Can spawning origin information of catch or a recruitment penalty improve assessment and fishery management performance for a spatially structured stock assessment model?

Abstract

We used simulations based on lake whitefish (Coregonus clupeaformis) populations to explore the benefits of using spawning origin information for parsing catch to spawning populations in stock assessments for intermixed fisheries exhibiting an overlapping movement strategy. We compared this origin-informed assessment model with a standard assessment model that did not parse catch. We additionally evaluated the influence of including annual recruitment penalties. For standard assessment models, spawning stock biomass estimates could be unstable and biased (sometimes by more than 50%), depending upon population mixing and productivity, and in some cases estimated near average zero recruitment in the terminal year. Incorporating information on population-specific harvest age composition improved spawning stock biomass estimation (e.g., by sometimes essentially removing 50% biases and improving accuracy). Assessments with recruitment penalties produced less biased terminal recruitment estimates (sometimes a 100% bias was removed). Under status quo target mortality rates, improvements in assessments did not necessarily translate to improved fishery management performance (e.g., avoiding depletion of spawning biomass), but such improvements, and overall better performance, were seen at lower target mortality rates.