The International Union for Conservation of Nature's (IUCN) Red List is the global standard for quantifying extinction risk but assessing population reduction (criterion A) of wide‐ranging, long‐lived marine taxa remains difficult and controversial. We show how Bayesian state–space models (BSSM), coupled with expert knowledge at IUCN Red List workshops, can combine regional abundance data into indices of global population change. To illustrate our approach, we provide examples of the process to assess four circumglobal sharks with differing temporal and spatial data‐deficiency: Blue Shark (Prionace glauca), Shortfin Mako (Isurus oxyrinchus), Dusky Shark (Carcharhinus obscurus), and Great Hammerhead (Sphyrna mokarran). For each species, the BSSM provided global population change estimates over three generation lengths bounded by uncertainty levels in intuitive outputs, enabling informed decisions on the status of each species. Integrating similar analyses into future workshops would help conservation practitioners ensure robust, consistent, and transparent Red List assessments for other long‐lived, wide‐ranging species.

中文翻译：

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估算IUCN红色名录中的种群减少：JARA-一种应用于远洋鲨鱼的决策支持工具

国际自然保护联盟（IUCN）红色名录是量化灭绝风险的全球标准，但是评估范围广泛，寿命长的海洋生物分类的种群减少（标准A）仍然是困难且有争议的。我们将在IUCN红色清单研讨会上展示贝叶斯状态空间模型（BSSM）以及专家知识如何将区域丰度数据组合为全球人口变化指数。为了说明我们的方法，我们提供了评估具有不同时空数据缺失的四种外接鲨的过程的示例：蓝鲨（Prionace glauca），短鳍鲨（Isurus oxyrinchus），昏暗鲨（Carcharhinus obscurus）和大锤头（Great Hammerhead）Sphyrna mokarran）。对于每个物种，BSSM在直观输出中以不确定性水平为界，提供了三代人的全球人口变化估计值，从而能够就每个物种的状态做出明智的决定。将类似的分析整合到未来的研讨会中，将有助于保护从业人员确保对其他长寿，大范围物种进行可靠，一致和透明的红色名录评估。