The effects of grazing on foliar trait diversity and niche differentiation in Tibetan alpine meadows

Though many processes are involved in determining which species coexist and assemble into communities, competition is among the best studied. One hypothesis about competition's contribution to community assembly is that more closely related species are less likely to coexist. Though empirical evidence for this hypothesis is mixed, it remains a common assumption in certain phylogenetic approaches for inferring the effects of environmental filtering and competitive exclusion. Here, we relate modern coexistence theory to phylogenetic community assembly approaches to refine expectations for how species relatedness influences the outcome of competition. We argue that two types of species differences determine competitive exclusion with opposing effects on relatedness patterns. Importantly, this means that competition can sometimes eliminate more different and less related taxa, even when the traits underlying the relevant species differences are phylogenetically conserved. Our argument leads to a reinterpretation of the assembly processes inferred from community phylogenetic structure.

Community assembly theory suggests that two processes affect the distribution of trait values within communities: competition and habitat filtering. Within a local community, competition leads to ecological differentiation of coexisting species, while habitat filtering reduces the spread of trait values, reflecting shared ecological tolerances. Many statistical tests for the effects of competition exist in the literature, but measures of habitat filtering are less well-developed. Here, we present convex hull volume, a construct from computational geometry, which provides an n-dimensional measure of the volume of trait space occupied by species in a community. Combined with ecological null models, this measure offers a useful test for habitat filtering. We use convex hull volume and a null model to analyze California woody-plant trait and community data. Our results show that observed plant communities occupy less trait space than expected from random assembly, a result consistent with habitat filtering.