Model uncertainty in the ecosystem approach to fisheries |
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| Authors: | Simeon L Hill George M Watters ré E Punt Murdoch K McAllister Corinne Le Quéré John Turner |
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| Institution: | British Antarctic Survey, Natural Environment Research Council, High Cross, Madingley Road, Cambridge CB3 0ET, UK;;Southwest Fisheries Science Center, NOAA Fisheries, Protected Resources Division, 1352 Lighthouse Avenue, Pacific Grove, CA 93950, USA;;USA School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195-5020, USA;;CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tas. 7001, Australia;;Fisheries Centre, University of BC, AERL, 2202 Main Mall, Vancouver, BC, Canada V6T 1Z4;;School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, UK |
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| Abstract: | Fisheries scientists habitually consider uncertainty in parameter values, but often neglect uncertainty about model structure, an issue of increasing importance as ecosystem models are devised to support the move to an ecosystem approach to fisheries (EAF). This paper sets out pragmatic approaches with which to account for uncertainties in model structure and we review current ways of dealing with this issue in fisheries and other disciplines. All involve considering a set of alternative models representing different structural assumptions, but differ in how those models are used. The models can be asked to identify bounds on possible outcomes, find management actions that will perform adequately irrespective of the true model, find management actions that best achieve one or more objectives given weights assigned to each model, or formalize hypotheses for evaluation through experimentation. Data availability is likely to limit the use of approaches that involve weighting alternative models in an ecosystem setting, and the cost of experimentation is likely to limit its use. Practical implementation of an EAF should therefore be based on management approaches that acknowledge the uncertainty inherent in model predictions and are robust to it. Model results must be presented in ways that represent the risks and trade‐offs associated with alternative actions and the degree of uncertainty in predictions. This presentation should not disguise the fact that, in many cases, estimates of model uncertainty may be based on subjective criteria. The problem of model uncertainty is far from unique to fisheries, and a dialogue among fisheries modellers and modellers from other scientific communities will therefore be helpful. |
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| Keywords: | Bayesian methods ecosystem approach to fisheries ecosystem models fisheries management model uncertainty operational management procedures |
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