Comparing the intersex genetic correlation for fitness across novel environments in the fruit fly,Drosophila serrata

Sexually antagonistic genetic variation can pose limits to the independent evolution and adaptation of the sexes. The extent of sexually antagonistic variation is reflected in the intersex genetic correlation for fitness (r_w^FM). Previous estimates of this correlation have been mostly limited to populations in environments to which they are already well adapted, making it difficult to gauge the importance of sexually antagonistic genetic variance during the early stages of adaptation, such as that occurring following abrupt environmental change or upon the colonization of new habitat. Here we assayed male and female lifetime fitness in a population of Drosophila serrata in four novel laboratory environments. We found that r_w^FM varied significantly across environments, with point estimates ranging from positive to negative values of considerable magnitude. We also found that the variability among estimates was because, at least in part, of significant differences among environments in the genetic variances of both male and female fitness, with no evidence of any significant changes in the intersex covariance itself, although standard errors of these estimates were large. Our results illustrate the unpredictable nature of r_w^FM in novel environments and suggest that, although sexually antagonistic genetic variance can be pronounced in some novel environments, it may have little effect in constraining the early stages of adaptation in others.     

The importance of evolutionary constraints in ecological time scales

Summary The importance of constraints, defined as factors that retard or prevent a population from reaching its immediate adaptive peak on an ecological time scale is analysed. This is done by means of simple quantitative genetic models, which if anything underestimate the importance of constraints. The results show that even in the simplest case the response to selection will not generally be in the same direction as the selection vector, i.e. the direction to the nearest optimum. Adding complexity identifies cases where selection may lead the population in suboptimal directions. It is concluded that information about univariate genetic variances is not sufficient to predict evolutionary responses and may even be misleading. However, genetic covariances are not always acting as constraints, but can under certain circumstances promote evolution towards the nearest optimum. This can be understood by a spectral decomposition of the genetic variance—covariance matrix, where it is shown that the eigenvector associated with the largest amount of variance will to various degrees determine the outcome of selection. A literature survey of the pattern of character covariation in morphological characters in natural populations shows a wide variety of correlation patterns, but quite often shows a high level of covariance between traits. This suggests that constraints to short-term evolution may be more common than generally appreciated.