Irish Sea fisheries have undergone considerable change in recent years following the decline of commercially important finfish stocks and their slow response to management's recovery plans. In 2015, the fishing industry called for a holistic exploration into the impact of environmental change and food web effects to identify the drivers underpinning stock dynamics. In this study, we identify correlations between large‐scale climatic indicators, temperature, primary and secondary productivity, and fish recruitment in the Irish Sea and incorporate them into an Ecopath with Ecosim food web model co‐created by scientists and fishers. Negative correlations were found between the North Atlantic Oscillation winter index (NAOw) and large zooplankton abundance and between the Atlantic Multidecadal Oscillation (AMO) and the recruitment of cod (Gadus morhua) and whiting (Merlangius merlangus). Using correlation analyses to direct the addition of environmental drivers to the Irish Sea ecosystem model improved the models fit against observed biomass and catch data and revealed the indirect impacts of environmental change as mitigated through trophic interactions. Model simulations suggest that historic environmental change suppressed the overall production of commercial finfish, limiting opportunities for the fishing industry, whilst also dampening the rate of stock recovery despite marked reductions in fishing effort. These results suggest that failure to account for ecosystem information may lead to misconceived expectations and flawed fisheries management; therefore, there is a need to operationalize ecosystem information through management procedures to support fisheries advice.

中文翻译：

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追溯分析环境因素对爱尔兰海商业种群和捕鱼机会的影响

由于重要的有鳍鱼类种群减少以及对管理层恢复计划的反应缓慢，近年来爱尔兰海渔业发生了巨大变化。2015年，捕捞业呼吁对环境变化和食物网效应的影响进行全面探索，以找出支撑种群动态的驱动因素。在这项研究中，我们确定了爱尔兰海中大规模气候指标，温度，主要生产力和次要生产力以及鱼类招募之间的相关性，并将其纳入由科学家和渔民共同创建的Ecopath食物网络模型Ecopath中。在北大西洋涛动冬季指数（NAOw）与大型浮游动物丰度之间以及大西洋多年代涛动（AMO）与鳕鱼的募集之间发现负相关（Gadus morhua）和白垩纪（Merlangius merlangus）。使用相关分析将环境驱动因素直接添加到爱尔兰海生态系统模型中，可以改善模型与观测到的生物量和捕获数据的拟合度，并揭示通过营养相互作用减轻的环境变化的间接影响。模型模拟表明，历史性的环境变化抑制了商业有鳍鱼类的总体产量，限制了捕捞业的机会，尽管捕捞努力明显减少，但也抑制了种群恢复速度。这些结果表明，无法解释生态系统信息可能导致误解的期望和有缺陷的渔业管理；因此，需要通过管理程序来运作生态系统信息，以支持渔业咨询。