Local assemblages are embedded in networks of communities connected by dispersal, and understanding the processes that mediate this local–regional interaction is central to understanding biodiversity patterns. In this network (i.e. metacommunity), the strength of dispersal relative to the intensity of environmental selection typically determines whether local communities are comprised of species well‐adapted to the local environment (i.e. species sorting) or are dominated by regionally successful species that may not be locally adapted (i.e. mass effects), which by extension determines the capacity of the landscape to sustain diversity. Despite the fundamentally spatial nature of these dispersal‐mediated processes, much of our theoretical understanding comes from spatially implicit systems, a special case of spatial structure in which patches are all connected to each other equally. In many real systems, both the connections among patches (i.e. network topology) and the distributions of environments across patches (i.e. spatial autocorrelation) are not arranged uniformly. Here, we use a metacommunity model to investigate how spatial heterogeneities may change the balance between species sorting versus mass effects and diversity outcomes. Our simulations show that, in general, the spatially implicit model generates an outlier in biodiversity patterns compared to other networks, and most likely amplifies mass effects relative to species sorting. Network topology has a strong effect on metacommunity outcome, with topologies of sparse connections and few loops promoting sorting of species into suitable patches. Spatial autocorrelation is another key factor; by interacting with spatial topology, intermediate‐scale clusters of similar patches can emerge, leading to a reduction of regional competition, and hence maintenance of gamma diversity. These results provide a better understanding of the role that complex spatial landscape structure plays in metacommunity processes, a necessary step to understanding how metacommunity processes relate to biodiversity conservation.

中文翻译：

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从物种分类到质量效应：空间网络结构介导了元社区原型之间的转移

地方性组织被嵌入到通过散布联系起来的社区网络中，而了解介导这种局部-区域相互作用的过程对于理解生物多样性模式至关重要。在这个网络（即元社区）中，相对于环境选择强度的扩散强度通常决定了当地社区是由适应当地环境的物种组成（即物种分选）还是由区域性成功物种主导，而不是局部适应（即质量效应），从而决定景观维持多样性的能力。尽管这些分散介导过程具有根本的空间性质，但我们的许多理论理解还是来自空间隐式系统，空间结构的一种特殊情况，其中小块都彼此相等地连接。在许多实际系统中，补丁之间的连接（即网络拓扑）和补丁之间的环境分布（即空间自相关）都没有统一排列。在这里，我们使用元社区模型来研究空间异质性如何改变物种分类与质量效应和多样性结果之间的平衡。我们的模拟表明，总体而言，与其他网络相比，空间隐式模型在生物多样性模式上产生了异常值，并且最有可能放大相对于物种分类的质量效应。网络拓扑结构对元社区的结果有很大影响，连接稀疏的拓扑结构和极少的循环促进将物种分类为合适的斑块。空间自相关是另一个关键因素。通过与空间拓扑相互作用，可以出现类似斑块的中等规模集群，从而减少区域竞争，从而保持伽玛多样性。这些结果更好地了解了复杂的空间景观结构在元社区过程中的作用，这是了解元社区过程与生物多样性保护之间关系的必要步骤。