• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • No language data
  • Tagged with
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

A COMPARISON OF NONINVASIVE SURVEY METHODS FOR MONITORING MESOCARNIVORE POPULATIONS IN KENTUCKY

Tom, Bryan Matthew 01 January 2012 (has links)
Harvest data are typically used to evaluate mesocarnivore population dynamics in many states, including Kentucky. While relatively easy to collect, these data are subject to reporting biases, and inferences about population trends can often only be made at coarse spatial scales. Gray fox (Urocyon cinereoargenteus), bobcat (Lynx rufus), and coyote (Canis latrans) populations in Kentucky are managed primarily through harvest data used to establish future harvest quotas. Increasingly, noninvasive survey methods have been used to characterize a number of population parameters for a variety of species; however, successful use of these methods is often site-specific. We assessed the efficacy and cost-effectiveness of two noninvasive survey methods, scat detection dogs and rub-pad hair snares, for surveying mesocarnivore species at two sites in the mixed-mesophytic forest of northeastern Kentucky. We sampled 100 hair snares covering approximately 100km2 and 27 transects covering approximately 27km2 from which 7 hair samples and 261 scat samples were collected respectively. Hair snares cost $397/sample at 6.4 hours/day, while scat detection dogs cost $47/sample at 4.9 hours/day. Genetic methods were used to identify biological samples to species and individual. Our findings should prove useful to state wildlife managers in comparatively evaluating methods for future mesocarnivore monitoring.

Page generated in 0.0641 seconds