Abstract

Metacommunity ecology has broadened considerably with the recognition that measuring beta diversity beyond the purely taxonomic viewpoint may improve our understanding of the dispersal- and niche-based mechanisms across biological communities. In that perspective, we applied a novel multidimensional approach including taxonomic, functional and phylogenetic data to enhance our basic understanding of macrophyte metacommunity dynamics. For each beta diversity metric, we calculated the mean overall value and tested whether the mean value was different from that expected by chance using null models. We also employed evolutionary and spatially constrained models to first identify the degree to which the studied functional traits showed a phylogenetic signal, and then to estimate the relative importance of spatial and environmental effects on metacommunity structure. We first found that most individual ponds were inhabited by species that were merely random draws from the taxonomic and phylogenetic species pool available in the study region. Contrary to our expectations, not all measured traits were conserved along the phylogeny. We also showed that trait and phylogenetic dimensions strongly increased the amount of variation in beta diversity that can be explained by degree of environmental filtering and dispersal limitation. This suggests that accounting for functional traits and phylogeny in metacommunity ecology helps to explain idiosyncratic patterns of variation in macrophyte species distribution. Importantly, phylogenetic and functional analyses identified the influence of underlying mechanisms that would otherwise be missed in an analysis of taxonomic turnover. Together, these results let us conclude that macrophyte species have labile functional traits adapted to dispersal-based processes and some evolutionary trade-offs that drive community assembly via species sorting. Overall, our exploration of different facets of beta diversity showed how functional and phylogenetic information may be used with species-level data to test community assembly hypotheses that are more ecologically meaningful than assessments of environmental patterns based on the purely taxonomic viewpoint.