title: The temporal distribution of directional gradients under selection for an optimum.
abstract: Temporal variation in phenotypic selection is often attributed to environmental change causing movements of the adaptive surface relating traits to fitness, but this connection is rarely established empirically. Fluctuating phenotypic selection can be measured by the variance and autocorrelation of directional selection gradients through time. However, the dynamics of these gradients depend not only on environmental changes altering the fitness surface, but also on evolution of the phenotypic distribution. Therefore, it is unclear to what extent variability in selection gradients can inform us about the underlying drivers of their fluctuations. To investigate this question, we derive the temporal distribution of directional gradients under selection for a phenotypic optimum that is either constant or fluctuates randomly in various ways in a finite population. Our analytical results, combined with population- and individual-based simulations, show that although some characteristic patterns can be distinguished, very different types of change in the optimum (including a constant optimum) can generate similar temporal distributions of selection gradients, making it difficult to infer the processes underlying apparent fluctuating selection. Analyzing changes in phenotype distributions together with changes in selection gradients should prove more useful for inferring the mechanisms underlying estimated fluctuating selection.
authors.affiliation: CEFE-CNRS, UMR 5175, 34293, Montpellier, France. luis-miguel.chevin@cefe.cnrs.fr.
authors.forename: Luis-Miguel
authors.initials: LM
authors.lastname: Chevin
authors.forename: Benjamin C
authors.initials: BC
authors.lastname: Haller
mesh_terms: D004777:Environment; D019143:Evolution, Molecular; D056084:Genetic Fitness; D008957:Models, Genetic; D012641:Selection, Genetic; D013997:Time Factors
keywords: Adaptation; contemporary evolution; fluctuating selection; quantitative genetics; time-series analysis