Data from: The interaction of phylogeny and community structure: linking the community composition and trait evolution of clades
Pearse, William D.; Legendre, Pierre; Peres-Neto, Pedro R.; Davies, T. Jonathan (2020), Data from: The interaction of phylogeny and community structure: linking the community composition and trait evolution of clades, v2, Dryad, Dataset, https://doi.org/10.5061/dryad.v26qd05
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.
National Science Foundation,
Award: ABI-1759965, EF-1802605