Jennifer M. Foca

Population density estimates are invaluable to wildlife managers, but difficult to attain. Several methods have been developed to estimate density using camera traps, many of which require further testing. The time-in-front-of-the-camera (TIFC) approach allows for density estimation when “unmarked” individuals are monitored using camera traps. We applied the TIFC model to populations of bison (Bison bison, B. bison athabascae), elk (Cervus elaphus canadensis), and moose (Alces alces) in Elk Island National Park (EINP) and to populations of elk and moose in Cooking Lake – Blackfoot Provincial Recreation Area (BPRA). EINP and BPRA are fully fenced natural areas in the Beaverhills Region of central Alberta, Canada. Our objectives were to (i) use the TIFC model to estimate ungulate densities in EINP and BPRA, and (ii) compare the performance of TIFC density estimates against aerial ungulate survey estimates. Camera trap data were collected from 43 cameras in EINP between December 2016 and October 2020, and 23 cameras in BPRA from April 2019 to August 2020. Annual densities were estimated in EINP north and south (2017–2019) and in BPRA (2019). Moose density estimates had the lowest discrepancy between approaches. Bison TIFC density estimates were lower than AUS densities, and elk TIFC density estimates were higher than AUS densities. In addition to the density estimates evaluated for the three focal species, the TIFC approach also was applied to white-tailed deer (Odocoileus virginianus) and mule deer (O. hemionus) in EINP and BPRA, in the absence of aerial survey data. We conclude that the TIFC model and AUS were complementary, with pros and cons of the two approaches varying based on focal species ecology. Careful consideration is required for several factors related to camera study design for TIFC density estimation that can affect the accuracy and precision of estimates.

Anthropogenic development affects the behavior and distribution of species both by removing and altering habitat in the development footprint and through adjacency effects within a zone of influence (ZOI) around development. Accurate estimates of ZOI are needed to understand and mitigate impacts from human development, but quantitative estimates of ZOI are rare, and most studies that develop them do so only for a single species. We developed an approach to estimate seasonal ZOI for multiple species using remote camera data. Seasonal habitat models formed the basis of the approach that we applied to four large mammals in the Elk Valley, British Columbia, Canada: bighorn sheep (Ovis canadensis), elk (Cervus canadensis), moose (Alces alces), and grizzly bears (Ursus arctos). We estimated the ZOI from open‐pit metallurgical coal mines for each species by forcing a categorical distance to mine variable into the top habitat model in each season. Our multispecies approach identified diverse ZOI responses to mining, ranging from strongly positive for bighorn sheep and elk to somewhat negative for grizzly bears and strongly negative for moose, with some seasonal variation. Our results highlight important conservation implications of estimating ZOI for multiple species. Species that exhibit positive ZOI may benefit from targeted on‐site reclamation efforts. Conversely, those that exhibit negative ZOI may benefit from mitigation strategies that address the underlying mechanisms driving the negative response, aiming to minimize ZOI. Additionally, implementing actions to offset adverse impacts could further enhance the overall outcome. Mixed mitigation strategies are more complex to implement but may be needed to prevent ongoing declines in global wildlife populations as governments and industry work toward recent nature‐positive commitments for our planet.

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.

Elk Island National Park (EINP) is a fenced park in the Beaver Hills UNESCO Biosphere Reserve of central Alberta where aspen parkland is being conserved. This area maintains high densities of native ungulates including elk (Cervus elaphus), bison (Bison bison bison,B. bison athabascae), moose (Alces alces), white-tailed deer (Odocoileus virginianus), and mule deer (O. hemionus). Our objective was to evaluate spatiotemporal overlap and interspecific interactions between bison and elk in EINP using camera traps. Bison and elk have overlapping habitat use and diet and are the primary focus of ungulate management in EINP. We examined distributions of both species in relation to season, landscape characteristics, anthropogenic features, and heterospecifics using generalized linear models (GLMs). We then examined seasonal daily activity patterns of bison and elk and calculated the degree of overlap. The spatial analysis revealed that bison counts were positively associated with higher proportions of open habitats across seasons and in areas farther from water in summer and fall but had no associations with distance to water during winter. Bison removal year (years during which bison removals were conducted by Parks Canada) was a significant predictor variable for bison counts in winter when the bison roundup takes place. Elk avoided areas with high linear feature density across seasons. During fall and winter, we observed higher elk counts associated with bison presence. Temporal activity patterns revealed that elk were crepuscular in all three seasons, but bison activity patterns varied with diurnal activity being more common in the summer, crepuscular activity in winter, and intermediate activity patterns during fall. Coefficients of overlap between elk and bison were high in all three seasons with the greatest difference in daily activity patterns in summer and the highest overlap in winter when both species showed strong crepuscular activity. Despite the fenced perimeter in EINP resulting in high ungulate densities, limited dispersal, and low predation, our data show patterns of habitat use and interactions between bison and elk that were similar to those in other systems. Spatiotemporal partitioning does not appear necessary for coexistence of bison and elk in the aspen parkland.