Can Community Structure Causally Determine Dynamics of Constituent Species? A Test Using a Host-Parasite Community
Can Community Structure Causally Determine Dynamics of Constituent Species? A Test Using a Host-Parasite Community
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DOI：
10.1086/704182
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发表时间：
2019-07
期刊：
影响因子：
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通讯作者：
R. Langendorf;D. Doak
中科院分区：
文献类型：
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作者：
R. Langendorf;D. Doak
人们对社区结构进行了广泛的研究，假设它们不仅是一种有用的簿记工具，而且还可以因果地影响它们产生的种群的动态。然而，对这一假设的令人信服的测试仍然难以捉摸，因为通常改变社区财产的唯一方法是操纵其组成人口，从而阻止对这些人口影响的独立测量。越来越多的证据表明，像收敛交叉映射(CCM)这样的方法可以用来通过耦合时间序列的状态空间重建来推断因果相互作用，这是一种仅依赖观测数据的方法。在这里，我们展示了CCM可以用来测试社区属性的因果效应，使用一个经过充分研究的斯洛伐克啮齿动物-体外寄生虫社区。CCM确定了该社区组织范围内的因果驱动因素，包括主机动态受到社区整体连接和集群化程度的影响的证据。我们的发现增加了越来越多的关于社区结构在疾病动力学中的重要性的文献，并主张在社区动力学分析中更广泛地使用因果推理。
Structures of communities have been widely studied with the assumption that they not only are a useful bookkeeping tool but also can causally influence dynamics of the populations from which they emerge. However, convincing tests of this assumption have remained elusive because generally the only way to alter a community property is by manipulating its constituent populations, thereby preventing independent measurements of effects on those populations. There is a growing body of evidence that methods like convergent cross-mapping (CCM) can be used to make inferences about causal interactions using state space reconstructions of coupled time series, a method that relies on only observational data. Here we show that CCM can be used to test the causal effects of community properties using a well-studied Slovakian rodent-ectoparasite community. CCM identified causal drivers across the organizational scales of this community, including evidence that host dynamics were influenced by the degree to which the community at large was connected and clustered. Our findings add to the growing literature on the importance of community structures in disease dynamics and argue for a broader use of causal inference in the analysis of community dynamics.