Density estimates accounting for differential animal detectability are difficult to acquire for wide-ranging and elusive species such as mammalian carnivores. Pairing distance sampling with call-response surveys may provide an efficient means of tracking changes in populations of coyotes (Canis latrans), a species of particular interest in the eastern United States. Blind field trials in rural New York State indicated 119-m linear error for triangulated coyote calls, and a 1.8-km distance threshold for call detectability, which was sufficient to estimate a detection function with precision using distance sampling. We conducted statewide road-based surveys with sampling locations spaced ≥6 km apart from June to August 2010. Each detected call (be it a single or group) counted as a single object, representing 1 territorial pair, because of uncertainty in the number of vocalizing animals. From 524 survey points and 75 detections, we estimated the probability of detecting a calling coyote to be 0.17 ± 0.02 SE, yielding a detection-corrected index of 0.75 pairs/10 km2 (95% CI: 0.52–1.1, 18.5% CV) for a minimum of 8,133 pairs across rural New York State. Importantly, we consider this an index rather than true estimate of abundance given the unknown probability of coyote availability for detection during our surveys. Even so, pairing distance sampling with call-response surveys provided a novel, efficient, and noninvasive means of monitoring populations of wide-ranging and elusive, albeit reliably vocal, mammalian carnivores. Our approach offers an effective new means of tracking species like coyotes, one that is readily extendable to other species and geographic extents, provided key assumptions of distance sampling are met.
Additional publication details
|Publication Subtype||Journal Article|
|Title||Pairing call-response surveys and distance sampling for a mammalian carnivore|
|Series title||Journal of Wildlife Management|
|Contributing office(s)||Patuxent Wildlife Research Center|
|Online Only (Y/N)||N|
|Additional Online Files (Y/N)||N|