Spatial modeling of Bering Sea walleye pollock with integrated age-structured assessment models in a changing environment

Climate change may affect the spatial distribution of fish populations in ways that would affect the accuracy of spatially aggregated age-structured assessment models. To evaluate such scenarios, spatially aggregated models were compared with spatially explicit models using simulations. These scenarios were based on hypothetical climate-driven distribution shifts and reductions in mean recruitment of walleye pollock (Gadus chalcogrammus) in the eastern Bering Sea. Results indicate that biomass estimates were reasonably accurate for both types of estimation models and precision improved with the inclusion of tagging data. Bias in some aggregated model scenarios could be attributed to unaccounted-for process errors in annual fishing mortality rates and was reduced when estimating effective sample size or time-varying selectivity. Spatially explicit models that allow estimation of variability in movement and ontogenetic parameters (specified as a random walk process) were shown to be feasible, whereas models that misspecified ontogenetic movement and climate change effects resulted in biased biomass and movement parameter estimates. These results illustrate that more complex models may characterize processes better but may be less robust for management advice.