Ecosystems are increasingly impacted by human activities, altering linkages among physical and biological components. Spatial community reassembly occurs when these human impacts modify the spatial overlap between system components, and there is need for practical tools to forecast spatial community reassembly at landscape scales using monitoring data. To illustrate a new approach, we extend a generalization of empirical orthogonal function (EOF) analysis, which involves a spatio‐temporal ecosystem model that approximates coupled physical, biological and human dynamics. We then demonstrate its application to five trophic levels for the eastern Bering Sea by fitting to multiple, spatially unbalanced datasets measuring physical characteristics (temperature measurements and climate‐linked forecasts), primary producers (spring and fall size‐fractionated chlorophyll‐a), secondary producers (copepods), juveniles (age‐0 walleye pollock), adult consumers (five commercially important fishes), human activities (seasonal fishing effort) and mobile predators (seabirds). We identify the spatial niche for each ecosystem component, as well as dominant modes of variability that are highly correlated with a known bottom–up driver of dynamics. We then measure spatial overlap between interacting variables (using Schoener's‐D) and identify that age‐0 pollock have decreased spatial overlap with copepods and increased overlap with adult pollock during warm years, and also that adult pollock have increased overlap with arrowtooth flounder and decreased overlap with catcher–processor fishing effort during these warm years. Given the warming conditions that are projected for the coming decade, the model forecasts increased prey and competitor overlap involving adult pollock (between age‐0 pollock, adult pollock and arrowtooth flounder) and decreased overlap with the copepod forage base and with the catcher–processor fishery during future warming. We recommend that joint species distribution models be extended to incorporate ‘ecological teleconnections' (correlations between distant locations arising from known mechanisms) arising from behavioral adaptation by mobile animals as well as passive advection of nutrients and planktonic juvenile stages.

中文翻译：

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使用与气候相关的时空生态系统模型预测社区重组

生态系统越来越受到人类活动的影响，从而改变了物理和生物组成部分之间的联系。当这些人类影响修改了系统组件之间的空间重叠时，就会发生空间群落重组，并且需要实用工具来使用监视数据来预测景观尺度上的空间群落重组。为了说明一种新方法，我们扩展了经验正交函数（EOF）分析的一般化，它涉及一个时空生态系统模型，该模型近似耦合了物理，生物和人类动力学。然后，我们通过拟合测量物理特征（温度测量和气候相关预报）的多个空间不平衡的数据集，证明其在白令海东部的五个营养级上的应用，初级生产者（春季和秋季大小的叶绿素a），次级生产者（足脚类），幼体（0岁角膜白poll鱼），成年消费者（五种重要商业鱼类），人类活动（季节性捕捞努力）和移动捕食者（海鸟） ）。我们确定了每个生态系统组成部分的空间生态位，以及与已知的自下而上的动力学驱动因素高度相关的主要变异模式。然后，我们测量相互作用变量之间的空间重叠（使用Schoener's-D），并确定0岁的小鳕在温暖的年份与co足类的空间重叠减少，与成年的小鳕重叠，并且成年的小鳕与箭齿比目鱼的重叠增加并减少。在这些温暖的年份中，与捕捞加工者的捕捞努力重叠。考虑到未来十年的变暖情况，该模型预测，成年狭鳕（0岁至零个狭鳕，成年狭鳕和箭齿比目鱼之间）的猎物和竞争者重叠将增加，而co足类草料基地和捕捞加工者的重叠将减少未来变暖中的渔业。我们建议扩展联合物种分布模型，以纳入“生态遥相关”（由已知机制引起的远距离之间的相关性），这些因移动动物的行为适应以及养分的被动平流和浮游幼年阶段而产生。成年的狭鳕和箭齿比目鱼）和在未来变暖期间与co足类草料基地和捕捞加工者渔业的重叠减少。我们建议扩展联合物种分布模型，以纳入“生态遥相关”（由已知机制引起的远距离之间的相关性），这些因移动动物的行为适应以及养分的被动平流和浮游幼年阶段而产生。成年的狭鳕和箭齿比目鱼）和在未来变暖期间与co足类草料基地和捕捞加工者渔业的重叠减少。我们建议扩展联合物种分布模型，以纳入“生态遥相关”（由已知机制引起的远距离之间的相关性），这些因移动动物的行为适应以及养分的被动平流和浮游幼年阶段而产生。