LAUSR

Abstract Spatial stock assessments have been developed to address violations of the dynamic pool assumption that the region to be assessed contains a single homogeneous stock. The possibility of such violation is often evident in data that suggest different trends in abundance or catch / survey age- / size-structure among areas that cannot be explained simply by the fishing history among areas. Currently, most stock assessments account for spatial structure using the ‘areas-as-fleets’ approach in which fishery or survey selectivity and catchability are assumed to differ spatially. However, several simulation studies suggest that adopting spatial approaches to stock assessment will improve estimation performance compared to the areas-as-fleets approach or ignoring spatial structure when conducting stock assessments, although at the cost of a larger number of estimable parameters. Spatial approaches to stock assessment and the provision of management advice have been available since the 1950s. However, spatial stock assessments only became adopted for management purposes in the 1990s, with the widespread adoption of the “integrated approach” to stock assessment, which allowed the use of multiple data sets for parameter estimation. The number of spatial stock assessments is now increasing rapidly. This paper outlines some of the key decisions that need to be made when conducting a spatial stock assessment (number of areas, how to model recruitment, movement, growth and dispersal, and model parameterization).