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Case study 3: Salmon Fisheries in the Baltic Sea

Introduction - Overview description of the case study

Description of the fishery, stocks and management system

Atlantic Salmon (Salmo salar) in the Baltic Sea is a long-migrating anadromous fish species, whose recruitment is strongly controlled by man. In 2004, a total of 7 million smolts initiated their sea migration either from natural reproduction (25%), occurring in about 40 rivers, or from hatchery releases (75%).

Three principal types of salmon fishery are engaged in the Baltic Sea: offshore, coastal and river. In the offshore fishery, driftnets (ODN) and long-lines (OLL) are used to capture feeding salmon in autumn and winter months (IX-V). In the coastal fishery, trap-nets (CTN), driftnets (CDN) and anchored coastal gillnets (CGN) are used to capture mature salmon returning to home rivers in spring and early summer (V-VII; in Poland up to mid XI). In the river fishery (RF), mainly recreational gear are used to exploit spawners.

Salmon fisheries are managed by TAC and by diverse technical measures. TAC measures aim to restrict catches in the offshore fishery, while time closures (sequential opening dates) are the main tool employed to control exploitation in the coastal fishery. The role of the TAC is to allocate salmon to the coastal fishery in the Gulf of Bothnia, and to the rivers in the Main Basin.

The overall management objective of IBSFC is to safeguard wild salmon stocks. Their operational objective is to increase the production of wild Baltic salmon to attain at least 50% of the natural production capacity of each river with current or potential production of salmon by 2010, while maintaining the catch levels as high as possible.

Salmon is likely the only species in the ICES advisory system, for which genetic risks are real, due to low population sizes and a high number of separate stock units, and the genetic aspect has not, to date, been taken into account in the management. Bayesian modelling of expert knowledge has demonstrated that current operational objectives are too uncertain to be used in tactical management, and a re-evaluation of the operational objectives is needed.

In 1992–1996, the M74 syndrome caused high mortality among yolk-sac fry of sea-run females. The incidence has been varying between 25 and 40% in the last three years. It is possible that the incidence of the syndrome continues to fluctuate rapidly, without any possibility of predicting its level. This poses a major risk to the health of the wild stocks.

The growth rate of salmon is linked to sprat biomass in the Baltic; as a result, their growth is impacted by multi-species factors. Growth rate has an impact on fishing mortality (due to gillnet selectivity), and on the probability to return to coast to unselective coastal trap-nets. Probabilistic run reconstruction models are needed to model these dependencies.

Both management tools and monitoring systems vary among salmon fisheries, and rely on multiple sources of information at international, national and local scales. The management tools are both national (opening dates in coastal fishery) and international (TAC), and the links between these tools must be taken into account in the analysis of management. This complex system requires computationally efficient analytical methodology if uncertainty is to be taken into account within a precautionary fisheries management framework (risk averse attitude).

In general, the management – assessment dependency has been described by the ICES Baltic Salmon and Trout working group (Anon. 2002) as follows: “the monitoring and assessment system should enable the monitoring of the status of the stocks and answers the management questions with adequate accuracy and reasonable costs”. The monitoring and assessment system should have at least the following features:

1) It should be able to evaluate the sustainability of current and future fishing, 2) It should have predictive power about the state of all wild stock components, and to take into account major uncertainties (like M74), 3) It should be able to quantify the extent to which the major management aims are achieved (safeguarding of all stock components).

Finding optimal balance between the assessment costs and accuracy is complicated by the fact that applying the precautionary approach implies that higher uncertainty should lead to a lower exploitation rate. In this sense, the definition of the required accuracy in the assessment is more of a management issue than purely a scientific decision. This philosophy is the background of the Baltic Salmon Case Study.

The main objective of the EFIMAS/COMMIT Salmon Case is to study the management – assessment dependency, and to find the optimal balance between the assessment costs and accuracy, in relation to management objectives.

Description of the base case and scenario evaluations

The base case OM includes a biological model that mirrors the biological model used in the ICES stock assessment working group (WGBAST), and functions for observation, assessment, advice, management, economic, and implementation including compliance.

The OM takes into account biological, economic and socio-economic uncertainties by running the operating model for a set of different scenarios. The following table provides an overview of the base case scenerio and the alternative scenerios considered.

Component Base case Alternative
Stock-recruit function Beverton-Holt Ricker
Natural mortality Normal Severe
Price Constant Elasticity
Costs Constant Increasing
Compliance Perfect Bad
Fishers behaviour Profit related CPUE related

Seven studies have been/will be carried out in relation to assessment/management scenario evaluations

Main analyses
1) Evaluation of the relative performance of potential management strategies with regard to management objectives, while taking into account the costs of the assessment and management system
2) Analysis of the impacts of different sources of uncertainty on the choice of alternative management approaches, in particular to identify those combinations of assessment and management actions that are robust to uncertainty

Sub-objectives
3) Analysis of alternative, river-specific biological reference points
4) Analysis of dependency of salmon productivity on environmental variables
5) Analysis of the impact of CPUE and price levels on the economic behaviour of the fishermen
6) Analysis of the total costs of assessment and management of salmon in Baltic countries
7) Analysis of the role of genetic stock identification in stock assessment

Description of approaches for scenario evaluations

Results (summary of scenario evaluations)

The main product of the CS is the complete and functional population dynamic OM for Baltic salmon in FLR (FLCore-version 2.0-2), constructed together with COMMIT-project. The OM is populated by probabilistic estimates of life history parameters and smolt abundances produced using the Bayesian Winbugs estimation model, and it produces future predictions e.g. for stock-specific smolt and spawner abundances, numbers of mature salmon migrating to the rivers, and wild and hatchery-reared catches by the different fisheries. Considerable progress has also been made in relation to the bio-economic modelling of Baltic salmon. The present bio-economic OM observes 4 countries with fishing fleets including 2-5 commercial fisheries using different gears. The economic data used to calibrate the model include price and fishing costs time series by country and by fishery. The model maximises the net present value (NPV) of salmon fishery, with fishing effort as the decision variable.

Approach 1 involves the evaluation of the relative performance of potential mgmt strategies with regard to management objectives, while taking into account the costs of the assessment and management system. The progress regarding this approach has been presented in two ICES-papers. The biological OM was applied by the Baltic Salmon and Sea-trout working group (WGBAST) in formulating their advice for 2007. Long-term stock projections for different Baltic salmon stocks were run for possible future levels of effort and fixed target levels of catch.

Approach 2 involves the analysis of the impacts of different sources of uncertainty on the choice of alternative management approaches, in particular to identify those combinations of assessment and management actions that are robust to uncertainty. Four different analyses that deal with this subject have been undertaken.

Approach 3 involves the calculation of separate MSY-based reference points (or conservation limits, CL) for 15 wild Atlantic salmon stocks within the Baltic Sea. These reference points provide a management alternative to the previous IBSFC reference points based on 50% of the remaining smolt production capacity. The recent progress regarding this approach has been described in the latest WG-report (WGBAST 2007). A scientific paper has been produced and is ready to be submitted.

Approach 4 involves the analysis of dependency of salmon productivity on environmental variables. The objective is to improve short-term predictions of the M74-syndrom (and potentially also those of post-smolt mortality), based on sprat stock predictions and relevant environmental variables and then to update the OM to facilitate the evaluation of alternative mgmt ref. points and HCR’s that take M74-risks into account based e.g. on the indices of sprat abundance. The relevant environmental data have been compiled, but the preliminary analyses indicated that this approach may not be a modelling priority in the CS. One important paper related to approach 4 has however been finalized. The paper explores how the M74 mortality affects the productivity and the stock-recruit relationship of the salmon stocks. The results have also been taken into account in the analysis of the river specific reference points.

Approach 5 involves the analysis of the impact of CPUE and price levels on the economic behaviour of the fishermen. Regarding this objective, a paper exploring the possible factors that have affected the fishing effort of Finnish, Swedish and Danish fishermen is in writing-up stage. In this paper non-linear regression models were applied to analyze times series of fishing effort, salmon catches, CPUE, salmon prices, gross productivity of catch per unit effort and TAC. The equations have been utilized in the development of teh bio-economic OM.

Approach 6 involves the estimation of the assessment and management costs of Baltic salmon, to be used in the evaluation of the performance and costs of different assessment-management alternatives (Approach 1). The available cost data have been compiled.

Approach 7 involves the analysis of the role of genetic stock identification in stock assessment. Present assessment of the exploitation rates of the wild Baltic salmon stocks relies on external tagging data (Carlin). Genetic stock mixture analyses (SMA) provide alternative data that could potentially reduce the uncertainty related to the estimates of exploitation rates and the surviving wild spawner abundances. The preliminary analyses confirmed the potential benefits of SMA-data, and the assessment model has been enhanced to allow the inclusion of the SMA data. However, so far these data have so far not been used in the assessment, partly due to new concerns about the uncertainties related to the genetic base-line sampling.

Dissemination

The biological OM was applied by the Baltic Salmon and Sea-trout working group (WGBAST) in formulating their advice for 2007. Long-term stock projections for different Baltic salmon stocks were run for possible future levels of effort and fixed target levels of catch.

In addition, the assessment models developed under EFIMAS have been used to provide the ICES advice on two special requests from the EU

  • with respect to the evaluation of the merits of DNA – analysis for stock assessment purposes and monitoring of fisheries impact on individual wild salmon stocks in the Baltic Sea area.
  • with respect to the development, evaluation and selection of new reference points for Baltic salmon stocks

Dissemination and References

Peer reviewed publications

Michielsens, C.G.J., Mäntyniemi, S. and Vuorinen, P.J. (2006). Estimation of annual mortality rates caused by Early Mortality Syndromes (EMS) and their impact on salmonid stock-recruit relationships. Canadian journal of fisheries and aquatic sciences, 63: 1968-1981.
Mäntyniemi, S. Romakkaniemi, A. and Arjas, Bayesian estimation of the number of individuals in a sample with a known weight. (Submitted).
Mäntyniemi, S. Bayesian population dynamics modelling: model specification, model checking and posterior computation. (Submitted).
Kulmala, S., Levontin, P., Lindroos, M., Michielsens, C., Pakarinen, T. and Kuikka, S. International management of the Atlantic salmon fishery in the Baltic Sea. (Submitted).
Michielsens, C.G.J., Dahl, J., Romakkaniemi, A., Pulkkinen, H., Karlsson, L. and Mäntyniemi, S. Precautionary biological reference points for Atlantic salmon (Salmo salar) stocks within the Baltic Sea. (to be submitted).

Other publications

Michielsens, C., Koljonen, M-L. and Mäntyniemi, S. (2004). The use of genetic stock identification results for the assessment of wild Baltic salmon stocks. Proceedings of the ICES Annual Science Conference, Vigo. ICES CM 2004/EE:03.
Levontin, P., McAllister, M. and Michielsens, C. (2004). Implications of semelparity assumption in modelling population dynamics of Atlantic salmon. Imperial College, London. Research document (part of a PhD thesis)
Levontin, P., McAllister, M. (2005). Evaluating management options for Baltic salmon (Salmo Salar) using bio-economic operating models in a generic simulation framework. Abstract only. Proceedings of the ICES Annual Science Conference, Aberdeen. ICES CM 2005/W:00.
Shivarov, A., Kulmala, S. and Lindroos, M. (2005). Fisheries management costs: The cost of Baltic salmon fisheries. University of Helsinki, Helsinki. Research Document.
Levontin, P., Kulmala, S., Lindroos, M., Michielsens, C. and McAllister, M. (2006). Evaluating fisheries management options for Atlantic salmon stocks (Salmo salar) in the Baltic Sea. Abstract only. Proceedings of the ICES symposium on management strategies: case studies of innovation, Galway. ICES SFMS 2006.
Kulmala, S., Levontin, P., Lindroos, M., Michielsens, C., Pakarinen, T. and S. Kuikka. International Management of the Atlantic Salmon Fishery in the Baltic Sea. University of Helsinki, Department of Economcis and Management, Discussion papers n:o 22, Environmental Economcis, Helsinki 2008 (Submitted)

Conference presentations

Michielsens, C., Koljonen, M-L. and Mäntyniemi, S. (2004). The use of genetic stock identification results for the assessment of wild Baltic salmon stocks. ICES Annual Science Conference, Vigo. Oral presentation.
Levontin, P., McAllister, M. (2005). Evaluating management options for baltic salmon (Salmo Salar) using bio-economic operating models in a generic simulation framework. ICES Annual Science Conference, Aberdeen. Oral presentation.
Levontin, P., Kulmala, S., Lindroos, M., Michielsens, C. and McAllister, M. (2006). Evaluating fisheries management options for Atlantic salmon stocks (Salmo salar) in the Baltic Sea. Symposium on management strategies: case studies of innovation, Galway. Oral presentation.
Kulmala, S., Lindroos, M. & Pintassilgo, P. Atlantic salmon fishery in the Baltic Sea - A case of trivial cooperation. Paper to be presented in the following conferences: European Association of Environmental and Resource Economists (EAERE) 25-28 June 2008, Gothenbourg and International Institute of Fisheries Economics and Trade (IIFET) 22-25 July 2008, Nha Trang, Vietnam.

Manuscripts in preparation

Grzebielec, R. Statistical analysis of the dependence of smolt production for Baltic salmon on SST and other climate variables in 1987-2006 by management units 1-4. EFIMAS Working paper (in writing-up phase).
Grzebielec, R. Post-smolt survival of wild salmon in relation to SST and other environmental factors. EFIMAS Working paper (in writing-up phase)
Jounela, P. and P. Suuronen. Introducing preseason forecasts for coastal salmon run in the northern Baltic Sea. (Manuscript).

  • Delivery Matrix by April 2006 (Note: See text from Meeting Minutes WP4 from EFIMAS Maastricht Meetings, September 2006). Case Study 3 Delivery Matrix

Links to Other Work

The work has been carried out in close cooperation with EU-project COMMIT. Also, the work uses data provided from ICES Baltic Salmon and Trout Assessment Working Group (WGBAST).

Acknowledgements

EFIMAS Contribution to the work

The Case Study 3 is common for EU FP6 projects EFIMAS and COMMIT, and especially the development of the OM (Approach 1) has been shared between these two projects. The work related to Approaches 2-7 has mainly been performed under EFIMAS, in cooperation with the ICES Baltic Salmon and Trout Assessment Working Group (WGBAST).

Of all the work done so far in the Baltic Salmon Case Study, about 75% has been performed in COMMIT and 25% in EFIMAS, whereas the opposite applies to the work done in relation to the specific objectives in EFIMAS.

In the References section, all the publications produced in the Salmon Case Study have been detailed by project (EFIMAS and COMMIT).

Participants

Coordinator: Matti Salminen

Participants:

Atso Romakkaniemi FGFRI Finland
Catherine Michielsens FGFRI Finland
Henni Pulkkinen FGFRI Finland
Frank Ivan Hansen DIFRES Denmark
Ingemar Perä NBF Sweden
Jan Horbowy SFI Poland
Jonas Dahl NBF Sweden
Lars Karlsson NBF Sweden
Marja-Liisa Koljonen FGFRI Finland
Marko Lindroos UHEL Finland
Matti Salminen FGFRI Finland
Murdoch McAllister IC UK
Per J. Sparre DIFRES Denmark
Polina Levontin IC UK
Rasmus Nielsen DIFRES Denmark
Richard Hillary IC UK
Ryszard Grzebielec SFI Poland
Samu Mäntyniemi UHEL Finland
 
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