Analysing how fish populations and their ecological communities respond to perturbations such as fishing and environmental variation is crucial to fisheries science. Researchers often predict fish population dynamics using species‐level life‐history parameters that are treated as fixed over time, while ignoring the impact of intraspecific variation on ecosystem dynamics. However, there is increasing recognition of the need to include processes operating at ecosystem levels (changes in drivers of productivity) while also accounting for variation over space, time and among individuals. To address similar challenges, community ecologists studying plants, insects and other taxa increasingly measure phenotypic characteristics of individual animals that affect fitness or ecological function (termed “functional traits”). Here, we review the history of trait‐based methods in fish and other taxa, and argue that fisheries science could see benefits by integrating trait‐based approaches within existing fisheries analyses. We argue that measuring and modelling functional traits can improve estimates of population and community dynamics, and rapidly detect responses to fishing and environmental drivers. We support this claim using three concrete examples: how trait‐based approaches could account for time‐varying parameters in population models; improve fisheries management and harvest control rules; and inform size‐based models of marine communities. We then present a step‐by‐step primer for how trait‐based methods could be adapted to complement existing models and analyses in fisheries science. Finally, we call for the creation and expansion of publicly available trait databases to facilitate adapting trait‐based methods in fisheries science, to complement existing public databases of life‐history parameters for marine organisms.

中文翻译：

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实现基于特征的方法在推进渔业科学方面的潜力

分析鱼类种群及其生态群落如何应对捕鱼和环境变化等扰动对渔业科学至关重要。研究人员经常使用被视为随时间固定的物种水平生活史参数来预测鱼类种群动态，同时忽略种内变化对生态系统动态的影响。然而，人们越来越认识到需要包括在生态系统层面运行的过程（生产力驱动因素的变化），同时还要考虑空间、时间和个体之间的差异。为了应对类似的挑战，研究植物、昆虫和其他分类群的社区生态学家越来越多地测量影响健康或生态功能的个体动物的表型特征（称为“功能特征”）。这里，我们回顾了鱼类和其他分类群中基于特征的方法的历史，并认为通过将基于特征的方法整合到现有的渔业分析中，渔业科学可以看到好处。我们认为，测量和建模功能特征可以改进对人口和社区动态的估计，并快速检测对捕鱼和环境驱动因素的反应。我们使用三个具体的例子来支持这一说法：基于特征的方法如何解释人口模型中的时变参数；改进渔业管理和收获控制规则；并告知基于大小的海洋群落模型。然后，我们将逐步介绍如何采用基于特征的方法来补充渔业科学中的现有模型和分析。最后，