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<p>Spatially explicit and accurate resource assessment to inform management strategies is essential to the implementation of policies for sustainable fishery resources and fostering marine biodiversity. Considering data constraints and population variability characteristics, we developed a data-moderate coupled framework to improve resource assessment for small marine pelagic fishes. We combined the VAST (Vector autoregressive spatio-temporal) spatial analysis model with two assessment models (the marine fish Red-List assessment model-JARA and the stock assessment model-AMSY) into a framework (coupled VAST-JARA-AMSY) to better elucidate stock status and facilitate improved fisheries management strategies. We applied this framework to study the anchovy stock in the Bohai Sea. The spatio-temporal module in the model framework revealed that the stock was affected by multiple pressures (water temperature, regional climate indices, and fishing pressure) and distributional changes in the pattern of density hotspots, and provided accurate biomass indices and their standard errors as inputs to the JARA and AMSY modules. The outputs from JARA and AMSY indicated that the stock has recovered to sustainable levels in recent years. VAST also provided spatial habitat information for further interpretation of JARA and AMSY stock assessment results to support conservation of anchovy resources.</p>

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A coupled VAST-JARA-AMSY framework for understanding the spatio-temporal dynamics of small pelagic fishes and improving the accuracy of fisheries management

  • 期刊论文

  • 发表日期：

    2025年7月26日

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  • Qingpeng Han,
  • Xiujuan Shan,
  • Harry Gorfine,
  • Xianshi Jin,
  • Yunlong Chen

摘要

Spatially explicit and accurate resource assessment to inform management strategies is essential to the implementation of policies for sustainable fishery resources and fostering marine biodiversity. Considering data constraints and population variability characteristics, we developed a data-moderate coupled framework to improve resource assessment for small marine pelagic fishes. We combined the VAST (Vector autoregressive spatio-temporal) spatial analysis model with two assessment models (the marine fish Red-List assessment model-JARA and the stock assessment model-AMSY) into a framework (coupled VAST-JARA-AMSY) to better elucidate stock status and facilitate improved fisheries management strategies. We applied this framework to study the anchovy stock in the Bohai Sea. The spatio-temporal module in the model framework revealed that the stock was affected by multiple pressures (water temperature, regional climate indices, and fishing pressure) and distributional changes in the pattern of density hotspots, and provided accurate biomass indices and their standard errors as inputs to the JARA and AMSY modules. The outputs from JARA and AMSY indicated that the stock has recovered to sustainable levels in recent years. VAST also provided spatial habitat information for further interpretation of JARA and AMSY stock assessment results to support conservation of anchovy resources.