Institut für Biologie, Plant Ecology, Freie Universität Berlin, Berlin, Germany.
PLoS One. 2012;7(4):e35942. doi: 10.1371/journal.pone.0035942. Epub 2012 Apr 26.
Community structure depends on both deterministic and stochastic processes. However, patterns of community dissimilarity (e.g. difference in species composition) are difficult to interpret in terms of the relative roles of these processes. Local communities can be more dissimilar (divergence) than, less dissimilar (convergence) than, or as dissimilar as a hypothetical control based on either null or neutral models. However, several mechanisms may result in the same pattern, or act concurrently to generate a pattern, and much research has recently been focusing on unravelling these mechanisms and their relative contributions. Using a simulation approach, we addressed the effect of a complex but realistic spatial structure in the distribution of the niche axis and we analysed patterns of species co-occurrence and beta diversity as measured by dissimilarity indices (e.g. Jaccard index) using either expectations under a null model or neutral dynamics (i.e., based on switching off the niche effect). The strength of niche processes, dispersal, and environmental noise strongly interacted so that niche-driven dynamics may result in local communities that either diverge or converge depending on the combination of these factors. Thus, a fundamental result is that, in real systems, interacting processes of community assembly can be disentangled only by measuring traits such as niche breadth and dispersal. The ability to detect the signal of the niche was also dependent on the spatial resolution of the sampling strategy, which must account for the multiple scale spatial patterns in the niche axis. Notably, some of the patterns we observed correspond to patterns of community dissimilarities previously observed in the field and suggest mechanistic explanations for them or the data required to solve them. Our framework offers a synthesis of the patterns of community dissimilarity produced by the interaction of deterministic and stochastic determinants of community assembly in a spatially explicit and complex context.
群落结构取决于确定性和随机性过程。然而，群落相似性（例如物种组成的差异）的模式难以根据这些过程的相对作用来解释。局部群落可能比假设的基于零假设或中性模型的群落更相似（发散）、不那么相似（收敛）或相似。然而，几种机制可能导致相同的模式，或者同时作用以产生模式，最近有大量研究致力于揭示这些机制及其相对贡献。我们使用模拟方法，解决了在生态位轴分布中存在复杂但现实的空间结构的影响，并分析了物种共存和β多样性的模式，这些模式通过相似性指数（例如 Jaccard 指数）来衡量，这些指数是基于零假设或中性动力学的预期（即，基于关闭生态位效应）。生态位过程、扩散和环境噪声的强度强烈相互作用，因此，生态位驱动的动态可能导致局部群落发散或收敛，具体取决于这些因素的组合。因此，一个基本的结果是，在实际系统中，只有通过测量生态位宽度和扩散等特征，才能将群落组装的相互作用过程分离开来。检测生态位信号的能力也取决于采样策略的空间分辨率，该分辨率必须考虑生态位轴的多尺度空间模式。值得注意的是，我们观察到的一些模式与以前在野外观察到的群落相似性模式相对应，为它们提供了机制解释或解决它们所需的数据。我们的框架提供了一个在空间明确和复杂的背景下，由群落组装的确定性和随机性决定因素相互作用产生的群落相似性模式的综合。
