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Climatic seasonality may affect ecological network structure: Food webs and mutualistic networks

机译:气候季节性可能影响生态网络结构:食物网和互惠网络

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摘要

Ecological networks exhibit non-random structural patterns, such as modularity and nestedness, which determine ecosystem stability with species diversity and connectance. Such structure-stability relationships are well known. However, another important perspective is less well understood: the relationship between the environment and structure. Inspired by theoretical studies that suggest that network structure can change due to environmental variability, we collected data on a number of empirical food webs and mutualistic networks and evaluated the effect of climatic seasonality on ecological network structure. As expected, we found that climatic seasonality affects ecological network structure. In particular, an increase in modularity due to climatic seasonality was observed in food webs; however, it is debatable whether this occurs in mutualistic networks. Interestingly, the type of climatic seasonality that affects network structure differs with ecosystem type. Rainfall and temperature seasonality influence freshwater food webs and mutualistic networks, respectively; food webs are smaller, and more modular, with increasing rainfall seasonality. Mutualistic networks exhibit a higher diversity (particularly of animals) with increasing temperature seasonality. These results confirm the theoretical prediction that the stability increases with greater perturbation. Although these results are still debatable because of several limitations in the data analysis, they may enhance our understanding of environment-structure relationships.
机译:生态网络展现出非随机的结构模式,例如模块性和嵌套性,它们决定了生态系统的稳定性以及物种的多样性和连通性。这样的结构稳定性关系是众所周知的。但是,另一个重要的观点却鲜为人知:环境与结构之间的关系。受理论研究的启发,这些研究表明网络结构可能会因环境变化而改变,我们收集了许多经验食物网和互惠网络的数据,并评估了气候季节性对生态网络结构的影响。不出所料,我们发现气候季节会影响生态网络结构。尤其是,在食物网中观察到由于气候季节性而导致模块性的增加;但是,这是否在互惠网络中发生是有争议的。有趣的是,影响网络结构的气候季节类型因生态系统类型而异。降雨和温度的季节性分别影响淡水食物网和互惠网络;随着降雨季节的增加,食物网更小,更模块化。随着温度季节的增加,互惠网络表现出更高的多样性(尤其是动物)。这些结果证实了理论上的预测,即稳定性随着扰动的增加而增加。尽管由于数据分析中的一些限制,这些结果仍然值得商bat,但它们可能会增强我们对环境与结构关系的理解。

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