Literature DB >> 27317885

Contrasting support for alternative models of genomic variation based on microhabitat preference: species-specific effects of climate change in alpine sedges.

Rob Massatti1, L Lacey Knowles1.   

Abstract

Deterministic processes may uniquely affect codistributed species' phylogeographic patterns such that discordant genetic variation among taxa is predicted. Yet, explicitly testing expectations of genomic discordance in a statistical framework remains challenging. Here, we construct spatially and temporally dynamic models to investigate the hypothesized effect of microhabitat preferences on the permeability of glaciated regions to gene flow in two closely related montane species. Utilizing environmental niche models from the Last Glacial Maximum and the present to inform demographic models of changes in habitat suitability over time, we evaluate the relative probabilities of two alternative models using approximate Bayesian computation (ABC) in which glaciated regions are either (i) permeable or (ii) a barrier to gene flow. Results based on the fit of the empirical data to data sets simulated using a spatially explicit coalescent under alternative models indicate that genomic data are consistent with predictions about the hypothesized role of microhabitat in generating discordant patterns of genetic variation among the taxa. Specifically, a model in which glaciated areas acted as a barrier was much more probable based on patterns of genomic variation in Carex nova, a wet-adapted species. However, in the dry-adapted Carex chalciolepis, the permeable model was more probable, although the difference in the support of the models was small. This work highlights how statistical inferences can be used to distinguish deterministic processes that are expected to result in discordant genomic patterns among species, including species-specific responses to climate change.
© 2016 John Wiley & Sons Ltd.

Entities:  

Keywords:  Carex; Cyperaceae; Pleistocene; Rocky Mountains; glaciation

Mesh:

Year:  2016        PMID: 27317885     DOI: 10.1111/mec.13735

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


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