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Management strategy evaluation using the individual-based, multispecies modeling approach OSMOSE

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  • Grüss, Arnaud
  • Harford, William J.
  • Schirripa, Michael J.
  • Velez, Laure
  • Sagarese, Skyler R.
  • Shin, Yunne-Jai
  • Verley, Philippe

Abstract

End-to-end ecosystem modeling platforms, including OSMOSE, are key tools for informing ecosystem-based fisheries management (EBFM). End-to-end models ideally implement two-way interactions between model components, yet two-way interactions between high trophic level (HTL) functional groups and humans (fisheries managers and fishers) are currently missing in OSMOSE. We developed a management strategy evaluation (MSE) framework for OSMOSE, which allows for feedback between HTL functional groups and fisheries managers. This framework couples OSMOSE to a management procedure integrating decision rules and accounting for scientific uncertainty and the acceptable risk of overfishing. We applied the MSE framework to the OSMOSE model of the West Florida Shelf, so as to conduct an evaluation of total allowable catch (TAC) strategies for red grouper (Epinephelus morio) in a context of episodic events of natural mortality. Our simulations indicate that TAC strategies that assume higher scientific uncertainty and/or lower acceptable risk of overfishing result in higher biomass-related metrics for red grouper. However, the levels of scientific uncertainty and acceptable risk of overfishing impose a trade-off between biomass-related and catch-related metrics for red grouper. Our simulations also indicate that updating red grouper TAC more frequently in a context of episodic events of natural mortality does not have a large impact on biomass-related and catch-related metrics for red grouper and other functional groups. The MSE we conducted for red grouper is strategic, and its outcomes, which were obtained under a specific set of assumptions, must be considered preliminary. We discuss how future research could help enhance understanding of the possible impacts of TAC strategies for red grouper. The MSE framework designed for OSMOSE links the dynamics of HTL functional groups to that of fisheries managers, thereby allowing OSMOSE to be better suited for informing EBFM. This framework is an invaluable asset in assessing the performance of fisheries management strategies, but could also be used for other purposes, such as the evaluation of research monitoring programs.

Suggested Citation

  • Grüss, Arnaud & Harford, William J. & Schirripa, Michael J. & Velez, Laure & Sagarese, Skyler R. & Shin, Yunne-Jai & Verley, Philippe, 2016. "Management strategy evaluation using the individual-based, multispecies modeling approach OSMOSE," Ecological Modelling, Elsevier, vol. 340(C), pages 86-105.
    • Handle: RePEc:eee:ecomod:v:340:y:2016:i:c:p:86-105
    DOI: 10.1016/j.ecolmodel.2016.09.011
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    References listed on IDEAS

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    1. Steenbeek, Jeroen & Buszowski, Joe & Christensen, Villy & Akoglu, Ekin & Aydin, Kerim & Ellis, Nick & Felinto, Dalai & Guitton, Jerome & Lucey, Sean & Kearney, Kelly & Mackinson, Steven & Pan, Mike & , 2016. "Ecopath with Ecosim as a model-building toolbox: Source code capabilities, extensions, and variations," Ecological Modelling, Elsevier, vol. 319(C), pages 178-189.
    2. Daniel S. Holland, 2010. "Management Strategy Evaluation and Management Procedures: Tools for Rebuilding and Sustaining Fisheries," OECD Food, Agriculture and Fisheries Papers 25, OECD Publishing.
    3. Elizabeth A Fulton & Anthony D M Smith & David C Smith & Penelope Johnson, 2014. "An Integrated Approach Is Needed for Ecosystem Based Fisheries Management: Insights from Ecosystem-Level Management Strategy Evaluation," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-16, January.
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    Cited by:

    1. Grüss, Arnaud & Palomares, Maria L.D. & Poelen, Jorrit H. & Barile, Josephine R. & Aldemita, Casey D. & Ortiz, Shelumiel R. & Barrier, Nicolas & Shin, Yunne-Jai & Simons, James & Pauly, Daniel, 2019. "Building bridges between global information systems on marine organisms and ecosystem models," Ecological Modelling, Elsevier, vol. 398(C), pages 1-19.
    2. Xing, Lei & Zhang, Chongliang & Chen, Yong & Shin, Yunne-Jai & Verley, Philippe & Yu, Haiqing & Ren, Yiping, 2017. "An individual-based model for simulating the ecosystem dynamics of Jiaozhou Bay, China," Ecological Modelling, Elsevier, vol. 360(C), pages 120-131.
    3. Xing, Lei & Chen, Yong & Zhang, Chongliang & Li, Bai & Tanaka, Kisei R. & Boenish, Robert & Ren, Yiping, 2020. "Evaluating impacts of imprecise parameters on the performance of an ecosystem model OSMOSE-JZB," Ecological Modelling, Elsevier, vol. 419(C).

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