B1597
Title: Statistical delimitation of biological species based on genetic and spatial data
Authors: Gabriele d Angella - University of Bologna (Italy) [presenting]
Christian Hennig - University of Bologna (Italy)
Abstract: The delimitation of biological species, i.e., deciding which individuals belong to the same species and whether and how many different species are represented in a genetic data set, is key to the conservation of biodiversity. Much existing work uses only genetic data for species delimitation, often employing cluster analysis. This can be misleading because geographically distant groups of individuals can be genetically quite different even if they belong to the same species. The problem of testing whether two potentially separated groups of individuals can belong to a single species is treated based on genetic and spatial data. Various approaches (some of which already exist in the literature) are compared based on simulated metapopulations. Approaches involve partial mantel testing, maximum likelihood mixed-effects models with a population effect, and jackknife-based homogeneity tests. A key challenge is that most tests are performed on genetic and geographical distance data, violating standard independence assumptions.
