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

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International Association for Bear Research and Management

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We evaluated the efficiency of an extension of a single season capture–mark–recapture (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 ( = 15–22), the Huggins robust-design model provided precise estimates of abundance (CV  =  8–14%) and female apparent survival (CV  =  9%). Apparent survival for females (ϕ =  0.80, SE  =  0.07) was 2.2× higher than for males (ϕ  =  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 population 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.

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