EcoPhyloMapper: an R package for integrating geographic ranges, phylogeny, and morphology

1. Spatial patterns of species richness, phylogenetic and morphological
diversity are key to answering many questions in ecology and evolution.
Across spatial scales, geographic 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 geographic 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 geographic
patterns of both phylogenetic and shape diversity. 2. We present the
ecoPhyloMapper R package (epm) that aims to streamline the handling of
geographic range polygons or point occurrences and integration of
resulting species metacommunities with phylogenetic trees and
morphological shape. 3. Geographic 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.
4. This R package will facilitate the geographic exploration of
multivariate shape data in concert with phylogenetic diversity, which will
in turn support macroecological research exploring how species assemblages
are structured. Further, this R package should prove useful across a wide
range of macroecological applications that extend beyond the study of
morphology.