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A proposal for restructuring Descriptor 3 of the Marine Strategy Framework Directive (MSFD)
Marine Policy 74 (2016) 128–135
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A proposal for restructuring Descriptor 3 of the Marine Strategy Framework Directive (MSFD) ⁎
Wolfgang Nikolaus Probsta, , Andrea Raub, Daniel Oesterwindb a b
Thünen Institute of Sea Fisheries, Palmaille 9, 22767 Hamburg, Germany Thünen Institute of Baltic Sea Fisheries, Alter Hafen Süd 2, 18069 Rostock, Germany
A R T I C L E I N F O
A BS T RAC T
Keywords: Fish stocks Assessment Indicator framework Selectivity Size distribution DPSIR PSR
In 2015 the EU Commission decided to review the structure of the criteria and indicators of the Marine Strategy Framework Directive (MSFD). This paper reviews some shortcomings of the current structure of Descriptor 3 (D3) addressing the status of exploited fish and shellfish stocks and suggests a more operational structure for D3. By reframing D3, the assessments of stock size and size distribution within the stock could be addressed within two distinct criteria. When relating status parameters, such as stock size and size structure to human pressures, the first criterion would assess fishing intensity while the second criterion would assess the selectivity pattern acting upon a fish stock. Within each criterion, the indicators would be embedded within an indicator framework and thereby assigned to predefined indicator types. Three different indicator frameworks were compared and analysed with regards to its operationality within D3, namely pressure-state (p-S), pressurestate-response (PSR) and driver-pressure-state-impact-response (DPSIR) frameworks. P-S or DPSIR were found to be either incomplete in fulfilling the MSFD reporting requirements (p-S) or too complicated to be implemented in the mid-term (DPSIR). PSR thus appears to provide the best compromise between operationality and MSFD requirements and could be applied to criteria within other descriptors to obtain a consistent indicator structure within the MSFD.
1. Introduction The European Marine Strategy Framework Directive (MSFD 2008/ 56/EC) was ratified in 2008 and requires the member states (MS) of the European Union to achieve “good environmental status” (GEnS) in their marine waters by 2020. Therefore the MSFD obliges the MS to fulfil predefined steps within an ambitious time schedule. An initial assessment of the current status of marine waters was required to be completed by 2012, as well as the definition of GEnS and the environmental targets of each MS. To facilitate these tasks, the European Commission structured the MSFD within eleven qualitative descriptors. Each descriptor is addressing a single environmental topic, e.g. conservation of biodiversity (D1), the status of commercially exploited fish and shellfish stocks (D3), eutrophication (D5) or pollution (D8). Within these eleven descriptors, a set of 29 criteria containing 56 indicators was proposed to be used by the MS in their assessment of environmental status [1]. The current structure of the MSFD indicator framework implies pressure and state relationships between several indicators and criteria, in which an anthropogenic pressure causes impacts in a ecological state [2,3]. However, these pressure-state (p-S) relationships
⁎
are in many cases not explicit and formally assigned. Furthermore, many indicators can be interpreted as either pressure- or stateindicators, e.g. the abundance of invasive species within Descriptor 2. And finally, not all state-indicators are related to one of the proposed pressure- indicators or vice versa. Therefore the current indicator framework of the MSFD lacks a rigid and consistent structure and proposals for the implementation of indicator frameworks have been recently put forward [4]. Frameworks of environmental indicators were developed several decades before the implementation of the MSFD. In the beginning of the 1990s the Organisation for Economic Co-operation and Development (OECD) proposed the combination of pressure-, stateand response indicators (PSR) to be used for environmental assessments [5]. The PSR was extended by the European Environmental Agency promoting a driver-pressure-state-impact-response (DPSIR) framework [6]. Driver indicators represent social, economic or even natural driving forces that affect human activities, which in turn exert pressures on components of the ecosystem. The pressures cause a change in the ecosystems state, which lead to an impact (positive or negative) and may warrant a societal response, i.e. through management authorities [6]. To date, PSR or DPSIR have been employed in
Corresponding author. E-mail address: [email protected] (W.N. Probst).
http://dx.doi.org/10.1016/j.marpol.2016.09.026 Received 23 November 2015; Received in revised form 14 September 2016; Accepted 14 September 2016 0308-597X/ © 2016 Elsevier Ltd. All rights reserved.
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Table 1 Current structure of Descriptor 3 according to the European Commission Decision 2010/477/EU. Criterion
Indicators
3.1 Level of pressure of the fishing activity 3.2 Reproductive capacity of the stock 3.3 Population age and size distribution
3.1.1Fishing mortality (F)3.1.2 Catch/biomass ratio 3.2.1 Spawning stock biomass3.2.2 Biomass indices 3.3.1 Proportion of fish larger than the mean size of first sexual maturation3.3.2 Mean maximum length across all species found in research vessel surveys3.3.3 95% percentile of the fish length distribution observed in research vessel survey3.3.4 Size at first sexual maturation
indicators of Criterion 3.3 are not specifically linked to Criterion 3.1, and though the length structure of fish stocks is influenced by fishing intensity [20,21], Criterion 3.3 also addresses the impacts of gear selectivity [22]. Finally, the Commission Decision does not address a third category of indicators, which is intended to measure management success [23]. It is generally agreed that policy indicators used for environmental assessments should be embedded into PSR or DPSIR-frameworks [10,11,23], but this has not been the case within the MSFD, generally, nor D3, in particular.
various studies [7–10] and have been investigated by various scientific disciplines [11–14], but these frameworks have been officially adapted by existing environmental marine policies [15]. The synthesis report by the European Commission on the initial assessment by the MS identified many gaps within, and many inconsistencies between, single MS assessments [16,17]. The EU Commission acknowledged that these gaps and inconsistencies partly stem from the incomplete structure of the Commission Decision including imprecise definitions of indicators and their associated metrics. Therefore, a process to review and revise the MSFD indicator framework was instigated in 2014 [4]. This paper intends to advance the revision of D3, which assesses the status of exploited fish stocks by three criteria: fishing intensity, stock size and size (or age) distribution within the stock (Table 1). The last criterion can be regarded as an amendment to the assessment scheme applied for the EU Common Fisheries Policy (CFP), which currently is based on two indicators: fishing mortality rates (F) and spawning stock biomass (SSB) [18]. The current structure of D3 is formally inconsistent within itself and the implementation of new indicators, which are currently not part of the CFP and therefore pose challenges to the member states and assessment bodies. D3 is a very good example for the inconsistent structure of the current MSFD indicator framework of the Commission Decision - it contains pressure as well as status indicators, but the indicator framework is not fully complete and the relationships between the pressure and the state indicators are not precisely defined. This paper provides a new conceptual approach for restructuring the criteria and indicators within the MSFD indicator framework exemplified for D3. The current structure and resulting shortcomings of D3 are reviewed, and a new structure is proposed that introduces two criteria (stock biomass and size distribution within the stock). The implementation of different indicator frameworks within each of these proposed criteria will be discussed and finally some exemplary indicators to fill such an indicator framework will be reviewed.
3. Suggestions for improvement of Descriptor 3 In the following section, conceptual improvements to the structure of D3 are suggested. Exemplary existing and potential indicators are reviewed and recommendations are provided regarding the indicator framework best suited for implementation within the MSFD. 3.1. Restructuring D3-Criteria D3 addresses the sustainable exploitation of fish and shellfish populations [24] while accounting for their reproductive potential and size structure. The following proposes the replacement of three previous criteria by two new ones, which centre around two P-S relationships concerning fisheries: The first proposed new criterion of D3 (D3C1*1) addresses stock biomass and how it is affected by fishing intensity [25,26]. The second proposed new criterion (D3C2*) deals with stock size structure and how it is affected by selectivity [22]. The simultaneous assessment of selectivity and fishing intensity, dating back to Beverton & Holt [27], has been scrutinized by recent studies [22,28,29], and is echoed in the here proposed conceptual approach for restructuring D3. Three points should be addressed when revising D3 within the Commission Decision:
• For many stocks age data are not available [25] or not reliable
2. The current structure and shortcomings of Descriptor 3 D3 of the MSFD deals with the status of commercially exploited fish and shellfish stocks by assessing the level of fishing exploitation, stock size and size structure within each exploited stock. In its current form D3 requires that the “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” [19]. To date the descriptor is structured into three criteria that include eight indicators in total (Table 1). The indicators within D3 are not categorised in the sense of being pressure- or state indicators. However, it is obvious that the indicators in Criterion 3.1 “Level of pressure of the fishing activity” addresses fishing mortality, thereby representing typical pressure indicators, whereas the indicators in Criteria 3.2 “Reproductive capacity of the stock” and 3.3 “Population age and size distribution” address states. Throughout its descriptors, the MSFD implies the analysis of P-S relationships, but neither provide any official categorization nor linkages between the indicators. Therefore, the current structure makes it difficult to assign specific pressures to state indicators. Within D3 the
• •
[30,31]. As long as these data gaps are not closed, which would be cost-intensive and time consuming, existing length structure data is preferred for development of appropriate indicators. Length data are readily available for the majority of exploited stocks. The consistent focus on the size distribution within the stock allows applying the same indicators to all stocks, which would make the assessments more consistent among stocks. Furthermore, most fisheries are sizeand not age-selective. The indicators of D3 should consistently apply to single stocks, not to communities or functional groups. Community indicators such as the mean maximum length in survey catches (MML) should be moved to Descriptor 1 (biodiversity) or Descriptor 4 (food webs) [24]. The simultaneous use of primary and secondary indicators within a criterion should be avoided. To date it is not clear, if alternative
1 The new criteria are labelled with asterisks to indicate that they are the suggestions of this study and should not be confused with criteria or indicator labels be the European Commission or ICES.
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Pressure and state-indicators are already inherent in the Commission Decision. Extending the already proposed indicators by response indicators would require minor adaptations compared to the implementation of DPSIR. The inclusion of response indicators into the Commission Decision would therefore be the simplest and fastest way to obtain an operational and more informative indicator framework [34]. 3.3. The implications of applying PSR-frameworks PSR implies causal links between pressure, state and response indicators: Human activities exert pressure on the environment thereby causing a change in the actual condition of the ecosystem and its components (state), which in the case of unwanted state change will trigger a response by policy and management [10]. Hereby management will feedback to pressures through human activities [5] while the effectiveness of environmental measures can be controlled by the effect exerted on environmental state. Accordingly, the assessment benchmarks should also be related with these PSR links in mind. Achieving the assessment benchmark of a pressure indicator should ideally result in the achievement of GEnS for the state indicator and the assessment benchmark of the response indicator should be compatible to the benchmark of the pressure indicator. In many cases, however, the environmental status of an ecosystem component is influenced by multiple, interacting anthropogenic pressures as well as natural factors. The influence of human induced pressures on ecosystem states thus has to be constantly validated to ensure that the defined pressure and response benchmarks are effectively managing the state eventually leading to an improvement (or maintenance) of GEnS. It is not always certain, how and in which time frames management can reverse changes in ecosystem state [37,38]. For example in the case of fisheries induced evolution it could be hard to reverse the effects of selection for early maturation [39]. The reversal of declines in the sizecomposition of fish communities may act on decadal scales [40,41]. Accordingly, some management targets within D3 might not be achievable within the near future and it has to be discussed if this failure should prevent the achievement of GEnS for the stock in the short-term. This might concern for example long-term fisheries management plans for commercially exploited stocks, aiming for the recovery of depleted stock biomass in a step-wise process in order to simultaneously taking social responsibility by safeguarding jobs [42]. Similarly, a long-term perspective for the recovery of the genetic resources of a fish stock may be necessary. The here presented examples of PSR-frameworks applied within D3 could be transferred to other criteria and descriptors of the MSFD. The consistent application of PSR-frameworks would be a great improvement to many of the current MSFD criteria, which vary in detail and specificity. PSR would provide links between the indicators within a criterion (or between and within descriptors) and clarify their role in the assessment and reporting scheme of the MSFD (Table 3, Fig. 4). State indicators could be used for the assessment of environmental status. Assessment benchmarks of pressure and state indicators could be used for the description of GEnS. Pressure and response indicators could be used to assess the achievement of environmental targets and the efficiency of the programme of measures. However, it should be noted that for many state indicators a clear relationship to a pressure may be missing. Nonetheless, such indicators may be provide valuable information on ecosystem properties and should be therefore included into the MSFD-framework.
Fig. 1. Application of the pressure-state relationships to the two newly proposed criteria (D3C1* & D3C2*) of Descriptor 3.
indicator metrics should and will be used within an indicator, but different metrics are often associated with different degrees of confidence and their combination when aggregating assessment results is considered problematic [32].
3.2. Choice of an indicator framework As mentioned above, for environmental assessment indicators are embedded into frameworks suggesting causal links between drivers, pressures, states, impacts and responses [5,33]. The MSFD does not formally declare support for a specific indicator framework. However, the MSFD implies P-S relationships between various descriptors, criteria and indicators. Besides P-S frameworks, several scientific studies propose the use of PSR [23,34] or DPSIR frameworks [4,6,10,33] when performing environmental impact assessments. The two newly suggested criteria (D3C1* and D3C2*) will be considered within P-S (Fig. 1), PSR (Fig. 2) and DPSIR frameworks (Fig. 3), and the potential implications of their use in the context of the fulfilment of MSFD reporting requirements and operationalisation will be compared (Table 2). It should be noted that several authors have expanded the DPSIR-framework by e.g. including human activities as an additional category [35], by evolving DPSIR into causal networks [33], or by including ecosystem services and risk assessment [36]. However, this study does not dwell on these more recent derivatives of DPSIR, as the comparison from P-S to PSR to DPSIR is sufficient to illustrate the trade-off between framework complexity and operationalisation. Finally, this study intends to suggest a simple, yet comprehensive indicator framework within each criterion of D3 for proper assessment of P-S relationships. From the comparison between the three indicator frameworks, it is evident that the P-S and PSR would be readily operational, but would leave gaps in the reporting on ecological impacts and economic and social consequences. In the case of P-S, gaps in reporting requirements would further concern environmental targets and measures according to MSFD Article 10 (Table 2). To the contrary, the implementation of a DPSIR framework would fill these gaps, but would require significantly larger research and assessment efforts. Therefore, developing an operational DPSIR may delay the implementation of an indicator framework in the short term. Hence PSR-frameworks for both criteria appear to be a good compromise between the needs of MSFD reporting of environmental status, pressures and management effectiveness on the one hand, and, on the other, ease of implementation within the short-term. Nevertheless, it should be acknowledged that the application of the DPSIR framework might be desirable in the mid-term future, allowing for time to fully grasp the interrelationships between socio-economic drivers and impacts and ecosystem statuses and changes.
4. Illustration of the proposed new D3-structure The following section presents some D3-indicators, which are either already in force under the CFP (primarily concerning D3C1*) [43] or have been discussed in various contexts within the scientific community and in literature [20,44,45]. It should be emphasized that 130
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Fig. 2. Application of pressure-state-response (PSR) frameworks to the two newly proposed criteria (D3C1* & D3C2*) of Descriptor 3.
4.1. Potential indicators for D3C1*
indicators presented here are not exhaustive, and alternative indicators not mentioned here may be appropriate. Thus the aim of this overview is not to propose a fixed suite of indicators, but rather to initiate a debate on how PSR- or DPSIR-indicators within D3 could look like, and to show that the new structure is, in part, already operational. The authors are aware that for many indicators (especially size-based indicators), there is an ongoing scientific debate on which indicator to use [46] and how to identify thresholds for GEnS (e.g. by defining a healthy age and size structure) [22]. Furthermore, the International Council for the Exploration of the Sea (ICES) states that the indicators for the size structure within a stock or selectivity have no operational reference points or are not consistent with the MSY-principle [47]. Hence ICES advises that the MS should not use any indicators that refer to size-structure or selectivity within their 2018 MSFD GES assessments [47]. It is therefore an open question whether the here suggested criterion D3C2* would still form part of the revised Commission decision and the MS’ assessments. The authors make no claims of having found the solution regarding these issues nor to the completeness in reviewing all indicators that may have been suggested by various authors. Scientific evaluation will be necessary to identify the best of any operational indicators and GEnS benchmarks to be used within the MSFD.
In D3C1*, the two indicators of fishing intensity and stock size (Table 3) have operational metrics; Fishing mortality (F) and spawning stock biomass (SSB) are already used in analytical stock assessments for many commercially exploited stocks [48]. The major challenge for the near future will be to include more commercially-exploited stocks into analytical assessment schemes that will allow for the assessment of exploitation intensity and stock size against the principle of maximum sustainable yield (MSY). Until these schemes become operational, secondary metrics of fishing intensity and stock size could be assessed e.g. by time-series techniques [45,49]. However, as mentioned above these secondary indicator metrics may be associated with lower levels of confidence [50] and thus ICES does not advise for their use [32]. For the DPSIR approach, recruitment (R) could be used as impact indicator within D3C1*, as one of the ultimate goals of fisheries management is to prevent recruitment overfishing [51]. However, recruitment is not only affected by the parent stock size (SSB), but also by environmental influences. Thus the SSB-R relationships of many stocks are fuzzy and potential reference points for R may be difficult to obtain. Hence the practicality of using R as an indicator within the MSFD needs to be considered. One solution would be to use R as a surveillance indicator which triggers more precautionary management action if it falls outside its known thresholds [52].
Fig. 3. Application of pressure-state-response (DPSIR) frameworks to the two newly proposed criteria (D3C1* & D3C2*) of Descriptor 3.
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Table 2 Differences in practical implications for the three indicator frameworks to implement the two new suggested D3-criteria (D3C1 and D3C2). R & D: research and development. P-S: pressure state-, PSR: Pressure-state-response-, DPSIR: Driver-pressure-state-impact-response indicator frameworks. MSFD: Marine Strategy Framework Directive. Framework
P-S
PSR
DPSIR
Assumed R & D needs D3C1* Assumed R & D needs D3C2* Suitable for the reporting of …MSFD Article 8 (1a) (Current environmental status)MSFD Article 8 (1b) (Predominant pressures & impacts)MSFD Article 8 (1c) (Economic and social impacts)MSFD Article 9 (Good environmental status)MSFD Article 10 (Environmental targets)MSFD Article 13 (Programmes of measures)
None Low YesPartlyNoYesNoNo
Low Medium YesPartlyNoYesYesYes
Medium High YesYesYesYesYesYes
The ratio between legal outtake from a stock (also referred to as TAC, total allowable catch) and the scientific catch recommendations has been argued to have the potential to allow assessing the efficiency of management against management targets [34,53] and could therefore be evaluated further for its potential as a response indicator within D3C1*. The benchmark of this indicator should express the full compliance of the management authorities defining the TAC with the higher level policy goal of sustainable exploitation of marine resources, taking into account long term management plans. This higher level goal is currently the sustainable exploitation of fish stocks according to the MSY-principle [26,54]. Another potential response indicator suggested by Piet et al. [34] is the ratio between the realized catch and the TAC set by management authorities; in this case the indicator would be a measure on the compliance of the fishing industry. However, many potential problems with the application of such an indicator should be considered: First, it would require that real catch information (including discards) is available. Second, the stock distribution area for which scientific advice is usually given differs in many cases from the management area, for which TACs are defined. In such cases this mismatch makes a direct comparison of TACs and scientific recommendation impossible. Third, one should keep in mind that an overall indicator of industry compliance may fail to detect violations of individual fleets or vessels. For example, if fleet A is under-fishing while another fleet B is overfishing their quota, both fleets considered together could still be compliant to the overall TAC, and the quotaviolation of fleet B may remain undetected.
Fig. 4. Visualisation of how a pressure-state-response indicator framework could contribute to the reporting obligations of the Marine Strategy Framework Directive. Blue lines represent indicator time series, dashed lines represent assessment benchmarks and green circles the current indicator status.
reference points which are operational or internationally agreed upon and further development and validation of such pressure indicators is necessary [47,56]. The state indicators within D3C2*should address the size-distribution within the stock. Several size-based indicators have been suggested by various authors to assess the effects of fishing [20,44,57], however, many of them are strongly influenced by recruitment [20,21] or lack well-defined assessment benchmarks [22,24]. In this regard, more research is required in order to identify an operational indicator and define the proper benchmarks, which reflect the demand of the EUCommission that a stock contains “a high proportion of old, large individuals” [1,47,56]. For the DPSIR approach the impact indicators of D3C2* could deal with growth overfishing [25,51] and genetic impacts of fishing, also known as the phenomenon of fisheries induced evolution [39,58–61]. An impact indicator of growth overfishing could e.g. capture a loss in yield due to the selectivity regime in practice when compared to the yield that could be obtained with an optimal selectivity regime. The
4.2. Potential indicators for D3C2* Despite the prevalent developing needs it appears to be appropriate that pressure indicators under D3C2* should reflect the selectivity regime, which is exerted on the exploited stock by the operating fishing fleet(s). Various potential pressure indicators were suggested in recent studies, e.g. the mean length in the commercial catch (LC ) or the proportion of individuals within the catch that are larger than a given reference size (Table 4). This reference size could be related to the onset of maturity, an optimal yield strategy [55] or to any other management target. However, there are currently no indicators and
Table 3 Some examples of existing and potential indicators for criterion D3C1* of Descriptor 3. F: Fishing mortality, FMSY: Reference point for F according to the principle of maximum sustainable yield, HR: ratio between commercial catches or landings and abundance indices from fisheries surveys (CPUE), SSB: Spawning stock biomass, MSYBtrigger: is considered the lower bound of SSB fluctuation around BMSY, R: Recruitment, TAC: Total allowable catch set by management authorities, TACMSY: Scientific recommendations for TAC according to MSY-principle, C: Annual commercial catch. Indicator type
Indicator name
Indicator metric (s)
Existing and potential assessment benchmark (GEnS)
Driver
Food demand
Not required
Pressure
Fishing intensity
Amount of consumed regional fish & shellfish per year F or HR
State Impact
Stock size Impaired reproduction (recruitment overfishing) Management & industry compliance
SSB or CPUE R
≥ MSYBtrigger or CPUE related to MSY To be developed
ICES [18],Probst and Oesterwind [77] ICES [18] ICES [18], Gascuel, Coll [78]
C: TACTAC:TACMSYC: TAC
E.g. ~1
Piet, van Overzee [34]
Response
132
< FMSY or HR related to MSY
Source (s)
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Table 4 Some examples of potential indicators for criterion D3C2* of Descriptor 3. Lm50: Size at which half of the population is mature, Lmat: Length related to average size-at-first-maturity, MCRS: Minimum conservation reference size. Assessment benchmarks (GEnS thresholds) are not indicated here, as the benchmarks of all indicators require further scientific development and validation. Indicator type
Indicator name
Potential indicator metric (s)
Driver Pressure
Food demand Selectivity pattern of commercial gears(s)
State
Size distribution in the stock
Impact
Growth overfishing and fisheries induced evolution Technical measures
Amount of consumed regional fish & shellfish per year Proportion of commercial catch larger than size of 50% maturity (Lm50) Proportion of catch at optimum length (Lopt)Mean length in commercial catch (L C )FImm/FMat 95% percentile of the fish length distribution observed in research vessel surveys (Former indicator 3.3.3)Slope & intercept of length spectraSize diversity indicesMean length of largest fish (Lmax5%)Proportion of megaspawners in stock Lost yieldMean size of first sexual maturation (Lmat)Changes in the probabilistic maturation reaction norm (PMRN) Lmat:MCRSBycatch or discard rates of undersized/non-consumable individuals
Response
Source (s)
genetic impacts of fishing could potentially be captured by changes in the probabilistic maturation reaction norm [62–65] or by indicators related to the size of first maturation [46]. Again, to date no operational indicators and reference points are available to evaluate fisheries induced genetic evolution [47]. Potential response indicators of D3C2* are not developed but could address the ratio between a current legal size restriction and a certain size related indicator threshold reflecting management compliance to high level political objectives. A further possibility could be to evaluate the compliance of the selectivity regime used by the operating fishing fleet(s) to existing size regulations i.e. by expressing the amount of discarded fish through discard rates or the amount of fish caught for non-human consumption e.g. in fisheries already falling under the EU landing obligation. Response indicators of this type could link the indicators of the EU data collection framework with the MSFD [66,67]. Generally, it must be mentioned that size-based indicators under D3 have yet to be validated and approved due to the lack of operational and biologically meaningful assessment benchmarks representing an accepted definition of a healthy age and size structure (within a fish stock) [47]. Accordingly, the indicators for D3C2* that have been reviewed here are not as well developed as the indicators of D3C1*, and thus cannot be considered as operational. Indicator development for the D3 size criterion of the MSFD has to be continued in the frame of internationally-coordinated science. Potential candidate indicators and reference points have to be chosen, tested and validated according to internationally agreed upon criteria and standards [46]. So far, the scientific and political debate is still ongoing.
ICES [46], Froese [55], ICES [65]Froese [55] Froese [55]Vasilakopoulos, O’Neill [29] Piet, Albella [44], Shin, Rochet [57]Shin, Rochet [57]Shin, Rochet [57]Probst, Kloppmann [45] Froese [55] Hilborn and Stokes [51,79]ICES [65]Heino, Dieckmann [62], Devine, Wright [64], ICES [65] NoneEU-COM [67]
aggregating the assessment on many stocks, would it be more recommendable not to use an one-out-all-out approach in order to account for uncertainty in the assessment status [69,73–75]. Several authors suggest implementing statistical procedures to determine a minimal number of stocks that should be at GEnS [45,76]. Further scientific and political discourse on this topic will become necessary in near future for the implementation of the MSFD. 6. Conclusions The adaptations to the structure of D3 proposed here can provide clarification about the purpose of each indicator and its role within the MSFD in order to assess the complex causes and impacts of marine ecosystem alterations. It is recommended that indicators and criteria of D3 (and maybe criteria of other descriptors as well) be reorganized within two PSR frameworks associated with two new criteria. These two criteria are aligned to “stock size” and “size structure within the stock”, and are suggested to replace the current three criteria of D3. Both new criteria together reconcile the assessment of fishing intensity and selectivity, which has been originally suggested by fisheries scientist in the mid-1900s. The first criterion builds on existing indicators used within the CFP and is thereby mostly operational. For the second criterion more research, indicator development and validation is necessary. However, the authors hope that this study has proposed a way forward in successful implementation of the MSFD under better consideration of interrelationships of environmental and fisheries policies objectives within the European Union. Acknowledgements
5. Some thoughts on integration of single indicator assessments
This study forms part of the Thünen-Institute (TI) research initiative on the implementation of the Marine Strategy Framework directive (MSFD) “Definition and validation of indicators and initial assessment” (www.ti.bund.de). This work also resulted partly from the BONUS Bio-C³ project and was supported by BONUS (Art 185), funded jointly by the EU and German national funding's: BMBF (Grant No. 03F0682B). Christopher Zimmermann and an anonymous reviewer provided valuable comments to a previous version of the manuscript. Marc Taylor reviewed spelling, style and grammar. W.N. Probst would like to thank ICES for the organization of the WKMSFDD3-workshops, in which lively discussions took place inspiring the ideas to this paper.
The MSFD can be considered as an integrated ecosystem assessment [68] , in which information of single indicators will usually be aggregated [69–71]. The question which arises concerning aggregation is whether the indicators of D3C1* and D3C2* should be applied for each stock separately or aggregated across all relevant stocks. An application of PSR per stock provides the highest detail of information and is congruent with the stock-by-stock assessment provided by ICES. Using aggregated indicators across all relevant stocks provides overviews on the number/proportion of stocks achieving GEnS within a given indicator/criterion, which may be closer to the information the EU Commission and member states require when focusing on the ‘bigger picture’ [50,72]. In the latter case the chosen indicators would have to be modified to “No. of stocks for which the indicator is above/ below its assessment benchmark or GEnS target”. Furthermore, it has to be decided if all relevant commercially exploited fish and shellfish stocks should achieve GEnS at the same time or rather, in the case of
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crossmark
A proposal for restructuring Descriptor 3 of the Marine Strategy Framework Directive (MSFD) ⁎
Wolfgang Nikolaus Probsta, , Andrea Raub, Daniel Oesterwindb a b
Thünen Institute of Sea Fisheries, Palmaille 9, 22767 Hamburg, Germany Thünen Institute of Baltic Sea Fisheries, Alter Hafen Süd 2, 18069 Rostock, Germany
A R T I C L E I N F O
A BS T RAC T
Keywords: Fish stocks Assessment Indicator framework Selectivity Size distribution DPSIR PSR
In 2015 the EU Commission decided to review the structure of the criteria and indicators of the Marine Strategy Framework Directive (MSFD). This paper reviews some shortcomings of the current structure of Descriptor 3 (D3) addressing the status of exploited fish and shellfish stocks and suggests a more operational structure for D3. By reframing D3, the assessments of stock size and size distribution within the stock could be addressed within two distinct criteria. When relating status parameters, such as stock size and size structure to human pressures, the first criterion would assess fishing intensity while the second criterion would assess the selectivity pattern acting upon a fish stock. Within each criterion, the indicators would be embedded within an indicator framework and thereby assigned to predefined indicator types. Three different indicator frameworks were compared and analysed with regards to its operationality within D3, namely pressure-state (p-S), pressurestate-response (PSR) and driver-pressure-state-impact-response (DPSIR) frameworks. P-S or DPSIR were found to be either incomplete in fulfilling the MSFD reporting requirements (p-S) or too complicated to be implemented in the mid-term (DPSIR). PSR thus appears to provide the best compromise between operationality and MSFD requirements and could be applied to criteria within other descriptors to obtain a consistent indicator structure within the MSFD.
1. Introduction The European Marine Strategy Framework Directive (MSFD 2008/ 56/EC) was ratified in 2008 and requires the member states (MS) of the European Union to achieve “good environmental status” (GEnS) in their marine waters by 2020. Therefore the MSFD obliges the MS to fulfil predefined steps within an ambitious time schedule. An initial assessment of the current status of marine waters was required to be completed by 2012, as well as the definition of GEnS and the environmental targets of each MS. To facilitate these tasks, the European Commission structured the MSFD within eleven qualitative descriptors. Each descriptor is addressing a single environmental topic, e.g. conservation of biodiversity (D1), the status of commercially exploited fish and shellfish stocks (D3), eutrophication (D5) or pollution (D8). Within these eleven descriptors, a set of 29 criteria containing 56 indicators was proposed to be used by the MS in their assessment of environmental status [1]. The current structure of the MSFD indicator framework implies pressure and state relationships between several indicators and criteria, in which an anthropogenic pressure causes impacts in a ecological state [2,3]. However, these pressure-state (p-S) relationships
⁎
are in many cases not explicit and formally assigned. Furthermore, many indicators can be interpreted as either pressure- or stateindicators, e.g. the abundance of invasive species within Descriptor 2. And finally, not all state-indicators are related to one of the proposed pressure- indicators or vice versa. Therefore the current indicator framework of the MSFD lacks a rigid and consistent structure and proposals for the implementation of indicator frameworks have been recently put forward [4]. Frameworks of environmental indicators were developed several decades before the implementation of the MSFD. In the beginning of the 1990s the Organisation for Economic Co-operation and Development (OECD) proposed the combination of pressure-, stateand response indicators (PSR) to be used for environmental assessments [5]. The PSR was extended by the European Environmental Agency promoting a driver-pressure-state-impact-response (DPSIR) framework [6]. Driver indicators represent social, economic or even natural driving forces that affect human activities, which in turn exert pressures on components of the ecosystem. The pressures cause a change in the ecosystems state, which lead to an impact (positive or negative) and may warrant a societal response, i.e. through management authorities [6]. To date, PSR or DPSIR have been employed in
Corresponding author. E-mail address: [email protected] (W.N. Probst).
http://dx.doi.org/10.1016/j.marpol.2016.09.026 Received 23 November 2015; Received in revised form 14 September 2016; Accepted 14 September 2016 0308-597X/ © 2016 Elsevier Ltd. All rights reserved.
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Table 1 Current structure of Descriptor 3 according to the European Commission Decision 2010/477/EU. Criterion
Indicators
3.1 Level of pressure of the fishing activity 3.2 Reproductive capacity of the stock 3.3 Population age and size distribution
3.1.1Fishing mortality (F)3.1.2 Catch/biomass ratio 3.2.1 Spawning stock biomass3.2.2 Biomass indices 3.3.1 Proportion of fish larger than the mean size of first sexual maturation3.3.2 Mean maximum length across all species found in research vessel surveys3.3.3 95% percentile of the fish length distribution observed in research vessel survey3.3.4 Size at first sexual maturation
indicators of Criterion 3.3 are not specifically linked to Criterion 3.1, and though the length structure of fish stocks is influenced by fishing intensity [20,21], Criterion 3.3 also addresses the impacts of gear selectivity [22]. Finally, the Commission Decision does not address a third category of indicators, which is intended to measure management success [23]. It is generally agreed that policy indicators used for environmental assessments should be embedded into PSR or DPSIR-frameworks [10,11,23], but this has not been the case within the MSFD, generally, nor D3, in particular.
various studies [7–10] and have been investigated by various scientific disciplines [11–14], but these frameworks have been officially adapted by existing environmental marine policies [15]. The synthesis report by the European Commission on the initial assessment by the MS identified many gaps within, and many inconsistencies between, single MS assessments [16,17]. The EU Commission acknowledged that these gaps and inconsistencies partly stem from the incomplete structure of the Commission Decision including imprecise definitions of indicators and their associated metrics. Therefore, a process to review and revise the MSFD indicator framework was instigated in 2014 [4]. This paper intends to advance the revision of D3, which assesses the status of exploited fish stocks by three criteria: fishing intensity, stock size and size (or age) distribution within the stock (Table 1). The last criterion can be regarded as an amendment to the assessment scheme applied for the EU Common Fisheries Policy (CFP), which currently is based on two indicators: fishing mortality rates (F) and spawning stock biomass (SSB) [18]. The current structure of D3 is formally inconsistent within itself and the implementation of new indicators, which are currently not part of the CFP and therefore pose challenges to the member states and assessment bodies. D3 is a very good example for the inconsistent structure of the current MSFD indicator framework of the Commission Decision - it contains pressure as well as status indicators, but the indicator framework is not fully complete and the relationships between the pressure and the state indicators are not precisely defined. This paper provides a new conceptual approach for restructuring the criteria and indicators within the MSFD indicator framework exemplified for D3. The current structure and resulting shortcomings of D3 are reviewed, and a new structure is proposed that introduces two criteria (stock biomass and size distribution within the stock). The implementation of different indicator frameworks within each of these proposed criteria will be discussed and finally some exemplary indicators to fill such an indicator framework will be reviewed.
3. Suggestions for improvement of Descriptor 3 In the following section, conceptual improvements to the structure of D3 are suggested. Exemplary existing and potential indicators are reviewed and recommendations are provided regarding the indicator framework best suited for implementation within the MSFD. 3.1. Restructuring D3-Criteria D3 addresses the sustainable exploitation of fish and shellfish populations [24] while accounting for their reproductive potential and size structure. The following proposes the replacement of three previous criteria by two new ones, which centre around two P-S relationships concerning fisheries: The first proposed new criterion of D3 (D3C1*1) addresses stock biomass and how it is affected by fishing intensity [25,26]. The second proposed new criterion (D3C2*) deals with stock size structure and how it is affected by selectivity [22]. The simultaneous assessment of selectivity and fishing intensity, dating back to Beverton & Holt [27], has been scrutinized by recent studies [22,28,29], and is echoed in the here proposed conceptual approach for restructuring D3. Three points should be addressed when revising D3 within the Commission Decision:
• For many stocks age data are not available [25] or not reliable
2. The current structure and shortcomings of Descriptor 3 D3 of the MSFD deals with the status of commercially exploited fish and shellfish stocks by assessing the level of fishing exploitation, stock size and size structure within each exploited stock. In its current form D3 requires that the “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” [19]. To date the descriptor is structured into three criteria that include eight indicators in total (Table 1). The indicators within D3 are not categorised in the sense of being pressure- or state indicators. However, it is obvious that the indicators in Criterion 3.1 “Level of pressure of the fishing activity” addresses fishing mortality, thereby representing typical pressure indicators, whereas the indicators in Criteria 3.2 “Reproductive capacity of the stock” and 3.3 “Population age and size distribution” address states. Throughout its descriptors, the MSFD implies the analysis of P-S relationships, but neither provide any official categorization nor linkages between the indicators. Therefore, the current structure makes it difficult to assign specific pressures to state indicators. Within D3 the
• •
[30,31]. As long as these data gaps are not closed, which would be cost-intensive and time consuming, existing length structure data is preferred for development of appropriate indicators. Length data are readily available for the majority of exploited stocks. The consistent focus on the size distribution within the stock allows applying the same indicators to all stocks, which would make the assessments more consistent among stocks. Furthermore, most fisheries are sizeand not age-selective. The indicators of D3 should consistently apply to single stocks, not to communities or functional groups. Community indicators such as the mean maximum length in survey catches (MML) should be moved to Descriptor 1 (biodiversity) or Descriptor 4 (food webs) [24]. The simultaneous use of primary and secondary indicators within a criterion should be avoided. To date it is not clear, if alternative
1 The new criteria are labelled with asterisks to indicate that they are the suggestions of this study and should not be confused with criteria or indicator labels be the European Commission or ICES.
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Pressure and state-indicators are already inherent in the Commission Decision. Extending the already proposed indicators by response indicators would require minor adaptations compared to the implementation of DPSIR. The inclusion of response indicators into the Commission Decision would therefore be the simplest and fastest way to obtain an operational and more informative indicator framework [34]. 3.3. The implications of applying PSR-frameworks PSR implies causal links between pressure, state and response indicators: Human activities exert pressure on the environment thereby causing a change in the actual condition of the ecosystem and its components (state), which in the case of unwanted state change will trigger a response by policy and management [10]. Hereby management will feedback to pressures through human activities [5] while the effectiveness of environmental measures can be controlled by the effect exerted on environmental state. Accordingly, the assessment benchmarks should also be related with these PSR links in mind. Achieving the assessment benchmark of a pressure indicator should ideally result in the achievement of GEnS for the state indicator and the assessment benchmark of the response indicator should be compatible to the benchmark of the pressure indicator. In many cases, however, the environmental status of an ecosystem component is influenced by multiple, interacting anthropogenic pressures as well as natural factors. The influence of human induced pressures on ecosystem states thus has to be constantly validated to ensure that the defined pressure and response benchmarks are effectively managing the state eventually leading to an improvement (or maintenance) of GEnS. It is not always certain, how and in which time frames management can reverse changes in ecosystem state [37,38]. For example in the case of fisheries induced evolution it could be hard to reverse the effects of selection for early maturation [39]. The reversal of declines in the sizecomposition of fish communities may act on decadal scales [40,41]. Accordingly, some management targets within D3 might not be achievable within the near future and it has to be discussed if this failure should prevent the achievement of GEnS for the stock in the short-term. This might concern for example long-term fisheries management plans for commercially exploited stocks, aiming for the recovery of depleted stock biomass in a step-wise process in order to simultaneously taking social responsibility by safeguarding jobs [42]. Similarly, a long-term perspective for the recovery of the genetic resources of a fish stock may be necessary. The here presented examples of PSR-frameworks applied within D3 could be transferred to other criteria and descriptors of the MSFD. The consistent application of PSR-frameworks would be a great improvement to many of the current MSFD criteria, which vary in detail and specificity. PSR would provide links between the indicators within a criterion (or between and within descriptors) and clarify their role in the assessment and reporting scheme of the MSFD (Table 3, Fig. 4). State indicators could be used for the assessment of environmental status. Assessment benchmarks of pressure and state indicators could be used for the description of GEnS. Pressure and response indicators could be used to assess the achievement of environmental targets and the efficiency of the programme of measures. However, it should be noted that for many state indicators a clear relationship to a pressure may be missing. Nonetheless, such indicators may be provide valuable information on ecosystem properties and should be therefore included into the MSFD-framework.
Fig. 1. Application of the pressure-state relationships to the two newly proposed criteria (D3C1* & D3C2*) of Descriptor 3.
indicator metrics should and will be used within an indicator, but different metrics are often associated with different degrees of confidence and their combination when aggregating assessment results is considered problematic [32].
3.2. Choice of an indicator framework As mentioned above, for environmental assessment indicators are embedded into frameworks suggesting causal links between drivers, pressures, states, impacts and responses [5,33]. The MSFD does not formally declare support for a specific indicator framework. However, the MSFD implies P-S relationships between various descriptors, criteria and indicators. Besides P-S frameworks, several scientific studies propose the use of PSR [23,34] or DPSIR frameworks [4,6,10,33] when performing environmental impact assessments. The two newly suggested criteria (D3C1* and D3C2*) will be considered within P-S (Fig. 1), PSR (Fig. 2) and DPSIR frameworks (Fig. 3), and the potential implications of their use in the context of the fulfilment of MSFD reporting requirements and operationalisation will be compared (Table 2). It should be noted that several authors have expanded the DPSIR-framework by e.g. including human activities as an additional category [35], by evolving DPSIR into causal networks [33], or by including ecosystem services and risk assessment [36]. However, this study does not dwell on these more recent derivatives of DPSIR, as the comparison from P-S to PSR to DPSIR is sufficient to illustrate the trade-off between framework complexity and operationalisation. Finally, this study intends to suggest a simple, yet comprehensive indicator framework within each criterion of D3 for proper assessment of P-S relationships. From the comparison between the three indicator frameworks, it is evident that the P-S and PSR would be readily operational, but would leave gaps in the reporting on ecological impacts and economic and social consequences. In the case of P-S, gaps in reporting requirements would further concern environmental targets and measures according to MSFD Article 10 (Table 2). To the contrary, the implementation of a DPSIR framework would fill these gaps, but would require significantly larger research and assessment efforts. Therefore, developing an operational DPSIR may delay the implementation of an indicator framework in the short term. Hence PSR-frameworks for both criteria appear to be a good compromise between the needs of MSFD reporting of environmental status, pressures and management effectiveness on the one hand, and, on the other, ease of implementation within the short-term. Nevertheless, it should be acknowledged that the application of the DPSIR framework might be desirable in the mid-term future, allowing for time to fully grasp the interrelationships between socio-economic drivers and impacts and ecosystem statuses and changes.
4. Illustration of the proposed new D3-structure The following section presents some D3-indicators, which are either already in force under the CFP (primarily concerning D3C1*) [43] or have been discussed in various contexts within the scientific community and in literature [20,44,45]. It should be emphasized that 130
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Fig. 2. Application of pressure-state-response (PSR) frameworks to the two newly proposed criteria (D3C1* & D3C2*) of Descriptor 3.
4.1. Potential indicators for D3C1*
indicators presented here are not exhaustive, and alternative indicators not mentioned here may be appropriate. Thus the aim of this overview is not to propose a fixed suite of indicators, but rather to initiate a debate on how PSR- or DPSIR-indicators within D3 could look like, and to show that the new structure is, in part, already operational. The authors are aware that for many indicators (especially size-based indicators), there is an ongoing scientific debate on which indicator to use [46] and how to identify thresholds for GEnS (e.g. by defining a healthy age and size structure) [22]. Furthermore, the International Council for the Exploration of the Sea (ICES) states that the indicators for the size structure within a stock or selectivity have no operational reference points or are not consistent with the MSY-principle [47]. Hence ICES advises that the MS should not use any indicators that refer to size-structure or selectivity within their 2018 MSFD GES assessments [47]. It is therefore an open question whether the here suggested criterion D3C2* would still form part of the revised Commission decision and the MS’ assessments. The authors make no claims of having found the solution regarding these issues nor to the completeness in reviewing all indicators that may have been suggested by various authors. Scientific evaluation will be necessary to identify the best of any operational indicators and GEnS benchmarks to be used within the MSFD.
In D3C1*, the two indicators of fishing intensity and stock size (Table 3) have operational metrics; Fishing mortality (F) and spawning stock biomass (SSB) are already used in analytical stock assessments for many commercially exploited stocks [48]. The major challenge for the near future will be to include more commercially-exploited stocks into analytical assessment schemes that will allow for the assessment of exploitation intensity and stock size against the principle of maximum sustainable yield (MSY). Until these schemes become operational, secondary metrics of fishing intensity and stock size could be assessed e.g. by time-series techniques [45,49]. However, as mentioned above these secondary indicator metrics may be associated with lower levels of confidence [50] and thus ICES does not advise for their use [32]. For the DPSIR approach, recruitment (R) could be used as impact indicator within D3C1*, as one of the ultimate goals of fisheries management is to prevent recruitment overfishing [51]. However, recruitment is not only affected by the parent stock size (SSB), but also by environmental influences. Thus the SSB-R relationships of many stocks are fuzzy and potential reference points for R may be difficult to obtain. Hence the practicality of using R as an indicator within the MSFD needs to be considered. One solution would be to use R as a surveillance indicator which triggers more precautionary management action if it falls outside its known thresholds [52].
Fig. 3. Application of pressure-state-response (DPSIR) frameworks to the two newly proposed criteria (D3C1* & D3C2*) of Descriptor 3.
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Table 2 Differences in practical implications for the three indicator frameworks to implement the two new suggested D3-criteria (D3C1 and D3C2). R & D: research and development. P-S: pressure state-, PSR: Pressure-state-response-, DPSIR: Driver-pressure-state-impact-response indicator frameworks. MSFD: Marine Strategy Framework Directive. Framework
P-S
PSR
DPSIR
Assumed R & D needs D3C1* Assumed R & D needs D3C2* Suitable for the reporting of …MSFD Article 8 (1a) (Current environmental status)MSFD Article 8 (1b) (Predominant pressures & impacts)MSFD Article 8 (1c) (Economic and social impacts)MSFD Article 9 (Good environmental status)MSFD Article 10 (Environmental targets)MSFD Article 13 (Programmes of measures)
None Low YesPartlyNoYesNoNo
Low Medium YesPartlyNoYesYesYes
Medium High YesYesYesYesYesYes
The ratio between legal outtake from a stock (also referred to as TAC, total allowable catch) and the scientific catch recommendations has been argued to have the potential to allow assessing the efficiency of management against management targets [34,53] and could therefore be evaluated further for its potential as a response indicator within D3C1*. The benchmark of this indicator should express the full compliance of the management authorities defining the TAC with the higher level policy goal of sustainable exploitation of marine resources, taking into account long term management plans. This higher level goal is currently the sustainable exploitation of fish stocks according to the MSY-principle [26,54]. Another potential response indicator suggested by Piet et al. [34] is the ratio between the realized catch and the TAC set by management authorities; in this case the indicator would be a measure on the compliance of the fishing industry. However, many potential problems with the application of such an indicator should be considered: First, it would require that real catch information (including discards) is available. Second, the stock distribution area for which scientific advice is usually given differs in many cases from the management area, for which TACs are defined. In such cases this mismatch makes a direct comparison of TACs and scientific recommendation impossible. Third, one should keep in mind that an overall indicator of industry compliance may fail to detect violations of individual fleets or vessels. For example, if fleet A is under-fishing while another fleet B is overfishing their quota, both fleets considered together could still be compliant to the overall TAC, and the quotaviolation of fleet B may remain undetected.
Fig. 4. Visualisation of how a pressure-state-response indicator framework could contribute to the reporting obligations of the Marine Strategy Framework Directive. Blue lines represent indicator time series, dashed lines represent assessment benchmarks and green circles the current indicator status.
reference points which are operational or internationally agreed upon and further development and validation of such pressure indicators is necessary [47,56]. The state indicators within D3C2*should address the size-distribution within the stock. Several size-based indicators have been suggested by various authors to assess the effects of fishing [20,44,57], however, many of them are strongly influenced by recruitment [20,21] or lack well-defined assessment benchmarks [22,24]. In this regard, more research is required in order to identify an operational indicator and define the proper benchmarks, which reflect the demand of the EUCommission that a stock contains “a high proportion of old, large individuals” [1,47,56]. For the DPSIR approach the impact indicators of D3C2* could deal with growth overfishing [25,51] and genetic impacts of fishing, also known as the phenomenon of fisheries induced evolution [39,58–61]. An impact indicator of growth overfishing could e.g. capture a loss in yield due to the selectivity regime in practice when compared to the yield that could be obtained with an optimal selectivity regime. The
4.2. Potential indicators for D3C2* Despite the prevalent developing needs it appears to be appropriate that pressure indicators under D3C2* should reflect the selectivity regime, which is exerted on the exploited stock by the operating fishing fleet(s). Various potential pressure indicators were suggested in recent studies, e.g. the mean length in the commercial catch (LC ) or the proportion of individuals within the catch that are larger than a given reference size (Table 4). This reference size could be related to the onset of maturity, an optimal yield strategy [55] or to any other management target. However, there are currently no indicators and
Table 3 Some examples of existing and potential indicators for criterion D3C1* of Descriptor 3. F: Fishing mortality, FMSY: Reference point for F according to the principle of maximum sustainable yield, HR: ratio between commercial catches or landings and abundance indices from fisheries surveys (CPUE), SSB: Spawning stock biomass, MSYBtrigger: is considered the lower bound of SSB fluctuation around BMSY, R: Recruitment, TAC: Total allowable catch set by management authorities, TACMSY: Scientific recommendations for TAC according to MSY-principle, C: Annual commercial catch. Indicator type
Indicator name
Indicator metric (s)
Existing and potential assessment benchmark (GEnS)
Driver
Food demand
Not required
Pressure
Fishing intensity
Amount of consumed regional fish & shellfish per year F or HR
State Impact
Stock size Impaired reproduction (recruitment overfishing) Management & industry compliance
SSB or CPUE R
≥ MSYBtrigger or CPUE related to MSY To be developed
ICES [18],Probst and Oesterwind [77] ICES [18] ICES [18], Gascuel, Coll [78]
C: TACTAC:TACMSYC: TAC
E.g. ~1
Piet, van Overzee [34]
Response
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< FMSY or HR related to MSY
Source (s)
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Table 4 Some examples of potential indicators for criterion D3C2* of Descriptor 3. Lm50: Size at which half of the population is mature, Lmat: Length related to average size-at-first-maturity, MCRS: Minimum conservation reference size. Assessment benchmarks (GEnS thresholds) are not indicated here, as the benchmarks of all indicators require further scientific development and validation. Indicator type
Indicator name
Potential indicator metric (s)
Driver Pressure
Food demand Selectivity pattern of commercial gears(s)
State
Size distribution in the stock
Impact
Growth overfishing and fisheries induced evolution Technical measures
Amount of consumed regional fish & shellfish per year Proportion of commercial catch larger than size of 50% maturity (Lm50) Proportion of catch at optimum length (Lopt)Mean length in commercial catch (L C )FImm/FMat 95% percentile of the fish length distribution observed in research vessel surveys (Former indicator 3.3.3)Slope & intercept of length spectraSize diversity indicesMean length of largest fish (Lmax5%)Proportion of megaspawners in stock Lost yieldMean size of first sexual maturation (Lmat)Changes in the probabilistic maturation reaction norm (PMRN) Lmat:MCRSBycatch or discard rates of undersized/non-consumable individuals
Response
Source (s)
genetic impacts of fishing could potentially be captured by changes in the probabilistic maturation reaction norm [62–65] or by indicators related to the size of first maturation [46]. Again, to date no operational indicators and reference points are available to evaluate fisheries induced genetic evolution [47]. Potential response indicators of D3C2* are not developed but could address the ratio between a current legal size restriction and a certain size related indicator threshold reflecting management compliance to high level political objectives. A further possibility could be to evaluate the compliance of the selectivity regime used by the operating fishing fleet(s) to existing size regulations i.e. by expressing the amount of discarded fish through discard rates or the amount of fish caught for non-human consumption e.g. in fisheries already falling under the EU landing obligation. Response indicators of this type could link the indicators of the EU data collection framework with the MSFD [66,67]. Generally, it must be mentioned that size-based indicators under D3 have yet to be validated and approved due to the lack of operational and biologically meaningful assessment benchmarks representing an accepted definition of a healthy age and size structure (within a fish stock) [47]. Accordingly, the indicators for D3C2* that have been reviewed here are not as well developed as the indicators of D3C1*, and thus cannot be considered as operational. Indicator development for the D3 size criterion of the MSFD has to be continued in the frame of internationally-coordinated science. Potential candidate indicators and reference points have to be chosen, tested and validated according to internationally agreed upon criteria and standards [46]. So far, the scientific and political debate is still ongoing.
ICES [46], Froese [55], ICES [65]Froese [55] Froese [55]Vasilakopoulos, O’Neill [29] Piet, Albella [44], Shin, Rochet [57]Shin, Rochet [57]Shin, Rochet [57]Probst, Kloppmann [45] Froese [55] Hilborn and Stokes [51,79]ICES [65]Heino, Dieckmann [62], Devine, Wright [64], ICES [65] NoneEU-COM [67]
aggregating the assessment on many stocks, would it be more recommendable not to use an one-out-all-out approach in order to account for uncertainty in the assessment status [69,73–75]. Several authors suggest implementing statistical procedures to determine a minimal number of stocks that should be at GEnS [45,76]. Further scientific and political discourse on this topic will become necessary in near future for the implementation of the MSFD. 6. Conclusions The adaptations to the structure of D3 proposed here can provide clarification about the purpose of each indicator and its role within the MSFD in order to assess the complex causes and impacts of marine ecosystem alterations. It is recommended that indicators and criteria of D3 (and maybe criteria of other descriptors as well) be reorganized within two PSR frameworks associated with two new criteria. These two criteria are aligned to “stock size” and “size structure within the stock”, and are suggested to replace the current three criteria of D3. Both new criteria together reconcile the assessment of fishing intensity and selectivity, which has been originally suggested by fisheries scientist in the mid-1900s. The first criterion builds on existing indicators used within the CFP and is thereby mostly operational. For the second criterion more research, indicator development and validation is necessary. However, the authors hope that this study has proposed a way forward in successful implementation of the MSFD under better consideration of interrelationships of environmental and fisheries policies objectives within the European Union. Acknowledgements
5. Some thoughts on integration of single indicator assessments
This study forms part of the Thünen-Institute (TI) research initiative on the implementation of the Marine Strategy Framework directive (MSFD) “Definition and validation of indicators and initial assessment” (www.ti.bund.de). This work also resulted partly from the BONUS Bio-C³ project and was supported by BONUS (Art 185), funded jointly by the EU and German national funding's: BMBF (Grant No. 03F0682B). Christopher Zimmermann and an anonymous reviewer provided valuable comments to a previous version of the manuscript. Marc Taylor reviewed spelling, style and grammar. W.N. Probst would like to thank ICES for the organization of the WKMSFDD3-workshops, in which lively discussions took place inspiring the ideas to this paper.
The MSFD can be considered as an integrated ecosystem assessment [68] , in which information of single indicators will usually be aggregated [69–71]. The question which arises concerning aggregation is whether the indicators of D3C1* and D3C2* should be applied for each stock separately or aggregated across all relevant stocks. An application of PSR per stock provides the highest detail of information and is congruent with the stock-by-stock assessment provided by ICES. Using aggregated indicators across all relevant stocks provides overviews on the number/proportion of stocks achieving GEnS within a given indicator/criterion, which may be closer to the information the EU Commission and member states require when focusing on the ‘bigger picture’ [50,72]. In the latter case the chosen indicators would have to be modified to “No. of stocks for which the indicator is above/ below its assessment benchmark or GEnS target”. Furthermore, it has to be decided if all relevant commercially exploited fish and shellfish stocks should achieve GEnS at the same time or rather, in the case of
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