A robust-design analysis to estimate American black bear population parameters in Utah

A robust-design analysis to estimate American black bear population parameters in Utah

We eveluated the efficiency of an extension of a single season capture-markrecapture (CMR) population estimation method, a closed-capture robust-design model, to monitor trends in population size, apparent survival, and temporary emigration rates over a 5-year period for a low-density population of American black bears (Ursus americanus) in north central Utah, USA. We also used robust-design Pradel models to estimate finite rate of population change and recruitment. We identified individual bears through genetic analysis of tissue samples collected non-invasively at scent-lured sampling sites. Although the population was relatively small (N̂ = 15-22), the Huggins robust-design model procise estimates of abundance (CV = 8-14%) and female apparent survival (CV = 9%). Apparent survival for females (ɸ = 0.80, SE = 0.07) was 2.2× higher than for males (ɸ = 0.36, SE = 0.12; p = 0.003). In contrast, temporary emigration was 40.8× higher for males (γ' = 0.58. SE = 0.24) than for females (γ' = 0.004. SE = 0.06; p = 0.024). Data were insufficient to estimate probability of staying for either sex. From the Pradel model, finite rate of populiation change was similar for males and females (λ = 1.05, SE = 0.12 for females; λ = 1.11, SE = 0.16 for males ) but recruitment was 3.0× higher for males (f = 0.75, SE = 0.17) than for females (f = 0.25, SE = 0.10; p = 0.013). Population size appeared to be stable or slightly increasing over the 5-year period. This noninvasive CMR study provided relatively efficient, precise estimates of a low-density black bear population on a small study site. We recommend using robust-design closed capture models if samples are taken over multiple years; in addition to population size, apparent survival, movement, recruitment, and finite population change can be estimated, providing timely insights into population trends and the mechanisms driving them.

  • Author(s) Jordan C. Pederson and Kevin D. Bunnell and Mary M. Conner and Craig R. McLaughlin
  • Volume 23
  • Issue 1
  • Pages 104-116
  • Publication Date 1 May 2012
  • DOI 10.2192/ursus-d-10-00029.1
  • File Size 360.18 KB