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Unformatted text preview: Beyond F ST : Analysis of population genetic data for conservation Devon E. Pearse 1,2, * & Keith A. Crandall 1 1 Department of Integrative Biology, Brigham Young University, Provo, UT 84602, USA; 2 National Marine Fisheries Service, Southwest Fisheries Science Center, Santa Cruz, CA 95060, USA ( * Author for correspondence, e-mail: email@example.com) Received 5 August 2003; accepted 3 November 2003 Abstract Both the ability to generate DNA data and the variety of analytical methods for conservation genetics are expanding at an ever-increasing pace. Analytical approaches are now possible that were unthinkable even five years ago due to limitations in computational power or the availability of DNA data, and this has vastly expanded the accuracy and types of information that may be gained from population genetic data. Here we provide a guide to recently developed methods for population genetic analysis, including identi- fication of population structure, quantification of gene ow, and inference of demographic history. We cover both allele-frequency and sequence-based approaches, with a special focus on methods relevant to conservation genetic applications. Although classical population genetic approaches such as F ST ST (and its derivatives) have carried the field thus far, newer, more powerful, methods can infer much more from the data, rely on fewer assumptions, and are appropriate for conservation genetic management when precise estimates are needed. Background The estimation of metapopulation structure and gene ow was one of the first applications of pop- ulation genetics, and despite spectacular advances in the types and amount of genetic data now available, many methods still used today are based on theoretical foundations built more than half a century ago (Fisher 1930; Wright 1931). These methods have provided population geneticists with the tools to analyze their data and robust, mean- ingful ways in which to interpret data from natural populations (Weir and Cockerham 1984; Slatkin and Barton 1989; Neigel 2002). However, it is now widely recognized that the idealized models of population structure, migration, demographics, and evolution on which these methods are based are far from realistic and are unlikely to occur in nature (Whitlock and McCauley 1999). This is particularly true in conservation genetic assess- ments because most populations and species of conservation concern are small and/or have re- cently declined in size, experienced fragmentation, or otherwise been perturbed. These are exactly the kind of demographic situations that can bias F ST ST- based estimates of migration (or other approaches that assume mutation-drift equilibrium; Whitlock and McCauley 1999; Kinnison et al. 2002). Despite the limitations, Wrights F ST ST (1951) has remained the standard parameter used to describe the amount of differentiation among pre-defined sub- populations, and from this, to estimate migration rates (Neigel 2002, Weir and Hill 2002).rates (Neigel 2002, Weir and Hill 2002)....
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