Panmictic Panacea? Demonstrating Good Practices for Developing Spatial Stock Assessments Through Application to Alaska Sablefish (Anoplopoma fimbria)

Abstract

Marine species and associated fisheries demonstrate complex spatial dynamics driven by biological, ecosystem and socioeconomic factors and integrating these spatial dynamics into stock assessment models can improve fishery management advice. While preliminary good practices for developing spatial stock assessment models have been proposed, comprehensive demonstrations applying these practices remain limited. Drawing on these good practices, we provide an end‐to‐end demonstration of developing a spatial stock assessment using Alaska sablefish (Anoplopoma fimbria). Our demonstration emphasises the utility of high‐resolution data analysis and conceptual models for informing key model structure decisions, the joint development of spatial and spatially‐aggregated models to enhance understanding of population dynamics, and the need for further guidance on integrating tagging data and diagnostic tools in spatial assessments. Spatial models highlighted regional differences in sablefish biomass, recruitment and age structure, but total population estimates generally aligned with outputs from spatially aggregated models. Moreover, the spatial model identified ontogenetic movement patterns for this highly mobile species. Overall, the spatially aggregated model for Alaska sablefish is likely adequate for management advice, but periodic spatial model updates could offer insights into spatial dynamics and regional depletion levels. Thus, we recommend concomitant use of both models: spatially aggregated models for informing population‐wide status, and spatial models for informing spatial fishery dynamics and local depletion. The sablefish application represents one of the first implementations of a spatial stock assessment using recently proposed good practices, serving as a valuable guide for future practitioners by underscoring critical decision points and analyses to address them when developing spatial stock assessments.