Abstract. International efforts to assess the status of marine ecosystems have been hampered by insufficient observations of food web interactions across many species, their various life stages, and geographic ranges. Hence, we collated data from multiple databases of fish stomach contents from samples taken across the North Atlantic and Arctic Oceans containing 944,129 stomach samples from larvae to adults, with 14,196 unique interactions between 227 predator species and 2158 prey taxa. We use these data to develop a data-driven, reproducible approach to classifying broad functional feeding guilds and then apply these to fish survey data from the Northeast Atlantic shelf seas to reveal spatial and temporal changes in ecosystem structure and functioning. In doing so, we construct predator-prey body size scaling models to predict the biomass of prey functional groups, e.g., zooplankton, benthos, and fish, for different predator species. These predictions provide empirical estimates of species- and size-specific feeding traits of fish, such as predator-prey mass ratios, individual prey mass, and the biomass contribution of different prey to predator diets. The functional groupings and feeding traits provided here help to further resolve our understanding of interactions within marine food webs and support the use of trait-based indicators in biodiversity assessments. The data used and predictions generated in this study are published on the Cefas Data Hub at: https://doi.org/10.14466/CefasDataHub.149 (Thompson et al., 2024).

中文翻译：

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北大西洋和北冰洋的鱼类功能群


摘要。由于对许多物种、其不同生命阶段和地理范围的食物网相互作用观察不足，国际上评估海洋生态系统状况的努力受到阻碍。因此，我们整理了从北大西洋和北冰洋采集的鱼胃内容物多个数据库的数据，其中包含从幼鱼到成鱼的 944,129 个胃样本，其中 227 个捕食者物种和 2158 个被捕食类群之间存在 14,196 种独特的相互作用。我们利用这些数据开发一种数据驱动的、可重复的方法来对广泛的功能性摄食协会进行分类，然后将其应用于东北大西洋陆架海域的鱼类调查数据，以揭示生态系统结构和功能的时空变化。在此过程中，我们构建了捕食者-被捕食者的体型大小缩放模型，以预测不同捕食者物种的被捕食者功能群的生物量，例如浮游动物、底栖动物和鱼类。这些预测提供了鱼类特定物种和大小的摄食性状的经验估计，例如捕食者-猎物质量比、个体猎物质量以及不同猎物对捕食者饮食的生物量贡献。这里提供的功能分组和摄食性状有助于进一步解决我们对海洋食物网内相互作用的理解，并支持在生物多样性评估中使用基于性状的指标。本研究中使用的数据和生成的预测发布在 Cefas 数据中心：https://doi.org/10.14466/CefasDataHub.149（Thompson 等人，2024）。