MULTIDIMENSIONAL ANALYSIS OF GEOGRAPHIC GENETIC STRUCTURE

Multilocus data are an important source of information on genetic variation within and among natural populations. Hierarchical techniques are used widely for examining multilo- cus data. However, the limitations of hierarchical (phenetic or phylogenetic) algorithms to depict geographic genetic structure, particularly within species, have long been recognized. Multidi- mensional scaling of genetic distances is herein examined as a useful technique for exploratory analysis of geographic genetic structure. The advantages and limitations of multidimensional scaling are discussed and illustrated with reanalyses of two case studies: pocket gophers (Tho- momys bottae) of the central California "genetic group" and a hybrid zone of two chromosomal forms of the tent-making bat (Uroderma bilobatum). Multidimensional scaling does recover hi- erarchical patterns when present and is especially useful to uncover nonhierarchical patterns of variation. The finding that reticular and clinal patterns of variation may be examined via multidimensional scaling even in the absence of fixed genetic differences between hybridizing taxa opens new possibilities for studying geographic genetic divergence and speciation. (Geo- graphic structure; multidimensional scaling; genetic variation; hybrid zones; Thomomys; Uro- derma.) The analysis of geographic genetic struc- ture of natural populations is of paramount importance for understanding the patterns and processes of differentiation and spe- ciation. Much of our knowledge of genetic variation stems from numerous electro- phoretic surveys carried out over the last two decades. A variety of techniques, in- cluding phenetic and cladistic hierarchical algorithms, may be used in the search for overall patterns on the basis of multilocus data such as those obtained by electropho- resis. Barring reticular evolution (itself not a trivial issue), a hierarchical approach is fully justified in interspecific assessments.

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