Which variants of MSY do we prefer? Report from the MYFISH workshop on identifying acceptable and feasible MSY variants, trade‐offs, constraints and management measures. Anna Rindorf, Mark Dickey‐Collas, Louize Hill, Niels Hintzen, Ellen Hoefnagel, Alexander Kempf, Adrian Leach, Polina Levontin, Pamela Mace, Steve Mackinson, John Mumford, Christian Olesen, Clive Potter, Raúl Prellezo, Dave Reid, Axel Rossberg, George Tserpes, Clara Ulrich, Rudiger Voss Abstract Maximum Sustainable Yield first appeared in the 1950’s but has lately experienced a revival as a reference point in modern fisheries management. Several variants of it have appeared in addition to the original variants of MSY (Maximise the sustainable yield in weight) and MEY (Maximise the sustainable economic yield). These variants have become increasingly important as the need to trade off yield of one species against that of another or against ecological, economic or social considerations has become apparent. As the variants approach this problem in different ways, the definition and choice of MSY variants becomes and essential point in MSY management. The current study decomposes MSY into three aspects: What to maximize (MSY variants), what to sustain (constraints to sustainability) and how to manage fisheries aiming for MSY (management measures). A range of new and existing MSY variants were suggested, described, categorised and evaluated on a regional basis by a total of 64 scientists, NGOs, managers and industry representatives organized in combined groups. The objective was to determine which of these variants are acceptable and feasible in practical management in each of five European regions: the Baltic Sea, the Mediterranean, the North Sea, the Western Waters and Widely ranging stocks distributed across several geographical areas. Only the MSY variant ‘Maximise inclusive governance’ (a version of Maximum Social Yield) was consistently highly rated in all regions. ‘Maximising yield of key commercial species’ was the second highest ranked across regions. 1 Introduction The idea of managing fisheries to obtain the largest sustainable yield (MSY) was formalised in the 1950s (Schaefer 1954, Ricker 1958). Maximizing yield from the fishery is an immediately appealing concept which solves the problem of fisheries management merely aiming to avoid unsustainable fishing, which often in practice becomes aiming at the borderline between sustainable and unsustainable fishing. However, the concept is not without problems in the theoretical and practical implementation and has therefore been a topic of much debate in fisheries (e.g. Larkin 1977, Punt and Smith 2001, Hilborn and Stokes 2010). The applications frequently attempt to maximise the weight or value landed ignoring stochasticity, changes in vital parameters as well as any interaction between species or in the fishing process. These simplifications are rarely appropriate. Exploited species do not exist in isolation. The catch of one species affects that of other species as the perturbation of the system propagates to other components through predator‐prey interactions or as technical interactions in the fishing process lead to mortality of species other than the fishing target. In a mixed fishery, MSY cannot be obtained for more than one species at a time (Brander 1995). Further, both MSY and the level of fishing which leads to MSY of prey species are highly dependent on the level of fishing on predators and competitors (Brander 1988, Gislason 1999, Collie et al. 2003, Richardson et al. 2010). Large fish eat small fish and an increase in the abundance of a top predator increases natural mortality on its prey species (including younger conspecifics), some of which are commercially exploited fish. An increase in biomass of predatory fish therefore leads not only to an increase in yield of the target species but also to a decrease in MSY of its prey species, confronting the management with a trade‐off between yield of different species. To respect these trade‐offs, the ecological and economical value of one species relative to the other must be determined. Furthermore, the exploitation rate must be regulated to a level presenting an agreed risk of negative effects on the ecosystem as a whole including species which are not commercially exploited. Even if species existed in isolation in a constant environment, implementing a management which maximise the average weight landed does not necessarily ensure the maximum value of fisheries to society (e.g. Punt and Smith 2001, Christensen 2010). Other variants of MSY such as Maximum Economic Yield (MEY) are therefore used to identify the economically optimal yield. However, economic considerations are not the only ones of importance to society: the added value in the processing chain (Christensen 2010), employment and average income in the fishing industry are only some of the indicators which have been suggested. Indicators incorporating the social value of these indicators in a Maximum Social Yield (MSOY) have been suggested and defined as the best possible rate of exploitation of a fishery under the prevailing socioeconomic conditions (Charles 1988, Christensen 2010, Dichmont et al. 2010). Similar to MSY in landed weight, MEY and MSOY are affected by variation in the underlying relationships such as ecosystem variability but in addition to this, factors such as value of landings, operational costs of fisheries, demand for labour and perceived value of social indicators impact indicators incorporating economic and social considerations. 2 Ecosystems are variable in time and even with perfect management, the stock will hence not be exactly at the biomass theoretically capable of delivering MSY over a prolonged period of time (B ). This has been MSY addressed through redefining MSY as the maximum average yield over a prolonged time period (Punt and Smith 2001) which enables the existence of MSY in a stochastic environment. However, it does not necessarily ensure that MSY management is sustainable in the way that biological limit reference points are avoided with appropriate levels of risk. To ensure this, it is necessary to divide the analysis of MSY into an analysis of constraints allowing the definition of the ‘sustainable arena’ and an analysis of what we want to maximise within this arena. The ‘sustainable arena’ is limited by constraints on ecosystem, economic and social aspects which we wish to ensure are above or below certain levels but do not wish to maximise. The objective of this study was in discussion among the stakeholders and scientists to suggest acceptable and feasible management strategies aiming at MSY in European fisheries. To achieve this purpose, management strategies aiming at MSY were decomposed into three aspects: What to maximize (MSY variants, implicitly requiring a selection of ‘exchange rates’ between yield of different species), what to sustain (constraints to sustainability) and how to manage fisheries (management measures). The answer to these questions is likely to depend on both geographical area and the compositions of the groups discussing them and parallel group sessions were therefore used in discussions. The groups were first tasked with identifying a generic list of possible candidates under each sub‐header. The groups were then redefined and regional groups tasked with identifying region specific acceptable and feasible MSY variants, constraints to sustainability and management measures. Methods Two workshops were conducted on April 24th to 26th 2012 in Vigo, Spain. The objective of the first workshop was to identify a generic list of possible candidates under each sub‐header. The objective of the second workshop was to identify acceptable and feasible MSY variants, constraints to sustainability and management measures. The top priority was given to identifying acceptable and feasible MSY variants and if time permitted, acceptable and feasible constraints to sustainability and management measures were also identified. The workshop was constructed with five identically constructed parallel sessions to allow regional comparisons of the MSY variants identified as acceptable and feasible. The 64 participants in the workshop included representatives from 13 universities, 14 fisheries research institutes, 8 industry organisations, 3 NGOs and 3 Management organisations. The majority of the organisations were European but representatives from New Zealand, Canada and US also participated. The participants were invited from MYFISH partners and organisations working together with MYFISH. The organisations working together with MYFISH included a list of 7 industry representatives (4 of which attended), 6 Regional Advisory councils (all of which attended) and 6 NGOs (3 of which attended). The invited persons who did not attend claimed that this was due to conflicting meetings and lack of time rather than lack of interest. Travel and subsistence costs were covered for all invited persons and hence there was no financial 3 burden imposed by attending the workshop. The workshop participants were 75% scientists and 25% NGO/industry/management and 28% of the participants were women. A full list of participants is given in Appendix A. Defining MSY variants, constraints to sustainability and management measures. The workshop was introduced with an afternoon of presentations, each highlighting particular aspects of MSY. All presentations are given in Appendix B. The following day, participants were divided into four different topic groups according to their individual preferences: Ecosystem concerns, Stock interaction concerns, Economic concerns and Social and implementation concerns. Topic groups were made to ensure that experts in each discipline had the opportunity to discuss among themselves and reach a consensus on suggestions rather than leave the choice between similar versions of variants to people summarising the results over all groups. Participants were allocated to groups based on their indication of interest prior to attending the workshop. The number of participants in the groups ranged from 11 to 18, with the Stock interaction and Social and Implementation groups having 11 and 12 participants, respectively, and the Ecosystem and Economic having 17 and 18 participants, respectively. The composition of the groups varied. Scientist tended to go to the group covering their area of expertise. NGOs were only represented in the groups on Ecosystem and Stock interactions. Industry representatives were present in all groups but mostly attended the Economic and Social and Implementation groups. Full details on participation are given in Appendix A. The groups were asked to focus on the three aspects of MSY management: Maximum yield o Which aspects do we want to maximize? o How can these aspects be quantified in the same unit? o Are there different versions of the unit which can be maximized? o What is an acceptable region of percentages of MSY? o Propose names for the suggested MSY variants Sustainability o Which ecosystem aspects need to be specified in constraints to the sustainable arena? o Which economic aspects need to be specified in constraints? o Which social aspects need to be specified in constraints? o How is the status of these aspects linked to fishing? o How can we set guidelines for setting border between ‘acceptable’ and ‘unacceptable’? o How can we set guidelines for cases where some species are more sensitive than others and/or data poor? Management measures o What are the broad categories of possible management measures which can be used to ensure the MSY variants while remaining in the sustainable area? 4 Identifying acceptable and feasible MSY variants, constraints to sustainability and management measures. The workshop took place in regional groups discussing which indicators are relevant in each region and which are preferable to others. Regional groups were used to allow the analysis of differences between geographical areas. The regions used were: Baltic Sea, Mediterranean, North Sea, Western Waters and Widely ranging stocks (fig. 1). Widely ranging stocks are not a geographically distinct region such as the others as this ‘region’ contains stock which migrate or have a distribution covering several geographical regions. Fig.1. Regional groups (bold). In addition to these regions, the Widely Ranging Fish regional study covers stocks which are not confined to a single area. Italics indicate subregions within the region when the expertise present did not cover the entire region. The regional groups ranged in size from 9 to 13 persons (Appendix A). All groups covered scientific disciplines and fishing industry but only 2 groups had NGOs represented (Appendix C). All regional groups had representatives from the topic groups on ecosystem and economic concerns, all but two groups (Western Waters and Mediterranean) had representatives from the group on social and implementation concerns and all regional groups except the Widely Ranging group had representatives from the stock interaction group. At least three topic groups were represented in all regional groups. To facilitate the discussions and the documentation of conclusions, the project partners from Imperial College London prepared a specially designed graphical tool. The tool is programmed in Excel and lists the various conceivable MSY variants, tradeoffs/constraints, and management measures identified in the open discussion on the previous day. Workshop participants were asked to provide ratings (R) for each of the option and to document the degree of uncertainty or disagreement in the group (U) after deliberation of each option. For MSY variants and constraints, ratings and uncertainty where queried separately with respect to three aspects 5 (does necessary information exist, does the measure react to management and how preferable is it as an MSY variant or constraint). For management measures, only two aspects were queried (will it aid in attaining MSY variants and constraints and how preferable is it as an MSY variant or constraint). The graphical tool shows a plot of the distribution of ratings (fig. 2). It is particularly helpful in rating how preferable the MSY variants were as disagreement could be clearly indicated and each participant can see that their opinion was indicated in the spread: one participant can feel represented by the small green column whereas others find that their preference is indicated by yellow, orange or red columns (fig. 2). In addition, workshop participants were given the possibility to include verbal comments in the spreadsheets explaining their decisions or issues they encountered during their deliberations. Fig. 2. Graphical tool to record ratings. If the group rates an aspect ‘Very good’ and the uncertainty or disagreement is very low, the resulting distribution shows a large column in ‘Very good’ and a small column in ‘Good’ (top left). Keeping ‘U’ constant at ‘Very low’ while changing ‘R’ to ‘Medium’ (top right) or ‘Very poor’ (bottom left) retains the narrow distribution but shifts the mode towards the right. In contrast, increasing ‘U’ to ‘High’ leads to a large spread around ‘R’. The ratings were integrated automatically to derive an overall score for each option using an algorithm developed by John Mumford, Adrian Leach and Polina Levontin. This led to a systematic scoring and ranking of options based on the agreed assessment by workshop participants. Lastly, the worksheets were further evaluated by the partners from Imperial College London (Adrian Leach, John Mumford, and Hannah Norbury) to identify the options with the highest preferences for each regional group, the degree of agreement among regional groups, and the overall ranking. 6 Workshop instructions The regional workshops began by a round of introduction where each participant stated their name, affiliation and their top priority in fisheries management. If during discussions, new variants, constraints or management measures came up, these could be added to the list. Part 1: Identify a list of MSY variants and constraints which are acceptable and feasible in your region Go through the list of MSY variants and constraints determining for each measure: Is the understanding and general knowledge of this measure in your group great enough evaluation? Are the suggested MSY variants, constraints and management measures relevant in your area, i.e. is there anyone in the group who thinks that this measure could be relevant to take forward to further discussions? If the measure is relevant and sufficient knowledge existed in the group, the group proceeded to rating the measure. Else, the line was left blank, indicating why in the comments field. Next, measures were rated according to Availability How easy is it to use suggested MSY variants, constraints and management measures in practice in your area, i.e. does the necessary information exist in an accessible form? (R) Rate the uncertainty in the group with respect to the rating reflecting e.g. if the data are only available under some conditions, are of a poor quality or if the groups disagrees. (U) Descriptiveness How responsive is the suggested MSY variants, constraints and management measures to implemented management actions? (R) Rate the uncertainty in the group with respect to the rating reflecting e.g. if the measure will only respond under some conditions or if the groups disagrees. (U) Performance and level of disagreement Give each measure a score according to how preferable it would be to use this measure as a MSY target, constraint or management measure in your region (R) Give each measure a score according to how great the consensus was for the priority given to this measure in your region (U) Part 2: Evaluate the list of possible management measures 7 Rate each management measure according to Potential Impact Rate the potential impact of each measure on the success of achieving management objectives assuming that the measure is fully implemented (perfect compliance etc.). (R) Rate the uncertainty in the group with respect to the rating reflecting e.g. if the measure will only work under some climatic conditions or if the groups disagrees. (U) Implementation feasibility Rate the chances of full implementation of the management measure bearing in mind technical, economic, labour constraints etc. (R) Rate the uncertainty in the group with respect to the rating reflecting e.g. if the measure will only work under some conditions or if the groups disagrees. (U) Results Summary of questions raised after the first day of presentations to be considered in the subsequent workshop • The need to account for stochasticity: Use long term averages Long term averages had different meanings in different disciplines – in ecosystem considerations, 100 years was considered appropriate whereas in social science much shorter periods were considered long term. • Lack of clarity in definition of ‘manage stocks to obtain MSY’ F is much more appropriate than MSY or B as a management target. There are global differences in MSY MSY whether to interpret F as a limit or target. However, there is general agreement that management based MSY on F are more robust than strategies based on MSY or B . MSY MSY • Should we have an increase in exploitation above a certain (high) level? • Trade offs are unavoidable • Preservation of the ecosystem Impacts on the ecosystem are unavoidable during exploitation • What do we optimize? 8 Weight? Rent? Discount rates? Consumer surplus? • MSOY Is MSOY=MEY including upstream and downstream? or is MSOY= value from a societal perspective in 4x4 categories: Utility, Experiental, Future, Institutional value from a social, cultural, governance, ecological perspective? • Include ALL managers and stakeholders iteratively along the way Group discussion after workshop on identifying MSY variants, constraints to sustainability and management measures. The group work from the morning session was presented by each of the facilitators and summed up in the afternoon by Dave Reid and Anna Rindorf as background for the discussion. Summary of conclusions and some general observations Important points identified by all groups were: • Stability of resource and exploitation rates • Large (but not necessarily maximum) Yield (weight or value) using broad targets • Use of Ecosystem and Economic as constraints to MSY variant solutions • Participatory process at local level to ensure social constraints • Incorporate risk tolerance at the core of your management plan • Less micro management/keep it simple After this summary, Dave Reid and Anna Rindorf attempted to summarise the relationship between MSY variants and various aspects. These summaries initiated a large debate and are therefore given here as a report of what was presented, not as a consensus of the group. It was suggested that there was a difference in how fisheries management measures would be able to help achieve MMSY (MSY in a multispecies environment), MEY and MSOY objectives. Fisheries management would be the main driver in achieving MMSY. It could also help achieve MEY, but other factors (e.g. market conditions, fuel prices etc.) could also impact on economic yield, and could potentially reduce or eliminate any improvements in economic outputs derived from fishery management. The same is probably true for MSOY. Aspects like maintenance of coastal communities, or employment, could certainly be affected to some extent by fisheries management, but numerous other factors would be acting independently on these aspects, e.g. wider social policy, demographic changes etc. This is captured in fig. 3. It was suggested in discussion that “Social” objectives could be expected to change quite fast in relation to biological or economic objectives (fig. 4). Maintenance of rural communities for example could be a priority now, and of less importance in the near future. However, equally, objectives to limit crew injuries or deaths would be less likely to change rapidly. In addition to this, there was an observation that the number of people who needed to be consulted increased from MSY over MEY to MSOY. 9 Fig. 3. The relationship between MSY variants and the potential impact of fisheries management measures. Horizontal error thickness indicates the degree of correlation between the MSY variants. Fig. 4. Relationship between MSY variants and the stability over time of the measure. Horizontal error thickness indicates the degree of correlation between the MSY variants. 10
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