Dataset

Data from: Linking genetic kinship and demographic analyses to characterize dispersal: methods and application to Blanding’s turtle

Reid, B. N. (Creator), Thiel, R. P. (Creator), Palsboll, P. (Creator), Peery, M. Z. (Creator), University of Groningen, 16-Aug-2016

Dataset

  • Brendan N. Reid (Creator)
  • Richard P Thiel (Creator)
  • Per Palsboll (Creator)
  • M. Zachariah Peery (Creator)
  • Department of Herpetology, American Museum of Natural History, Central Park West at 79 Street, New York, NY 10024. breid@amnh.org.
  • Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53704.

Description

This dataset includes location and genetic data for Blanding's turtles sampled in Wood County, WI. The first sheet ("NestingFemaleData") includes data for females captured during terrestrial nesting surveys. Nesting areas are as described in the publication; any turtle captured outside of the seven main nesting areas identified are listed as "other". The second sheet ("NonNestingData") includes all other turtles, including adult males, adult females captured in aquatic locations, and juveniles of unknown sex. For all location data, "X" and "Y" are UTM coordinates (UTM zone 15N, WGS84 datum). When individuals were captured more than once, coordinates represent the centroid of all capture points. Missing data for microsatellites are represented as "xxx".
Date made available16-Aug-2016
PublisherUniversity of Groningen
Geographical coverageWood County, Wisconsin, USA
Access to the dataset Open
Contact researchdata@rug.nl

    Keywords on Datasets

  • Mark-recapture, breeding dispersal, natal dispersal, population simulation, spatial genetic autocorrelation, Emydoidea blandingii
Related Publications
  1. Linking genetic kinship and demographic analyses to characterize dispersal: Methods and application to Blanding's turtle

    Reid, B. N., Thiel, R. P., Palsbøll, P. J. & Peery, M. Z., 2016, In : Journal of Heredity. 107, 7, p. 603-614 12 p.

    Research output: Contribution to journalArticleAcademicpeer-review

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ID: 72130007