9) as part of a region

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yes yes yes yes 5 5

3. Parameter/metric

Indicators based on lifeforms can be used to assess community response to sewage pollution (Charvet et al., 1998; Tett et al., 2008), anoxia (Rakocinski, 2012), fishing (Bremner et al., 2004) and climate change (Beaugrand, 2005). Indicators based on zooplankton/phytoplankton ratios are being used to assess environmentally driven changes in the food web, and the possible impact of eutrophication (HELCOM, 2012). The underlying principle of the zooplankton/phytoplankton ratio is that higher grazing efficiency implies fewer losses in the food web, less energy and nutrients passing through the microbial loop, and, consequently, more energy transferred to the higher trophic levels such as fish. An important advantage of these plankton indicators is that the proposed concepts are relatively easy transferable to other European waters (Gowen et al. 2011; Rombouts et al., in press). Ratios of plankton can provide information on ecosystem structure and flow. Combination of life form pairs will depend on the habitat and the objective of the indicator, e.g. as a measure of GES for pelagic habitats, food webs, seafloor integrity or eutrophication.

In practice, the use of functional groups is often favoured over indicator species since indices of species abundance are frequently subject to large inter-annual variation, often due to natural physical dynamics rather than anthropogenic stressors (de Jonge, 2007). Functional group abundance is often less variable because variability in the abundances of the group’s constituent species averages out. Moreover, indicators based on functional groups have been proved relevant for the description of the communities structure and biodiversity and more operational than taxonomic-based indicators (intercomparibility) (Estrada et al. 2004; Gallego et al. 2012; Mouillot et al. 2006; Garmendia et al. 2012).

Life-form pairs can provide an indication of changes in: the transfer of energy from primary to secondary producers (changes in phytoplankton and zooplankton); the pathway of energy flow and top predators (changes in gelatinous zooplankton and fish larvae); benthic/ pelagic coupling (changes in holoplankton (fully planktonic) and meroplankton (only part of the lifecycle is planktonic, the remainder is benthic) (Table. 1; see Gowen et al. 2011). Data on pairs will be expressed in abundance or biomass, whichever is most relevant to the group in question and available from monitoring programmes.

Pairs chosen will depend on the habitat types, so regional adaptation will be needed. As the knowledge base increases, new pairs can be developed as indicators for other pressures than currently measured. See Gowen et al (2011) and Tett et al (2008) for further technical information on the method.

Table 1: Proposed plankton lifeform pairs. Descriptor Lifeform pair 1 Lifeform pair 2 Lifeform pair 3

D1: Copepod Non-copepod Biodiversity Diatoms Dinoflagellates Large copepods Small copepods grazers grazers

Shift in size of secondary Energy transfer from primary Shift in algal community composition producers/primary grazers could have food producers to less trophically useful Reasoning: towards less trophically useful groups web impacts secondary producers

Nutrient run off (point or non-point), hydrological change (from dredging, aggregate extraction, trawling, river damming), aquaculture, warm water Pressure(s): outflows Fishing Nutrients, fishing

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Changes in these important aspects of the plankton community provide a comprehensive overview of the planktonic component of pelagic ecosystem structure and function. Reasoning:

Trawling, aquaculture, oil spills, river damming, aggregate extraction, mining, wind farms, warm water outflows from nuclear plants, dredging, fishing, industrial spills, contaminant resuspension from sea bed disturbance, agriculture, urban waste Pressure(s): water, point source pollution, atmospheric deposition

D4: Food- Gelatinous webs zooplankton Fish larvae Copepods Phytoplankton Holoplankton Meroplankton

Energy transfer from primary to secondary Reasoning: Energy flow pathway to top predators producers Benthic-pelagic coupling

Fishing (including pressure on Pressure(s): Fishing Fishing benthos from trawling), nutrients

D5: Potentially toxin Eutrophicat Diatoms (Si Dinoflagellates Psuedo- producing ion users) (non-Si users) Ciliates Microflagellates nitzschia spp. dinoflagellates

Shift in algal community composition towards less trophically useful and Shift in algal community towards Reasoning: potentially harmful groups dinoflagellate HABs

Pressure(s): Nutrients Nutrients Nutrients D6: Sea floor integrity Holoplankton Meroplankton

Reasoning: Benthic-pelagic coupling

Fishing (including pressure on benthos Pressure(s): from trawling), nutrients

4. Baseline and Reference level Currently not all member states have defined a baseline approach so this is still under discussion. The UK approach is “Baseline set in the past (but not as a reference pristine condition, just as a starting point for change)” and UK targets will be evaluated as “change away from the baseline”. This is one approach which can be considered at the regional level. This choice was made because data may not always exist in all regions, time-series length may vary, and the first available data may be from a time period which is not necessarily in Good Environmental Status. In accordance with our target (Section 5, below) the absence of a significant trend in an indicator or lack of a significant correlation between the indicator trend and the trend in a human pressure will be used as evidence that the target for Good Environmental Status (for that criterion and the plankton community as a whole) has been met. However, this presupposes that the starting point of the time-series represented baseline (or reference) conditions and hence Good Environmental Status. This may not be the case. Where data exist, it will be necessary to use this to determine the current status of the plankton at those locations but 2 – 3 years of data will have to be collected from new monitoring sites to characterise the status of the plankton. If, however, existing data sets

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5. Setting of GES boundaries / targets

The only Member State with a proposed target is the UK. The UK target is: “Plankton community not significantly influenced by anthropogenic drivers.”. This target allows unmanageable climate change but triggers management action if linked to an anthropogenic pressure and could be used with all datasets across all Member States.

6. Spatial scope

This indicator is important at the regional level. It will be assessed at the habitat level. The UK and France both divided their habitats into regions based on ecohydrodynamics but different models were used so these would need to be harmonized. The UK has defined 4 habitat types while France has 10 for the English Channel and North Sea and Bay of Biscay (Gailhard-Rocher et al. 2012). Sampling depth required will vary between monitoring programmes and is also dependent on habitat.

7. Monitoring requirements Coastal Shelf Offshore Frequency of data Bi-weekly Monthly Monthly collection* Monitoring method In situ In situ In situ Who is responsible for Member state Member state Member state monitoring? Freq of indicator update and Annual update Annual update Annual update assessment Minimal amt of monitoring Depends on amt of Depends on amt of Depends on amt of locations habitats. The CPR habitats. The CPR is habitats. The CPR is a is a European a European scale European scale plankton scale plankton plankton monitoring monitoring programme. monitoring programme. programme. *A complementary need exists for both long-term time-series as well as high frequency monitoring, particularly in habitats considerably influenced by anthropogenic pressures.

8. Reporting

This indicator should be updated annually, based on monthly or bi-weekly monitoring. Reporting is per Member State.

9. Resources needed

10. Further work i. New pairs can be developed as indicators for other pressures, habitats and pelagic compartment (bacteria, virus), as the knowledge base increases.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development ii. Baseline and reference states (not as a pristine conditions, but as a starting point for change) need to be developed at the regional scale but this is dependent on length of time-series. iii. Taxonomic resolution should be intercompared and intercalibrated. iv. Ideally to truly asses this indicator at the regional scale, it would have to be monitored and assessed using the same methodology throughout the region. However, until funding is available for this, the indicator can still inform an assessment of Good Environmental Status for regions with adequate data collection. v. Some groups are undersampled with lots of data missing: microphyto, pico, nano and bacteria and micro zooplankton including ciliates.

References: Bremner, J., Frid, C.L.J., Rogers, S.I., 2004. Biological traits of the North Sea benthos – Does fishing affect benthic ecosystem function? Benthic habitats and the effects of fishing. In: Barnes, P., Thomas, J. (Eds.), Symposium 41. American Fisheries Society, Bethesda, MD. Beaugrand, G. 2005. Monitoring pelagic ecosystems using plankton indicators, ICES Journal of Marine Science, 62: 333-338. Charvet, S., Roger, M.C., Faessel, B., Lafont, M. 1998. Biomonitoring of freshwater ecosystems by the use of biological traits. Annal. Limnol. – Int. J. Limnol. 34, 455-464. de Jonge, V.N. 2007. Toward the application of ecological concepts in EU coastal water management. Mar. Pollut. Bull. 55, 407-414. Estrada, Marta, Peter Henriksen, Josep M. Gasol, Emilio O. Casamayor, et Carlos Pedrós-Alió. « Diversity of Planktonic Photoautotrophic Microorganisms Along a Salinity Gradient as Depicted by Microscopy, Flow Cytometry, Pigment Analysis and DNA-based Methods ». FEMS Microbiology Ecology 49, no 2 (2004): 281– 293. doi:10.1016/j.femsec.2004.04.002. Gallego, I., T. A. Davidson, E. Jeppesen, C. Perez-Martinez, P. Sanchez-Castillo, M. Juan, F. Fuentes- Rodriguez, et al. Taxonomic or ecological approaches? Searching for phytoplankton surrogates in the determination of richness and assemblage composition in ponds. Ecological Indicators 18 (2012): 575‑585. doi:10.1016/j.ecolind.2012.01.002. Garmendia, Maialen, Ángel Borja, Javier Franco, et Marta Revilla. Phytoplankton composition indicators for the assessment of eutrophication in marine waters: Present state and challenges within the European directives. Marine Pollution Bulletin no 0 (2012). doi:10.1016/j.marpolbul.2012.10.005. Gowen, R.J. McQuatters-Gollop, A. Tett, P. Best, M. Bresnan, E. Castellani, C. Cook, K. Forster, R. Scherer, C. Mckinney, A. 2011. The Development of UK Pelagic (Plankton) Indicators and Targets for the MSFD, Belfast, 2011. HELCOM, 2012. Development of the HELCOM core-set indicators Part B. GES 8/2012/7b, Brussels. Mouillot, D., S. Spatharis, S. Reizopoulou, T. Laugier, L. Sabetta, A. Basset, et T. Do Chi. Alternatives to taxonomic-based approaches to assess changes in transitional water communities. Aquatic Conservation- Marine and Freshwater Ecosystems 16(2006): 469‑482. doi:10.1002/aqc.769.

Rakocinski, C.F. 2012. Evaluating macrobenthic process indicators in relation to organic enrichment and hypoxia. Ecol. Indic., 13, 1-12. Richardson, A.J. and Gibbons, M.J. 2008. Are jellyfish increasing in response to ocean acidification? Limnology and Oceanography 53(5), 2035–2040.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Raybaud, V. Héroin, D. Raud, T. Brylinski, J.-M. Stemmann, L. Thibault-Botha, D. Sautour, B. 2011 Census and analysis of zooplankton metadata of the French coasts since 1955. Journal of Oceanography: Research and Data, 4, 11-37. Rombouts, I., Beaugrand, G., Fizzala, X., Gaill, F., Greenstreet, S.P.R., Lamare, S., Le Loc’h, F., McQuatters-Gollop, A., Mialet, B., Niquil, N., Percelay, J., Renaud, F., Rossberg, A.G., Féral, J.P. (in press) Food web indicators under the Marine Strategy Framework Directive: from complexity to simplicity? Ecological Indicators. Tett, P., Carreira, C., Mills, D.K., van Leeuwen, S., Foden, J., Bresnan, E., Gowen, R.J. 2008. Use of a phytoplankton community index to assess the health of coastal waters. ICES J. Mar. Sci. 65(8), 1475-1482.

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Plankton biomass and/or abundance

1. Indicator

Name: Plankton biomass and/or abundance

Code: PH2

Proposed to BDC 2013 as: Core indicator

State of methodological development:

Development step Defined

Indicator metrics Yes but vary by country

Ecosystem components Pelagic attributed (species/habitat types)

Applicability to sub-regions Yes

Assessment scales Regional

Monitoring parameter Biomass and/or abundance of phytoplankton and zooplankotn

Monitoring frequency Monthly

[Further review from other CPs desired]

2. Appropriateness of the indicator

Biodiversity component: Pelagic habitats

MSFD criterion:

1.6.2 Relative abundance and/or biomass, as appropriate

4.3 Abundance/distribution of key trophic groups/species

Also used to inform D2, D3, D5.

MSFD indicator: yes

Phytoplankton biomass: Operational

Phytoplankton abundance: Already developed but not operational yet – Sept 2014 (UK)

Zooplankton abundance or biomass: Already developed but not operational yet – Sept 2014 (UK)

Sensitivity to Relevance to Practicable Applicable Number of CPs Consensus among specific pressures management across reporting/using the CPs on usefulness measures region indicator (n=9) as part of a region wide set (n=8)

yes yes yes yes 7 7

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Plankton biomass and plankton abundance are measured in different ways both within and between member states; however relative changes (trends) in each time-series can be compared between datasets. Primary production is the process by which photosynthetic organisms use energy from sunlight to synthesize organic molecules from inorganic materials. Almost all life on earth, including marine life, depends on this basic process 1. Pelagic phytoplankton are responsible for approximately 95% of all marine primary productivity1, making phytoplankton biomass a commonly-used indicator for primary production.

Phytoplankton biomass is estimated through phytoplankton carbon from biovolume, particulate organic carbon, chlorophyll concentration or the Continuous Plankton Recorder’s Phytoplankton Colour Index (PCI). There are multiple ways to measure chlorophyll concentration (HPLC, flouresence, remote sensing) which are employed within individual member states. The Continuous Plankton Recorder (CPR) survey monitors plankton biomass and abundance at the European-scale. The PCI is a unique measurement of phytoplankton biomass2. Accumulation of phytoplankton cells on the CPR silk gives it a greenish colour3. The PCI also accounts for fragile, broken and fragmented cells that contribute to phytoplankton biomass but are not morphologically identifiable, making it a more comprehensive indicator of phytoplankton biomass than cell counts alone. PCI is based on a relative scale of greenness and is determined on the CPR silk by reference to a standard colour chart. There are four different ‘‘greenness’’ values: 0 (no greenness), 1 (very pale green), 2 (pale green), and 6.5 (green); darker green CPR silks are higher in phytoplankton biomass than silks which are not green or pale in colour. Categories of PCI are assigned numerical values based on acetone extracts (Colebrook and Robinson 1965). PCI has been shown to correspond with satellite measurements of chlorophyll-a4-5. Furthermore, primary production and phytoplankton biomass estimates in the Northeast Atlantic have virtually identical spatial distribution patterns to PCI, with PCI values representing the major phytoplankton patterns of variation in time and space 6-9. Because PCI is derived from CPR samples, the dataset is extensive in both spatial extent (North Atlantic/North Sea) and temporal length (1948-present), allowing trends and dynamics observed in Scottish waters to be placed into a regional context. The PCI indicator is updated annually and the semi-quantitative nature of the PCI (based on a ratio scale) allows the statistical determination of trends from PCI data.

Zooplankton biomass is generally estimated by the carbon content of zooplankton samples. The biomass may be further broken down into size components to arrive at biomass per size spectrum. The Continuous Plankton Recorder doesn’t record zooplankton biomass outright, but biomass can be derived from CPR zooplankton abundance counts. Phytoplankton and zooplankton abundance methodologies also vary between surveys. Plankton may be identified and enumerated by traditional manual light microscopy or by semi-automated methods such as flow cytometry, or a combination of both. In general, taxonomic resolution is greater with manual methods than semi-automated.

Country Phytoplankton biomass Phytoplankton abundance Zooplankton biomass Zooplankton abundance

FR Chl a, Individuals per litre Carbon and/or nitrogen Individuals per m2 or (microscopy, flow content per m3 Particulate organic carbon, cytometry) Phytoplankton carbon (from biovolume)

Total or per size class Total or per size spectrum Total or per size spectrum Total or per size spectrum

SE Phytoplankton carbon (from Individuals per litre Carbon content Individuals per m2 or

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UK Phytoplankton Colour Index Could be operationalized Could be operationalized, Individuals per sample (PCI) from the CPR, Chl from CPR, other datasets from CPR, other datasets (CPR) or m2 (other)

4. Baseline and Reference level

Currently not all member states have defined a baseline approach so this is still under discussion.

The UK approach is “Baseline set in the past (but not as a reference pristine condition, just as a starting point for change)” and UK targets will be evaluated as “change away from the baseline”. This is one approach which can be considered at the regional level. This choice was made because data may not always exist in all regions, time-series length may vary, and the first available data may be from a time period which is not necessarily in Good Environmental Status. In accordance with our target the absence of a significant trend in an indicator or lack of a significant correlation between the indicator trend and the trend in a human pressure will be used as evidence that the target for Good Environmental Status (for that criterion and the plankton community as a whole) has been met. However, this presupposes that the starting point of the time-series represented baseline (or reference) conditions and hence Good Environmental Status. This may not be the case. Where data exist, it will be necessary to use this to determine the current status of the plankton at those locations but 2 – 3 years of data will have to be collected from new monitoring sites to characterise the status of the plankton. If, however, existing data sets can be used to characterise Good Environmental Status for plankton communities (using ecological theory, modelling, the absence of obvious human pressure and expert opinion), it may be possible to use such data as baseline conditions for new monitoring sites and existing sites at which the status of the plankton does not meet GES.

5. Setting of GES boundaries / targets

6. Spatial scope

This indicator is important at the regional level. It will be assessed at the habitat level. The UK and France both divided their habitats into regions based on ecohydrodynamics but different models were used so these would need to be harmonized. The UK has defined 4 habitat types while France has 9. Sampling depth required will vary between monitoring programmes and is also dependent on habitat.

7. Monitoring requirements

Coastal Shelf Offshore

Frequency of data collection* Bi-weekly Monthly Monthly

Monitoring method In situ In situ In situ/remote sensing

Who is responsible for monitoring? Member state Member state Member state

Freq of indicator update and assessment Annual update Annual update Annual update

Minimal amt of monitoring locations Depends on amt of Depends on amt of Depends on amt of habitats. habitats. The CPR is a habitats. The CPR is a The CPR is a European scale European scale plankton European scale plankton plankton monitoring

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*A complementary need exists for both long-term time-series as well as high frequency monitoring, particularly in habitats considerably influenced by anthropogenic pressures.

8. Reporting

This indicator should be updated annually, based on monthly monitoring. Reporting is per Member State.

9. Resources needed

10. Further work

i. Baseline and reference states need to be developed at the regional scale.

ii. Methodologies should be intercompared and intercalibrated.

iii. Ideally to truly asses this indicator at the regional scale, it would have to be monitored and assessed using the same methodology throughout the region. However, until funding is available for this, the indicator can still inform an assessment of Good Environmental Status for regions with adequate data collection.

References:

1 Nybakken, J. W. Marine Biology - An Ecological Approach. 5 edn, (Benjamin Cummings, 2001).

2 McQuatters-Gollop, A. et al. Is there a decline in marine phytoplankton? Nature 472, E6-E7, doi:doi:10.1038/nature09950(2011) (2011).

3 Batten, S. D., Walne, A. W., Edwards, M. & Groom, S. B. Phytoplankton biomass from continuous plankton recorder data: an assessment of the phytoplankton colour index. Journal of Plankton Research 25, 697-702 (2003).

4 Raitsos, D. E., Reid, P. C., Lavender, S. J., Edwards, M. & Richardson, A. J. Extending the SeaWiFS chlorophyll data set back 50 years in the northeast Atlantic. Geophysical Research Letters 32, art. no.-L06603 (2005).

5 McQuatters-Gollop, A. et al. A long-term chlorophyll dataset reveals regime shift in North Sea phytoplankton biomass unconnected to nutrient levels. Limnology and Oceanography 52, 635-648 (2007).

6 Colebrook, J. M. & Robinson, G. A. Continuous plankton records: seasonal cycles of phytoplankton and copepods in the north-eastern Atlantic and North Sea. Marine Ecology 6, 123-139 (1965).

7 Gieskes, W. W. C. & Kraay, G. W. Continuous Plankton Records: changes in the plankton of the North Sea and its eutrophic Southern Bight from 1948 to 1975. Netherlands Journal of Sea Research 11, 334-364 (1977).

8 Reid, P. C., Robinson, G. A. & Hunt, H. G. Spatial and temporal patterns of marine blooms in the north-eastern Atlantic and North Sea from the Continuous Plankton Recorder Survey. 27-37 (1987).

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Plankton biodiversity indexes

1. Indicator

Name: Plankton biodiversity indexes

Code: PH-3

Proposed to BDC 2013 as: Core indicator

State of methodological development:

Development step Defined

Indicator metrics In progress

Ecosystem components attributed (species/habitat types) Pelagic habitats

Applicability to sub-regions Yes

Assessment scales Regional

Monitoring parameter Abundance

Monitoring frequency Monthly

[Further review from other CPs desired]

2. Appropriateness of the indicator

Biodiversity component: Pelagic habitats MSFD criterion: Condition of the typical species and communities (MSFD 1.6.1) Composition and relative proportions of ecosystem components (MSFD 1.7.1) Also used to inform D2, D3, D5. MSFD indicator: yes Biodiversity indexes are theoretically developed but need testing before operationalization

yes yes yes yes 4 4

3. Parameter/metric

The biodiversity indices are based on the description of diversity (eg Shannon, Menhinick, Simpson’s), species richness (eg Margalef), evenness (eg Pielou’s), or dominance (Breger-Parker’s). The advantage of these indices is that they allow an accurate description of the pelagic assemblages and also the direct comparison of communities that have few or no species in common. These indices are required for detailed qualitative assessment of biodiversity, in complement of others indices. Moreover, some of them are able to

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Index selection is dependent on type of data available – indexes using micro, pico, nano and bacteria will be more complete as indicators than indexes addressing only a portion of the pelagic community.

4. Baseline and Reference level

Currently not all member states have defined a baseline approach so this is still under discussion. The UK approach is “Baseline set in the past (but not as a reference pristine condition, just as a starting point for change)” and UK targets will be evaluated as “change away from the baseline”. This is one approach which can be considered at the regional level. This choice was made because data may not always exist in all regions, time-series length may vary, and the first available data may be from a time period which is not necessarily in Good Environmental Status. In accordance with our target (Section 5, below) the absence of a significant trend in an indicator or lack of a significant correlation between the indicator trend and the trend in a human pressure will be used as evidence that the target for Good Environmental Status (for that criterion and the plankton community as a whole) has been met. However, this presupposes that the starting point of the time-series represented baseline (or reference) conditions and hence Good Environmental Status. This may not be the case. Where data exist, it will be necessary to use this to determine the current status of the plankton at those locations but 2 – 3 years of data will have to be collected from new monitoring sites to characterise the status of the plankton. If, however, existing data sets can be used to characterise Good Environmental Status for plankton communities (using ecological theory, modelling, the absence of obvious human pressure and expert opinion), it may be possible to use such data as baseline conditions for new monitoring sites and existing sites at which the status of the plankton does not meet GES.

5. Setting of GES boundaries / targets

6. Spatial scope

This indicator is important at the regional level. It will be assessed at the habitat level. The UK and France both divided their habitats into regions based on ecohydrodynamics but different models were used so these would need to be harmonized. The UK has defined 4 habitat types (Moffat, 2011) while France has 10 for the English Channel and North Sea and Bay of Biscay (Gailhard-Rocher et al. 2012). Sampling depth required will vary between monitoring programmes and is also dependent on habitat.

7. Monitoring requirements

Coastal Shelf Offshore Frequency of data collection* Bi-weekly Monthly Monthly Monitoring method In situ In situ In situ Who is responsible for monitoring? Member state Member state Member state Freq of indicator update and Annual update Annual update Annual update assessment Minimal amt of monitoring locations Depends on amt of habitats. Depends on amt of Depends on amt of habitats. The The CPR is a European scale habitats. The CPR is a CPR is a European scale plankton plankton monitoring European scale monitoring programme.

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8. Reporting

This indicator should be updated annually, based on monthly monitoring. Reporting is per Member State.

9. Resources needed

Varies between Member States. It’s cheaper to go with what we already have than to get all Member States using the same methodology. The closest we are to all Member States using a comparable monitoring methodology is the Continuous Plankton Recorder survey, which monitors at the European scale, but national monitoring networks are necessary, in particular in coastal waters. These biodiversity indices require counts for all the species/genera, with a high taxonomic resolution, a high level of expertise, and laboratory infrastructure to analyse samples. Some national monitoring network exist, in particular for the WFD, and an optimization of the resources should be explored (even if the geographical areas covered are not the same),

10. Further work i. Overview of existing regional or national monitoring for the relevant parameters and biodiversity indices projects. ii. Test the indices for comparision,consistency and pertinence within biogeographical regions. iii. Further work is needed to link biodiversity indexes, particularly zooplankton, more clearly to specific anthropogenic pressures, and to compare the results between such indices and others, based on taxonomic- free data (body size, abundance distribution among functional groups…) iv. Baseline and reference states need to be developed at the regional scale. v. Taxonomic resolution should be intercompared and intercalibrated. Data should be gathered in an unique database. vi. Ideally to truly asses this indicator at the regional scale, it would have to be monitored and assessed using the same methodology throughout the region. However, until funding is available for this, the indicator can still inform an assessment of Good Environmental Status for regions with adequate data collection. vii. Some groups are undersampled with lots of data missing: for example, microphyto, pico, nano and bacteria and micro zooplankton. References: Estrada, Marta, Peter Henriksen, Josep M. Gasol, Emilio O. Casamayor, et Carlos Pedrós-Alió. « Diversity of Planktonic Photoautotrophic Microorganisms Along a Salinity Gradient as Depicted by Microscopy, Flow Cytometry, Pigment Analysis and DNA-based Methods ». FEMS Microbiology Ecology 49, no 2 (2004): 281–293. doi:10.1016/j.femsec.2004.04.002. Gailhard-Rocher, Isabelle, Martin Huret, Pascal Lazure, Frédéric Vandermeirsch, Julie Gatti, Pierre Garreau, et Francis Gohin. Identification de « paysages hydrologiques » dans les eaux marines sous jurdidtion française (France métropolitaine) R.INT.ODE/DYNECO/D 12-04, 2012. Gallego, I., T. A. Davidson, E. Jeppesen, C. Perez-Martinez, P. Sanchez-Castillo, M. Juan, F. Fuentes- Rodriguez, et al. « Taxonomic or ecological approaches? Searching for phytoplankton surrogates in the determination of richness and assemblage composition in ponds ». Ecological Indicators 18 (juillet 2012): 575‑585. doi:10.1016/j.ecolind.2012.01.002. Garmendia, Maialen, Ángel Borja, Javier Franco, et Marta Revilla. « Phytoplankton composition indicators for the assessment of eutrophication in marine waters: Present state and challenges within the European directives ». Marine Pollution Bulletin no 0. Consulté le décembre 13, 2012. doi:10.1016/j.marpolbul.2012.10.005.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Lugoli, F., M. Garmendia, S. Lehtinen, P. Kauppila, S. Moncheva, M. Revilla, L. Roselli, et al. « Application of a new multi-metric phytoplankton index to the assessment of ecological status in marine and transitional waters ». Ecological Indicators 23, no 0 (décembre 2012): 338‑355. doi:10.1016/j.ecolind.2012.03.030 Moffat, C., Aish, A., Hawkridge, J.M., Miles, H., Mitchell, P. I., McQuatters-Gollop, A., Frost, M., Greenstreet, S., Pinn, E., Proudfoot, R., Sanderson, W. G., & Tasker, M. L., 2011. Advice on United Kingdom biodiversity indicators and targets for the Marine Strategy Framework Directive. Healthy and Biologically Diverse Seas Evidence Group, Report to the Department for Environment, Food and Rural Affairs, 207pp.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Food webs

Number Previous Indicator Category code* FW-1 NA Reproductive success of marine birds in relation to food availability Core

FW-2 NA Production of phytoplankton Core

FW-3 NA Size composition in fish communities (LFI) Core

FW-4 NA Changes in average trophic level of marine predators (cf MTI) Core

FW-7 NA Fish biomass and abundance of dietary functional groups Candidate

FW-8 NA Changes in average faunal biomass per trophic level (Biomass Trophic Spectrum) Candidate

FW-9 NA Ecological Network Analysis indicator (e.g. trophic efficiency, flow diversity) Candidate

Reproductive success of marine birds in relation to food availability

1. Indicator

Name: Reproductive success of marine birds in relation to food availability

Code: FW-1 (NA)

Proposed to BDC 2013 as: Core indicator

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components attributed (species/habitat types) Partially

Applicability to sub-regions Yes

Assessment scales Yes

Monitoring parameter Yes

Monitoring frequency Yes

2. Appropriateness of the indicator

Biodiversity component: Marine Birds

MSFD criterion: 4.1 Productivity (production per unit biomass) of key species or trophic groups

MSFD indicator: 4.1.1 Performance of key predator species (mammals, seabirds) using their production per unit biomass (productivity)

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Sensitivity to Relevance to management Practicable Applicable Number of CPs Consensus among specific pressures measures across reporting/using CPs on usefulness region the indicator as part of a region (n=9) wide set (n=8)

8 8 High - Sensitive to High Depends on cause of Data on breeding Yes changes in prey changes to prey availability success for some availability, human (if fishing -high; if climate- species widely disturbance, low). available; for other contaminants and High for human disturbance, species only predation. contaminants* and available for parts predation of sub-regions (*in combination with TMAP- (e.g. Wadden monitoring of contaminants Sea). in bird eggs)

Marine birds can be highly sensitive to changes in the abundance and diversity of their primary prey, whether driven by climate, exploitation, or both (Ainley and Blight 2009, Cury et al. 2011, Montevecchi 2007, Frederiksen et al. 2007). The indicator is intended to complement another proposed indicator on annual breeding success of kittiwakes in relation to sandeel availability (under 1.3.1), in order to keep a watching- brief on the population condition of other species.

Abrupt declines in prey abundance may result in reduced marine bird breeding performance. A key point that underlines the limits of this indicator is that unless predators are actually food limited, then variation in predator performance will infer little about food web processes in lower trophic levels, and as such would not be appropriate for use as a food web indicator (Rombouts et al., in press).

The responses to declining prey may be slow and non-linear (Asseburg et al., 2006; Croxall et al., 1999; Furness and Tasker, 2000; Piatt et al., 2007). Many marine bird species are able to switch to alternative prey, and breeding success can recover after a few years (Asseburg et al., 2006; Chiaradia, 2010). So, ideally, if a bird species were to be selected as a food web indicator, the predator should have little alternative prey available in the environment so that the indicator can be linked more easily to the actual declining prey (Danhärdt et al., 2011; Furness and Tasker, 2000). Since only few species will correspond to these criteria, the selection of dietary groups (e.g. benthic intertidal feeders, surface fish eaters, deep divers, etc.) is likely to be more robust than the use of indicator species as a food web indicator.

3. Parameter/metric

‘Annual colony failure rate’ i.e. the percentage of colonies failing per year, per species (from Cook et al. 2012).

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development In this context, ‘marine birds’ include the following taxonomic groups that are commonly aggregated as ‘waterbirds’ and ‘seabirds’:

Waterbirds: shorebirds (order Charadriiformes); ducks, geese and swans (Anseriformes); divers (Gaviiformes); and grebes (Podicipediformes);

Seabirds: petrels and shearwaters (Procellariiformes); gannets and cormorants (Pelecaniformes); skuas, gulls, terns and auks (Charadriiformes).

Species selected for this indicator should be sensitive to changes in pressures such as anthropogenic impacts on their food supply, predation by non-indigenous species, disturbance and contaminants - see Furness & Tasker (2000) who applied criteria to identify the most sensitive seabird species (Table 1, in Tech Spec Birds) and Koffijberg et al. (2011) who identified species for the Wadden Sea (Table 2, in Tech Spec Birds).

These models were used to estimate the annual colony failure rate (i.e. proportion of colonies in a sample that had annual breeding success of 0.1 or less chicks fledged per pair ) for each of 17 species during 1986- 2010 (data from UK Seabird Monitoring Programme). Of these 17 species, five were selected for the indicator for the Greater North Sea (Kittiwake, Little Tern, Sandwich Tern, Common Tern and Arctic Tern) and eight for the Celtic seas indicator (Kittiwake, Common and Arctic Terns [both subject to improved monitoring], Lesser Black-backed Gull and Herring Gull), on the basis of a) sufficient data to construct a robust failure rate model that accurately predicted observed failure rates; and of b) high or moderate sensitivity to reductions in sandeel abundance, as quantified marine bird by Furness & Tasker (2000) (Table 1, in Tech Spec Birds). Arctic skua was omitted from the Greater North Sea indicator because of its limited distribution in this sub-region.

4. Baseline and Reference level

Complex baseline data for species, colonies and divisions of sub-regions are available.

5. Setting of GES boundaries / targets

The target proposed by the UK for the indicator is:

Criterion level target (1.3): Widespread seabird colony breeding failures should occur rarely in other species that are sensitive to changes in food availability.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development The aim of the target is to ensure that only a small proportion of colonies fail per year, probably due to local problems, rather than any large scale anthropogenic impact. The aim of the target of 3 years out of six is to ensure that the cumulative effect of successive failures does not have a significant impact on recruitment into the regional population. Cook et al. (2012) tested various target thresholds on each species indicator of annual colony failure rate. They found that some species e.g. terns, experience breeding failure on a regular basis, others e.g. auks, rarely fail to breed. The threshold of the 15-year mean breeding failure rate was appropriate for species that regularly failed to breed, while a fixed threshold of 5% was appropriate for highlighting failures in species that rarely fail.

6. Spatial scope

Breeding success of marine birds is monitored at colonies of a number of species throughout the NE Atlantic (see ICES 2007). Further work is needed to determine if the development of this indicator at the sub-regional scale will be restricted by lack of monitoring or data availability.

7. Monitoring requirements

The frequency at which data should be collected, annually

The monitoring method, Walsh et. Al. 1995; for Wadden Sea Koffijberg et. Al. 2011

National Monitoring Schemes in the Wadden Sea within the Who is responsible for the monitoring, Trilateral Monitoring and Assessment Programme (TMAP)

number required could be provided following further analysis Minimal required amount of monitoring locations. of existing data

Most countries in the region collect breeding productivity data on marine bird species. Further work required to determine if Does the required monitoring already exist? sufficient data are collected by each country to construct indicators for relevant species in each sub-region.

8. Reporting

Breeding failure Alerts coding (see Table 2, in Tech Spec Birds, from Cook et al. 2012):

“red alert” when target is exceeded in four or more of the preceding six years;

“amber alert” when target is exceeded in three of the preceding six years;

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development "green alert" when target is exceeded in less than three years of the preceding six.

Data needs to be collated centrally from CPs (at least at a sub-regional scale) and then analysed to produce indices, which can then be assessed against targets.

In comparison to B-3 indicator, the food-web indicator should be reported per trophic group instead of per species.

9. Resources needed

Monitoring breeding success is more straightforward in some species than others, so species-specific methods have been designed and are widely used (see e.g. Walsh et al. 1995). Generally monitoring is conducted by observing a sample of nests within a colony and recording progress from laying, hatching and fledging. This requires one or two observers visiting a colony several times during the breeding season (i.e. usually May-Aug, but varies with species). Resources required for these visits are dependent on how remote the colony is i.e. colonies on uninhabited remote offshore islands are more expensive to monitor than colonies on mainland coasts. Monitoring costs in most countries are minimised by using volunteer observers, but professional observers are sometimes used to monitor some colonies – usually those on remote offshore islands. Hence, monitoring costs will vary between countries depending on the number of colonies to be monitored, the accessibility of these colonies and on how much of the monitoring can be done by volunteers.

10. Further work

In order to apply this indicator to evaluate food web functioning, the predator-prey relationships involved need to be adequately understood (Rombouts et al., in press). As a result, dietary groups of birds could be selected, e.g. benthivores, piscivores, etc. to calculate the indicator for food webs. Further development of this indicator is currently underway in the ICES Working Group on Seabird Ecology.

To calibrate the predator performance-prey intake relationship, it is important to understand the way that prey consumption is affected by changes in the abundances of all potential prey species and therefore, some information on prey abundance will be required (Asseburg et al. 2006). These could be obtained from prey abundance estimates from fish species indicators. In turn, the variability in prey consumption can be assessed from stomach flushing and stable isotope analyses to provide indirect information on the trophic structure of the food web (Chiaradia et al. 2010). However, currently, this type of data is not collected routinely.

References:

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Ainley, D.G., Blight, L.K. 2009. Ecological repercussions of historical fish extraction from the Southern Ocean. Fish and Fisheries 10, 13-38. Asseburg, C., Harwood, J., Matthiopoulos, J., Smout, S. 2006. The functional response of generalist predators and its implications for the monitoring of marine ecosystems. In: Top predators in marine ecosystems (eds. Boyd, I.L., Wanless, S., Camphuysen, C.J.), pp. 262-274. Cambridge University Press, Cambridge. Chiaradia, A., Forero, M.G., Hobson, K.A., Cullen, J.M. 2010. Changes in diet and trophic position of a top predator 10 years after a mass mortality of a key prey. ICES J. Mar. Sci. 67, 1710-1720. Croxall, J.P., Reid, D.G., Prince P. 1999. Diet, provisioning and productivity responses of marine predators to differences in availability of Antarctic krill. Mar. Ecol. Prog. Ser. 177, 115-131. Cook A.S.C.P., Ross-Smith V.H. & Robinson R.A. 2012. Development of MSFD Indicators, Baselines and Target for Seabird Breeding Failure Occurrence in the UK. BTO Research Report No. 615. The British Trust for Ornithology, UK. Cury, P.M., Boyd, I.L., Bonhommeau, S., Anker-Nilssen, T., Crawford, R.J.M., Furness, R.W., et al. 2011. Global Seabird Response to Forage Fish Depletion - One-Third for the Birds. Science 334, 1703-1706. Danhärdt, A., Fresemann, T., Becker, P.H. 2011. To eat or to feed? Prey utilization of Common Terns Sterna hirundo in the Wadden Sea. J. Ornithol. 152, 347-357. Frederiksen, M., Edwards, M., Mavor, R.A., Wanless, S. 2007. Regional and annual variation in black-legged kittiwake breeding productivity is related to sea surface temperature. Mar. Ecol. Prog. Ser. 350, 137-143. Furness RW and ML Tasker 2000. Seabird-fishery interactions: quantifying the sensitivity of seabirds to reductions in sandeel abundance, and identification of key areas for sensitive seabirds in the North Sea. Marine Ecology Progress Series 202: 253–264. ICES. 2007. Report of the Working Group on Seabird Ecology (WGSE), 19–23 March 2007, Barcelona, Spain. ICES CM 2007/LRC:05. 123 pp. Koffijberg, K., Stefan Schrader & Veit Hennig 2011: Monitoring Breeding Success of Coastal Breeding Birds in the Wadden Sea – Methodological Guidelines and Field Manual. Joint Monitoring Group for Breeding Birds Common Wadden Sea Secretariat April 2011.Thyen, S., P.H. Becker, K.-M. Exo, B. Hälterlein, H. Hötker & P. Südbeck, 1998: Monitoring breeding success of coastal birds. Final report of the pilot studies 1996-1997. Wadden Sea Ecosystem Ecosystem No. 8. Common Wadden Sea Secretariat, Wilhelmshaven, Germany. Montevecchi, W.A. 2007. Binary dietary responses of northern gannets Sula bassana indicate changing food web and oceanographic conditions. Mar. Ecol. Prog. Ser. 352, 213-220. Piatt, J.F., Sydeman, W.J., Wiese F. 2007. A modern role for seabirds as indicators. Mar. Ecol. Prog. Ser. 352, 199-204. Rombouts, I., Beaugrand, G., Fizzala, X., Gaill, F., Greenstreet, S.P.R., Lamare, S., Le Loc’h, F., McQuatters-Gollop, A., Mialet, B., Niquil, N., Percelay, J., Renaud, F., Rossberg, A.G., Féral, J.P. (in press) Food web indicators under the Marine Strategy Framework Directive: from complexity to simplicity? Ecological Indicators. Willems, F., R. Oosterhuis, L. Dijksen, R.K.H. Kats & B.J. Ens, 2005: Broedsucces van kustbroedvogels in de Waddenzee 2005. Sovon-onderzoeksrapport 2005/07. SOVON, Beek-Ubbergen. Walsh, P.M., Halley, D.J., Harris, M.P., del Nevo, A., Sim, I.M.W., & Tasker, M.L. 1995. Seabird monitoring handbook for Britain and Ireland. Published by JNCC / RSPB / ITE / Seabird Group, Peterborough.

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Production of phytoplankton

1. Indicator

Name: Production of phytoplankton

Code: FW-2 (NA)

Proposed to BDC 2013 as: Core indicator

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components attributed (species/habitat types) Yes

Applicability to sub-regions Yes

Assessment scales Yes

Monitoring parameter Yes

Monitoring frequency Yes

2. Appropriateness of the indicator

Biodiversity component: Phytoplankton

MSFD criterion: 4.1 Productivity of key species or trophic groups

MSFD indicator: NA

Highly sensitive but high High high 7 7 medium specific – responds to multiple pressures

Phytoplankton metrics are currently being applied in the Water Framework Directive as indicators of habitat quality, however, whilst promising, further development is needed for their application as food web indicators. The proposed indicator “Production of phytoplankton” is not operational.

The phytoplankton production indicator is not very specific since it can respond to multiple pressures (hydrological changes, contaminants, nutrient inputs and climate change). However, phytoplankton groups have fast turnover rates and therefore respond rapidly to anthropogenic pressures. The indicator is highly sensitive and can be useful as an early warning indicator of direct pressures on the food web from e.g. waste

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development water discharge, agricultural practices, etc. Moreover, the indicator can be used to interpret changes in higher trophic levels that are not related to top-down pressures (e.g. selective extraction).

The indicator is practicable since the metrics could be collected during existing monitoring programmes and therefore, additional costs for monitoring will be minimal.

3. Parameter/metric

Several phytoplankton biomass indicators exist (e.g. biovolume, species composition, etc.), however, in a food web context, primary production is likely to be the most appropriate measure since it is a flux indicator of the potential for higher trophic levels to produce biomass. Moreover, considering primary production at different size ranges could provide information on the trophic efficiency between different parts of the food web. Other parameters, such as chlorophyll biomass and oxygen concentration could be used in addition to primary production so that the impacts of pressures could be more easily interpreted.

4. Baseline and Reference level

Baselines have not been defined yet. The collection of long-term time series of primary production and oxygen concentrations will help establish a seasonal pattern of reference (as an example see Boalch et al., 1978; Boalch, 1987). Upper limits of primary production will be set on an annual basis and on the basis of seasonal events (type spring bloom).

5. Setting of GES boundaries / targets

Targets have not been clearly defined yet. The setting of targets should be done separately for coastal and offshore systems. Coastal systems are indeed more vulnerable because of a generally lower water turnover rate than that of offshore systems. Biomass and production thresholds should not be set too low because these parameters also measure the capacity of ecosystems to generate and sustain resources, either through fishing or through shellfish aquaculture. As an indicator of habitat quality, the annual primary production should probably not exceed 300 g C m–2 yr–1 for coastal systems and daily values should probably be less than 2 or 3 g C m–2 day–1 at the time of phytoplankton blooms (these values should be lower for offshore regions that are generally much less naturally fertilized). In terms of biomass, chlorophyll thresholds should probably be set at > 30 g L–1 for coastal ecosystems (much less for offshore regions) but this value could be significantly different between different locations and need to be adjusted.

6. Spatial scope The metric should be adjusted according to the type of ecosystem and probably locally given the diverse capabilities of the respective environments. 7. Monitoring requirements

Currently, monitoring is focused on chlorophyll biomass and very few long-term time-series of primary production and sites that track the seasonal evolution of primary production exist. A good example, however, are the coastal and the open shelf stations, L4 and E1, in the western English Channel that has been monitored more or less regularly on a monthly basis using the research vessels of the Plymouth Marine Laboratory and the Marine Biological Association, UK (www.westernchannelobservatory.org.uk/data.php). Similar monitoring systems, such as the SOMLIT network of marine stations along the French coast, could be established to incorporate the measurement of primary production in parallel to the existing collection of other parameters of phytoplankton. In any case, it will be essential to establish a standardized protocol for data collection and analysis between Member States to facilitate a regional evaluation of GES.

8. Reporting

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Annual reports will establish the first reference seasonal patterns in different observation points selected by the Member States. In a second time, probably with maturity longer than 5 years, management actions should be undertaken if a drift of a given ecosystem is observed.

9. Resources needed

The metrics could be collected during existing monitoring programmes and therefore, costs for additional monitoring will be minimal. Costs of analyses should be refined but are about 20 euros maximum per sample in terms of material needed (for the 13C methodology). Based on a bi-monthly monitoring of surface water, the cost per station should not exceed 500 euros (excl. personnel and travel costs).

10. Further work

Throughout the OSPAR region, many monitoring sites collect data on chlorophyll biomass but very few sites track the seasonal evolution of primary production. This parameter can now be measured under safe experimental conditions using the stable isotope 13C. The latter is an essential parameter to assess food web functioning and to evaluate the potential impacts of bottom-up pressures on higher trophic levels of the food web. In order to advance the development of food web indicators, there is a general need to coordinate data collection across trophic levels over a large spatial and temporal extent.

Further work is needed to establish appropriate targets for the phytoplankton production indicator in a food web context. In setting those targets, the resilience capacity of the impacted systems should also be taken into account. Firstly, however, a comprehensive study of primary production rates across different ecosystems of the OSPAR region and the link with higher trophic levels will be needed. Many investigators have examined ratios between fishery yield/landings from an ecosystem and the underlying primary production across ecosystems (Rogers et al., 2010) and some consistency in this ratio certainly exists (Nixon 1988; Iverson, 1990; Chassot et al., 2007; Gaichas et al., 2009).

A similar promising indicator for food web efficiency at the base of the food web measures the relative flow of biomass in the food web through the microbial heterotrophic component (Turley et al. 2000). The measure is based on bacterial community biomass production (e.g. 3H-thymidine uptake) relative to autotrophic 14 planktonic primary production (e.g. HCO3- uptake method) (Turley et al. 2000). Since this indicator has relevance for fish yield, sediment flux and thereby also benthic production, further development and evaluation is highly recommended (Rogers et al., 2010). Methods can be used in routine monitoring programs at reasonable cost and with good spatio-temporal coverage.

References Boalch G.T., Harbour D.S., Butler E.I. (1978). Seasonal phytoplankton production in the western English Channel 1964-1974. Journal of the Marine Biological Association of the United Kingdom 58, 943-953.

Boalch, G.T. (1987). Changes in the phytoplankton of the Western English Channel in recent years. British Phycological Journal 22 (3), 225-235.

Chassot E, Mélin F, Le Pape O, Gascuel D (2007) Bottom-up control regulates fisheries production at the scale of eco-regions in European seas. Mar Ecol Prog Ser 343: 45–55.

Gaichas, S., Skaret, G., Falk-Petersen, J., Link, J.S., Overholtz, W., Megrey, B.A., Gjøster, H., Stock- hausen, W.T., Dommasnes, A., Friedland, K.D., Aydin, K.Y. (2009) A comparison of community and trophic structure in five marine ecosystems based on energy budgets and system metrics. Progress in Oceanography 81 (2009) 47–62.

Iverson, R.L. (1990) Control of marine fish production. Limnol. Oceanogr. 35:1593-1604.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Nixon, S.W., (1988) Physical energy inputs and the comparative ecology of lake and marine eco-systems. Limnol. Oceanogr. 33:1005-1025.

Rogers, S., Casini, M., Cury, P., Heath, M., Irigoien, X., Kuosa, H., Scheidat, M., Skov, H., Stergiou, K., Trenkel, V., Wikner, J., Yunev, O., Piha H. 2010. Marine Strategy Framework Directive Task Group 4 Report, Food Webs. In. European Commission Joint Research Centre, ICES.

Turley, C. M., Bianchi M., Christaki U., Conan P., Harris J. R. W., Psarra S., Ruddy G., et al (2000) Relationship between primary producers and bacteria in an oligotrophic sea - the Mediterranean and biogeochemical implications. Mar. Ecol.-Prog. Ser. 193: 11-18.

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Size composition of fish communities (cfr. Large Fish Indicator)

1. Indicator

Name: Size composition of fish communities (cfr. Large Fish Indicator)

Code: FW-3 (NA)

Proposed to BDC 2013 as: Core indicator

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components attributed (species/habitat types) Yes

Applicability to sub-regions Yes

Assessment scales Yes

Monitoring parameter Yes

Monitoring frequency Yes

2. Appropriateness of the indicator

Biodiversity component: Fish

MSFD criterion: 4.2 Proportion of selected species at the top of food webs

MSFD indicator: 4.2.1 Large fish (by weight)

High High High High 8 8

The LFI as an OSPAR EcoQO for the North Sea is fully operational. It is part of the indicator suite that member states have to report on under the Data Collection Framework to evaluate the effects of fishing on the ecosystem (2010/93/EU). There is a medium degree of consensus amongst Contracting Parties for inclusion of the indicator as a common indicator for food webs (see “Further work”).

The Large Fish Indicator takes no account of species identity but rather of individual sizes. However, it was shown to reflect mostly the proportion (by weight) of large-bodied species in communities (Shephard et al. 2011). Large-bodied species tend to be more vulnerable to fishing, which is why the LFI is sensitive (Greenstreet et al. 2011, ICES 2011) and specific (Houle et al. 2012) to fishing pressure. Models (ICES 2011, Shephard et al. 2013) and data (Fung et al. 2012) suggest that recovery of the indicator from pressures can be slow (lasting several decades), implying good responsiveness to unsustainable exploitation. Because the distribution of biomass over body sizes (size spectra; Kerr and Dickie 2001) is an

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development emergent property of food webs, size-based metrics that are sensitive and specific to pressures can be used as indicators of food web structure. The indicator’s definition is simple and easily communicated.

3. Parameter/metric

According to SEC (2008), the LFI is calculated as:

W40cm P40cm  WTotal where W>40cm is the weight of fish longer than 40 cm and WTotal is the total weight of all sampled fish. Weights are estimated from numbers at length for each species using the formula W=a*(length)b, where the parameters a and b have to be determined for each species empirically, from the literature, or using databases (e.g. www.fishbase.org). The indicator is survey specific. The “large” fish threshold may need to be adjusted depending on survey and indicator purpose, i.e. as a diversity or food web indicator. Optimal threshold values balance low fluctuations due to recruitment variability and sampling errors with sensitivity to pressures. The OSPAR EcoQO is based on the North Sea IBTS data and defines the size threshold of 40 cm. Up- and downscaling is simplified when the same size threshold is used throughout regions.

4. Baseline and Reference level

The baseline has been defined in some areas (e.g. North Sea, Celtic Sea).The baseline should reflect historical conditions where overall exploitation was considered to be sustainable. A reference level of 0.3 has been specified for the LFI for the North Sea IBTS surveys, and this has been adopted as the OSPAR EcoQO for the North Sea fish community. A reference level has been proposed for the West Coast Ground Fish Survey (WCGFS), which is for 0.4 of the fish community by weight to be larger than 50cm (Shepherd et al. 2011), however the WCGFS was discontinued in 2004.

5. Setting of GES boundaries / targets

The targets have been defined in some areas (e.g. North Sea). For each region the proportion (by weight) of fish greater than a specific size caught during routine demersal fish surveys (e.g. the ICES International Bottom Trawl Survey) should reach or exceed the reference level.

6. Spatial scope

This indicator should be applied at the sub regional level or at the survey level. Appropriate aggregation methods across surveys within subregions still need to be developed

7. Monitoring requirements

Data for this metric come from scientific fisheries surveys which ideally sample the entire fish community. Current implementations, however, focus on demersal habitats. The metric requires that surveys are conducted at regular intervals (e.g., annually) in the same area with a standard gear. Sufficiency of available sample sizes can be judged using re-sampling techniques (Shephard et al. 2012).

Currently, the most important data source for the LFI is fisheries groundfish surveys which are conducted as part of the ICES and IGFS international bottom trawl survey programme in the North Sea, the Celtic Seas, Bay of Biscay and Iberia (see figure 1).

8. Reporting

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development The LFI is part of the indicators that member states have to collect for the data collection framework. The raw data from the IBTS surveys are uploaded into the ICES DATRAS data base and can be used for indicator calculation. Several ICES working groups and STECF have evaluated this indicator based on contributions from member states, but there is currently no formal reporting structure where every member states supplies the results of this indictor on a regular basis. There is potential for developing a more formal reporting structure through ICES or the regional databases which will form part of the new Data Collection framework (ref).

9. Resources needed

The resources needed for this indicator are estimated to be high, but costs primarily met under the national programmes and the Data collection framework. Current monitoring requirements are covered under the DCF and a gap analysis would be necessary to identify any subregions or ecosystems that are not adequately covered. Reporting, data analysis and development as well as assessment could be carried out within the ICES framework under WGBIODIV, WGECO or regional ecosystem assessment working groups. It is assumed that management measures would relate to fisheries and come under the CFP.

10. Further work

The trans-regional applicability of the LFI still needs to be demonstrated. Whereas the LFI has been validated in the North Sea, adaptation and interpretation of the metric for other region, e.g. the southern part of the Bay of Biscay, has so far remained inconclusive. Calculations of the LFI in other parts of European waters, e.g. Northern part of Bay of Biscay, West Scotland and the Baltic, are currently being carried out by the European Scientific Technical and Economic Committee for Fisheries (STECF). Development of the indicator is also ongoing within ICES working groups (WGECO).

As currently defined, the LFI acts as an indicator of the “health” of the demersal fish community in response to variation in fishing pressure and might therefore exclude important parts of the marine food web. To close this gap, the LFI needs further development, examination, and validation (see case study; ICES, 2012; Rombouts et al., in press).

Further work will be needed in terms of:

a. Species selection:

Careful consideration will need to be given on the selection of species to include in the analysis. Selection criteria should include coverage by the surveys used and ecological significance. For the purpose of characterizing food-web structure, inclusion of pelagic species is desirable and inclusion of non-fish species, as conventionally done for the MTI, should be considered.

b. Metric development:

The metric of the indicator needs to be further refined and agreed among CPs who share MSFD subregions. In order to ensure transparency and repeatability of the indicator, step by step calculation methods (e.g. Fung et al. 2012) should be specified as ‘pseudo-code’ or flow diagrams, including defined data clearing routines applied to central datasets (such as ICES’ DATRAS database), and a defined list of biological parameters used in the calculations (such as a and b parameters).

c. Target setting:

Targets to be established for each marine region relative to a region-specific reference period, and dependent on the species included in the indicator calculation.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development The indicator “Fish biomass of dietary groups” (4.7; ICES 2012) could provide complementary information to the Large Fish Indicator on the composition of the fish community.

References

Fung, T., Farnsworth, K. D., Reid, D. G., Rossberg, A. G., 2012. Recent data suggest no further recovery in North Sea Large Fish Indicator. ICES Journal of Marine Science 69 (2), 235–239.

Greenstreet, S. P. R., Rogers, S. I., Rice, J. C., Piet, G. J., Guirey, E. J., Fraser, H. M. & Fryer, R. J., 2011. Development of the EcoQO for the North Sea fish community. ICES Journal of Marine Science 68, 1-11.

Houle, J. E., Farnsworth, K. D., Rossberg, A. G., Reid, D. G., 2012. Assessing the sensitivity and specificity of fish community indicators to management action. Canadian Journal of Fisheries and Aquatic Sciences 69 (6), 1065–1079.

ICES, 2011. Report of the Working Group on the Ecosystem Effects of Fishing Activities (WGECO). ICES Document CM 2011/ACOM: 24, Copenhagen.

Kerr, S. R. & Dickie, L. M., 2001. The biomass spectrum: a predator prey theory of aquatic production. New York: Columbia University Press.

Rombouts, I., Beaugrand, G., Fizzala, X., Gaill, F., Greenstreet, S.P.R., Lamare, S., Le Loc’h, F., McQuatters-Gollop, A., Mialet, B., Niquil, N., Percelay, J., Renaud, F., Rossberg, A.G., Féral, J.P. (in review) Food web indicators under the Marine Strategy Framework Directive: from complexity to simplicity? Ecological Indicators

Shephard, S., Reid, D. G. & Greenstreet, S. P. R., 2011. Interpreting the large fish indicator for the Celtic Sea. ICES Journal of Marine Science 68, 1963-1972.

Shephard, S., Fung, T., Houle, J. E., Farnsworth, K. D., Reid, D. G., Rossberg, A. G., 2012. Size-selective fishing drives species composition in the Celtic Sea. ICES Journal of Marine Science 69 (2), 223–234.

Shephard, S., Fung, T., Rossberg, A. G., Farnsworth, K. D., Reid, D. G., Greenstreet, S. P. R., and Warnes, S. (2013), Modelling recovery of Celtic Sea demersal fish community size-structure. Fish. Res., in press, http://dx.doi.org/10.1016/j.fishres.2012.12.010 .

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Fig. 1) Distribution of the national groundfish surveys that are part of the ICES International bottom trawl survey (from ICES IBTSWG 2012).

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Case study FW-3 – Potential application Intensive exploitation of the target species usually at the highest trophic level can result in significant changes in the abundance and composition of the lower trophic levels, and thus the ecosystem as a whole. Currently, the calculation of the LFI only includes a single component of the food web and it does not take into account, for example, pelagic fish species which constitute a high proportion of the diet of demersal piscivores. Therefore, additional information on trophic structure is needed to interpret the LFI in a food web context. Information on the trophic structure of the fish community can be obtained by assigning fish species within a food web to their respective feeding or trophic guilds and monitor their relative changes in biomass.

Currently, a Trophic Guild Indicator is being developed (Paula Haynes, pers. comm.) and the preliminary results were presented at the ICES WGECO 2012. Trophic guild time series were calculated for three fisheries surveys operating in the MSFD ‘Celtic Seas’ sub region, in order to describe changes in the broad trophic structure of the fish community as expressed in these survey data. The surveys included the UK West Coast Ground Fish Survey, the Irish Groundfish Survey (Celtic Sea), and the Irish Sea Survey.

A previous study on the Celtic Sea computed the Large Fish Indicator (LFI), which characterizes the size composition of the fish community, and found an overall reduction in the proportion of large fish in the area (Shephard et al., 2011). Interestingly, as demonstrated by the Trophic Guilds indicator used here, the change in size structure was not reflected by a change in the trophic guild composition (Fig. 1). The biomass abundances of trophic guilds fluctuated without trends, as opposed the continuous decline in the abundance of fish found using the LFI. Therefore, the Trophic Guilds Indicator is providing complementary information to the LFI on the composition of the fish community. This approach, accounting for ontogenetic changes which occur in the diet of fish when assigning them to trophic guilds, does therefore allow for the identification of trends in the size composition of community structure over time.

400000 Planktivore 0.600 Pelagic piscivore 350000 Demersal piscivore 0.500 ength 300000 Benthivore

-2 LFI 0.400 250000

200000 0.300

150000

Biomass Km Kg 0.200 100000 0.100 50000

0 0.000 1986 1989 1992 1995 1998 2001 2004 Year

Proportion (by weight) of in Proportionfishl (by >50cm weight)

Figure 1. Trends in abundance (Kg Km-2) of key functional groups of fish in the Celtic Sea fish community (WCGFS data). The LFI time-series is taken from Shephard et al. (2011). From ICES, 2012.

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Changes in average trophic level of marine predators (e.g. Marine Trophic Index)

1. Indicator

Name: Changes in average trophic level of marine predators (e.g. Marine Trophic Index)

Code: FW-4 (NA)

Proposed to BDC 2013 as: Core indicator

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components attributed (species/habitat types) Yes

Applicability to sub-regions Yes

Assessment scales Yes

Monitoring parameter Yes

Monitoring frequency Yes

2. Appropriateness of the indicator

Biodiversity component: Ecosystem

MSFD criterion: 4.3 Abundance/ distribution of key trophic groups and species

MSFD indicator: 4.3.1 Abundance trends of functionally important selected key trophic groups/species

High High High High 8 8

In February 2004 the Marine Trophic Index (MTI) was adopted by the Conference of the Parties to the Convention on Biological Diversity (CBD) as one of eight indicators to monitor achievement of a significant reduction in the current rate of biodiversity loss by 2010. MTIs at different scales are available from the Sea Around Us website, hosted by the Fisheries Centre of the University of British Columbia (http://www.seaaroundus.org/). This indicator is highly developed and currently applied globally across ecosystems (www.indiseas.org).

An important advantage of this indicator is that the proposed concept is transferable across OSPAR regions. However, mean trophic levels of species will need to be estimated on a regional/sub-regional scale. Also, this indicator is practicable since abundance data from existing scientific surveys can be used. As such, the

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Fisheries have been demonstrated to have an especially marked impact on predators, whose abundance can be severely depleted. The MTI was developed to assess the impacts of fishing on food webs, it is thus specific (Pauly and Watson, 2005). However, in certain fish communities, the mean trophic level has been found to be rather insensitive to fishing impacts (e.g. North Sea: Jennings et al., 2002). Nevertheless, it is easy-to-estimate and has been widely applied as a „large-scale‟ indicator of the health of both fisheries and marine ecosystems, using the full range of ecosystem trophic levels, and for areas of different spatial scales in both data-rich (e.g., Canada, Iceland, North-Sea) and data-poor areas (e.g., Greece, Cuba, Portugal, India, Brazil, Uruguay) (Pauly et al. 1998, Pauly and Watson 2005, Cury et al. 2005).

3. Parameter/metric

MTI is calculated using both estimates of species abundances, usually derived from scientific surveys, and their mean trophic level. The trophic level (TL) expresses the position of an organism in a food web, and is estimated using data from dietary analyses. Ideally mean trophic levels are estimated from local gut contents and isotopes analyses. Otherwise, estimates from trophic models such as Ecopath or estimates from online data portals, such as FishBase, can be used. Only predators whose TL is higher than 3.25 are considered.

4. Baseline and Reference level

Baselines have been determined in some regions. The MTI has to be known from a past state of the ecosystem assumed to be not impacted (or little impacted) by fishing at the ecosystem scale. Alternatively, the pristine ecosystem state can be simulated and the MTI estimated, using trophic models such as Ecopath with Ecosim (Christensen and Pauly 1992, Walter et al. 1997) or EcoTroph (Gascuel 2005, Gascuel and Pauly 2005).

During a preliminary phase and in order to determine an appropriate reference, the ecosystem MTI, estimated from surveys, should be compared to the MTI of landings, which can be biased by fishing strategies (highlighting the “Fishing through the food-web” phenomena) but which can usually been estimated over a much longer period of time, using the past catch statistics.

5. Setting of GES boundaries / targets

The target is an “acceptable” deviation from the baseline and should be determined for each ecosystem individually. Alternatively, a low impacted system could be used as a reference and in that case, the measured MTI should not statistically be different from the reference MTI.

6. Spatial scope

The MTI is applicable as an indicator of marine functional diversity at the regional or sub-regional level, taking into account the exploitable fraction of the ecosystem (benthic and pelagic components).

7. Monitoring requirements

Estimates of mean trophic levels or MTI derived from catch statistics have been criticized due to potential biases induced by changes occurring in the fishing strategies (Branch et al. 2010). Such biases do not arise when scientific survey data is used.

Routine fishery-independent surveys can be used (e.g. data collected from the shelf seas by research vessels: Pinnegar et al., 2002), for different spatial and temporal scales, for example from localised ecosystems such as enclosed bays, to larger areas such as the Large Marine Eco-systems or wider oceanic areas, using annual or seasonal data (Rogers et al., 2010). However, the task of assembling data sets

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In order to establish trophic relationships more accurately so that trophic levels can be estimated, data on species feeding habits is urgently needed. Currently, comprehensive datasets on the feeding ecology of many of the key species in marine food webs are insufficient, and this is especially true for species at lower trophic levels. The first requirement therefore is further extensive data collection to fill these gaps in our knowledge of food web structure and connectivity (Carafa et al., 2007, Moloney et al., 2010; Rossberg et al., 2011). Hence, we suggest that large-scale surveys should aim to collect data for dietary analyses, such as isotopic, fatty acid, stomach content, contaminant analyses and visual observations, more systematically.

8. Reporting

To be completed

9. Resources needed

To be completed

10. Further work

The estimation of MTI is based on a few assumptions and has drawbacks (Rogers et al., 2010). The trophic level (TL) of fish can be variable in time and space so the use of a generic TL value might affect the MTI value and the significance and sign of the trend. Before this indicator can be fully operational throughout European Regional Seas, further work is necessary to agree on TL values of fish species (such as those already provided by FishBase www.fishbase.org) and those for other components (such as benthic invertebrates) which may also be available. Dietary analyses should be carried out at a regional scale to further investigate the nature and spatial and temporal variability of trophic relationships so that more accurate estimates of trophic levels can be obtained. Temporal changes in trophic level of a species or group of species can indicate progressive changes in prey and can be used to highlight adverse effects on food web status.

Further regionalisation of the indicator is needed and for this purpose, the use of case studies with long-time series data across regions will help to identify a reference level and interpret potential deviations.

References

Branch, T and Watson, R and Fulton, E and Jennings, S and McGillard, C and Pablico, G and Ricard, D and Tracey, S, 2010. Trophic fingerprint of marine fisheries, Nature, 468: 431-435.

Carafa, R., Dueri, S., Zaldívar, J.M. 2007. Linking terrestrial and aquatic ecosystems: Complexity, persistence and biodiversity in European food webs. In: EUR 22914 EN, Joint Research Centre.

Christensen, V., and Pauly, D. 1992. The ECOPATH II—a software for balancing steady-state ecosystem models and calculating network characteristics. Ecological Modelling, 61: 169–185.

Cury, P. M., Shannon, L. J., Roux, J-P, Daskalov, G. M., Jarre, A., Moloney, C. L., and Pauly, D. 2005. Trophodynamic indicators for an ecosystem approach to fisheries. ICES Journal of Marine Science, 62: 430- 442.

Gascuel, D. 2005. The trophic-level based model: a theoretical approach of fishing effects on marine ecosystems. Ecological Modelling, 189: 315–332.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Gascuel, D., and Pauly, D. 2009. EcoTroph: modelling marine ecosystem functioning and impact of fishing. Ecological Modelling, 220: 2885–2898.

Jennings, S., Greenstreet, S.P.R., Hill, L., Piet, G.J., Pinnegar, J.K., & Warr, K. (2002) Long-term trends in the trophic structure of the North Sea fish community: evidence from stable-isotope analysis, size-spectra and community metrics. Marine Biology, 141, 1085-1097.

Pauly, D., Christensen, V., Dalsgaard, J., Froese, R., and Torres, F. C. 1998. Fishing down marine food webs. Science, 279: 860–863.

Pauly, D., and Watson, R. 2005. Background and interpretation of the Marine Trophic Index as a measure of biodiversity. Philosophical Transactions of the Royal Society of London, Series B, 360: 415–423.

Moloney, C.L., St John, M.A., Denman, K.L., Karl, D.M., Koster, F.W., Sundby, S., Wilson, R.P. 2010. Weaving marine food webs from end to end under global change. J. Mar. Syst. 84, 106-116.

Rossberg, A. G., Farnsworth, K. D., Satoh, K., Pinnegar, J. K., 2011. Universal power-law diet partitioning by marine fish and squid with surprising stability-diversity implications. Proc. R. Soc. B 278 (1712), 1617–1625.

Walters, C., Christensen, V., and Pauly, D. 1997. Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Reviews in Fish Biology and Fisheries, 7: 139–172.

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Change of plankton functional types (life form) index Ratio between: Gelatinous zooplankton & Fish larvae, Copepods & Phytoplankton; Holoplankton & Meroplankton

Code: FW-5 (NA)

Proposed to BDC 2013 as: Core indicator

NOTE: The text for this indicator is the same detail as provided for PH-1

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Biomass, species composition and spatial distribution of zooplankton

1. Indicator

Name: Biomass, species composition and spatial distribution of zooplankton

Code: FW-6 (NA)

Proposed to BDC 2013 as: Candidate indicator

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components attributed (species/habitat types) Yes

Applicability to sub-regions No

Assessment scales No

Monitoring parameter Yes

Monitoring frequency No

2. Appropriateness of the indicator

Biodiversity component: Plankton

MSFD criterion: 4.3 Abundance/ distribution of key trophic groups and species

MSFD indicator: 4.3.1 Abundance trends of functionally important selected key trophic groups/species

Unknown Medium High High 6 6

This indicator is partly implemented by HELCOM but will need further testing and development; the indicator is thus currently not operational.

Zooplankton constitutes an important link between primary producers and higher trophic levels in the food web where they play an important role in the energy transfer. In many coastal systems, such as in the Bay of Biscay, for example, phytoplankton and zooplankton are responsible for strong bottom-up processes that control the structure and dynamics of upper trophic levels (Lassalle et al. 2011). Long-term changes in the biomass, species composition and size structure of zooplankton communities can be used to indicate environmentally driven changes in the pelagic system (Beaugrand et al. 2005, Beaugrand et al. 2010), and the possible impact of anthropogenic pressures such as nutrient enrichment and oil spills (HELCOM 2012). The zooplankton indicator is not very specific since it can respond to multiple pressures, however,

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development zooplankton groups have fast turnover rates and therefore respond rapidly to changes in the environment and anthropogenic pressures.

An important advantage of plankton indicators is that the proposed concepts are relatively easy transferable across European waters. The indicator is straightforward to measure.

3. Parameter/metric

Biomass (expressed as µg C/m2, for example) is calculated using abundance of zooplankton and their individual weight or mean length. If length measurements are to be used, a species and/or size specific conversion factor will need to be applied.

[ADD EQUATION FOR THE CALCULATION OF BIOMASS]

Zooplankton community structure can be defined in terms of its species composition (diversity index) or in terms of its size structure (size spectra).

4. Baseline and Reference level

The baseline has not been determined yet. The baseline can be defined using historical data but this may not reflect GES. The reference period will probably have to be adjusted depending on the length of the time series in the specific area.

5. Setting of GES boundaries / targets

The targets have not been determined yet. This indicator will need a trend based target, i.e. the zooplankton community structure and biomass is not significantly influenced by anthropogenic drivers.

6. Spatial scope

The scale of assessment has not been defined yet. This indicator will probably be assessed at the regional level/pelagic habitat level.

7. Monitoring requirements

Preferably, the frequency of sampling should be monthly or preferable bi-weekly during the productive season. The indicator should be updated and assessed annually or every other year. Minimal amount of monitoring locations will be dependent on amount of habitats.

To obtain comparable results across the OSPAR region, a standard protocol for sampling and analysis should be agreed. In the HELCOM area, for example, a vertical haul of 90 µm WP2-net is being used to sample mainly macro-zooplankton (HELCOM 2012). Platforms of opportunity (e.g. ferries and merchant ships) can provide a cost-effective means to collect large spatial oceanographic data by on-board observers or by carrying scientific instruments (Evans and Hammond, 2004; Kiszka et al. 2007). For example, the European FerryBox Network incorporates 11 research institutes from eight countries and deploys automated sensors for measuring biological, chemical, and physical variables, which are attached to commercial ferries. Other projects include the Continuous Plankton Recorder (CPR) survey, the largest plankton monitoring programme in the world. The plankton sampling instrument is towed from merchant ships on their normal sailings and has monitored the presence or abundance of more than 400 plankton species on a monthly basis over the North Atlantic since 1946. Semi-quantitative data from towed sampling devices such as the Continuous Plankton Recorder may complement but not replace the quantitative data from vertical tows.

The analysis of species composition, abundance and size of individual organisms are usually performed using microscopy but automated imaging techniques and/or molecular methods may complement microscopy in the future. Image analysis can also be used to analyse zooplankton that has been sampled

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development using traditional methods, e.g. by nets, pumps or water bottles. ZOOSCAN, for example, is an automatic image technique for zooplankton identification and enumeration (Gorsky et al. 2010). However, the speed of analysis is comprised by the accuracy of identification and therefore, human visual recognition will still be needed to identify organisms at the species level. One of the advantages of this type of data analysis, however, is that a homogenous and secure digital zooplankton image data bank can be established and can be used for comparison of images across systems world-wide.

In order to advance the development of food web indicators, there is a general need to coordinate data collection across trophic levels over a large spatial and temporal extent. In terms of zooplankton, microzooplankton and gelatinous zooplankton are generally undersampled groups across the OSPAR region and adapted protocols will need to be established to adequately sample these groups (e.g. the use of a 690- 700 µm Regent-net to sample gelatinous zooplankton; Priscilla Licandro, pers. comm.).

8. Reporting If the target is not met, management actions should be taken. Agreements should be made between states on how to report the results to facilitate comparisons between monitoring programs. 9. Resources needed

The indicator has to be further assessed and calibrated between Member States in order to standardize data sets.

10. Further work

This indicator is at the developmental stage and still needs to be tested and adapted by Member States. Before this indicator can be adopted, further research will be necessary to understand the responses of zooplankton to changes in water quality (HELCOM 2012) and the effects of these responses on higher trophic levels.

Baseline and reference values will need to be developed depending on the length of the time series and sampling frequency/method.

Enumeration procedures and weight estimate procedures should be calibrated between Member States to ensure comparable data between habitats/regions.

References

Beaugrand, G. 2005. Monitoring pelagic ecosystems using plankton indicators, ICES Journal of Marine Science, 62: 333-338.

Beaugrand, G., Edwards, M., Legendre, L. 2010. Marine biodiversity, ecosystem functioning and carbon cycles. Proc. Natl. Acad. Sci. U.S.A. 107, 10120-10124.

Evans, P.G. and Hammond, P.S. 2004. Monitoring cetaceans in European waters. Mammal Review, 34: 131–156.

Gorsky, G., Ohman, M.D., Picheral, M., et al. 2010. Digital zooplankton image analysis using the ZooScan integrated system. Journal of Plankton Research, 32: 285–303.

Kiszka, J., Macleod, K., Van Canneyt, O., Walker, D. and Ridoux, V. 2007. Distribution, encounter rates, and habitat characteristics of toothed cetaceans in the Bay of Biscay and adjacent waters from platform-of- opportunity data. ICES Journal of Marine Science, 64: 1033–1043.

HELCOM, 2012. Development of the HELCOM core-set indicators Part B. GES 8/2012/7b, Brussels.

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Fish biomass and abundance of dietary functional groups

1. Indicator

Name: Fish biomass and abundance of dietary functional groups

Code: FW-7 (NA)

Proposed to BDC 2013 as: Candidate indicator

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components attributed (species/habitat types) Partially

Applicability to sub-regions No

Assessment scales No

Monitoring parameter Yes

Monitoring frequency No

2. Appropriateness of the indicator

Biodiversity component: Fish

MSFD criterion: 4.3 Abundance/ distribution of key trophic groups and species

MSFD indicator: 4.3.1 Abundance trends of functionally important selected key trophic groups/species

Sensitivity to Relevance to Practicable Applicable Number of CPs Consensus among specific pressures management across region reporting/using the CPs on usefulness as measures indicator (n=9) part of a region wide set (n=8)

Medium Medium High High 7 7

The concept is currently under development (ICES 2012) but is not operational yet.

Contrasting other indicators for food web ecological status, this indicator relates to absolute biomasses. Marine food web couple fish community production and biomass to primary production (Chassot et al., 2007; Moreau and De Silva, 1991; Thurow, 1997; Ware and Thomson, 2005). By monitoring both the biomass of fish and primary production (or proxies thereof), an imbalance in this coupling can be detected. Fish community biomass has been shown to recover from overexploitation on a decadal timescale (McClanahan 2007). Differentiation between trophic/functional groups in fish biomass time series is recommended because (i) survey catchability differs by functional group and corrections for this are difficult (ii) changes in system-level trophic efficiency can so be distinguished from changes in the dominant trophic pathways, among others. Traditionally, the coupling between primary production and fish is investigated in terms of long-term total yield as a measure of fish production. However, in situations where management measures

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development can lead to changes in exploitation rates, total fish biomass becomes the more informative metric. The metric is easily understood and communicated.

3. Parameter/metric

Fish abundance and biomass are expected to decrease in exploited populations (Beverton and Holt, 1957), and this applies to target and non-target species that are taken as by-catch and are exposed to similar impacts. Some non-target species can increase in abundance because of lower predation by depleted target predator species (Rochet and Trenkel, 2003). The biomass of fish can be calculated from abundance data using existing scientific survey data. Fish species will need to be assigned to feeding groups or trophic guilds, based on information from dietary analyses.

4. Baseline and Reference level

A baseline level has not been determined yet. Several studies have shown a strong coupling between fish biomass or production and primary production or nutrient concentration (Chassot et al., 2007; Moreau and De Silva, 1991; Thurow, 1997; Ware and Thomson, 2005). These studies allow definition of baseline and reference levels for the indicator in relation to corresponding data for primary production. Where reference levels are not known due to the absence of appropriate time series, trend targets can be set. The trend in population abundance/ biomass should alter in a predictable specified direction towards community recovery.

5. Setting of GES boundaries / targets

Targets have not been determined yet. Eutrophication of marine ecosystems goes along with enhanced fish biomass and production, but also with adverse disturbances of marine communities (Thurow, 1997). Target setting therefore requires addressing two questions: (a) A target for the fish biomass relative to that supported by current primary production (baseline value target). (b) A target for primary production. Because the latter involves trade-offs in societal goals, target setting on scientific grounds might be difficult.

6. Spatial scope

The scale of assessment has not been determined yet. This indicator will likely be applied at the sub-regional level or at the survey level. Appropriate aggregation methods across surveys within subregions still need to be developed.

7. Monitoring requirements

Data for this metric can be used from scientific fisheries surveys, such as the national groundfish surveys that are part of the ICES International bottom trawl survey. [PELAGIC MONITORING? DO SIMILAR PROGRAMMES EXIST??] The metric requires that surveys are conducted at regular intervals (e.g. annually) in the same area with a standard gear. Sufficiency of available sample sizes can be judged using re-sampling techniques (Shephard et al. 2012).

Similar data will also be needed for indicator FC-1 “Population abundance/ biomass of a suite of selected species”.

8. Reporting

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development are used for the reporting and publishing of other species abundance indicators such as WGNAPES and WGMEGS. Most of the species which are reported on are commercial species. There is potential for developing more reporting of non-commercial species through ICES working groups such as WGBIODIV.

9. Resources needed

10. Further work

The indicator is currently available as a prototype only (ICES 2012). Questions that need to be addressed are, among others, how to incorporate the coupling to nutrient status and/or primary production operationally, how good indicator reproducibility based on current survey data is, and what levels of nutrient load and fish productivity/biomass are desirable.

In any case, this indicator could provide complementary information to the Large Fish Indicator on the composition of the fish community.

References

Chassot, E., Mélin, F., Le Pape, O., Gascuel, D. (2007). Bottom-up control regulates fisheries production at the scale of eco-regions in European seas. Marine Ecology Progress Series, 343(7), 45-55.

ICES, 2012. Report of the Working Group on the Ecosystem Effects of Fishing Activities (WGECO). ICES Document CM 2012/ACOM: 26, Copenhagen.

McClanahan, T. R., Graham, N. A., Calnan, J. M., MacNeil, M. A. (2007). Toward pristine biomass: reef fish recovery in coral reef marine protected areas in Kenya. Ecological Applications, 17(4), 1055-1067.

Moreau, J., De Silva, S. S. (1991). Predictive fish yield models for lakes and reservoirs of the Philippines, Sri Lanka and Thailand (Vol. 319). Food & Agriculture Org.

Thurow, F. (1997). Estimation of the total fish biomass in the Baltic Sea during the 20th century. ICES Journal of Marine Science: Journal du Conseil, 54(3), 444-461.

Ware, D. M., Thomson R. E. (2005). Fish Production in the Northeast Pacific Bottom-Up Ecosystem Trophic Dynamics Determine Science 308, 1280-1284.

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Changes in average faunal biomass per trophic level (Biomass Trophic Spectrum)

1. Indicator

Name: Changes in average faunal biomass per trophic level (Biomass Trophic Spectrum)

Code: FW-8 (NA)

Proposed to BDC 2013 as: Candidate indicator

State of methodological development:

Development step Defined

Indicator metrics Yes

Ecosystem components attributed (species/habitat types) Partially

Applicability to sub-regions Yes

Assessment scales Yes

Monitoring parameter Yes

Monitoring frequency Yes

2. Appropriateness of the indicator

Biodiversity component: Ecosystem

MSFD criterion: 4.3 Abundance/ distribution of key trophic groups and species

MSFD indicator: 4.3.1 Abundance trends of functionally important selected key trophic groups/species

Medium Medium Medium High 5 5

Whereas the currently proposed indicator 4.3.1. is suggested to relate to a single group/species, biomass could be considered over several trophic levels simultaneously. The BTS is an example of such an ecosystem-based indicator that allows a more holistic view of the food web structure than species/population indicators.

The BTS has already been used to assess trophic structure and functioning in relation to fishing pressure (Gascuel et al. 2005, 2011) in various ecosystems within (e.g. Bay of Biscay) and outside (e.g. Guinea and Mauritania) the OSPAR region. Therefore, this indicator can be considered as well developed but not operational yet in a management context.

An important advantage of this indicator is that the proposed concept is transferable across OSPAR regions, however, mean trophic levels of species will need to be estimated on a regional/sub-regional scale. Also, this indicator is practicable since data on fish and invertebrates are collected simultaneously on existing scientific

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The BTS can be an appropriate indicator to monitor global changes in the food web, as well as reductions in abundance of predators. Since the indicator has initially been developed to evaluate the impacts of fishing pressure on food webs, it responds mainly to this pressure. However, other pressures, such as pollution and climate change, can also affect biomass at various trophic levels and thus this indicator may respond to multiple pressures. Further development will be needed to understand the responsiveness of the indicator to pressures other than fishing.

Some studies analysed changes or differences between BTS in a statistical way. For instance, bootstrap techniques have been use do demonstrate significant differences in BTS from protected and non-protected areas (Gascuel et al. 2005) while GLM were used to identify changes over time in Senegalese BTS (Laurans et al. 2004). Sensitivity analyses were also performed in case where BTS were derived from ecosystem models (Gascuel et al. 2011, Gasche et al. 2012, Colleter et. al. 2012).

3. Parameter/metric

Using survey data or model outputs, abundances per species or group (usually expressed in tons/km2) are distributed on a range of trophic levels around the mean trophic level of the species or group, and according to the variability between individuals. The trophic level (TL) expresses the position of an organism in a food web, and is estimated using diet data. Mean TLs can be derived either (and preferably) from local gut contents and isotopes analyses, or from trophic models such as Ecopath, or by using estimates from online data portals, such as FishBase. BTS are usually built using an empirical smooth function distributing each population or group across TLs according to a lognormal distribution whose standard error increases with TLs. The BTS is the sum of the distributions for all species or groups.

4. Baseline and Reference level

If a past state of the ecosystem can be independently considered as representative of GES, its BTS can obviously be considered as the reference level. Otherwise, an ecosystem model has to be built and can be used to simulate pristine state which can be considered as the reference state.

During a preliminary phase and in order to determine an appropriate reference, BTS should be compared to Catch trophic spectrum (CTS), which can usually been estimated over a long period of time, using past catch statistics.

5. Setting of GES boundaries / targets

The current BTS should not be statistically different from the reference BTS. Setting the target still requires further development. It could be based on the following: a minimal acceptable level of the ratio BTScurrent/BTSreference for all trophic levels (between 2 and 5 or 6); a maximum acceptable change in the BTS slope; a minimum value for the trophic level of first fishery-induced decrease.

6. Spatial scope

BTS is applicable at the level of region or sub-region, taking into account all marine animals simultaneously (mammals, finfish, invertebrates, etc.). BTS can for instance be estimated for the large European ecosystems defined as reference for the implementation of the Ecosystem Approach to Fisheries Management (EAFM), by the European Scientific Technical and Economic Committee for Fisheries (STECF). BTS can also be estimated either for demersal or pelagic organisms only.

7. Monitoring requirements

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development In order to establish trophic relationships more accurately so that trophic levels can be estimated, data on species feeding habits is urgently needed. Currently, comprehensive datasets on the feeding ecology of many of the key species in marine food webs are insufficient, and this is especially true for species at lower trophic levels. The first requirement therefore is further extensive data collection to fill these gaps in our knowledge of food web structure and connectivity (Carafa et al. 2007, Moloney et al. 2010, Rossberg et al. 2011). Hence, we suggest that large-scale surveys should aim to collect data for dietary analyses, such as isotopic, fatty acid, stomach content, contaminant analyses and visual observations, more systematically.

The development of a monitoring strategy might be difficult since the indicator integrates many components of the food web. Currently, biomass data to calculate the BTS have been derived from abundances of all fish and benthic invertebrate species collected during existing scientific surveys, for example, in the Bay of Biscay (EVHOE) and in the North Sea (IBTS). Other existing large-scale survey data do exist in all European seas and could be used for this purpose.

BTS can also been derived from more complete ecosystem models (such as Ecopath or EcoTroph) and then used to compare the current state of a given ecosystem to its simulated pristine state. Such an approach has for instance been used in the Bay of Biscay to assess the fishing impact on the food web and more particularly on top predators (Lassalle et al. 2012). It has also been applied to assess the efficiency of Marine Protected Areas (Libraleto et al. 2010; Colleter et al. 2012; Vall et al. 2012).

8. Reporting

9. Resources needed

10. Further work

The calculation of the BTS, in the Bay of Biscay for example, is often limited by the data available in the scientific survey. As a result, only a fraction of the food web is usually taken into account. To further extend the indicator including other components of the food web, ecosystem models can be used if in situ data cannot be collected.

To improve the indicator, dietary analyses should be carried out at a regional scale so that the nature and spatial and temporal variability of trophic relationships can be investigated and more accurate estimates of trophic levels can be obtained. Temporal changes in trophic level of a species or group of species can indicate progressive changes in prey and can be used to highlight adverse effects on food web status.

Currently, the BTS is being tested across several ecosystems in Europe so that the indicator can be further developed and validated. For the evaluation of GES, in particular, further work will be needed in terms of target setting. Also, since changes in biomass can be caused by several direct and indirect pressures, the influences of these pressures on the BTS should be further investigated.

References

Carafa, R., Dueri, S., Zaldívar, J.M. 2007. Linking terrestrial and aquatic ecosystems: Complexity, persistence and biodiversity in European food webs. In: EUR 22914 EN, Joint Research Centre.

Colléter M., Gascuel D., Ecoutin JM., De Morais L.T., 2012 - Modelling trophic flows in ecosystems to assess the efficiency of Marine Protected Area (MPA), a case study on the coast of Senegal. Ecological Modelling, 232:1-13.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Gasche L., Gascuel D., Shannon L., Shin Y-J., 2012 - Global assessment of the fishing impacts on the Southern Benguela ecosystem using an EcoTroph modelling approach. Journal of Marine Systems, 90(1):1- 12.

Gascuel, D., Bozec, Y.M., Chassot, E., Colomb, A., Laurans, M. 2005. The trophic spectrum: Theory and application as an ecosystem indicator. ICES J. Mar. Sci. 62, 443-452.

Gascuel, D., Guénette, S., Pauly D. 2011. The trophic-level-based ecosystem modelling approach: Theoretical overview and practical uses. ICES J. Mar. Sci. 68, 1403-1416.

Laurans M., Gascuel D., Chassot E., Thiam D., 2004 - Changes in the trophic structure of fish demersal communities in West Africa in the three last decades. Aquatic Living Resources, 17: 163-174.

Lassalle G., Gascuel D. , Le Loc’h F., Lobry J., Pierce G., Ridoux V., Santos B., Spitz J., and Niquil N., 2012 - Assessing the effects of fisheries on marine top-predators: the Bay of Biscay case study. ICES Journal of Marine Sciences, 69: 925-938.

Libralato S., Coll M., Tempesta M., Santojanni A., Spoto M., Palomera I., Arneri E., Solidoro C., 2010 - Food- web traits of protected and exploited areas of the Adriatic Sea. Biological Conservation 143: 2182–2194

Moloney, C.L., St John, M.A., Denman, K.L., Karl, D.M., Koster, F.W., Sundby, S., Wilson, R.P. 2010. Weaving marine food webs from end to end under global change. J. Mar. Syst. 84, 106-116.

Valls A., Gascuel D., Guénette S., Francour P., 2012 - Modeling trophic interactions to assess the potential effects of a marine protected area: case study in the NW Mediterranean Sea. Marine Ecology-Progress Series (MEPS). 456: 201–214.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development

Ecological Network Analysis indicator (e.g. flow diversity)

1. Indicator

Name: Ecological Network Analysis indicator (e.g. trophic efficiency, flow diversity)

Code: FW-9 (NA)

Proposed to BDC 2013 as: Candidate indicator

State of methodological development:

Development step Defined

Indicator metrics Partially

Ecosystem components attributed (species/habitat types) No

Applicability to sub-regions No

Assessment scales Yes

Monitoring parameter Partially

Monitoring frequency No

2. Appropriateness of the indicator

Biodiversity component: Ecosystem

MSFD criterion: 4.3 Abundance/ distribution of key trophic groups and species

MSFD indicator: 4.3.1 Abundance trends of functionally important selected key trophic groups/species

Unknown Unknown Unknown Unknown 3 3

This indicator is relevant under D4 but is not a Commission Decision indicator. However, additional criteria that relate to the functioning and dynamics of food webs are needed to define GES, going a step forward to what is currently described in the Commission Decision. Further development of MSFD food web indicators should be directed towards more integrative and process-based indicators (Rombouts et al. in press).

A high value of flow diversity reflects a diverse and relatively stable food web. An important advantage of this indicator is that it can be used as a link between food web characteristics and habitat diversity. A high degree of habitat diversity within a system increases the flow diversity of the food web. So the indicator will be valuable to control and document habitat improvements such as for example restoration measures of estuaries.

The sensitivity and accuracy depends on the monitoring data that are used to determine the indicator. The indicator is not very simple to determine, but it is universal with respect of its spatial applicability and species identity within the food web.

3. Parameter/metric

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Flow diversity (Baird et al. 1998) determines diversity and evenness of flows between compartments in a given food web and is derived from ecological network analysis. Flow diversity, defined as Development Capacity/Total System Throughput, encompasses both the numbers of interactions and the evenness of flows in the food web (Mann et al. 1989, Baird et al. 2004).The flow diversity index is based on the network analysis of the particular food web and can be derived from the routine of this modelling. It includes a measure of the real and potential system organisation and the energy flow through the compartments of the web. Stability of food web increases (1) when top predators are using multiple prey species and (2) when medium ranked trophic levels are used by multiple predators. The normal flow diversity index should be determined to reflect especially those parts of the food web, which connect the upper part of the food web.

The model will need information on the biomass of different trophic groups (e.g. production for phytoplankton) and dietary data that can be obtained from, e.g. stable isotopes, stomach contents, etc. Hence, the main disadvantage of this indicator is that it is data intensive; we need information on the entire food web to get a measure of flow diversity. The necessary data to calculate this type of measure is currently only available in few regions across OSPAR.

4. Baseline and Reference level

Baselines have not been defined yet. As a baseline reference, food webs should be selected representing most of the habitats at the target region. These reference food webs should fulfil special criteria such as a high degree of pristine conditions, low direct human influence and low degradation.

5. Setting of GES boundaries / targets

Targets for GES have not been defined yet. Theoretically, the target is that flow diversity of a system should be as high as possible. If comparisons of temporal food web scenarios of the same area are showing an increasing trend in flow diversity then the environmental conditions may improve and the food web tends to be stabilized. So the target is directional or trend based. There is hardly a baseline value possible to develop, however reference food webs could help in finding desirable conditions for the particular food web. It is not defined yet from which point on a given food web becomes destabilized and thus will be sensitive to perturbations. We can assume that if top predators are only dependent on a single food source that this would be an alarming situation.

6. Spatial scope

The appropriate scale of assessment will need to be determined in relation to the habitat type/ecosystem, however the indicator can applicable at all scales from regional to local.

7. Monitoring requirements

The indicator is integrative. Most existing monitoring data for a certain region can be used to construct its food web. The food web should be characterized in terms of biomass of the particular compartments and it is necessary to know the food spectra of the different species forming the food web. The food web can be based on annual average data or can be also reflect different seasons. It could be organised in a way that one person who is familiar with network analysis, is integrating the existing monitoring data on the suitable food web compartments. Member states may have different targets with respect to their monitoring activities so that due to existing gaps new monitoring data have to be started. Monitoring locations should reflect the relevant types of habitats and climate regimes in a certain region.

8. Reporting

One advantage of this indicator is that it links food web characteristics and species/habitat diversity. Since most data will already be collected to calculate other diversity indicators, same data sources could be used.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development A high degree of habitat diversity within a system increases the flow diversity of the food web. So the indicator will be valuable to control and document habitat improvements such as for example restoration measures of estuaries.

9. Resources needed

The cost may be limited if the needed variables measured in the field are already collected for other diversity indicators. For example, if biomass data are estimated for the dominant species for Descriptor 1 and in primary production is estimated, then the only extra cost will be correspond to the modelling and calculation. A specialist may then be able to build a pre-model taking 8 man-month for a special site, but then the modification of the model for each new period would only take one man-month.

10. Further work

For theoretical reasons, this index appears as a good candidate as an indicator describing the food-web structure related to stability, but further developments are necessary to establish correlation of this indicator with pressures and effects of management strategies. Such studies may be done i) through large inter-site comparisons, with the objective of unravelling different natural and anthropic constraints, or 2) by analysing data sets of food-web dynamics in a situation of changing pressures or management strategies. Other indicators from Ecological Network Analysis may be developed in the future. This is for example the case of the trophic efficiency, that is the mean ratio of production of one trophic level to the production of the lower trophic level.

References

Baird, D., R. R. Christian, C. H. Peterson and G. A. Johnson 2004. Consequences of hypoxia on estuarine ecosystem function: Energy diversion from consumers to microbes. Ecological Applications 14(3): 805-822.

Baird, D., J. Luczkovich and R. R. Christian 1998. Assessment of spatial and temporal variability in ecosystem attributes of the st marks national wildlife refuge, Apalachee bay, Florida. Estuarine,Coastal and Shelf Science 47(3): 329-349.

Mann, K. H., Field, J. G., and Wulff, F. 1989. Network analysis in marine ecology: an assessment. In Network Analysis in Marine Ecology. Ed. by F. Wulff, J. G. Field, and K. H. Mann. Springer, Berlin. 284 pp.

Rombouts, I., Beaugrand, G., Fizzala, X., Gaill, F., Greenstreet, S.P.R., Lamare, S., Le Loc’h, F., McQuatters-Gollop, A., Mialet, B., Niquil, N., Percelay, J., Renaud, F., Rossberg, A.G., Féral, J.P. (in press) Food web indicators under the Marine Strategy Framework Directive: from complexity to simplicity? Ecological Indicators

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Non-indigenous species

Number Previous Indicator Category code* NIS-1 41 Pathways management measures Candidate

NIS-2 40 Rate of new introductions of NIS (per defined period) Candidate

Pathways management measures [draft as at 28 Jan 2013]

1. Indicator

Name: Pathways management measures

Code: NIS-1

Proposed to BDC 2013 as: candidate indicator

State of methodological development:

Development step Defined

Indicator metrics

Ecosystem components attributed (species/habitat types)

Applicability to sub-regions

Assessment scales

Monitoring parameter

Monitoring frequency

2. Appropriateness of the indicator

The number of Non-Indigenous Species (NIS) is growing due to globalisation and the increasing demand for international trade opening new routes of introduction. Invasive NIS are recognised as one of the greatest threats to global biodiversity. Under descriptor 2 of the MSFD there is a requirement to manage NIS so that their introduction does not ‘adversely alter ecosystems’. To effectively manage NIS in the marine environment in a sustainable manner the number of new introductions of NIS will need to be reduced prior to attempting to control and/or eradicate those that are already present.

This indicators aim is to reduce the risk of the introduction of new NIS through management of pathways/vectors of introduction. The effectiveness of the applied management will be measured as a rate of introduction of new NIS into managed areas.

There are 2 aspects to this indicator: a) the implementation of the control measures to reduce the risk of introduction and b) the measurement of the targets to determine the success of the implemented controls. It is important that both aspects are considered concurrently as a direct cause and effect comparison.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Sensitivity to Relevance to Practicable Applicable Number of CPs Consensus among CPs on specific management across reporting/using the usefulness as part of a region wide pressures measures region indicator (n=9) set (n=8)

2 8

[If relevant mention also e.g. link to other directives, agreements, lists of protected species.

Also add other information of relevance e.g. role in ecosystem etc (text previously under 8. Appropriateness of the indicator can be placed here),]

3. Parameter/metric

a) The effort to improved management of pathways/vectors.

b) The number of new NIS introduced into a specific geographical area over a given time.

4. Baseline and Reference level

In considering the 2 aspects of this indicator it is important that baselines and reference levels are set for both:

a) There have been no specific, prolonged attempts to control pathways of introduction of NIS into a geographical area; therefore there is little or no precedence for reference. Methods will need to be developed by which management applied to pathways/vectors can be quantified. This will have to take into account the type of pathway and/or vector being managed and the degree of effort applied. It is important that any management implemented is quantified so that a direct link can be made between management effort and their effects in reducing the number of new NIS introduced. Given the lack of specific management strategies new baseline data will be required to parameterise the pathway management strategies implemented.

b) Very little baseline data is available on the rate of introduction of NIS over time. Given the lack of dedicated monitoring/surveillance programmes for NIS in the marine environment the detection of recently established species have been relatively poor. This has resulted in a lack of clarity as to when and where NIS are initially introduced, and the means that they have been introduced by. This has led to speculation on the timing and the route of introduction, which could potentially be rectified by dedicated monitoring/surveillance programmes. It is therefore likely that new baselines will have to be established for this indicator.

5. Setting of GES boundaries / targets

The proposed target is:

Reduction in the risk of introduction of NIS through improved management of the main pathways/vectors.

The overall target of the indicator is to reduce the risk of introduction of new NIS through management of the pathways and vectors of introduction. To be able to effectively implement such an indicator 2 parameters are required to be measured. Therefore the indicator can be broken down into 2 further targets in respect to the different parameters:

a) Improved management of pathways/vectors is implemented.

b) The rate of introduction of new NIS is reduced in specific geographical locations.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Given the broad range of pathways and vectors that may lead to the introduction of NIS it would be impossible and potential ineffective to implement control measures on all. It is therefore suggested that priority pathways/vectors are identified through a risk based approach.

6. Spatial scope

It is suggested that pathway/vector management and subsequent monitoring/surveillance for new NIS focus on areas identified as having a high or very high likelihood of introduction for NIS. This can be determined by assessing the intensity of high risk pathways in certain geographical locations.

7. Monitoring requirements

Monitoring would be required to assess both targets to determine the level of management implemented as well as to determine the effectiveness of the management by monitoring for the present of new NIS:

a) Methods by which the management of pathways can be quantified will have to be developed. This will vary on the type of pathway/vector being managed and the management methods used. The frequency at which the methods should be measured will need to be decided upon, but at least initially this is suggested to be regularly to assist in developing a baseline.

b) To determine the effectiveness of the implemented pathway/vector management at preventing introductions of new NIS, monitoring/surveillance will have to be implemented. The type of monitoring will depend on the taxonomic group that is being assessed. It is proposed that the absence/presence of new NIS is recorded over a set period of time and the rate of new introductions calculated. Sensitivity of detection for the various monitoring programmes utilised will have to be determined.

8. Reporting

It is suggested that reports should be produce detailing the spatial scope and the identification of areas of high likelihood of introduction. For each location and/or area the following should be reported:

 The main pathways of introduction and how they were identified.

 The management methods applied to the pathway/vector and quantification of effort.

 Monitoring method used to detect new NIS and their sensitivity.

 Number of new NIS detected over the sampling period.

 A comparison between the application of management and detection rate, this could potential be presented as a traffic light type system. A simple ratio of species found over effort made could be used as an arbitrary figure to compare between location in and between Member States.

9. Resources needed

Resources required to implement this indicator has been broken down by target:

a) The resources required to manage the pathways/vectors will vary significantly depending on the type of pathway/vector being managed.

b) It is likely that existing monitoring programmes can be utilised to assess for the absence or presence of certain taxonomic groups, although in some cases new monitoring/surveillance may be required for certain taxonomic groups.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development 10. Further work

Development of methodology is required for:

 Identifying areas where new NIS are likely to be introduced.

 Identifying high risk pathways/vectors.

 Quantifying pathway and vector management.

 Monitoring and surveillance for new NIS.

 Assessing GES with the information from the management and monitoring programmes.

References:

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Rate of new introductions of NIS (per defined period) [draft as at 28 Jan 2013]

Name: Rate of new introductions of NIS (per defined period)

Code: NIS-2

Proposed to BDC 2013 as: candidate indicator

State of methodological development:

Development step Defined

Indicator metrics

Ecosystem components attributed (species/habitat types)

Applicability to sub-regions

Assessment scales

Monitoring parameter

Monitoring frequency

1. Introduction

For the implementation of the Marine Strategy Framework Directive (MSFD) in the North East Atlantic region, indicators are developed that should be used in the assessment of marine biodiversity across OSPAR regions and subregions. The present document aims at the development of such an indicator for non-indigenous species as these species may become invasive and pose a great threat to marine ecosystems. European non-indigenous species (NIS) policy primarily focuses on the prevention of new introductions. Secondarily the focus is on reducing the risk of spreading in the early stages of the development of NIS populations. The aim of the present indicator for non-indigenous is to estimate the effectiveness of management measures that are taken by the member states to reduce the number of new introductions.

This technical specifications document describes the development of a trend indicator for non-indigenous species in two phases: method development and operationalization. Method development hereby encompasses defining monitoring parameters and indicator metrics, describing the species and habitats that are to be monitored and discussing the applicability of the indicator on a spatial scale, determining the appropriate assessment area and monitoring frequency. Operationalization concerns defining baseline and GES-boundary/target, data flows, a protocol for status assessment, and the reporting.

The implementation of the trend indicator for non-indigenous species is illustrated with examples of the Dutch coastline and on-going monitoring programs as the Rijkswaterstaat Waterdienst of the Dutch Ministry of Infrastructure and the Environment issued the development of this technical specifications document.

2. Indicator

The trend indicator for non-indigenous species aims at reflecting the rate of increase or decrease in new introductions of non-indigenous species through anthropogenic activities.

3. Reasoning for the development of this indicator

The present indicator is developed for “Descriptor 2: Non-Indigenous species” of the Marine Strategy Framework Directive where it is described as MSFD indicator 2.1.1: “Trends in abundance, temporal

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development occurrence and spatial distribution in the wild of non-indigenous species, particularly invasive non- indigenous species, notably in risk areas, in relation to the main vectors and pathways of spreading of such species.”

3.1 Status of development

The trend indicator for non-indigenous species becomes operational when at least two years of relevant data on the parameters are made available. In the absence of relevant data, it is advised to use two years data collected after the development of the indicator.

4. Selection of parameter/metric

4.1 Abundance of non-indigenous species

Abundance of non-indigenous species plays no role in the calculation of the trend indicator for non-indigenous species. Abundance monitoring is relatively expensive. It is less important than recording all local non- indigenous species. The abundance parameter is also not important for the NIS-goals set for the trend indicator:

[1] ideally no new non-indigenous species are introduced, and

[2] ideally the number and composition of non-indigenous species remains at a level where only non-indigenous species that have already settled at a location are present, i.e. a reference level indicating that the number of non-indigenous species has remained the same in the period of three successive years’ i.e. the non-indigenous encountered species in the system appear to have settled for the “long-term”.

From a benefit-cost perspective it is therefore best to focus on finding as many non-indigenous species as possible within a location, and not on scoring the abundances of these species.

4.2 Temporal occurrence and spatial distribution of non-indigenous species

The management measures for marine non-indigenous species should be focused on preventing new introductions through various ways. This approach is the most cost-efficient and in most cases it is the only way to manage non-indigenous species. To evaluate this management measure, one should monitor the trends in the temporal occurrence and spatial distribution of recently introduced species To monitor the trend indicator of non-indigenous species the two parameters [A] & [B] should therefore be calculated on a yearly basis (Table 1). [A] provides an indication of the introductions of “new” species (in comparison with the prior year), and [B] gives an indication of the increase or decrease of the total number of non- indigenous species:

[A] The number of non-indigenous species at Tn (for example T2013) that was not present at Tn-1

(for example T2013-1=2012). To calculate this parameters the non-indigenous species lists of both years are compared to check which species were recorded in 2013, but were not recorded in 2012.

[B] The number of non-indigenous species at Tn minus the number of non-indigenous species at Tn-1.

Hereby Tn stands for the year of reporting. For example, to calculate [A] in 2012 one should score

how many non-indigenous species are present in 2012 (=T2012) at the locations concerned, that

where not present there in 2011 (=T2012-1=2011), regardless of whether or not this species was present in 2010 and earlier years. To calculate this parameter only the total number of non- indigenous species is used in the comparison (species names are not compared).

Trends in both [A] and [B] should be monitored to develop the best management plan for non-indigenous species in an area. A positive or negative trend in [B] illustrates respectively an increase and a decrease

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development in the number of non-indigenous species in an area, which is a good trend indicator of non-indigenous species. One also needs to calculate [A] however as it is possible to have both a negative trend in [B], indicating a decrease the total number of non-indigenous species, and a positive trend in [A] at the same time, indicating that management in the area is not sufficient yet. A positive trend in [A] ([A]>0) indicates that “new” species are introduced into the area and one should therefore investigate how and with which vector they are introduced. If this concerns a vector introduced by anthropogenic activities, one may focus management on that vector. If the new non-indigenous species arrive by their natural distribution capacities, one may focus on backtracking the location of origin and focus management on that location. Although one may have a negative trend in [B] ([B]<1) indicating that the total number of non-indigenous species decreases, there may still be a positive trend

Example calculation of [A] and [B] for location 1 (Table 1):

[A] = 2, i.e. the species Styela clava and Rapana venosa were found in 2013, but not in 2012.

[B] = 5 - 4 = 1, i.e. in 2013 five non-indigenous species were recorded while four non-indigenous species were recorded in 2012. In 2013 one non-indigenous species was found (=[B]) that was not recorded in 2012.

These parameters should be calculated for at least 2 locations per region per “potential import vector”, e.g. “ballast water”, “hull-fouling” and “aquaculture transports”. The criteria on the basis of which these locations are chosen can be the following:

[1] past research has shown them to be hotspots for non-indigenous species that can be transported with the transport vector concerned,

[2] the species communities at the two locations do not directly influence each other,

[3] vulnerable areas with prospects for invasion by new introductions.

The number of non-indigenous species at each of the selected locations has to be monitored following a specific protocol for that location, ensuring that the number of non-indigenous species within a location can be compared over the years to produce trends. The monitoring protocol developed for each location should aim at reflecting the occurrence of many non-indigenous species at that location. Monitoring protocols may be different between locations. The use of different monitoring protocols at different locations must not be a problem as long as all protocols aim at scoring non-indigenous species present in the location.

5. Baseline and Reference level

The reference level is set based on the parameters A, B and Tn. Hereby Tn stands for the year of reporting.

The metric [A] is the number of non-indigenous species at Tn (for example T2013) that was not present at

Tn-1 (for example T2013-1=2012). To calculate this parameters the non-indigenous species lists of both years are compared to check which species were recorded in 2013, but were not recorded in 2012. The metric

[B] represents the number of non-indigenous species at Tn minus the number of non-indigenous species at

Tn-1. For example, to calculate [A] in 2012 one should score how many non-indigenous species are present in 2012 (=T2012) at the locations concerned, that where not present there in 2011 (=T 2012-1=2011), regardless of whether or not this species was present in 2010 and earlier years. To calculate this parameter only the total number of non-indigenous species is used in the comparison (species names are not compared).

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development The reference value (at which impacts from anthropogenic pressures are absent or negligible) for metric

[A] is [A at Tn] = [A at Tn-1]=0, indicating that in the last three years no new non-indigenous species were introduced.

The reference value for [B] is [B at Tn] = [B at Tn-1] = [B at Tn-2], indicating that the number of non- indigenous species has remained the same in three years’ time, i.e. the non-indigenous species present appear to have settled for the “long-term”.

In conclusion the impacts from anthropogenic pressures are assumed to be absent or negligible when [A at Tn] = [A at Tn-1] = 0 and [B at Tn] = [B at Tn-1] = [B at Tn-2].

The baseline is set by considering the following statements:

[1] ideally no new non-indigenous species are introduced, and

[2] ideally the number of non-indigenous species reduces to a level where only non-indigenous species that have already settled at a location are present, i.e. the number of non-indigenous species is decreased to a level where only settled non-indigenous species are present. It is hereby assumed that the eradication of settled non-indigenous species in the marine environment is virtually impossible.

The number of non-indigenous species found during the Initial Assessment (IA) is therefore not used as the baseline. Instead, the reference values for [A] and [B] are based on trends in numbers of non- indigenous species that are found over the years.

6. Target setting

The target for the trend indicator for non-indigenous species is trend-based: An acceptable target situation for the indicator is a negative trend in the numbers of introductions, occurrences and spatial distribution.

When [A at Tn] < [A at Tn-1] (indicating that the number of “new” species introduced to the area in the year

Tn is lower than in the prior year, i.e. Tn-1) and [B] <0 (indicating that the number of non-indigenous species at a location has decreased), until the Reference level is reached. The reference level [A at Tn] =

[A at Tn-1] = 0 and [B at Tn] = [B at Tn-1] = [B at Tn-2], should indicate that no new non-indigenous species were introduced in the last three years, and that the number of non-indigenous species is decreased to a level where only settled (for at least three years) non-indigenous species are present. Of course, this target accounts for all locations that are monitored.

7. Spatial scope

Marine species, and especially invasive marine species, tend to have relatively large distributional ranges in comparison to terrestrial and fresh water species as there are less physical barriers in the marine environment that may limit their spread. Most species for example have a pelagic stage during which they can drift along with the sea currents over large distances. Therefore monitoring the presence of marine non-indigenous species in for example a part of a sea port, will therefore provide a reasonably good indication of the species that are present in the whole port and close by waters. One can therefore obtain an overview of the non-indigenous species present at a large spatial scope, while only monitoring a relatively small number of locations.

To select these locations it has to be investigated what potential import vectors are present in the waters of the member state, for example “ballast water”, “hull-fouling” and “aquaculture transports”. At least two monitoring locations may be selected for each vector. Location selection should be based on the following criteria:

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development [1] past research has shown them to be hotspots for non-indigenous species that can be transported with the transport vector concerned,

[2] the species communities at the two locations do not directly influence each other,

[3] vulnerable areas with prospects for invasion by new introductions

Monitoring can be done at least once in a year and preferably in the warmer months because most of the species are present then. However, with sufficient resources, the monitoring may be done several times per year to reduce the risk that species are missed because of their seasonal disappearances from the location. The results of monitoring at locations selected for the same vector should be compared between the member states, to get an overview on a large spatial scope at regional seas level. Comparing results at this level ensures management focus on reducing the chances of NIS spread to other areas in the European waters.

The indicator accounts for the trends in numbers of non-indigenous species in each of the selected monitoring locations separately.

8. Monitoring requirements

The use of standard monitoring protocols and methods (without specifically aiming at scoring all species present at all locations) is probably one of the main reasons that so many marine non-indigenous species are missed. In the major continuous monitoring programs along the European coast, the focus is made on the sampling of few habitats (e.g. soft substrata) excluding species present in other habitats like hard substrata (Bouma, 2012; Sluis et al., 2012; Vandekerkhove& Cardoso, 2010).

In general, monitoring non-indigenous species should be focused on finding non-indigenous species in an area. The present marine monitoring program in the Netherlands is the MWTL and focuses on reflecting the abundance of marine species in the North Sea. Most non-indigenous species are missed however, especially the rare and recently introduced ones. This is probably also the case in other EU member states that use similar marine monitoring programs as the MWTL in the Netherlands.

To monitor trends in number, abundance and in the scope of distribution of non-indigenous species, one may need to develop a monitoring protocol for each location/region separately, aiming at scoring as many non-indigenous species as possible at that location. This means that monitoring protocols can be different between locations.

Points of importance when setting up a monitoring protocol focusing on finding non-indigenous species:

[A] Involve taxonomists, typically working for or in close cooperation with natural history museums. These are scientists that have specialised themselves in identifying and describing species. Identifying non-indigenous species can be very difficult as these species may origin from anywhere worldwide. Most identifications in marine monitoring programs along the European coasts are done by ecologists that usually do have a good knowledge of the common and native species, but find it difficult to identify “non-indigenous” species. The involvement of “true” taxonomists is therefore very important.

[B] The number of samples that has to be taken in an area should be estimated based on the homogeneity of the species communities in that area. This can for example be done by the obligation that one needs to take/search through new samples until at least 90% of the species in that area are found. To check this, various statistical analytic methods exist with which the total

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development species diversity in an area can be estimated on the basis of the species found in past samples taken.

[C] Make an assessment of the micro-habitats based on variations in salinity, substrate, currents, wave-action, etc. that are present at a location, and make certain that an assessment of non- indigenous species is done in each of these habitats with the best available monitoring method (from a benefit-cost perspective). Hereby one should focus on scoring species of various trophic groups and life strategies including endofauna and epifauna, but also the species with a mainly pelagic occurrence.

[D] To select the areas that need to be monitored for each country, one first needs to assess the potential import vectors. The most common ones are usually “ballast water”, “hull-fouling” and “aquaculture transports”. In addition less prominent vectors which are of little importance in the area may also need to be monitored. Even if for example “aquaculture transports” is assumed to be a vectors of little importance, if it is present, one needs to monitor it. “Small” imports of shellfish, if they are not properly managed, may form a major import vector of non-indigenous species. Finally one may also base the selection of monitoring locations on the vulnerability of marine water systems to exotic species to the degree that this can be predicted (Leewis& Gittenberger, 2011).

[E] Per vector, one needs to select at least two areas in which one expects to find most non- indigenous species that are introduced by that vector. Those two areas need to be monitored at least once per year, preferably in the warmer months as most species are present then. Ideally the monitoring should take place several times per year to reduce the risk that species are missed because of their seasonality.

[F] The monitoring may at least partly be placed under the responsibility of parties that benefit by the presence of the vector, for example port owners, pleasure craft harbour owners and the shellfish industry. Of course the monitoring itself should be done by an independent party and the results have to be reported to the ministry responsible for water management.

[G] When comparing monitoring data between locations and Member States, one may need to assess whether the location specific monitoring protocols did aim at scoring all non-indigenous species present. If that is so, the results can be compared. If there is any doubt on the basis of a monitoring protocol whether all non-indigenous species are scored, one should make an assessment of the number of species that are probably missed before comparing the results. Additionally a feasibility study should be conducted of whether the monitoring protocol concerned can be adjusted in such a way that it does aim at scoring all non-indigenous species present. As it is too expensive and time consuming to score all species in an area, one may decide that it is sufficient if one scores at least 90% of the species. Various statistical analyses exist with which the total species diversity in an area can be estimated.

9. Appropriateness of the indicator

An indicator for non-indigenous species is useful if the monitoring requirements described in the previous paragraph are met in the member states concerned. The indicator is expected to be very sensitive and accurate.

The problem is the development of a more focused monitoring campaign for the assessment of non- indigenous species. This is not the case in many of the on-going marine monitoring programs along the European coast. In the existing monitoring programs the focus is usually on endofauna but most non-

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development indigenous species are epifaunal species that live on hard substrata. Adjustments to the existing monitoring protocols and programs for the purpose of collecting data on non-indigenous species may not be sufficient.

A purpose specific monitoring strategy needs to be designed to produce useful data for the indicators. This could be done by making the (Stakeholders) parties that benefit by the presence of the vector, partly responsible for the monitoring. The involvement of stakeholders in the monitoring will result into [1] promoting them to maintain a management system to reduce the risk of introducing non-indigenous species, [2] easing the organisation and coordination of the monitoring itself, [3] easing the communication to the local stakeholders and [4] shortening the response time if any new non-indigenous species are found.

Both the maritime industry and the shellfish industry are already used to cooperating in monitoring programmes reducing the risks of non-indigenous species, and also benefit by these programs. Many non- indigenous species including Japanese oysters and New Zealand barnacles tend to foul the hulls increasing gasoline costs. Quite some “Japanese” sea-squirts and gastropods tend to smother shellfish beds and may feed on oysters greatly reducing their numbers. It is therefore feasible to involve these industries in the monitoring of non-indigenous species.

10. Reporting

The results of the monitoring at the selected locations should be forwarded to the national reporting center for the MSFD. Informing the national authorities is a prerequisite to the MSFD reporting. In addition, the results are ideally linked to a management-control system/protocol for no-indigenous species focusing on controlling the vectors.

One should have at least three years of data per location in order to calculate the trend indicator and to define the reference level for the non-indigenous species. This is assumed to be so when no new non- indigenous species were introduced in the last three years, and the number of non-indigenous species is decreased to a level where only characteristic resident non-indigenous species (settled for at least three years) are present. For developing new monitoring protocols specifically aiming at finding non-indigenous species, one should at least plan two years during which each country monitors non-indigenous species according to the monitoring program they have developed. During those two years, the results of the monitoring programs can be compared in time (between the two years) and space between the various member states. These results are compared with one question in mind: how can each of the monitoring programs be improved (from a cost/benefit point of view) aiming at finding as many non-indigenous species as possible. After those two years an evaluation should take place during which it is estimated what percentage of the non-indigenous species present at the various locations, is indeed found in the monitoring protocol that was chosen. If less than ~90% of the non-indigenous species present in an area are scored, the monitoring protocol is probably not fit for producing the data necessary to calculate the non-indigenous species trend indicator that is described here.

If the majority of the Member States is not able to develop and maintain a monitoring program that is able to score at least ~90% of the non-indigenous species present in an area, the use of any “trend indicator for marine non-indigenous species” is not feasible.

11. Costs

It is expected that each country will probably select about 6 locations for monitoring, i.e. two for each of the vectors “hull fouling”, “ballast water” and “shellfish transports”. As was already suggested above, the costs may at least party be paid by those that benefit from the presence of the vectors like harbour owners, the shellfish industry, etc.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development The total annual costs per member state for setting up a monitoring program for the non-indigenous species indicator is estimated to be about 100.000,- Euro. Cost estimates per location are included in Table 2.

The ~49,000 Euro estimate of the total annual costs of “Trend indicator non-indigenous species” (Table 2) concern a bare minimum price assuming that no more than two locations per vector are monitored, only three potential import vectors are present in the member state and the locations chosen are relatively small. Ideally more than two locations per vector are monitored and especially in the first years of monitoring, monitoring may be sub-optimal and relatively slow as new species are found and monitoring methods need to be optimised. A more realistic estimate of total annual costs is therefore 100.000,- Euro per member state.

Total species assessment of a shellfish area (mussel beds / oyster reefs):

~5.000-10.000 Euro

This price estimation is based on about 40 total species assessments focussing on non-indigenous species that have already been done since 2010 in Ireland, England, Sweden, Norway, Denmark, Germany and in The Netherlands. These assessments are done as a part of a Management & Control transport protocol for shellfish transports, i.e. the Shellfish Import Monitoring Protocol (Gittenberger, 2010), which is made mandatory in the Netherlands since 2012 by legislation (Bleker, 2012). This probably concerns the most wide-spread continuous (every three years all areas have to be checked) marine monitoring project focusing specifically on non-indigenous species in western Europe. It is fully paid by the shellfish industry. Such a monitoring program can form a very valuable and relatively low cost data resource for the non- indigenous species trend indicator described here.

Total species assessment of all (~35) pleasure craft harbours in the whole Wadden Sea (Netherlands / Germany / Denmark) per year:

~60,000 Euro

This price estimation is based two assessments in the Dutch Wadden Sea (in 2009 and 2011) and one assessment in the German Wadden Sea (in 2012).

Assessment of species with a fouling community study. Costs / year / locality:

~2.000-3.000 Euro

N.B. These costs include four checks (every season) of epifaunal species diversity per year.

In many of the on-going marine monitoring programs epifauna species are missed. A relatively simple and low-cost method of monitoring these species is the deployment of settlement/fouling plates. These fouling plates can be hung on ropes attached to buoys, floating docks, pilings, etc. One can check them for species on a regular basis without the need of scuba-divers by pulling the rope up and scoring the species that are growing on the plates. This methodology, in various variants, is commonly used in many countries to monitor epifaunal species. In the Netherlands GiMaRIS runs a continuous fouling community monitoring project since ~2006 in which about 200 SETL-plates in ports and pleasure craft harbours are checked for species all along the Dutch coast. The size and material of the plates used was copied (enabling comparisons to be made) from the Smithsonian Marine Invasions Laboratory. Over the years they have used thousands of these plates all along the coasts of eastern and western America and Canada, in Hawaii, and in New Zealand, specifically for monitoring non-indigenous species. The same methodology was also used along the European coast in the MarPACE project, a project of the MARBEF EU Network of Excellence. In the Netherlands the method was validated in 2007 and 2008 to assess the

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development ecological quality of The Netherlands sea ports on the basis of epifaunal inventory for the Dutch Ministry of Transportation and Water Management (Gittenberger, 2008). Furthermore, over the years, this fouling community study has repeatedly proven to be very useful for detecting new non-indigenous species in both marine and freshwater, for monitoring their spread and for monitoring their effect on the populations of native Dutch species (Gittenberger &Schipper, 2008; Gittenberger & Moons, 2011; Gittenberger & van Stelt, 2011; Lindeyer& Gittenberger, 2011; Schonenberg& Gittenberger, 2008).

All cost estimates made here are all-in including both the monitoring and reporting in either English, German and/or Dutch.

12. Further work

Further work encompasses that the member states [1] make an assessment of the import vectors present, [2] select at least two areas for each of these vectors to be monitored, [3] assess which monitoring already exists in these areas, [4] where necessary apply new developed monitoring protocols focusing on non- indigenous species in these areas. A final step is the evaluation of monitoring protocols by calculating the trend indicator for non-indigenous species metrics and comparing the results between the various areas.

For example, in The Netherlands “Ballast water”, “Shellfish transports”, and “Hull fouling” are the most important import vectors. When selecting two areas for “Ballast water” one may think of the port of Rotterdam and the entrance channel (Noordzeekanaal) to the port of Amsterdam as two areas where one expects to find most species introduced by this vector in The Netherlands. For “Shellfish transport” one may select an area in the Oosterschelde, close to Yerseke where most shellfish are imported, and a second area in the Dutch Wadden Sea. For “Hull fouling” the pleasure craft harbours in Zeeland and the pleasure craft harbours in the Wadden Sea can be selected as the two areas. In addition the port of Rotterdam and the port of Den Helder (military harbour) may be selected as two areas where one expects to find species introduced by hull fouling of larger ships that in general travel over greater distances than the pleasure crafts. When focusing on the monitoring in the port of Rotterdam, one may find that there is already an on-going monitoring program of the plankton species present, paid for by the government. In addition there is already an on-going (non-governmental) marine fouling community study present in the port of Rotterdam, focusing on fouling species on floating objects. Two habitats in which non-indigenous species may be present, but are not monitored in the port of Rotterdam may be the soft bottom (endofaunal species) habitats and the “hard substrata” like the dikes and sea-walls. It should therefore be assessed how these two habitats can also be searched for non-indigenous species. For the ballast water vector one may also include the assessment of non-indigenous species in a selection of ballast water samples taken in the port of Rotterdam from ships that have ballast water treatment systems on-board that are officially approved by the ballast water convention. When a monitoring program is developed for the Port of Rotterdam encompassing the above described, it is expected to be suitable for monitoring introductions by both the vector “Ballast Water” and the vector “Hull fouling”. For evaluation and optimization purposes, the results of the monitoring program in the port of Rotterdam have to be compared with the results of monitoring programs focusing on non-indigenous species in ports in other Member States.

For most areas new monitoring protocols need to be developed for monitoring non-indigenous species. This view is also supported by Vandekerkhove & Cardoso (2010) describing that most existing monitoring programs fail to detect some indicative alien species. This is confirmed by Sluis et al. (2012) and Bouma (2012) for the marine monitoring programs within The Netherlands. An example case of how many non- indigenous species are missed with the present monitoring methods and programs is given below for the Dutch Wadden Sea (similar results are known for the German Wadden Sea):

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development In a recent study for the Dutch Ministry an overview was made of 309 common marine macrozoobenthos species that were recorded in Dutch marine monitoring programs (Gittenberger & van Loon, 2011). For these species the sensitivities to environmental and anthropogenic pressures like sedimentation, fisheries and organic enrichment were scored as a part of the design, calibration and intercalibration of the marine benthos metric the BEQI-2 (Boon et al., 2011). This metric aims at fulfilling the obligations of the Dutch government set by the European Water Framework Directive and the future Marine Strategy Framework Directive for improving the water quality in European waters.

For this study the MWTL-database data of the Dutch Wadden Sea from 1989-2008 was used. Only 8 of the Wadden Sea species in this dataset concern non-indigenous species. This indicates that by far most of the non-indigenous species in the Wadden Sea are missed in the monitoring program as one can easily find, in one assessment, about 30 non-indigenous (mostly benthic) species in the Dutch Wadden Sea if one focuses the monitoring on finding non-indigenous species.

This is illustrated by two assessments, i.e. in 2009 and 2011, of each three weeks time (with ~two scientist), that specifically focused on finding non-indigenous species in the Dutch Wadden Sea (Gittenberger et al., 2010; Gittenberger & Rensing, 2012; Gittenberger et al., 2012). During these two assessments respectively 28 and 34 non-indigenous species were found. In total 18 of these species were “new” to the Dutch Wadden Sea. Most of these ‘new’ species have probably been overlooked during prior monitoring projects in this UNESCO world heritage site that did not focus on finding non-indigenous species.

Over the years in total 72 non-indigenous species have been recorded in the Dutch Wadden Sea. About half of these species were scored in the 2009 and 2011 assessments described above. One may assume on the basis of these results that about half of the non-indigenous species that have ever been recorded in the Wadden Sea (~35) has settled itself in the area. In the standard marine monitoring programs in the Wadden Sea for the Dutch ministry only 8, i.e. about 25% of these settled non-indigenous species were recorded in 10 years’ time (1989-2008), while the presence of virtually all of the non-indigenous species (~35) present can be recorded in an assessment of only three weeks’ time, when one specifically focusses the monitoring on non-indigenous species.

Furthermore, the non-indigenous species that were recorded in the MWTL-database mainly concern very common species like the Japanese oyster and the New Zealand barnacle that have settled in the Wadden Sea decades ago. Their presence and abundance is not very useful for the trend indicator of non- indigenous species that is described here. For this trend indicator the presence and abundance of new and recently introduced non-indigenous species that may not be very common yet, is much more valuable.

In conclusion it can be said that the monitoring programs that form the basis of the Dutch MWTL-database do not seem to be suitable for monitoring trends in non-indigenous species (numbers and abundances) and therefore do not provide useful data for a potential trend indicator of non-indigenous species. This can be resolved by using monitoring protocols that are specifically focussing on finding non-indigenous species.

13. References Bouma, S., 2012. Indicators for non-indigenous species in the Marine Strategy for the Dutch part of the North Sea. Bureau Waardenburg bv report nr 12-155: 49 pp. Bleker, H., 2012. Beleidsregels van de Staatssecretaris van Economische Zaken, Landbouw en Innovatie van 6 juni 2012, nr. 267278, houdende vaststelling van beleidsregels inzake schelpdierverplaatsingen. Staatscourant 12068: 4 pp. Boon, A.R., Gittenberger, A. & W.M.G.M. van Loon, 2011. Review of marine benthic indicators and metrics for the WFD and design of an optimized BEQI. Deltares report 1203801-000-ZKS-0006: 65 pp.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Gittenberger, A., 2008. Ecological quality of The Netherlands sea ports: on the basis of epifauna inventory. Naturalis report 2008/01: 35 pp.DGW, Ministry of Transportation and Water Management, Den Haag, The Netherlands. Gittenberger, A. & C. Schipper, 2008. Long live Linnaeus, Lineus longissimus (Gunnerus, 1770)(Vermes: Nemertea: Anopla: Heteronemertea: Lineidae) the longest animal worldwide and its relatives, occurring in The Netherlands. Zoologische Mededelingen 82(7): 59-63. Gittenberger, A., 2010. Schelpdier import monitoring protocol. GiMaRIS rapport 2010.10: 9 pp. n / Shellfish import monitoring & action protocol. GiMaRIS report 2010.14: 9 pp. Issued by the Vereniging van Importeurs van Schelpdieren. Gittenberger, A. & W.M.G.M. van Loon, 2011. Common marine macrozoobenthos species in The Netherlands, their characteristics and sensitivities to environmental pressures. GiMaRIS 2011.08: 38 pp. Gittenberger, A. & J.J.S. Moons, 2011. Settlement and competition for space of the invasive violet tunicate Botrylloides violaceus Oka, 1927 and the native star tunicate Botryllus schlosseri (Pallas, 1766) in The Netherlands. Aquatic Invasions 6(4): 435-440. Gittenberger, A. & R.C. van Stelt, 2011. Artificial structures in harbors and their associated ascidian fauna. Aquatic Invasions 6(4): 413-420. Gittenberger, A., Rensing, M., Stegenga, H. & B.W. Hoeksema, 2010. Native and non-native species of hard substrata in the Dutch Wadden Sea. Nederlandse Faunistische Mededelingen 33: 21-75. Gittenberger, A. & M. Rensing, 2012. Nieuwe exoten in de Waddenzee. De Levende Natuur 113(3): 96-100. Gittenberger, A., Rensing, M., Schrieken, N. & H. Stegenga, 2012. Waddenzee inventarisatie van aan hard substraat gerelateerde organismen met de focus op exoten, zomer 2011. GiMaRIS rapport 2012.01: 61 pp. i.o.v. de Producentenorganisatie van de Nederlandse Mosselcultuur. Vandekerkhove, J. & Cardoso, A.C., 2010. Alien Species and the Water Framework Directive Questionnaire Results. JRC Scientific and Technical Report. EUR 24257EN – 2010. Leewis, R.J. & A. Gittenberger, 2011. Assessing the vulnerability of Dutch water bodies to exotic species: A new methodology. Current Zoology 57(6): 863-873. Lindeyer, F. & A. Gittenberger, 2011. Ascidians in the succession of marine fouling communities. Aquatic Invasions 6(4): 421-434. Schonenberg, D,B, & A. Gittenberger, 2008. The invasive quagga mussel Dreissena rostriformis bugensis (Andrusov, 1879)(Bivalvia: Dreissenidae) in the Dutch Haringvliet, an enclosed freshwater Rhine- Meuse estuary, the westernmost record for Europe. Basteria 72: 345-352. Van der Sluis, M.T., Paijmans, A.J., van den Heuvel-Greve, M.J. & J.H.M. Schobben, 2012. Advies ecologisch monitoringsprogramma Noordzee ten behoeve van de kaderrichtlijn marien en de vogel- en habitatrichtlijn. IMARES report C127/12: 206 pp.

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OSPAR Commission Ver.18 Jan 2013/Living document on common biodiversity indicator development Table 1.Example table to illustrate the calculation of [A] and [B] at Location 1.

Non-indigenous species scored at 2012 2013 Number of species Change in number Location 1 not present at Tn -1 of species between (T2012) Tn -1 (T2012) and Tn (T2013) Crassostrea gigasx Yes No 0 -1 Didemnum vexillum Yes Yes 0 0 Styela clava No Yes 1 +1 Rapana venosa No Yes 1 +1 Elminius modestus Yes Yes 0 0 Diadumene lineata Yes Yes 0 0

A = 2 = B = 1 = - 0+0+1+1+0+0 1+0+1+1+0+0

Table 2. Cost estimates of monitoring and reporting for the Trend indicator non-indigenous species”.

Location selected for the vector “shellfish transports” (for example: shellfish ~7,000 Euro production area) Location selected for the vector “hull fouling” (for example: pleasure craft harbour) ~3,000 Euro Location selected for the vector “ballast water” (for example: part of the port of ~7,000 Euro Rotterdam) Total monitoring costs for two locations / vector 2 x ~17,000 Euro Reporting / calculation of trend parameters for “Trend indicator non-indigenous ~15,000 Euro species” Total costs “Trend indicator non-indigenous species” ~49,000 Euro

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