Journal
MOLECULAR ECOLOGY
Volume 25, Issue 3, Pages 689-705Publisher
WILEY
DOI: 10.1111/mec.13517
Keywords
adaptive genetic differentiation; conservation genetics; gene flow; landscape genomic modelling; population genomics; riverscape genetics; salmonids
Funding
- NASA [NNX14AB84G]
- USGS Mendenhall Fellowship
- NSF [DEB-1050459, DEB-1258203]
- Montana Fish Wildlife and Parks
- Bonneville Power Administration [2010-026-00, 2008-907-00, 2009-005-00]
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Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population-specific and pairwise F-ST) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate-related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and F-ST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin-wide to the metapopulation scale). Sensitivity analysis (leave-one-population-out) revealed consistent relationships between climate variables and F(ST)within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N=10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.
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