A framework for delineating biogeographical regions based on species distributions

Abstract

Aim Biogeographical regionalizations, such as zoogeographical regions, floristic kingdoms or ecoregions, represent categorizations central to many basic and applied questions in biogeography, ecology, evolution and conservation. Traditionally established by experts based on qualitative evidence, the lack of transparency and quantitative support has set constraints on their utility. The recent availability of global species range maps, novel multivariate techniques and enhanced computational power now enable a quantitative scrutiny and extension of biogeographical regionalizations that will facilitate new and more rigorous uses. In this paper we develop and illustrate a methodological roadmap for species-level biogeographical regionalizations at the global scale and apply it to mammals.Methods We explore the relative usefulness of ordination and clustering methods and validation techniques. The performance of nine different clustering algorithms is tested at different taxonomic levels. The grain of regionalization (i.e. the number of clusters) will usually be driven by the purpose of the study, but we present several approaches that provide guidance.Results Non-metric multidimensional scaling offers a valuable first step in identifying and illustrating biogeographical transition zones. For the clustering of regions, the nine different hierarchical clustering methods varied greatly in utility, with UPGMA (unweighted pair-group method using arithmetic averages) agglomerative hierarchical clustering having consistently the best performance. The UPGMA approach allows a tree-like phenetic representation of the relative distances of regions and can be applied at different levels of taxonomic resolution. We find that the new quantitative biogeographical regions exhibit both striking similarities to and differences from the classic primary geographical divisions of the world's biota. Specifically, our results provide evidence that the Sahara, northern Africa, the Arabian Peninsula and parts of the Middle East should be regarded as part of the Afrotropics. Further, the position of the New Guinean continental shelf, Lydekker's Line, is supported as an appropriate border to separate the Oriental and Australian regions. Main conclusionsWe propose that this sort of new, quantitative delineation and relationship assessment across taxonomic and geographical grains is likely to offer opportunities for more rigorous inference in historical and ecological biogeography and conservation.

Endemism and functional convergence across the North American soil mycobiome

“…1A). This result shows that geographic endemism is a key feature of fungal communities, as seen with plants and animals, and broadly parallels biogeographic provinces previously described for North America (29). As a consequence of geographic endemism, soil fungal communities displayed a significant distance-decay relationship spanning the meter to continental scale (Fig.…”

Out of Asia: Natricine snakes support the Cenozoic Beringian Dispersal Hypothesis

“…Species were coded to one of 6 standard zoogeographic regions recognized by Wallace (1876), Barry (2001) and Kreft and Jetz (2010), which have been shown to be useful at estimating ancestral areas in other snake groups (Burbrink and Lawson, 2007): Neotropic, Nearctic, Western Palearctic, Ethiopian (African), Eastern Palearctic, and Oriental. These ranges were determined using the Reptile Database and associated literature included with each taxon (http://www.reptile-database.org Rossman et al, 1996;Gibbons and Dorcas, 2004).…”

Provincialization of terrestrial faunas following the end-Permian mass extinction

“…Discussion Analyzing Biogeographic Structure. Quantitative studies of community similarity and biogeographic structure frequently make use of a combination of similarity or distance metrics and cluster analyses (10,11). A wide range of similarity and distance metrics have been proposed, which use differing definitions of similarity and make various assumptions about issues such as the weighting of joint occurrences or mismatches.…”

“…To measure this factor, we used a network clustering algorithm that measures the potential to compress a taxon-locality bipartite network into subunits. These measures have several advantages over most current biogeographic methods (10,11) because the summary measures follow directly from the occurrence data of the taxa included, rather than being filtered through a similarity measure. We also analyzed the average number of basins in which species occur as well as the proportion of endemic taxa per locality.…”