Management strategy analysis for multispecies fisheries, including technical interactions and human behavior in modelling management decisions and fishing

A multispecies fishery management strategy evaluation (MSE) framework based on the example of the groundfish fishery in the Bering Sea and Aleutian Islands region of Alaska was used to examine the interplay between a bycatch species and three groundfish species. The study introduces a framework for a realistic multispecies fishery MSE by accounting for fleet dynamics, multispecies fishery quota allocation, and the temporal dynamics of technical interactions. The quota allocation and the fleet dynamics models were implemented using linear programming, and regression approaches were used to realistically project future users’ behavioral response to changes in the fishery. Models were calibrated and then validated using historical and out-of-sample data, respectively. The results highlight the importance of accounting for technical interactions and their inter-annual dynamics for both quota allocation and fleet dynamics to design a realistic multispecies fishery MSE (without them, the amount of lost yield in...

[1]  J. Wilen,et al.  Dissecting the tragedy: A spatial model of behavior in the commons , 2011 .

[2]  D. L. Alverson,et al.  By-Catch: Problems and Solutions , 2000 .

[3]  James N. Ianelli,et al.  Incorporating predation interactions in a statistical catch-at-age model for a predator-prey system in the eastern Bering Sea , 2005 .

[4]  Stéphanie Mahévas,et al.  Regional metier definition: a comparative investigation of statistical methods using a workflow applied to international otter trawl fisheries in the North Sea , 2012 .

[5]  B. Fadely,et al.  Alaska marine mammal stock assessments, 2015 , 2012 .

[6]  N. Daan,et al.  Multispecies models relevant to management of living resources , 1990 .

[7]  André E. Punt,et al.  Drawing the lines: resolving fishery management units with simple fisheries data , 2009 .

[8]  David C. Smith,et al.  Lessons in modelling and management of marine ecosystems: the Atlantis experience , 2011 .

[9]  W. Patrick,et al.  Estimating the economic impacts of bycatch in U.S. commercial fisheries , 2013 .

[10]  K. Schnier,et al.  Common property, information, and cooperation: Commercial fishing in the Bering Sea , 2009 .

[11]  Vera Alexander,et al.  Oceanography of the eastern Bering Sea ice‐edge zone in spring1 , 1981 .

[12]  William H. Press,et al.  Numerical Recipes 3rd Edition: The Art of Scientific Computing , 2007 .

[13]  C. Walters,et al.  Quantitative fisheries stock assessment: Choice, dynamics and uncertainty , 2004, Reviews in Fish Biology and Fisheries.

[14]  Anthony D. M. Smith,et al.  Implementing effective fisheries-management systems – management strategy evaluation and the Australian partnership approach , 1999 .

[15]  Alan M. Springer,et al.  The Bering Sea Green Belt: shelf-edge processes and ecosystem production , 1996 .

[16]  Kirstin K. Holsman,et al.  A comparison of fisheries biological reference points estimated from temperature-specific multi-species and single-species climate-enhanced stock assessment models , 2016 .

[17]  Alan Haynie,et al.  Stock Assestment and Fishery Evaluation Report for the Groundfishes Fisheries of the Gulf of Alaska and Bering Sea/Aleutian Island Area : Economic Status of the Groundfish Fisheries off Alaska, 2006 , 1999 .

[18]  Hilaire Drouineau,et al.  Evaluation of the bio-economic sustainability of multi-species multi-fleet fisheries under a wide range of policy options using ISIS-Fish , 2009 .

[19]  S. J. Cripps,et al.  Defining and estimating global marine fisheries bycatch , 2009 .

[20]  Ray Hilborn,et al.  Institutions, incentives and the future of fisheries , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[21]  A. Haynie,et al.  Empirical Models of Fisheries Production: Conflating Technology with Incentives? , 2017, Marine Resource Economics.

[22]  André E. Punt,et al.  Management strategy evaluation: best practices , 2016 .

[23]  J. Ianelli,et al.  Assessment of the yellowfin sole stock in the Bering Sea and Aleutian Islands , 2016 .

[24]  Arni Magnusson,et al.  What makes fisheries data informative , 2007 .

[25]  N. Bunnefeld,et al.  Management strategy evaluation: a powerful tool for conservation? , 2011, Trends in ecology & evolution.

[26]  S. Döbert.  Status and Future Prospects of CLIC , 2008 .

[27]  P. Rousseeuw.  Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[28]  G. Thompson.  Assessment of the Pacific Cod Stock in the Eastern Bering Sea , 2016 .

[29]  H. Johnson,et al.  A comparison of 'traditional' and multimedia information systems development practices , 2003, Inf. Softw. Technol..

[30]  R. Hilborn,et al.  Rebuilding Global Fisheries , 2009, Science.

[31]  Alan C. Haynie,et al.  Hidden Flexibility: Institutions, Incentives, and the Margins of Selectivity in Fishing , 2015, Land Economics.

[32]  Peter T. Kuriyama,et al.  Catch shares have not led to catch-quota balancing in two North American multispecies trawl fisheries , 2016 .

[33]  HilbornRay,et al.  How does species association affect mixed stock fisheries management? A comparative analysis of the effect of marine protected areas, discard bans, and individual fishing quotas , 2013 .

[34]  André E. Punt,et al.  The importance of length and age composition data in statistical age-structured models for marine species , 2015 .

[35]  Philippe Grosjean,et al.  FLR: an open-source framework for the evaluation and development of management strategies , 2007 .

[36]  Jt T. Finn,et al.  Optimal Effort Allocation Among Competing Mixed-Species Fisheries, Subject to Fishing Mortality Constraints , 1986 .

[37]  M. Ives,et al.  A bio-economic management strategy evaluation for a multi-species, multi-fleet fishery facing a world of uncertainty , 2013 .