Data from: Investigating sensitivity of phylogenetic community structure metrics using North American desert bats

A relatively recent approach to characterizing structure of natural communities is to use phylogenies of species pools to compare patterns of relatedness between real and simulated communities. Such an approach can provide mechanistic insights into structure. Despite popularity of phylogenetic approaches, we do not yet fully understand how phylogenetic community structure (PCS) metrics might be impacted by changes to the phylogeny or community membership data from which they are calculated. We investigate metric sensitivity and examine PCS of bats from the 4 great desert regions of North America. We inferred a phylogeny of the regional species pool to calculate PCS metrics using community membership data delimited using 3 different methods. We also randomized our phylogeny to determine how reasonable changes to the tree affect PCS metrics. Overall, PCS metrics are quite robust to moderate changes in the phylogeny from which they are calculated. These metrics also are fairly insensitive to our 3 methods of delimiting communities. Additionally, we found that in general, communities are significantly phylogenetically clustered, suggesting habitat filtering has been important in community assembly.表征自然群落结构的一种较新研究范式，是借助物种种库的系统发育（phylogeny）数据，对比真实群落与模拟群落之间的亲缘关系模式。此类方法可为群落结构解析提供机制层面的深入认知。尽管系统发育分析方法已得到广泛应用，但目前学界仍未完全明晰：系统发育群落结构（phylogenetic community structure, PCS）指标会如何受到其计算所依赖的系统发育数据或群落成员数据变动的影响。本研究针对指标敏感性展开探究，并对北美四大荒漠区域的蝙蝠群落的PCS进行分析。我们通过构建区域物种种库的系统发育树，结合采用3种不同方法界定得到的群落成员数据，计算PCS指标。此外，我们通过对系统发育树进行随机化处理，以明确树结构的合理变动会对PCS指标产生何种影响。整体而言，PCS指标对于其计算所依赖的系统发育树的中等程度变动，具备较强的鲁棒性。同时，这些指标对本研究采用的3种群落界定方法也表现出相当的不敏感性，即几乎不受群落界定方法差异的影响。另外，我们还发现：总体而言，各类群落均呈现出显著的系统发育聚集模式，这表明生境过滤在群落组装过程中发挥了关键作用。