Ecosystem models for fisheries management: finding the sweet spot |
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| Authors: | Jeremy S Collie Louis W Botsford Alan Hastings Isaac C Kaplan John L Largier Patricia A Livingston Éva Plagányi Kenneth A Rose Brian K Wells Francisco E Werner |
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| Institution: | 1. Graduate School of Oceanography, University of Rhode Island, Narragansett, RI, USA;2. Wildlife, Fish and Conservation Biology, University of California Davis, Davis, CA, USA;3. Environmental Science and Policy, University of California, Davis, CA, USA;4. Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA;5. Bodega Marine Laboratory, University of California Davis, Bodega Bay, CA, USA;6. NOAA Fisheries, Alaska Fisheries Science Center, Seattle, WA, USA;7. CSIRO Wealth from Oceans Flagship, Brisbane, Qld, Australia;8. Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge, LA, USA;9. Fisheries Ecology Division, Southwest Fisheries Science Center, National Marine Fisheries Service, Santa Cruz, CA, USA;10. Southwest Fisheries Science Center, National Marine Fisheries Service, La Jolla, CA, USA |
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| Abstract: | The advent of an ecosystem‐based approach dramatically expanded the scope of fisheries management, creating a critical need for new kinds of data and quantitative approaches that could be integrated into the management system. Ecosystem models are needed to codify the relationships among drivers, pressures and resulting states, and to quantify the trade‐offs between conflicting objectives. Incorporating ecosystem considerations requires moving from the single‐species models used in stock assessments, to more complex models that include species interactions, environmental drivers and human consequences. With this increasing model complexity, model fit can improve, but parameter uncertainty increases. At intermediate levels of complexity, there is a ‘sweet spot’ at which the uncertainty in policy indicators is at a minimum. Finding the sweet spot in models requires compromises: for example, to include additional component species, the models of each species have in some cases been simplified from age‐structured to logistic or bioenergetic models. In this paper, we illuminate the characteristics, capabilities and short‐comings of the various modelling approaches being proposed for ecosystem‐based fisheries management. We identify key ecosystem needs in fisheries management and indicate which types of models can meet these needs. Ecosystem models have been playing strategic roles by providing an ecosystem context for single‐species management decisions. However, conventional stock assessments are being increasingly challenged by changing natural mortality rates and environmentally driven changes in productivity that are observed in many fish stocks. Thus, there is a need for more tactical ecosystem models that can respond dynamically to changing ecological and environmental conditions. |
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| Keywords: | ecosystem‐based management fisheries marine model complexity trade‐off |
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