title: Fisher's geometric model with a moving optimum.
abstract: Fisher's geometric model has been widely used to study the effects of pleiotropy and organismic complexity on phenotypic adaptation. Here, we study a version of Fisher's model in which a population adapts to a gradually moving optimum. Key parameters are the rate of environmental change, the dimensionality of phenotype space, and the patterns of mutational and selectional correlations. We focus on the distribution of adaptive substitutions, that is, the multivariate distribution of the phenotypic effects of fixed beneficial mutations. Our main results are based on an "adaptive-walk approximation," which is checked against individual-based simulations. We find that (1) the distribution of adaptive substitutions is strongly affected by the ecological dynamics and largely depends on a single composite parameter γ, which scales the rate of environmental change by the "adaptive potential" of the population; (2) the distribution of adaptive substitution reflects the shape of the fitness landscape if the environment changes slowly, whereas it mirrors the distribution of new mutations if the environment changes fast; (3) in contrast to classical models of adaptation assuming a constant optimum, with a moving optimum, more complex organisms evolve via larger adaptive steps.
authors.affiliation: Mathematics and BioSciences Group, Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, A-1090, Vienna, Austria. Sebastian.Matuszewski@univie.ac.at.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Matuszewski
authors.forename: Joachim
authors.initials: J
authors.lastname: Hermisson
authors.forename: Michael
authors.initials: M
authors.lastname: Kopp
mesh_terms: D000222:Adaptation, Physiological / Q000235:genetics*; D005075:Biological Evolution; D004777:Environment; D058685:Genetic Pleiotropy; D005828:Genetics, Population; D008957:Models, Genetic; D009154:Mutation / Q000235:genetics; D010641:Phenotype; D012641:Selection, Genetic; D013997:Time Factors
keywords: Adaptation; models/simulations; mutations; pleiotropy; population genetics; selection-natural