Codistribution as an indicator of whole metacommunity response to environmental change
Codistribution as an indicator of whole metacommunity response to environmental change
复制标题
共同分布作为整个元社区对环境变化响应的指标
DOI：
10.1111/ecog.06605
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发表时间：
2023
期刊：
影响因子：
5.9
通讯作者：
Christopher D. Terry J
中科院分区：
文献类型：
--
作者：
Christopher D. Terry J
生态群落对环境驱动因素的景观规模响应可能难以有效地总结和区分随时间变化的预期背景周转。元群落结构可以通过拟合联合物种分布模型（JSDM）并将方差解释为环境、空间和物种共分布分量来封装。在这里，我们确定了这些组成部分如何随着时间的推移对定向环境变化做出反应，并提出元群落结构的这些变化作为持续定向压力的指标。通过模拟，我们确定了物种共同分布所解释的变异的下降如何可以诊断生态崩溃，而环境和空间预测因子的解释力的增加可能表明外围地区的损失和扩散限制。然后我们在两个经过充分研究的系统中测试这些结果。众所周知，蝴蝶对气候变化有强烈的反应，我们的研究表明，21 年来，英格兰南部蝴蝶群落的共同分布成分有所下降。相比之下，同一地区的鸟类被认为对气候压力的反应较弱，尽管占用率较高，但通过这种方法测量，并没有显示出元群落结构的明显变化。我们的结果表明，这些方法很有可能总结和比较外部驱动因素对整个社区的影响。
The landscape scale response of ecological communities to environmental drivers can be challenging to efficiently summarise and differentiate from expected background turnover through time. Metacommunity structure can be encapsulated by fitting joint species distribution models (JSDMs) and partitioning the variance explained into environmental, spatial and species‐codistribution components. Here we identify how these components respond through time with directed environmental change and propose these changes in metacommunity structure as an indicator of sustained directional pressure. Through simulations, we identify how declines in the variation explained by species codistribution could diagnose ecological disintegration, while increases in the explanatory power of environmental and spatial predictors may indicate losses in peripheral areas and dispersal limitations. We then test these results in two well‐studied systems. Butterflies are known to be strongly responding to climate change, and we show that over 21 years the codistribution component declines for butterfly communities in southern England. By contrast, birds in the same region are thought to be responding less strongly to climatic pressure and, despite high occupancy turnover, do not show clear changes in metacommunity structure as measured by this approach. Our results suggest that these approaches could have a high potential to summarise and compare the impacts of external drivers on whole communities.
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