Genomic data detect corresponding signatures of population size change on an ecological time scale in two salamander species.

  • Associate Professor
  • BMF
  • Associate Chair
  • Bioinformatics and Computational Biology
  • Biology
  • Ecology and Evolutionary Biology
  • Genetics and Genomics
316 TH Morgan Building
TitleGenomic data detect corresponding signatures of population size change on an ecological time scale in two salamander species.
Publication TypeJournal Article
Year of Publication2017
JournalMolecular ecology

Understanding the demography of species over recent history (e.g. <100 years) is critical in studies of ecology and evolution, but records of population history are rarely available. Surveying genetic variation is a potential alternative to census-based estimates of population size, and can yield insight into the demography of a population. However, to assess the performance of genetic methods, it is important to compare their estimates of population history to known demography. Here, we leveraged the exceptional resources from a wetland with 37 years of amphibian mark-recapture data to study the utility of genetically based demographic inference on salamander species with documented population declines (Ambystoma talpoideum) and expansions (A. opacum), patterns that have been shown to be correlated with changes in wetland hydroperiod. We generated ddRAD data from two temporally sampled populations of A. opacum (1993, 2013) and A. talpoideum (1984, 2011) and used coalescent-based demographic inference to compare alternate evolutionary models. For both species, demographic model inference supported population size changes that corroborated mark-recapture data. Parameter estimation in A. talpoideum was robust to our variations in analytical approach, while estimates for A. opacum were highly inconsistent, tempering our confidence in detecting a demographic trend in this species. Overall, our robust results in A. talpoideum suggest that genome-based demographic inference has utility on an ecological scale, but researchers should also be cognizant that these methods may not work in all systems and evolutionary scenarios. Demographic inference may be an important tool for population monitoring and conservation management planning.

Short TitleMol Ecol
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