State-Space Production Models and Graphical Methods for Assessing and Communicating the Status of the Lake Nipigon Whitefish (Coregonus clupeaformis) Fishery

A series of alternative state-space surplus production models were used to estimate biological reference points, i.e., F_MSY and B_MSY, and their uncertainty, for the Lake Nipigon lake whitefish fishery. We estimated the historic and current status of this fishery and found that both the reference point estimates and stock status were highly uncertain. We also developed a graphical Bayesian inference approach to improve communication about the status of the fishery among stakeholders and managers. Parameter estimates and stock status were highly sensitive to the priors, and the catch and CUE time series used in the analysis. DIC was used to rank the models and model predictive ability was assessed using Bayesian p-values. All four models were found to be plausible; therefore, a Bayesian decision network model of the fishery was used to estimate and rank the value of information (in terms of trade-offs between ecological and economic risk) associated with these alternative hypotheses about the population dynamics.  The results indicated that the VoI about the population dynamics was high at 18% of the maximum expect value of annual profits. Options to reduce stock status uncertainty to more acceptable levels are discussed.