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

Schyler O. Nunziata, Stacey L. Lance, David E. Scott, Emily Moriarty Lemmon, David W. Weisrock

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)1060-1074
Number of pages15
JournalMolecular Ecology
Volume26
Issue number4
DOIs
StatePublished - Feb 1 2017

Bibliographical note

Publisher Copyright:
© 2016 John Wiley & Sons Ltd

Funding

We thank the numerous people who have assisted with data collection, entry and management of the 37-yr Rainbow Bay study, especially J. Pechmann, B. Metts, A. Chazal, A. Dancewicz-Helmers, R. Estes, J. Greene, R. Semlitsch, J. McGregor-Morton, G. Moran and W. Gibbons. We thank the University of Kentucky Center for Computational Sciences and the Lipscomb High Performance Computing Cluster for access to computing resources. This research was supported by University of Kentucky (UKY) Department of Biology Mini-Ribble Grant, UKY College of Arts and Sciences Summer Research Fellowship, Kentucky NSF EPSCoR Award Number 3049024999, SSAR Grants in Herpetology, Kentucky Academy of Sciences Marcia Athey Fund, U. S. Department of Energy under Financial Assistance Award Number DE-FC09-07SR22506 to the University of Georgia Research Foundation, National Science Foundation Awards DEB-0949532 and DEB-1355000 (to DWW), and was also made possible by the Department of Energy's Set Aside Program and status of the Savannah River Site as a National Environmental Research Park.

FundersFunder number
Kentucky Academy of Sciences
NSF-Kentucky EPSCoR3049024999
U. S. Department of EnergyDE-FC09-07SR22506
National Science Foundation (NSF)DEB-0949532, DEB-1355000
Michigan State University-U.S. Department of Energy (MSU-DOE) Plant Research Laboratory
University of Kentucky
University of Kentucky Information Technology Department and Center for Computational Sciences
University of Georgia Research Foundation

    Keywords

    • Ambystoma
    • amphibian decline
    • coalescent
    • demographic inference
    • genetic monitoring
    • temporal samples

    ASJC Scopus subject areas

    • Ecology, Evolution, Behavior and Systematics
    • Genetics

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