Fractal triads efficiently sample ecological diversity and processes across spatial scales

The relative influence of ecological assembly processes, such as environmental filtering, competition, and dispersal, vary across spatial scales. Changes in phylogenetic and taxonomic diversity across environments provide insight into these processes, however, it is challenging to assess the effect of spatial scale on these metrics. Here, we outline a nested sampling design that fractally spaces sampling locations to concentrate statistical power across spatial scales in a study area. We test this design in northeast Utah, at a study site with distinct vegetation types (including sagebrush steppe and mixed conifer forest), that vary across environmental gradients. We demonstrate the power of this design to detect changes in community phylogenetic diversity across environmental gradients and assess the spatial scale at which the sampling design captures the most variation in empirical data. We find clear evidence of broad-scale changes in multiple features of phylogenetic and taxonomic d...

诸如环境过滤（environmental filtering）、竞争（competition）与扩散（dispersal）等生态组装过程（ecological assembly processes）的相对影响力随空间尺度而异。不同环境下系统发育多样性（phylogenetic diversity）与分类多样性（taxonomic diversity）的变化可为解析此类生态过程提供参考，但评估空间尺度对这些多样性指标的影响仍颇具挑战。本研究提出一种嵌套采样设计（nested sampling design），通过以分形方式布设采样位点，使研究区域内各空间尺度均能获得充足的统计效力。我们在犹他州东北部一处植被类型差异显著的研究样地对该设计进行了验证，该样地涵盖蒿灌丛草原（sagebrush steppe）与针叶混交林（mixed conifer forest）等植被类型，且植被类型随环境梯度（environmental gradients）发生变化。本研究证实该设计可有效检测环境梯度下群落系统发育多样性（community phylogenetic diversity）的变化，并能评估采样设计在哪一空间尺度下可捕捉到经验数据（empirical data）中的最大变异。我们发现了明确证据，表明系统发育与分类多样性的多项特征存在大范围尺度上的变化……