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A large microsatellite data set from three species of bear (Ursidae) was used to empirically test the performance of six genetic distance measures in resolving relationships at a variety of scales ranging from adjacent areas in a continuous distribution to species that diverged several million years ago. At the finest scale, while some distance measures performed extremely well, statistics developed specifically to accommodate the mutational processes of microsatellites performed relatively poorly, presumably because of the relatively higher variance of these statistics. At the other extreme, no statistic was able to resolve the close sister relationship of polar bears and brown bears from more distantly related pairs of species. This failure is most likely due to constraints on allele distributions at microsatellite loci. At intermediate scales, both within continuous distributions and in comparisons to insular populations of late Pleistocene origin, it was not possible to define the point where linearity was lost for each of the statistics, except that it is clearly lost after relatively short periods of independent evolution. All of the statistics were affected by the amount of genetic diversity within the populations being compared, significantly complicating the interpretation of genetic distance data.

An Empirical Evaluation of Genetic Distance Statistics Using Microsatellite Data From Bear (Ursidae) Populations