Data from: The interaction of phylogeny and community structure: linking the community composition and trait evolution of clades

Aim. Community phylogenetic studies use information about species' evolutionary relationships to understand the ecological processes of community assembly. A central premise of the field is that species' evolution maps onto ecological patterns, and phylogeny reveals something more than species' traits alone about ecological mechanisms structuring communities such as environmental filtering, competition, and facilitation. We argue, therefore, that there is a need to better understand and model the interaction of phylogeny with species' traits and community composition. Innovation. We outline a new approach that identifies clades that are eco-phylogenetically clustered or overdispersed, and then assesses whether those clades have different rates of trait evolution. Eco-phylogenetic theory would predict that the traits of clustered or overdispersed clades might have evolved differently, either in terms of tempo (fast or slow) or mode (e.g., under constraint or neutrally). We suggest that modelling the evolution of independent trait data in these clades represents a strong test of whether there is an association between species' ecological co-occurrence patterns and evolutionary history. Main conclusions. Using an empirical dataset of mammals from around the world, we identify two clades of rodents whose species tend not to co-occur in the same local assemblages (are phylogenetically overdispersed), and then find independent evidence of slower rates of body mass evolution in these clades. Our approach, which assumes nothing about the mode of species' trait evolution but rather seeks to explain it using ecological information, presents a new way to examine eco-phylogenetic structure.Supplementary Materials 1Description of 'exact' methods to calculate clade-level significance and additional permutation tests of evolutionary model fitting.si-1.pdfSupplementary Materials 2R code that calculates the variance metric we outline in our manuscript. This code will be incorporated in the R package 'pez', which is available on CRAN (under 'clade.var'); please use the 'pez' version as we will be more easily able to update and maintain the code there.si-2-functions.RSupplementary Materials 3R code to run the simulations of our approach, as outlined in our manuscript.si-3-simulations.RSupplementary Materials 4R code to run our empirical analyses, as outlined in our manuscript. Please note that this script is completely reproducible, and will download the empirical data the user needs to repeat our analyses.si-4-empirical.RFunding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: ABI-1759965, EF-180260