Survival and Recruitment of Gray Wolf Pups Before and after Harvest

Knowledge about recruitment in a population can be critical when making conservation decisions, particularly for harvested species. Harvest can affect population demography in complex ways and this may be particularly true for species whose successful reproduction is linked with complex social dynamics. We used noninvasive genetic sampling and a natural experiment to estimate recruitment in gray wolves (Canis lupus) before and after harvest in the northern Rocky Mountains, Idaho USA (2008-2013). We hypothesized that recruitment would decline after hunting and trapping began and that the decline in recruitment would be attributable to the harvest of pups and not subtler mechanisms associated with group dynamics and reduced reproductive success. We collected fecal samples from wolves in 10 packs for 6 consecutive years, extracted DNA, and genotyped 154 individual pups across 18 microsatellite loci. Population harvest rates averaged 23.8% (SD = 9.2). Our hypothesis that recruitment would decline was supported; survival from 3 – 15 months of age decreased from 0.60 (95% CI: 0.48-0.72) without harvest to 0.38 (95% CI: 0.28-0.48) with harvest and recruitment declined from 3.2 (95% CI: 2.1-4.3) to 1.6 (95% CI: 1.1-2.1) pups per pack after harvest was initiated. We attributed just 18-38% of pup mortality directly to harvest and suggest that there are indirect effects of harvest on recruitment that may be associated with changes in group size and structure. Models that do not include both direct and indirect effects of harvest on recruitment may underestimate the potential impact of harvest on population growth in social species

Hair of the Dog: Obtaining Samples From Coyotes and Wolves Noninvasively

Canids can be difficult to detect and their populations difficult to monitor. We tested whether hair samples could be collected from coyotes (Canis latrans) in Texas, USA and gray wolves (C. lupus) in Montana, USA using lure to elicit rubbing behavior at both man-made and natural collection devices. We usedmitochondrial and nuclearDNA to determine whether collected hair samples were from coyote, wolf, or nontarget species. Both coyotes and wolves rubbed on man-made barbed surfaces but coyotes in Texas seldom rubbed on hanging barbed surfaces. Wolves in Montana showed a tendency to rub at stations where natural material collection devices (sticks and debris) were present. Time to detection was relatively short (5 nights and 4 nights for coyotes and wolves, respectively) with nontarget and unknown species comprising approximately 26% of the detections in both locations. Eliciting rubbing behavior from coyotes and wolves using lures has advantages over opportunistic genetic sampling methods (e.g., scat transects) because it elicits a behavior that deposits a hair sample at a fixed sampling location, thereby increasing the efficiency of sampling for these canids. Hair samples from rub stations could be used to provide estimates of abundance, measures of genetic diversity and health, and detection–nondetection data useful for cost-effective population monitoring

Virtual snow stakes: a new method for snow depth measurement at remote camera stations

Abstract Remote cameras are used to study demographics, ecological processes, and behavior of wildlife populations. Cameras have also been used to measure snow depth with physical snow stakes. However, concerns that physical instruments at camera sites may influence animal behavior limit installation of instruments to facilitate collecting such data. Given that snow depth data are inherently contained within images, potential insights that could be made using these data are lost. To facilitate camera‐based snow depth observations without additional equipment installation, we developed a method implemented in an R package called edger to superimpose virtual measurement devices onto images. The virtual snow stakes can be used to derive snow depth measurements. We validated the method for snow depth estimation using camera data from Latah County, Idaho, USA in winter 2020–2021. Mean bias error between the virtual snow stake and a physical snow stake was 5.8 cm; the mean absolute bias error was 8.8 cm. The mean Nash Sutcliffe Efficiency score comparing the fit of the 2 sets of measurements within each camera was 0.748, indicating good agreement. The edger package provides researchers with a means to take critical measurements for ecological studies without the use of physical objects that could alter animal behavior, and snow data at finer scales can complement other snow data sources that have coarser spatial and temporal resolution

S1;S2 from Harvest and group effects on pup survival in a cooperative breeder

S1. Details of sample of wolves harvested in Idaho USA, 2009-2014. Month animal was harvested is listed in parentheses. BF = breeding female, BM = breeding male, NBF = nonbreeding female, NBM = nonbreeding male. Not all harvested wolves had viable DNA samples or complete information taken during mandatory hunter check-in. This table does not represent the total harvest for the study areas in this paper.;S2. Data used for analysis of pup survival, Alberta, Idaho and Yellowstone National Park, Ausband et al