A long‐term evaluation of biopsy darts and DNA to estimate cougar density: An agency‐citizen science collaboration

Abstract

Accurately estimating cougar (Puma concolor) density is usually based on long‐term research consisting of intensive capture and Global Positioning System collaring efforts and may cost hundreds of thousands of dollars annually. Because wildlife agency budgets rarely accommodate this approach, most infer cougar density from published literature, rely on short‐term studies, or use hunter harvest data as a surrogate in their jurisdictions; all of which may limit accuracy and increase risk of management actions. In an effort to develop a more cost‐effective long‐term strategy, we evaluated a research approach using citizen scientists with trained hounds to tree cougars and collect tissue samples with biopsy darts. We then used the DNA to individually identify cougars and employed spatially explicit capture–recapture models to estimate cougar densities. Overall, 240 tissue samples were collected in northeastern Washington, USA, producing 166 genotypes (including recaptures and excluding dependent kittens) of 133 different cougars (8–25/yr) from 2003 to 2011. Mark–recapture analyses revealed a mean density of 2.2 cougars/100 km2 (95% CI = 1.1–4.3) and stable to decreasing population trends (β = −0.048, 95% CI = −0.106–0.011) over the 9 years of study, with an average annual harvest rate of 14% (range = 7–21%). The average annual cost per year for field sampling and genotyping was US$11,265 ($422.24/sample or $610.73/successfully genotyped sample). Our results demonstrated that long‐term biopsy sampling using citizen scientists can increase capture success and provide reliable cougar‐density information at a reasonable cost. © 2016 The Wildlife Society.

Less invasive monitoring of cougars in Colorado's front range

“…Accounting for this is especially important for cougars because they are highly mobile and utilize large home ranges (Dickson and Beier ; females ~100 km 2 with some males >750 km 2 , unpublished data from this study). With the exception of Beausoleil et al () and Proffitt et al (), densities reported above were not corrected for spatial extent and therefore, could be biased high. Spatially explicit capture–recapture models, could also be used in a similar fashion to estimate density with our data, especially if telemetered animals were not available (Efford et al , Efford and Fewster ).…”

“…Two studies effectively estimated cougar density in Montana, USA, using bio‐darting to obtain tissue samples from cougars treed by hounds, and backtracking cougars during winter to obtain hair samples (Russell et al , Proffitt et al ). Additionally, Beausoleil et al () developed an effective sampling approach using a citizen scientist approach and bio‐darting to estimate cougar density at a game management unit scale in northeastern Washington, USA. This approach does account for detection probability, but is still field intensive.…”

“…For example, although Sawaya et al () reported snow‐tracking as an effective method to estimate cougar density in their study area, Alldredge () reported that varying snow conditions and limited access to private lands made snow‐tracking logistically infeasible in the Front Range of Colorado. Similarly, Beausoleil et al () presented an effective strategy to use citizen scientists and bio‐darting, but given the extent of private property on the Front Range of Colorado, and presumably other areas with a wildland–urban interface, this would not be practical. Study area size may also dictate sampling approaches because many (mark–recapture, snow‐tracking, scat detection) would be impractical at large scales.…”

Spatially explicit population estimates for black bears based on cluster sampling

“…Cluster sampling coupled with spatially explicit capture‐recapture techniques has the potential to provide reliable estimates for a wide array of species and sampling situations. For example, SCR methods have been used in conjunction with area searches for mountain lions ( Felis concolor ; Beausoleil et al ), acoustic sampling for ovenbird ( Seiurus aurocapilla ; Dawson and Efford ), mark‐resight for raccoons ( Procyon lotor ; Sollmann et al ), camera traps for tigers ( Panthera tigris ; Gopalaswamy et al ), pellet collection for white‐tailed deer ( Odocoileus virginianus ; Goode et al ), and a variety of other methods and species. These and many other situations have the potential to benefit from cluster sampling designs when the sampling space is extensive.…”

Estimating Mountain Lion Abundance in Arizona Using Statistical Population Reconstruction

“…Unfortunately, the most common approaches for estimating mountain lion abundance tend to be too resource‐intensive to apply to large areas or annual surveys. Approaches such as mark‐recapture techniques (Lambert et al , Russell et al ), genetic mark‐recapture using DNA extracted from tissue, scat, or hair samples (Russell et al , Davidson et al , Beausoleil et al ), or identifying individuals from photographs captured by remote cameras (Kelly et al , Smythe , Negrões et al , Rosas‐Rosas and Bender ) have typically been applied to a limited geographic area or population. Recent advances in spatial mark‐resight models using camera trap data provide another means to estimate abundance (Rich et al , Murphy et al ) but still may be cost‐ and labor‐prohibitive for long‐term monitoring across a large landscape (Skalski et al , Clawson et al , Hatter ).…”