Interactions between microenvironment, selection and genetic architecture drive multiscale adaptation in a simulation experiment

Abstract

When environmental conditions differ both within and among populations, multiscale adaptation results from processes at both scales and interference across scales. We hypothesize that within-population environmental heterogeneity influences the chance of success of migration events, both within and among populations, and maintains within-population adaptive differentiation. We used a simulation approach to analyse the joint effects of environmental heterogeneity patterns, selection intensity and number of QTL controlling a selected trait on local adaptation in a hierarchical metapopulation design. We show the general effects of within-population environmental heterogeneity: (i) it increases occupancy rate at the margins of distribution ranges, under extreme environments and high levels of selection; (ii) it increases the adaptation lag in all environments; (iii) it impacts the genetic variance in each environment, depending on the ratio of within- to between-populations environmental heterogeneity; (iv) it reduces the selection-induced erosion of adaptive gene diversity. Most often, the smaller the number of QTL involved, the stronger are these effects. We also show that both within- and between-populations phenotypic differentiation (QST) mainly results from covariance of QTL effects rather than QTL differentiation (FSTq), that within-population QTL differentiation is negligible, and that stronger divergent selection is required to produce adaptive differentiation within populations than among populations. With a high number of QTL, when the difference between environments within populations exceeds the smallest difference between environments across populations, high levels of within-population differentiation can be reached, reducing differentiation among populations. Our study stresses the need to account for within-population environmental heterogeneity when investigating local adaptation.