Use of spatial capture-recapture modeling and DNA data to estimate densities of elusive animals.

摘要: Abstract: Assessment of abundance, survival, recruitment rates, and density (i.e., population assessment) is especially challenging for elusive species most in need protection (e.g., rare carnivores). Individual identification methods, such as DNA sampling, provide ways studying efficiently noninvasively. Additionally, statistical methods that correct undetected animals account locations where are captured available to estimate other demographic parameters. We collected hair samples European wildcat (Felis silvestris) from cheek-rub lure sticks, extracted the samples, identified each animals’ genotype. To wildcats, we used Bayesian inference a spatial capture-recapture model. WinBUGS fit model accounted differences detection probability among individuals seasons between two arrays. detected 21 individual wildcats (including possible hybrids) 47 times. Wildcat was estimated at 0.29/km2 (SE 0.06), 95% activity occur within 1.83 km their home-range center. Lures located systematically were associated with greater number detections than lures placed cell on basis expert opinion. Detection cats greatest late March. Our generalized linear mixed model; hence, it can be easily extended, instance, incorporate trap- individual-level covariates. believe combined use noninvasive sampling techniques models will improve assessments, animals.