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Defining spatial structure for fishery stock assessment
Journal article   Open access   Peer reviewed

Defining spatial structure for fishery stock assessment

Steven X. Cadrin
Fisheries research, Vol.221, p.105397
01/2020

Abstract

Interdisciplinary stock identification Spatial structure Stock assessment
•The spatial extent of stock assessment should reflect the fished population, and major patterns of heterogeneity should be represented.•Ignoring spatial structure can lead to major failures in stock assessment and fisheries management.•Best practice for defining appropriate spatial structure involves interdisciplinary stock identification and simulation testing. In principle, the spatial extent of fishery stock assessment should reflect the biological population, and major fishing patterns or population heterogeneity within the area should be represented. However, these theoretical requirements are commonly dismissed in practice, often when there is compelling evidence that spatial scope and structure is mis-specified and without testing if the mis-specified model performs well for informing fishery management. Population dynamics theory, case studies in fishery management as well as simulation tests demonstrate that accurately accounting for spatial structure in stock assessments can improve model performance, and ignoring spatial structure can lead to misperceptions of stock status and failures in fisheries management. Therefore, the development of stock assessment applications should include an evaluation of the most appropriate spatial scope and structure. Some common challenges in defining and modeling spatial structure can be addressed by adopting general best practices, but each species and its fisheries are unique. Accordingly, determining the most appropriate spatial structure involves 1) an interdisciplinary synthesis of all available information to determine the most plausible paradigms of population structure and fishing patterns, 2) the development of spatial operating models that are conditioned on these paradigms, and 3) testing the performance of estimation models and management strategies that are based on the current spatial management unit as well as alternative spatial scopes and structures that reflect population structure and fishing patterns.

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