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Empirical validation of closed population abundance estimates and spatially explicit density estimates using a censused population of North American red squirrels

  • Author / Creator
    Van Katwyk, Kristin E
  • Capture-mark-recapture (CMR) data is widely used to estimate a range of population parameters including abundance and density. Closed population estimators have gained wide acceptance and have become increasingly sophisticated. More recently, spatially explicit capture-recapture (SECR) models implemented have gained popularity. Although model accuracy has been tested via simulation studies there have been few empirical tests of either method. I took advantage of a fully enumerated population of red squirrels (Tamiasciurus hudsonicus) to test the accuracy of closed population abundance estimator and the maximum likelihood SECR density estimator. I found abundance estimates were positively biased by 45%, largely due to trapping grid edge effects. Adjusting for edge effects via the boundary strip method decreased bias to -22%. With the addition of inter-trap movements, SECR models produced density estimates that were negatively biased by only 4.6%. These empirical validations support the use of SECR models for density estimates or derived population abundance.

  • Subjects / Keywords
  • Graduation date
    2014-06
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3C53F88Z
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Biological Sciences
  • Specialization
    • Ecology
  • Supervisor / co-supervisor and their department(s)
    • Boutin, Stan (Biological Sciences)
  • Examining committee members and their departments
    • Derocher, Andrew (Biological Sciences)
    • Bayne, Erin (Biological Sciences)