Abstract The El Nino Southern Oscillation (ENSO) produces global marine environment conditions that can cause changes in abundance and distribution of distant fish populations worldwide. Understanding mechanisms acting locally on fish population dynamics is crucial to develop forecast skill useful for fisheries management. The present work addresses the role played by ENSO on the round sardinella population biomass and distribution in the central-southern portion of the Canary Current Upwelling System (CCUS). A combined physical-biogeochemical framework is used to understand the climate influence on the hydrodynamical conditions in the study area. Then, an evolutionary individual-based model is used to simulate the round sardinella spatio-temporal biomass variability. According to model experiments, anomalous oceanographic conditions forced by El Nino along the African coast cause anomalies in the latitudinal migration pattern of the species. A robust anomalous increase and decrease of the simulated round sardinella biomass is identified in winter off the Cape Blanc and the Saharan coast region, respectively, in response to El Nino variations. The resultant anomalous pattern is an alteration of the normal migration between the Saharan and the Mauritanian waters. It is primarily explained by the modulating role that El Nino exerts on the currents off Cape Blanc, modifying therefore the normal migration of round sardinella in the search of acceptable temperature conditions. This climate signature can be potentially predicted up to six months in advance based on El Nino conditions in the Pacific.

中文翻译：

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厄尔尼诺现象是非洲西北部海岸圆形沙丁鱼分布的预测因子

摘要 厄尔尼诺南方涛动 (ENSO) 产生的全球海洋环境条件可能导致全球远洋鱼类种群的丰度和分布发生变化。了解当地作用于鱼类种群动态的机制对于开发对渔业管理有用的预测技能至关重要。目前的工作解决了 ENSO 在加那利洋流上升流系统 (CCUS) 中南部部分的圆形沙丁鱼种群生物量和分布中所起的作用。结合物理-生物地球化学框架用于了解气候对研究区水动力条件的影响。然后，使用基于进化个体的模型来模拟圆形沙丁鱼时空生物量变异性。根据模型实验，厄尔尼诺沿非洲海岸造成的异常海洋条件导致该物种的纬度迁徙模式异常。响应厄尔尼诺变化，在布兰克角和撒哈拉海岸地区的冬季分别发现模拟圆形沙丁鱼生物量的异常增加和减少。由此产生的异常模式是撒哈拉和毛里塔尼亚水域之间正常迁移的改变。这主要是由厄尔尼诺现象对布兰克角海流的调节作用来解释的，因此改变了圆形沙丁鱼在寻找可接受的温度条件时的正常迁移。根据太平洋的厄尔尼诺现象，可以提前六个月预测这种气候特征。