Abstract

Abstract Spatial patterns of species richness, phylogenetic and morphological diversity are key to answering many questions in ecology and evolution. Across spatial scales, geographical and environmental features, as well as evolutionary history and phenotypic traits, are thought to play roles in shaping both local species communities and regional assemblages. By examining these geographical patterns, it is possible to infer how different axes of biodiversity influence one another, and how their interaction with abiotic factors has led to the spatial distribution of species assemblages—and their attributes—that we observe in the present. Although there has been interest in this area of research for some time, it has recently become more tractable to include multivariate shape data in such analyses. Shape information has the potential to provide a more direct measure of the functional morphology of species as compared to individual trait measurements and might be more relevant to understanding community composition. However, few tools currently exist to explore geographical patterns of both phylogenetic and shape diversity. We present the EcoPhyloMapper r package (epm) that aims to streamline the handling of geographical range polygons or point occurrences and integration of resulting species metacommunities with phylogenetic trees and morphological shape. Geographical maps can be generated that demonstrate spatial patterns in diversity metrics pertaining to phylogenetic similarity, multivariate shape similarity and disparity, and combinations of the two. Patterns of taxonomic, phylogenetic and shape disparity turnover can also be visualized. Biodiversity indices summarized across grid cells can easily be exported to GIS software as well as to other r packages that specialize in community assembly or geospatial statistics. This r package will facilitate the geographical exploration of multivariate shape data in concert with phylogenetic diversity, which will, in turn, support macroecological research exploring how species assemblages are structured. Furthermore, this r package should prove useful across a wide range of macroecological applications that extend beyond the study of morphology.

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