Publication | Open Access
Determining Selection across Heterogeneous Landscapes: A Perturbation-Based Method and Its Application to Modeling Evolution in Space
25
Citations
57
References
2017
Year
Perturbation-based MethodPopulation DynamicLandscape ConnectivityPopulation EcologySocial SciencesEvolution StrategyBiogeographyModeling EvolutionIndividual-based ModelsEvolutionary DynamicTheoretical GeomorphologyWay Evolutionary ProcessesQuantitative GeneticsTheoretical EcologyGeographyDirectional SelectionLandscape Evolution ModelPopulation GeneticsBiologyEvolutionary DynamicsHeterogeneous LandscapesNatural SciencesEvolutionary BiologySpatial Ecology
Spatial structure can decisively influence the way evolutionary processes unfold. To date, several methods have been used to study evolution in spatial systems, including population genetics, quantitative genetics, moment-closure approximations, and individual-based models. Here we extend the study of spatial evolutionary dynamics to eco-evolutionary models based on reaction-diffusion equations and adaptive dynamics. Specifically, we derive expressions for the strength of directional and stabilizing/disruptive selection that apply both in continuous space and to metacommunities with symmetrical dispersal between patches. For directional selection on a quantitative trait, this yields a way to integrate local directional selection across space and determine whether the trait value will increase or decrease. The robustness of this prediction is validated against quantitative genetics. For stabilizing/disruptive selection, we show that spatial heterogeneity always contributes to disruptive selection and hence always promotes evolutionary branching. The expression for directional selection is numerically very efficient and hence lends itself to simulation studies of evolutionary community assembly. We illustrate the application and utility of the expressions for this purpose with two examples of the evolution of resource utilization. Finally, we outline the domain of applicability of reaction-diffusion equations as a modeling framework and discuss their limitations.
| Year | Citations | |
|---|---|---|
Page 1
Page 1