Predictive power and risk assessment for marine fisheries in Canada

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All fisheries exist within feedback systems that link harvest decisions to highly uncertain environment-fish stock dynamics. Failure rates of historical fishery management procedures, combined with the possibility that environment-stock interactions are changing faster than we can learn about them, raises concerns about our ability to accurately predict risks of future fishery failure. I propose research aimed at improving fishery models used to represent environment-stock interactions in fishery management strategy research. I will use (i) empirical analyses to test fishery model predictive power, (ii) empirical and simulation models to evaluate mechanistic hypotheses to explain changes in key population dynamics processes, and (iii) simulation of fishery management systems to identify how perceptions of risk depend on underlying model assumptions. Fishery system simulations integrating realistic ecological processes into fishery management planning will help identify critical knowledge gaps that affect risks in Canadian fisheries. Our broad selection of species will increase both the power of specific case studies and the broader relevance to management strategy evaluation research.