Report on Impacts on Net Socio-Economic Benefits of Achieving GES and Consequences of Monitoring

WP 2 Deliverable 2.1

Report on impacts on net socio-economic benefits of achieving GES and consequences of monitoring

Deliverable 2.1

Dissemination Level: Public

LEAD CONTRACTOR Plymouth Marine Laboratory (PML)

AUTHORS

Mel Austen (PML), Soile Oinonen (SYKE), Tobias Bӧrger (PML), Arantza Murillas (AZTI), Jonathan P. Atkins (UHULL), Stefanie Broszeit (PML), Daryl Burdon (UHULL), Jennifer Lockett (PML), Tiziana Luisetti (Cefas), Henrik Nygård (SYKE), Lucille Paltriguera (Cefas), Eija Rantajärvi (SYKE), Louise Roberts (UHULL), Joona Salojärvi (SYKE), Maria C. Uyarra (AZTI)

SUBMISSION DATE 15 | September | 2016 Contents

1. Executive Summary 4 1.1. Summary of Research in Deliverable 2.1 ...... 6 1.2. Identification of cost-effective MSFD monitoring and assessment systems ...... 7 1.3. Case studies ...... 9 1.4. Identification and assessment of the socio-economic consequences of management practices aimed at achieving GES ...... 10 1.5. Conclusions...... 13

2. Introduction 16

3. Description of case study areas 17 3.1. Gulf of Finland (GoF) ...... 17 3.2. East Coast Marine Plan (ECMP) area, England ...... 18 3.3. Bay of Biscay (BoB) ...... 19

4. Specific objective 2.1: Identification of cost-effective MSFD monitoring and assessment systems 21

5. Identification and assessment of the socio-economic consequences of management practices aimed at achieving GES 80 5.1 Cost-benefit analysis: Introduction and methodology ...... 80 5.2 Costs and benefits of achieving GES in Finnish marine waters ...... 85 5.3 CBA of management measures in the Bay of Biscay (BoB) ...... 89 5.4 CBA of management measures in the East Coast Marine Plan (ECMP) area in England ...... 108 5.5 Discussion ...... 147

6. Conclusions 152

7. References 153 Website links: ...... 165

8. Annex - National biodiversity monitoring and its costs in the Gulf of Finland in the Gulf of Finland 166

ABBREVIATIONS USED IN THIS DOCUMENT

BBI: Benthic brackish-water index BFT: bluefin tuna BoB: Bay of Biscay BWM: ballast water management BWTS: Ballast water treatment system CBA: cost-benefit analysis CEA: cost-effectiveness analysis CEI: cost-effectiveness index CFP: Common Fisheries Policy CPR: Continuous Plankton Recorder CVM: contingent valuation method DCE: discrete choice experiments EA: Ecosystem Approach ECMP: East Coast Marine Plan EEI: ecological effectiveness index EMFF: European Maritime and Fisheries Fund ESI: European Structural and Investment GBP: Great Britain Pounds GES: Good Environmental Status GoF: Gulf of Finland GVA: Gross Value Added HP: hedonic pricing IA: Impact Analysis IAS: Invasive Alien Species IBTS: International Bottom Trawl Survey ICES: International Council for the Exploration of the Sea IMO: International Maritime Organization IQ: Individual quotas ISSG: (IUCN) Invasive species specialist group ITQ: Individual Transferable Quota IUCN: International Union for Conservation of Nature MCA: multi-criteria analysis MCDA: multi criteria decision analysis MEA: Millennium Ecosystem Assessment MSFD: Marine Strategy Framework Directive MSY: Maximum Sustainable Yield NIS: Non-Indigenous Species NNSS: (Great Britain) Non-Native Species Secretariat NPV: Net Present Value PAM: passive acoustic monitoring PoMs: Programme of Measures PV: present values SAC: Special Areas of Conservation SAHFOS: Sir Alistair Hardy Foundation for Ocean Sciences SEI: socio-economic index SPA: Special Protection Areas SSB: Standing Stock Biomass TAC: Total Allowable Catch TAE: Total Allowable Effort TCM: travel cost method TEEB: The Economics of Ecosystems and Biodiversity TEV: total economic value TFC: Transferable Fisheries Concessions URA: Basque Water Agency VAT: Value Added Taxes WCO: Western Channel Observatory WTP: willingness to pay Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

1. Executive Summary

1. The overarching objective of this report was to summarise the developed approaches to determine the socio-economic implications of maintaining or changing monitoring and management practices aimed at achieving and maintaining good environmental status (GES) of EU regional seas. The aim of this work is to support development by member states of cost-effective monitoring systems and cost-effective adaptive management strategies and measures. Our approaches have been:  Identification of cost-effective Marine Strategy Framework Directive (MSFD) indicator monitoring and assessment systems relevant to three European case study areas (Finland, East Coast of England and Bay of Biscay);  Identification and assessment of approaches for determining the economic consequences of relevant management measures aimed at achieving and maintaining GES.

2. This DEVOTES (DEVelopment Of innovative Tools for understanding marine biodiversity and assessing good Environmental Status) report provides a list of attributes to assess the multiple dimensions (ecological, economic and social) of monitoring, an approach to assess the monitoring costs, and shows how multi criteria decision analysis (MCDA) of the three dimensions of monitoring can be conducted to estimate cost-effectiveness of monitoring activity. An interdisciplinary approach is required. Using three case studies in EU regional seas the report shows how cost- effectiveness analysis can be conducted for different aspects of monitoring. While following the general framework of MCDA, case study analyses were conducted independently of each other, each responding to particular requirements and challenges in its geographical location

3. DEVOTES has adapted, developed and applied a 6-step approach for undertaking environmental cost-benefit analysis (CBA) in the context of MSFD management practices and development of a Programme of Measures (PoMs) to achieve GES. An interdisciplinary approach is required. Three case studies illustrate how an environmental CBA can be conducted with respect to PoMs and the associated challenges. While following the general framework of environmental CBA, case study analyses were conducted independently of each other, each responding to particular requirements and challenges in its geographical location. Consequently, the case studies highlight advantages and shortcomings of different approaches to the implementation of environmental CBA in an MSFD framework.

4. In Finland a complete quantitative environmental CBA was undertaken using expert elicitation to define management measures and costs, benefits transfer of stated preference values to value benefits, and direct connection of the benefit estimates to the change in the status of the GES descriptors. Even though the original studies only partially covered GES descriptors, the estimated benefits were higher than the expected costs of the measures.

5. For England’s East Coast Marine Plan area, scenarios analysis proved a useful tool in the context of a situation where there is considerable uncertainty concerning the links between new management measures, the ecosystem and the links to welfare impacts. Lack and high uncertainty of data restricts the full application of an environmental CBA. In the context of high uncertainty about bio- physical and economic data on the impacts of a PoMs, the preliminary qualitative analysis undertaken proved valuable in identifying the main ecosystem services which may be affected under each management measure.

6. Both qualitative and quantitative CBA were applied to management measures in the Bay of Biscay resulting from the implementation of the reformed Common Fisheries Policy (CFP) and directly related to the MSFD, CBA was facilitated by using existing bio-economic models that have been developed and applied in other areas of Europe and that are flexible enough to be applied elsewhere. While such models are well developed for fishing activities, models that can be used for other maritime activities are still not sufficiently developed.

7. This report highlights challenges and opportunities, and makes recommendations for the use and further development of environmental CBA in the impact assessment of PoMs under the MSFD.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

1.1. Summary of Research in Deliverable 2.1

This summary for the general reader aims to serve as a more detailed, plain English summary of the extended scientific deliverable (which will be made publically available once it is published in peer review journals).

General Introduction The introduction of complex and integrative environmental legislation, such as the MSFD, inevitably incurs additional costs, such as in the establishment of new monitoring and improvement of existing monitoring of the multiple indicators across European seas. This can be financially challenging. Policy makers and regulators in all EU countries are obliged to manage their resources carefully and hence they will seek to comply with the MSFD in the most cost effective way.

Furthermore, EU countries are required to consider whether new management measures and monitoring schemes are needed to enable them to achieve GES and if so, to implement them. Many countries appear to be reliant solely on existing measures and monitoring programmes without creating new ones (Boyes et al., 2016). Socio-economic analysis of the use of marine waters, the cost of degradation of the marine environment, and the cost-benefit analysis of implementing new management measures that is required under the MSFD could provide motivation to achieve GES. However, whilst economic analysis is a mainstay tool of governance, approaches to achieve such analysis specifically for the MSFD in relation to the marine environment and its management had not been developed at the start of the MSFD process.

The overarching objective of this report was to develop approaches to determine the socio-economic implications of maintaining or changing monitoring and management practices aimed at achieving and maintaining GES of marine biodiversity. The aim is to support development by member states of cost- effective monitoring systems and cost-effective adaptive management strategies and measures. Our approaches have been:  Identification of cost-effective MSFD indicator monitoring and assessment systems relevant to three case study areas;  Identification and assessment of approaches for determining the economic consequences of relevant management measures aimed at achieving and maintaining GES.

Case Studies Within this report, research was reinforced through application of developed approaches and methodologies in three case study regions: the Gulf of Finland (GoF) (Section 4) and Finnish waters (section 5) in the Baltic Sea; UK marine waters (section 4) and the East Coast Marine Plan area in the North Sea (section 5); and the Bay of Biscay in the Atlantic Ocean (sections 4 and 5). Case study sites were chosen to cover a diversity of regional and sub-regional seas, and areas where relevant marine

monitoring and management issues and data have already been identified, either directly for MSFD or for other purposes.

1.2. Identification of cost-effective MSFD monitoring and assessment systems

Introduction The 2008 MSFD mandates implementation of an Ecosystem Approach (EA) and requires member states to achieve and maintain GES of EU regional seas by year 2020, for which it indicates that Member States should have established and implemented, by 15 July 2014 except where otherwise specified in the relevant Community legislation, a monitoring programme for ongoing assessment and regular updating of targets, in accordance with Article 11(1); (Article 5). The monitoring should therefore help to answer the question “what is the state of the sea in respect to the goal of GES?”

The MSFD does not require socio-economic aspects to be considered in monitoring, although these may serve to avoid impairing the quality of monitoring. Borja and Elliot (2013) pointed out that the most significant threat to performing adequate monitoring is limited financial resources. While implementing MSFD compliance monitoring programmes within member states, cost-effectiveness may be an issue. Two key issues determine a cost-effectiveness analysis: first is the identification and measurement of the costs, and second is the definition and measurement of effectiveness.

Reducing the quality of monitoring (e.g. by decreasing spatial and temporal coverage) can cost more than investing in it because of risks of decision-making errors: inaccurate evaluation could devalue the ecosystem services1 (e.g. Nygård et al., 2016). Furthermore, political decision makers may consider other socio-economic monitoring benefits, such as maintaining a bank of knowledge, professional skill and experience development, technological development and enhancing public engagement. These aspects can also add value in society, financially and socially, in the long term. To consider such aspects DEVOTES applies MCDA as a tool for cost-effectiveness analysis.

This DEVOTES report provides a list of attributes to assess the multiple dimensions of monitoring, an approach to assess the monitoring costs, and shows how the MCDA can be conducted using three case- studies in EU regional seas. Using three case studies in EU regional seas this report shows how cost- effectiveness analysis can be conducted for different aspects of monitoring. In the Gulf of Finland case study data was collected for one year within the national monitoring program. The aim was to assess

1 Ecosystem services are the direct and indicted contributions that ecosystems provide for human welfare (de Groot et al. 2010b) e.g. provisioning services including food and fishmeal as a raw material for aquaculture, s regulating services including climate regulation and bioremediation of waste, and cultural services such as charismatic marine species that act as a focus for leisure, recreation and tourism (Hattam et al., 2015a) 7

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

the cost-effectiveness of monitoring programmes for biodiversity related indicators in the Gulf of Finland in terms of complying with the requirements of the MSFD. In the Bay of Biscay case study monitoring data was collected from several years and within several frameworks to support different European policies, such as the Water Framework Directive, but which are of use to the MSFD. The aim was to compare the cost-effectiveness of different monitoring activities in respect of how effectively they cover MSFD descriptors. The UK case study investigated the cost-effectiveness of existing programmes to monitor plankton/pelagic habitats in order to highlight gaps and identify potential options for improving the cost-effectiveness of these programmes.

DEVOTES framework for cost-effectiveness analysis of marine biodiversity monitoring activities The MCDA for the three case-studies was undertaken using Rapfish (Pitcher and Preikshot, 2001), a non- parametric evaluation methodology, developed by the Fisheries Centre at the University of British Columbia, Canada. DEVOTES further developed the Rapfish tool to be applied in the context of marine monitoring using a five-step process:  Step 1: identify and define potential attributes according to which the cost-effectiveness of marine monitoring programmes will be assessed. These attributes are grouped into three categories: ecological, economic and social.  Step 2: Make the attributes comparable by scoring them. Kavanagh and Pitcher (2004) provide approximate scores on a scale from the worst to the best score. Following their approach, minimum and maximum possible levels are established for each attribute.  Step 3: Define the objective and scenarios against which to perform the cost-effectiveness analysis.  Step 4: Run the analysis.  Step 5: Run sensitivity analysis using Monte Carlo simulation and run leverage analysis to check the effect of removal of one attribute at a time on the process to assess the cost-effectiveness. A long list of attributes was developed for ecological, economic and social criteria of monitoring programmes (Table 4.1). This list was then tailored to the requirements of each of the three case- studies. To make the attributes comparable they were assigned scores with minimum and maximum possible values. The multidimensional aspect of determining cost-effectiveness of monitoring programmes is a function of the scenario, the case-study (M) and the selected attributes (N). Rapfish reduces the multidimensional problem into two dimensional space, in which one dimension is the score representing the value of the chosen index and the other dimension represents the fact that other score combinations for the attributes could provide similar index value (see detailed information in Pitcher et al. 2004). Depending on the characteristics of the applied attributes, different indexes to assess the cost- effectiveness of monitoring can be calculated. For example: - An ecological effectiveness index (EEI) which considers only the ecological criteria and the related attributes. - A cost-effectiveness-index (CEI) which combines both ecological and economic criteria.

The use of Rapfish multi criteria decision analysis enables an assessment of the effectiveness of monitoring programs and provides insight on options to improve effectiveness with the given monitoring budget.

1.3. Case studies

Three case studies are used for the purpose of this work: the Gulf of Finland, the Bay of Biscay and the UK. In the Gulf of Finland extensive information on monitoring programmes and associated detailed costs data for different phases of the monitoring programme was collated from multiple sources. The approach and lessons learnt are provided in Chapter 4 of this report. Flow charts describing the different phases in the monitoring programme proved to be useful in identifying costs and were produced for part of the monitoring programmes. Minimum threshold scores for the attributes to comply with MSFD were assigned and a dummy monitoring program with these scores was used as a baseline for assessment of compliance of the different Gulf of Finland scores for the monitoring sub programmes. The Rapfish methodology identified that only 8 out of 18 sub-programmes exceeded the compliance threshold and enabled identification of the attributes that contributed to poor compliance. Furthermore, a relative cost-effectiveness ranking of the different biodiversity monitoring sub- programmes was determined by dividing the effectiveness scores derived from the Rapfish analysis by the estimated costs for each sub-programme.

The Bay of Biscay took a different approach and examined the effectiveness of the contribution of the monitoring activities to assessment of the different MSFD Descriptors in terms of different attributes, such as, the number of MSFD indicators assessed, their quality and a combination of these. Combining ecological and socio-economic attributes to create a combined cost effectiveness score confirms the importance of the latter in considering effectiveness. Again minimum threshold scores for the attributes to comply with MSFD were assigned and a dummy monitoring program with these scores was used as a baseline, in this case for assessment of cost effectiveness of the different monitoring activities for assessing the different descriptors. CEI values for descriptors D1 (biodiversity), D10 (litter) and D7 (hydrographical conditions) are below this threshold, D4 (food-webs) is close to it, and the remaining descriptors are above it.

The UK case study took another approach again to examine the cost-efficiency of two existing plankton monitoring programmes that will inform the state of pelagic habitats in UK waters. Here, cost-efficiency is defined as whether the existing monitoring programmes for pelagic habitats/plankton are fulfilling the requirements of MSFD monitoring purposes given the costs being incurred. The analysis highlights overlaps and gaps between the two monitoring programmes identifying areas where the efficiency of plankton monitoring in the UK could be achieved, including options to do so. The analysis was not strictly a cost-effectiveness analysis since the least cost-option for plankton monitoring was not identified.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

1.4. Identification and assessment of the socio-economic consequences of management practices aimed at achieving GES

Introduction The EU MSFD requires member states to implement PoMs that will ensure the marine environment in European regional seas reaches GES by 2020. In 2012, all member states were required to carry out an assessment of the current state of the marine environment in their jurisdictions to establish a baseline. Each member state then had to plan and implement its own PoMs to achieve GES by 2020. Prior to the implementation of these PoMs the MSFD requires the conduction of impact assessments including CBA (Article 13.3).

A major challenge to the use of CBA in an MSFD framework, however, “is the lack of knowledge on the links between potential measures, improvement of marine ecosystems and corresponding economic and social value” (DG Environment 2015, p. 29). While it has been suggested that ecosystem service classifications are a way to map and assess these links (e.g. Interwies et al. 2013b, Bertram et al. 2014), a comprehensive conceptual framework for the use of ecosystem service and benefit categories in the assessments of benefits arising from the implementation of a PoMs under the MSFD is still lacking. Research conducted in DEVOTES WP2 (‘Social-economic implications for achieving GES’) addresses this gap in the literature to facilitate the linking of changes in marine ecosystems caused by the reduction of pressures under new or a modified PoMs and their resulting economic and social benefits.

Development of DEVOTES approach The approach for identification and assessment of the socio-economic consequences of management practices aimed at achieving GES is based on Hanley and Barbier’s (2009) recommendations for environmental CBA which involves the following six steps: Step 1: Definition of project or policy measure; Step 2: Identification of the impacts of the project or policy measure; Step 3: Valuation of these impacts in economic (i.e. monetary) terms; Step 4: Discounting of flows of costs and benefits occurring over time; Step 5: Application of the present value test; and Step 6: Sensitivity analysis. These steps and what they involve are developed in detail in the report and in Bӧrger et al (2016), in particular in the context of MSFD management practices and how they should be applied in practice. Key points include:

1. Definition of project or policy measure Any environmental CBA of PoMs should only consider new measures which are implemented based on either the MSFD or other policies. It should start by specifying and justifying the particular management measures under consideration. These measures will be introduced so that the analysis can build on a clear understanding of the changes in management.

2. Identification of the impacts of the project or policy Once the management measures have been specified in detail, their impacts on affected ecosystems can be identified and where possible quantified. The identification and assessment of the physical impacts of proposed measures is particularly challenging in the marine environment. It is also necessary to determine a baseline of the current status and future projections that would result without additional management. There are a number of tools that can be employed at this stage including ecosystem and bio-economic modelling, expert elicitation, scenarios analysis and ecosystem service assessments.

3. Valuation of these impacts in economic terms Once the anticipated changes in the provision of environmental goods and ecosystem services have been assessed quantitatively, these can be valued in economic terms. For some goods, market prices will be available for use in valuation. Many goods and services are not traded in markets but their provision is impacted by environmental policies none-the less. Alternative valuation methods have to be used including revealed preference methods such as hedonic pricing (HP) and the travel cost method (TCM), and stated preferences methods such as contingent valuation method (CVM) (Carson and Hanemann 2005) and discrete choice experiments (DCE) (Louviere et al. 2000). The implementation of management measures to achieve GES will affect stakeholders in different ways. These impacts are the opportunity costs, i.e. the value of what is lost or sacrificed in order to implement and comply with the management measure. The costs often included in the analysis are:  Costs to the regulator and/or government for implementing the management measure.  Costs to businesses or industry for complying with the management measure.  Environmental/damage costs.  Social costs.

4. Discounting Different case studies may apply different discount rates given the specific policy guidelines.

5. Net present value test Once all costs and benefits have been monetised and discounted to a common base period, they can be compared. A PoMs passes the net present value test if discounted benefits outweigh discounted costs.

6. Sensitivity analysis Due to the often high uncertainties around both the assessment of the physical/ecological impacts of the policy measure under study and the valuation of these impacts, sensitivity analysis is required. Uncertainty stems from incomplete data and evidence surrounding some of the ecological impacts as well as from assumptions that often have to be made at different stages of the analysis. To test the dependency of the results on any one assumption, sensitivity analysis can be applied. A clear and transparent procedure is crucial when conducting a sensitivity analysis, so that the effect of any one assumption on the final result (i.e. net present value test) can be demonstrated.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

The particular challenges of applying environmental CBA to PoMs within the MSFD lie in Steps 2 and 3. For these, an interdisciplinary approach is required. Three case studies illustrate how an environmental CBA can be conducted with respect to PoMs and the associated challenges. While following the general framework of environmental CBA, case study analyses were conducted independently of each other, each responding to particular requirements and challenges in its geographical location. Consequently, the case studies can be used to highlight advantages and shortcomings of different approaches to the implementation of environmental CBA in an MSFD framework.

Finland’s marine waters case study An economic analysis was undertaken to support the preparation of Finland’s national PoMs for the MSFD. The national PoMs Working Group led the process and prepared and planned the new measures. The Working Group members were environmental scientists and other related officials, researchers and NGOs. A cost-effectiveness analysis (CEA) of the PoMs provided a cost-effectiveness ranking of new measures and proposed a set of cost-efficient candidate PoMs (Oinonen et al. 2016a). Due to the lack of comprehensive ecological-economic models applicable for MSFD-related analyses the estimates of the effectiveness of measures were based on expert elicitation. Environmental effectiveness of a measure was defined as a probability of bridging the gap between the present environmental status and GES, and the joint effectiveness of two or several measures was computed convolving the distributions of individual measures. The costs of measures were similarly estimated using expert elicitation and conditional probability distributions. The expected total costs for the Finnish PoMs was €136.2m.

The economic benefits of reaching GES in Finnish marine waters were estimated based on existing stated preference studies on the benefits of improving the state of the Baltic Sea. The approach connected the benefit estimates directly to the change in the status of the GES descriptors.

The net present value of achieving a good environmental status for biodiversity, food webs and eutrophication in year 2020 in Finland’s marine waters is around €2,000m. However, the PoMs will not lead to GES of these Descriptors by 2020. Based on the environmental effectiveness assessment as part of the CEA (Oinonen et al. 2016a), the probability of reaching GES by 2020 is 0.77 for biodiversity and food webs, and 0.02 for eutrophication. The benefits of the PoMs are estimated at €300m–894m i.e. lower than the benefits of reaching GES. Comparison of the estimated benefits (€300-890m) to the costs (€140m) of the Finnish PoMs indicates that despite the fact that the GES will not be achieved by 2020, the benefits of the PoMs exceed the costs by a factor of 2-6.

The England East Coast Marine Plan (ECMP) area case study Focussed on the England East Coast Marine Plan (ECMP) area a scenarios approach was used to compare different potential future states under new PoMs to achieve GES. Management measures assessed were mitigation of underwater noise and management of invasive alien species (IAS) introduction through ballast water treatment and the aim was to compare costs and benefits for each

scenario. Further, an ecosystem service approach was used to assess the impact of the potential management measures on such services and the benefits they provide. An ecosystem services framework was used to identify the ecosystem structures, ecosystem processes, ecosystem services and societal benefits which may be impacted by the new MSFD measures. The research highlighted the uncertainties in both determining the impacts of the management measures on the ecosystem, and then relating these uncertain impacts to services and benefits so that only qualitative changes in benefits could be estimated. Due to this, and also a lack of relevant valuation data for the study site, it was not possible to complete all of the steps required for a quantitative CBA.

The Bay of Biscay case study This case study developed a CBA of three management measures related to commercial and sport fishing activities, particularly under the reformed CFP but supporting the objectives of the MSFD. Fisheries management functions and costs were considered but many of these are coordinated at national level making it difficult to access costs and allocate them specifically to the Bay of Biscay. Some of the minimum public costs accrued by using the European Maritime and Fisheries Fund (EMFF) were identified. Benefits of the measures were determined using the FishRent bioeconomic model for fisheries and a scenario approach around the following management measures (i) the application of the landing obligation, (ii) the fishing vessel scrapping subsidies, and (iii) the introduction of individual rights. Benefits values were derived as percentage changes in net present value of Gross value added or percentage change in profits. Important public costs attached to certain CFP-related management measures could not be split between each specific management measure. Therefore, it was not possible to complete a fully quantitative CBA.

1.5. Conclusions

For all three case studies the scarcity of valuation studies that focus specifically on benefits arising from changes in all or specific MSFD Descriptors was challenging. The Finnish study developed a pragmatic alternative for estimating the economic value of marine protection when applicable data are available and conducting extensive new valuation studies is not feasible. Even though the existing studies did not explicitly assess the benefits of achieving GES, the results are suitable for indicating the benefits from the PoMs.

A major challenge indicated in the case studies, relates to comparing the present values of costs and benefits for a specific period of time. The discount rate is crucial to make costs and benefits incurred at different points in time comparable in the present. Depending on the discount rate used, benefits that are realised at a later point in time could have lower present values than the costs that are incurred once the measure is implemented affecting the overall outcome of the CBA. Furthermore, environmental CBAs for different management measure options may not be comparable if they have not used the same discount rates.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

If the management measures under study impact a range of ecosystem services that cannot be easily quantified, the qualitative approach in the UK case shows how the focus can be kept broad so as not to overlook important impacts of the management measures under consideration. This demonstrates the trade-off between highly quantified CBAs which often only focus on a very narrow array of ecosystem services and the broad, but often not quantified approach taken in the UK case.

By showcasing and discussing three CBA examples in the context of the EU MSFD, this report and Bӧrger et al. (2016) that arises from the research, highlight challenges and opportunities for the use and further development of this technique in the impact assessment of PoMs. Recommendations are made to further develop the CBA approach to better integrate the ecosystem service approach with established environmental valuation techniques. Further research into the linkages between MSFD Descriptors and established ecosystem service classifications is required so that the specific CBA can then be linked to the suitable Descriptor via the affected ecosystem services. The use of cost-effectiveness analysis is recommended where the measurement of benefits within an environmental CBA is difficult. Another alternative approach that has potential for application in the context of the MSFD is to use multi-criteria analysis (MCA) in the impact assessment when quantification or monetisation are not possible or when impacts are measured in different units (e.g. monetary vs. physical) and have to be compared. Finally, the use of modelling is recommended where appropriate bio-economic and ecosystem models already exist and there is sufficient data to parameterise them, or where there is sufficient data available to construct new models.

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Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

2. Introduction

Inevitably, the Marine Strategy Framework Directive (MSFD) as a new legislative framework has brought about unforeseen challenges to the different stakeholders who need to be involved in implementing it, particularly in its first round of application. Furthermore, the MSFD was initiated at a time of growing, global economic crisis. Yet the introduction of complex and integrative environmental legislation such as the MSFD also inevitably incurs additional costs, such as in the establishment of new monitoring and improvement of existing monitoring of the multiple indicators across European seas. This can be financially challenging. Policy makers and regulators in all EU member states are obliged to manage their resources carefully and hence they will seek to comply with the MSFD in the most cost-effective way. Yet they have many choices to make on the different types of monitoring they can apply: the suites of approaches that will best comply with the legislative needs within the limits of their budgets (Veidemane and Pakalniete, 2015). Although the MSFD does not require consideration of the socio- economic aspects of monitoring Borja and Elliott (2013) noted that limited financial resources are the most significant threat to implementation of adequate monitoring.

Furthermore, EU member states are required to consider whether new management measures and monitoring schemes are needed to enable them to achieve Good Environmental Status (GES) and if so to implement them. Many countries appear to be reliant solely on existing measures and monitoring programmes without creating new ones (Boyes et al., 2016). Here, the socio-economic analysis of the use of marine waters, the cost of the present-date degradation of the marine environment, and the cost-benefit analysis of implementing new management measures that is required under the MSFD could provide motivation to achieve GES. However, whilst economic analysis is a mainstay tool of government, approaches to achieve such analysis specifically for the MSFD in relation to the marine environment and its management had not been developed at the start of the MSFD process.

 Identification of cost-effective MSFD indicator monitoring and assessment systems relevant to three case study areas;  Identification and assessment of approaches for determining the economic consequences of relevant management measures aimed at achieving and maintaining GES.

In developing this research WP2 has been closely dependent on inputs from scientists in WPs 1, 3 4, 5 and 6 to help socio-economists understand cost-benefit implications of preferred existing monitoring methodologies (WP 1,3,4), of developing and novel monitoring methodologies (WP5) and systems (WP6), and of changes in ecosystem services that would be reflected by MSFD Indicators (WP3). WP2 links closely to WP6 as much of the case study example work was carried out in collaboration with 16

natural scientists and their efforts in WP6 particularly with respect to gathering case study specific data (primary and existing). Socio-economic results of WP2 contribute to development of adaptive management strategies (WP6).

3. Description of case study areas

Within this report, research was reinforced through application of developed approaches and methodologies in three case study regions: the Gulf of Finland (GoF) (Section 4) and Finnish waters (section 5) in the Baltic Sea; UK marine waters (section 4) and the East Coast Marine Plan area in the North Sea (section 5); and the Bay of Biscay in the Atlantic Ocean (sections 4 and 5). Case study sites were chosen to cover a diversity of regional and subregional seas, and areas where relevant marine monitoring and management issues and data have already been identified either directly for MSFD or for other purposes. They also reflect a pragmatic element as they were chosen to coincide geographically with the available, relevant expertise of partners engaged in the DEVOTES WP2 (‘Social- economic implications for achieving GES’), particularly with respect to economic analysis.

3.1. Gulf of Finland (GoF)

The Gulf of Finland is the Baltic Sea case study area (Figure 3.1). It covers the Finnish coastal waters and open sea areas. The Gulf of Finland is a 400 km long gulf in the north-eastern Baltic Sea, which at its entrance it is around 70 km wide and has a mean depth of 37 m. As there is no sill towards the Baltic Proper, the Gulf of Finland is influenced by the hydrographical conditions in the Baltic Proper, as well as by a large fresh water input especially from the river Neva in the east. Thus, the salinity varies from almost fresh in the eastern parts to 5-7 in the surface and 7-10 in the deep waters in the west (Alenius et al., 1998). The density stratification at around 60 m, restricts vertical water circulation and oxygen transport to the bottom water in the deeper parts of the gulf, resulting in reduced oxygen conditions below the halocline. As a result of intense human activity in its drainage area, the Gulf of Finland is impacted by eutrophication as well as hazardous substances affecting the biodiversity and the ecosystem structure in the area (HELCOM 2010). It is regarded as being one of the most pressurised sea areas within the Baltic Sea, causing challenges for efficient management but it also has good data availability building on a significant amount of past research.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Figure 3.1 The Gulf of Finland case study area in the Baltic Sea.

3.2. East Coast Marine Plan (ECMP) area, England

The North Sea case study area is the East Coast Marine Plan (ECMP) area in the UK section of the Southern North Sea. The ECMP covers both The East Inshore and the East Offshore Marine Plan Areas shown as areas 3 and 4 in Figure 3.2. This area of sea encompassed by the ECMP stretches from Flamborough Head to Felixstowe, and extends out to the seaward limit of the territorial sea (approximately 12 nautical miles) and beyond to the boundary of the Exclusive Economic Zone. It includes maritime borders with the Netherlands, Belgium and France.

Although several human activities occur in the area, the following activities are the most extensive in terms of spatial extent, taking account of the historical activity levels and considering future expansion: shipping and ports, offshore wind energy, fishing, and oil and gas extraction. Also important to the area are cabling, aggregate extraction, aquaculture, and leisure and tourism. The area also has several protected areas including 11% by area of England’s Special Areas of Conservation (SACs) under the EU Habitats Directive and 29% of Special Protection Areas (SPAs) under the EU Wild Birds Directive; 10% of its area is designated as Sites of Special Scientific Interest and it has important Ramsar sites in the Humber estuary and The Wash.

The East Inshore and East Offshore Marine Plans which cover the ECMP are the first two marine plans to be produced for English seas from an expected total of 10 Marine Plans (Defra 2014). Analysis has

suggested that an economic benefit of €12.6bn is likely to accrue from the Marine Plans. The case study area was chosen as it is a coherent management area with 11 objectives setting out what the marine plans aim to achieve supported by 38 detailed policies. It was assumed that arising from the Plan development the ECMP should be comparatively rich in the interdisciplinary economic, social and environmental data that would be required.

The ECMP contains several habitats of conservation interest including coastal salt marsh, blue mussel beds, estuarine rocky habitats, Sabellaria spinulosa reefs, subtidal chalk, intertidal mudflats, sheltered muddy gravels and subtidal sands and gravels as well as various species of conservation interest. Further information on the ECMP is provided in MMO (2012) and Defra (2014).

Figure 3.2 East Coast Marine Plan Area, England (ECMP). The case study encompasses England’s East Inshore and East Offshore Marine Plan areas (Areas 3 and 4).

3.3. Bay of Biscay (BoB)

The Bay of Biscay (BoB) case study is the Basque coast located within the Bay of Biscay, in the Atlantic area within the Atlantic Ocean ecoregion. It covers the marine environment that expands from the

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Spanish coast of the Basque Country, delimited to the West by the Cantabria region and to the East by France, to 200 nautical miles offshore to the boundary of the Exclusive Economic Zone. It includes maritime borders with France.

It is predominantly a deep sea (going down to 5,000 m water depth), with a narrow continental shelf (between 7 and 20 km). Beyond 200 m water depth, there is a steep slope (10-30%), encompasing submarine canyons. The coast is mountainous, with cliffs (20-150 m high), which extend over 70% of the 150 km of the coastal area (the remainder are beaches or low coast). It is a mesotidal, temperate sea with high wave exposure (in winter waves can reach 15 m), due to its long (>4,000 km) fetch. The area has a mean tidal range of 1.5 m at neap tides and 4 m at spring tides, with the maximum annual tidal range exceeding 4.5 m. Except close to the coast, where small rivers flow (mean flow: 2-36 m3 s-1), salinity in surface waters is around 35.5. Complete information on features and biodiversity can be consulted in Borja and Collins (2004) and Pascual et al. (2011) respectively.

Figure 3.3 Bay of Biscay case study area

In this case study area the most important pressures are derived from fishing activities (mostly pelagic, but also demersal trawling). Other pressures are associated with shipping, a small number of dredged sediment disposal sites, and coastal based activities (including treated water discharges). Additional information can be consulted in Borja et al. (2006) and Pascual et al. (2013).

4. Specific objective 2.1: Identification of cost- effective MSFD monitoring and assessment systems

4.1 Introduction

The 2008 MSFD mandates implementation of an Ecosystem Approach (EA) and requires member states to achieve and maintain (GES) of EU regional seas by year 2020, for which it indicates that member states should have established and implemented, by 15 July 2014 except where otherwise specified in the relevant Community legislation, a monitoring programme for ongoing assessment and regular updating of targets, in accordance with Article 11(1); (Article 5). The monitoring should therefore help to answer the question “what is the state of the sea in respect to goal of GES?”

According to Zampoukas et al. (2013), marine monitoring can be defined as “the systematic measurement of biotic and abiotic parameters of the marine environment, with predefined spatial and temporal schedule, having the purpose to produce datasets that can be used for application of assessment methods and derive credible conclusions on whether the desired state is achieved or not and on the trend of changes for the marine area concerned”. Accordingly the monitoring activities include the choice of elements, the location of sampling sites, the periodicity of sampling, the collection of field samples and data, processing of the samples in the laboratory and, the compilation and management of the data. The following definitions are used (after DEVOTES deliverable 1.4: ‘Report on SWOT analysis of monitoring’): Monitoring Programme are all substantive arrangements for carrying out monitoring, including general guidance with cross-cutting concepts, monitoring strategies, monitoring guidelines, data reporting and data handling arrangements. Monitoring programmes include a number of scheduled and coordinated activities to provide the data needed for the ongoing assessment of environmental status and related environmental targets (Zampoukas et al., 2014). A monitoring programme can include one or several monitoring activities. Monitoring Activities are the repeated sampling and analysis in time or space of one or more ecosystem components which is carried out by an individual agency or institution. Data and marine information are obtained on a routine or specific basis, using sea surveys, remote sensing, ferry boxes, data mining or any other way.

To assess the environmental status of the marine environment (Figure 4.1), the MSFD defines 11 quality GES descriptors (Annex I MSFD 2008/56/EC), which are related to biodiversity, non-indigenous species, species of commercial interest, food-webs, eutrophication, sea-floor integrity, hydromorphology, contaminants in the sea and seafood, litter and energy. These descriptors are in turned defined by 29 criteria and 56 indicators (56) (COM DEC 2010/477/EU). The DEVOTES project primarily focuses on the biodiversity descriptor (D1), as well as on non-indigenous species (D2), food webs (D4) and sea-floor integrity (D6). The marine biodiversity monitoring includes basic monitoring of all components of the marine ecosystem biota, supporting information on the abiotic environment, and pressures. Despite the MSFD mandate to establish and develop monitoring programs by 2014 (first cycle) and in following

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

years (second cycle), the MSFD does not require socio-economic aspects to be considered in monitoring, although these may serve to avoid impairing the quality of monitoring. Borja and Elliott (2013) pointed out that the most significant threat to performing adequate monitoring is limited financial resources. While implementing MSFD compliance monitoring programmes within member states, cost- effectiveness may be an issue. Studies by the World Health Organization (WHO, 2003), Postle et al (2005) and Martin-Ortega and Balana (2012) highlight two key issues that determine a cost- effectiveness analysis: first is the identification and measurement of the costs, and second is the definition and measurement of effectiveness. These studies highlight that the analysis identifies options or actions that can achieve an objective (i.e. the effectiveness of the options to achieve an objective) at the least cost. Depending on the objective, the definition and scope of effectiveness will vary and will therefore be up to the researcher to define.

Reducing the quality of monitoring (e.g. by decreasing spatial and temporal coverage), however, can cost more than investing in it because of risks of decision-making errors: inaccurate evaluation could devalue the ecosystem services (Nygård et al. 2016). Furthermore, political decision makers may consider other socio-economic monitoring benefits, such as maintaining a bank of knowledge, professional skill and experience development, technological development and enhancing public engagement. These aspects can also add value in society, financially and socially, in the long term. To consider such aspects DEVOTES develops an application of MCDA as a tool for cost-effectiveness analysis.

Figure 4.1. A conceptual figure of monitoring and related processes. The monitoring activities are marked with blue colour. The grey boxes on the right hand side show how the information collected cascades to other parts of the MSFD cycle (Source of the ‘descriptor wheel’: Meren pärskäys 2015).

The application of the MCDA requires a scoring system which makes the different aspects of monitoring activities comparable. The identified attributes and their scoring will be the base input for the MCDA through which an effectiveness index can be calculated for monitoring activities. This DEVOTES report provides a list of attributes to assess the multiple dimensions of monitoring and an approach to assess the monitoring costs. Using three case studies in EU regional seas the report shows how cost- effectiveness analysis can be conducted for different aspects of monitoring. In the Gulf of Finland case study data were collected for one year within the national monitoring program. The aim was to assess the cost-effectiveness of monitoring programs for biodiversity related indicators in the Gulf of Finland in terms of complying with the requirements of the MSFD. In the Bay of Biscay case study monitoring data were collected from several years and within several frameworks to support different European policies such as the Water Framework Directive (WFD) or the Common Fisheries Policy (CFP), which are of relevance to the MSFD. The aim was compare the cost-effectiveness of different monitoring activities in respect of how well they cover indicators for the MSFD descriptors. The UK case study investigated the cost-effectiveness of existing programs to monitor plankton/pelagic habitats in order to highlight gaps and identify potential options for improving the cost-effectiveness of these programs.

4.2 Review of previous projects on cost-effectiveness

Various aspects of monitoring effectiveness have been studied but in only a few projects e.g. EuMon, WATER and MARMONI. In some of them the term “cost-effectiveness” is also briefly highlighted. These projects focused on the compatibility of monitoring programs for various environmental policy requirements and will be discussed next.

The EuMon-project focused on the effectiveness of EU-wide biodiversity monitoring methods and systems of surveillance for species and habitats of EU interest (Figure 4.2). The project produced recommendations on different aspects of monitoring schemes: scientific quality, coherence, time and cost-effectiveness. It highlighted that the effort of monitoring can be expressed in two ways: in time requirements (measured by manpower; including professionals and volunteers) or in financial costs (personnel, material and equipment). Time and cost-effectiveness was proposed to be measured as a ratio of 1) the level of information obtained by the scheme (areal coverage, taxonomic and ecological extent, scientific quality) and 2) the effort required to conduct the scheme.

Further, EuMon highlighted that if monitoring schemes differ e.g. in geographic scope, taxonomic extent, time and cost requirements a simplified composite measure (e.g. an index of general quality) cannot be reasonably calculated or meaningfully compared across schemes. Therefore, they suggested that the calculation and comparison of composite measures should only be done for sets of schemes that are similar to some degree in their goals and methods. They also pointed out that a full evaluation process of monitoring effectiveness should also involve, besides coherence and scientific quality, time and cost-effectiveness aspects (Lengyel, 2007).

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Figure 4.2 A conceptual figure of basic principles of a monitoring scheme as presented in EuMon-project (Julliard et al., 2005).

The WATER-project reviewed central concepts of environmental and statistical uncertainty of biological monitoring indicators especially how they are defined in the WFD (i.e. precision and confidence) and analysed them against assessment criteria for Swedish coastal and inland waters. The project developed a general framework where uncertainty connected to monitoring of biological indicators (which is associated with evaluation and classification of ecological status) can be systematically assessed in order to improve the coherence and transparency of status assessments. The ultimate goal was to reduce uncertainty in monitoring using more appropriate sampling designs and various ways to account for the factors contributing to uncertainty. Within the WATER-project the cost-effectiveness of monitoring was not considered (Lindegarth et al. 2013).

The MARMONI-project’s socio-economic assessment aimed at facilitating the construction of both cost- efficient and policy-compliant marine biodiversity monitoring schemes in the project’s countries. The first analysis revealed that current national monitoring data supply was inadequate to comply with the MSFD requirements. The project developed new indicators, as well as testing new indicators and monitoring methods; the main purpose was to fill major gaps in biodiversity monitoring related to the key functional groups. They proposed the use of new methods in order to modernize monitoring and to improve its cost-effectiveness (Figure 4.3). The optimal design of schemes was not studied; spatiotemporal sampling frequency was only used to calculate monitoring costs and to identify their socio-economic impact (i.e. the policy-compliance of monitoring). The assessment was built on three aspects of monitoring: costs, compliance (with MSFD) and confidence (i.e. accuracy of the used methods to obtain data for indicators). Different alternatives of monitoring schemes were analysed: current (existing indicators and methods), hypothetical-1 policy compliance (including new indicators and current methods) and hypothetical-2 policy compliance (including new indicators and new methods) (Figure 4.4). Compliance and confidence score varied from 0 to 4; the compliance was assigned to

indicators and was not country specific, whereas confidence was assigned to the monitoring methods and varied among the countries.

MARMONI observed that some new methods can reduce costs and increase compliance of monitoring as they improve spatial and temporal coverage of sampling. However, as many sample analyses require skilled personnel, they concluded that the cost-efficiency of a monitoring programme can be best improved if the field, laboratory and data treatments are developed in balance (Veidemane & Pakalniete, 2015).

Figure 4.3 The core elements of the socio-economic assessment in MARMONI-project (Veidemane & Pakalniete, 2015).

Figure 4.4 Scenario approach for the analysis of monitoring schemes (Source: Pakalniete K., MARMONI- project).

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

4.3 DEVOTES framework for cost-effectiveness analysis of marine biodiversity monitoring activities

To run the MCDA for the three case-studies, DEVOTES applied Rapfish, a non-parametric evaluation methodology, developed by the Fisheries Centre at the University of British Columbia, Canada. Before the applications, DEVOTES adapted the Rapfish tool to be applied in the context of marine monitoring. Rapfish methodology has already been used to compare the sustainability status of many fisheries (Alder et al., 2000; Baeta et al., 2005; Preikshot et al., 1998; Tesfamichael and Pitcher, 2006; Murillas et al, 2008; Murillas et al, 2014; Garmendia et. al, 2009), it is now being adapting to assess aquaculture (Rapaqua), and for ecological restoration sites (Raprestore), and there have been pilot studies of its application to assess recreational fishing quality (http://www.rapfish.org/home/news). This research report presents the first attempt to adapt Rapfish to assess the effectiveness and the cost-effectiveness of marine monitoring activities. The application of Rapfish is a five-step process:

 Step 1: identify and define potential attributes according to which the cost-effectiveness of marine monitoring programmes will be assessed. These attributes are grouped into three categories: ecological, economic and social.  Step 2: Make the attributes comparable by scoring them. Kavanagh and Pitcher (2004) provide approximate scores on a scale from the worst to the best score. Following their approach, minimum and maximum possible levels are established for each attribute.  Step 3: Define the objective and scenarios of the cost-effectiveness analysis.  Step 4: Run the analysis.  Step 5: Run sensitivity analysis using Monte Carlo simulation and run leverage analysis to check the effect of removal of one attribute at a time on the process to assess the cost-effectiveness.

4.4 Attributes for the cost-effectiveness analysis

Identification and definition of the attributes for the cost-effectiveness analysis (Step 1) was an iterative process. First a long list of attributes was developed (Table 1) and for each case study this list was later revised and updated to be context specific. Most of the attributes of the environmental criteria are based on the DEVOTES deliverable D3.1. The economic and social criteria were developed based on a literature review and on internal workshops in DEVOTES (MS7 report).

The economic criteria include all costs that occur when the monitoring effort takes place. The monitoring effort can be divided into three general steps, starting with the design of the indicator and planning of the monitoring parameters needed. The second step involves the deployment of equipment (such as a research vessel, plane, remotely operated vehicles) and where necessary, personnel to collect and bring back samples. Lastly, samples need to be prepared and analysed, and results need to be interpreted and reported. All these steps should be included in the cost estimates to be able to see where the costs occur. The economic criteria could thus include the following attributes: personnel costs (including overheads and other costs); equipment costs; ship costs; subcontractor costs. 26

The ecological criteria provide insight into how well the monitoring programme responds to its purpose, which is to provide sound information about the status of the environment that is then used to guide environmental policy making. Some of the potential attributes have been reviewed in DEVOTES Deliverable 3.2 (D3.2: ‘Report on the criteria for good indicators selection’) which uses the ICES (2013) criteria as a starting point. In the ICES (2013) report, 16 criteria that aim to review the appropriateness of an indicator were identified and these were reduced to 7 in D3.2. The ecological criteria could include the following attributes: scientific basis; ecosystem relevance; responsiveness to pressures; possibility to set targets.

In addition to economic and ecological criteria, a social criterion was included. No references to social criteria being used in assessing environmental monitoring systems were found in the literature review. With regard to industries and livelihoods such as fishing, however, social criteria have been used (see for example Brooks, 2010). These are attributes that reflect the quality of life of the employees and the community they work in. In addition to economic income and employment, ‘social capital’ criteria have been used as a social attributes. These include the relationship networks that provide feelings of belonging; access to information, knowledge and decision making, which provide a sense of control; security; and purpose in people’s lives. However, monitoring is not an industry as such that employs people and affects the social environment of its employees and the society, but a tool for research and environmental assessments. In the DEVOTES cost-effectiveness of monitoring workshop, the attributes within this criteria that were discussed are: employment/personnel number; reusability of data for different purposes, new knowledge – value of information; information: data acquisition and availability; legally defendable; accreditation (adequacy of processes, capacity building, skills of staff, maintenance of skills, experience of staff involved, etc.); citizen science (opportunity for public to contribute), standardised method (different people can use and understand it).

Table 4.1 shows the list of 26 potential criteria and attributes that could be used in a CEA for monitoring programmes.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Table 4.1 List of potential attributes according to criteria Nb. Attribute Criter Definition/Notes ia 1 Relevance to cover Based on the number of MSFD indicators assessed due to the monitoring effort. Under the major MSFD GES set of MSFD 29 descriptors criteria and 56 indicators are defined (Appendix 1, Table 1) (COM criteria DEC 2010/477/EU) 2 Scientific basis Based on sound scientific concept as documented by peer reviewed publications and general acceptance within the scientific community. There is a conceptual understanding between pressure and indicator response with some degree of consistency in that response. 3 Ecosystem relevance Needs to be indicative of changes within a biological component that reflect the status of the ecosystem in terms of structure and function/process. It should also be linked to ecosystem services where possible (based on documented evidence/published, peer-reviewed literature)

4 Responsiveness to Reflects changes in ecosystem component that are caused by variation in any specified pressure manageable pressure. Must have a high signal to noise ratio. The indicator should respond sensitively to particular changes in pressure. The response

Ecological should be unambiguous and in a predictable direction, based on theoretical or empirical knowledge, thus reflecting the effect of the pressure on the ecosystem component in question 5 Possibility to set The indicators should provide a basis for setting targets against which environmental status targets can be objectively assessed. Clear targets that meet appropriate target criteria (absolute values or trend directions) for the indicator can be specified that reflect management objectives, such as achieving GES. 6 Precautionary Indicators that signal potential future change in an ecosystem attribute, before actual harm, capacity/early are advantageous (to include in a suite of indicators along with supporting environmental warning/anticipator data). This could facilitate preventive management, which could be less costly than y restorative management. 7 Concrete, Indicators should ideally be (easily and) accurately determined using technically feasible and measurable, quality assured methods. Quantitative measurements are preferred over qualitative, accurate, precise categorical measurements which are, in turn, preferred over expert opinions and professional and repeatable judgment. For assessment at a large spatial scale (e.g. Regional Sea), data availability may not be sufficient to enable the use of quantitative indicators. Therefore qualitative or semi- quantitative indicators are likely to be required. Accuracy – ability to test bias in the context of natural/expected spatial and temporal variability Precision – assess sampling effort to achieve required level of precision (power analysis, species area curves, how much needed to get a significant effect. Repeatable – requirement to identify contextual information in the methodology to enable

transference of application and use independent quantification methods

8 Cost-effective Sampling, measuring, processing, analysing indicator data, and reporting assessment outcomes, should make effective use of limited financial resources. The cost of achieving a

certain level of accuracy and precision and spatial cover should be considered. Economic A good indicator should provide high quality data at an affordable cost. This may involve expensive sampling techniques but this could be offset by high resolution data covering a large spatial area (e.g., aerial surveys) 9 Existing ongoing Indicators must be supported by current or planned monitoring programs that provide the monitoring data* data necessary to derive the indicator. Ideal monitoring programs should have a time-series capable of sup-porting baselines and reference point setting. Data should be collected on multiple sequential occasions using consistent protocols, which account for spatial and temporal heterogeneity. A time series data set constitutes a knowledge base 10 Personnel costs : Total personnel cost of those who process and interpret the raw data (with unit used appropriate to the case study). Laboratory/desk analysis personnel cost 11 Sustained Total cost of the fixed sampling stations (e.g. buoys), including the equipment cost for the observatory cost sampling station, personnel cost of developing and running the station

Nb. Attribute Criter Definition/Notes ia 12 Field survey cost Total cost of "going out" (i.e. field work) to do the survey per year: equipment cost (including the vessel or other transport), staff cost, sub-contractor cost 13 Subcontractor costs Cost of subcontracting if not included under other cost categories 14 Cost of training Cost of training if not included under other cost categories (training given might also be a social criteria)

15 Cost synergies Different types of cost synergies could be included: (i) Synergies within other MSFD

descriptors: does the monitoring activity inform us of the state of other descriptors (i.e. not just the biodiversity descriptors)?. (ii) Synergies with other policies, programmes (CFP, WFD,

conomic HD,…)- Reusability of data. Does the monitoring activity inform us of the state of other issues E that fall under other European (or national??) legislation? 16 Duplication of Is there more than one organisation developing or undertaking the monitoring activity for the sampling efforts same thing in the same place? 17 Others: overhead, Other costs (specify) not included in the rest of the costs insurance, training costs… 18 New knowledge – Power of the new knowledge to help the decision maker’s to choose an optimal course of value of information action ( to achieve the policy targets)

19 Information: data acquisition and availability 20 Employment/ Number of people needed to develop monitoring not included in cost indicators (economic personnel number/ dimension)

hours 21 Legally defendable Legally permissible

22 Accreditation Social Adequacy of processes, capacity building, skills of staff, maintenance of skills, experience of staff involved, etc. 23 Citizen science Opportunity for public to contribute 24 Destructiveness of use of non-invasive techniques instead such as video/camera, remote sensing  scale: monitoring and destructive and non-destructive social acceptability 25 Reusability of data The data can be reused for multiple purposes 26 Standardised Different people can use and understand method Source: Ecological criteria are mainly based on D3.1 DEVOTES and workshops while the rest of the indicators are from internal DEVOTES WP2 workshops (see MS7 report)

4.5 Scoring system for attribute comparison

In order to make the attributes comparable they are assigned scores. Coming from the fisheries field perspective, Kavanagh and Pitcher (2004) provide approximate scores on a scale from the worst to the best score. Following their approach, it is possible to refer to this scale system using the “good” and “bad” terminology for the minimum and maximum possible values for each attribute. Due to the slightly different focus of each of the case studies, the scoring systems used were individually developed to be fit–for-purpose.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

4.6 Multi Criteria Decision Analysis and scenarios

The multidimensional aspect of determining cost-effectiveness of monitoring programmes is a function of the scenario, the case-study (M) and the selected attributes (N) (Figure 4.5). Rapfish reduces the multidimensional problem into a two dimensional space, in which one dimension is the score representing the value of the chosen index and the other dimension represents the fact that other score combinations for the attributes could provide a similar index value (see detailed information in Pitcher et al., 2004). Depending on the characteristics of the applied attributes, different indexes to assess the cost-effectiveness of monitoring can be calculated. For example:

- An ecological effectiveness index (EEI) which consider only the ecological criteria and the related attributes. - A cost-effectiveness -index (CEI) which combines both ecological and economic criteria. The use of Rapfish multi criteria decision analysis enables an assessment of the effectiveness of monitoring programs and provides insight on options to improve effectiveness with the given monitoring budget.

M1 M2 …. MK N1 I11 I12 … I1K N2 I21 I22 … I2K N N3 I31 I32 … I3K ….

NJ IJ1 IJ2 … IJK

M = 1

M1 N1 I1 N2 I2 N N3 I3 ….

NJ IJ

N1……….Nj: case studies; monitoring activities; monitoring programs

M1…….MK: dimensions/criteria

I1…….IJ: Cost-effectiveness index

Figure 4.5. From NxM matrix to Nx1

4.7 Case study 1: Cost Effectiveness of monitoring in the Gulf of Finland

4.7.1 Aim of case study The aim is to assess the cost-effectiveness of monitoring programmes for biodiversity related indicators in the Gulf of Finland in terms of complying with the requirements of the MSFD, here focusing on the descriptors 1 (Biodiversity), 4 (Food webs), 6 (Sea-floor integrity) that are the focus of DEVOTES, but also indicator D2 (non-indigenous species) because the introduction of alien species can have significant effects on the biodiversity of the Baltic Sea. Only monitoring and related costs occurring in Finland are addressed.

4.7.2 Description of national biodiversity monitoring in the Gulf of Finland The Finnish sea areas, both the open sea and coastal waters, have been monitored in accordance with the programme of the COMBINE Baltic Sea protection agreement. Based on this programme, the current monitoring programmes follow the requirements of the MSFD and in addition, the monitoring of coastal waters fulfils the requirements of the WFD and national water protection programmes. The monitoring activities are divided between several research institutes, but main authorities are the Finnish Environment Institute and Regional Environmental Centres coordinated by the Ministry of Environment. The marine biodiversity monitoring basically includes monitoring of all compartments of the marine ecosystem; biota, supporting information on the abiotic environment as well as pressures, and together constitutes five monitoring programmes (marine mammals, birds, fish, benthic habitats and water column habitats), further divided into 19 sub-programmes. Together, these monitoring programmes provide the data needed for the biodiversity indicators of GES in Finland. The Natural Resources Institute Finland is in charge for the marine mammals and fish monitoring programmes, whereas the bird monitoring programme has been jointly coordinated by the Finnish Museum of Natural History, Natural Resources Institute Finland and Finnish Environment Institute, including considerable voluntary work by bird enthusiasts. The monitoring programmes for benthic and water column habitats are primarily implemented by the Finnish Environment Institute and Regional Environmental Centres. In the Gulf of Finland, the marine biodiversity monitoring follows the same monitoring programmes as at national level and the only national sub-programme not implemented in the Gulf of Finland is the European whitefish monitoring.

The monitoring programme for marine mammals constitutes monitoring of the two seal species grey seal and ringed seal, the only marine mammals resident in Finnish waters. The seal monitoring is performed through aerial surveys and additional data on condition and health is obtained from samples

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

gathered from hunted seals and fisheries by-catches. The bird monitoring programme is to a large extent based on voluntary monitoring by bird enthusiasts. In the sea bird monitoring, the number of wintering birds and nesting birds’ population sizes are estimated. The rapidly growing populations of great cormorant and barnacle goose are the focus of monitoring effort. The hunting pressure on sea birds is assessed based on reported hunting catches and occurrences of mass mortalities are recorded. The fish monitoring programme in the Gulf of Finland comprise monitoring of the sea trout population and in coastal areas the abundance of cyprinids is monitored using gillnet sampling.

The monitoring programmes for benthic and water column habitats are divided into the open sea and coastal monitoring. Monitoring of the open sea areas is carried out using the research vessel Aranda. Its three annual voyages cover the northern parts of the Baltic Sea. Nutrients are monitored in January- February, benthic macrofauna and zooplankton in May-June, and zooplankton and phytoplankton in August. Each year, Aranda visits an average of 80 stations within the context of COMBINE monitoring and in total approximately 150 station visits are recorded annually. Of these, around 30 monitoring stations are located in the Gulf of Finland (Figure 3.1). In the coastal waters of the Gulf of Finland, the water quality (hydrography and chlorophyll a concentration) is monitored intensively (>6 times per year) at 10 stations. In addition to the intensive stations water quality is monitored less frequently at around 70 stations (including statutory monitoring). Phytoplankton is monitored at 8, zooplankton at 4, macrophytes at 23 and benthic macrofauna at 112 stations. In addition to the sampling campaigns, remote sensing and the ships of opportunity provided with a ferrybox (Alg@line) provide data on chlorophyll a concentration in the surface and a phytoplankton sample for community analysis is taken eight times per year at one station on the Alg@line route, supporting the water column monitoring programme.

As the monitoring of the Finnish marine environment consist of many monitoring programmes and the monitored area is not restricted to the Gulf of Finland, the cost analysis for biodiversity monitoring has taken a starting point at national sub-programme level and where possible the costs for monitoring in the Gulf of Finland have been estimated based on number of samples or effort in the Gulf of Finland. Table 4.2 gives an overview of the biodiversity indicator (MSFD descriptors 1, 2, 4 and 6) related monitoring programmes and subprograms existing in Finland. The monitoring work needed to collect the information required for these monitoring schemes are described below. A full description of the monitoring of the Finnish marine areas can be found in the Finnish monitoring handbook (Korpinen et al., 2014).

Figure 4.6 Example of Aranda route and sampling stations in the Gulf of Finland (COMBINE1, 2014).

Table 4.2 Finnish monitoring programme and the related indicators responding to MSFD descriptors D1, D2, D4 and D6. Information is based on the Finnish marine monitoring programme for the MSFD (Korpinen et al., 2014). Programme Subprograms MSFD MSFD Indicators Descriptors Criteria Biodiversity: Abundance of D1, D4 1.1, Distribution of seals Marine seals 1.2, Population size of grey and ringed seals and mammals 1.3, population development 4.1, Number of seal pups 4.2, 4.3 Biodiversity: Health of seals D1, D4, D8 1.3, Pregnancy rate of seals Marine 4.1, 8.2 Blubber thickness of grey seal and ringed seal mammals Biodiversity: Archipelagic D1 1.1, Abundance of breeding seabirds Birds birds 1.2, 1.3 Distribution of breeding seabirds Number of species in Favourable Conservation Status according to the Habitats and Birds Directives Number of threatened marine species Biodiversity: Wintering D1, D4 1.1, Abundance of wintering seabirds Birds waterbirds 1.2, Distribution of wintering seabirds 4.2, 4.3 Biodiversity: Mass D1, D8 1.3, 8.2 Occurrence of mass mortalities of guillemots and Birds mortalities of razorbills marine birds Biodiversity: Breeding D1, D4, D8 1.1, White-tailed eagle reproductive capacity Birds success of 1.2, white-tailed 1.3, eagle 4.1, 8.2 Biodiversity: Hunting catch D1 1.2 Numbers of game animals killed Birds Biodiversity: European D1 1.3 Size structure and age-specific mean length of Fish whitefish whitefish ascending spawning rivers in Bothnian Bay 33

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Biodiversity: Sea trout D1 1.1, Juvenile production of sea trout in relation to the Fish 1.2, 1.3 river-specific potential Fishing mortality in different sea trout size classes Biodiversity: Fishing net D1, D4 1.2, 4.3 Abundance of cyprinids in coastal waters Fish monitoring Biodiversity: Open sea soft D1, D2, D4, 1.2, Species richness index of offshore benthic soft- Benthic bottom habitats D6 1.3, bottom fauna habitats 2.1, Size structure of long-lived macrobenthic species 2.2, 4.3, 6.2 Biodiversity: Coastal soft D1, D2, D4, 1.1, Benthic Brackish-water index (BBI) for soft-bottom Benthic bottom habitats D6 1.2, macrofauna habitats 1.3, Size structure of long-lived macrobenthic species 2.1, 2.2, 4.3, 6.2 Biodiversity: Macroalgae and D1, D2, D4, 1.2, Lower depth limits of bladderwrack and red algae Benthic blue mussel D5, D6 1.3, Size distribution of long-living species (in habitats populations 1.4, development) 1.5, 1.6, 2.1, 2.2, 4.3, 5.3, 6.1 Biodiversity: Physical loss D6, D8 6.1, 8.2 Number of permits for dredging and the amount of Benthic and damage of dredged material habitats benthos Amount of contaminants dredged masses (in developement) Cumulative impact of anthropogenic activities (in development) Biodiversity: Zooplankton D1, D2, D4 1.4, Mean size and total stock abundance of Water column composition 1.5, zooplankton habitats and abundance 1.6, Condition of first level grazers (in development) 1.7, 2.1, 2.2, 4.3 Biodiversity: Phytoplankton D1, D2, D4, 1.4, 1.5 Biomass of Phytoplankton Water column composition D5 , 1.6, Phytoplankton’s taxonomic diversity habitats and abundance 1.7, In development: 2.1, 2.2, Proportion of cyanobacteria of the total 4.3, 5.2 phytoplankton biomass Extent, abundance and species composition of the blooms of cyanobacteria and dinoflagellates Ratio of diatoms and dinoflagellates Functional diversity of phytoplankton Biodiversity: Pathogenic D1 1.6 Hygienic indicator bacteria in the sea (in Water column microbes development) habitats Biodiversity: Physical D1 1.4, Secchi-depth Water column monitoring of D5 1.5, Salinity and its change

habitats water column 1.6, 5.2 Temperature and its change Water stratification and its change Biodiversity: Wind waves, D1 1.4, No indicators or targets Water column sea level and 1.5, 1.6 habitats ice conditions Alien species Alien species D2 2.1, 2.2 Introduction of new non-indigenous species Change in abundance of established non- indigenous species Ratios of non-indigenous and native species in well-known species groups In development: Change in abundance and distribution of harmful non-indigenous species Biopollution index

4.7.3 Monitoring costs in the Gulf of Finland Monitoring of the marine biodiversity of the Gulf of Finland is not directly connected to the descriptors or criteria of MSFD, but is composed of several monitoring programmes focusing on different components of the biota. Thus, the monitoring programmes do not follow the same structure as the descriptors, but each monitoring programme produces information relevant to one or more descriptors and their criteria (see Table 4.2). To evaluate the costs for biodiversity monitoring, the costs for the separate monitoring programmes need to be addressed. The easiest way to estimate the costs for marine biodiversity monitoring would be to just sum the resource needs for all monitoring programmes producing data for the biodiversity assessment, but such a lump sum would be rather uninformative and in order to make a cost-effectiveness analysis more detailed information, recognising the costs for different phases of the monitoring programme, is needed. Flow charts describing the different phases in the monitoring programme are helpful, and have been produced for part of the monitoring programmes. The assessment of GES in marine waters is based on indicators. Thus, the cost estimates of monitoring programmes need to be connected to the biodiversity indicators. The data feeding into the indicators is collected through the monitoring programmes and often several parameters need to be considered in the calculations of the indicators. The same parameters may also be utilised in several indicators. Additional parameters, not directly used in the indicator, but necessary for a proper interpretation of the indicators, are also collected in the monitoring programmes. As the different information needed for a specific indicator may be collected in several monitoring programmes, it is not always possible to estimate the cost for an indicator based on only one monitoring programme, but the cost need to be calculated based on parameters.

Two examples of calculation of monitoring costs for sub-programmes are presented here but the full list of biodiversity monitoring programmes and the costs calculation are provided in Annex 1.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Biodiversity monitoring programme for marine mammals

The only marine mammals present in the Gulf of Finland are seals; the grey seal and the ringed seal. Two monitoring sub-programmes have been established to assess the status of the seal populations, covering the abundance of seals and health status of seals.

Sub-programme Abundance of seals

The aim with the monitoring is to follow the seal population sizes and reproduction success, to be able to detect changes in these. To assess the abundance of seals, three indicators have been defined in the Finnish monitoring programme:

 Distribution of seals  Abundance of grey seal and ringed seal and population development  Number of grey seal pups

Methods and costs The grey seal is monitored in May-June during its moulting season when the seals are gathering at their moulting locations. Abundance of seals is monitored by surveillance flights covering all known and potential moulting locations in the outer archipelago zone. All observed seal gatherings are photographed and the numbers of individuals are later counted from the pictures. The aerial surveys are operated during a two week period that is agreed among the neighbouring countries to avoid calculating the same individuals twice. In Finland, there are two separate counting groups: the Gulf of Finland and Archipelago Sea are monitored by one group and the Gulf of Bothnia by another. During the surveillance flights, the plane holds a pilot (from the flight service provider), photographer and bookkeeper (researchers from the monitoring institute). Grey seal pups are counted around ca 50 islets in the outer parts of the Archipelago Sea during two surveillance flights in February-March. All islets are photographed and the pups are counted from the photographs. The seal pup monitoring is usually performed in combination with the Finnish Border Guard’s surveillance flights. The ringed seal is monitored in April within the fast sea ice zone, which varies yearly. In the southern areas the monitoring is not always possible depending on the sea ice situation. Seals are counted along the flight route, or from photographs of larger gatherings, and the results are later extrapolated to cover the total sea ice area.

The overall costs of the seal monitoring programme in the Finnish Game and Fisheries Research Institute (nowadays Natural Resources Institute Finland) were 107,488 euros, and took 0.66 person years (in 2012). The grey seal monitoring flights take about 7 days during which the total flying time is around 40 hours. The plane and pilot are bought from a service provider through a tender. Depending on the plane type, the costs vary around 650–950 €/h + VAT. The total cost for the plane is thus 26,000–38,000 euros + VAT. In addition, the accommodation and travel costs for the pilot are covered. Also the researchers travel and accommodate in the monitoring location. During the flights, a camera is needed, which costs around 1500€, and back up cameras also need to be accounted for. The counting of the grey seals from 36

the photographs takes a couple of months of researcher time (among other work). The reporting of the results, which includes a press release and a statement for the ministry, takes 1-2 days for the researcher. The results from all Baltic Sea countries doing seal monitoring are put together in a yearly HELCOM Seal meeting, for which an additional 2-3 days of researcher time need to be accounted.

The ringed seal monitoring takes about 4 days (2 days in the Gulf of Finland, 2 days in the archipelago), during which the total flying time is around 15 hours. The plane used is cheaper than the one used in grey seal monitoring, and costs about 350€/h. The counting of ringed seals is easier because they occur in smaller groups and can usually be calculated on the spot or within a couple of days. No official statement or report is made about the ringed seal monitoring, but the results are used for the indicator assessment. Otherwise the cost factors are similar to the ones in the grey seal monitoring.

Table 4.3 Yearly costs of the sub-programme for abundance of seals. Type of expenditure Resource needs Aerial surveys -grey seal monitoring 39,680 € (average incl. VAT) -ringed seal monitoring 6,510 € (average incl. VAT) Equipment 3,000 € Personnel costs 0.66 man-years Total costs (2012) 107,488 €

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Abundance of seals

No Is monitoring performed Order from consultant by institute?

Yes

Planning of monitoring

Using satellite photos Travel to RV (plane) (?) (Turku, Vaasa or Helsinki)

Perform surveillance flight(s) (taking photos of perceived seals)

Travel back to office

Analyze photos

Write report

Figure 4.7. Process chart for assessing the abundance of seals monitoring scheme.

Biodiversity monitoring programme for benthic habitats Monitoring of benthic habitats is divided in four sub-programmes, of which two focus on soft bottom habitats in open sea and coastal areas, respectively. Hard bottom habitats are monitored in the “Macroalgae and blue mussel communities” sub-programme. A sub-programme “Physical loss and damage of the sea-floor” focuses on pressures on the benthic habitats.

Sub-programme Coastal soft bottom habitats Indicators The sub-programme for coastal soft bottom habitats is similar to that for the open sea, but sampling is done with smaller boats in the coastal areas. The two indicators in this monitoring scheme are need the same type of data as is collected in the “Open sea soft bottom habitats” sub-programme:

 Benthic brackish-water index (BBI) for soft-bottom macrofauna  Size structure of long-lived macrobenthic species

Methods and costs The sampling activity is similar to the open sea monitoring scheme depicted in Figure 4.8, but smaller boats suitable for navigating in shallower waters are used. As the van Veen grab is operated by winch needing a more robust boat, the shallowest areas are sampled using a hand-operated Ekman grab from a smaller boat. In total, there are 282 sampling stations in regular monitoring. Of these, 112 stations are located in the Gulf of Finland. In addition, 350 stations are monitored as statutory monitoring. As some stations are sampled on rotation, a total of around 360 stations are sampled every year in the Finnish coastal areas.

For coastal monitoring smaller boats are used. The average price for small boat is €1,130 per day (2/3 of stations) and for large boat €3,480 per day (1/3 of stations). The type of boat depends on whether the station is situated in inner or outer archipelago. Sampling in the inner archipelago is most conveniently done using small boats, where as in the more exposed outer archipelago larger boats are needed. . Costs for the sub-programme were estimated using the MARMONI scheme for calculating monitoring costs (Table 4.4).

Table 4.4 Costs for benthic monitoring in coastal waters (ref to MARMONI A5 excel). Type of expenditure € / sample Resource needs Sampling (grab samples) total 580 208,906 -vessel 478 -equipment 6 -personnel 94 Laboratory (community total 235 84,559 composition and abundance) -equipment 8 -personnel 226 Data management and reporting 13 4,645 Fixed costs (overheads) 253 91,211 TOTAL 1,081 389,320

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Planning of macrozoobenthos sampling Optimisation € of sampling

No Order from Is sampling performed consultant by the institute? Analysis of Yes results

Preparation of Assessment of BD sampling status

Hydrography Sampling Supporting onboard R/V Sediment information characteristics

Indicators Sieving of

samples 1.3.3 1.3.4 4.3.4

Preservation of samples Calculation of D2 indicators indicators

Data preparation Occurrence of Transport to alien species laboratory

Size measurements Quantitative analysis Preparation of of macrozoobenthos samples for analysis species composition Biomass analyses

Figure 4.8. Process chart of zoobenthos sampling.

4.7.4 ‘Lessons Learnt’ from Experiences of collecting information on monitoring costs • Start with making a flow chart describing the different steps in monitoring; from planning to assessment and reporting. This will help in identifying from where the costs stem. • Costs may need to be extracted from various sources (interviews with those responsible for monitoring and accountants, or check equipment costs). If possible indicate the level of accuracy of the costs (exact price, good estimate, rough estimate). • As some samples can be used for several analyses and monitoring purposes, it was challenging to allocate the costs for biodiversity monitoring. • Allocation of costs for the use of a research vessel was also challenging, as several monitoring programmes are conducted during the same cruise. We chose an approach where proportion of samples collected for each monitoring programme during the cruise was used to allocate costs between the monitoring programmes. • When assessing the cost-effectiveness of different methods, the full use of the data produced must be taken into account. Although a method proves cost-effective to produce data for an indicator, potential information that can be obtained from a sample using other methods may be overlooked resulting in data deficiency for assessing other indicators. • Compliance and confidence of data and indicators were assessed in this exercise using expert opinion. The principles of how to evaluate compliance and confidence should be agreed on to allow comparisons among monitoring programmes.

4.7.5 The CEA analysis The aim of the Gulf of Finland case study was to evaluate how well the different biodiversity monitoring sub-programmes comply with the MSFD with regards to criteria and ecosystem components (mammals, fish, birds, benthic and pelagic habitats). Initial analysis with ecological criteria only provides an estimate of which sub-programmes have the highest compliance with the MSFD requirements. A baseline was established as the minimum requirement of a sub-programme to fulfil MSFD purposes so that an estimate of the compliance of the sub-programmes to fulfil the MSFD criteria could be obtained. By using the cost data for the biodiversity monitoring sub-programmes and relating them to the respective compliance scores based on ecological criteria, cost-effectiveness indices were calculated. Thus, it is possible to compare a cost-effectiveness index for each of the different sub-programmes and identify how the biodiversity monitoring can be improved, i.e. increase its compliance, in a cost-effective way.

4.7.6 Selected attributes and their scoring Only the sub-programmes of the Finnish biodiversity monitoring programme relevant for the Gulf of Finland were analysed. Thus, two sub-programmes of the Finnish biodiversity monitoring programme are excluded: European whitefish and the mass mortalities of birds.

Eight attributes were used to assess the effectiveness of the sub-programmes, i.e. their compliance with the requirements of the MSFD. Expert elicitation was used to score each sub-programme according to

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

these attributes (Table 4.5 and Table 4.6). Depending on the attribute, scoring is divided into two levels: low (0), or high (2), or three levels: low (0), medium (1) or high (2).

Furthermore, to define the compliance of the monitoring sub-programme to biodiversity component assessments according to the MSFD, only two attributes are used: number of biodiversity components and number of MSFD criteria that can be fulfilled. As most biodiversity monitoring sub-programmes are focused on one biodiversity component, a two level scoring was applied for the criteria on biodiversity components. For the attribute of the MSFD criteria, the scale was derived from the sub-programmes, where at most one sub-programme covered nine MSFD criteria.

To assess the quality of the monitoring programme the confidence of the assessment was considered based on the data collected in the monitoring programme. In order to have high confidence proper spatial and temporal coverage was considered in order to get a reliable estimate of the biodiversity status and to understand the sources of variation. The medium score that coverage does not decrease significantly is somewhat arbitrary, but this class was considered to give a good estimate of the biodiversity status, although it is not optimal. If a reliable estimate of the biodiversity status cannot be achieved the score is 0.

Involvement and maintenance of diverse skills and knowledge, such as highly educated staff, taxonomy specialists etc., were considered under the social criteria human skills. Here, a two level scale was applied, where losing skills or capacity was scored low and maintenance of skills and human capacity was scored high. Extent of work refers to data collection. Using already existing data is cost-effective when considering a single assessment, but in a monitoring perspective, constant collection of new data is needed e.g. to maintain time series. Thus, collecting new data got a high score, whereas only re-using available information got a low score. A two level scoring was applied for this attribute. Regarding synergies, no synergy gains were scored low, whereas utilizing synergies between sub-programmes, got a high score. If the monitoring data only can be applied to fulfilling requirements of the MSFD, data applicability got a low score. If the data additionally fulfils other national or international interests a medium score was given, whereas if the monitoring data additionally can contribute to scientific and societal interests and needs, the criterion got high score.

Table 4.5 Attributes and scorings used for sub-programmes of the Finnish biodiversity monitoring programme. Attributes 0 1 2 Compliance of monitoring programme -Biodiversity only 1 NA several components covered -MSFD criteria covered 1-3 4-6 7-9 Confidence (quality) of assessment -Spatial coverage Too low to do a Spatial coverage of the Provides a fully covering reliable biodiversity assessment does not biodiversity assessment assessment decrease significantly -Temporal coverage Too low to do a Temporal coverage of Includes seasonal/annual reliable biodiversity the assessment does variation in the assessment not decrease biodiversity assessment significantly -Human skills No special skills NA Special skills needed needed (taxonomic, technical, etc.) -Extent of work Only reporting and NA Continuing data re-use of existing collection, indicator data sources calculation and reporting -Monitoring synergies No synergy NA Provides synergy benefits benefits to other to other sub-programmes sub-programmes -Applicability of data Monitoring Monitoring Contribute to societal and designed only to compatible with scientific needs, for fulfill MSFD several directives and example provides data for requirements other national early warning systems and interests future predictions

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Table 4.6 Scoring of the biodiversity monitoring sub-programmes according to the selected attributes

work

MSFD

Spatial Spatial

criteria ofdata

Extent of of Extent

coverage coverage

Synergies

Temporal Temporal

omponents

Biodiversity Biodiversity

Applicability Applicability

c Human skills Human Abundance of seals 0 1 2 2 2 2 0 1 Health of seals 0 0 1 1 2 2 0 1 Archipelagic birds 0 0 2 2 2 2 0 1 Wintering waterbirds 0 1 1 2 2 2 0 1 Breeding success of white-tailed 0 1 2 2 2 2 0 1 eagle Hunting catch 2 0 1 2 0 0 0 0 Sea trout 0 0 2 2 2 2 0 1 Fishing net monitoring 0 0 0 2 2 2 0 1 Open sea soft bottom habitats 2 1 2 2 2 2 2 1 Coastal soft bottom habitats 2 2 0 2 2 2 0 1 Macroalgae and blue mussel 2 2 1 2 2 2 0 1 populations Physical loss and damage of 0 0 2 2 0 0 0 0 benthos Zooplankton composition and 2 2 2 2 2 2 2 1 abundance Phytoplankton composition and 2 2 2 1 2 2 2 1 abundance Pathogenic microbes 0 0 1 2 0 0 0 1 Physical monitoring of water 0 0 2 2 2 2 2 2 column Wind waves, sea level and ice 0 0 2 2 2 0 0 2 conditions Alien species 2 0 0 0 2 0 0 1 Dummy (1BD) 0 1 2 2 1 2 1 1 Dummy (many BD) 2 2 2 2 1 2 1 1

The set of scored attributes was analysed using Rapfish. To set the thresholds all attributes were assessed according to what was considered to be the minimum requirements to fulfil MSFD purposes, with the exception of the attribute Applicability of data, where it was considered that the monitoring data need to be useful also beyond MSFD requirements (Table 4.7). Depending on whether the sub- programme accounted for only one biodiversity component or several biodiversity components different thresholds were set. Using these minimum threshold scores for the attributes, dummy monitoring programs were built and run in Rapfish together with the monitoring sub-programmes. The monitoring sub-programmes were then compared with the dummy programmes to interpret their compliance to the MSFD requirements.

Table 4.7. Scoring of the Dummy monitoring programmes to set the thresholds for minimum requirements to serve MSFD. Sub-programmes considering only Sub-programmes considering one biodiversity component several biodiversity components Biodiversity components only 1 several MSFD criteria 4-6 7-9 Spatial coverage Sufficient to provide a reliable Sufficient to provide a reliable assessment assessment Temporal coverage Sufficient to provide a reliable Sufficient to provide a reliable assessment assessment Human skills Indifferent in terms of skills needed Indifferent in terms of skills needed Extent of work Collection of new data is essential Collection of new data is essential Synergies Indifferent in terms of synergies Indifferent in terms of synergies with other monitoring programmes with other monitoring programmes Applicability of data The monitoring should not only be The monitoring should not only be because of MSFD because of MSFD

To estimate the cost-effectiveness of the different biodiversity monitoring sub-programmes and to be able to compare them, the effectiveness scores derived from the Rapfish-analysis were divided by the estimated costs for each sub-programme. This value is not to be taken as an exact definition of the sub- programmes cost-effectiveness and the absolute numbers should not be compared, but rather gives an opportunity to rank the sub-programmes.

4.7.7 Results Analysing the biodiversity monitoring sub-programmes using the chosen attributes, the sub- programmes accounting for only one biodiversity component reaching above the threshold were: Abundance of seals, Archipelagic birds, Breeding success of white-tailed eagle and Sea trout sub- programmes. Of the sub-programmes covering several biodiversity components the following reached above the set threshold: Open sea soft bottom habitats, Zooplankton composition and abundance, Phytoplankton composition and abundance and Physical monitoring of water column sub-programmes (Figure 4.9). The common denominator of all the sub-programmes that reached the threshold of minimum requirements was that the attributes spatial and temporal distribution, human skills and extent of work were scored in the highest category in all these sub-programmes.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

100

80 70 SEI 60 50 SEI 40 economicindex Threshold (1 BD) - 30

20 Threshold (many BD) Socio 10

Sea trout

Alienspecies

Huntingcatch

Healthof seals

Archipelagicbirds

Abundanceof seals

Pathogenicmicrobes

Winteringwaterbirds

Opensea soft bottom…

Physicalmonitoring of…

Fishing net monitoring

Zooplanktoncomposition…

Windwaves, sealevel and…

Breedingsuccess ofwhite-…

Phytoplanktoncomposition…

Physicallossand damage of… Coastalbottomsoft habitats Macroalgaeand blue mussel… Figure 4.9. The Rapfish socio-economic index (SEI) for the different biodiversity monitoring sub- programmes (red: sub-programmes considering one biodiversity (BD) component, green: sub- programmes considering several biodiversity components). The thresholds of minimum requirements to serve the MSFD used in the analyses are indicated with horizontal lines.

Based on our approach to estimate cost-effectiveness, the Archipelagic birds sub-programme comes out as using most resources per effectiveness score, whereas the Macroalgae and blue mussel populations sub-programme uses the least (Figure 4.10). As costs could not be estimated for the Wintering waterbirds and Breeding success of white-tailed eagle sub-programmes, these are excluded from this analysis.

Macroalgae and blue mussel populations Pathogenic microbes Physical loss and damage of benthos Alien species Phytoplankton composition and abundance Hunting catch Coastal soft bottom habitats Open sea soft bottom habitats Health of seals Zooplankton composition and abundance Fishing net monitoring Abundance of seals Sea trout Physical monitoring of water column Wind waves, sea level and ice conditions Archipelagic birds 0 500 1000 1500 2000 2500 3000 Euro/Socio-Economic Index

Figure 4.10 Cost-effectiveness ranking of the biodiversity monitoring sub-programmes.

4.7.8 Discussion In the Rapfish analysis several biodiversity monitoring sub-programmes were below the threshold of MSFD compliance. Their prominent weaknesses were:  Health of seals: Responding to few MSFD criteria, poor spatial and temporal coverage  Wintering waterbirds: Poor spatial coverage  Hunting catch: Responding to few MSFD criteria, poor spatial coverage and relying on data collected elsewhere  Fishing net monitoring: Responding to few MSFD criteria and poor spatial coverage  Coastal soft bottom habitats: Poor spatial coverage  Macroalgae and blue mussel populations: Poor spatial coverage  Physical loss and damage of benthos: Responding to few MSFD criteria and relying on data collected elsewhere  Pathogenic microbes: Responding to few MSFD criteria, poor spatial coverage and relying on data collected elsewhere  Wind, waves, sea level and ice conditions: Responding to few MSFD criteria and relying on data produced elsewhere  Alien species: Responding to few MSFD criteria, poor spatial and temporal coverage

Generally, to improve the effectiveness of the sub-programmes that scored below the threshold the weaknesses of the sub-programmes should be considered. For sub-programmes that responded to few MSFD criteria it could be considered if it is possible to modify the sub-programme so that more MSFD criteria can be covered. For example, the fishing net monitoring could potentially be modified, or the 47

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

data could be utilised to develop additional indicators that cover more MSFD criteria. However, for some of the other sub-programmes it may not be feasible to try to modify the programmes to cover more MSFD criteria, as would be the case for Health of seals, Hunting catch and Pathogenic microbes.

Sub-programmes presently having poor spatial and/or temporal coverage can be improved by increasing the relevant aspect of the sampling effort. However, for such a solution it has to be kept in mind that increasing spatial and temporal coverage would most likely also increase the costs of the sub- programme. Regarding the Health of seals sub-programme, it is not feasible to increase the spatial and temporal coverage of data as the samples for this monitoring sub-programme mostly stem from hunted seals and seal caught as by-catch by fisheries. The same is true also for the Hunting catch sub- programme. The Pathogenic microbes sub-programme rely on data collected elsewhere, and thus an increase in spatial coverage may not be easily achieved if additional sampling is not initiated. In the Wintering birds sub-programme spatial coverage is difficult to increase using the present observation method. As the distribution of sea birds is highly dependent on the ice conditions and counting is done from the shore, different methodology, e.g. aerial surveys, would be needed to increase the spatial coverage. For the Fishing net monitoring, Coastal soft bottom habitats and Macroalgae and blue mussel populations sub-programmes an increase in sampling intensity could improve the spatial coverage of the data produced. In order to improve the spatial coverage of the Alien species sub-programme additional sampling in for example harbours is needed to cover the most vulnerable sites for species introductions.

To improve the biodiversity monitoring sub-programmes scoring low in the Extent of work criteria, additional sampling would be needed to decrease the dependency on data collected elsewhere. With additional sampling, spatial and/or temporal coverage could also be improved in some sub- programmes. However, it needs to be considered if the sub-programmes depending on data collected elsewhere are of types that are worth investing in to improve the biodiversity assessment, or if they are included only because they are easily available.

The cost-effectiveness ranking of the sub-programmes can be utilised to see which sub-programmes of those scoring below the minimum threshold considered required for MSFD purposes can be improved to meet the requirements for least amount of money, given the restrictions of improvement mentioned earlier. The sub-programmes where the easiest improvements could be done, were the Fishing net monitoring, the Coastal soft bottom habitats and the Macroalgae and blue mussel populations sub- programmes. For these an increase in spatial coverage would improve the overall scoring. The Macroalgae and blue mussel populations sub-programme is the most cost-effective of these, so increasing the spatial coverage of this sub-programme would be an effective way to improve the biodiversity monitoring programme. However, an assessment of how much additional sampling, i.e. how many more dive transects (in the case of the Macroalgae and blue mussel populations sub-programme), is needed to increase the spatial representability would be necessary to judge if this would be feasible.

In theory, and if linearity can be assumed between the outcome of the Rapfish analysis and the costs of each sub-programme, the cost to bring sub-programmes performing below the threshold to the threshold of minimum requirements for MSFD purposes could be estimated. Similarly the savings could be estimated of reducing the efforts in sub-programmes that perform above the threshold but still ensuring that they fulfil the requirements. This is of course a very speculative approach, and each sub- programme would need to be looked at separately if such assumption can be made. As already stated, some of the sub-programmes cannot feasibly be improved to the threshold level.

The monitoring of open sea areas in the Gulf of Finland is cost-efficient in the way that expenses for the research vessel, which make up the largest single cost, are used efficiently as many monitoring programmes are performed and combined during the same cruises. Phytoplankton, zooplankton, macrobenthic fauna as well as physical and chemical monitoring are undertaken during the COMBINE monitoring cruises. In addition, the data collected during these cruises are also utilised in the monitoring of alien species and samples are also collected for monitoring of radioactive substances in the sediments, oil pollution and toxins produced by cyanobacteria blooms. Thus, the ship costs per monitoring programme cannot be notably reduced. As many parameters are sampled at the same time, additional value is provided to the interpretation of results. Also in the coastal monitoring, cost- efficiency is strived for by combining sampling efforts. Parallel to the sampling for water quality, phytoplankton and zooplankton samples are collected. The exception is the coastal zoobenthic monitoring, where sampling is relatively time consuming and thus water quality samples cannot be taken at the same time as they need to be transported to the laboratory at the same day.

The choice of monitoring methodology can also affect cost-effectiveness. Different monitoring methods were not compared as part of this work, but were investigated in the MARMONI-project (Veidemane & Pakalniete, 2015). Regarding the cost-effectiveness of methods for producing data for indicators, the MARMONI project concluded that adopting a semi-automated approach to measure size of bivalves can improve the cost-effectiveness of producing data for the indicator “Population structure of Macoma balthica”, although the confidence of the data is slightly poorer. However, the cost for length measurements of bivalves is only a small part of the total costs for the benthic monitoring and produce data for only one indicator. The indicator can describe the functionality of benthic communities, but it cannot displace the other benthic indicators in describing biodiversity of benthic communities as it only represents one species. Sampling effort to obtain samples for the length measurement of bivalves will not increase, but the same samples collected for taxonomical analysis and assessment of the state of the benthic communities can be utilised. Thus, extra costs connected to adding this new indicator to the assessments and monitoring programme will only arise from the analyses.

Comparing the traditional microscopy method to analyse zooplankton samples with an automated Figure analysis (ZooFigure) indicated that ZooFigure is an economical method to produce the data needed for the indicator “Mean size and total stock of zooplankton” (Veidemane & Pakalniete, 2015). At present, this indicator is the only indicator developed for zooplankton, but as microscopy analysis

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

provide additional data required for instance in monitoring of alien species, the traditional microscopy method provides more value for money. Moreover, future development may involve zooplankton indicators directed more towards biodiversity and then data with higher taxonomical resolution will be needed.

Phytoplankton monitoring is carried out utilizing a set of observation platforms: sampling from research vessel (open sea) or boats (coastal area), ferrybox sampling and remote sensing. All of these platforms have their pros and cons. Sampling from research vessel at open sea and following laboratory analyses give a good taxonomic precision, whereas the spatial resolution is only adequate and temporal resolution is poor. In coastal areas the temporal resolution is better, but few stations are intensively sampled. The ferrybox system provides high temporal resolution along the shipping route, however the spatial component is restricted, as the ship only follows the same route. Additionally, only hydrographical parameters, including chlorophyll a concentrations, are measured continuously. Samples for taxonomic analysis are only collected from one spot, and not at every passage. Remote sensing offers good spatial and temporal coverage, but no taxonomic information can be derived using this method. Thus, the different methods can be seen as complementing each other and together providing more information than any of them used alone. In terms of biodiversity, the taxonomic resolution has to be considered as most important, even if good spatial and temporal resolution of chlorophyll a concentrations, indicating the biomass of phytoplankton or cyanobacteria, can provide information on the state of the environment.

4.8 Case study 2: A cost-effectiveness analysis to marine monitoring activity in the Bay of Biscay

4.8.1 Aim of case study

The main objective is to understand how effective existing monitoring programmes in the Bay of Biscay are at contributing to achieving the MSFD requirements, considering the underlying costs. The case study summarizes the key aspects of the results of a quantitative assessment of the cost-effectiveness of monitoring activities in the Bay of Biscay. It provides an overview of the cost-effectiveness status of the implementation of monitoring activities needed to reach the requirements set by the MSFD. The cost- effectiveness analysis is carried out considering the adequacy of the monitoring costs given the outputs obtained from the monitoring activity and their contribution to the assessment of the different MSFD Descriptors (D). This work emphasizes the importance of revising monitoring activities with respect to both their scientific basis and also their associated cost.

Marine Strategy Framework Directive descriptors D1. Biological diversity is maintained. The quality and occurrence of habitats and the distribution and abundance of species are in line with prevailing physiographic, geographic and climate conditions. D2. Non-indigenous species introduced by human activities are at levels that do not adversely alter the ecosystem. D3. Populations of all commercially exploited fish and shellfish are within safe biological limits, exhibiting a population age and size distribution that is indicative of a healthy stock. D4. All elements of the marine food webs, to the extent that they are known, occur at normal abundance and diversity and levels capable of ensuring the long-term abundance of the species and the retention of their full reproductive capacity. D5. Human-induced eutrophication is minimised, especially adverse effects thereof, such as losses in biodi• versity, ecosystem degradation, harmful algal blooms and oxygen deficiency in bottom waters. D6. Sea-floor integrity is at a level that ensures that the structure and functions of the ecosystems are safeguarded and benthic ecosystems, in particular, are not adversely affected. D7. Permanent alteration of hydrographical conditions does not adversely affect marine ecosystems. D8. Concentrations of contaminants are at levels not giving rise to pollution effects. D9. Contaminants in fish and other seafood for human consumption do not exceed levels established by Community legislation or other relevant standards. D10. Properties and quantities of marine litter do not cause harm to the coastal and marine environment. D11. Introduction of energy, including underwater noise, is at levels that do not adversely affect the marine environment.

4.8.2 Monitoring costs in the Bay of Biscay

AZTI research institute has developed monitoring activities in the coastal and offshore marine waters of the Bay of Biscay (BOB) for the past 25-30 years in the framework of different regional, national, and European projects. In addition to the WFD monitoring network, which started in 1995 within estuaries and along the coast, three offshore sampling locations were introduced between 2002 and 2006 (Borja et al., 2011) with standardised monitoring practices as a means to better contribute to the MSFD. The application of the MSFD was directly related to the introduction of these last three sampling locations, which obviously could be also used to get information to meet other aims outside the application of the MSFD. In addition to these sampling locations, three scientific campaigns have been carried out yearly since 2010. These monitoring activities are not developed under the context of specific monitoring programmes and they are considered to be part of the AZTI´s ongoing activity. As the obtained data is used to assess the MSFD requirements, it therefore represents the most important monitoring activity in the Bay of Biscay (AZTI does not represent the official body in charge of the implementation of the different pieces of legislation, in particular the implementation of the MSFD, but contributes to the application of many of them).

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Material costs, travel costs, personnel costs, and subcontracting are the main cost type attached to these campaigns. The distribution of these costs in relation to each MSFD descriptor has been determined (Figure 4.11)

120000

100000 Personnel hours /indicator 80000 Personnel total costs

60000 Travel costs

40000 Other costs

20000 Material costs

0 D1 D10 D2 D3 D6 D7 D8

Figure 4.11 Costs (€) attributed to the different MSFD Descriptors during the different monitoring activities undertaken by AZTI that contribute to the MSFD monitoring for the Bay of Biscay. D1: biodiversity, D2: non-indigenous species, D3: commercial fish, D6: sea-floor integrity, D7: hydrography, D8: contaminants, D10: litter.

4.8.3 Methodology: selected criteria and attributes and the scoring system applied

Rapfish has been used to assess the cost-effectiveness of monitoring programmes delivered by AZTI taking into account economic, ecological, and social criteria, with a total of fifteen attributes. This case study was chosen due to the availability of suitable data for capturing information on cost-effectiveness of marine monitoring activities over the short-term. A long term analysis would require a longer time series of data, which is not available given the early stage in the application of the MSFD, although it would be possible to get longer time series for specific MSFD indicators.

The list of attributes for the criteria, and a scoring system for them was compiled (Table 4.8, as described above (sections 4.4 and 4.5)).

Table 4.8 Attributes and scoring system for the Bay of Biscay case study Number attributes Possible “Bad” “Good” Notes scores

1 Coverage of 0,1,2 0 2 less than 50% of MSFD indicators (0), 50-75% (1), more than 75% (2) major GES indicators 2 Scientific basis 0,0.5,1 0 1 Fully met (1): peer-reviewed literature; Partially met (0.5): documented but not peer-reviewed; Not met (0): not documented or peer-reviewed literature is contradictory 3 Ecosystem 0,1 0 1 Fully met (1): the metric complies with indicator function; Not met (0): the metric does not comply with indicator (ecosystem element) function relevance 4 Responsiveness 0, 0.5,1 0 1 Fully met (1): the indicator is primarily responsive to a single or multiple pressures and all the pressures stated relationships are fully understood to pressure and defined, both under the disturbance and recovery phases of the relationship; Partially met (0.5): the indicator´s response to one or more pressures are understood, but the indicator is also likely to be significantly influenced by other non-anthropogenic (e.g. environmental) drivers, and perhaps additional pressures, in a way that is not clearly defined. Response under recovery conditions may not be well understood; Not met (0): not clear pressure state relationship is evident. 5 Possibility to set 0, 0.5,1 0 1 Fully met (1): an absolute target value for the indicator is set; Partially met (0.5): no absolute target set for the indicator, but a target trend targets direction for the indicator is established; Not met (0): targets or trends unknown. 6 Precautionary 0,1 0 1 Fully met (1): indicator provides early warning because of its high sensitivity to a pressure or environmental driver with short response capacity/early time; Not met (0): relatively insensitive indicator that is slow respond warning/anticipat ory 7 Concrete, 0, 0.5,1 0 1 Fully met (1): data and methods are technically feasible, widely adopted and quality assured in all aspects, an/or signal to noise ratio is high; all measurable, data for the indicator are quantitative; Partially met (0.5): potential accurate, precise issues with quality assurance, or methods not widely adopted, poor signal to noise ratio; and/or data for the indicator are semi-quantitative and repeatable or largely qualitative; Not met (0): indicator is not concrete or doubtful; noise excessively high due either to poor data quality or the indicator is unduly sensitive to environmental drivers and/or the indicator is largely based on expert judgement. 9 Existing on going 0, 0.5,1 0 1 Fully met (1): long-term and ongoing data from which historic reference levels can be derived and past and future trends determined; Partially monitoring data met (0.5): no baseline information, but ongoing monitoring or historic data available, but monitoring programme discontinued, however potential to reestablish the programme exists; Not met (0): data sources are fragmented, no planned monitoring programme in the future. 10 Personnel costs 0,1,2, 2 0 RÉLATIVE COSTS, cost value for each assessed issue in relation to the rest of issues: Low (0), medium (1), high (2) 11 Sustained 0,1,2 2 0 RELATIVE COSTS: Low (0), medium (1), high (2) observatory costs 12 Field survey costs 0,1,2 2 0 RELATIVE COSTS, cost value for each assessed issue in relation to the rest of issues: Low (0), medium (1), high (2) 15 Cost synergies 0, 1,2 0 2 SYNERGIES: No (0), Partially (1), Yes (2) 16 Duplication of 0,1 1 0 DUPLICATION: No (0), Yes (1) sampling efforts 20 Employment 0,1,2 2 0 RELATIVE number of hours needed by all people employed in monitoring. It is a relative number Low (0), medium (1), high (2) 22 Accreditation 0,1,2 0 2 SKILL: low (0), medium (1), high (2) (skill of the staff)

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

4.8.4 Results This section presents the results obtained using Rapfish analysis focusing first on ecological criteria estimating the ecological effectiveness index, and then producing a cost-effectiveness index that takes into account the combined ecological, economic and social attributes.

4.8.4.1 Relative ecological effectiveness index, EEI By considering only the ecological criteria to produce an ecological effectiveness index (EEI), compliance with MSFD requirements is assessed using different approaches depending on the particular objectives and the data availability:

Approach 1: This approach considers monitoring activity in relation to the Commission Decision (COM DEC 2010/477/EU) coverage of MSFD indicators for GES and thus only considers attribute 1 “Coverage of major GES indicators” (¡Error! No se encuentra el origen de la referencia.). Attribute 1 assesses how many MSFD indicators it is possible to assess given the current level and quality of monitoring activities. It addresses the questions: Does the monitoring system allow a complete or a partial assessment of each MSFD indicator? Which and how many ecosystem components are included in the assessment of each MSFD indicator? For example, for Descriptor 3 concerning populations of all commercially exploited fish and shellfish, Approach 1 considers how many fish and shellfish populations are included in the monitoring activities. For D1 Biodiversity, ideally monitoring should be extended to all ecosystem components, ranging from plankton to mammals (Borja et al., 2011). Under Approach 1 it is assumed that all the indicators established by Commission equally meet certain ecological attributes, such as: scientific basis or ecosystem relevance (i.e. other ecological attributes listed in ¡Error! No se encuentra el origen de la referencia.).

Approach 2: This approach considers the quality of the monitoring activities in their coverage of the MSFD indicators. Thus, it takes into account the quality of the assessed MSFD indicators (attributes 2 to 7 (¡Error! No se encuentra el origen de la referencia.) in contrast to Approach 1, which puts the emphasis on the quantity of indicators addressed by monitoring activities (attribute 1 (¡Error! No se encuentra el origen de la referencia.). Under this second approach only attributes 2 to 7 (¡Error! No se encuentra el origen de la referencia.) are included in the analysis, and it is assumed that not all the indicators established by Commission equally meet certain ecological attributes, such as: scientific basis or ecosystem relevance.

Approach 3. This approach combines the two previous ones; that is, it considers that effectiveness of monitoring depends on how well monitoring covers different descriptors (through indicators) and also on the quality of the ecological attributes. This approach tends to produce similar results to approach 2, since the number of attributes included under approach 3 is usually higher than in approach 1. Thus, the best way of producing the EEI is to develop both previous approaches to get the complementary information from both approaches.

Under Approach 1 (Figure 4.12) the EEI (represented on the horizontal axes of Figure 4.12) of D2 (non- indigenous species) and D7 (hydrological conditions), has a value close to 0, which implies few or no MSFD indicators are assessed, the opposite happens for descriptor D8 (contaminants) where the EEI value is close to 100, indicating that many indicators are assessed for this descriptor. Low dispersion is observed in the vertical axis for most of the index values of the different Descriptors, except for D2 and D7. For these descriptors, potential changes in the attribute scores could produce a very different index result.

However, it is very important to understand these results together with the index values coming from Approach 2. The best and worst EEI results would not be as extreme when taking into account the quality of the assessed indicators.

-10 0 10 20 30 40 50 60 70 80 90 100

D1 D2 D3 D4 D5 D6 D7 D8 D10

Figure 4.12 Ecological effectiveness index (EEI) by MSFD descriptor under Approach 1

When moving to Approach 2, ¡Error! No se encuentra el origen de la referencia. shows how the EEI, represented by the horizontal axes, lies between 20 and 88, with lowest values related to D7 (hydrological conditions) and D10 (marine litter), meaning that the monitoring for these descriptors is of poorer quality. In general, low dispersion is observed in the vertical axis for most of the Descriptors, with the exception of D7, which shows higher dispersion and thus its effectiveness level could be achieved through the combination of very different scores of the selected attributes, which could have some management implications. In the Bay of Biscay the only indicator that contributes to the assessment of D7 is 7.1.1 Extent of area affected by permanent alterations, for which information is obtained from diverse monitoring activities. These activities do not appear to be very effective for assessing this indicator since D7 has the lowest possible scores for most attributes: scientific basis, ecosystem relevance, responsiveness to pressures, possibility to set up targets, existing or ongoing monitoring.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

0 10 20 30 40 50 60 70 80 90 100 EEI D1 D2 D3 D4 D5 D6 D7 D8 D10

Figure 4.13 Ecological effectiveness index (EEI) by MSFD descriptor under Approach 2

Interestingly, D2 (non-indigenous species), which had the lowest EEI under Approach 1, has the highest score under Approach 2. That is, with the monitoring activities that are in place it is possible to assess only one indicator in relation to D2; but, this indicator has the highest quality of all the indicators assessed (i.e. high score values for all the quality attributes). Most other descriptors (except for marine litter) were of moderate-good quality level.

The leverage of individual attributes on Rapfish ordinations determines how much each attribute influences the overall ordination. According to this analysis (Figure 4.13), scientific basis (Attribute 2) is the key attribute influencing the EEI score. In contrast, possibility to set targets (Attribute 5) contributes least to the EEI score under Approach 2. The remaining attributes present a more similar influence.

Concrete, measurable, accurate, precise and repeteable

Precautionary capacity

Possibility to set targets

Responsiveness to pressure

Ecosystem relevance

Scientific basis

0.0 2.0 4.0 6.0 8.0 Root Mean Square Change % in Ordination when Selected Attribute Removed (on Status scale 0 to 100)

Figure 4.14 Ecological effectiveness index (EEI): leverage of attributes

When comparing the EEI score differences between the three approaches, the following results are observed and displayed in Figure 4.15. The change in the EEI between approaches highlights that the outcomes from Approach 1 are rather different from those from Approaches 2 and 3, which are quite 56

similar to each other. The changes in the EEI are low for descriptors D1 (very low), D4, D5 and D7; moderate for descriptors D3, D6 and D8, D10 and very high for descriptor D2.

These results are of great interest in decision making; when differences are large the quality of the mixed EEI is reduced. For example, if data on the quality of monitoring are not available, decision makers are forced to evaluate the compliance of the MSFD purely on the number of MSFD indicators. In the case of D1 (biodiversity), there appears to be a good relationship between the quantity and quality of the compiled MSFD indicators. However, for and D4 (food-webs) and D6 (sea-floor integrity) there is a mismatch, highlighting that monitoring should focus on using higher quality indicators for these descriptors and similarly for D5, D8 and D10.

It is worth noting that for D2 the differences between assessments are the largest, even though there is little data available to assess this descriptor, that data provides a good quality, ecologically based indicator.

120

100

60 EEI 40

0 D1 D2 D3 D4 D5 D6 D7 D8 D10 -20

Approach 2 Approach 1 Approach 3

Figure 4.15 Comparing Ecological effectiveness index (EEI) based on inclusion of Attributes in the analysis: Approach 1 - coverage of MSFD indicators by quantity, Approach 2 - quality of coverage of MSFD indicators, Approach 3 combining quality and quantity of coverage of MSFD indicators

Cost-effectiveness index (CEI) The economic and social sustainability associated with monitoring activities can also be analysed together with the previous ecological effectiveness analysis. CEI should be assessed only once the EEI has been assessed because if the monitoring is not effective then it is not relevant to add the economic dimension to the analysis. The main interest is to fulfil the MSFD requirements and only then to be sure 57

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

this is done at least cost. Thus, in addition to the EEI, marine monitoring could potentially gain in effectiveness by being more cost-effective. One way of reducing costs is to have joint monitoring activities (e.g. joint cruises) across different organizations, hence duplication of sampling effort is an

Attribute within the CEA Repeating the Rapfish analysis, considering all attributes (i.e. ecological, social and economic indicators), produces CEIs from 51 to 84 Figure 4.16, whereas for the previous analysis the EEIs were lower (e.g. 20) for some descriptors

These results highlight that even if some Descriptors are not well supported by monitoring activities (e.g. D7 and D10), they may be comparatively cost-effective. This result may imply that there is a good relationship between the outcomes from monitoring and the costs incurred. The distribution of financial resources among the monitoring activities in the Bay of Biscay seems to be in accordance with the ecological effectiveness attached to the MSFD descriptors, even for D7 and D10, which may justify the current financial distribution.

The monitoring activities for D8 (contaminants) and D5 (eutrophication) are ranked as the most cost- effective. This is possibly due to very specific monitoring activities in place which have been carried out systematically for many years to address these descriptors. Furthermore, monitoring of D3 (commercially exploited species) also ranks amongst the highest. In this case, the existing monitoring programs within other policies are likely to highly and positively contribute to the cost-effectiveness of this descriptor. Regarding the biodiversity descriptors (D1, D4, and D6), it is not surprising to find them as being “medium” cost-effective, since they are quite complex descriptors, which encompass a rather large number of indicators.

A Monte Carlo analysis was performed to evaluate potential effects on the CEI score due to different errors (for example associated with uncertainty in the raw data, or the subjectivity of the scoring system). The CEI outcomes after several iterations Figure 4.17 display similar results to those observed in Figure 4.16. Horizontal and vertical axes represent similar issues as before (Figure 4.16): the CEI is represented on the horizontal axes while dispersion is observed in the vertical axis for the index values of the different Descriptors (that is, potential changes in the attribute scores which could produce very different index results). The leverage of individual attributes is shown in Figure 4.18 In this case the main attributes influencing the CEI scores are those pertaining to the socio-economic criteria. There is a notable influence of personnel costs, cost synergies and existing on-going data (highlighted in Figure 4.18) but the influence of employment is less important.

0 10 20 30 40 50 60 70 80 90 100

D1 D2 D3 D4 D5 D6 D7 D8 D10

Figure 4.16 Relative Cost-effectiveness index (CEI) by MSFD descriptor

0 0 10 20 30 40 50 60 70 80 90 100 CEI -10

-20

-30

-40

-50

-60

-70

Figure 4.17 Cost-effectiveness index (CEI) Monte Carlo analysis

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Duplication effort

Employment

Accreditation

Sustained observatory costs

Field survey costs

Personnel costs

Existing and on going data

Cost synergies

Relevance to cover major GES indicators

Concrete, measurable, accurate, precise and…

Precautionary capacity

Possibility to set targets

Responsiveness to pressure

Ecosystem relevance

Scientific basis

0,0 1,0 2,0 3,0 4,0 5,0 6,0

Figure 4.18 Leverage of the Cost-effectiveness index (CEI) attributes

4.8.4.2 Determining minimum and critical thresholds

Despite the apparently good CEI of the monitoring activities in the Bay of Biscay for most of the MSFD descriptors, it is recommended to introduce minimum and if possible, critical CEI thresholds. In this subsection we explore how minimum and critical levels can be set that could be used as reference points to determine whether marine monitoring is cost-effective or not. The identification of thresholds enables the assessment of the CEI in relative terms (the relative position of the estimated CEI for the different MSFD descriptors), and also in absolute terms - because managers would be able to get an individual output for each MSFD descriptor by comparing the CEI with the estimated thresholds. In order to determine these thresholds, for this particular case study, each attribute must be assigned a minimum threshold score that can be considered as "good enough" in relation to the good level value (100). This procedure has been done following Garmendia et al, (2011). The Rapfish analysis is then repeated using these new minimum threshold scores for the attributes as a “dummy” monitoring programme. The Rapfish result for this dummy monitoring is designated as the minimum threshold or reference point. In this case study intermediate score values for each attribute are applied as minimum threshold values (e.g. 0.5 where the scores ranges from 0 to 1). The results of Rapfish, displayed in Figure 4.19, show that the threshold CEI is around 57, (52 to 59 using Monte Carlo analysis). Comparing with the previous results (Figure 4.16) CEI values for D1, D10 and D7 are below this threshold, D4 is close to it, and the remaining descriptors (D2, D3, D6, D8 and D5) are above it. Monitoring activities providing information on those descriptors whose CEI value is below this threshold should be reviewed, in order to identify where efforts should be placed considering all three criteria. In the Bay of Biscay and at the EU level, great efforts are being placed particularly regarding D1 (biodiversity) as it reflects on

much of the information of other descriptors, as well as D10 (marine litter) which has had increasing attention recently. In addition, a critical threshold is also estimated by repeating a similar procedure for the minimum threshold. Each manager decides the values but as a potential example intermediate reference values for each ecological attribute are applied but at a maximum cost for the following cost-related attributes: personnel costs, field survey costs, and sustained observatory costs. This dummy scoring represents a state in which a manager could allocate a very large amount of money but only attain an intermediate value for each attribute. Notice this dummy score should be defined by each manager for each case study and should be taken as a threshold scenario. The results of Rapfish estimate the critical threshold to be around 53, (52 to 55) using Monte Carlo analysis). Even under this critical threshold, none of the monitoring for descriptors (D1, D7, and D10) would be considered as cost effective. Figure 4.20 shows the CEI values in relation to the minimum and critical thresholds.

0 0 10 20 30 40 50 60 70 80 90 100

Minimum threshold for the CEI -1

-2

-3

-4

Figure 4.19 Minimum threshold Monte Carlo analysis

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

95 85 75 65 55 45 D1 D2 D3 D4 D5 D6 D7 D8 D10

CEJ CEI Critical threshold Minimum threshold

Figure 4.20 Cost-effectiveness index (CEI) in relation to the minimum and critical thresholds

Figure 4.18 shows that the key attributes influencing the CEI are related to the economic criteria, but in the leverage analysis Figure 4.21 the key attributes relate to the ecological criteria, in particular, the responsiveness to pressure, the ecosystem relevance and the scientific basis. At the critical threshold, both economic and ecological criteria, are influential. In particular, the key attributes are: sustained observatory costs, field survey cost, personnel cost, responsiveness to pressure, ecosystem relevance and scientific basis. This result indicates to policy makers which attributes are important at different stages..

Duplication effort Duplication effort Employment Employment Accreditation Accreditation Sustained… Sustained… Field survey costs Field survey costs Personnel costs Personnel costs Existing and on… Existing and on going… Cost synergies Cost synergies Relevance to… Relevance to cover… Concrete,… Concrete,… Precautionary… Precautionary capacity Possibility to set… Possibility to set… Responsiveness… Responsiveness to… Ecosystem… Ecosystem relevance Scientific basis Scientific basis 0.0 1.0 2.0 3.0 0.0 0.5 1.0 1.5 Root Mean Square Change % in Root Mean Square Change % in Ordination when Selected Ordination when Selected Attribute Attribute Removed (on Status Removed (on Status scale 0 to 100) scale 0 to 100)

(a) (b) Figure 4.21 Leverage of the Cost-effectiveness index (CEI) attributes around the minimum threshold (a) and critical threshold (b)

4.8.4.3 Discussion

This work analyses the cost-effectiveness of Bay of Biscay marine monitoring using the Rapfish methodology. This technique facilitates research into the cost-effectiveness of monitoring in a multidimensional and multicriteria framework providing relevant and useful information for policy makers. The application of Rapfish is not straightforward, and both the criteria and attributes themselves and the scoring system have been redefined to adapt them to the context of this case study. Two relative indexes are estimated, firstly, the EEI, based on ecological attributes and producing an effectiveness index and secondly, the CEI which provides an assessment of the relative cost- effectiveness by adding the socio-economic attributes, in relation to the EEI. The latter shows the relative position of the CEI scores for the different MSFD descriptors. According to this relative position the following ranking is achieved from the least to the most cost-effective monitoring in terms of contribution of monitoring activity to the assessment of the MSFD indicators: D7, D10, D1, D4, D3, D6, D2, D8, and D5.

However, in order to derive cost-effectiveness knowledge in absolute terms and determine whether monitoring is (or is not) cost-effective at each relative position under the previous ranking, thresholds are needed. This work presents two thresholds: a minimum and a critical threshold. Two of the biodiversity descriptors (D1 and D4) fall close and other descriptors (D7 and D10) fall below the minimum threshold. Leverage analysis shows that all the attributes are relevant in determining the cost-effectiveness index. Following Tesfamichael and Pitcher (2006), the attributes which scored highly in leverage should be given due attention in future planning of cost-effective monitoring. In this sense, it is possible to differentiate between key attributes depending on the distances that exist between the CEI and the thresholds. The outcomes of the leverage analysis differ depending on whether the focus is on minimum or critical thresholds (Figure 4.21). Whereas ecological attributes make the highest contribution at the critical threshold, economic criteria become more influential at the minimum threshold. Such information can be very relevant for defining/adjusting monitoring programs.

Integration of the ecological, and socio-economic attributes in a unique CEI enables exploration of potential trade-offs among these different criteria. Win-win situations are hard to find and policy makers usually face complex decisions where ecological improvement could be in conflict with an excessive monetary cost. Thus, it is important to check first if the EEI value is above a minimum ecological (EEI) threshold before determining a more complex/complete CEI or, developing both indexes to be sure about the compensability limits which is similar to producing a strong index.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

4.9 Cost efficiency of marine monitoring activity: A case study in the UK 4.9.1 Aim of case study The objective for the UK case study is to examine the cost-efficiency of existing plankton monitoring programmes that will inform the state of pelagic habitats in UK waters. For this analysis, cost-efficiency is defined as whether the existing monitoring programmes for pelagic habitats/plankton are fulfilling the requirements of MSFD monitoring purposes given the costs being incurred.

4.9.2 Description of monitoring in the UK Case Study Area Due to the significant overlaps between the biodiversity descriptors, the UK’s approach to developing targets and indicators for these descriptors was to focus on three species groups (marine mammals, birds and fish) and three habitat groups (pelagic habitats, sediment habitats and, rock and biogenic reef habitats) (HM Government, 2012). The Department for Environment, Food and Rural Affairs (Defra), which is the main government body responsible for the implementation of the MSFD in the UK, published the Marine Strategy Part 2 in 2014 (Defra, 2014). This identifies existing monitoring programmes that will be used to monitor the state of GES descriptors and their associated indicators. It also identifies gaps that will be addressed by new monitoring programmes that will be developed. The Table 4.9 and Table 4.10 below provide a summary of the monitoring programmes for biodiversity and the descriptors and indicators covered.

Table 4.9 Species: Descriptor 1 (Biodiversity) and Descriptor 4 (Food Webs) Monitoring Programme Descriptors/Indicators covered Fish International Bottom Trawl Survey  MSFD Indicator 1.1.1: Distributional range (Continental Shelf Seas and (IBTS), supplemented by additional fish Shelf-edge Seas) surveys such as the English Beam Trawl  MSFD Indicator 1.1.2: Distributional pattern within range (Continental Survey and herring acoustic survey Shelf Seas and Shelf-edge Seas)  MSFD Indicator 1.2.1: Population abundance  MSFD Indicator 1.2.1: Population biomass based on Fish population biomass  MSFD Indicator 1.3.1: Populations demographic characteristics  MSFD Indicator 1.7.1: Composition and relative proportions of ecosystem components  MSFD Indicator 4.2.1: Large fish by weight  MSFD Indicator 4.3.1: Abundance trends of functionally important selected groups/species Marine Mammals (Seals and Cetaceans)  UK Seals Monitoring Programme Seals  UK By-catch Monitoring Scheme  MSFD Indicator1.1.1: Distributional range  UK Stranding Scheme  MSFD Indicator 1.1.2: Distributional pattern within range  Inshore Bottlenose Dolphin  MSFD Indicator 1.2.1: Population abundance Population Monitoring Scheme  MSFD Indicator 4.3.1: Abundance trends of functionally important selected groups/species.  MSFD Indicator 4.1.1: Performance of key predator species using their production per unit biomass (productivity) Cetaceans  MSFD Indicator 1.1.2: Distributional pattern within range.

 MSFD Indicator 1.2.1: Population abundance  MSFD Indicator 4.3.1: Abundance trends of functionally important selected groups/species  MSFD Pressure Indicator: Population condition pressure indicators based Harbour porpoise bycatch and short-beaked common dolphin bycatch Birds (seabirds and waterbirds)  The Seabird Monitoring  MSFD Indicator 1.1.2: Distributional pattern within range Programme (SMP)  MSFD Indicator 1.2.1: Population abundance  The Wetland Bird Survey (WeBS)  MSFD Indicator 4.3.1: Abundance trends of functionally important  The Breeding Bird Survey (BBS) selected groups/species.  supplemented by data from  MSFD Indicator 1.3.1: Population demographic characteristics. periodic surveys to monitor  MSFD Indicator 4.1: Performance of key predator species using their indicators of change in the production per unit biomass (productivity) distribution of seabird breeding colonies, waterbird coastal breeding sites and intertidal wintering or migration sites of shorebirds

Table 4.10 Habitats: Descriptor 1 (Biodiversity), 4 (Food Webs) and 6 (Seafloor integrity) Monitoring Programme Descriptors/Indicators covered Pelagic Habitats  2 programmes collecting and  MSFD Indicator 1.4.1: Distributional range. monitoring plankton:  MSFD Indicator 1.4.2: Distributional pattern o Fixed sampling stations;  MSFD Indicator 1.6.1: Condition of the typical species and o Continuous Plankton Recorder) communities  MSFD Indicator 1.6.2: Relative abundance and biomass.  MSFD Indicator 1.7.1: Composition and relative proportion of ecosystem components  MSFD Indicator 4.3.1: Abundance trends of functionally important selected groups/species  MSFD Indicator 6.2.2: Multi-metric indexes assessing benthic community condition and functionality. Benthic habitats (does not cover D4; only D1 and D6 are applicable) By 2014, habitat monitoring will be Sediment habitats and Rocky and Biogenic Reefs Habitats supported by a strategy developed by  MSFD Indicator 1.4.1: distributional range the JNCC-led Biodiversity Monitoring  MSFD Indicator 1.4.2: distributional pattern R&D Programme. There are a number of  MSFD Indicator 1.5.1: habitat area the monitoring programmes that are  MSFD Indicator 1.6.1 Condition of the typical species and already well-established...these include communities monitoring within coastal water bodies  MSFD Indicator 6.1.1: Type, abundance, biomass and areal extent of using WFD tools for intertidal sediment relevant biogenic substrate habitats, subtidal sediment habitats,  MSFD Indicator 6.1.2: Extent of the seabed significantly affected by intertidal rocky habitats and saltmarshes human activities for the different and intertidal seagrass beds.

4.9.3 Cost Efficiency Analysis

As shown in Table 4.10 above, the Continuous Plankton Recorder and fixed sampling stations are the monitoring programmes in the UK for pelagic habitats or plankton. The analysis undertaken here is not a comparison of the relative merits of the two plankton monitoring programmes as the data gathered and the information produced from these are not substitutes but are instead complementary with each other. Instead, the analysis aims to highlight overlaps and gaps between the two monitoring

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

programmes in order to identify areas where the efficiency of plankton monitoring in the UK could be achieved. This means that the analysis is not strictly a cost-effectiveness analysis since the least cost- option for plankton monitoring is not identified.

Due to the UK’s approach in developing targets and indicators for the MSFD, the MSFD indicators on plankton cover the three biodiversity descriptors 1 (Biodiversity), 4 (Food Webs) and 6 (Seafloor integrity). The MSFD indicators that will be used to monitor the status of pelagic habitats/plankton in UK waters according to the MSFD descriptors and criteria are shown in Table 4.11.

Table 4.11 UK MSFD indicators for pelagic habitat MSFD Descriptor MSFD Criterion UK target UK indicator 1 Biodiversity 1.4 Habitat At the scale of the MSFD sub-regions, distribution of 1.4.1: Distributional distribution plankton community is not significantly adversely influenced range. by anthropogenic pressures, as assessed by indicators of 1.4.2: Distributional changes in plankton functional types (life form) indices pattern

1.6 Habitat At the scale of the MSFD sub-regions, condition of plankton 1.6.1: Condition of the condition community is not significantly adversely influenced by typical species and anthropogenic pressures communities 1.6.2: Relative abundance and biomass. 1.7 Ecosystem At the scale of the MSFD sub-regions, structure of plankton 1.7.1: Composition structure community is not significantly adversely influenced by and relative anthropogenic drivers, as assessed by indicators of changes proportion of in plankton functional types (life form) indices ecosystem components 4 Food Webs 4.3 Abundance/ At the scale of the MSFD sub-regions, 4.3.1: Abundance distribution of key abundance/distribution of plankton community is not trends of functionally trophic significantly adversely influenced by anthropogenic important selected groups/species pressures, as assessed by indicators of changes in plankton groups/species functional types (life form) indices 6 Seafloor 6.2 Condition of At the scale of the MSFD sub-regions, condition of plankton 6.2.2: Multi-metric integrity benthic community is not significantly adversely influenced by indexes assessing community anthropogenic pressures benthic community condition and functionality.

Continuous Plankton Recorder Continuous Plankton Recorder (CPR) surveys are operated by the Sir Alistair Hardy Foundation for Ocean Sciences (SAHFOS) to monitor the near-surface plankton of the North Atlantic and North Sea on a monthly basis on a network of specified shipping routes. Commercial passenger and cargo vessels have helped and continue to voluntarily help in the survey (referred to as ‘ships of opportunity’ in the literature) by towing a CPR during trips.

The activities involved in this monitoring programme, excluding the management of the programme, can be roughly divided into logistics, sampling and maintenance of equipment, processing of raw data,

data entry and analysis. Richardson et al. (2006) provide an in-depth description of the sampling and analysis techniques used in the CPR. The sampling technique involves the towing of the CPR at the standard depth of around 7 metres, with water entering the CPR through a small opening and into a silk filtering mesh that captures and preserves the plankton. The samples are then transferred to the lab for identification and analysis. There are four stages of analysis for the samples covering different aspects of the plankton: 1) the phytoplankton colour index; 2) larger phytoplankton cells; 3) smaller zooplankton; and 4) larger zooplankton. The analysis is undertaken by trained taxonomists using microscopes.

The UK’s Department for Environment, Food and Rural Affairs provides funding for the Continuous Plankton Recorder monitoring programme and the total funding set aside for the programme for 2011 to 2021 is just under £3.5million2 or around £350,000 per year over the 10-year period. This funding covers approximately 21% of SAHFOS’ main sampling effort in the North Atlantic (David Johns, SAHFOS, pers. comm.). The survey covers a large area around the UK as shown in Figure 4.22, but not all areas are frequently sampled due to coverage being limited to the routes of the ships of opportunity.

Figure 4.22 Routes of Continuous Plankton Recorder (CPR) tows around the UK (source: David Johns and Abigail McQuatters-Gollop, SAHFOS, pers. comm.)

2http://randd.defra.gov.uk/Default.aspx?Menu=Menu&Module=More&Location=None&Completed=0&ProjectID= 18079#Description 67

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Fixed sampling stations

There are 13 fixed sampling stations for physical, atmospheric, biological and chemical parameters around the UK (Scherer et al. 2015). The locations of these stations are presented in Figure 4.23 below as pink dots. Different sampling techniques are employed for these sampling stations, including the use of bottles, net tows and instrumented buoys that take and preserve water samples.

Figure 4.23 Locations of fixed sampling stations around the UK (source: Scherer et al, 2015)

To illustrate the operations within these fixed sampling stations and to aid the analysis, we focus on the Western Channel Observatory (WCO). The WCO has two sampling stations L4 and E1 which are operated by the Plymouth Marine Laboratory and the Marine Biological Association. In situ biological (e.g. plankton samples), chemical (e.g. nutrients) and physical (e.g. temperature) measurements are taken from these 2 stations; weekly at the L4 station while fortnightly measurements are done at the E1 station. Figure 4.24 shows the location of these stations relative to the south-west coast of England.

Figure 4.24 Locations of the Western Channel Observatory’s L4 and E1 fixed sampling stations, in the Western English Channel (source: http://www.westernchannelobservatory.org.uk/l4_e1_map.php)

A range of plankton sampling techniques are used in the L4 and E1 sampling stations. For example, zooplankton is sampled using fine meshed nets that are hauled vertically along the water column or across the surface3, whereas phytoplankton is sampled at a depth of 10 metres using a 10 litre Niskin bottle4. Microscopic analysis is used to identify major zooplankton taxonomic groups while the inverted microscopy is used to identify and analyse phytoplankton samples.

A significant amount of funding for the sampling at the L4 and E1 stations and the resulting analysis of the data gathered is provided by the UK’s Natural Environmental Research Council. The estimated costs for these sampling stations for MSFD purposes is around £250,000 per year (Stefanie Broszeit, Plymouth Marine Laboratory, pers. comm).

4.9.3.1 Selected effectiveness attributes and scoring

The effectiveness attributes chosen for this task were based on the discussions and workshops held during the DEVOTES Annual meetings in Ancona (2014) and Lisbon (2015). Recommendations from the Technical guidance on monitoring for the MSFD (Zampoukas et al, 2014) and recommendations on plankton monitoring for the MSFD in the UK (Scherer et al, 2015) were also taken into account. These attributes reflect the important aspects of a monitoring programme with regard to the need to inform MSFD assessments on the state of the marine environment, and in this case, pelagic habitats. The attributes and scoring used for the UK case study (

3 http://www.westernchannelobservatory.org.uk/documents/pml-wco_phytoplankton_protocols.pdf 4 http://www.westernchannelobservatory.org.uk/documents/pml-wco_phytoplankton_protocols.pdf 69

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Table 4.12 Effectiveness attributes and scoring systems for UK plankton monitoring

Rationale for including the Attributes Issues(s) to consider Score Definition of Score attribute Yes, sampling has been and is still done at regular intervals in order to Does the time period 2 capture short, medium and long for which the sampling It is essential that changes over term changes in relevant plankton is or has been time are captured in order to characteristics. Temporal undertaken sufficient to distinguish between natural Sampling is done irregularly but the coverage capture the changes in variations and human-induced total period over which sampling 1 relevant plankton changes. has been done is long enough to characteristics? capture changes. Sampling is done irregularly and is 0 not sufficient to capture changes The information captured should Samples are taken at appropriate be at a spatial level that is 2 points which are representative of aligned with the coverage of the the region of interest. Are plankton samples MSFD, which is at a marine Samples are taken at appropriate taken at appropriate Spatial region and sub-regional level. 1 points but there are gaps in points which are coverage Additionally, the spatial coverage coverage within the region covered. representative of the should take into account region of interest? The coverage is insufficient to be dynamics in the marine 0 representative of the region of environment that affect the interest. distribution of plankton. The monitoring activity covers all 2 Coverage of key features of plankton. Plankton is composed of the relevant There are some features that are Does the monitoring different types (e.g. phyto- and features or not covered by the monitoring activity capture relevant zooplankton) and species, and it 1 properties activity, but most of the key ones features or types of is essential that a comprehensive of what is are captured. plankton? or complete ‘picture’ of plankton being There are too many key features is captured. monitored. 0 not covered by the monitoring activity. Does the monitoring Covers more than 5 (out of 11) 2 activity inform us of the There are many links between MSFD descriptors Coverage of state of other the MSFD descriptors therefore Covers more than 1 but less than 5 MSFD 1 descriptors (i.e. not just it is important for these links to MSFD descriptors descriptors the biodiversity be covered where they exist. 0 Covers only 1 MSFD descriptor descriptors)? Synergies The objectives of the MSFD are Yes, provides data to support more Does the monitoring with other linked to several other policy 1 than 1 policy area/ EU Directive/ activity inform us of the policies, areas or Directives (e.g. the National legislation state of other issues programme Water Framework Directive) that fall under other Provides data to support only 1 s- therefore it is important for the European and national 0 policy area/ EU Directive/ National Reusability data produced to be re-usable to legislation? legislation of data inform these policies. Covers more than 50% of the 2 relevant indicators (i.e. pelagic Coverage of more indicators habitat indicators) How many MSFD implies that a broader range of Coverage of Covers more than 25% but less than indicators does the information on the status of MSFD 1 50% of the relevant indicators (i.e. monitoring activity relevant GES descriptors can be indicators pelagic habitat indicators) cover? gathered; i.e. a better picture can be provided with less effort. Covers less than 25% of the 0 relevant indicators (i.e. pelagic habitat indicators) 70

The data and/or results are fully Marine areas defined in the compatible or comparable with MSFD are shared by different EU 2 data from other member and/or Could the data and member and non-member non-member states. Comparabili results be easily states. It is essential that data The data and/or results are partly ty and combined with data and the analysis produced by compatible or comparable with compatibilit from other Member Member States can be easily 1 data from other member and/or y of data States in order to compared and put together to non-member states. and results contribute to a regional provide a coherent regional or The data and/or results are not assessment? sub-regional picture of GES and compatible or comparable with to facilitate coordination of 0 data from other member and/or management measures. non-member states.

) is intentionally different from the ones used in the Bay of Biscay and Gulf of Finland case studies due to the different focus of the assessment, i.e. on plankton monitoring instead of a high level biodiversity monitoring. We are assuming that a monitoring programme is fully compliant with the requirements of the MSFD (for plankton/pelagic habitat monitoring), and thus cost-efficient, if it attains the maximum score for all the attributes.

Table 4.12 Effectiveness attributes and scoring systems for UK plankton monitoring

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Does the monitoring Covers more than 5 (out of 11) 2 activity inform us of the There are many links between MSFD descriptors Coverage of state of other the MSFD descriptors therefore Covers more than 1 but less than 5 MSFD 1 descriptors (i.e. not just it is important for these links to MSFD descriptors descriptors the biodiversity be covered where they exist. 0 Covers only 1 MSFD descriptor descriptors)? Synergies The objectives of the MSFD are Yes, provides data to support more Does the monitoring with other linked to several other policy 1 than 1 policy area/ EU Directive/ activity inform us of the policies, areas or Directives (e.g. the National legislation state of other issues programme Water Framework Directive) that fall under other Provides data to support only 1 s- therefore it is important for the European and national 0 policy area/ EU Directive/ National Reusability data produced to be re-usable to legislation? legislation of data inform these policies. Covers more than 50% of the 2 relevant indicators (i.e. pelagic Coverage of more indicators habitat indicators) How many MSFD implies that a broader range of Coverage of Covers more than 25% but less than indicators does the information on the status of MSFD 1 50% of the relevant indicators (i.e. monitoring activity relevant GES descriptors can be indicators pelagic habitat indicators) cover? gathered; i.e. a better picture Covers less than 25% of the can be provided with less effort. 0 relevant indicators (i.e. pelagic habitat indicators) The data and/or results are fully Marine areas defined in the compatible or comparable with MSFD are shared by different EU 2 data from other member and/or Could the data and member and non-member non-member states. Comparabili results be easily states. It is essential that data The data and/or results are partly ty and combined with data and the analysis produced by compatible or comparable with compatibilit from other Member Member States can be easily 1 data from other member and/or y of data States in order to compared and put together to non-member states. and results contribute to a regional provide a coherent regional or The data and/or results are not assessment? sub-regional picture of GES and compatible or comparable with to facilitate coordination of 0 data from other member and/or management measures. non-member states.

4.9.3.2 Scoring of the plankton monitoring programmes in the UK

As mentioned above, the analysis of plankton monitoring in the UK is not a comparison of the relative merits of the CPR and the fixed sampling stations as the information produced from these are not substitutes but are both required to inform of the status of pelagic habitats in the UK. Additionally, the E1 and L4 fixed sampling stations are part of a network of sampling stations and therefore contribute to a larger set of ‘fixed points’ data. To aid the analysis, they are used to represent other sampling stations, but it has to be noted that not all fixed sampling stations are operated in the same way. For example, not all stations take both phytoplankton and zooplankton samples. Each of these programmes were evaluated and scored (Table 4.13) relative to the attributes presented in the previous section in order to show how they complement each other and where the gaps are.

To assess the cost-efficiency of these plankton monitoring programmes, we examined if the programmes are fulfilling MSFD requirements given the costs incurred. Where the programme has not been given the highest possible score, we identify gaps and the merits of other options (e.g. ’doing more

of the same’, using new technologies for sampling or analysis) to improve the score. We also refer to the recommendations of Scherer et al. (2015) with regards to how the existing plankton monitoring programme in the UK could be improved. However, as mentioned above, we are not comparing the CPR with the fixed sampling stations. For example, if the fixed sampling station scores are higher than the CPR in one attribute, we do not say that the fixed sampling station should replace the CPR. Instead, we highlight whether one could cover the gap in the other or whether other options need to be considered. On the other hand, if both are not assigned the same but not the highest scores, we do not say that both are equally good or bad but instead identify how they can be improved.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Table 4.13 Evaluation and scoring of attributes of UK plankton monitoring programmes. CPR: Continuous Plankton Recorder Range of Continuous Plankton Recorder E1 and L4 sampling stations score Attributes (lowest to Score Rationale for score Score Rationale for score highest) The fixed sampling stations have The CPR samples most of the North been collecting data for a long Atlantic at a monthly basis and has period. Sampling at station L4 has been since 1951 providing a long time occurs weekly, while sampling at E1 Temporal series. However, due to the sampling 0 - 2 1 2 occurs fortnightly. These are coverage method (i.e. ships of opportunity sufficient to provide information on towing the CPR), the points that are the dynamic changes of what is sampled are not sampled at regular being monitored. intervals.

On their own (i.e. L4 and E1 stations), they cannot give Because of the method of data information on for sub-regional collection (i.e. CPRs are towed by assessment. Results need to be Spatial commercial ships/vessels), a large 0 – 2 1 1 combined with results from other coverage area has been and can be covered. fixed sampling stations. There are However, it does not cover inshore also gaps in coastal sampling in sites. other parts of the UK (e.g. the North Sea) (Scherer et al 2015). A broader picture of the status of Due to the mesh size used to capture plankton is captured by the plankton samples, smaller sampling methods used at fixed Coverage of phytoplankton and zooplankton point stations. This is because the relevant species are under-sampled. different techniques could be features or 0 – 2 1 Additionally, the depth (~7m from the 2 deployed, e.g. finer mesh sizes for properties of surface) at which the samples are net sampling which could capture what is being taken means that plankton that live in smaller plankton species, or taking monitored different parts of the water column samples at lower depths to capture are not captured. species that could only be found in specific areas of the water column. Covers: D1, D4 and D5, but has scope Coverage of to cover D2 as well. However, for D1 Covers D1, D4, D5 and D6, but MSFD 0 – 2 1 1 and D4, only specific to plankton specific to plankton indicators only. descriptors indicators Synergies with Apart from the MSFD, informs the Apart from the MSFD, provides other policies, Water Framework Directive and also information for fisheries programmes- 0 – 1 1 informs on climate change impacts 1 management (e.g. the Common Reusability of and can contribute to fisheries Fisheries Policy) data assessments. The CPR covers the following Covers the following indicators for indicators for plankton: biomass Coverage of plankton: biomass (1.6.1, 1.6.2), (1.6.2), diversity (1.7.1), lifeform index MSFD 0 – 2 2 2 diversity (1.7.1), lifeform index (4.3.1; 1.4.1 and 1.4.2); 5 indicators indicators (4.3.1) and (benthic community out of the 7 for plankton condition and functionality) 6.2.2 (McQuatters-Gollop et al 2015) There are limits in the comparability Like the CPR, there are limits in the and compatibility of data and results comparability and compatibility of from the CPR with those taken by data and results from fixed sampling Comparability other OSPAR region Member States. stations with those taken by other and This is because of Member State OSPAR region Member States. This compatibility 0 – 2 1 national monitoring programme 1 is because of Member State national of data and differences in terms of sampling monitoring programme differences results frequency and methodologies, as well in terms of sampling frequency and as taxonomic techniques and level of methodologies, as well as taxonomic resolution (McQuatters-Gollop et al techniques and level of resolution 2013). (McQuatters-Gollop et al 2013).

4.9.4 Results and discussion

Neither the CPR nor the fixed sampling stations received the highest possible score (Table 4.13) indicating that currently, the plankton monitoring programme in the UK is not providing all the required information for MSFD monitoring purposes given the costs currently being incurred. Scherer et al. (2015) also identified that the current monitoring programme for pelagic habitats in the UK is insufficient to meet the needs of the MSFD. Even though the programmes complement each other with regards to gathering information about the state of pelagic habitats around the UK, there are gaps that exist in how this is currently monitored which imply gaps in knowledge. For example, in the attribute of ’coverage of relevant features’, the fixed sampling stations score higher than the CPR. However, this does not mean that because information on a feature of a pelagic habitat (e.g. small plankton species) is not captured by the CPR, the fixed sampling stations supplement this automatically. This is because the fixed sampling stations do not cover the same spatial extent as the CPR.

As for the coverage of MSFD descriptors, neither the CPR nor the fixed sampling stations were given the highest score, but they covered the necessary descriptors relating to biodiversity (and eutrophication) even though they are only specific to pelagic habitats. Although there are links between the different descriptors, it is not feasible to cover all MSFD descriptors with a single monitoring programme. However, due to the costs involved in sampling and analysis, a programme that covers several descriptors is more likely to be less resource intensive than programmes individually covering each descriptor. The same can be said with regards to indicators within a descriptor or a set of descriptors. Coverage of more indicators implies that a broader range of information on the status of relevant GES descriptors can be gathered; i.e. a better picture can be provided with less effort. In terms of the practicality of using different monitoring programmes to gather data on other aspects of the ecosystem, there have been examples where this has been tested, often referred to as ’opportunistic sampling’. For example, and under efforts for the North Sea case study by Cefas within DEVOTES Work package 5, marine litter, plankton and benthos samples have also been collected during the English 3rd quarter North Sea groundfish surveys5 of the International Bottom Trawl Survey (IBTS)6. Although these efforts are not yet formally adopted for inclusion in the monitoring of other MSFD descriptors in the UK, it shows that other options which do not involve the extension of existing monitoring programmes for specific descriptors/indicators can be utilised to fill evidence gaps. It is possible that these efforts are less costly compared to extending existing monitoring programmes and therefore the more cost- effective approach to ensuring that MSFD-sufficient monitoring for plankton in the UK. For example, the costs for the sampling done for the DEVOTES work on the IBTS described above excluded the costs of the research vessel since this (i.e. research vessel cost) is financed through the Data Collection Framework of DG-MARE.

5 This is the monitoring programme that will contribute towards information on the status of fish (for the relevant biodiversity descriptors and for D3- commercial fish and shellfish). See the UK’s Marine Strategy Part 2 (Defra, 2014). 6 http://www.devotes-project.eu/devotes-fieldwork-conducted-by-cefas/ 75

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

With regards to the comparability and compatibility of data and results with other countries in the North-East Atlantic region, both monitoring programmes were given the middle score of 1. However, to improve on this particular attribute requires coordination between countries at the OSPAR level, which is not something the UK can achieve on its own. The comparability and compatibility of data and results does not only contribute to better understanding of the state of European and sub-regional seas, but it has also been identified as crucial for implementing appropriate management measures (Zampoukas et al., 2014). Additionally, coordinated monitoring efforts could also identify overlaps between monitoring efforts of different countries. Overlaps could indicate resource inefficiencies, and where these could be minimised or avoided indicates potential cost savings.

This assessment of the cost-efficiency of pelagic habitat monitoring has identified gaps and weaknesses in the existing programme in terms of delivering the needs for the MSFD in relation to the current status relative to GES and to support the implementation of appropriate management measures. Scherer et al. (2015) have provided recommendations on how to improve the existing monitoring programmes (i.e. CPR and fixed sampling stations) to support the MSFD in the UK, and the ideal scenario is for improvement in both the CPR and the fixed sampling stations7. However, in the light of resource constraints, it is likely that other options need to be explored. Making use of ‘opportunistic sampling’ during other monitoring activities, as for example, demonstrated by efforts in DEVOTES work package 5, could allow for additional information to be gathered without having to employ a significant amount of resources. However, by its nature of being ‘opportunistic’, there is a risk with regards to inconsistencies with when and where the samples are taken. However, if these opportunistic sampling activities are incorporated with other regular monitoring activities (i.e. ones that occur around the same place at about the same time every year), then the data gathered can provide more meaningful information and supplement the ones gathered in through the CPR and the fixed sampling stations. The development, testing or use of new technologies or techniques for sampling and analysis of plankton, for example the ones that are trialled in DEVOTES8 could also show where existing monitoring could be improved given existing costs or where resources could be saved given reduced budgets for monitoring.

The assessment has also highlighted that improvements in monitoring, either in sampling or analysis, can improve not just the knowledge on the status of the indicator but also on the choice of indicator to use in assessing status relative to GES. It is not appropriate to assume that the MSFD indicators will stay the same since the data and information produced from monitoring experiences informs the development of indicators and the associated GES targets. This means that increasing the effectiveness of monitoring is contingent not only on learning how to improve existing sampling and analysis efforts

7 This involves the establishment of additional fixed sampling stations in areas that are not covered, regular sampling of phyto- and zooplankton at each fixed point sampling station and the establishment of a CPR route in relevant areas within each sub-regional marine areas in the UK as defined in Charting Progress 2. 8 DEVOTES deliverable 5.1 outlines the different technologies explored for monitoring biodiversity. http://www.devotes-project.eu/wp-content/uploads/2014/01/deliverable-5-1.pdf 76

but also on the key issues that need to be monitored. Since monitoring for the MSFD is usually paid for by public resources, the cost is the main constraint in deciding how much or what kind of monitoring could be done. However, sacrificing, for example, temporal or spatial coverage in order to meet cost constraints means sacrificing additional information that will otherwise be crucial in making future decisions. Additional sampling may not always be the key to getting the required information therefore finding other ways to sample or analyse existing data could also provide better insights on the state of the marine environment. This also allows for a more targeted improvement in the current state of pelagic habitat monitoring to ensure that overlaps and inefficient use of resources are avoided.

4.10 Summary

Section 4 describes the work conducted under the DEVOTES Tasks 2.1.1 (‘Identify criteria to determine the cost-effectiveness of different suites of monitoring and assessment systems used and developed for MSFD’) and 2.1.2 (‘Assess the cost-effectiveness of different suites of monitoring and assessment systems used and developed for MSFD’). The overall objective of these two tasks was to assess the costs of the existing marine monitoring programmes against the ability of the programs to deliver data applicable for the marine status assessment required by the MSFD.

The concept of a cost-effectiveness analysis of MSFD monitoring is straightforward. Monitoring programmes to support the MSFD need to be identified followed by measurement the effectiveness of these in terms of informing us about the state of the marine environment in relation to GES. In addition, a cost estimate for the monitoring activities is needed. Then a cost-effectiveness ranking of the activities can be developed and an advice on the set of activities needed to fulfil the objective with the least costs can be given. In practice, however several challenges were faced.

The task was to assess the cost-effectiveness from ecological, economic and social points of view. This gave rise to the use of MCDA. DEVOTESs applied an existing MCDA tool called Rapfish that is able to scale multidimensional problems to a two-dimensional scale. The monitoring programmes of the DEVOTES case-studies varied so much that it was not possible to undertake a common analysis for all the case-study areas. Instead, the case studies follow the same analytical steps following the general MCDA principles modified for the MSFD monitoring. The first step is to define the objectives and any scenarios for the analysis: which monitoring programmes do we want to consider in the analysis and what do we want to find out about them? The second step is to identify potential attributes and then scores for each attributes according to which the cost-effectiveness of marine monitoring activities or programs will be assessed. The third step is the analysis of the cost-effectiveness of the monitoring programmes given the attributes and scores and the cost of the programmes. Lastly, the fourth step is the sensitivity analysis to identify how the effectiveness of the monitoring programmes improves given a change in the scenario (e.g. additional sampling). Estimating the monitoring costs was very challenging, firstly finding the costs and then breaking them down to a level which allows us to identify costs at every stage of the monitoring programme (e.g. sampling, analysis). DEVOTES developed and

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

applied a flow chart approach to illustrate the monitoring process and to identify where the costs incur. The detailed costs were possible to estimate only for the Gulf of Finland case study. The other case- studies used aggregated cost estimates.

The list of attributes against which the effectiveness of the monitoring was assessed was developed based on a literature review, other DEVOTES WP outputs and DEVOTES internal workshops. The initial list of attributes (see Table 4.14) included 26 attributes, but each case-study selected and modified this list to be suitable for the research question in hand; Gulf of Finland case-study used 8 attributes, Bay of Biscay 15 attributes and the UK case-study 7 attributes. Naturally, the threshold values (and definition) used for the effectiveness index also varied by case-study. The results show that for all the case studies there is potential for improvements in the effectiveness of existing monitoring programmes with respect to the MSFD requirements. However, an increase in the effectiveness in respect to MSFD may lead to a decrease in the applicability of the data sets for other environmental monitoring purposes.

Table 4.14 Application in 3 case study sites of the DEVOTES framework for cost-effectiveness analysis of marine biodiversity monitoring activities Gulf of Finland Bay of Biscay UK Evaluate how well the Examine the efficiency of existing different biodiversity plankton monitoring To understand how effectively we Research monitoring sub-programmes programmes in terms of their are contributing to the MSFD question / comply with the MSFD with ability to inform about the status requirements considering the objective regards to criteria and of pelagic habitats relative to underlying costs. ecosystem components Good Environmental Status given covered the costs being incurred. Scenarios NA NA NA 1. Coverage of major GES indicators 2. Scientific basis 1. Temporal coverage 3. Ecosystem relevance 2. Spatial coverage 4. Responsiveness to pressure 1. Biodiversity components 3. Coverage of the relevant 5. Possibility to set targets covered features or properties of 6. Precautionary capacity/early 2. MSFD criteria covered what is being monitored Attributes warning/anticipatory 3. Spatial coverage 4. Coverage of MSFD (common 7. Concrete, measurable, accurate, 4. Temporal coverage descriptors attributes are precise and repeatable 5. Human skills 5. Synergies with other shown in 8. Existing ongoing monitoring 6. Extent of work policies bold) data 7. Synergies 6. Coverage of MSFD indicators 9. Personnel costs 8. Applicability of data 7. Comparability and 10. Sustained observatory costs compatibility of data and 11. Field survey costs results 12. Cost synergies

13. Duplication of sampling efforts 14. Employment 15. Accreditation (skill of the staff) Thresholds were set judging all criteria according to what was considered being the Intermediate score values for each minimum requirements to indicator were applied to estimate a fulfil MSFD purposes, with minimum threshold (e.g. 0.5 when the exception of the score goes from 0 to 1). A critical Applicability of data-criteria, threshold was set with intermediate where it was considered that reference values for each ecological Threshold the monitoring data need to Highest possible score indicator are applied but at a be useful also beyond MSFD maximum costs for the following requirements. Depending on cost-related attributes: personnel whether the sub-programme costs, field survey costs, and accounts for only one sustained observatory costs. biodiversity component or

several biodiversity components different thresholds were set. UK Government funding for the Total Sum cost estimates for each of the Continuous Plankton Recorder: Sum cost estimates for each monitoring scenarios (personnel cost, vessels, £300,000 per year of the scenarios costs etc.) E1 and L4 Fixed sampling stations MSFD cost: £250,000 per year. The plankton monitoring Some room for improvement, programme in the UK is not CEA of especially regarding biodiversity- providing all the required Some room for improvement monitoring related indicators (D1, D4, and D6), information for MSFD monitoring and marine litter purposes given the costs currently being incurred.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

5. Identification and assessment of the socio- economic consequences of management practices aimed at achieving GES

5.1 Cost-benefit analysis: Introduction and methodology

Environmental cost-benefit analysis (CBA) is an approach to account for all effects – positive and negative – of public programmes on societal welfare. It is widely used in the appraisal of public projects in e.g. the environmental, health and transport sectors. Public policy measures, particularly in the environmental sector, produce not only changes in environmental quality, but also affect the living conditions of humans, prices of market goods and services as well as costs and revenues of firms. The aim of any CBA is to test whether total benefits of any particular action are larger than the costs and losses associated with its implementation (Hanley 2001, Hanley and Barbier 2009).

The EU MSFD requires member states to implement programmes of measures (PoMs) that will ensure the marine environment in European regional seas reaches good environmental status (GES) by 2020. In 2012, all member states were required to carry out an assessment of the current state of the marine environment in their jurisdictions to establish a baseline. Each member state then had to plan and implement its own PoMs to achieve GES by 2020. Prior to the implementation of these PoMs the MSFD requires the conduction of impact assessments including CBA (Article 13.3).

A major challenge to the use of CBA in an MSFD framework, however, “is the lack of knowledge on the links between potential measures, improvement of marine ecosystems and corresponding economic and social value” (DG Environment 2015, p. 29). “Environmental economic analyses are interdisciplinary, and sound analyses cannot be produced by economists working in isolation” (Oinonen et al. 2016b, p. 23). While it has been suggested that ecosystem service classifications are a way to map and assess these links (e.g. Interwies et al. 2013b, Bertram et al. 2014), a comprehensive conceptual framework for the use of ecosystem service and benefit categories in the assessments of benefits arising from the implementation of a PoMs under the MSFD is still lacking. Research conducted in DEVOTES WP2 addresses this gap in the literature to facilitate the linking of changes in marine ecosystems caused by the reduction of pressures under new or a modified PoMs and their resulting economic and social benefits.

Several reports have addressed the requirements in the MSFD for socio-economic analysis and CBA in particular (COWI 2010, Bertram and Rehdanz 2013, Bertram et al. 2014), appropriate methods (Turner et al. 2010, WG-ESA 2010, Reinhard et al. 2012, Interwies et al 2013a, b). Bertram and Rehdanz (2013), for example, discuss the limitations of economic valuation in the MSFD context and point out that this threatens the effectiveness of this policy instrument. These authors point out that existing valuation studies in the marine environment focus too much on direct ecosystem benefits and systematically ignore less tangible effects on human welfare. Responding to this concern and building on the above

studies, parts of the present research shift the focus to the applicability of the ecosystem service perspective in the assessment of ecosystem benefits under the MSFD. Although not explicitly required by the Directive, the use of such a perspective for this task has been suggested (WG-ESA 2010, Koss et al. 2011).

A number of CBA frameworks have been cited within the literature (e.g. Boardman et al. 2006; Defra 2007; Hanley and Barbier 2009) and have been successfully applied within a marine context, for example in the case of seabed restoration following the cessation of dredging marine aggregate extraction (Cooper et al. 2011). The present analysis is based on Hanley and Barbier’s (2009) recommendations for environmental CBA which involves the following six steps:

1. Definition of project or policy measure

2. Identification of the impacts of the project or policy

3. Valuation of these impacts in economic terms

4. Discounting of flows of costs and benefits that occur over time

5. Application of the net present value test

6. Sensitivity analysis

These steps and what they involve in particular are detailed in the following sections.

1. Definition of project or policy measure

Any CBA requires a clear definition of the project or policy measure that is to be assessed. Regarding the definition of measures to be implemented within the MSFD, technical, legislative, economic and policy driven actions are possible (DG Environment 2015). Naturally, it is the PoMs to achieve GES which are the focus of any environmental CBA to be conducted in an MSFD framework. In the MSFD these measures are generally referred to as management measures. According to the MSFD, management measures can be classified as existing or new measures. Existing measures (Art 13.1 & 13.2) are:

 Category 1.a: Measures relevant for the achievement and maintenance of GES under the MSFD, that have been adopted under other policies and implemented;

 Category 1.b: Measures relevant for the achievement and maintenance of GES under the MSFD that have been adopted under other policies but that have not yet been implemented or fully implemented;

New measures (Art 13.3) are:

 Category 2.a: Additional measures to achieve and maintain GES which build upon existing implementation processes regarding other EU legislation and international agreements but go beyond what is already required under these;

 Category 2.b: Additional measures to maintain and achieve GES which do not build upon existing EU legislation or international agreements.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Any environmental CBA of PoMs should only consider new measures which are implemented based on either the MSFD or other policies. Each of the three case studies will begin by specifying and justifying the particular management measures under consideration. These measures will be introduced so that the analysis can build on a clear understanding of the changes in management.

2. Identification of the impacts of the project or policy

Once the management measures have been specified in detail, their impacts on affected ecosystems can be identified and where possible quantified. The identification and assessment of the physical impacts of proposed measures is particularly challenging in the marine environment because of open access, transboundary movement of resources and pollution, mixing of cumulative impacts and the general complexity of marine and coastal ecosystems, all of which exacerbates the assessment of the effectiveness and benefits of such measures (DG Environment 2015). It is also necessary to determine a baseline of the current status and future projections that would result without additional management. There are a number of tools that can be employed at this stage and which will be detailed in the case studies:

 Ecosystem and bio-economic modelling: Models project the short and long-term ecological, economic and social impacts in a quantitative way (Peck et al. in press). A set of quantitative indicators is defined together with specific reference values, and it is analysed if and how many objectives can be achieved. Different models enable an indicator-based approach to provide assessments of the successes and failures of management systems with regard to the sustainability dimensions (economic, biological, social and institutional). The Socioec project (EU FP7; www.socioec.eu) emphasised that in the field of fisheries there is an extensive range of models that provide a comprehensive impact assessment of different management alternatives as asked for by the CFP (EC (2013) and Prellezo et al. (2009) reviewed many of the bio-economic models that are already being applied in the EU.  Expert elicitation: In cases where ecosystem (or bio-economic) models do not exist, environmental effectiveness of measures can be estimated based on expert elicitation. Structured group interviews can be used to populate an effectiveness indicator for the measures included in the PoMs (MAGRAMA 2015; Oinonen et al. 2016a).  Scenario analysis: When the level of uncertainty with respect to, for example, the data available for the analysis or future policy circumstances/effects is high, an approach that can be used, together with or as an alternative to ‘what if’ modelling, is the construction of hypothetical, albeit plausible, scenarios (Turner et al. 2014). The Millennium Ecosystem Assessment (MEA 2003) defines scenarios as ‘plausible alternative futures, each an example of what might happen under particular assumptions’. Model projections can be used to construct plausible outcomes from the scenarios, as can expert opinion, and they can be framed in terms of ecosystem service outcomes. For example, Haines-Young et al. (2011) developed six different but internally coherent socio-economic storylines for the future of the UK under the impact of climate change within the UK’s National Ecosystem Assessment. 82

 Ecosystem service assessments: Ecosystem services are the direct and indirect contributions that ecosystems provide for human welfare (de Groot et al. 2010b). The merit of applying an ecosystem services approach for economic valuation is to provide an exhaustive classification of all channels through which these services are provided (e.g. MEA 2005; TEEB 2010; UK NEA 2011) as well as an explicit differentiation between ecosystem functions, the services they provide and the benefits that materialise for humans (Boyd and Banzhaf 2007; Fisher et al. 2008; Ojea et al. 2012; Turner et al. 2015). In practice, indicators have to be developed which capture the extent of ecosystem service delivery in a quantitative way (Hattam et al. 2015a,b; Atkins et al. 2015). These ecosystem service indicators need to be linked to a set of ecosystem benefit indicators that describe the resulting benefits for society.

3. Valuation of these impacts in economic terms

Once the anticipated changes in the provision of environmental goods and ecosystem services have been assessed quantitatively, these can be valued in economic terms. Value in this respect means the effect that the consumption or enjoyment of these goods or services has on human welfare. Environmental valuation seeks to express this effect on people’s utility in monetary terms. The total economic value (TEV) provides a classification for potential value motivation (Turner 1999), i.e. why people value certain goods and services and how their welfare is affected if the provision of these changes. It distinguishes between use and non-use values. Use value can further be subdivided into direct and indirect use as well as option values. Non-use values consist of bequest and existence values. While this classification is useful on a theoretical level it should be noted that on a practical level it is often neither possible nor necessary to distinguish between them.

If the environmental goods or ecosystem services impacted by a certain policy are directly traded in markets, simple market prices (where necessary after subtracting any subsidies or other market distortions) can be used for their valuation. This technique can often be used to monetise the costs of implementing a certain environmental policy, because costs to industry, households and direct implementation costs to administration and authorities can be expressed in terms of extra work effort or forgone profits. The provision of a great number of goods and services is impacted by environmental policies, however, these are often not traded in markets. Therefore, alternative valuation methods have to be used. So-called revealed preference methods, which can measure use values, include hedonic pricing (HP) and the travel cost method (TCM). Both use and non-use values can only be assessed by stated preferences methods, i.e. the contingent valuation method (CVM) (Carson and Hanemann, 2005) and discrete choice experiments (DCE) (Louviere et al., 2000).

The implementation of management measures to achieve GES will affect stakeholders in different ways. These impacts are the opportunity costs, i.e. the value of what is lost or sacrificed in order to implement and comply with the management measure. The costs often included in the analysis are:

 Costs to the regulator and/or government for implementing the management measure. This includes administration and enforcement costs and may be composed of labour, equipment or other capital costs; 83

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

 Costs to businesses or industry for complying with the management measure. This could be in the form of lost earnings and/or additional (one-off or recurring) operating (including labour and capital) costs;  Environmental/damage costs. Implementation of management measures are aimed at reducing environmental pressure or damage. However, there may be cases where the implementation of a measure results in negative impacts;  Social costs. There may be some management measures that have adverse social impacts such as loss of jobs or employment, erosion of cultural heritage or identity or negative effects on public health and safety. These impacts are not always measured in monetary terms therefore in cases where these are significant, it is important to describe them qualitatively.

4. Discounting

CBA requires the comparison of costs and benefits that accrue at different points in time. The streams of instantaneous costs 퐶푡 and benefits 퐵푡 that accrue at any one point in time t over the time horizon

푡 = 1, … , 푇 have to be discounted to make them comparable. The present values (PV) of costs 푃푉푐and benefits 푃푉퐵 are

푇 퐶푡 푃푉 = ∑ (1) 푐 (1 + 훿)푡 푡=1 and

푇 퐵푡 푃푉 = ∑ (2) 퐵 (1 + 훿)푡 푡=1 respectively. 훿 is the discount rate. Different case studies may apply different discount rates given the specific political guidelines.

5. Net present value test

Once all cost and benefits have been monetised and discounted to a common base period, they can be compared. A public project (or a PoMs in the framework of this study) passes the net present value test if discounted benefits outweigh discounted costs, i.e. 푃푉퐵 > 푃푉퐶. Put differently, the implementation of the proposed measures increase social welfare and hence should go ahead if the discounted net benefits (푃푉퐵 − 푃푉퐶 > 0) are positive.

6. Sensitivity analysis

Due to the often high uncertainties around both the assessment of the physical/ecological impacts of the policy measure under study and the valuation of these impacts, sensitivity analysis is required.

Uncertainty stems from incomplete data and evidence surrounding some of the ecological impacts as well as from assumptions that often have to be made at different stages of the analysis. To test the dependency of the results on any one assumption, sensitivity analysis can be applied. A clear and transparent procedure is crucial when conducting a sensitivity analysis, so that the effect of any one assumption on the final result (i.e. net present value test) can be demonstrated.

The particular challenges of applying CBA to PoMs within the MSFD lie in Steps 2 and 3. For these, an interdisciplinary approach is required. This will be illustrated by looking at three case studies of how a CBA can be conducted with respect to PoMs. While following the general framework of environmental CBA laid out in Section 2, these analyses were conducted independently of each other, each responding to particular requirements and challenges in its geographical location. Consequently, the case studies can be reviewed to highlight advantages and shortcomings of different approaches to the implementation of environmental CBA in an MSFD framework. It should be noted that these steps are not always explicit in any CBA. Steps 1 and 2, for instance, could potentially be conducted as one because measures of environmental policy are often determined by the effect they have on an ecosystem. Hence the ‘physical’ (i.e. ecological) impact’ of Step 2 is in the centre of the definition of the policy measure in Step 1. Similarly Steps 3 and 4 can sometimes go together when future benefits are valued over a number of time periods. The three case studies detailed below illustrate the differing applications of this 6-step framework.

5.2 Costs and benefits of achieving GES in Finnish marine waters

In Finland, the economic analyses to support the preparation of the national (PoMs) were executed in two phases. As the first step, a cost-effectiveness analysis (CEA) of the PoMs was conducted, after which the economic benefits of the PoMs were estimated. Economists responsible for the analyses formed a sub-working group under the national PoMs Working Group that led the process and prepared and planned the new measures. The members of the PoMs Working Group were environmental scientists and other related officials, researchers and NGOs. In total, over sixty people participated in dozens of meetings. At the time the economists working group was established there was a consensus that that there is a gap between the present status of the marine environment and the GES. Also, a first list of measures and the screenings of measures, based on technical feasibility and social acceptability were already prepared before the economic analysis. Based on this, a list of 41 candidate measures to bridge the gap between the present status and the GES was passed to the economists group. Ten measures were excluded during the process leading to the public hearing, leaving in total 31 candidate measures for consideration in the cost-effectiveness, which are listed in Table 5.1.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Table 5.1.New measures in the Finnish Programme of Measures (source: Oinonen et al. 2016a)

The CEA (Oinonen et al. 2016a) provided the cost-effectiveness ranking of new measures and proposed a set of cost-efficient candidate PoMs. Due to the lack of comprehensive ecological and economic models applicable for MSFD economic analyses the estimates of the costs and effectiveness of measures was based on expert elicitation. The data was collected in six thematic workshops that followed a structured group interview format. Each workshop had 6-13 experts and they handled 6-10 measures. The environmental effectiveness of a measure was defined as a probability to bridge the gap between the present environmental status and GES, and the joint effectiveness of two or several measures was computed convolving the distributions of individual measures. This enabled calculation of an estimate of the probability of achieving GES by 2020 for each descriptor. Similarly, the costs of measures were

estimated using expert elicitation and conditional probability distributions. The expected total costs for the Finnish PoMs was €136.2m (Oinonen et al. 2016a).

The economic benefits of reaching GES in Finnish marine waters were estimated based on existing valuation studies on the benefits of improving the state of the Baltic Sea. These studies elicit people’s willingness to pay (WTP) for specific improvements in the marine environment (e.g. Bateman et al. 2002, Turner et al. 2010), and the benefit estimates reflect mainly cultural ecosystem services, i.e. recreation and non-use values. Previous work had revealed that it is relatively straightforward to link the valuation studies directly to the MSFD descriptors of GES, instead of linking the descriptors to ecosystem services and further to valuation studies (Hasler et al. 2016). Thus, the approach connected the benefit estimates directly to the change in the status of the GES descriptors. This means that rather than assessing the impact on human welfare from changes in the provision of ecosystem services from reaching GES, we assessed the impact on welfare from changes in the descriptors of GES.

Three main criteria were considered in choosing the economic valuation studies that could be applied to estimating the benefits of reaching GES and to ensure the results would be as reliable as possible. First, we followed the cost-effectiveness analysis by Oinonen et al. (2016a) who proposed to focus on those MSFD descriptors of GES which were assessed as not being at good status in the MSFD Initial Assessment in 2012. Those descriptors were D1 (Biodiversity), D4 (Food webs), D5 (Underwater noise), D8 (Concentration of contaminants), D9 (Contaminants in fish and other seafood). Second, the search was limited primarily to Finnish valuation studies with the Baltic Sea as the study area. When Finnish studies were not available, the suitability of studies conducted in the other coastal countries of the Baltic Sea was considered. Third, we aimed to use recently conducted studies to provide up-to-date benefit estimates from studies that use state-of-the-art methodology.

The identified studies used stated preference methods (contingent valuation and choice experiment) to estimate the change in use and non-use values from improvements in the marine environment. There was a recent contingent valuation study on eutrophication (D5), covering the entire Baltic Sea area (Ahtiainen et al. 2014). This study provided an estimate of Finnish WTP for improving the eutrophication level in the Baltic Sea from the business-as-usual state to a (near) good state by the year 2050. According to the study, the benefits of reaching GES to the Finnish population by 2050 would be €3,580m, of which €1,022m would accrue by 2020.

The estimate obtained from the Ahtiainen et al. (2014) study was thought to reflect relatively well the benefits of reaching the GES with regard to eutrophication to the Finnish population. The characteristics used to describe eutrophication in the valuation study were water clarity, blue-green algal blooms, fish species composition, underwater meadows and oxygen conditions in sea bottoms. These are clearly linked to the MSFD descriptor on eutrophication (D5) and its more detailed characterization, which includes water clarity, algal blooms, ecosystem effects and oxygen deficiency. The differences between the timeframe of Ahtiainen et al.’s 2014 study and the timeframe for the PoMs to achieve GES (2050 vs 2020), as well as the differences between the Ahtiainen et al.’s 2014 study area (the entire Baltic Sea) and the area of the case study (Finnish marine waters) were assumed to work in opposite directions. The longer timeframe may have led to lower benefit estimates, and the larger geographic area to higher

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

estimates compared to the MSFD policy change. As there was no reliable information on how to adjust the estimate for these differences, the benefit estimate from Ahtiainen et al.’s 2014 study was used as it was.

In the estimation of benefits, the descriptors for biodiversity (D1) and food webs (D4) were combined due to their partial overlap. For these descriptors, the benefit estimate was based on a choice experiment study that valued the benefits from preserving pristine areas, increasing the amount of healthy vegetation (such as underwater meadows), and increasing the size of fish stocks (Kosenius and Ollikainen 2015). The study indicated that the benefits to the Finnish population would be €363m– 1,068m, with the lower bound estimate including only the preservation of pristine areas and the upper bound including all four improvements in the marine environment.

The attributes of the choice experiment are related to the descriptors of biodiversity and food web (D1 and D4) and their specification (Finnish Ministry of Environment 2014). Preservation of pristine areas and healthy vegetation can be linked to the area of distribution and status of species and biotopes in D1, whereas the condition of fish species is linked to healthy fish populations in D4. In the study by Kosenius and Ollikainen (2015), the time frame coincided with the MSFD target year of 2020. Although the benefits were estimated for the entire Finnish population, the study area was limited to the archipelago between Finland and Sweden. It is likely that the benefits would be larger if the environmental change would take place in the entire Finnish marine area. Again, as no adjustment factor was available, the original benefit estimate was used.

The benefits could not be estimated for contaminants in the marine environment (D8) and contaminants in seafood (D9) due to lack of information. The few existing valuation studies on contaminants in the Baltic Sea are focused on individual substances, e.g. tributyltin (Noring et al. 2015) or oil (Ahtiainen 2007, Juntunen et al. 2013). Moreover, the new measures targeting contaminants were related to research activities (see Table 5.1, measures M30 and 31) thus their contribution in achieving GES by 2020 was assessed to be very low (see Oinonen et al. 2016a S2 Table. Probability distributions for gap closure. doi:10.1371/journal.pone.0147085.s002).

The results showed that the net present value of achieving a good environmental status for biodiversity, food webs and eutrophication in year 2020 is around €2,000m. However, the PoMs will not lead to GES of these Descriptors in Finnish marine waters by 2020. Based on the environmental effectiveness assessment as part of the CEA (Oinonen et al. 2016a), the probability of reaching GES by 2020 is 0.77 for biodiversity and food webs, and 0.02 for eutrophication. Thus, the benefits of the PoMs are lower than the benefits of reaching GES. To obtain the expected benefits from the PoMs, the benefits of reaching GES were multiplied with the probability of reaching GES. Thus, the benefits from the PoMs to the Finnish population are estimated at €300m–894m (see Table 5.2). Most of the benefits come from improvements in biodiversity and food webs, as the probability of achieving GES is relatively high for these descriptors. Reducing eutrophication would also lead to significant benefits, but as the probability of reaching GES in the time frame is very low, the expected benefits are low as well.

Comparison of the estimated benefits (€300-890m) to the costs (€140m) of the Finnish PoMs indicates that despite the fact that the GES will not be achieved by 2020, the benefits of the PoMs exceed the costs by a factor of 2-6.

The developed approach is a pragmatic alternative for estimating the economic value of marine protection when applicable data is available and conducting extensive new valuation studies is unfeasible.

Even though the existing studies did not assess explicitly the benefits of reaching GES, their results are suitable for indicating the benefits from the PoMs.

Existing results were used as time and other resource constraints prevented implementing any new studies.

Table 5.2. Estimated benefits from reaching Good Environmental Status (GES) and implementing the Programme of Measures (PoMs).

Descriptor Benefits of reaching GES (in Benefits from the PoMs (in Biodiversity and food webs (D1, D4) 3632014 – 1€,m068) 2802014 – €822m) Eutrophication (D5) 1,022 – 3,580 20 – 72 In total 1,385 – 4,648 300 – 894 The benefit estimates were discounted to the year 2014 using a 3% interest rate and calculated for the Finnish adult population.

5.3 CBA of management measures in the Bay of Biscay (BoB)

Management measures under consideration

The objective of this section has been to identify the main maritime sectors present in the Bay of Biscay (BoB). We first describe the collection, classification and presentation of maritime sector in order to then identify which management measures are relevant for each of those maritime activities. It should be noted that only “fully” maritime sectors are taken into account. This terminology comes from Kalaydjian et al. (2012) and Foley et al. (2014) who divided maritime-related activities into two groups, fully and partially maritime, while Suris-Regueiro et al. (2013) established three groups, adding the intermediate category of mainly maritime. Fernández et al. (2015) identify the fully and partial maritime sectors in Spain (NUTS 0) which also helps to identify these sectors in the BoB (NUTS 3). The socio- economic weight of each of the activities was characterized using a series of indicators that were selected for the entire European Atlantic Arc, under the framework of the INTERREG MARNET project (http://marnetproject.eu/). In order to ensure homogeneity and comparability between the regions, a series of common indicators was established such as the number of people employed, number of enterprises, value added, exports and turnover. As can be observed in Table 5.3 and Table 5.4 the most important sectors, in term of their contribution to the Spanish economy, are: living resources, ship and boat building, transport, construction and coastal tourism.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Table 5.3. Fully maritime sectors: Spain 2009-2011. VA: Value Added

% Spanish economy

Employment VA (000 €) Productivity Employment VA LIVING RESOURCES 155,840 4,012,287 25.75 0.82% 0.42% Marine Fishing 39,203 867,207 Marine aquaculture 27,111 145,822 Processing and preserving of fish, crustaceans and 18,767 737,429 mollusc Wholesale of fish, crustaceans and molluscs 48,836 1,908,847 Retail sale of fish, crustaceans and molluscs 2,1924 352,983 SHIP AND BOAT BUILDING 25,176 1,250,360 49.66 0.13% 0.13% Building of ships and floating structures + of pleasure 11,582 829,986 and sporting boats Repair and maintenance of ships and boats. 13,594 420,374 TRANSPORT 27,951 1,162,769 41.60 0.15% 0.12% Sea and coastal passenger water transport 4,838 153,598 Sea and coastal freight water transport 13,114 496,476 Inland passenger water transport 621 20,109 Inland freight water transport 468 38,355 Renting and leasing of water transport equipment. 8,910 454,232

TOTAL 208,968 6,425,416 30.75 1.10% 0.67% Source: Fernández et al. (2015)

Table 5.4. Partially maritime sectors: Spain 2009-2011

% Spanish economy

Employment VA (000 €) Productivity Employment VA CONSTRUCTION 21,187 992,573 46.85 0.11% 0.10% Construction of water projects (harbours, ports, 21,187 992,573 waterways, locks, etc.) COASTAL TOURISM 890,911 51,351,556 57.64 4.70% 5.34% Hotels and similar accommodation 149,603 16,531,113 Holiday and other short-stay accommodation 36,120 1436,624 Camping grounds, recreational vehicle parks 4,308 534,313 and others Restaurants and mobile food service activities 361,769 19,031,048 Beverage serving activities 339,111 13,818,458 Source: Fernández et al. (2015)

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Table 5.6 shows the type of ecosystem services, functions, related ecosystem processes and components, together with the services provided and the type of uses of each of them, in relation to several maritime activities. All of this information was jointly considered when identifying the potential list of management measures in the BoB. The list of management measures was derived (Table 5.5) covering the BoB’s most important maritime activities and related services:

Table 5.5. Management measures under consideration in the Bay of Biscay (BoB) case study MANAGEMENT MEASURES UNDER CONSIDERATION IN THE BoB A. Management measures related to the most relevant sectors based on their economic contribution (Table 5.3 and Table 5.4)  Management measures related to fully maritime sectors o Related to extraction of living resources (fishing) o Related to maritime transport  Management measures related to partial maritime sectors o Related to coastal tourism, in particular, sport fishing B. Management measures related to other relevant (current and potential) uses in terms of ecosystem services (and benefits) although contributing to a lesser extent in economic terms.  Related to research and conservation  Related to the extraction of non-living resources (dredging)  Related to renewable energy generation  Related to coastal discharges based on coastal structures  Related to land-based industry (Surface water management and waste water treatment and disposal) A brief description of the management measures that were considered follows below. However, the quantitative analysis focusses only on the most relevant sectors and management measures adopted.

 Management measures related to the extraction of living resources

A new CFP has been agreed by Council and Parliament to be effective from 1 January 2014 (Regulation (EU) No 1380/2013 of the European Parliament and of the Council) after a long public debate launched by the European Commission since 2011. The Green paper on reform of the CFP and the following citizen´s consultation reports outlined different proposals. These included five main policies: the implementation of discard bans, the objective of Maximum Sustainable Yield (MSY) by 2015, the regionalisation of management measures, an emphasis on the social dimension and the promotion of Transferable Fisheries Concessions (TFCs). Rights-based management has been presented by the EC as a more efficient management approach to reduce overcapacity and give more responsibility to the industry. The management measures considered in the BoB case study includes some of these last proposals coming from the CFP.

Table 5.6. Type of ecosystem services, functions, related ecosystem processes and components, together with the services provided and the type of uses of each of them, in relation to several important maritime activities and management measures implemented. Modified and expanded from Borja et al, 2015. DP(S)IR model Maritime Activity Ecosystem processes and Type of Management measure. Notes

Type of services Ecosystem benefits components uses

Nutrient cycling Biogeochemical activity Biological productivity Indirect

Primary Photosynthesis, Nutrient fixing, Food-webs Indirect production chemosynthesis

Research and Biodiversity System diversity Ecosystem resilience Indirect Gaztelugatze marine protected area conservation Habitat Suitable space for wild Maintenance of Indirect organism, reproductive and biodiversity and beneficial nursery areas species

Resilience Stabilize environments Reduce vulnerability Indirect

Extraction of living Maintenance of Suitable habitats Food Direct Management measures related to the application of the last Common Fishery Policy

resources fisheries

Extraction of non- Direct The management of dredging activities is the responsibility of the Port Authority. living resources

Supporting (dredging)

Renewable energy Energy and Geochemical activity Industry, energy sources Direct BIMEP embodies the clearest example to date of the commitment of the Basque Government generation (wave minerals to marine (wave energy, current energy, etc.) and offshore wind energy. and offshore wind energy)

Chemicals/phar Industrial and health Direct maceuticals compounds

Coastal discharges Waste disposal Transport, dispersion, Pollutants trapping and Direct The regional Basque Water Agency (URA) is responsible for the implementation of the Water based on coastal dilution cycling Framework Directive structures

Raw materials Biogeochemical activity Food inputs to the system, Direct food-webs

Maritime Activity Ecosystem processes and Type of Management measure.Notes

Type of services Ecosystem benefits components uses

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Carbon capture CO2 reduction Climate change mitigation Direct and storage (artificial)

Gas regulation Role of ecosystems in UV protection, Indirect biogeochemical processes maintenance of air quality

Climate Influence on biologically Influence of climate, Indirect regulation mediated processes maintenance of Tª, precipitation

Disturbance Dampening environmental Storm protection, flood Direct prevention disturbance, wave mitigation, coastal

attenuation protection

Maritime transport Erosion control Sediment stabilization Sea-level rise, subsidence Indirect Ley 14/2014, de 24 de julio, de Navegación Marítima.

Water Runoff, river discharge, Drainage, natural Direct Regulating regulation infiltration irrigation, flood mitigation

Nutrient Role of biota in storage and Maintenance of productive Direct regulation recycling ecosystems

Land-based Waste Removal of nutrients and Pollution control, Indirect The regional Basque Water Agency (URA) is responsible for the implementation of the Water industry (Surface treatment pollutants detoxification Framework Directive water management and waste water treatment and disposal)

Biological Trophodynamic regulation of Control of pests, invasions Indirect regulation populations

Educational Training Direct

Scientific Knowledge, blue Direct technologies

Aesthetic Well-being Nonuse

Existence/Bequ Biophilia Nonuse

Cultural est

Tourism and Tourism and Recreational grounds Direct There are several Spanish legislations that regulate recreational/sport fishing. The most recreation (sport recreation relevant one for external waters: Real Decreto 347/2011. With respect to the internal waters, fishing) Decreto 198/2000.

The BoB is characterized by multi-fleet and multi-species fisheries fishing in different areas. This work analyses the main fleets with base port at the Basque Country: the trawler and purse seiner fleets. The trawler fleet comprises bottom otter trawlers and bottom pair trawlers which operate in fisheries9 mainly managed through TAC (Total Allowable Catch) and TAE (Total Allowable Effort). Access rights were imposed on the Basque trawler fleet in 1981. Subsequently, in 1992, these rights became cumulative, and a few years later, in 1997, the rights became transferable with limitations. Finally the current Individual Transferable Quota (ITQ) system was established in 2006. The Basque purse seiner fleet operates sequentially, distributing its activity across the mackerel, anchovy and tuna seasons, shifting fishing gear to pole and line (using live bait) and trolling in the tuna season. The main species targeted by the Basque purse-seiner fleet are regulated through TAC, although recently, individual fishing rights have been introduced to manage bluefin tuna (BFT) and mackerel. Both fishing segments have to accomplish the landing obligation management measure. In general, the scrapping subsidies represent an important management measure for any Basque feet. Finally, a complete set of technical measures and spatial measures are also applied for all the fleet segments. A detailed characterization of the BoB fishing related management measures can be found in Le Floch et al. (2015), Prellezo (2010), and Andrés and Prellezo (2012).

 Management measures related to maritime transport

The Spanish Port Authorities are the bodies that regulate/manage and control the maritime transport. The main regulation at the international level is MARPOL, and there are two additional Conventions that also apply (Convention on the control of harmful antifouling and Ballast Water Management Convention). The main Spanish regulation is the “Ley 14/2014, de 24 de julio, de Navegación Marítima”.

 Management measures related to sport fishing (tourism and recreation)

There are several Spanish instruments that regulate recreational/sport fishing. The most relevant is applied to waters offshore of the baseline from which the breadth of territorial waters is measured: Royal Decree 347/2011 with the Decree 198/2000 applied to the inshore waters. Some of the management measures established (Zarauz et al., 2013) include:

 Administrative authorizations, needed to develop sport fishing using a boat. The number of licenses is not allowed to be higher than the number of crew.  Prohibited and allowed species are established. Prohibited species are listed in the Annex II Reg. 198/2000 of the Basque Country. There are additional species for which special protection is established (e.g. Thunnus alalunga, Thunnus obesus, Merluccius merluccius).  Maximum tonnage of landings by species and by vessel (25 kg)

9 A fishery is a group of vessel voyages targeting the same (assemblage of) species and/or stocks, using similar gear, during the same period of the year and within the same area (study group on the development of fishery-based forecasts, ICES, 2003). The location does involve the definition of a fishery (Prellezo et al, 2009). 95

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 Fishing gears allowed. Mainly hand lines.  Fishing areas where this activity is not allowed to develop are also established (e.g. bathing areas, biotopes or biodiversity special areas).

 Management measures related to research and conservation

Borja et al. (1999) developed a preliminary selection of the most interesting sites along the BoB to establish marine protected areas. Gaztelugatxe was selected for its characteristics (including submarine caves, rocky marine arches and islands, summer upwelling, and high quality water). The small Marine Reserve of Gaztelugatxe (158 Ha) was created in 1998 (229/1998 Decree of 15 September of the Basque Government), with the aim of protecting the goose barnacle population (Borja et al., 2006).

 Related to the extraction of non-living resources (dredging)

Dredging activities requests from licensing. The management of dredging activities is the responsibility of the Port Authority who requests permission for dredging activities from the Spanish Government. Depending on the volume to be dredged an Environmental Impact assessment may be requested.

 Related to renewable energy generation

Currently, little renewable activity is developed in the BoB. BIMEP embodies the clearest example to date of the commitment of the Basque Government to marine (wave energy, current energy, etc.) and offshore wind energy. Bimep is designed for testing and demonstrating prototype devices for harnessing ocean energy in terms of their safety and economic and technical viability prior to their full-scale commercial development. Bimep provides manufacturers of ocean energy devices with the opportunity to install their equipment in open sea conditions for demonstration and operational (power generation) purposes or for testing (bimep web page, http://bimep.com/en/ sobre-bimep/desarrollo-del-proyecto/). The characteristics of the sea in this part of the BoB are ideal for testing the effectiveness of new wave energy devices and technologies being developed by companies throughout Europe. Preliminary studies on the project began in 2007. Since then, steady progress has been made from a conceptual to a detailed design, and the required environmental permits have been requested and obtained from the Ministry of the Environment, Rural and Marine Affairs. A strict monitoring programme will be followed to gather information on the impact of wave energy on the environment.

 Related to coastal discharges based on coastal structures

The regional Basque Water Agency (URA) is responsible for the implementation of the Water Framework Directive (and the Spanish transposition of this Directive “Ley 62/2003, de 30 de diciembre, de medidas fiscales, administrativas y del orden social”). Although the Spanish government is responsible for the implementation of the Marine Strategy Framework Directive (transposed into Spanish legislation via the “Ley 41/2010, de 29 de Diciembre, de protección del medio marino”, URA is also involved.

Public costs of the programmes of measures

This BoB analysis will be mainly based on the management measures related to fishing activities (commercial and sport fishing). Fisheries management must logically involve at least the following three main functions (Arnason et al. 2000, OECD 2003). 1. Fisheries management administration (monitoring, designing, setting and modifying fisheries management rules and measures); 2. Research (biological, social and economic research to inform fisheries management decision-makers); 3. Enforcement (enforcing fisheries management rules). All these functions of fisheries management are costly although typically, the enforcement function, monitoring fishing operations and enforcing rules, are most costly with research not far behind. Compared to these two functions, the cost of setting fisheries management rules is usually quite small (Zableckis et al. 2009).

The fisheries management function comprises several sub-functions: system design; system implementation; adjusting management settings within an existing management system; recommending amendments or additions to the existing management system; administering the system; setting system measures such as the TAC. Results from research (primarily biological, economic and social) provide the knowledge basis for carrying out this function. The enforcement part of the fisheries management involves surveillance of the fishing activity, on-site enforcement of the existing fisheries management rules and measures, and processing and issuing of sanctions to alleged violators.

All these functions of fisheries management are costly and should be considered as part of the cost- benefit analysis of fishery management, however, these are evaluated by Governments at national level and little knowledge exists at the level of each fishery/métier/fishing activity.

In the analysis here we try to overcome this challenge by identifying at least a minimum cost using the European Maritime and Fisheries Fund (EMFF), which is the fund for the EU's maritime and fisheries policies for 2014-2020. It is one of the five European Structural and Investment (ESI) Funds which complement each other and seek to promote a growth and job based recovery in Europe (http://ec.europa.eu/fisheries/cfp/emff/index_en.htm). The EMFF is used to co-finance projects, along with national and private funding. Each country is allocated a share of the total Fund budget, based on the size of its fishing industry. Thus, this work considers the operational programme of the Basque Country as a minimum public cost of the different management measures applied in the BoB.

Deliverable 2.2 Socio-economic impacts of achieving GES and monitoring practices within MSFD

Table 5.7 Public cost attached to the maritime measures co-financed by European Maritime and Fisheries Fund for 2014-2020. CFP: Common Fisheries Policy. General Maritime Ecosystem Management cost Specific activity Management Measure Activity services (´000 euros) Extraction of Inshore and Sustainable Scrapping subsidies in application 8,000 fishing resources offshore fleets Food provision of the CFP Extraction of Inshore and Sustainable Measures to promote temporal 5,200 fishing resources offshore fleets Food provision fishing bans Measures to apply the Landing Extraction of Basque fleet Sustainable obligation, LO (Art. 15 CFP). 2,000 fishing resources (mainly trawlers) food provision Measures to reduce the fishing impacts on marine environment Extraction of Basque fleet Sustainable Energy efficiency and climate 1,000 fishing resources (mainly trawlers) food provision change mitigation. To promote the Extraction of application of the Sustainable Control and enforcement at ports 5,750 fishing resources Common Fisheries food provision Policy Tourism and Sport fishing Recreation Administrative authorizations N.A recreation Maritime Sea level rise Administrative authorizations Maritime transport N.A transport Sustainable Measures to promote a sustainable 9,500 Aquaculture Aquaculture Food provision aquaculture

Protection and restoration of Research and Conservation Biodiversity marine biodiversity and 1,700 Conservation ecosystems

Benefits of the programmes of measures

This section mainly deals with the benefits related to the program of measures derived from the CFP application. With this objective in mind an impact-analysis (IA) method, following EU (2009) has been developed to identify the quantitative impacts of fishing management efforts on the economic value of the benefits from the food provision ecosystem service. In particular, a quantitative assessment using the FishRent model, able to evaluate the bioeconomic performance of the fleets over a period of 25 years, is used. FishRent is a multifleet and multispecies model composed of six modules (Murillas and Andrés, 2016): a biological module (stock-growth relation and biomass function), an economic module (revenues, costs, cash flow, etc.), an interface module (production function, discards and landings), a market module (price of fish and fuel price), a behaviour module (fleet size, effort and investment) and finally, a policy module that determines the level of landings and/or the effort involved. A set of scenarios have been identified for which medium to long term simulations have been run. The scenarios approach takes into account the baseline, the status quo, and potential management measures for which different endogenous and exogenous variables are considered. Endogenous variables are generally simulated by the model through dynamic equations (effort, investment functions, etc.), while

exogenous variables are associated with external factors. These potential management measures are considered to be the alternative scenario (to the status quo).

To derive FishRent outcomes for each measure both market prices and private/operational costs are considered within the economic and market modules. However, the additional public costs are not included due to the complexity of assigning those public cost to individual measures. Thus it is not possible to develop a complete CBA.

The main BoB relevant topics coming from the CFP are related to the following alternative scenarios: (i) the application of the landing obligation, (ii) the scrapping subsidies, and (iii) the introduction of individual rights. These three measures are taken into account as pilot measures to focus on their impact on food provision service. With that aim, the two main Basque fleets will be covered: the trawlers and the purse seiners.

The introduction of scrapping subsidies implies a public cost around €8,000 (´000) in the period from 2014 to 2020 (see Table 5.7). The lack of these subsidies would prevent vessels from leaving fishing activity which would contribute to the increasing overcapitalization problem and overexploitation of the commercially exploited target species. This economic measure implies a social impact because the total Basque fleet could be reduced to 20 medium-small size vessels or 7 large vessels as a result of its implementation.

Following Murillas et al. (2011) using FishRent the economic value of food provision can be assessed by using the Gross Value Added (GVA) concept, or the expected Profits. Some other authors use the market price when insufficient data is available. Moreover, we project over the long term (to 15 years) the impact of the measure. The impact on food provision value mainly depends on the fishing gear and the activity. For the BoB the economic results from projections under the following scenarios were:

(i) a reduction of 7 trawlers implied an increased NPV of the GVA of 2.25%, and NPV of profits of 52%. These results will become lower after 25 years. The evolution of the GVA over time is shown in Figure 5.1. Given the Basque trawlers activity a GVA of 2.25% represents around €12,000 (´000). (ii) Similarly, a reduction of 7 purse seiners implied an increased NPV of the GVA of 4.43% (around €15,000 (´000)), and NPV of profits of 38%.

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50000 40000 30000

20000 1000 euros 1000 10000 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Simulation years

With scrapping subsidies No scrapping subsidies

Figure 5.1 Impact of scrapping subsidies on Net Present Value of Gross Value Added for trawlers

The application of the landing obligation, which represents an alternative scenario, implies an important adjustment of the fishing activity of the Basque trawlers in relation to the status quo (under which the sector achieves good bioeconomic results). Under this alternative management measure there would be a reduction from 24 to 12 trawl vessels in the next 25 years and, an increase of around 33% in fish biomass. The impact on the food provision value is high given a reduction of the NPV of GVA to 15 years of 45% and the NPV of profits around 88%. The main results from simulation are shown in Figure 5.2. The introduction of the landing obligation will take BoB trawl fisheries to an unsustainable situation in terms of economic performance, although the biological element of sustainability will be improved. However, the outcome depends on the different trawler segments (Sg): otter trawler, pair trawler, and longliners. The outcome for pair trawlers is the worst, while the others will remain more or less stable. In particular, under status quo the pair trawlers would have the capacity to increase their number of vessels by up to 50% in the long term. For the biological dimension, the catchable biomass under the alternative scenario is higher than for the status quo, for all species in both the short and medium term (being hake, megrim, mackerel, horse mackerel, and anglerfish). However, the catchable biomass reaches a similar level in the long term (after 25 years) for all species except hake and anglerfish, whose catchable biomass is much higher within the alternative scenario.

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10 Number of vessels of Number 5

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Simulation years

Status Quo, Sg1 Status Quo, Sg2 Status Quo, Sg3 Alternative, Sg1 Alternative, Sg2 Alternative, Sg3

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5000000 300000

4500000 250000 4000000

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50000 Catchable biomass (Tonnes), Sp3, Sp4 Sp4 Sp3, (Tonnes), biomass Catchable

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Status Quo, Sp3 Status Quo, Sp4 Alternative, Sp3 Alternative, Sp4 Status Quo, Sp1 Status Quo, Sp2 Status Quo, Sp5 Alternative, Sp1 Alternative, Sp2 Alternative, Sp5

(c ) Catchable biomass for the main six species

Figure 5.2. Landing obligation ( Alternative scenario) impact on trawler activity - main results from simulations in terms of the differences by trawl segment (Sg1: OTBS, otter trawlers; Sg2: OTBP, pair trawlers and Sg3: LLB, longliners) between the Status Quo and the Alternative 1, associated with the application of the landing obligation, for (a) the number of vessels, (b) the Gross Value Added and (c) the catchable biomass (tonnes) for all the analysed species (Sp) Sp1: Hake; Sp2: Megrim; Sp3: Mackerel; Sp4: Horse mackerel and, Sp5: Anglerfish.

The introduction of individual quotas in purse seine fisheries to manage blue fin tuna represents the alternative management measure for this fleet.

The NPV of GVA decreases slightly and NPV of profit (25 years) is 1% lower with the introduction of Individual quotas (IQ) managed in a common pool. The rent is redistributed and a higher number of vessels remain in the fishery than under the Status Quo with no IQ. The economic results are more profitable than in the Status Quo only in the case of selling the blue fin tuna rights (ITQ) every two years, providing an increase of the NPV of profit around the 33% with respect to the Status Quo (Figure 5.3). Figure 5.4 shows that the biomass in the long run of the vast majority of the species is slightly better in the Status Quo scenario than under the introduction of IQ.

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Not all the purse seiners segments are affected equally within the alternative scenario. Four segments were modelled: pure purse seiners (Seg1), purse seiners and trolling (Seg2), purse seiners and live bait with high blue fin tuna catchability (Seg3), and purse seiners and live bait with low blue fin tuna catchability (Seg4), the last two being the most important and the main objective of this analysis. Their main target species are anchovy (Sp1), horse mackerel (Sp2), mackerel (Sp3), sardine (Sp4), albacore (Sp5), and blue fin tuna (Sp6). In the status quo, the yearly GVA of Seg3 is always higher than in alternative, while the opposite is true with Seg4. The homogeneous redistribution of the blue fin tuna rent that occurs within the alternative scenario implies that the Seg3 yields part of its blue fin tuna rent to Seg4.

Figure 5.3. Evolution of gross value added of segments in Status Quo scenario (SQ), Individual Quotas (IQ) represented as Alternative, and Individual Transferrable Quota (ITQ) scenarios represented as an External Factor (EF0). Purse seiner segments: pure purse seiners (Seg1), purse seiners and trolling (Seg2), purse seiners and live bait with high blue fin tuna catchability (Seg3), and purse seiners and live bait with low blue fin tuna catchability (Seg4)

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Figure 5.4. Evolution of Standing Stock Biomass (SSB) of Anchovy (ANE), Mackerel (MAC), Sardine (PIL), Horse Mackerel (HOM), Albacore (ALB) and Bluefin tuna (BFT) in Status Quo (SQ), IQ and ITQ scenarios.

Management measures concerning sport fishing. Considering only the boats that were dedicated to sport fishing (376), the vast majority were licensed (98%) and were enrolled in the Second Book of Ship Registration Department of Agriculture and Fisheries (92.7%). Thus, only 29 vessels should be removed from this sport activity. The direct impact on vessel investment, production value and the rent of reducing around 29 vessels sport fishing activity is estimated based on Zarauz et al. (2013). In particular, the investment is reduced by €1,500 (´000), which implies a production and rent reduction of around €2,000 (´000) and €500 (´000), respectively. In addition to the direct impact, the indirect impact of this recreational activity is also included: production and rent declines by around €1,400 (´000) and €500 (´000), respectively.

In addition to the obligation of being licensed, Annex III of the Order of 26 February 1999 regulates marine recreational fishing for species considered to have differentiated protection measures whose capture requires possession of an express authorization of the General Secretariat Maritime Fishing for the boat and posting of a landing declaration. The regulation applies to medium or large size species, which require larger vessels to catch them. The percentage of boats possessing the authorization varies significantly with the type of boat: 89% of large motor and 73% sailboats are declared to have it, compared to 46% of small motor boats and only 19% of “txipironeras” (Zarauz et. al., 2013). Thus, the introduction of this conservation measure limits access to protected species to 142 vessels. However,

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the impact of this measure cannot be assessed because it is not compulsory to get this special authorization. The impact will be more important for large motor vessels: a total of 25 vessels do not to have authorisation.

Maritime transport. The impact of this important activity (the Bilbao Authority Port has 62 million Euro of revenue volume and a net value of €33.5 million) on the ecosystem service is difficult to assess but as there are no specific management measures associated, no impact analysis was developed.

Measures related to research and conservation are identified in the BoB. These are included because they are related to the fish food provision service. Borja et al. (2006) state that marine protected areas are expected to play an important role in the BoB. In particular, the main aim of the small Marine Reserve of Gaztelugatxe (158ha), established in 1998, was to protect the goose barnacle Pollicipes pollicipes. After several years of protection there are differences in density, biomass, size and weight of the goose barnacle inside the protected area and outside it. However, no economic information exists to develop an economic IA. Moreover, no specific public costs are expended to manage the Marine Reserve, although the EMFF assign €1,700 (´000) public cost to research and conservation activities.

A summary of the full socio-economic assessment of management measures in BoB is presented in Table 5.8.

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Table 5.8. Bio-socioeconomic impact on ecosystem services of management measures on maritime activities in the Bay of Biscay

Valuation Economic IA availability Previous Maritime Ecosystem Management approach Present Social and biological IA (monetary value Activity Year Quantitative Type of data Activity services Measure in approach (non-monetary variables) % and/or (´000 euros)) /qualitative/ literature both Ecosystem service value trawler reduction increases: 2.25% GAV15; 52% Profit15 and 27% Profit 25 Economic Potential reduction in 20 vessels Extraction Inshore and Sustainable purse seiners reduction increases: 4% Scrapping 2014- and (medium-small size), or 7 large of fishing offshore Food Both ---- Fishrent model GAV , ; 9% Profit and 23% Profit subsidies 2020 biological vessels 15 25 15 25 resources fleets provision data inshore (bait live) reduction increases: 6- 9% GAV 15,25; 80% Profit15 and 148% Profit 25 Biological valuation and Economic No from 24 to 12 vessels in the next Extraction Basque fleet Sustainable Landing estimate 2015- and previous 25 years (pair trawlers) Reduction: of fishing (mainly food obligation, LO Both NPV15-25 of 2019 biological studies resources trawlers) provision (Art. 15 CFP) market value hake catchable biomass increase GVA15,25; 45% Profit15 88% data on LO (GVA) 33% in the long-term Fishrent model Biological valuation and Economic No Extraction Basque Sustainable IQ for BFT estimate and previous Maintenance of the number of of fishing Purse food managed in ---- Both NPV15-25 of Reduction around 1% GVA ; biological studies vessels 25 resources seiners provision common pool market value data on IQ (GVA) Fishrent model

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Valuation Economic IA availability Previous Maritime Ecosystem Management approach Present Social and biological IA (monetary value Activity Year Quantitative Type of data Activity services Measure in approach (non-monetary variables) % and/or (´000 euros)) /qualitative/ literature both Ecosystem service value Biological valuation and Economic No Extraction Basque Sustainable ITQ for BFT estimate and previous Increase of 21% in the number Increase 33% Profit 25 of fishing Purse food managed in --- Both NPV15-25 of biological studies of inshore vessels in 25 years resources seiners provision common pool market value data on ITQ (GAV) Fishrent model To promote the Employment Extraction application Sustainable Control and 2013 data. 220 vessels, 2122 2014- , TRB, Market GAVcf (2013) of fishing of the food enforcement Both Market values direct employment and 51,875 2020 Revenues, values resources Common provision at ports TRB 231,985 Landings Fisheries Policy Production, revenues, Reduction in the number of Tourism and Sport Administrative and costs of Market values Reduction of €2,000 of production value Recreation 2014 Both ----- vessels allowed to fish: 29 recreation fishing authorizations the activity, (Added Value) (€400 of added value) vessels. vessel census Nb Foley et al, Bilbao and establishme 2014; Maritime Maritime 2008- Suris et No valuation is done due to the lack of Pasajes Port Both nt, Fernández No valuation is done transport transport 2012 al,2011 management measures attached Authority employment Macho et al, and GAV 2015 The Gaztelugatze Marine No valuation is done due to the lack of Two marine Biological Reserve has significant economic data Research and protected 2014- data for Borja et Borja et al, Conservation Biodiversity Qualitative differences in comparison with Conservation areas 2020 goose al, 2006) 2006) non-protected areas in barnacle preserving the goose barnacle

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Discussion

There are several maritime activities developed in the BoB but not many are relevant in terms of their contribution to the regional economy. Moreover, it is difficult to identify management measures specifically affecting those activities, and therefore affecting the different ecosystem services. An exception is found in relation to fishing activity. A complete public cost programme exists at the European Level (the EMFF) to co-finance the national and regional programs needed to implement certain management measures mainly introduced by the last CFP. However, the lack of disaggregated information concerning the EMFF makes it difficult to undertake a complete cost-benefit analysis of each proposed measure. With this objective in mind the impact-analysis (IA) method, was successfully developed to identify the quantitative impacts of fishing management efforts on the economic value of the benefits from the food provision ecosystem service using the FishRent model. The economic incentives for maintaining scrapping subsidies for the trawl fleet depend on the amount of money expected to be put into this measure. If the allocated money is lower, the impact on fishing activity and therefore, on the food provision is more than proportionally reduced. However, when applying the scrapping subsidies to the purse seiners a positive impact could be extended over the long term. Concerning the application of the landing obligation as a conservation measure, , a total research- related public cost of 1% was applied. Unlike the situation with scrapping subsidies there is no direct relationship between the public cost and the economic benefits. In this case, the cost effort will prevent a decrease around 45% NPV of GVA which might happen when the landing obligation is applied. Another pillar of the CFP is the introduction of individual rights and this measure might positively impact on food provision value when transferability is allowed, pushing up NPV of profits by around 33%. Given the final aim of enabling the application of the CFP an important cost representing 4% of the total EMFF total cost is assigned to control and enforcement activities. The main impact is assessed by assuming a high level of compliance in the application of the different management measures. Thus, this extra general cost should also, although partially, be assigned to the cost-benefit analysis of the other measures.

5.4 CBA of management measures in the East Coast Marine Plan (ECMP) area in England

The UK case study focuses on the East of England Marine Plan area (Defra 2014), or East Coast Marine Plan (ECMP) area. The assessment of costs and benefits of the PoMs to achieve GES required a scenarios approach to be able to compare different potential future states. A comparison of costs and benefits can be performed for each scenario. Further, an ecosystem service approach is used to assess the impact of potential management measures on such services and the benefits they provide.

Management measures under consideration In the UK, new management measures to be implemented under the MSFD are still under consultation. It is therefore not clear to what extent the MSFD will rely on new measures or if management based on existing policies will be sufficient to achieve GES targets in most descriptors. Among a wide range of

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possible management measures to achieve GES, this analysis is specifically looking at pressures which are caused by activities which were not well management before the implementation of the MSFD. Consequently, the UK case study focused on aspects where there might be new measures in the future: Mitigation of underwater noise and management of invasive alien species (IAS). These were chosen because assessments prior to and during the DEVOTES management measures workshop (Bӧrger et al 2015) revealed gaps in management for these issues. These management measures aim to address Descriptor 2 (invasive alien species) and Descriptor 11 (underwater noise) but due to the effect of the pressures addressed with these measures positive effects on Descriptor 1 (biological diversity), Descriptor 4 (marine food webs) and Descriptor 6 (seafloor integrity) may also be expected. In this research we aim to measure these positive effects on D1, D4 and D6. Specific management measures to address underwater noise and the introduction of IAS will be detailed further in the respective sections below.

Costs and benefits of the mitigation of underwater noise Man-made underwater noise is a growing area of importance within the scientific literature and is included within environmental impact assessments and statements, and within recent European regulations, such as the MSFD and the OSPAR convention (e.g. Borja et al. 2010). Following Elliott (2013) mitigation measures [for noise] should be economically viable, i.e. realistic in terms of the impact upon the industries making noise in the ocean; technologically feasible i.e. using technology to the advantage of reducing noise; and culturally inclusive i.e. noise reducing measures must be accepted by society and communities if they are to be successful. However due to the scarcity of scientific data relating to the impacts of sound, management measures are limited, particularly for fish and invertebrates. This has led to uncertainty regarding how regulators, stakeholders and scientists should proceed when so many activities produce underwater sounds. There are many aspects to consider in management of underwater noise:  The wide range of sound types produced by anthropogenic activities - these include short impulsive sounds and long-term continuous sounds, with varying frequency ranges, occurrences and mobility. This means that a range of different metrics may be used to represent sources (e.g. different methods to calculate sound levels, such as averaging across the total of a signature, or measuring the maximum amplitude of a single pulse), and in many cases these are not well reported or agreed upon.  Within each noise-producing activity there are a range of variations according to the method used - for example, with pile driving the noise produced varies with the type of hammer, diameter of pile, number of piles, pile material, pile jacket, in addition to variation with environmental parameters and sediment characteristics. This makes the extrapolation within, and between sources, difficult and findings too general.  There is a lack of agreement regarding which components of a sound field should be measured. Sound consists of a pressure and a particle motion component; it is standard for pressure to be measured, and in some cases for particle motion to be extrapolated from these measurements. There is a lack of easily-available equipment allowing the direct measurement of water-borne particle motion due to the difficulties of making such sensors, which are currently commercially

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unavailable. There is disagreement as to the relevance of particle motion in sound measurements, though it is now clear that particle motion is detected by many fish species (but not marine mammals) in addition to/instead of pressure and should therefore be considered in tandem with pressure.  The variation of acoustic propagation in the aquatic environment. This is likely to vary with environmental conditions and the source properties such as type, source level, frequency range, duration and repetition. It is difficult to generalise between sources since every sound has distinct characteristics varying in level, frequency, occurrence pattern and may also be stationary/mobile or single/multiple sources (Tasker et al. 2010). Furthermore the source level varies across distance due to absorption and refraction as the sound travels through the water, and varies with boundaries and depth, making prediction of levels difficult under certain scenarios. Additionally, many sources such as drilling and pile driving directly contact the seabed and are likely to produce a strong sediment vibration, which is likely to propagate large distances and yet the levels produced are largely unknown and has received little research attention.  It is likely that many noise-producing activities also create other stressors on the marine environment - for example, the building and maintenance of an offshore wind platform also brings boat traffic which may be associated with pollutants, light, and water movement. Another example is that species at higher trophic levels such as marine mammals and sharks are particularly susceptible to contaminants, and many are also highly susceptible to sounds. The effects of multiple stressors on the environment are discussed in Crain et al. (2008).  The hearing abilities of many marine species are not well known. There is more data available for marine mammals than fish, but in general the methodologies for investigating hearing ability are still developing (for example behavioural methods for defining auditory sensitivity are now deemed more reliable than physiological methods- see Ladich and Fay 2013). In addition to this, hearing abilities of marine species are highly diverse. For example in the case of fish, some species have specialised connections between the ear and the gas bladder allowing detection of sound pressure, whilst others only detect particle motion (e.g. flatfish, sharks, rays). Other species are able to detect ultrasound, whilst others only detect a narrow frequency band. In regard to invertebrates, the hearing capabilities of many species are still uncertain, although it is likely that most species are able to detect particle motion only. Furthermore, many species contacting the sediment are likely to detect substrate-borne vibration, yet the sensitivities and capabilities for this type of detection are only recently receiving research attention (Roberts et al. 2015, 2016). In the case of marine mammals, these are unable to detect particle motion and are responsive to pressure only.  There are very few peer-reviewed papers for species (e.g. fish, invertebrates) which link quantified sound exposures to effects. Of the existing data, many studies have been undertaken in laboratory tanks where the acoustic field is highly complex and difficult to predict (Parvulescu 1964). Yet field studies are expensive and logistically complicated in many cases, for example with difficulties of monitoring species and of producing noise sources similar to those that might be experienced. As such, in many cases it is not possible to predict the effect of a noise source in

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terms of a sound level translated to a particular effect (dose response), although such curves are available for some marine mammal species.  There are few data relating short term behavioural or physiological effects up to a community or population level, which is crucial when trying to understand the significance impacts across ecosystems. In addition to this, the effects of any stimulus are likely to vary by individual, for example with body condition, motivational state, previous exposure, even with the ‘personality’ of the animal.  Lack of ambient sound level measurements for many environments. It is difficult to consider the impact of anthropogenic sources if the background sound levels are not well understood. Overall these factors make the management of underwater noise a complicated issue, and have led to an inability to set detailed noise exposure criteria for many fish and invertebrates (Popper et al. 2014) and to discussions relating to criteria set for marine mammals (Southall et al. 2007). Yet, sound is important in marine species for navigation, communication, reproduction, and foraging, and it is clear that additional man-made sounds would impact these activities (for recent reviews see Hawkins et al. 2014, Hawkins and Popper 2014).

Approach Secondary evidence and other information were gathered to assess the potential impacts of underwater noise and how this might affect the ecosystem services and benefits in the ECMP area. Information regarding the management measures and the types of noise in the marine environment is presented in Table 5.9. Relevant information for key fish, invertebrate and marine mammal species in the ECMP area was collated and summarised in relation to known impacts of noise (Table 5.10). In addition to this, the ECMP area has been treated as an area that experiences all sources of anthropogenic noise, although the most prevalent sources are likely to be due to shipping and offshore marine energy development/maintenance. After collating the source, management and impacts data, key ecosystem functions, processes, services and benefits were all identified (Figure 5.5), with example indicators included (Table 5.11). A number of scenarios were developed by the authors for underwater noise measures (Table 5.12) with their associated assumptions presented in Table 5.13. Finally, the impact of each policy option on ecosystem services and benefits was assessed (Table 5.14).

The key types of noise sources that exist in the marine environment are presented in Table 5.9, in association with management measures for each (after Roberts 2015). For most of these there is currently insufficient experimental evidence regarding effectiveness in altering frequency ranges and/or source levels. The options can be split into those which directly affect the source itself, and those that are focussed towards the receiver. Both of these approaches have caveats and require a significant amount of experimental evidence and research to support design and implementation, as summarised in Table 5.9. This is particularly difficult given the limited data relating to sound levels produced by different sources in varied conditions, and also the lack of data regarding precise exposure levels that are likely to elicit responses in fish, marine mammals and invertebrates. In addition to this, the testing of such measures in terms of reducing biological impact is focussed upon marine mammals and specific measures, for example regarding the effectiveness of acoustic deterrents (Richardson et al. 1995, Wier

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2000, Stone and Tasker 2006), with effects upon mobile/less mobile fish and invertebrates little understood (Popper et al. 2014).

The sound level produced from sources such as pile driving, can be controlled directly by the operators, either to minimise the level, vary the construction regime or by stopping completely. One example of minimising the level is to explore different piling types such as impact piling and vibroesis (Nedwell et al. 2003a,b), or to use smaller diameter piles or foundation types that do not require as many driven piles. Such measures are highly dependent on the seabed and environmental conditions, and the type of platform being built (Thomsen 2006, Götz 2009). Bubble curtains or acoustic-isolation material may be used to surround the pile, such measures have been shown to reduce source levels by 20 dB (depending on the frequency) and 5 – 25 dB respectively (predominantly upper frequencies) (Wursig et al. 2000; Nedwell et al. 2003a,b, Thomsen et al. 2006, Nehls et al. 2007). In the case of bubble curtains, experimental tests have indicated a reduction in the 400 – 800 Hz band frequency range, which is of relevance to marine mammals where some species communicate within this frequency range (Wursig et al. 2000). However such measures are extremely expensive, requiring high power air compressors to release sufficient air, with the amount of bubbles affecting the frequency range dampened, and extensive testing still in progress to create more efficient systems. Furthermore the curtain must stay vertical without gaps, meaning that in strong currents it must either be enclosed within a sleeve or be generated with more power (Nehls et al. 2007).

Rather than implementing engineering measures, another option is to vary the construction regime itself, for example by increasing the duration but reducing the strike impacts. Such approaches have been shown to reduce source levels by 10 – 15 dB in the > 2 kHz range (Thomsen et al. 2006), however it is not known whether a more continuous signal is more or less of an impact upon marine species. Other options include using biological knowledge to reduce the impact upon the receiving animal; either by ensuring that noise does not take place in a particular area, time of year/day, or by restricting activity to times when animals are not detected. These methods largely rely on the presence of sufficient biological data about the study area species composition, the species hearing abilities and the extent to which noise is likely to impact those species. In the example of pile driving, a soft-start approach can be used to gradually introduce the piling noise allowing animals time to leave the area before the noise level is at maximum amplitude, or acoustic deterrents may be used for a similar purpose (Richardson et al. 1995). Alternatively, construction activity may be restricted to times when animals are not detected, although this depends upon successful detection techniques. For example, passive acoustic monitoring (PAM), which relies upon detection of vocalisations, is largely restricted to animals which are vocalising at the time, environmental conditions and upon the skills and ability of the listener to detect them (Gordon and Tyack 2002, Parsons et al. 2008). Since no species vocalises constantly, it is possible for animals to go undetected and whilst fish and invertebrates do create ‘choruses’ the technique currently is used only for marine mammals.

In many cases mitigation measures are likely to come at a great expense to the developer, in terms of engineering techniques, noise and biological monitoring costs. In addition to this there are additional

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responsibilities to ensure measures are managed correctly on site, without impacting the activity being undertaken and without bias. However the benefits of these measures include significant benefits in terms of technological advancement, which are likely to improve construction methods and efficiency to the developer, and also biological benefits such as maintenance of populations and protection of species.

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Table 5.9. Types of noises and management measures for each, developed from Roberts (2015) Method Noise source Mitigation example Considerations Key references Stop sound All Cease activity or use alternative technology. Not always possible. emission Weir & Dolman (2007). Reduce vessel speed. Quieter ships. No evidence that quieter vessels are quieter, noisier in other ways. De Robertis & Handegard (2013). Shipping Exclude activity from sensitive areas or at specific Not always possible. times. Use alternative foundation types e.g. gravity

foundation. Dependent on seabed conditions. Thomsen et al. (2006); Gotz et al. Pile driving & Use alternative piling types e.g. vibroesis. (2009). drilling Difficult to install pile sleeves at sea. Expensive, may only be affective in Bubble curtains, soft pads, foam, hydro sound Wursig et al. (2000); Nedwell et al. shallow water. Producing sufficient bubbles to achieve success at all dampener. (2003a, b); Nehls et al. (2007). Minimise frequencies. sound output Sonar Minimise sound output. Restrict frequency range. Reduce duration or frequency of dredging. Not always possible within the context of fisheries. Dredging Change gear type to a low impact version. Research required as to which gears ‘better’. Vary foundation structure e.g. jacket, monopole, Depends on the frequency range to be reduced as to which foundation is Marmo et al. (2013). gravity foundation. best. Operational Vary structural pattern of wind farm itself e.g. windfarm (gear Negligible difference between the two. diamond vs square. box, vibration) Encourage biofouling/reef structures to dampen Efficacy unknown. sound. Bubble curtains, soft pads, foam, hydro sound Difficult to install; Expensive, may only be affective in shallow water; Explosives dampener. Producing sufficient bubbles to achieve success at all frequencies. Increase number of strikes but reduce driving force. Relationship between diameter of pile and sound level not well defined. Thomsen et al. (2006). Trade intensity Pile driving Increasing duration reduces the sound but may mask biological acoustic for duration or Use many smaller piles instead of one large. signals more as longer signal. size for Seismic shooting Fewer surveys, shorter surveys etc. Shorter pulses are more effective at driving pile than longer. duration Sonar Restrict frequencies or survey times. No evidence of the efficacy of such measures. Pile driving & Often manual approach, depends on the crew. Exclude or drilling Richardson et al. (1995); Stone & drive animals Soft-start, ramp-up, acoustic deterrents. AD’s may only be effective within small radius, possibly below the ranges Seismic Tasker (2006); Wier (2008). away that hearing shifts may occur. Ramp-up may affect ability of animals to Sonar localise the sound source. Explosives Depends upon successful detection; observer ability and availability (experience, enthusiasm, training, independence) and environmental Restrict activity Pile driving & Passive acoustic monitoring; Active acoustic variability (sea state, time). Mostly used for marine mammals, however Gordon & Tyack (2002); Clark & to detection- drilling monitoring; Visual monitoring. may be possible for invertebrate and fish choruses in some instances, Gagnon (2006); Parsons et al. (2008). free periods but lower amplitudes AAM- transmits acoustic energy, potential for biological disturbance.

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The ICES (2014) fish stock data (value in GBP and live weight, tonnes) was used to calculate proportional shares of the main species of fish and invertebrates that might be found in the ECMP area. Approximate shares were calculated specifically for each species in the ECMP area by summing different figures spatially. The thirty species with the largest shares are presented in Table 5.10 as being of commercial importance in the ECMP area. For the marine cetacean survey, abundance data was collated from Hammond et al. (2013), which provide abundances of key species in European Atlantic Shelf Waters from a SCANS II survey, which was undertaken to allow the EU to monitor and maintain cetaceans. From the data, the survey area ‘U’ was used for Table 5.10, defined as the east coast area of the UK encompassing the ECMP area. For pinnipeds, survey data from the University of St Andrews (Sea Mammal Research Unit, 2014) was used, however for grey seal this data relates to hauled-out adults (commonly used in population estimates) from the whole of the SE England coastal area, and for harbour seals the data relates to pup production in the whole of England (pup productions are used for this species due to uncertainties of overall population estimates). The key species included in Table 5.10 are split into approximate categories according to data availability. Most notably, only two invertebrates groups are included - these are the crustaceans and the molluscs since it is these groups that have the most data regarding underwater noise/vibration effects, as invertebrates have only recently gained research interest, and the sensory abilities of many are still in dispute. Fish are divided into those with a swimbladder and those without. However, it is of note that whilst the swimbladder can enhance hearing ability, for this to apply there needs to be a connection to the inner ear - this connection is not always present (see Ladich and Fay 2013 for review of hearing), hence the subdivision here between the two is not related to hearing ability directly; although, for example, flatfish and shark/rays, without a swimbladder are likely to be sensitive to the particle motion component of an acoustic stimuli rather than pressure.

A brief review of the literature, in addition to expert knowledge, has been used to inform the completion of the ‘species specific information’ columns in Table 5.10. Types of effects have been sub-divided into behaviour, physiology and physical (with physical incorporating, for example, damage to hearing organs, changes to hearing ability or damage to eggs). In order to avoid misrepresentation of data, cells with ‘yes’ have also been rated according to the number of peer- reviewed journal articles available in that category- from red (< 5) to green (10-15+). For example, whilst both lobsters and harbour porpoises have data relating to behavioural effects, there is a wealth of data regarding porpoise in comparison to lobster, hence the respective green and red shading. In this way, a cursory glance at the species-specific information indicates that, in general, invertebrates have received much less research compared to fish and marine mammals. A similar approach was used to populate the ‘generalised information’ column, which is again split into three groups of effect. For example in the case of lobsters, there are species specific studies relating to Nephrops norvegicus (e.g. Goodall 1990, Solan et al. 2016), Crangon crangon (e.g. Lagardere 1982) and various shore crabs found in the ECMP area, but there are some additional experiments regarding other decapods such as freshwater crayfish and semi-terrestrial crabs which is of relevance since these are likely to have similar sensory detection abilities. The colour coding in these

115 Deliverable 2.1 Report on impacts on net socio-economic benefits of achieving GES and consequences of monitoring n cells, represents whether the generalised information available is enough to set sound exposure criteria for these groups. This judgement was made according to recent literature, for example Popper et al.’s (2014) sound exposure criteria for fish, and Southall et al.’s (2007) criteria for cetaceans. Red represents a lack of sufficient data, with green indicating that there is sufficient data to set levels - for example there are generalised criteria for cetaceans available, whereas for many fish and invertebrates criteria setting is not possible due to lack of empirical data. It is of note that very little information was found in relation to cartilaginous fish, and in particular to skates and rays.

A ‘lab or field’ column has been added to indicate whether the available reviewed data was undertaken in the laboratory or field setting. This is of particular importance in bioacoustics since, aside from the stresses that captivity is likely to inflict upon study animals, acoustic propagation within small laboratory tanks is complex (Parvulescu 1964). This makes replication of an anthropogenic source in a tank, for example, difficult due to the presence of boundary walls and reflective surfaces which are likely to distort the waveform beyond its original form. As such, in terms of acoustics, field studies are preferable to reflect natural conditions. In addition to this, captivity is unfeasible for some species (for example large marine mammals). Finally, the ‘key references’ column points towards references per group as an indication of the literature available. More detailed information in terms of the acoustic source type (and exposure level) has not been included here and so the table considers noise as a whole, rather than specific source types, which for the purpose of this exercise was deemed sufficient coverage.

Table 5.10 indicates the lack of data regarding crustaceans and bivalves, although there have been studies relating directly to the species found in the ECMP area, for example C. crangon, C. maenus, N. norvegicus (e.g. Goodall 1990, Berghahn et al. 1995, Wale et al. 2013a,b). However within these studies, the work has been predominantly laboratory based, with effects exhibited being changes to foraging and anti-predator behaviour, postural changes and changes in oxygen consumption and stress proteins. There is some information regarding the sensitivity of non-ECMP species such as freshwater crayfish and semi-terrestrial crabs to substratum vibration (reviewed in Roberts, 2015). In the molluscs, work has focussed upon the cephalopods with clear demonstrations of acoustic trauma in relation to noise (e.g. Andre et al. 2011), and behavioural changes such as ink jetting. There are few data relating to bivalves, although commercial EMCP area species such as Mytilus edulis have received attention recently in relation to sediment vibration (Roberts et al. 2015). Typical effects seen in such bivalves to date include valve closure in response to vibration, changes in oxygen consumption and malformations in larvae (e.g. Solan et al. 2016). There are also indications that sound is an important settlement cue in invertebrate larvae (and fish) and therefore it is likely that noise would affect this (Lillis et al. 2014). Fish have received more research attention than invertebrates, however data is still lacking for many species of fish (Popper et al. 2014). Data collection regarding species that detect particle motion alone, such as flatfish, has been hindered due to difficulties of measuring particle motion in the water column. Behavioural changes in schooling fish such as herring, mackerel and sprat, indicate changes in schooling such as density and depth changes in response to noise, and displacement from important areas such as feeding and

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foraging (Pitcher et al. 1996; Hawkins et al. 2014), increased swimming and startle responses in captivity (e.g. Kastelein et al. 2008). In those fish that vocalise during reproduction, such sounds can be masked by additional background noise (reviewed in Radford et al., 2014). Other effects include auditory changes (e.g. temporary or permanent auditory threshold shift), and stress and mortality (for a comprehensive review see Popper and Hastings 2009) with physiological changes likely to include changes in stress hormones, metabolism, growth and energy budget changes (see Roberts 2015 for a review; Santulli et al. 1999). For fish with swim bladders physical damage may be induced such as sensory membrane lesions and gas bladder ruptures and lethal injury in larvae has been demonstrated (e.g. Govoni et al. 2008). Observed effects of noise upon marine mammals have included physiological changes such as stress, physical damage, and acoustically-induced stranding (Nowacek et al. 2007, Weilgart 2007). For example, in March 2000, 17 cetaceans were stranded along the coasts of three Bahamian islands - these included minke, cuvier and blainvilles beaked whale. Prior to the stranding the US Navy was undertaking anti-submarine exercises with 2 – 10 kHz sonar, and it is thought the two events were linked since there was evidence of auditory damage in the stranded animals (Götz 2009). In addition to this, behavioural changes, such as avoidance of certain areas, feeding, migration disruption and decreased surface time have been demonstrated (Kastelein et al. 2005, Nowacek et al. 2007, Kastelein et al. 2013); and vocalisation changes such as changes in song frequency and length (Foote et al. 2004). One species of the ECMP area, the harbour porpoise, is especially popular for study, possibly due to its small size and prevalence.

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Table 5.10. Occurrence of marine mammals, fish and shellfish in the East Coast Marine Plan (ECMP) area and how they are affected by noise (and sediment vibration where applicable). Information availability rating: Red = very few peer-reviewed studies available; Orange- limited availability; Green- multiple peer-reviewed studies available. It is of note that in general fish and invertebrates have received much less research focus than marine mammals. Values and live weight in tonnes taken from ICES data for the ECMP area for 2014.* from all of England ** from SE England only Species specific information Generalised information Live weight (in Lab or Lab or Key references Type Species Value (in £) Behav. Physiol. Phys. Behav. Physiol. Phys. t) Field Field Goodall (1990); Solan et al lobster 6,948,412 990 Y Y L/F L/F (2016) crabs (mixed- spider, brown, Wale et al (2013a,b); Roberts et 4,443,458 3,788 Y Y L L/F Crustaceans edible, shore crab) Y Y Y al (2016) Lagadere (1982); Berghahn et al shrimp 513,661 243 Y Y L L (1995); Regnault and Lagardere (1983) cephalopods: octopus, 22,031 7 Y Y L L Andre et al (2011) cuttlefish Molluscs Y Y Y Kastelein (2008); Mosher (1972); bivalves: oysters, clams, 4,029 23 Y Y Y L L Roberts et al (2015); Solan et al cockles (2016); Lillis et al (2014) sole/lemon sole; plaice; dab; Thomsen et al (2010); Berghahn Fish 6,937,218.030 4,067.657 Y Y L/F F turbot; brill; flounder et al (1995) (minus Y Y Y mackerel 3,851 1.795 Y L/F F Hawkins et al (2014) swimbladder) sharks, skates and rays 218,882 162 Y L/F Myrberg (1978) cod 203,400 110.194 Y Y L/F Buerkle (1968); Løkkeborg and bass 371,406 51.398 Y L/F Ona (1996); Misund et al. (1995); herring 101,963 302.396 Y F Enger (1981); Santuli et al. (1999); Engas et al (1995); Engas Fish haddock 8,795 7.549 Y L/F Y Y Y L/F et al (1995); Pitcher et al. (1996); (Swimbladder) Løkkeborg & Ona (1996); mullet 8,498 5.254 Y F Kastelein et al. (2008); Govoni et al (2008); Caltrans et al. (2001); Radford et al. (2014) All Population estimates Y Y L/F Nowacek et al (2007); Weilgart harbour porpoise 88,100 Y Y L/F (2007); Southall et al (2007); minke whale 23,528 Y Y Foote et al. (2004) Kastelein et Marine humpback whale n/a Y F al. (2005); McCauley et al. Y Y Y L/F Mammals fin whale n/a Y F (2000); Williams et al. (2014) bottlenose dolphin 16.485 Y Y L/F harbour seal 4,504** L/F Gordon et al. (2004) Y grey seal 5,213 *

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Increasingly ecosystem service approaches are being incorporated into marine policy and management to recognise the impact of environmental change on human welfare (Börger et al. 2014). Application of an ecosystem services framework is therefore seen as a fundamental part of embedding the ecosystem approach in marine management (Atkins et al. 2011). The ecosystem service framework applied here was developed from The Economics of Ecosystems and Biodiversity (TEEB) framework (de Groot et al. 2010b), but has been adapted by Hattam et al. (2015a) for specific use in the marine environment. Based on the review of evidence above, Figure 5.5 identifies the ecosystem structures, processes, services and benefits which may be impacted from MSFD measures to reduce underwater noise in the marine environment.

Management measure Ecosystem structure Ecosystem processes Ecosystem Services Benefits

Food provision Gene pool Measures for Biological Marine Food protection noise reduction Diversity Webs Recreation [Descriptor 11] [Descriptor 1] [Descriptor 4] and leisure Wild fish and shellfish for food Aesthetic experience Support of [Descriptor 3] Availability of breeding habitats populations Cultural Charismatic heritage species

Cognitive development

Figure 5.5 Conceptual model displaying the potential effects of noise reduction on the ecosystem structure, processes, services and benefits it provides. Further explanation in the text

Given the complexity of the marine ecosystem and the need for integrated management, indicators are required to provide insight into the behaviour and state of coastal and marine ecosystems, together with an indication of the trajectory of change due to natural and human events (Gibbs and Cole 2008, Elliott 2011, Atkins et al. 2015). It has been suggested that indicators have three basic functions (Aubry and Elliott 2006): to simplify - amongst the diverse components of an ecosystem, a few indicators are needed according to their perceived relevance for characterising the overall state of the ecosystem; to quantify - the indicator is compared with reference values considered to be characteristic of either 'pristine' or heavily impacted ecosystems to determine changes from reference or expected conditions; and to communicate - with stakeholders and policy makers, by promoting information exchange and comparison of spatial and temporal patterns. Indicators can therefore be used to reflect either the state of the science of an area (Atkins et al. 2015) or to provide a useful tool for supporting management decisions (Hattam et al. 2015a,b). A number of studies have developed ecosystem service indicators for the marine environment (e.g. Atkins et al. 2015, Hattam et al. 2015a), with further indicator development undertaken within the DEVOTES project (see the DEVOTool). Based on the ecosystem structure, processes, services and benefits identified above (Figure 5.5), example indicators which could be applied to assess the impact of management measures to address underwater noise have been identified (Table 5.11).

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Table 5.11. Example indicators that show changes in ecosystem structure, processes, services and benefits (sources: DEVOTool; Hattam et al. 2015a, Atkins et al. 2015) Example Indicators

Ecosystem Biological diversity Biomass of marine biota (g, kg) Abundance of marine biota (number) Species diversity (Shannon Wiener Structure Index) Availability of habitats Change in area of habitat (km2 or m2 % cover of habitat Change in physical conditions (e.g. per unit time) sediment type) Ecosystem Marine food webs Changes over time in community Species diversity (diversity indices) Productivity (production per unit Processes composition (abundance) biomass) or key species Support of breeding Quantity of larvae supplied to a Male:female ratio Adult:juvenile ratio populations particular location (number per m3) Ecosystem Gene pool protection Presence/absence of desirable species Diversity of desirable species (diversity Biodiversity Intactness Index (BII) Services indices) Wild fish and shellfish for Biomass of fish or shellfish (g, kg) Abundance of fish or shellfish Species diversity (Shannon Wiener food (number) Index) Charismatic species Abundance of marine mammals Species composition, age profile Mortality rates (number per species) Benefits Food provision Nutrition from seafood consumption Fish and shellfish landed for human Fisheries revenues and contribution to (g protein per year) consumption (tonnes) Gross Value Added (GVA) (£) Recreation and leisure Number of wildlife watchers Number of beach users Amount of time spent participating (hours/day per activity) Aesthetic experience Number of marine features of given Area of features given stated Length of heritage coast (km) stated appreciation appreciation (m2, km2) Cultural heritage Sites with cultural heritage (visitor Sites of cultural heritage (degree of Cultural importance of site (gained numbers) importance) from discourse analysis) Cognitive development Field trips (number of trips and Scientific studies (number of scientific Scientific studies (number of research number of people involved) studies) papers published)

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In order to test the impact of MSFD management measures for underwater noise on ecosystem service provision, a number of scenarios were developed (Table 5.12). The scenarios were made up of two components: an environmental scenario, which in this case related to the level of marine activities (namely shipping and construction relating to wind farm developments); and a management response, which reflects whether specific MSFD management measures are implemented to address underwater noise. This resulted in four independent outcomes which could be used to assess their impact on ecosystem service provision in the ECMP area. Given the limited knowledge and evidence base available on the impacts of underwater noise on ecosystem service provision, a number of exemplary assumptions were taken into account during the development of the scenarios (Table 5.13). Assumptions with respect to wind farm developments in the ECMP area, related to implementation of development in areas leased for offshore wind farms in UK waters in Rounds 2 and 3 by the Crown Estate (Higgins and Foley 2014). In the low impact scenario only Round 2 developments were in place. For the high impact scenario both Round 2 and Round 3 wind farm developments were in place. It is acknowledged that other construction activities may take place in the ECMP area, however it is envisaged that wind farm construction may potentially cause the greatest impact and site specific evidence for the number of turbines associated with each development is known for the area.

Table 5.12. Development and definition of scenarios. Note: Impact is defined as potential impact that is the likelihood of environmental damage if levels of underwater noise increase up until 2020

Management response

Environmental scenarios No MSFD management (additional) MSFD (current management management (noise measures continue) reduction measures)

Low impact: Marine activities Outcome 1 Outcome 2 (shipping, construction) remain at current levels Low impact GES (no expected impact)

High impact: Increase in marine Outcome 3 Outcome 4 activities (shipping, construction) by 25% High impact GES (no expected impact)

Table 5.13. Overview of exemplary assumptions in the environmental scenarios Assumptions

Scenario Installation of wind Shipping Fishing turbines

푈푊푁 푈푊푁 푈푊푁 Low impact 퐿1 퐿2 퐿3

푈푊푁 푈푊푁 푈푊푁 High impact 퐻1 퐻2 퐿3

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Description of scenarios for underwater noise

The high and low impact scenarios are based on the following assumptions:

푈푊푁 퐿1 : Only Round 2 wind farm projects will be completed. This includes all wind farms currently being built (Dudgeon, 67 turbines) and those that are in pre-construction status (Race Bank, 91 turbines; Galloper Wind Farm, 56 turbines) or have been consented (Triton Knoll, approx. 160 turbines). This results in the need for pile driving for 374 turbines10

푈푊푁 퐻1 : All Round 2 and 3 wind farm projects will be completed as currently planned. For Round 3 these are all wind farms in the following statuses: pre-construction (East Anglia One, 102 turbines; Hornsea Project One, 171 turbines), consent application submitted (East Anglia Three, approx. 140 turbines; Hornsea Project Two, approx. 170 turbines), concept/early planning (East Anglia One North and Two, est. 100 turbines each; Hornsea Project Three and Four, 112 turbines each; Norfolk Boreas and Vanguard, 225 turbines each). Adding those built under Round 2 (374) this results in the need for pile driving for 1,831 turbines.

푈푊푁 퐿2 : Ship movements remain at current levels within the ECMP area (c. 576 passenger vessels, 49,624 container vessels, and 8,676 tanker vessels (yearly average of 2011-2014 data)).

푈푊푁 퐻2 : Ship movements increase by 25% compared to 2011-2014 data.

푈푊푁 퐿3 : Noise impacts on commercial fish species will decrease catches in the ECMP area by 5%.

푈푊푁 퐻3 : Noise impacts on commercial fish species will decrease catches in the ECMP area by 50%.

The impact of the aforementioned scenarios on ecosystem service provision has been assessed qualitatively, based on literature and expert judgement, given that there was insufficient site- specific evidence available at this time (Table 5.14). Under the low impact Outcome 1, it is assumed that there would be negligible impact on gene pool protection as current noise levels are unlikely to physically affect marine organisms at the population level. For example, it is generally accepted that for fishes, behavioural changes are likely to have greater population level impact than physical damage, since these occur at lower levels of sound occurring at greater distances from the source (Popper et al. 2014).

A potential negative effect has been highlighted for the impact on both wild fish and shellfish provision and charismatic species; although population effects are considered unlikely, small-scale changes in the behaviour or physiology of these organisms may occur (e.g. Regnault and Lagardere 1983, Weilgart 2007, Hawkins et al. 2014b).

10 Turbine numbers extracted from www.4coffshore.com

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With respect to the benefits, there was insufficient evidence available to assess whether the impacts under Outcome 1 would be negligible or potentially negative. No positive impacts on either ecosystem service provision or benefits have been identified under this scenario.

Under Outcome 2, it is considered that there would be a negligible impact on gene pool protection, which reflects the fact that under Outcome 1 there was a negligible impact as a result of current noise levels. It is assumed that the additional management measures employed to achieve GES could result in a potential positive impact on fish and shellfish provision and on charismatic species. Likewise, the provision of benefits under the additional GES management measures was considered to be either negligible or potentially positive. There is currently no site-specific knowledge underlying these relationships, however it can be assumed that there would be no negative impacts on ecosystem service or benefits provision associated with these additional management measures.

Outcome 3 reflects the impact of an increase in both marine construction and shipping, and thus represents an overall increase in underwater noise compared to current levels. There is existing evidence to suggest past increases in levels of ambient ocean noise levels may be attributed to shipping in this way (e.g. Andrew 2003, McDonald et al. 2006, Frisk 2012). With respect to ecosystem services, a potential negative impact would be anticipated on the provision of gene pool protection and wild fish and shellfish for food, whilst a potential significant negative impact would be observed on charismatic species, in particular marine mammals. In turn, these effects would result in a potential negative or significant negative effect on food provision benefits (depending on species sensitivity), and a potential significant negative effect on recreation and leisure, and aesthetic benefits in relation to the impact of underwater noise on charismatic species. Both cultural heritage and cognitive developments may also show potential negative effects.

In order to achieve GES under Outcome 4 additional management measures would be implemented and result in potential positive effects and significant positive effects on the range of ecosystem services and benefits identified (Table 5.14). The only distinction between levels of provision relates to the greater potential impact of underwater noise on charismatic species and their associated benefits (leisure and recreation and aesthetic benefits). Site-specific evidence would however be required to enable quantitative assessments of the potential impacts.

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Table 5.14. Impact of four different settings of noise impact and reduction policy options (‘outcomes’) on the provision of key ecosystem services and benefits

Policy Options Outcome 1 Outcome 2 Outcome 3 Outcome 4

Current noise levels Current noise levels Noise levels increase; no Noise levels increase; continue; no additional continue; MSFD management measures MSFD management Description management measures management measures implemented measures implemented implemented implemented Gene pool protection 0 0 - +

Ecosystem Wild fish and shellfish for Services food -- + -- +

Charismatic species - + -- ++

Food provision 0/- 0/+ - +

Recreation and leisure 0/- 0/+ -- ++

Benefits Aesthetic experience 0/- 0/+ -- ++

Cultural heritage 0/- 0/+ - +

Cognitive development 0/- 0/+ - + Key: ++ Potential significant positive effect; + Potential positive effect; 0 Negligible effect; − Potential negative effect; −− Potential significant negative effect.

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Costs and benefits of ballast water management to prevent the introduction of invasive alien species

Management of invasive species: Ecological effects of ballast water management

Invasive alien species (IAS) are defined as those species with a “significant negative impact on biodiversity as well as serious economic and social consequences” (EC 2014). Their introduction has long been recognised as a key threat to marine ecosystems and the services these deliver. They can also cause economic damages by impacting fisheries, by clogging water intake pipes and by hull fouling (Molnar et al. 2008). Due to their importance and potential impacts, IAS are addressed by the MSFD in a specific descriptor (D2). However, they can also change the ecosystem including biodiversity (D1), the food web (D4) through changes in feeding relationships, and they can impact the seafloor and associated benthos (D6).

On a general level the management of IAS involves activities such as exclusion, containment and adaptation and mitigation (Perrings 2002, Oreska and Aldridge 2011). Specific measures for invasive species management cannot always be clearly allocated to any one of these categories, but they serve as a framework to structure the range of potential measures. Exclusion involves the prevention of the introduction and establishment of IAS as well as the eradication of already introduced species. Since in the marine environment eradication is impractical and hence impossible in most cases (Anon 2012), the analysis in this report considers only preventive measures. For the marine environment, shipping is the key vector for species globally and the most efficient way to avoid arrival of new species is successful ballast water management (Molnar et al. 2008, Ojaveer et al. 2014). The main introduction pathways and vectors of potential IAS arrivals are managed under several dedicated policy frameworks (Ojaveer et al. 2014). For example, ICES has a Code of Practice on Introduction and Transfers of Marine Organisms, it is anticipated that the International Convention for the Control and Management of the Ships Ballast Water and Sediments of the International Maritime Organization (IMO) will enter into force in September 2017, and international guidelines on ship hull fouling prevention are under development (Ojaveer et al. 2014).

Prevention measures affect the main introduction vectors of IAS, such as commercial shipping, recreational boating, aquaculture (EC 2007) and fisheries, ship decommissioning and other marine industries (Anon 2012). With respect to the deliberate or accidental introduction of species into a new ecosystem, Anon (2012) mention the development of industry codes of practice, improved enforcement of existing regulations, awareness building amongst stakeholders and possibly new legislation as potential measures. On an international level, the IMO Ballast Water Convention (IMO 2004) has not come into effect yet, but sufficient states have now ratified it that it will come into force in 12 months’ time in September 2017. For this case study, the focus will be on prevention measures because these are additional measures not yet in place but currently discussed for the UK i.e. Category 2a and b measures. The main measure to address the risk of introduction of IAS is the installation of ballast water management (BWM) systems in vessels operating in the ECMP area. This management measure will be implemented once the IMO Convention enters into force.

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After Northern California, the North Sea has been recognised as the second most invaded ecoregion in the world, with the majority of the IAS arriving through shipping (Molnar et al. 2008). Therefore, in the ECMP area case study, the adoption of ballast water management was chosen for the cost benefit analysis as an approach to reduce the risk of introduction of IAS and thereby aid the achievement of GES.

This work addressed the following research questions:

 What are the ecological, economic, social and benefits of effective ballast water management?  Which indicators are necessary to measure impacts of NIS on ecosystem services and benefits?

Ecological approach

Ecosystem services are the direct and indirect contributions of ecosystems to human well-being and can be used in the management of the marine environment by allowing the balancing of trade-offs between conservation of biodiversity and management objectives (de Groot et al. 2010a). The ecosystem services approach was chosen in this study to ensure that not only tangible benefits are considered and valued in the CBA but also those services for which economic assessment of the benefits derived from them is not as straight-forward and which are therefore at times overlooked or considered as ‘free’, for example the service of bioremediation of waste (Beaumont et al. 2008).

Due to the importance and potential negative effects of IAS, there are many publications and online resources that catalogue IAS by species as well as further information such as vectors, country/are of origin, damage in invaded areas, publications. This analysis focussed on species that do not yet occur in the ECMP but have the potential to lead to a reduction in ecosystem services and benefits which would be reflected in reduced services and economic losses. Following a discussion among participants of the work package and using a horizon scanning publication (Roy et al. 2014), thirteen species were taken into consideration for this case study (Table 5.15). The aim of this exercise was to find up to two species that are not yet in the study area, that use ballast water as a vector and would therefore be affected by ballast water management. Scenarios were then developed to assess how these two species would affect the ecosystem services and benefits provided and which indicators would show such changes. Each species was assessed in terms of their potential impact, and management measures following (Olenin et al. 2014) (Table 5.16).

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Table 5.15 Species that were suggested for the study and the reasons for exclusion. Information sources: AquaNIS: Information system on aquatic non-indigenous and cryptogenic species (www.corpi.ku.lt/databases/index.php/aquanis/); CABI: Invasive species compendium (www.cabi.org); DAISIE: Delivering Alien Invasive Species Inventories for Europe (www.europe- aliens.org/default.do); ISSG: IUCN Invasive Species Specialist Group (www.issg.org/); NEMESIS: National Exotic Marine and Estuarine Species Information System (www.invasions.si.edu/nemesis/index.jsp); NBN: National Biodiversity Network (www.nbn.org.uk/); NNSS: GB Non-native species secretariat (www.nonnativespecies.org/home/index.cfm)

Phylum Common Species name Reason for exclusion References name Annelida Red-gilled Marenzelleria Low impacts according to few sources AquaNIS mud worm neglecta on this species available, difficult to carry out a risk assessment with little information Annelida Red-gilled Marenzelleria Low impacts according to few sources NNSS mud worm viridis on this species available, difficult to carry out a risk assessment with little information Ascidian Carpet Didemnum Hull fouling more important as a NNSS seasquirt vexillum vector Cnidaria Nomad Rhopilema Ballast water not an important vector DAISIE jellyfish nomadica in this species Crustacea Chinese mitten Eriocheir Already occurs widely in the study NNSS crab sinensis area Japanese Hemigrapsus Species was chosen for this study See ¡Error! shore crab sanguineus o se encuentra el origen de la referencia. Mollusca Pacific oyster Crassostrea Main vector aquaculture, deliberate NBN gigas introduction into the study area American Ensis directus Already occurs widely in the study NNSS razor clam area Asian oyster Ocenabra Similar to Rapana venosa but feeds NEMESIS drill inornata preferentially on oysters rather than a variety of bivalves Mollusc Veined whelk Rapana venosa Species was chosen for this study See ¡Error! o se encuentra el origen de la referencia. Seaweed Sea grapes Caulerpa Mostly using other vectors, Verlaque et racemosa var temperatures in the study area not al. (2003) cylindracea suitable Seaweed Killer alga Caulerpa Mostly using other vectors, ISSG taxifolia temperatures in the study area not suitable Vertebrate Lionfish Pterois volitans Temperatures in the study area not CABI suitable for the species

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Two species, the gastropod Rapana venosa and the decapod crustacean Hemigrapsus sanguineus were selected for this analysis. Both species are predators feeding on intertidal and subtidal invertebrates and therefore have the potential to change the biodiversity in areas affected as well as the food web and ecosystem services. As a first step, we identified evidence of negative effects of these species in other sea regions.

Table 5.16 Invasive Alien Species assessment criteria for Rapana venosa and Hemigrapsus. sanguineus based on Olenin et al. (2014) but adapted to give further information for the case study. Questions in italics were added to the original list. The Table was populated using information from species information websites: ISSG (IUCN Invasive species specialist group), NNSS (Great Britain non- native species secretariat, as well as their risk assessment and fact sheets (NNSS RA and NNSS FS respectively)), Epifanio 2013 and Katsanevakis et al. (2014). See Table 5.9 for explanation of abbreviations Assessment criteria Rapana venosa Hemigrapsus sanguineus Is a NNSS Risk Assessment available? Yes No, but a NNSS factsheet 1. Is there actual evidence of the species being No No found in ballast water and/or sediments?

2. Is there a risk for the species of becoming Yes, planktonic larvae Yes, planktonic larvae entrained in ballast tanks? a) Species has pelagic life-history stage; 80 days (RA NNSS) 16-55 days (NNSS) b) Species performs diurnal vertical migration; No No c) Species has a pelagic host; No No d) Species is present in sediments in shallow No Likely water ports (ballast water uptake areas). 3. Is there a risk for the species to be spread Yes, aquaculture, Yes, through planktonic further within the selected area? ballast water, hull transport larvae a) The species is already established in all No No colonisable regions /countries in a particular LME; b) The species is unable to colonize further FALSE FALSE areas based on its known physiological limits. What are the physiological limits of the Yes, occur in Britany, France Yes, occur in Europe and species, do they fit the ECPA? (NNSS RA) North America, USA, France, Netherland (ISSG) a) Salinity > 16 Marine b) Temperature (ºC) 4-27 Not known c) Other physiological limits Tolerates hypoxia (ISSG) Intertidal, needs boulders and crevices (NNSS FS)

Fecundity Larval production 50 000 eggs per female, can per whelk is nearly 400 000 be produced several times (NNSS RA) per season (NNSS FS)

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Assessment criteria Rapana venosa Hemigrapsus sanguineus Natural enemies/competitors None (NNSS RA) Some birds and fish may feed on them (ISSG)

4. Has the species been documented as having None known No (NNSS) an impact upon human health (mortality, illness, poisoning, toxicity, pain, irritation)? 5. Is there a potential for high risk for the No No species to impact upon human health (i.e. there is insufficient evidence to rule out an unacceptable risk)? 6. Has the species been documented as having Yes, but correlative No an impact upon economy? (Black Sea) (ISSG) a) Damage to property; Voracious predator feeds No on bivalves (ISSG) b) Decline of employment; With decline of bivalves, No but no evidence c) Decline of income. With decline of bivalves, No but no evidence Positive effects? Commercially exploited No in the Black Sea (Katsanevakis et al. 2014) 7. Is there a potential for high risk for the Yes, feared to negatively Yes, feed on mussels and species to impact upon economy (i.e. there is impact bivalve fisheries and oysters with potential insufficient evidence to rule out an aquaculture if successful competition also with unacceptable risk)? invasion (NNSS, NNSS RA, juvenile Cancer pagurus ISSG) (NNSS FS) 8. Has the species been documented as having Yes, competes with native Yes, reduction in common an impact upon environment (native Buccinum undatum, can shore crabs abundance, and communities, habitats, ecosystem functioning)? threaten habitat forming mussel density in areas of bivalves (Black Sea) leading high density of this crab, to reduced habitat (NNSS RA) similar effects across the wider community (NNSS factsheet), omnivorous also feed on seaweeds (Epifanio 2013) 9. Is there a potential for high risk for the Yes, habitat reduction by Yes, predators may reduce species to impact upon environment (i.e. there destruction of mussel beds snails, barnaclae and is insufficient evidence to rule out an (no source!) polychaetes as well as unacceptable risk)? juvenile crustaceans (NNSS factsheet) 10. Has the species been documented as having No No an impact upon cultural and social values? a) Degradation of culturally and nationally No No important habitats; b) Degradation of amenity; No No c) Impact on human activities (i.e. diving, No, but harvesting of No swimming, sailing, fishing). shellfish maybe reduced (no source) 11. Is there a risk of the species impacting No No cultural and social

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Assessment criteria Rapana venosa Hemigrapsus sanguineus values (i.e. there is insufficient evidence to rule out a high risk)? Already occurs in the ECPA? No No, but in Kent Other information Can also spread through Small, up to 4.5 cm aquaculture, hull fouling, may be near the Doggerbank (NNSS)

Rapana venosa (Valenciennes 1846)

R. venosa is a large Asian gastropod native to the Sea of Japan, Yellow Sea, Bohai Sea and the East of China to Taiwan (Mann et al. 2004). It has been successfully established in five known regions mainly through ballast water as a vector. It occurs on sandy and hard bottom habitats to a depth of 40 m (Mann et al. 2004). The species has been identified as the prime reason for the decline of the Mytilus galloprovincialis in the Black Sea (Mann et al. 2004 and references therein). In the Black Sea, R. venosa has been reported to be responsible for decreasing densities of large bivalve molluscs at many sites. In some sites Ostrea edulis, Pecten ponticus and Mytilus galloprovincialis have nearly gone extinct a few years after introduction (Zolotarev 1996). R. venosa also influenced soft sediment communities in the Black Sea by feeding on soft sediment bivalves (Zolotarev 1996). Mussel beds can be strongly affected by invasion of this species leading to loss of the beds and their associated communities (Salomidi et al. 2012). Caging experiments in the Adriatic have shown that R. venosa is a selective feeder and can therefore lead to changes in the community structure (Savini and Occhipinti-Ambrogi 2006). R. venosa of 104.5 mm mean shell length (s.d. 9.9 mm) ate 1.2 g wet weight day-1 of bivalves (temperature not reported) (Savini and Occhipinti-Ambrogi 2006). A laboratory experiment feeding the clam Mercenaria mercenaria to R. venosa showed that large whelks (101-160 mm shell length) can consume 2.7 grams wet weight day-1 at 26 °C (Savini et al. 2002).

R. venosa can also compete with native whelks such as Buccinum undatum (Katsanevakis et al. 2014). Management after introduction will be difficult and has been unsuccessful in areas already invaded by this species, for example France (Mann et al. 2004). Once they reach adult size, they have no predators (ISSG http://www.issg.org/). The probability of observing young individuals is minimal and therefore detection is expected to only occur once large individuals are established at the receptor site, expected no earlier than 3-4 years after introduction (Mann et al. 2004). However, the species has supported a fishery in the Black Sea and their shells have been sold to tourists showing that there may be some economic benefits derived from the species (Mann et al. 2004, Katsanevakis et al. 2014).

Hemigrapsus sanguineus

H. sanguineus, the Asian shore crab, is native to the Asia-Pacific region inhabiting the hard-bottom intertidal and shallow subtidal and can reach high local densities (Katsanevakis et al. 2014, ISSG, (http://www.issg.org/) accessed 22/04/2016). It is a small crustacean, the largest male observed in a

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French study had a carapace width of 41.6 mm (Dauvin and Dufosse 2011). A study on the East Coast of the US showed that it is an effective predator on juvenile bivalves, including M. edulis, Mya arenaria, and native oyster Crassostrea virginica (Brousseau et al. 2001).

H. sanguineus also competes with crustaceans and preys on juvenile crustaceans such as Carcinus maenas (Lohrer and Whitlatch 2002). In mainland Europe, the species has achieved significant reductions in C. maenas abundance and mussel densities (NNSS fact sheet). H. sanguineus have high fecundity with females laying up to 50,000 eggs several times during a mating season. Larvae are planktonic for up to one month. Growth and maturation are rapid and juveniles reach a mean carapace width of 20 mm within 2 years. Predators may include shore birds, some fishes and other crabs and the species may serve as an important food source for these groups (Katsanevakis et al. 2014). H. sanguineus has been recorded from the French coast of the English Channel to the North Sea coast of the German state of Schleswig-Holstein. A study along the French coast found that their densities doubled in 1-2 years with an increase of five times the density in Dunkirk harbour. At sites with high densities of H. sanguineus, densities of C. maenas were found to be low (Dauvin and Dufosse 2011).

H. sanguineus feeds mainly on hard bottom substrates in the intertidal and subtidal while R. venosa feeds on soft and hard bottom areas of the shallow subtidal. Therefore, jointly, they feed in most shallow coastal areas. Table 5.17 lists the prey species of the two IAS and the ecosystem services and benefits they may contribute to.

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Table 5.17. Species involved in food production and bioremediation services that may be affected by the two invasive species. The service gene pool protection involves more species and therefore effects of the two species will be hard to demonstrate. Values and live weight in tonnes taken from ICES data for the ECMP area for 2014. For some species values and weights are combined by ICES and therefore values can only be given as part of the rest of the group. Colour coding: green: data based on at least one experimental study, orange: observational information from at least one study, red: general assumption found in published papers based on general evidence (for example: "species feeds on bivalves and may therefore lead to a change in community structure") a) Rapana venosa b) Hemigrapsus sanguineus

Table 5.17a) Rapana venosa Type Species affected by R. venosa Processes that Services in which Value (in £) Live Prey species Lab/field/ Prey group Information Example lead to species is involved in weight specific Observation/ generalised rating references services that (in information Suggested information species may be tonnes) involved in Scallop Include Food production/ Predation Katsanevakis et al. Pecten maximus and Bioremediation/ 1,389,943 742.095 2014 Aequipecten opercularis Biological checks and balances

Cockles Cerastoderma edule Food for birds of Food production/ Predation Katsanevakis et al. recreational Bioremediation/ 2,745,759 4,399.512 2014 interest Biological checks and balances

Clams include Mya arenaria, Food for birds of Food production/ Part of Part of Predation Field Savini et al. 2006 Mercenaria mercenaria, razor recreational Bioremediation/ 505.25 0.215 clams interest Biological checks and balances

Oyster Ostrea edulis Food production/ Predation observational Cinar et al. 2005, Bioremediation/ 2,996 0.480 Zolotarev et al. Biological checks and 1996 balances

Hard- Mercenaria mercenaria Food production/ Part of Part of Predation Field Savini et al. 2006 shell clam Bioremediation/ 505.25 0.215 Biological checks and balances

Mussel Mytilus spp Food for birds of Food production/ Predation Field Savini et al. 2006 recreational Bioremediation/ 527 22.250 interest Biological checks and balances

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Type Species affected by R. venosa Processes that Services in which Value (in £) Live Prey species Lab/field/ Prey group Information Example lead to species is involved in weight specific Observation/ generalised rating references services that (in information Suggested information species may be tonnes) involved in Razor Ensis ensis Food production/ Part of Part of Predation Katsanevakis et al. clam Bioremediation/ 505.25 0.215 2014 Biological checks and balances

Razor Ensis arcuatus Food production/ Part of Part of Predation Katsanevakis et al. clam Bioremediation/ 505.25 0.215 2014 Biological checks and balances

Razor Ensis silique Food production/ Part of Part of Predation Katsanevakis et al. clam Bioremediation/ 505.25 0.215 2014 Biological checks and balances

Native Buccinum undatum Food production 2,182,385 2,839.80 Competition Suggested Katsanevakis et al. whelk 2014

Table 5.17 b) Hemigrapsus sanguineus Type Species affected by H. Processes that Services in which Value (in £) Live Prey species Lab/field/ Prey group Information Example sanguineus lead to services species is involved weight specific Observation/Su generalised rating references that species may in (in information ggested informatio be involved in tonnes) n

Scallop Include Food production/ Predation Katsanevakis et al. Pecten maximus and Bioremediation/ 2014 Aequipecten opercularis Biological checks and balances 1,389,943 742.095 Cockles Cerastoderma edule Food for birds of Food production/ Predation Katsanevakis et al. recreational Bioremediation/ 2014 interest Biological checks and balances 4,399.51 2,745,759 2 Clams Mya arenaria Food for birds of Food production/ Predation Field Savini et al. 2006 recreational Bioremediation/ interest Biological checks and balances Part of Part of 505.25 0.215

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Type Species affected by H. Processes that Services in which Value (in £) Live Prey species Lab/field/ Prey group Information Example sanguineus lead to services species is involved weight specific Observation/Su generalised rating references that species may in (in information ggested informatio be involved in tonnes) n

Oyster Ostrea edulis Food production/ Predation observational Cinar et al. 2005, Bioremediation/ Zolotarev et al. Biological checks 1996 and balances 2,996 0.480 Hard-shell Mercenaria mercenaria Food production/ Predation Field Savini et al. 2006 clam Bioremediation/ Biological checks and balances Part of Part of 505.25 0.215 Mussel Mytilus spp Food for birds of Food production/ Predation Field Savini et al. 2006 recreational Bioremediation/ interest Biological checks and balances 527 22.250 Razor clam Ensis ensis Food production/ Predation Katsanevakis et al. Bioremediation/ 2014 Biological checks and balances Part of Part of 505.25 0.215 Razor clam Ensis arcuatus Food production/ Predation Katsanevakis et al. Bioremediation/ 2014 Biological checks and balances Part of Part of 505.25 0.215 Razor clam Ensis silique Food production/ Predation Katsanevakis et al. Bioremediation/ 2014 Biological checks and balances Part of Part of 505.25 0.215 Native Buccinum undatum Food production 2,182,385 2,839.80 Competition Suggested Katsanevakis et al. whelk 2014

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Proposed impacts of these two species on ecosystem services

A conceptual model (Figure 5.6 shows how successful BWM excluding the two species can keep the ecosystem, the services and benefits it provides at current levels rather than deteriorating (deterioration only due to these two species). This model is most likely not exhaustive because the link between ecosystem properties such as biodiversity and ecosystem services is still a major scientific challenge (Pereira et al. 2010, Strong et al. 2015).

Figure 5.6. Conceptual model showing the effect of ballast water management on the ecosystem, the services and benefits it provides. It also shows which Good Environmental Status descriptors are affected at each stage. Further explanation in the text.

If BWM is successful in preventing the introduction of the two species, the following services could be maintained at current levels: Wild animals for food, particularly invertebrate species such as bivalves and some crab species. The abundance of bivalves can be affected by both species but filter feeding bivalves are important contributors to bioremediation of waste (Broszeit et al. 2016). The element of bioremediation of waste carried out by filter feeding bivalves will be maintained because bivalves will not be reduced by the two IAS. The service of gene pool protection is defined as the contribution of the marine habitats to the maintenance of viable gene pools through evolutionary processes enhancing adaptability of species to environmental change (Hattam et al. 2015a). Biogenic reefs, such as mussel beds, are important shelter areas for several species; as nursery areas and for food and functioning. Biogenic reefs contribute to biodiversity and gene pool protection by providing this service (Palomo et al. 2007). Gene pool protection will remain, particularly for species that use biogenic reefs such as mussel beds for shelter. The service of biological checks and balances, defined as the contribution of marine ecosystems to the maintenance of population dynamics, disease and

135 Deliverable 2.1 Report on impacts on net socio-economic benefits of achieving GES and consequences of monitoring n pest control (Hattam et al. 2015a) will remain as filter feeders will continue to remove pests such as harmful algal blooms and pathogens such as E. coli from the water column. To be able to measure and monitor such changes in case these two species establish themselves in the ECMP area, a list of indicators for each of the services and benefits has been prepared (Table 5.18).

The following ecosystem benefits will be maintained if these two species remain outside of the ECMP area: food provision, particularly of such species that serve as prey to the two species: several species of bivalves, some crustaceans and gastropods, however, R. venosa has been sold as food to some markets (Katsanevakis et al. 2014). Biotic raw materials may be provided by the shells of R. venosa that can be sold to tourists (Katsanevakis et al. 2014). Leisure and recreation may be affected in two ways: without the NIS (Non-Indigenous Species) present, filter feeding may remain at current levels (no other potential impacts such as climate change were considered for this analysis) meaning that bathing water quality remains at current levels and tourists coming to see sea birds attract revenue locally. Abundance of sea birds remains at current levels (again excluding other potentially negative changes to bird abundance) if their invertebrate prey are not removed by the two IAS (assuming bottom-up control of this feeding relationship (Kendall et al. 2004).

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Table 5.18. Example indicators for ecosystem services and/or benefits. For each status, service or benefit between one and three indicators were found. These indicators need baseline (before invasion) data. MSFD: Indicator taken from DEVOTOOL, Maes: taken from Maes et al. (2016), all other indicators taken from Hattam et al. (2015a) and Atkins et al. (2015). NIS: Non-Indigenous Species Status, service, benefit Indicator 1 Indicator 2 Indicator 3 Biodiversity Abundance or biomass of species Species diversity (diversity indices) (number per area) NIS abundance Spatial distribution of non- Trends in the arrival of new invasive species Trends in the abundance of settled (new species) indigenous species (mapping) (numbers as compared to a baseline) invasive species (change in the Status (DEVOTOOL) (DEVOTOOL) abundance of settled invasive species) (DEVOTOOL) Food web dynamics Changes over time in community Species diversity (diversity indices) Population dynamics (age class, composition (abundance/biomass) male: female ratios) Harmful algal blooms (due to Presence/absence of HABs (per area or volume) lack of filter feeders) Wild animals for food Biomass of shellfish (g, kg) Abundance of fish or shellfish (number) Quality of shellfish Biotic raw materials Presence/absence of desirable species Quantity (weight per area)/quality of raw (per area) materials (unit depending on material) Services Bioremediation of waste Presence/absence of pathogens Total dissolved solids (quantity per volume Number of shellfish area closures (quanity per volume seawater) seawater) (per area per year) Gene pool protection Presence/absence of desirable species Genetic diversity of desirable species and Biodiversity Intactness Index (per area) subspecies (diversity indices) Biological checks and Presence/absence of pests/NIS (per Quality and quantity of pest control species Presence/absence of HABs (per balances area) (suitable predator of IAS, health, abundance) area or volume) Food provision Fisheries revenues and Nutrition from seafood consumption (g Shellfish landed for human consumption contribution to Gross protein per year) (tonnes) Value Added (GVA) (£) Ornamentals and aquaria Ornamental use (weight) by type Benefits Aesthetic experience Number and/or area of marine features of given stated appreciation Leisure and recreation Water quality indicators, blue flag Area of biotopes of key interest to Abundance of sea birds of beach guide recreational users (size, distribution) recreational interest (abundance per area)

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Scenario selection

It is difficult to predict the potential impacts of IAS in an uninvaded environment (Kulhanek et al. 2011). Therefore, scenarios may be a good tool to evaluate future pathways of impacts as an alternative approach (Pereira et al. 2010) to estimate costs and benefits of ballast water management. For this study we selected two scenarios to demonstrate extreme situations while it is anticipated that a likely future lies somewhere in between. They are defined as:

 High impact of the two invasive species on ecosystems and provision of relevant ecosystem services

 Low impact of the two invasive species on ecosystems and provision of relevant ecosystem services.

Impact is defined here as expected ecosystem damage. High and low impact was chosen in the face of uncertainty with respect to a number of assumptions explained below. In response to these scenarios, different management actions are possible. For this exercise we look at (1) no additional management and (2) management necessary to achieve GES, which in the case of invasive species is ballast water management. As a combination of possible scenarios and management responses, three outcomes are expected (Table 5.19).

Table 5.19. Scenarios of impacts of invasive species and management responses (BWM: Ballast water management) Management response

No MSFD management (additional) MSFD Environmental scenarios (current management management (BWM) measures continue)

Outcome 1 Outcome 2 Low impact Limited expected damage GES (no expected impact)

Outcome 3 Outcome 4 High impact Large expected damage GES (no expected impact)

It should be noted that in theory and by definition in the Directive, any measure that is implemented will lead to the achievement of GES. For Descriptor D2, the relevant target for the UK is defined as “reduction in the risk of introduction of non-native species through improved management of the main pathways / vectors” (Anon 2012, p. 53). Therefore, the outcomes in the right-hand column of Table 5.19 are the same. While theoretically there might be a difference between scenarios in terms of the costs of their implementation, in the case of BWM implementation cost will be the same in

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both scenarios. Generally in a CBA of this kind, the benefits of taking measures to achieve GES (i.e. BWM) are the damages avoided, which are dependent on the assumed level of impact in the scenarios. Therefore, the benefits of reaching GES targets are likely to differ between the high and low impact scenarios, with the former being larger due to the bigger change from high impact to GES.

Description of scenarios

Due to the fact that the two IAS are not present in the ECMP area, assumptions are made to characterise the two environmental scenarios. Table 5.20 lists a number of species or habitats that are likely to be affected by the introduction of R. venosa or H. sanguineus. According to the two- scenario approach, for each aspect two extreme scenarios, LIAS and HIAS, are characterised.

The scenarios for high and low impacts assume both species appear in the ECMP area at the same time. Due to their current absence from the ECMP area, current data can be used for the scenario of GES and the high and low scenarios were deducted as percentage changes from the current status.

Table 5.20. Overview of exemplary assumptions in the scenarios for Invasive Alien Species. BWTS: Ballast water treatment system Assumptions

Environmental Fisheries Seabirds Water Gene pool BWTS costs scenario quality protection

퐼퐴푆 퐼퐴푆 퐼퐴푆 퐼퐴푆 퐼퐴푆 Low impact 퐿1 퐿2 퐿3 퐿4 퐿5

퐼퐴푆 퐼퐴푆 퐼퐴푆 퐼퐴푆 퐼퐴푆 High impact 퐻1 퐻2 퐻3 퐻4 퐻5

To assess the impacts of R. venosa and H. sanguineus in the ECMP area, a number of assumptions for the low and high impact scenarios have to be made. The levels of some impacts were set using low and high impact definitions by Ojaveer et al. (2015). Examples are the following:

퐼퐴푆 퐿1 : In the low impact scenario, this impact is assumed to be a reduction of catches of commercial species of shellfish by 10%, with a gradual lead in time of three years. These species are: Scallops (Pecten maximus), queen scallops (Aequipecten opercularis), cockles (Cerastoderma edule), clams (Mya arenaria, mercenaria mercenaria), razor clams (Ensis ensis, Ensis arcuatus and Ensis siliqua), oysters (Ostrea edulis), mussels (Mytilus sp), brown crabs (Cancer pagurus), green shore crabs (Carcinus maenas), velvet swimmers (Necora puber) and pink shrimps (Pandalus montagui)

퐼퐴푆 퐻1 : If the two species are introduced into the ECMP area, their effect on the catches of the above species list will be a reduction of 70%, with a gradual lead in time of three years.

퐼퐴푆 퐿2 : Bird abundance for the service of leisure and recreation: <10%

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퐼퐴푆 퐻2 : Bird abundance for the service of leisure and recreation: 40 %

퐼퐴푆 퐿3 : Water quality on beaches (through reduced bioremediation of waste): <10 %

퐼퐴푆 퐻3 : Water quality on beaches (through reduced bioremediation of waste): <70 % Gene pool protection will be difficult to quantify in the absence of good baseline data. We would need to know more about the species that inhabit mussel beds and reefs that might be lost or drastically reduced in the presence of the two IAS.

퐼퐴푆 퐿4 : not specified

퐼퐴푆 퐻3 : not specified When it comes to the costs of installing and operating ballast water treatment systems on vessels going in and out of the ECMP area, the following assumptions are made: (1) All container ships and tankers and 30% of passenger vessels come from high seas (e.g. Asia); (2) 10% of the total operating costs of BWTS is attributed to the case ECMP area; and (3) any type of vessel enters the ECMP area from an intercontinental origin five times per year on average. In the low and high impact scenarios, the assumptions with respect to the future development of shipping traffic are:

퐼퐴푆 퐿5 : Intercontinental shipping traffic in and out of the ECMP area will decrease by 10% compared to average annual arrivals for 2011 to 2014.

퐼퐴푆 퐻5 : Intercontinental shipping traffic in and out of the ECMP area will increase by 25% compared to average annual arrivals for 2011 to 2014.

While for some services and benefits such as food provision this was comparably straight forward, the effect of the IAS on other services was more indirect such as the effect of prey reduction on seabirds and the associated loss in revenue due to reduced numbers of bird watchers. Due to the difficulty in predicting impacts of IAS on naïve habitats this use of scenarios seemed the most pragmatic way to deal with the large associated uncertainty. Particularly for birds the effect of reduced prey does not necessarily lead to reduced revenue. However, in an example from the Dutch Wadden Sea a reduction in prey led to reductions in some of the bird species (Beukema 1993). In this instance, a severe winter and simultaneous continuation of an intensive fishery for mussels (Mytilus edulis) and cockles (Cerastoderma edule) led to a reduction in the abundance of both species due to a succession in recruitment failures over three years. These two bivalve species are important prey items for seabirds, particularly oystercatchers (Haematopus ostralegus) and eider duck (Somateria mollissima). Table 5.21 displays potential impacts of R. venosa and H.sanguineus on a number of ecosystem benefits.

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Table 5.21. Predicted effects of introduction of Rapana venosa and Hemigrapsus sanguineus on ecosystem services and benefits

Policy Options Outcome 1 Outcome 2 Outcome 3 Outcome 4

Low impact; no additional Low impact; MSFD High impact; no High impact; MSFD Description management measures management measures management measures management measures implemented implemented implemented implemented Wild animals for food - 0 -- 0

Biotic raw materials + 0 + 0

Ecosystem Bioremediation of waste Services - 0 -- 0

Gene pool protection - 0 -- 0

Biological checks and balances - 0 -- 0

Food provision - 0 -- 0

Ornamentals and aquaria + 0 + 0 Benefits Aesthetic experience - 0 -- 0

Leisure and recreation - 0 -- 0 Key: ++ Potential significant positive effect; + Potential positive effect; 0 Negligible effect; − Potential negative effect; −− Potential significant negative effect.

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Quantification of costs and benefits of management measures Costs For the purpose of the analysis and due to available data, the focus here is on the cost to businesses or industry of complying with the management measure. It is recognised that other costs, e.g. cost of implementation, will be incurred but these are not estimated here. The costs to industry are presented as present value of costs up to 2020, using a discount rate of 3.5% as recommended in the UK’s HM Treasury Green Book (HM Treasury 2015). Costs are presented in present value terms so that they can be compared with benefits that may be incurred at a different time period. The MSFD requires GES to be achieved by 2020, but the assessment covers a longer time period as both costs and benefits will be incurred as long as the management measure is in place.

The Ballast Water Management Convention does not order the use of specific ballast water management systems but it provides guidelines to ensure the uniform implementation of ballast water management, including a list of systems that are approved by countries that have signed on to the Convention11. The most effective way to avoid the arrival of IAS is the installation of ballast water treatment systems in seagoing vessels (Fernandes et al. 2016). However, for this to be effective, it is important that there is a high degree of compliance and monitoring and other measures to address IAS introductions from other pathways (e.g. leisure boating) also need to be in place. The cost of ballast water treatment depends on the particular technology used. For the UK case study, we are assuming that the technologies examined in Fernandes et al (2016) will be used by vessels travelling along the East Coast of the UK. Based on 퐼퐴푆 퐼퐴푆 assumptions 퐿5 and 퐻5 , and additional assumptions regarding shipping traffic in the ECMP area, the total discounted cost up to 2020 of installing and operating ballast water treatment systems of all relevant vessels in that area ranges between £2,420m and £3,143m, following a change in intercontinental traffic into the area of -10% and +25%, respectively.

It is worth highlighting that the UK Government is taking a risk-based approach to the monitoring and management of Descriptor 2 and that currently, it doesn’t envisage additional management measures for this Descriptor (Defra 2015).

Benefits Benefits can be assessed through ecosystem service and benefit categories, as indicated above; either due to the improvement in ecosystem service provision or, predominantly in the case of IAS, the avoided loss of the ecosystem service provision.

However, benefits are not limited to the change in ecosystem service provision. Indirect benefits can include any avoided costs (e.g. to industry or local communities) of having to correct or minimise adverse impacts. For example, the eradication of the invasive and non-indigenous carpet sea squirt Didemnum

11http://www.imo.org/en/OurWork/Environment/BallastWaterManagement/Documents/Table%20of%20BA%20FA% 20TA%20updated%20April%202016.pdf

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vexillum in Holyhead Marina in Wales was estimated to cost £120,000 per eradication attempt12 (Kleeman 2009). If this cost is avoided due to the implementation of a measure which stopped or minimised the risk of introduction of the species, then this can be considered an indirect benefit of that particular measure. This means that the benefit of the measure is a combination of the avoided loss of ecosystem service provision (direct benefit) and the avoided cost of having to address the issue at a latter (and potentially more problematic) stage (indirect benefit). Consideration of this indirect benefit also allows for the identification of the more cost-effective means of addressing a problem. In the case of the carpet sea squirt example, a decision maker can compare the present value costs of implementing something now (e.g. to avoid introduction of the species) with the present value cost of having to deal with the problem in the future (e.g. eradication).

As with the cost of the management measures, it is important to focus on the additional benefits; i.e. what is the marginal change in the quantity and value of the benefits relative to what is present under a scenario without the management measure. However, in the case of ecosystem services and benefits, this has proved to be challenging mainly due to the uncertainties regarding determining how the marginal change in ecosystem service provision relates to a marginal change in ecosystem state arising from the introduction of the measure. The economic valuation of the benefits of management measures does not necessarily require new studies to estimate these benefits since using benefit estimates from existing studies with a similar context (i.e. benefit transfer) is acceptable practice in ecosystem service valuation or CBA (Richardson et al. 2015). However, without knowing the marginal change in ecosystem service provision, it is difficult to apply these values with any degree of confidence. It is also possible that the direction of change of the economic value of the benefit is not the same as the direction of change of the ecosystem service provision. The practice of assigning economic values to ecosystem services is inherently anthropocentric therefore several benefit values (e.g. those that are measured by willingness to pay) are based on human perceptions. Due to limited human knowledge and understanding of the features and functioning of marine and coastal ecosystems, individuals are not always able to see how an improvement in biodiversity or in species populations could affect them. Alternatively, it is possible that at a particular threshold, economic values for a good or service no longer change proportionately with the change in the amount of the good or service due to diminishing returns.

Discussion

The collation of noise sources and their associated management measures in Table 5.9 highlighted the range of options available for mitigation. However, in many cases the effectiveness of such measures is not well understood - for example key references are included within the table, but in general there were few peer-reviewed papers regarding the listed sources. Furthermore, whilst a range of solutions exist, these are not all fully developed at present - for example bubble curtains are in the testing stage, and to the authors knowledge currently there are no industry-standard products available that developers could use. However, even if they were available, due to the wide range of noise producing scenarios, even within source-type categories, there can be no one-size-fits-all solution. In the case of bubble curtains for

12 Labour and materials only; given the size of the marina, the technique used and the degree of the problem.

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example, one device may be successful in shallow, low velocity water currents, but would not be effective in deeper waters with higher current speeds. Similarly, the same bubble curtain may reduce the noise in one pile driving scenario, but not in another due to variations in piling operations, and environmental conditions. Some mitigation measures are also simply not possible, such as reducing the number of piles used, or the diameter of piles used may not be practical to the construction or the area of development.

Whilst a range of mitigation measures exist, in many cases the effects of unmitigated noise upon fish, invertebrate and marine mammal species are largely unknown, as shown in Table 5.10 leading to conclusions drawn from few data. For example in the case of ECMP area species, studies have concentrated upon behavioural effects rather than physiological or physical damage, and many are solely laboratory based. Within this species set it was necessary to group species together to find relevant studies, since it was not always possible to find species-specific papers. Table 5.10 highlights the imbalance between fish, invertebrates and marine mammals, with the latter receiving more research attention in general. However there are many more species of fish compared to marine mammals, with a more diverse range of sensory structures and lifestyle strategies so this cannot be fully attributed to lack of interest. For many species there is a predominance of laboratory experiments rather than field experiments, which face technical complexities, but field experiments face other difficulties such as the practicalities of marine field work. Despite this, Table 5.10 illustrates that noise (as a whole) is likely to affect anti-predator behaviour, foraging, reproduction, and cause physiological changes such as production of stress proteins. Such effects are likely to be of greater consequence than physical damage alone, which is likely to affect fewer animals (e.g. those closer to source) - but may cause large-scale problems such as stranding which appear to involve physical damage and also behavioural change. In all cases, the challenge is to scale-up individual level effects to population level, which would be of most use to managers and developers, and for biological data to catch up with the rapid rate of technological development seen in offshore marine activities. One way to do this would be to use an individual-based modelling approach (Rossington et al. 2013, Willis 2011), where movements of animals are defined by rules that can be scaled up to whole populations - however such approaches require empirical data.

Since the impacts of unmitigated noise are not well understood, the effectiveness of mitigated noise sources is also difficult to understand, as more data are required. Yet the costs of mitigating sources are high to the developer, for example real time detection of marine mammals requires two marine mammal observers, specialist equipment and sometimes additional vessels- estimated at £1,000 per day (Gordon et al. 2007), with the risk of animals going undetected being up to 50% in some cases. Hence the implementation of measures is costly but may not always be effective. On the other hand the development of other techniques such as the use of acoustic deterrents may reduce the cost - since these devices require only one untrained operator and it is not weather dependent, for example.

A range of indicators has been highlighted which accomplishes an important step when it comes to management of the impact of underwater noise on ecosystem service provision in the marine environment. While indicators can provide insight into the behaviour and state of coastal and marine ecosystems, together with an indication of the trajectory of change due to natural and human events, in this specific case knowledge of the direct impacts of underwater noise on ecosystem service provision is

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limited, and there was no site-specific evidence available. However, identification of indicators does provide some guidance on areas for future research effort.

Similar uncertainties were evident in the steps for ascertaining the impacts of IAS on the different ecosystem components and ecosystem services in ECMP, and the appropriate management measures to address them in terms of ballast water management systems. Uncertainties are compounded by the different context that preventative management of IAS is focussed on management measures to avoid potential reduction in ecological status rather maintaining or restoring it. Additionally, it is not possible to predict with certainty how an uninvaded ecosystem will react to a new IAS. This uncertainty is then exacerbated when assumptions are made about changes to services and benefits from changes in the ecosystem. For example, a reduction in bivalves may lead to a reduction in seabird abundance but this assumes a bottom-up regulation of the ecosystem (Kendall et al. 2004).

For each management issue four scenarios were developed to test the potential impact of MSFD management measures on the provision of ecosystem services and societal benefits. It is challenging to develop scenarios for managing underwater noise, given the broad range of types of noise emitted within the marine environment and the difficulty of differentiating between background noise levels and levels generated by marine-based activities such as construction and shipping. As such a number of assumptions were required to be made for the purposes of this assessment. This is also a reflection of the state of the research field where numerous ‘information gaps’ are present making the effects of noise difficult to investigate and understand (Hawkins et al. 2014). Based on the literature, shipping and wind farm construction associated noise were the two main sources of underwater noise identified for consideration – and these activities were grouped together for the purposes of the scenarios analysis. Given the absence of any underlying site specific evidence on underwater noise this was deemed an appropriate choice. Similarly in the highly competitive world of commercial shipping and ballast water treatment systems, and the evolving technology of the latter, it is difficult to obtain good data relating to costs of these systems.

The assessment of evidence suggests that a number of ecosystem services and benefits could be affected by the impacts of underwater noise in the marine environment and by IAS. Although there was a relatively good evidence base with respect to the key commercial fish and shellfish species and charismatic species with the ECMP area, there was no ECMP field data available on the potential impact on these species of underwater noise generated from shipping and wind farm construction. For IAS such data can only be inferred from similar scenarios and habitats elsewhere presenting further challenges. Even though current evidence is quite limited, this assessment demonstrates that underwater noise and IAS may impact upon the provision of a number of ecosystem services and this highlights areas for future research.

Recommendations

Given then diversity of ECMP area key species (and all species), biological mitigation techniques for underwater noise would ideally be species-specific. For example, seals do not vocalise, and are also difficult to spot at sea, hence visual and passive acoustics are not suitable detection methods; whereas porpoises do vocalise and hence PAM would be a useful technique.

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Mitigation measures should also be scenario specific, due to the variation of noise that anthropogenic activities can produce, the variation in propagation conditions, the possibility of other stressors and methodologies used in each construction scenario. There is no easy way to mitigate such a range of sounds, in a similar way as it is difficult to mitigate to protect all marine species - measures must be chosen and executed by carefully considering the particular scenario of the noise producing activity. Finally, in order for effective management to be achieved, more testing is required of mitigation measures to understand which are successful and are possible to deploy within construction scenarios. This includes further testing of the procedures currently in place in UK waters to understand if these are effective, and extension to other methodologies. It would also be valuable to thoroughly assess the cost to the developer of implementing mitigation, in relation to the effectiveness and to how implementation can be regulated. This must also extend to further empirical studies relating to the sensory abilities of marine species, and the impacts from individual to population level that noise may cause.

In this study, we concentrated on ballast water management because it is a very effective way of reducing the risk of IAS introductions. However, other measures should take place simultaneously for example reduction of hull fouling on ships. In addition, due to the high uncertainties related with the effects that IAS can have on ecosystems, it is imperative to keep updating information repositories, adding in new findings of their effects on ecosystems, as well as information on how to treat affected areas. Monitoring for such species can help preventing IAS from entering new areas. For example, H. sanguineus has been found in Kent and therefore regional managers in the ECMP should put effort into monitoring this species in the ECMP. In some cases early detection can help stopping an IAS from establishing itself in a naïve environment.

Using the ecosystem services approach helps to not only look at impacts in those sectors that are easily monetised, such as fisheries, but also those services that the ecosystem provides that are not as obvious. For example, negative changes to the level of bioremediation provided in an area may at first not be noticed but have knock-on effects on local tourism if water quality is reduced. Therefore, monitoring changes in the provision of ecosystem services may work as an early warning sign that other services and benefits may also suffer and become reduced over time.

To detect both, impacts of noise or presence and effects of IAS monitoring should be undertaken and this should include the use of indicators provided in Tables 5.5 and 5.12. This will allow the assessment of changes to the ecosystem, the services and benefits it provides and help to counter-act negative impacts of either noise or the IAS studied in this report by acting on negative changes in these indicators to avoid reduction in the provision of ecosystem services and wider benefits to society. This assessment has highlighted the requirement for further research in a number of areas, including the need for a greater understanding of the links between underwater noise or IAS and ecosystem service provision; a better understanding of the types of underwater noise generated by existing marine sectors, or

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possible IAS and how this may change in the future; and a better understanding of the impact of different IAS and of different management options, both individually and in combination, for mitigating the impacts of underwater noise.

5.5 Discussion

Challenges applying a CBA approach under the MSFD

While environmental CBA is an established analytical tool for the appraisal of environmental management measures (Boardman et al. 2006, Hanley and Barbier 2009), its application in the context of the MSFD and the marine environment in general is challenging. In all three case studies presented here there is limited ecological evidence available to support the analyses. The Finnish case study showed that by using expert elicitation a quantitative approach is possible and it included a wide range of management measures. Moreover, the Finnish approach could be extended to include an ecosystem service assessment. However, lack of data can (and did) result in a focus on only a limited number of ecosystem services which are more easily quantified.

A second and related challenge is the scarcity of valuation studies that focus specifically on benefits arising from changes in all or specific MSFD Descriptors.13 This challenge was highlighted by the limited use of existing valuation studies in the Finnish case and the total absence of such information that could be applied in the UK case study. Only the major cost components of the management measures in the UK study could be monetised. The effect on ecosystem benefits of reducing underwater noise and the likelihood of introducing IAS could only be established in a qualitative way. This is because of the uncertainty on the changes in ecosystem service provision following the implementation of the management measures and the absence of existing valuation studies focusing on these services. The Finnish study developed a pragmatic alternative for estimating the economic value of marine protection when applicable data are available and conducting extensive new valuation studies is not feasible. Even though the existing studies did not explicitly assess the benefits of achieving GES, the results are suitable for indicating the benefits from the PoMs. Even though the Finnish case study was largely funded as part of the national MSFD programme, existing results were used as time and other resource constraints prevented implementation of any new studies. The BoB case study highlighted the clear link between the investment (i.e. private and public costs) and ecosystem service benefits. However, important public costs attached to certain CFP-related management measures, cannot be split among each specific management measure, which may limit the application of a complete CBA.

Norton and Hynes (2014) used a stated preference survey to assess the non-market benefits of achieving GES in Ireland but such studies are rare.

13 Apart from the studies used in the Finnish case study and to the best of our knowledge, the only valuation studies relating directly to MSFD Descriptors is Norton and Hynes (2014).

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The third challenge in the context of practical MSFD implementation is the lack of public resources to conduct fit-for-purpose valuation studies. From a theoretical perspective, it is important in any type of valuation approach to focus on assessing additional benefits, i.e. what is the marginal change in the quantity and value of the benefits relative to what is present under a scenario without the management measure. However, in the case of ecosystem benefits, this has proven challenging due to the uncertainties regarding the marginal change in ecosystem service provision. The economic valuation of the benefits of management measures does not necessarily require new studies to estimate these benefits since using benefit estimates from existing studies with a similar context (i.e. benefit transfer) is acceptable practice in ecosystem service valuation or CBA (Richardson et al. 2015). However, without knowing the marginal change in ecosystem service provision, it is difficult to apply these values with any degree of confidence. It is also possible that the direction of change of the economic value of the benefit is not the same as the direction of change of the ecosystem service provision. The practice of assigning economic values to ecosystem services is inherently anthropocentric, and therefore benefit values (e.g. those that are measured by willingness to pay) are based on human perceptions. Due to limited human knowledge and understanding of the features and functioning of marine and coastal ecosystems, individuals are not always able to see how an improvement in biodiversity or in species populations could affect them (Duarte et al. 2000).

A final challenge indicated in the case studies, relates to comparing the present values of costs and benefits (Pearce 1998) for a specific period of time. The discount rate 훿 is crucial to make costs and benefits incurred at different points in time comparable in the present (equations 1 and 2). The discount rate reflects different levels of desirability between consumption and/or opportunity costs that occur at different points in time (Feldstein 1964), and it is also an expression of concern regarding the distributional equity between current and future generations and among future generations (Arrow et al. 1995). A positive discount rate means that future values countless and hence are ‘penalised’ and the higher the discount rate, the more future values are penalised. Depending on the discount rate used, benefits that are realised at a later point in time could have lower present values than the costs that are incurred once the measure is implemented affecting the overall outcome of the CBA. Furthermore, CBA’s for different management measure options may not be comparable if they have not used the same discount rates. The length of the time period, over which costs and benefits are assessed, also affects the total NPV as it determines the temporal extent of the costs and benefits that are considered in the assessment. The MSFD states that GES should be achieved by 2020, however, it does not provide guidance on the time period for assessing the impacts of implementing new management measures to achieve GES. If the assessment covers only the time period from 2016 (when new measures are expected to be implemented) up to 2020 (when GES is supposed to be achieved), the short time span and the impact of discounting on benefits that materialise at the later date mean that there is a risk that costs of implementing new management measures will most often outweigh the benefits. For issues such as changes in the environment, biodiversity or climate change, whose effects cover long periods of time, using a short time span for assessing the costs and benefits of any policy action is not ideal. The choice to take action on these issues is a direct recognition that long time spans will be involved and several generations will be affected (Stern 2006, HM Government 2011). This means that for the assessment to be meaningful, the time period of

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assessment needs to be realistic and long enough to take into account any lags in the response of the environment to the implementation of MSFD PoMs.

Opportunities for applying CBA under the MSFD

If the management measures under study impact a range of ecosystem services which cannot be easily quantified, the qualitative approach in the UK case shows how the focus can be kept broad so as not to overlook important impacts of the management measures under consideration. This demonstrates the trade-off between highly quantified CBAs which often only focus on a very narrow array of ecosystem services and the broad, but often not quantified approach taken in the UK case. For the latter, multi-criteria analysis (MCA) (Linkov et al. 2006) might be a potential way forward (DCLG 2009), as it can incorporate cost and benefit measures of different units (e.g. non-monetised ecosystem service changes). Further research to test the applicability of MCA in this context is needed.

A further opportunity relates to the fact that CBA allows for the examination of the trade-offs between different options to achieve GES within the parameters of economic efficiency (OECD 2006), taking into account other constraints (e.g. discount rate, time period of assessment) that are used in the analysis and how these affect the values that are calculated. Therefore, results of a CBA can help decision makers to examine trade-offs giving them the opportunity to develop a PoMs where the discounted net benefits

(PVB − PVC ) are maximised and which can effectively draw from existing policy actions already implemented to alleviate environmental pressures or even contribute to future policies. Additionally, sensitivity analyses which take into account different levels of the constraints (e.g. different discount rates, different time period for assessment) used can be done to show the variability of total costs and benefits in the face of different types of uncertainty.

’Lessons learnt’ during case study application of the CBA approaches under the MSFD

Finnish marine water, Baltic Sea

Existing bio-economic models were available for D2, D3 and D5 but the models would need to have been updated to be applicable in the MSFD contexts. Expert elicitation was a successful alternative approach (to modelling) that provided comprehensive analysis covering all descriptors. Benefit transfer was relatively straightforward to execute. Even though the original studies only partially covered GES descriptors, the estimated benefits were higher than the expected costs of the measures.

East coast marine plan area, UK

Scenarios analysis proved a useful tool in the context of a situation where there is considerable uncertainty concerning the links between management measures and the ecosystem the links to welfare impacts. Previous studies have demonstrated that scenarios can be used to ‘test’ which policy actions are robust and sustainable, however it is recognised that the big challenge for using scenario analysis is communicating findings to stakeholders and policy-makers effectively (Burdon et al. 2015). Lack and high uncertainty of

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data restricts the full application of a CBA. In particular there were insufficient site-specific data to assess the potential ecological impact of the management measures and to quantify and value any changes in ecosystem services and welfare benefits. As such, these two steps were only partially fulfilled precluding the completion of the CBA. In the context of high uncertainty about bio-physical and economic data on the impacts of a PoMs, the preliminary qualitative analysis undertaken in this case study proved valuable in identifying the main ecosystem services which may be affected under each management measure and thus identified areas for further site-specific research. An even deeper analysis such as a MCA could now be performed while waiting for reliable quantitative data to be made available.

Bay of Biscay, Spain

Many different economic maritime activities operate in the BoB. However, there has been little previous effort to develop any qualitative or quantitative assessment of impact (ecological or socio-economic) of those activities on the value of ecosystem services. One contributory reason for this, among others, is that the “partial” maritime nature of most of the sectors involved hinders extraction of the required data from the available statistics. Due to this limited knowledge only a few new measures could be proposed for application to the different private economic activities, with the exception of the commercial fishing sector, which is mainly affected by the newly reformed CFP. The capacity for providing both qualitative and quantitative assessments related to the BoB management measures resulting from the CFP relies on existing bio-economic models that have been developed and applied in other areas of Europe and that are flexible enough to be applied in the BoB. While such models are well developed for fishing activities, models that can be used for other maritime activities are still not sufficiently developed.

Conclusions and recommendations

By showcasing and discussing three CBA examples in the context of the EU MSFD, this report highlights challenges and opportunities for the use and further development of this technique in the impact assessment of PoMs. The six-step approach in Hanley and Barbier (2009) has been used as a structural framework to build an MSFD-specific CBA set in different contexts across Europe. Both expert elicitation and the ecosystem services approach are shown to facilitate Step 2. Challenges arise in Step 3, the economic valuation of these impacts. While the Finnish and Spanish case studies monetise both costs and benefits, the UK case study could only express implementation costs of measures in monetary terms. Application of the step-by-step process for CBA in contrasting case studies with differing levels of data availability has highlighted a number of issues. As such the following recommendations can be made:

(1) The CBA approach needs to be further developed to better integrate the ecosystem service approach with established environmental valuation techniques (Börger et al. 2014). To aid this, further research into the linkages between MSFD Descriptors and established ecosystem service classifications is required so that the specific CBA can then be linked to the suitable Descriptor via the affected ecosystem services. This would also help mitigate problems of adjusting existing valuation estimates to situations with slightly different types of environmental change, geographic area or time horizon. However, for pressure indicators

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(e.g. D5 eutrophication) where existing valuation studies already show a reduction in ecological indicators and associated reduced economical values, an ecosystem service approach might be circumvented. In such cases it might be easier to link the existing value estimates directly to the Descriptors and assess the ecosystem services separately.

(2) The use of cost-effectiveness analysis is recommended where the measurement of benefits within an environmental CBA is difficult as demonstrated in the first step of the Finnish case study and supported by the European Commissions’ DG-Environment (2015) who state “CEA [cost-effectiveness analysis] is used when measurement of benefits in monetary terms is difficult” (p. 9). According to the EC Impact Assessment Guidelines, a CBA can be done at various levels, depending on data availability. It can be either a full CBA when the most significant parts of both costs and benefits can be monetised utilising economic values derived through various economic techniques or a partial CBA in cases where only a part of the costs and benefits can be quantified and/or monetised (DG-Environment 2015, p. 9).

(3) Another alternative approach that has potential for application in MSFD is to use multi-criteria analysis (MCA) in the impact assessment when quantification or monetisation are not possible or when impacts are measured in different units (e.g. monetary vs. physical) and have to be compared. The above case studies, the UK case in particular, highlight how information about environmental change in terms of ecosystem services can be developed for use in MCA. This approach can be accompanied by expert elicitation.

(4) Finally, the use of modelling is recommended where appropriate bio-economic and ecosystem models already exist and there is sufficient data to parameterise them, or where there is sufficient data available to construct new models. For example, if management measures affect ecosystem services for which sufficient data are available as demonstrated in the Spanish case study, bio-economic modelling can provide cost and benefit estimates which can feed into the CBA process. Modelling is also a valuable tool for projecting potential changes in ecosystems service provision in the future where real-time data is not available.

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6. Conclusions

Various approaches and methodologies have been developed to analyse cost-effectiveness of monitoring under MSFD. These have been partially tested through application to case studies raising various challenges, particularly regarding availability of appropriate monitoring costs data at the right level of granularity, and resources to undertake such analyses. Further testing and application is now needed to develop and improve the methods and approaches. Better monitoring of the costs of monitoring programmes will be required to take these approaches forward. For all the case studies there is potential for improvements in the effectiveness of existing monitoring programmes with respect to the MSFD requirements. However, an increase in the effectiveness in respect to MSFD may lead to a decrease in the applicability of the data sets for other environmental monitoring purposes.

Similarly approaches for undertaking environmental CBA in relation to PoMs for MSFD have been developed and tested in case studies. Application of the approaches was challenging. Ecological evidence on the impacts of measures is required that could be obtained through modelling studies and monitoring and analysis of data from other sites where similar measures have already been implemented. Further research into the linkages between MSFD Descriptors and established ecosystem service classifications is required so that the specific CBA can then be linked to the suitable Descriptor via the affected ecosystem services. Valuation data is needed for benefits that could arise from changes in MSFD descriptors – this requires new valuation studies specifically aiming at the marine ecosystem services and benefits across European regional seas. Further economic work is required regarding public costs of MSFD and how they can be attributed among the benefits. Another area that needs more focus is consideration of the appropriate discount rates for environmental CBA generally and MSFD specifically to take into account any lags in the response of the environment to the implementation of MSFD PoMs. Future application of MCA as an alternative to CBA should be investigated further as a technique that could be used where (especially valuation) data is heterogeneous. MCA and CBA combined with sensitivity analyses have significant potential to inform on the trade-offs of implementing different management measures to achieve GES. Bio- economic models that can inform CBA of POMs are well developed for fishing activities, but models that can be used for benefits from other maritime activities still need to be developed.

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8. Annex - National biodiversity monitoring and its costs in the Gulf of Finland in the Gulf of Finland

Biodiversity monitoring programme for marine mammals The only marine mammals present in the Gulf of Finland are seals; the grey seal and the ringed seal. Two monitoring sub-programmes have been established to assess the status of the seal populations, covering the abundance of seals and health status of seals. Harbour porpoise is only coincidentally observed in Finnish waters and no regular monitoring of the species is done, but the observations are collected and added to the Baltic-wide database.

Sub-programme Abundance of seals The aim with the monitoring is to follow the seal population sizes and reproduction success, to be able to detect changes in these. To assess the abundance of seals, three indicators have been defined in the Finnish monitoring programme:

 Distribution of seals  Abundance of grey seal and ringed seal and population development  Number of grey seal pups

Methods and costs The grey seal is monitored in May-June during its moulting season when the seals are gathering at their moulting locations. Abundance of seals is monitored by surveillance flights covering all known and potential moulting locations in the outer archipelago zone. All found seal gatherings are photographed and the numbers of individuals are later counted from the pictures. The aerial surveys are operated during a two week period that is agreed among the neighbouring countries to avoid calculating the same individuals twice. In Finland, there are two separate counting groups: the Gulf of Finland and Archipelago Sea are monitored by one group and the Gulf of Bothnia by another. During the surveillance flights, the plane holds a pilot (from the flight service provider), photographer and bookkeeper (researchers from the monitoring institute). Grey seal pups are counted around ca 50 islets in the outer parts of the Archipelago Sea during two surveillance flights in February-March. All islets are photographed and the pups are counted from the photographs. The seal pup monitoring is usually performed in combination with the Finnish Border Guard’s surveillance flights. The ringed seal is monitored in April within the fast sea ice zone, which varies yearly. In the southern areas the monitoring is not always possible depending on the sea ice situation. Seals are counted along the flight route, or from photographs of larger gatherings, and the results are later extrapolated to cover the total sea ice area.

The overall costs of the seal monitoring programme in the Finnish Game and Fisheries Research Institute (nowadays Natural Resources Institute Finland) were 107 488 euros, and took 0.66 person years (in 2012). The grey seal monitoring flights take about 7 days during which the total flying time is around 40 hours. The

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plane and pilot are bought from a service provider through a tender. Depending on the plane type, the costs vary around 650–950 €/h + VAT. The total cost for the plane is thus 26 000–38 000 euros + VAT. In addition, the accommodation and travel costs for the pilot are covered. Also the researchers travel and accommodate in the monitoring location. During the flights, a camera is needed, which costs around 1500€, and back up cameras also need to be accounted for. The counting of the grey seals from the photographs takes a couple of months of researcher time (among other work). The reporting of the results, which includes a press release and a statement for the ministry, takes 1-2 days for the researcher. The results from all Baltic Sea countries doing seal monitoring are put together in a yearly HELCOM Seal meeting, for which an additional 2-3 days of researcher time need to be accounted.

Table 8.1 Yearly costs of the sub-programme for abundance of seals. Type of expenditure Resource needs Aerial surveys -grey seal monitoring 39 680 € (average incl. VAT) -ringed seal monitoring 6 510 € (average incl. VAT) Equipment 3000 € Personnel costs 0.66 man-years Total costs (2012) 107 488 €

Sub-programme Health of seals Indicators The aim of the monitoring is to follow age and gender distribution, reproduction success and health status of the seal populations. Two indicators are defined for determining the health status of seals:  Pregnancy rate of seals  Blubber thickness of grey seal and ringed seal

Methods and costs Data for the indicators representing the health status of seals are collected from hunted seal individuals, as well as seals caught as by-catch by fishermen. The hunting season of grey seal is 16th April – 31st December, and the hunters send samples to the researchers. The needed samples are jaws and genitals, and occasionally some other organs. The hunter measures the blubber thickness, which tells about fitness of the seal, and also the weight and height and sends the information to the researchers. Traditionally, the hunters have sent the samples and information voluntarily, but now a small budget is reserved for compensations to the hunters. Jaws are used for determining the age of the seal from the growth rings of

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the canine tooth. Sex is determined from the genitals, and for females it is checked whether they have been pregnant or not. Also possible malformations (sometimes caused by hazardous substances) are checked. Around 70–150 grey seal samples are received yearly. Concerning ringed seal, too few samples are received for reliable determination of health status.

Total costs for this monitoring programme were 70 224 euros and occupied 0.64 man-years in the Finnish Game and Fisheries Research Institute. Two researchers are needed to work for a few days a year: one to prepare the tooth samples for age determination and another to do the research. HELCOM does monitor the health status, which is determined from the samples of one or more years, but no yearly report is written.

Table 8.2 Yearly costs for the Health of seals sub-programme. Type of expenditure Resource needs Man years 0.64 man-years Total costs 70 224 €

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Abundance of seals

No Is monitoring performed Order from consultant by institute?

Yes

Planning of monitoring

Using satellite photos Travel to RV (plane) (?) (Turku, Vaasa or Helsinki)

Perform surveillance flight(s) (taking photos of perceived seals)

Travel back to office

Analyze photos

Write report

Figure 8.1 Process chart for assessing the abundance of seals monitoring scheme.

Biodiversity monitoring programme for birds The monitoring of birds is divided to five sub-programmes which produce information on the breeding population sizes and distribution of archipelagic birds, amount and distribution of wintering waterbirds, observations of mass mortality of sea birds, breeding success of white-tailed eagle as well as numbers of hunted seabirds. A large part of the bird monitoring work is based on voluntary monitoring by bird enthusiasts.

Sub-programme Archipelagic birds Indicators

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Monitoring of archipelagic birds aims at gathering information on changes in abundance and distribution of breeding waterbirds. In total 31 bird species are monitored and data is produced for the following indicators:  Abundance of breeding seabirds  Distribution of breeding seabirds  Number of species in Favourable Conservation Status according to the Habitats and Birds Directives  Number of threatened marine species

Methods and costs Abundance of archipelagic seabirds is mainly monitored by counting the number of nesting pairs in permanent monitoring areas. In total 43 areas are monitored in Finland, of which 20-30 are counted yearly and all at least every third year. Twelve of these monitoring areas are located in the Gulf of Finland. In addition, the population size of the great cormorant and barnacle goose is more intensively monitored.

The costs for monitoring of the archipelagic bird populations at Finnish Environment Institute are around 17 500 €, of which around 1 500 € is paid as compensations for voluntary work. The monitoring of great cormorant and barnacle goose population sizes are around 50 000 € per year. A total of approximately 1.1 man years are needed for the bird monitoring at Finnish Environment Institute. Archipelagic bird monitoring at the former Finnish Game and Fisheries Institute (nowadays Natural Resources Institute Finland), were 86 305 € and occupied 1.13 man years. In addition, Metsähallitus also performs bird monitoring in the archipelago for which approximately 10 000 € is used yearly. Thus the total costs for monitoring of archipelagic birds in Finland is around 163 805 €, and of this approximately 49 500 € is used in the Gulf of Finland.

Sub-programme Wintering waterbirds Indicators The aim is to monitor the abundance of wintering waterbirds in the Finnish sea areas as part of the Baltic- wide monitoring of wintering waterbirds. The monitoring is concentrated along the coast and the sea ice situation influences the distribution of the birds. The sub-programme delivers data to the following indicators:  Abundance of wintering seabirds  Distribution of wintering seabirds

Methods and costs Abundances of waterbirds are counted along predefined routes. In total 102 routes along the whole Finnish coastline are monitored yearly. Of these, 30 routes are located in the Gulf of Finland. Most of the routes are counted on a voluntary basis by bird enthusiasts, coordinated by the Finnish Museum of Natural History, and thus the costs for this sub-programme were not estimated.

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Sub-programme Mass mortalities of seabirds Indicators The aim with the monitoring is to detect mass mortalities of seabirds and to investigate the reasons causing the mass mortalities. This sub-programme produces information for the indicator:  Occurrence of mass mortalities of guillemots and razorbills

Methods and costs The information on mass mortalities of seabirds is collected from many sources. Observations are mainly collected in connection with other monitoring activities or reported by the public. The frequency of mass mortalities is recorded as well as the number of affected birds.

There are no direct costs connected with the collection of data as the information is gathered in connection with other monitoring or reported by the public.

Sub-programme Breeding success of white-tailed eagle Indicators The monitoring follows the breeding success of the white-tailed eagle along the Finnish coast. As an apex predator persistent hazardous substances accumulate in the eagle, affecting its breeding success. In the sub-programme, data is collected for assessing the indicator:  White-tailed eagle reproductive capacity

Methods and costs The number of white-tailed eagle territories and the number of eagle chicks per territory are counted. Nests are visited once per year and chicks are ringed. The monitoring of white-tailed eagle has been quite comprehensive covering most of the white-tailed eagle territories. Monitoring costs were estimated to be

Sub-programme Hunting catch Indicators The monitoring of hunting catches aims at quantifying the direct pressure on the hunted game populations. The sub-programme collects information for the following indicator:  Number of game animals killed

Methods and costs The data for the indicator is collected by questionnaires sent to the hunters. For game requiring permits, like seals, the data is collected directly according to the used permits. As the questionnaire does not specify if birds are hunted at sea or inland, the only species that can be properly monitored regarding the management of the marine areas are long-tailed duck, eider duck, and grey-lag goose. The costs have been approximately 26 200 €/year occupying 0.12 man-years.

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Biodiversity monitoring programme for fish The fish biodiversity monitoring programme is divided into three sub-programmes: whitefish, sea trout and coastal fish populations. Partly the monitoring is carried out in rivers, where numbers of spawning anadromous fish are monitored. Whitefish is only monitored in the Bothnian Bay and thus not treated here. Monitoring of fish populations is also carried out under the monitoring programme for commercially exploited fish stocks, where monitoring is aimed at keeping the commercial fish stocks at a sustainable level, thus not suited for biodiversity assessments apart from the data collected on salmon in the Gulf of Bothnia.

Sub-programme Sea trout Indicators The aim with the monitoring is to follow the natural juvenile production of sea trout in the spawning rivers as well as to estimate the fishing pressure on different size classes using tagged individuals of sea trout. The following indicators get data from the sub-programme:

 Juvenile production of sea trout in relation to the river-specific potential  Fishing mortality in different sea trout size classes

Methods and costs The number of juvenile sea trout in the rivers is estimated through electrofishing predefined sampling areas. As well, the numbers of juvenile sea trout migrating to the sea and adult sea trout returning to the spawning rivers are estimated. To estimate the fishing mortality of sea trout, juvenile sea trout migrating to the sea are tagged and when caught, the fishermen return the tags to the research institute. The costs for the sea trout sub-programme have been 122 000 €/year requiring 1.3 man-years.

Sub-programme Coastal fish populations Indicators The aim with the sub-programme is to monitor the coastal fish populations. Especially, the abundance of cyprinids is monitored as an indicator of changes in the food web. The monitoring of coastal fish population is still under development and no finalized indicators are yet in use. However, a proposed indicator “Abundance of cyprinids in coastal waters” is under development.

Methods and costs The coastal fish populations are sampled with monitoring fishnets, in which several mesh sizes are combined in order to effectively sample the full size spectra of fish. At present, there is only three sampling areas in Finland, of which two are located in the Gulf of Finland. At each sampling area 30-40 predefined sites are fished with one net per year. Yearly costs for monitoring of coastal fish populations have been around 77 000 € and requiring 0.7 man-years.

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Biodiversity monitoring programme for benthic habitats Monitoring of benthic habitats is divided in four sub-programmes, of which two are focusing on soft bottom habitats in open sea and coastal areas, respectively. Hard bottom habitats are monitored in the “Macroalgae and blue mussel communities” sub-programme. A sub-programme “Physical loss and damage of the sea-floor” focuses on pressures on the benthic habitats.

Sub-programme Open sea soft bottom habitats Indicators The aim with the monitoring is to follow the condition of the open sea soft bottom benthic macrofauna communities in terms of species richness and size distribution of long lived species. Two indicators, which both utilises same samples, get data through this sub-programme:

 Species richness index of offshore benthic soft-bottom fauna  Size structure of long-lived macrobenthic species

Methods and costs The process chart describing this monitoring activity is depicted in ¡Error! No se encuentra el origen de la referencia.Figure 8.1. Sampling is done onboard R/V Aranda following the HELCOM COMBINE manual (http://www.helcom.fi/action-areas/monitoring-and-assessment/manuals-and-guidelines/combine- manual), where replicate sediment samples are taken using a 0.1 m2 Van Veen grab. The samples are sieved and preserved, and transported to laboratory to be analysed with a stereomicroscope. In the laboratory, all specimens are determined to lowest possible taxonomic level, usually species level. Abundance and biomass are determined for each species and additional size measurements are done for bivalves and crustaceans. In total, around 45 stations in the northern Baltic Sea are sampled yearly. Of these, ten stations are located in the Gulf of Finland. The number of sampled sites per year varies depending on the sampling route. In addition to the biological samples, a CTD cast is taken at each station and the near- bottom oxygen levels are measured. Information about the sediment characteristics and presence of hydrogen sulfide is recorded.

The labour need for the sampling campaign add to a total of four persons working in two shifts. Analyses of the collected samples in the laboratory occupy one person year-round. A senior researcher responsible for the monitoring takes care of planning the sampling as well as data management, including quality check, and reporting together with the researcher. The costs of Aranda are well known, but it is more difficult to assess the share of ship costs that should be accounted because several sampling activities are taken on one cruise. Costs for the benthic monitoring at open sea were estimated using the MARMONI scheme for calculating monitoring costs, where the ship costs are split between monitoring programmes based on the number of samples taken during a cruise. The costs are presented in Table 8.3. Equipment needed (not including consumables) for the monitoring activity is listed in Table 8.4.

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Table 8.3 Costs for benthic monitoring at open sea. Type of expenditure € / sample Resource needs Sampling (grab samples) total 350 42 205 -vessel 228 -equipment 12 -personnel 110 0.7 man-years Laboratory (community composition, total 237 28 486 abundance, biomass) -equipment 11 -personnel 226 1.6 man-years Data management and reporting 39 4 645 (0.05 man-years) Fixed costs (overheads) 282 33 948 TOTAL 909 109 104

Table 8.4 Research equipment and costs EQUIPMENT (DEVICES) For Sampling, Lab. Analyses, Data Investments per Life- management unit, € time

2 x 0.1 m2 Van Veen grab Sampling 7199,44 20 2 x sieve 1.0 x 1.0 mm Sampling 820,88 10

2 x additional sieve 0.5 x 0.5 mm Sampling 820,88 10

Stereomicroscope incl. Camera Analysis 10500 20

5 x Container for emptying the Sampling 65 5 grab Set of forceps Analysis 100 5

Software (tailored for counting & Analysis and Data Management 0 10 data management)

Computer including standard Analysis 1500 3 software Computer including standard Data management 1500 3 software

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 Benthic brackish-water index (BBI) for soft-bottom macrofauna  Size structure of long-lived macrobenthic species

Methods and costs The sampling activity is similar to the open sea monitoring scheme depicted in Figure 8.2, but the research vessel used is instead of R/V Aranda smaller boats suitable for navigating in shallower waters are used. As the van Veen grab is operated by winch needing a more robust boat, the shallowest areas are sampled using a hand-operated Ekman grab from a smaller boat. In total, there are 282 sampling stations in regular monitoring. Of these, 112 stations are located in the Gulf of Finland. In addition, 350 stations are monitored as statutory monitoring. As some stations are sampled on rotation, a total of around 360 stations are sampled every year in the Finnish coastal areas.

For coastal monitoring smaller boats are used. The average price for small boat is €1130 per day (2/3 of stations) and for large boat €3480 per day (1/3 of stations). The type of boat depends on whether the station is situated in inner or outer archipelago. Sampling in the inner archipelago is most conveniently done using small boats, where as in the more exposed outer archipelago larger boats are needed. Apart from using an Ekman grab sampler instead of van Veen grab in the inner archipelago, the equipment needed is the same as listed in Table 8.4. Costs for the sub-programme were estimated using the MARMONI scheme for calculating monitoring costs (Table 8.5).

Table 8.5 Costs for benthic monitoring in coastal waters (ref to MARMONI A5 excel). Type of expenditure € / sample Resource needs Sampling (grab samples) total 580 208 906 -vessel 478 -equipment 6 -personnel 94 Laboratory (community composition total 235 84 559 and abundance) -equipment 8 -personnel 226 Data management and reporting 13 4 645 Fixed costs (overheads) 253 91 211 TOTAL 1081 389 320

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Planning of macrozoobenthos sampling Optimisation € of sampling

No Order from Is sampling performed consultant by the institute? Analysis of Yes results

Preparation of Assessment of BD sampling status

Hydrography

Sampling Supporting onboard R/V Sediment information characteristics

Indicators Sieving of

samples 1.3.3 1.3.4 4.3.4

Preservation of samples Calculation of D2 indicators indicators

Data preparation Occurrence of Transport to alien species laboratory

Size measurements Quantitative analysis Preparation of of macrozoobenthos samples for analysis species composition Biomass analyses

Figure 8.2 Process chart of zoobenthos sampling.

Sub-programme Macro-algae and blue mussel communities Indicators The monitoring focuses on hard bottom communities, where especially habitat-forming species are followed. At present, only one indicator is operative, namely the lower depth limit of bladderwrack and red algae, but an indicator describing the status of blue mussel communities is under development.

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Methods and costs The monitoring is based on diving transects, during which the macro-algal species composition and coverage, as well as the lowest depth distribution of the species are recorded. There are in total 24 diving transects where the macro-algal community is monitored and the lower depth limit of bladderwrack is checked at 75 sites. In the Gulf of Finland the number of sites is 23. The costs for macro-algae monitoring have been 12 100 € per year, but this does not include the costs for monitoring blue mussel communities as this is a new part of the monitoring programme.

Sub-programme Physical loss and damage of the sea-floor Indicators The sub-programme monitors the pressures (dredging, dredge spoil disposal, extraction etc.) on the sea- floor. These activities are permit based and through information from the permit applications data is gathered for the indicator “Number of permits for dredging and the amount of dredged material”. Indicators describing the amount of hazardous substances in dredge spoil disposals and cumulative impact of anthropogenic pressures are under development.

Methods and costs The volume of dredged and disposed material is collected from the permits and stored in a database. This is a new monitoring sub-programme and costs are not available or have been estimated.

Biodiversity monitoring programme for water column habitats The programme describes the physical environment and biological communities in the water column. It consists of the three subprograms on the biological elements; zooplankton, phytoplankton and pathogenic microbes, as well as two subprograms on the physical elements. The physical monitoring subprograms describe the physical habitat in terms of temperature, salinity, ice conditions, waves and sea level.

Sub-programme Zooplankton composition and abundance Indicators The aim with the sub-programme is to describe the secondary production in the water column through zooplankton community composition and abundance. The zooplankton community functions as a link between the primary producers and higher trophic levels such as fish and thus have an important role in the food web. There is only one operative indicator in this subprograms illustrating the quality of zooplankton as food for fish:  Mean size and total stock abundance of zooplankton

Methods and costs Zooplankton samples are collected by vertical tows from either ~5 m above the bottom to the surface (shallow stations, ≤ 30 m) or in depth layers (deep stations, ≥ 30 m) as designed and specified by HELCOM monitoring programmes. Most commonly, a 100 μm WP2 net (diameter 57 cm) equipped with a flow meter is used. The species composition and abundance (individuals per m3) is counted using an inverted

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microscope. The biomass (mg/m3) is is defined by using species and stages specific pre-established weight values from HELCOM manual. Alternatively, a subsample is scanned and analysed automatically through Figure recognition. Using this method, biomass is estimated using the size distribution of zooplankton. There are 17 sampling stations in the open sea and 14 in the coastal waters of which 6 and 4 are in the Gulf of Finland, respectively. Out of the coastal GoF stations one station is sampled seven times per year, whereas the rest are sampled twice a year. The open sea stations are sampled twice every year. Sampling is done during spring and summer.

One researcher is needed onboard R/V Aranda to take the samples, but same researcher also takes the phytoplankton samples. For taxonomic analyses one researcher is needed and storing the data. A senior researcher responsible for the monitoring takes care of the planning of sampling as well as data management, including quality check, and reporting together with the researcher.

Open sea stations are sampled using R/V Aranda, whereas the coastal sampling is done from smaller boats in conjunction with the phytoplankton monitoring. For sampling a WP2 plankton net is used and samples are preserved and transported to the laboratory for analysis. Samples are analysed using stereo- and inverted microscopes equipped with cameras and specially developed software for counting and data management is used. Costs for the sub-programme were estimated based on the open sea monitoring using the MARMONI scheme for calculating monitoring costs (Veidemane & Pakalniete 2015) (Table 8.6). Equipment needed (not including consumables) for the monitoring activity is listed in Table 8.7.

Table 8.6 Costs for zooplankton monitoring in open sea (ref to MARMONI A5 excel). Type of expenditure € / sample Resource needs Sampling (net samples) total 235 19 770 -vessel 185 -equipment 16 -personnel 35 0.1 man-years Laboratory (community total 183 15 343 composition, abundance, biomass) -equipment 36 -personnel 147 0.3 man-years Data management and reporting 28 2 321 (0.01 man-years) Fixed costs (overheads) 674 56 604 Other costs (retaining proficiency 441 37 045 and training) TOTAL 1561 131 084

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Table 8.7 Equipment needed for the zooplankton monitoring. EQUIPMENT (DEVICES) For Sampling, Lab. Analyses, Data Investments per Life-time management unit, €

Zooplankton sampler Sampling 3680 5 Inverted microscope Analysis 5979 20

Stereomicroscope incl. Camera Analysis 10500 20

Software (tailored for counting & Data Management 8500 15 data management) Computer Analysis+Data manag 1500 3

Camera for inverted microscope Analysis 976 10

Sub-programme Phytoplankton composition and abundance Indicators The sub-programme aims at describing the species composition and amount of pelagic primary producers. This is done by quantitative microscope analysis of phytoplankton samples. The phytoplankton community forms the base of the food web, thus changes in the food web can often be early detected in the phytoplankton community. The monitoring strives to describe the seasonal succession in the phytoplankton community and to detect anomalies in species composition. There are two operational indicators in this subprogramme:  Biomass of phytoplankton  Taxonomic diversity of phytoplankton

In addition, several other indicators (e.g. proportion of cyanobacteria of the total phytoplankton biomass, ratio of diatoms and dinoflagellates and functional diversity of phytoplankton) utilizing the same samples, are being developed.

Methods and costs Phytoplankton sampling is done in three settings: (1) automatic sampling from Alg@line, (2) open sea sampling from R/V Aranda, and (3) coastal sampling with smaller boats. The sampling process is depicted in ¡Error! No se encuentra el origen de la referencia.. On Alg@line eight samples from one station in the Gulf of Finland are taken yearly. The open sea sampling visits twelve stations, of which two in the Gulf of Finland, once a year. In the coastal areas a total of 100 stations with varying frequencies are sampled yearly. Of these, 20 are located in the Gulf of Finland. Around 300 phytoplankton samples are analysed yearly.

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Alg@line: For running the Alg@line, a commercial ship to is needed, but there are no costs with regards to operating the ship, except possible negotiation costs to get the ship in the programme. The ferrybox system that will be installed in the ship costs 70500 euros. For maintaining the equipment, retrieving and preserving samples a researcher employed full time is needed and in addition an intern during the summer months. To analyze the samples approximately a researcher is needed for 10 days.

Aranda: For the sampling the vessel is needed for 3 weeks (but several other sampling is done on the same trip as well). One researcher is needed on board to take samples, but the same person takes also zooplankton and chlorophyll a samples so only 1/3 of this time goes for phytoplankton monitoring. Analysing the samples takes around 15 days for a researcher. Costs for the phytoplankton monitoring on R/V Aranda were estimated using the MARMONI scheme for calculating monitoring costs (Table 8.8).

Coastal sampling: Costs for the coastal phytoplankton monitoring are based on information collected from the regional ELY- centres and estimated based on the MARMONI scheme for calculating monitoring costs (Table 8.9). In SYKE, one researcher uses ca. 88 days yearly to analyse the 70 samples taken by regional environmental centres.

Table 8.8 Costs for phytoplankton monitoring at open sea. Type of expenditure € / sample Sampling (net samples) 423 -vessel 185 -equipment 23 -personnel 214 Laboratory (community composition) 256 -equipment 218 -personnel 38 Data management 44 Fixed costs (overheads) Other costs (retaining proficiency and training) TOTAL

Table 8.9 Costs for phytoplankton monitoring in coastal areas. Type of expenditure € / sample Sampling (net samples) 7 (as many water quality parameters are sampled at the same time phytoplankton sampling cost is around 1/90 – 1/75 of the total sampling costs, if only phytoplankton was taken sampling costs would

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be 600-700 per sample) -vessel 4 -equipment 1 -personnel 2 Laboratory (community composition) 220 (estimated consultant price, not possible to split into equipment and personnel costs) -equipment -personnel Data management 143 (including planning, inviting tenders, data management) Fixed costs (overheads) Other costs (retaining proficiency and training) TOTAL 370

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Planning of phytoplankton sampling

No Order from Is sampling € consultant performed by the institute?

Yes Optimising of sampling Preparation of sampling

Sampling via automated sampling Analysis of results Sampling system Maintenance onboard R/V (FerryBox system)

Chlorophyll a, nutrients Assessment of BD Preservation Transport to status of samples lab Hydrography

Preservation of Supporting Transport to samples information laboratory

4.3.2 4.3.3 Phytoplankton Phyto- taxonomic plankton diversity trait-based Preparation of samples functional for analysis diversity Calculation of indicators Other phytoplankton indicators Quantitative analysis (=non-BD) of phytoplankton Data preparation species composition

Occurrence of alien species, and/or exceptional (bloom)events, and/or toxic and potentially toxic Real time species phytoplankton community composition analysis Report

Figure 8.3 Process chart of phytoplankton sampling

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Sub-programme Pathogenic microbes The aim with the sub-programme is to assess the hygienic quality of coastal waters. At present the quality of water is assessed at public bathing places. The monitoring is co-ordinated under the Bathing water Directive and the information collected is also utilised under the MSFD. Thus, no additional costs or resources are at this point associated with the implementation under the MSFD.

Sub-programme Physical monitoring of the water column Indicators The sub-programme monitors the temperature, salinity and Secchi-depth of the Baltic Sea. Remote sensing gives a good spatial coverage of the surface, whereas frequent in situ measurements are provided by the Alg@line programme. The whole water column is sampled on the monitoring cruises. The physical parameters give important supporting information for the biodiversity monitoring as they describe the properties of the pelagic habitat. The following indicators are monitored:  Water transparency  Temperature and its changes  Salinity and its changes  Water stratification and its changes

Methods and costs Secchi depth is measured using a white plate with the diameter of 30 cm. Temperature and salinity are measured using a CTD, which samples the whole water column, or from water samples taken at certain depth intervals. Stratification is derived from the density gradient in the water column. Surface temperature and water transparency can also be monitored using remote sensing.

The CTD used on-board research vessels costs, depending on which sensors it is equipped with, around 70 000 - 80 000 euros. The costs for monitoring of the physical parameters during monitoring cruises were estimated using the scheme developed in the MARMONI project.

Table 8.10 Costs for monitoring physical-chemical parameters at open sea. Type of expenditure € / sample Sampling 191 -vessel 185 -equipment CTD rosette (see below) -personnel 6 Laboratory Most analyses are done onboard, thus costs are included in the sampling costs -equipment part of Aranda budget -personnel included in the sampling costs Data management Fixed costs (overheads)

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Other costs (retaining proficiency and training) TOTAL The above is for sampling and analysing water samples. The use of CTD is estimated to cost 505 €/day (230 equipment costs + 275 personnel costs). Average of 3.3 stations per day = 153 €/station. An average of 44.4 samples for physical-chemical parameters are taken per station = 8 480 € per station. CTD + analyses = 8 633 € per station.

Sub-programme Waves, sea level and ice conditions The monitoring of waves, sea level and ice condition provide supporting information for the biodiversity monitoring programmes. The real-time information is produced by the Finnish Meteorological Institute as part of their operative activities. Waves are monitored using wave buoys, sea level by coastal mareographs and sea ice conditions by remote sensing and in situ observations. Costs are estimated to be 115 000 € per year.

Monitoring programme for Alien species The programme monitors the arriving and already arrived alien species in the Finnish marine areas and tries to work out their origin and how they arrived. It aims at describing which alien species are occurring and what are their abundances and distributions. The programme is based on the monitoring programmes for the water column, benthic habitats and fish, and requires detailed taxonomic resolution in order to confidently pick up arrivals and distribution of the often low abundant alien species. A need to expand the monitoring of alien species to harbours has been identified and harbour monitoring is under development. The following indicators are monitored:  Introduction of new non-indigenous species  Change in abundance of established non-indigenous species  Ratios of non-indigenous and native species in well-known species groups

In addition, indicators on harmful non-indigenous species, treatment of ballast water and a biopollution index is under development.

The methods follow the monitoring programmes for the water column, benthic habitats and fish. Traps and settling plates are developed to be used in the harbour monitoring, but as this monitoring is not yet ongoing, costs are not estimated.

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