Spatial Congruence Analysis (SCAN): An objective method for detecting biogeographical patterns based on species range congruences

Abstract

Similar species ranges may represent outcomes of common biological processes and so form the basis for biogeographical concepts such as areas of endemism and ecoregions. Nevertheless, spatial range congruence is rarely quantified, much less incorporated in bioregionalization methods as an explicit parameter. Furthermore, most available methods suffer from limitations related to the loss, or the excess of range information, or scale bias associated with the use of grids, and the incapacity to recognize independent overlapped patterns or gradients of range distributions. Here, we propose an analytical method, Spatial Congruence Analysis (SCAN), to identify biogeographically meaningful groups of species, called biogeographic elements. Such elements are based on direct and indirect spatial relationships among species ranges and vary depending on an explicit measure of range congruence controlled as a numerical parameter in the analysis. A one-layered network connects species (vertices) using pairwise spatial congruence estimates (edges). This network is then analyzed for each species, separately, by an algorithm that accesses the entire web of spatial relationships to the reference species. The method was applied to two datasets: a simulated gradient of ranges and real distributions of birds. The gradient results showed that SCAN can describe gradients of distribution with a high level of detail, without confounding transition zones with true biogeographical units, a frequent pitfall of other methods. The bird dataset showed that only a small portion of range overlaps is biogeographically meaningful, and that there is a large variation in types of patterns that can be found with real distributions. Distinct reference species may converge on similar or identical groups of spatially related species, may lead to recognition of nested species groups, or may even generate similar spatial patterns with no species in common. The biological significance or causal processes of these patterns should be investigated a posteriori. Patterns can vary from simple ones, composed by few highly congruent species, to complex, with numerous alternative component species and spatial configurations, depending on particular parameter settings as determined by the investigator. This approach eliminates or reduces limitations of other methods and permits pattern description without hidden assumptions about processes, and so should make a valuable contribution to the biogeographers toolbox. "If there is any basic unit of biogeography, it is the geographic range of a species." - Brown, Stevens & Kaufman [1]. "[spatial] congruence [...] should be optimized, while realizing that this criterion will most likely never be fully met" - HP Linder [2].