Testing limits to adaptation along altitudinal gradients in rainforest Drosophila

J.R. Bridle, S. Gavaz, Jason Kennington

    Research output: Contribution to journalArticlepeer-review

    56 Citations (Scopus)

    Abstract

    Given that evolution can generate rapid and dramatic shifts in the ecological tolerance of a species, what prevents populations adapting to expand into new habitat at the edge of their distributions? Recent population genetic models have focused on the relative costs and benefits of migration between populations. On the one hand, migration may limit adaptive divergence by preventing local populations from matching their local selective optima. On the other hand, migration may also contribute to the genetic variance necessary to allow populations to track these changing optima. Empirical evidence for these contrasting effects of gene flow in natural situations are lacking, largely because it remains difficult to acquire. Here, we develop a way to explore theoretical models by estimating genetic divergence in traits that confer stress resistance along similar ecological gradients in rainforest Drosophila. This approach allows testing for the coupling of clinal divergence with local density, and the effects of genetic variance and the rate of change of the optimum on the response to selection. In support of a swamping effect of migration on phenotypic divergence, our data show no evidence for a cline in stress-related traits where the altitudinal gradient is steep, but significant clinal divergence where it is shallow. However, where clinal divergence is detected, sites showing trait means closer to the presumed local optimum have more genetic variation than sites with trait means distant from their local optimum. This pattern suggests that gene flow also aids a sustained response to selection.
    Original languageEnglish
    Pages (from-to)1507-1515
    JournalProceedings of the Royal Society B: Biological Sciences
    Volume276
    Issue number1661
    DOIs
    Publication statusPublished - 2009

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