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North-facing slopes and elevation shape asymmetric genetic structure in the range-restricted salamander Plethodon shenandoah.

Kevin P MulderNandadevi Cortes-RodriguezEvan H Campbell GrantAdrianne B BrandRobert C Fleischer
Published in: Ecology and evolution (2019)
Species with narrow environmental tolerances are often distributed within fragmented patches of suitable habitat, and dispersal among these subpopulations can be difficult to directly observe. Genetic data can help quantify gene flow between localities, which is especially important for vulnerable species with a disjunct range. The Shenandoah salamander (Plethodon shenandoah) is a federally endangered species known only from three mountaintops in Virginia, USA. To reconstruct the evolutionary history and population connectivity of this species, we generated both mitochondrial and nuclear data using sequence capture from individuals collected across all three mountaintops. Applying population and landscape genetic methods, we found strong population structure that was independent of geographic distance. Both the nuclear markers and mitochondrial genomes indicated a deep split between the most southern population and the genetically similar central and northern populations. Although there was some mitochondrial haplotype-splitting between the central and northern populations, there was admixture in nuclear markers. This is indicative of either a recent split or current male-biased dispersal among mountain isolates. Models of landscape resistance found that dispersal across north-facing slopes at mid-elevation levels best explain the observed genetic structure among populations. These unexpected results highlight the importance of incorporating landscape features in understanding and predicting the movement and fragmentation of this range-restricted salamander species across space.
Keyphrases
  • genetic diversity
  • genome wide
  • copy number
  • oxidative stress
  • electronic health record
  • single cell
  • dna methylation
  • climate change
  • big data
  • functional connectivity
  • white matter
  • data analysis