Estimating Coyote Densities with Local, Discrete Bayesian Capture‐Recapture Models

Abstract

Recent advances in noninvasive genetic sampling and spatial capture-recapture (SCR) techniques are particularly useful for monitoring cryptic wildlife species such as carnivores. In southern Arizona, USA, coyotes (Canis latrans) are thought to negatively affect endangered Sonoran pronghorn (Antilocapra americana sonoriensis), although no estimates of coyote abundance or monitoring programs exist. Sonoran pronghorn are provided supplemental feed and water in this region, resulting in areas where pronghorn and other species are congregated. Because of the higher density of artificial water sources for Sonoran pronghorn on the Cabeza Prieta National Wildlife Refuge (CPNWR), we predicted that coyote density would be higher relative to the Barry M. Goldwater Range (BMGR), where artificial water sources are less dense. We used discrete Bayesian SCR models in a local evaluation approach to provide baseline estimates of coyote abundance and understand how coyote density varied between 2 contrasting areas of land use. We identified 106 individuals from scat samples across 3 sessions in 2013 and 2014 and achieved high genotyping and individual identification success rates (~78%). Encounter rates at water catchments were nearly 11 times higher compared to road and trail transects. As predicted, we found that coyote density was on average 2 times higher on the CPNWR (11.2 coyotes/100 km 2) compared to the BMGR (5.3 coyotes/100 km 2). The local evaluation approach significantly reduced computational time, making the discrete Bayesian approach more practical to implement across a large study area. Our study represents an important contribution towards developing a robust monitoring program for coyotes. We hope that our novel implementation of the local evaluation approach increases the ability of wildlife managers to understand the effects of land use and other ecological influences on large carnivore populations.

Evidence of reduced abundance, density, and survival of coyotes under federal management for red wolf recovery

“…22.2 in Bekoff & Gese, 2003; abstract summaries in Mastro et al, 2012), those in the NC Recovery Area were lower than densities reported in all regions except those reported at the coyote's northernmost range limits (e.g., O'Donoghue et al, 1997). We also report lower coyote density estimates than those reported in more recent studies such as those conducted in southwest Arizona (53.0–112 coyotes/1000 km 2 ; Woodruff et al, 2021), the Great Basin Desert of Utah (70–80 coyotes/1000 km 2 ; Lonsinger et al, 2018), the Appalachian region of Virginia (24–90 coyotes/1000 km 2 ; Morin et al, 2016), and the Savannah River region of South Carolina (800–1500 coyotes/1000 km 2 ; Kilgo et al, 2017). Of those studies, Appalachia and the Savannah River region were neighboring areas of the NC Recovery Area exhibiting greater densities of coyotes.…”

An efficient method for simultaneous species, individual, and sex identification via in‐solution single nucleotide polymorphism capture from low‐quality scat samples

“…Assuming that the total suitable habitat in the sampled region is 800 km 2 , that is, the total area sampled not including the mountainous habitat in the southeast, the density of coyotes in the area is 0.10 individuals/km 2 (95% CI = 48–210 or 0.06–0.26 coyotes/km 2 ). Previous studies of western coyotes have reported values including 0.053–0.112 coyote/km 2 (Woodruff et al, 2021), 0.14 coyotes/km 2 (Ralls & White, 1995), and 0.07–0.08 coyotes/km 2 (Lonsinger, Lukacs, et al, 2018). In general, coyote densities tend to be lower in desert areas where they are sympatric with kit foxes because coyotes have higher water needs than kit foxes which are better adapted to arid environments (Lonsinger, Lukacs, et al, 2018).…”

“…Because canids tend to be elusive and difficult to study, noninvasive genetic sampling methods have been utilized extensively, for example, to estimate abundance and genetic diversity of coyotes (e.g., Morin et al, 2016; Prugh et al, 2005; Woodruff et al, 2021) and kit foxes (e.g., Lonsinger et al, 2018; Lonsinger et al, 2018; Wilbert et al, 2015, 2019). Scat, the most commonly collected material in noninvasive genetic studies (Waits & Paetkau, 2005), is particularly easy to identify in the field because canids defecate to mark territories (Morin et al, 2016).…”

Population density and ranging behaviour of a generalist carnivore varies with human population

“…For example, the red fox ( Vulpes vulpes ) has adapted to cities globally, with densities up to four times greater in cities than in adjacent rural areas (Marks & Bloomfield, 1999 ), and human footprint is the biggest driver of fox home range size on a global scale (Main et al., 2020 ). Coyote ( Canis latrans ) populations are denser around clumped natural resources (Woodruff et al., 2021 ), and have also adapted to urban environments, where they can reach higher densities than in rural areas (Fedriani et al., 2001 ; Jonathan, 2011 ). Coyote home ranges are also smaller in urban environments (Grubbs & Krausman, 2009 ), indicating that they are obtaining sufficient resources from a smaller area than they would normally obtain from more natural settings.…”