Subsistence hunting, or “country food,” is essential for Indigenous Peoples who face high food insecurity and is critical for Indigenous Food Sovereignty. For many First Nations of Canada, subsistence hunting is also inextricably linked to traditional conservation practices, as hunting is an important way of engaging with nature. In the boreal of Canada, large game such as moose (Alces alces) are a primary source of protein for many First Nations. However, resource extraction, including forestry practices and oil and gas extraction, has shifted large game distributions and affected the availability and abundance of food resources. Here, we used remote camera trap data and generalized linear models to evaluate moose habitat use and spatial-numerical response to possible stressors in north-central Alberta, including fire, harvest, oil and gas extraction, and other disturbances. We also examined the effects of human-caused stressors on habitat use by sex and age class data. The proportion of various land cover types and human land use for resource extraction were important in moose habitat use. Overall, adult moose avoided burned areas and grasslands. Notably, male, female, and young moose all used habitat differently and at different spatial scales. However, young moose (with their mothers) strongly selected natural forest disturbances such as burned areas but avoided human-created disturbances such as petroleum exploration “seismic” lines. Female moose with young attempting to maximize forage opportunities do not use human-disturbed forests in the same ways they use naturally disturbed areas. This also aligns with observations from Indigenous communities, which have linked human disturbance to declines in moose densities and displacement from traditional hunting grounds. Understanding and predicting shifts in large game distributions is critical to supporting Indigenous Food Sovereignty and identifying where industries operating on First Nations lands can better engage responsibly with First Nations.

The global urban population is expected to increase by 2.5 billion people over the next 30 years. Yet the doubling of urban landscapes in the last decades have already led to habitat loss and concomitant impacts to biodiversity. Nonetheless urban landscapes remain important for wildlife, and global syntheses have revealed that wealthy urban areas house more biodiversity, a ‘luxury effect’. We researched some of the mechanisms for the luxury effect for urban black-tailed deer, a species of increasing concern in urban landscapes across the northwestern Nearctic. We satellite collared twenty deer in an urban landscape in British Columbia, Canada, with high-resolution fix rates. We used generalized models in an information-theoretic framework to weigh evidence for competing hypotheses about the role of tree cover, productivity, public green spaces, and wealth in explaining deer selection. Wealth, manifesting as housing lot size, emerged as the dominant predictor of deer space-use, which is highly concentrated into very small home-ranges. Other landscape elements stemming from affluence, including golf courses and parklands, were also strongly selected by deer. We show post-colonization landscape conversion from dry semi-arid savannah to well-watered high-productivity landscapes is supporting deer, with ramifications for the rest of the biotic community. With urban landscapes becoming an increasingly important for biodiversity conservation, understanding these mechanisms can help to promote wildlife-human coexistence.

Human disturbance directly affects animal populations but indirect effects of disturbance on species behaviors are less well understood. Camera traps provide an opportunity to investigate variation in animal behaviors across gradients of disturbance. We used camera trap data to test predictions about predator-sensitive behavior in three ungulate species (caribou Rangifer tarandus; white-tailed deer, Odocoileus virginianus; moose, Alces alces) across two boreal forest landscapes varying in disturbance. We quantified behavior as the number of camera trap photos per detection event and tested its relationship to predation risk between a landscape with greater industrial disturbance and predator abundance (Algar) and a “control” landscape with lower human and predator activity (Richardson). We also assessed the influence of predation risk and habitat on behavior across camera sites within the disturbed Algar landscape. We predicted that animals in areas with greater predation risk (more wolf activity, less cover) would travel faster and generate fewer photos per event, while animals in areas with less predation risk would linger (rest, forage), generating more photos per event. Consistent with predictions, caribou and moose had more photos per event in the landscape where predation risk was reduced. Within the disturbed landscape, no prey species showed a significant behavioral response to wolf activity, but the number of photos per event decreased for white-tailed deer with increasing line of sight (m) along seismic lines (i.e. decreasing visual cover), consistent with a predator-sensitive response. The presence of juveniles was associated with shorter behavioral events for caribou and moose, suggesting greater predator sensitivity for females with calves. Only moose demonstrated a positive association with vegetation productivity (NDVI), suggesting that for other species influences of forage availability were generally weaker than those from predation risk. Behavioral insights can be gleaned from camera trap surveys and provide information about animal responses to predation risk and the indirect impacts of human disturbances.

Density estimation is a key goal in ecology but accurate estimates remain elusive, especially for unmarked animals. Data from camera-trap networks combined with new density estimation models can bridge this gap but recent research has shown marked variability in accuracy, precision, and concordance among estimators. We extend this work by comparing estimates from two different classes of models: unmarked spatial capture-recapture (spatial count, SC) models, and Time In Front of Camera (TIFC) models, a class of random encounter model. We estimated density for four large mammal species with different movement rates, behaviours, and sociality, as these traits directly relate to model assumptions. TIFC density estimates were typically higher than SC model estimates for all species. Black bear TIFC estimates were ~ 10-fold greater than SC estimates. Caribou TIFC estimates were 2-10 fold greater than SC estimates. White-tailed deer TIFC estimates were up to 100-fold greater than SC estimates. Differences of 2-5 fold were common for other species in other years. SC estimates were annually stable except for one social species; TIFC estimates were highly annually variable in some cases and consistent in others. Tests against densities obtained from DNA surveys and aerial surveys also showed variable concordance and divergence. For gregarious animals TIFC may outperform SC due to the latter model’s assumption of independent activity centres. For curious animals likely to investigate camera traps, SC may outperform TIFC, which assumes animal behavior is unaffected by cameras. Unmarked models offer great possibilities, but a pragmatic approach employs multiple estimators where possible, considers the ecological plausibility of assumptions, and uses an informed multi-inference approach to seek estimates from models with assumptions best fitting a species’ biology.

1. Landscape change is a key driver of biodiversity declines due to habitat loss and fragmentation, but spatially shifting resources can also facilitate range expansion and invasion. Invasive populations are reproductively successful, and landscape change may buoy this success. 2. We show how modelling the spatial structure of reproductive success can elucidate the mechanisms of range shifts and sustained invasions for mammalian species with attendant young. We use an example of white-tailed deer (deer; Odocoileus virginianus) expansion in the Nearctic boreal forest, a North American phenomenon implicated in severe declines of threatened woodland caribou (Rangifer tarandus). 3. We hypothesized that deer reproductive success is linked to forage subsidies provided by extensive landscape change via resource extraction. We measured deer occurrence using data from 62 camera-traps in northern Alberta, Canada, over three years. We weighed support for multiple competing hypotheses about deer reproductive success using multi-state occupancy models and generalized linear models in an AIC-based model selection framework. 4. Spatial patterns of reproductive success were best explained by features associated with petroleum exploration and extraction, which offer early seral vegetation resource subsidies. Effect sizes of anthropogenic features eclipsed natural heterogeneity by two orders of magnitude. We conclude that deer populations are likely buffered from overwinter mortality by landscape change, wherein early seral forage subsidies support high springtime reproductive success to offset or exceed winter losses. 5. Synthesis and Applications. Modelling spatial structuring in reproductive success can become a key goal of remote camera-based global networks, yielding ecological insights into mechanisms of invasion and range shifts to inform effective decision-making for global biodiversity conservation.