A Bayesian decision analysis to set escapement goals for Fraser River sockeye salmon (Oncorhynchus nerka)

This paper illustrates a complete Bayesian decision analysis for evaluating multistock harvest goals in the fishery on Fraser River sockeye salmon (On corhynchus nerka). We identify four key steps necessary to assess a resourc e production system. Each step entails choices that can alter the perceived consequences of management decisions. A Markov chain Monte Carlo sample ca ptures uncertainty in the population dynamics. The Bayesian formalism then translates this uncertainty into uncertain policy outcomes. We examine a re latively simple control law, designed to protect stocks at low abundance. W e restrict our attention to retrospective policy analysis by investigating what might have happened to sockeye stocks if management had proceeded diff erently during years for which historical data are available. A formal obje ctive function quantifies societal values associated with a range of policy options. To confine the paper to manageable scope, we consider only relati vely simple assumptions. Our analytical framework offers an iterative route to policy design, where managers play an active role in formulating policy options and evaluating their consequences.