The northern Bering Sea is transitioning from an Arctic to subarctic fish community as climate warms. Scientists and managers aim to understand how these changing conditions are influencing fish biomass and spatial distribution in this region, as both are used to inform stock assessments and fisheries management advice. Here, we use a spatio‐temporal model for walleye pollock (Gadus chalcogrammus) to provide two inputs to its stock assessment model: (a) an alternative model‐based biomass index and (b) alternative model‐based age compositions. Both inputs were derived from multiple fishery‐independent data that span different regions of space and time. We developed an assessment model that utilizes both the standard and model‐based inputs from multiple surveys despite inconsistencies in spatial and temporal coverage, and we found that using these data provide an improved spatial and temporal scope of total pollock biomass. Age composition information indicated that pollock density is increasing and moving farther north, particularly for older pollock. We found that including an index of cold pool extent could be used to extrapolate pollock densities in the northern Bering Sea in unsampled years. Stock assessment parameter estimates were similar for standard and model‐based input. This study demonstrates that spatio‐temporal model‐based estimates of a biomass index and age composition can facilitate rapid changes in stock assessment structure in response to climate‐driven shifts in spatial distribution. We conclude that assimilating data from regions neighboring standard survey areas, such as the Chukchi Sea and western Bering Sea, would improve understanding and management efforts as fish distributions change under a warming climate.

中文翻译：

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使用基于模型的指数和年龄组成来适应气候驱动的分布变化，这些条件是来自角膜白斑鳕（Gadus chalcogrammus）种群评估中的多次调查

随着气候变暖，白令海北部正在从北极鱼过渡到北极鱼。科学家和管理人员旨在了解这些不断变化的条件如何影响该地区的鱼类生物量和空间分布，因为两者都可用于提供种群评估和渔业管理建议。在这里，我们使用时空模型对角膜白斑鳕（Gadus chalcogrammus）为其库存评估模型提供两个输入：（a）基于模型的替代生物量指数和（b）基于模型的替代年龄组成。两种输入均来自跨时空不同区域的多个与渔业无关的数据。尽管空间和时间覆盖范围不一致，我们开发了一种评估模型，该模型利用了来自多个调查的标准输入和基于模型的输入，并且我们发现使用这些数据可改善狭鳕总生物量的时空范围。年龄构成信息表明，鳕鱼密度正在增加并向北移动，特别是对于较老的鳕鱼。我们发现，在未采样的年份中，可以使用包括冷池范围的指数来推断白令海北部的鳕鱼密度。标准和基于模型的输入的库存评估参数估计值相似。这项研究表明，基于时空模型的生物量指数和年龄组成的估计可以促进种群评估结构快速变化，以应对气候驱动的空间分布变化。我们得出的结论是，在气候变暖的情况下，随着鱼类分布的变化，从邻近标准调查区（例如楚科奇海和白令海）收集的数据将改善理解和管理工作。