Abstract：
Predicting species distribution in the ocean has become a crucial task to assess marine ecosystem responses to ongoing climate change. In the Humboldt Current System (HCS), the endemic copepod Calanus chilensis is one of the key species bioindicator of productivity and water masses. Here we modeled the geographic distribution of Calanus chilensis for two bathymetric ranges, 0-200 and 200-400 m. For the 0-200 m layer, we used the Bayesian Additive Regression Trees (BART) method, whereas, for the 200-400 m layer, we used the Ensembles of Small Models (ESMs) method and then projected the models into two future scenarios to assess changes in geographic distribution patterns. The models were evaluated using the multi-metric approach. We identified that chlorophyll-a (0.34), Mixed Layer Depth (0.302) and salinity (0.36) explained the distribution of C. chilensis. The geographic prediction of the BART model revealed a continuous distribution from Ecuador to the southernmost area of South America for the 0-200 m depth range, whereas the ESM model indicated a discontinuous distribution with greater suitability for the coast of Chile for the 200-400 m depth range. A reduction of the distribution range of C. chilensis is projected in the future. Our study suggests that the distribution of C. chilensis is conditioned by productivity and mesoscale processes, with both processes closely related to upwelling intensity. These models serve as a tool for proposing indicators of changes in the ocean. We further propose that the species C. chilensis is a high productivity and low salinity indicator at the HCS. We recommend further examining multiple spatial and temporal scales for stronger inference.
摘要：
预测海洋中的物种分布已成为评估海洋生态系统对持续气候变化响应的关键任务。在洪堡电流系统(HCS)中，特有co足类Calanuschilensis是生产力和水团的关键生物指示物种之一。在这里，我们对两个测深范围的Calanuschilensis的地理分布进行了建模，0-200和200-400m。对于0-200m层，我们使用贝叶斯加性回归树(BART)方法，然而,对于200-400米的层，我们使用小型模型集合（ESM）方法，然后将模型预测到两个未来场景中，以评估地理分布模式的变化。使用多度量方法对模型进行了评估。我们确定叶绿素a(0.34)，混合层深度（0.302）和盐度（0.36）解释了C.chilensis的分布。BART模型的地理预测揭示了从厄瓜多尔到南美最南端的0-200m深度范围的连续分布，而ESM模型表明不连续分布，对于200-400m深度范围的智利海岸具有更大的适用性。预计将来会减少C.chilensis的分布范围。我们的研究表明，辣椒的分布受生产力和中尺度过程的制约，这两个过程都与上升流强度密切相关。这些模型是提出海洋变化指标的工具。我们进一步建议C.chilensis物种是HCS的高生产率和低盐度指标。我们建议进一步检查多个时空尺度，以获得更强的推断。
