The Influences of Species Richness and Climate on the Phylogenetic Structure of African Haplorhine and Strepsirrhine Primate Communities

Many factors contribute to the structure of primate communities, including historical processes, interspecific competition, and climate. Here, we quantify the phylogenetic structure of individual primate communities to evaluate these factors relative to a null model. Then, we examine the effects of species richness and local climate on variation in community phylogenetic structure. We analyze 71 haplorhine and 29 strepsirrhine communities in Africa and quantify their net relatedness (NRI) and nearest taxon (NTI) indices. Significantly low, i.e., phylogenetically even, NRI and NTI values are indicative of interspecific competition in the past, resulting in closely related species not being found in the same community. In contrast, significantly high, i.e., phylogenetically clustered, NRI and NTI values suggest that closely related species have similar ecological requirements, resulting in closely related species occupying the same community. In a second set of analyses, we used simultaneous autoregressive models to examine if species richness, rainfall, and temperature predict variation in community phylogenetic structure. Most individual communities exhibited phylogenetically random species assemblages. However, significantly structured haplorhine communities were even whereas strepsirrhine communities were clustered. Species richness significantly predicted variation in haplorhine phylogenetic structure, whereas abiotic factors significantly predicted variation in strepsirrhine phylogenetic structure. We suggest that past interspecific competition and habitat filtering have affected a relatively small proportion of African primate communities, but that past interspecific competition has more strongly influenced haplorhine communities whereas environmental conditions have more strongly influenced strepsirrhine communities. Our study illustrates the utility of phylogenetic metrics and spatially explicit models for understanding primate communities.