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With a shrinking supply of wilderness and growing recognition that top predators can have a profound influence on ecosystems, the persistence of large carnivores in human-dominated landscapes has emerged as one of the greatest conservation challenges of our time. Carnivores fascinate society, yet these animals pose threats to people living near them, resulting in high rates of carnivore death near human settlements. We used 41 y of demographic data for more than 2,500 brown bears—one of the world’s most widely distributed and conflict-prone carnivores—to understand the behavioral and demographic mechanisms promoting carnivore coexistence in human-dominated landscapes. Bear mortality was high and unsustainable near people, but a human-induced shift to nocturnality facilitated lower risks of bear mortality and rates of conflict with people. Despite these behavioral shifts, projected population growth rates for bears in human-dominated areas revealed a source-sink dynamic. Despite some female bears successfully reproducing in the sink areas, bear persistence was reliant on a supply of immigrants from areas with minimal human influence (i.e., wilderness). Such mechanisms of coexistence reveal a striking paradox: Connectivity to wilderness areas supplies bears that likely will die from people, but these bears are essential to avert local extirpation. These insights suggest carnivores contribute to human–carnivore coexistence through behavioral and demographic mechanisms, and that connected wilderness is critical to sustain coexistence landscapes.

Mammalian predators encounter unique hunting challenges during the winter as snow increases the cost of locomotion and influences predator-prey interactions. Winter precipitation may also affect predators' ability to detect and pursue prey. We investigated the effects of snowfall events on grey wolves (Canis lupus) in a boreal forest ecosystem in northeastern Alberta, Canada. We predicted that wolves would respond to snowfall events by reducing their travel speed and the time they spent travelling. Over the course of two winters, we used remote cameras to identify localized snowfall events and estimate snow depth. We used telemetry data from 17 wolves to calculate travel speed and time spent travelling versus resting. Data were categorized by time of day (night versus day) and time since snowfall events, and analyzed using linear and logistic regression mixed-effects models. We found that wolves were less likely to travel on dates of snowfall events than any date prior to or after an event. Wolves also travelled slower during snowfall events, but only when compared to their travel speed 24 hours before. Effects were most pronounced at night, when movements appeared to be consistent with hunting behavior, and activity levels resumed within 24 hours of a snowfall event. Including snow depth as a variable did not improve model fit. Collectively, our findings suggest that wolves' response is not driven by increased hunting success or by energetic considerations resulting from increased snow depth. Instead, we propose that wolves reduce their activity levels because precipitation dampens hunting success. Snowfall events may impact wolves' ability to detect prey and changes in prey behavior could also lead to decreased encounter rates. We encourage scientists to further investigate the effects of short-term weather events on movement rates and predator-prey interactions.

Quantifying the relative influence of multiple mechanisms driving recent range expansion of non‐native species is essential for predicting future changes and for informing adaptation and management plans to protect native species. White‐tailed deer (Odocoileus virginianus) have been expanding their range into the North American boreal forest over the last half of the 20th century. This has already altered predator–prey dynamics in Alberta, Canada, where the distribution likely reaches the northern extent of its continuous range. Although current white‐tailed deer distribution is explained by both climate and human land use, the influence each factor had on the observed range expansion would depend on the spatial and temporal pattern of these changes. Our objective was to quantify the relative importance of land use and climate change as drivers of white‐tailed deer range expansion and to predict decadal changes in white‐tailed deer distribution in northern Alberta for the first half of the 21st century. An existing species distribution model was used to predict past decadal distributions of white‐tailed deer which were validated using independent data. The effects of climate and land use change were isolated by comparing predictions under theoretical “no‐change between decades” scenarios, for each factor, to predictions under observed climate and land use change. Climate changes led to more than 88%, by area, of the increases in probability of white‐tailed deer presence across all decades. The distribution is predicted to extend 100 km further north across the northeastern Alberta boreal forest as climate continues to change over the first half of the 21st century. Quantifying the relative influence of multiple mechanisms driving recent range expansion of non‐native species is essential for predicting future changes and for informing adaptation and management plans to protect native species. Our objective was to quantify the relative importance of land use and climate change as drivers of white‐tailed deer range expansion and to predict decadal changes in northern white‐tailed deer distribution for the first half of the 21st century. Climate changes led to more than 88%, by area, of the increases in probability of white‐tailed deer presence across all decades. The distribution is predicted to extend 100 km further north across the northeastern Alberta boreal forest as climate continues to change over the first half of the 21st century.

Adaptive management is a powerful means of learning about complex ecosystems, but is rarely used for recovering endangered species. Here, we demonstrate how it can benefit woodland caribou, which became the first large mammal extirpated from the contiguous United States in recent history. The continental scale of forest alteration and extended time needed for forest recovery means that relying only on habitat protection and restoration will likely fail. Therefore, population management is also needed as an emergency measure to avoid further extirpation. Reductions of predators and overabundant prey, translocations, and creating safe havens have been applied in a design covering >90,000 km². Combinations of treatments that increased multiple vital rates produced the highest population growth. Moreover, the degree of ecosystem alteration did not influence this pattern. By coordinating recovery involving scientists, governments, and First Nations, treatments were applied across vast scales to benefit this iconic species.

1. Habitat choice is an evolutionary product of animals experiencing increased fitness when preferentially occupying high-quality habitat. However, an ecological trap (ET) can occur when an animal is presented with novel conditions and the animal's assessment of habitat quality is poorly matched to its resulting fitness. 2. We tested for an ET for grizzly (brown) bears using demographic and movement data collected in an area with rich food resources and concentrated human settlement. 3. We derived measures of habitat attractiveness from occurrence models of bear food resources and estimated demographic parameters using DNA mark-recapture information collected over 8 years (2006-2013). We then paired this information with grizzly bear mortality records to investigate kill and movement rates. 4. Our results demonstrate that a valley high in both berry resources and human density was more attractive than surrounding areas, and bears occupying this region faced 17% lower apparent survival. Despite lower fitness, we detected a net flow of bears into the ET, which contributed to a study-wide population decline. 5. This work highlights the presence and pervasiveness of an ET for an apex omnivore that lacks the evolutionary cues, under human-induced rapid ecological change, to assess tradeoffs between food resources and human-caused mortality, which results in maladaptive habitat selection.

The gut microbiome impacts host health and fitness, in part through the diversification of gut metabolic function and pathogen protection. Elevations in glucocorticoids (GCs) appear to reduce gut microbiome diversity in experimental studies, suggesting that a loss of microbial diversity may be a negative consequence of increased GCs. However, given that ecological factors like food availability and population density may independently influence both GCs and microbial diversity, understanding how these factors structure the GC-microbiome relationship is crucial to interpreting its significance in wild populations. Here, we used an ecological framework to investigate the relationship between GCs and gut microbiome diversity in wild North American red squirrels ( Tamiasciurus hudsonicus ). As expected, higher GCs predicted lower gut microbiome diversity and an increase in metabolic taxa. Surprisingly, but in line with prior empirical studies on wild animals, gastrointestinal pathogens decreased as GCs increased. Both dietary heterogeneity and an upcoming food pulse exhibited direct effects on gut microbiome diversity, whereas conspecific density and reproductive activity impacted diversity indirectly via changes in host GCs. Our results provide evidence of a gut–brain axis in wild red squirrels and highlight the importance of situating the GC-gut microbiome relationship within an ecological framework.

Background Our understanding of gut microbiota has been limited primarily to findings from human and laboratory animals, but what shapes the gut microbiota in nature remains largely unknown. To fill this gap, we conducted a comprehensive study of gut microbiota of a well-studied North American red squirrel ( Tamiasciurus hudsonicus ) population. Red squirrels are territorial, solitary, and live in a highly seasonal environment and therefore represent a very attractive system to study factors that drive the temporal and spatial dynamics of gut microbiota. Result For the first time, this study revealed significant spatial patterns of gut microbiota within a host population, suggesting limited dispersal could play a role in shaping and maintaining the structure of gut microbial communities. We also found a remarkable seasonal rhythm in red squirrel’s gut microbial composition manifested by a tradeoff between relative abundance of two genera Oscillospira and Corpococcus and clearly associated with seasonal variation in diet availability. Our results show that in nature, environmental factors exert a much stronger influence on gut microbiota than host-associated factors including age and sex. Despite strong environmental effects, we found clear evidence of individuality and maternal effects, but host genetics did not seem to be a significant driver of the gut microbial communities in red squirrels. Conclusion Taken together, the results of this study emphasize the importance of external ecological factors rather than host attributes in driving temporal and spatial patterns of gut microbiota in natural environment.

Camera traps (CTs) are an increasingly popular tool for wildlife survey and monitoring. Estimating relative abundance in unmarked species is often done using detection rate as an index of relative abundance, which assumes that detection rate has a positive linear relationship with true abundance. This assumption may be violated if movement behavior varies with density, but the degree to which movement behavior is density‐dependent across taxa is unclear. The potential confounding of population‐level relative abundance indices by movement would depend on how regularly, and by what magnitude, movement rate and home‐range size vary with density. We conducted a systematic review and meta‐analysis to quantify relationships between movement rate, home‐range size, and density, across terrestrial mammalian taxa. We then simulated animal movements and CT sampling to test the effect of contrasting movement scenarios on CT detection rate indices. Overall, movement rate and home‐range size were negatively correlated with density and positively correlated with one another. The strength of the relationships varied significantly between taxa and populations. In simulations, detection rates were related to true abundance but underestimated change, particularly for slower moving species with small home ranges. In situations where animal space use changes markedly with density, we estimate that up to thirty percent of a true change in relative abundance may be missed due to the confounding effect of movement, making trend estimation more difficult. The common assumption that movement remains constant across densities is therefore violated across a wide range of mammal species. When studying unmarked species using CT detection rates, researchers and managers should explicitly consider that such indices of relative abundance reflect both density and movement. Practitioners interpreting changes in camera detection rates should be aware that observed differences may be biased low relative to true changes in abundance. Further information on animal movement, or methods that do not depend on assumptions of density‐independent movement, may be required to make robust inferences on population trends. Animal movement rate and home range size are density‐dependent across a wide range of taxa. This potentially confounds interpretation of detection indices from camera trap surveys. When studying unmarked species using detection rates, researchers and managers should explicitly consider that such indices of relative abundance reflect both density and movement.

Occupancy models are increasingly applied to data from wildlife camera‐trap (CT) surveys to estimate distribution, habitat use, or relative abundance of unmarked animals. Fundamental to the occupancy modeling framework is the temporal pattern of detections at camera stations, which is influenced by animal population density and the speed and scale of animal movement. How these factors interact with CT sampling designs to affect the interpretation of occupancy parameter estimates is unclear. We developed a simple yet ecologically relevant animal movement simulation to create CT detections for animal populations varying in movement rate, home range area, and population density. We also varied CT sampling design by the duration of sampling and the density of CTs in our simulated domain. A single‐species occupancy model was fitted to simulated detection histories, and model‐estimated probabilities of occupancy were compared to the asymptotic proportion of area occupied (PAO), calculated as the union of all simulated home ranges. Occupancy model parameter estimates were sensitive to simulated movement and sampling scenarios. Occupancy models overestimated asymptotic PAO when a low population density of simulated animals moved quickly over large home ranges and this positive bias was insensitive to sampling duration. Conversely, asymptotic PAO was underestimated when simulated animals moved slowly in large‐ or intermediately sized home ranges. This negative bias decreased with increasing sampling duration and a lower density of CTs. Our results emphasize that the interpretation of occupancy models depends on the underlying processes driving CT detections, specifically animal movement and population density, and that model estimates may not reliably reflect variation in these processes. We recommend carefully defining occupancy if it is applied to CT data in order to better match sampling and analytical frameworks to the ecology of sampled wildlife species.

1. Human activities have dramatic effects on the distribution and abundance of wildlife. Increased road densities and human presence in wilderness areas have elevated human-caused mortality of grizzly bears and reduced bears' use. Management agencies frequently attempt to reduce human-caused mortality by managing road density and thus human access, but the effectiveness of these actions is rarely assessed. 2. We combined systematic, DNA-based mark-recapture techniques with spatially explicit capture-recapture models to estimate population size of a threatened grizzly bear population (Kettle-Granby), following management actions to recover this population. We tested the effects of habitat and road density on grizzly bear population density. We tested both a linear and threshold-based road density metric and investigated the effect of current access management (closing roads to the public). 3. We documented an c. 50% increase in bear density since 1997 suggesting increased landscape and species conservation from management agencies played a significant role in that increase. However, bear density was lower where road denisities exceeded 0.6 km/km² and higher where motorised vehicle access had been restricted. The highest bear densities were in areas with large tracts of few or no roads and high habitat quality. Access management bolstered bear density in small areas by 27%. 4. Synthesis and applications. Our spatially explicit capture-recapture analysis demonstrates that population recovery is possible in a multi-use landscape when management actions target priority areas. We suggest that road density is a useful surrogate for the negative effects of human land use on grizzly bear populations, but spatial configuration of roads must still be considered. Reducing roads will increase grizzly bear density, but restricting vehicle access can also achieve this goal. We demonstrate that a policy target of reducing human access by managing road density below 0.6 km/km², while ensuring areas of high habitat quality have no roads, is a reasonable compromise between the need for road access and population recovery goals. Targeting closures to areas of highest habitat quality would benefit grizzly bear population recovery the most.