Drivers of population genetic differentiation in the wild: isolation by dispersal limitation, isolation by adaptation and isolation by colonization
Research output: Contribution to journal › A1: Web of Science-article
- Universiteit Gent Laboratorium voor Milieutoxicologie en Aquatische Ecologie (LMAE)
|Number of pages||17|
|Publication status||Published - 1-Dec-2013|
Empirical population genetic studies have been dominated by a neutralist view, according to which gene flow and drift are the main forces driving population genetic structure in nature. The neutralist view in essence describes a process of isolation by dispersal limitation (IBDL) that generally leads to a pattern of isolation by distance (IBD). Recently, however, conceptual frameworks have been put forward that view local genetic adaptation as an important driver of population genetic structure. Isolation by adaptation (IBA) and monopolization (M) posit that gene flow among natural populations is reduced as a consequence of local genetic adaptation. IBA stresses that effective gene flow is reduced among habitats that show dissimilar ecological characteristics, leading to a pattern of isolation by environment. In monopolization, local genetic adaptation of initial colonizing genotypes results in a reduction in gene flow that fosters the persistence of founder effects. Here, we relate these different processes driving landscape genetic structure to patterns of IBD and isolation by environment (IBE). We propose a method to detect whether IBDL, IBA and M shape genetic differentiation in natural landscapes by studying patterns of variation at neutral and non-neutral markers as well as at ecologically relevant traits. Finally, we reinterpret a representative number of studies from the recent literature by associating patterns to processes and identify patterns associated with local genetic adaptation to be as common as IBDL in structuring regional genetic variation of populations in the wild. Our results point to the importance of quantifying environmental gradients and incorporating ecology in the analysis of population genetics.
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