Phylogenetic and functional trait-based analyses inform our understanding of community composition, yet methods for quantifying the overlap in information derived from functional traits and phylogenies remain underdeveloped. Does adding traits to analyses of community composition reduce the phylogenetic signal in the residual variation? If not, then measured functional traits alone may be insufficient to explain community assembly. We propose a general statistical framework to quantify the proportion of phylogenetic pattern in community composition that remains after including measured functional traits. We then illustrate the framework with applications to two empirical data sets. Both data sets showed strong phylogenetic attraction, with related species likely to co-occur in the same communities. In one data set, including traits eliminated all phylogenetic signals in the residual variation of both abundance and presence/absence patterns. In the second data set, including traits reduced phylogenetic signal in residuals by 25% and 98% for abundance and presence/absence data, respectively. Our framework provides an explicit way to estimate how much phylogenetic community pattern remains in the residual variation after including measured functional traits. Knowing that functional traits account for most of the phylogenetic pattern should provide confidence that important traits for phylogenetic community structure have been identified. Conversely, knowing that there is unexplained residual phylogenetic information should spur the search for additional functional traits or other processes underlying community assembly.
Keywords: community assembly; functional traits; phylogenetic linear mixed model (PLMM); phylogeny; species composition.
© 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.