Dispersal-Vicariance Analysis: A New Approach to the Quantification of Historical Biogeography

TLDR: This work presents a new biogeographic method, dispersal-vicariance analysis, which reconstructs the ancestral distributions in a given phylogeny without any prior assumptions about the form of area relationships, and describes the algorithms that find the optimal reconstruction.

Abstract: Quantification in historical biogeography has usually been based on the search for a single branching relationship among areas of endemism. Unlike organisms, however, areas rarely have a unique hierarchical history. Dispersal barriers appear and disappear and may have differ- ent effects on different species. As a result, the biota of an area may consist of several components with separate histories, each of which may be reticulate rather than branching. In an attempt to address these problems, I present a new biogeographic method, dispersal-vicariance analysis, which reconstructs the ancestral distributions in a given phylogeny without any prior assumptions about the form of area relationships. A three-dimensional step matrix based on a simple biogeo- graphic model is used in the reconstruction. Speciation is assumed to subdivide the ranges of widespread species into vicariant components; the optimal ancestral distributions are those that minimize the number of implied dispersal and extinction events. Exact algorithms that find the optimal reconstruction(s) are described. In addition to their use in taxon biogeography, the in- ferred distribution histories of individual groups serve as a basis for the study of general patterns in historical biogeography, particularly if the relative age of the nodes in the source cladograms is known. (Cladistic biogeography; comparative phylogeography; dispersal; extinction; historical biogeography; optimization; vicariance; widespread species.) In historical biogeography, whether fo- cused on patterns below the species level (comparative phylogeography) or above the species level, there is a need for quan- titative methods to assess the likelihood of alternative hypotheses. Most methods used today are based on the assumption that there is a single branching pattern among areas of endemism caused by vi-