title: Distribution of variation over populations.
abstract: Understanding the significance of the distribution of genetic or phenotypic variation over populations is one of the central concerns of population genetic and ecological research. The import of the research decisively depends on the measures that are applied to assess the amount of variation residing within and between populations. Common approaches can be classified under two perspectives: differentiation and apportionment. While the former focuses on differences (distances) in trait distribution between populations, the latter considers the division of the overall trait variation among populations. Particularly when multiple populations are studied, the apportionment perspective is usually given preference (via F(ST)/G(ST) indices), even though the other perspective is also relevant. The differences between the two perspectives as well as their joint conceptual basis can be exposed by referring them to the association between trait states and population affiliations. It is demonstrated that the two directions, association of population affiliation with trait state and of trait state with population affiliation, reflect the differentiation and the apportionment perspective, respectively. When combining both perspectives and applying the suggested measure of association, new and efficient methods of analysis result, as is outlined for population genetic processes. In conclusion, the association approach to an analysis of the distribution of trait variation over populations resolves problems that are frequently encountered with the apportionment perspective and its commonly applied measures in both population genetics and ecology, suggesting new and more comprehensive methods of analysis that include patterns of differentiation and apportionment.
authors.affiliation: Institut für Populations- und ökologische Genetik, Am Pfingstanger 58, 37075 Göttingen, Germany. hgregor@gwdg.de
authors.forename: Hans-Rolf
authors.initials: HR
authors.lastname: Gregorius
mesh_terms: D000465:Algorithms; D000818:Animals; D004463:Ecology; D019143:Evolution, Molecular; D005787:Gene Frequency; D014644:Genetic Variation; D005828:Genetics, Population; D006801:Humans; D008957:Models, Genetic; D008962:Models, Theoretical; D010641:Phenotype; D011110:Polymorphism, Genetic; D012641:Selection, Genetic