To better understand the relative influences of dispersal limitation and environmental filtering on the structure of ecological communities it is necessary to leverage newly available data and develop novel quantitative frameworks. It has recently been proposed that insight can be gained by using phylogenetic and functional trait data in conjunction with traditional approaches to characterize spatial turnover in community structure (β-diversity). Studies taking this approach are rapidly emerging due to the increasing availability of phylogenetic and functional data. Lacking, however, is an understanding of how to appropriately infer processes by combining empirical patterns of phylogenetic, functional and taxonomic β-diversity. Here we develop a practical framework that allows rigorous inference of the strengths of dispersal limitation and environmental filtering. Our framework simulates community assembly by analytically linking biological processes through ecological and evolutionary time. The strengths of dispersal limitation and environmental filtering parameterize the analytical model, which informs the simultaneous evolution of species’ range centroids and abiotic environmental optima on the regional phylogeny. These two species’ "traits" influence local community assembly across a suite of local sites, where assembly also depends on the strengths of dispersal limitation and environmental filtering. Phylogenetic, functional, and taxonomic β-diversity across those sites were then analyzed with commonly used statistical tools.

Results/Conclusions

We show that no single type of data (phylogenetic, functional or taxonomic) and no single β-diversity metric provides unambiguous inferences of community assembly processes. Furthermore, we show that using only taxonomic information can lead to serious mistakes when inferring community assembly processes. By combining the three types of β-diversity our framework is, however, able to correctly infer the relative influences of dispersal limitation and environmental filtering and closely approximate the absolute strengths of these processes. The framework developed here is a powerful new tool that will help unify empirical patterns of phylogenetic, functional and taxonomic β-diversity in the context of important ecological processes. To that end, we provide practical recommendations for linking our simulation-based framework to large-scale empirical analyses of phylogenetic, functional and taxonomic β-diversity.