Energy development and consumption drive changes in global climate, landscapes, and biodiversity. The oil sands of western Canada are an epicenter of oil production, creating landscapes without current or historical analogs. Science and policy often focus on pipelines and species‐at‐risk declines, but we hypothesized that differential responses to anthropogenic disturbances shift the entire mammal community. Analysis of data collected from 3 years of camera trapping and species distribution models indicated that anthropogenic features best explained the distributions of the ten mammal species included in the study. Relative abundances of some mammals were positively correlated with anthropogenic feature density, and others were negatively correlated. Effect sizes were often larger than for natural features. Increasing anthropogenic spatial complexity, access to multiple habitats, and new forage sources favor generalist predators and browsers, to the detriment of specialists, likely altering ecological processes. This issue has far‐reaching implications: as the oil sands landscape changes so too does its mammal community, serving as a bellwether of future change for energy landscapes worldwide.
Climate and landscape change are drivers of species range shifts and biodiversity loss; understanding how they facilitate and sustain invasions has been empirically challenging. Winter severity is decreasing with climate change and is a predicted mechanism of contemporary and future range shifts. For example, white-tailed deer (Odocoileus virginianus) expansion is a continental phenomenon across the Nearctic with ecological consequences for entire biotic communities. We capitalized on recent temporal variation in winter severity to examine spatial and temporal dynamics of invasive deer distribution in the Nearctic boreal forest. We hypothesized deer distribution would decrease in severe winters reflecting historical climate constraints, and remain more static in moderate winters reflecting recent climate. Further, we predicted that regardless of winter severity, deer distribution would persist and be best explained by early seral forage subsidies from extensive landscape change via resource extraction. We applied dynamic occupancy models in time, and species distribution models in space, to data from 62 camera traps sampled over 3 years in northeastern Alberta, Canada. Deer distribution shrank more markedly in severe winters but rebounded each spring regardless of winter severity. Deer distribution was best explained by anthropogenic landscape features assumed to provide early seral vegetation subsidy, accounting for natural landcover. We conclude that deer dynamics in the northern boreal forest are influenced both by landscape change across space and winter severity through time, the latter expected to further decrease with climate change. We contend that the combined influence of these two drivers is likely pervasive for many species, with changing resources offsetting or augmenting physiological limitations.
Camera traps (CTs) are an increasingly popular method of studying animal behavior. However, the impact of cameras on detected individuals-such as from mechanical noise, odor, and emitted light-has received relatively little attention. These impacts are particularly important in behavioral studies in conservation that seek to ascribe changes in behavior to relevant environmental factors. In this article, we discuss three sources of bias that are relevant to conservation behavior studies using CTs: (a) disturbance caused by cameras; (b) variation in animal-detection parameters across camera models; and (c) biased detection across individuals and age, sex, and behavioral classes. We propose several recommendations aimed at mitigating responses to CTs by wildlife. Our recommendations offer a platform for the development of more rigorous and robust behavioral studies using CT technology and, if adopted, would result in greater applied benefits for conservation and management.
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