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Anthropogenic disturbances have been demonstrated to affect animal behavior, distribution, and abundance, but assessment of their impacts on fitness-related traits has received little attention. We hypothesized that human activities and infrastructure cause a decrease in the individual performance of preys because of anthropogenically enhanced predation risk. We evaluated the impacts of commercial logging and road networks on the fitness of a large herbivore known to be sensitive to human disturbance: the forest-dwelling woodland caribou (Rangifer tarandus caribou). For 8 consecutive years (2004-2011) we monitored 59 individuals using GPS telemetry in the Charlevoix region of Québec, Canada. We also used Very High Frequency telemetry locations collected on 28 individuals from 1999-2000. We related habitat selection of adult caribou at various spatio-temporal scales to their probability of dying from predation, and to indices of their reproductive success and energy expenditure. The probability that adult caribou died from predation increased with the proportion of recent disturbances (including cutblocks ≤ 5 years old) in their annual home range. The respective effects of increasing paved and forestry road densities depended upon the overall road density within the home range of caribou. At a finer scale of 10 to 15 days before their death, caribou that were killed by a predator selected for recent disturbances more than individuals that survived, and avoided old mature conifer stands. The home range area of caribou increased with road density. Finally, the composition of the home range of females had no effect on their reproductive success. We show that human activities and infrastructure may influence the individual performance of large prey species in highly managed regions. We outline the need to consider the full set of impacts that human development may have on threatened animal populations, with particular emphasis on predator-prey relationships and population dynamics.

Wild prey can reduce predation risk by avoiding areas used by their predators. As they get older, individuals should be able to fine‐tune this avoidance based on their increased experience with predation risk. Such learning mechanisms are expected to play a key role in how individuals cope with risk during their life, particularly in altered landscapes where human disturbances have created habitat conditions distinct from those of the past. We studied the role of experience on the avoidance of risky areas by boreal caribou (Rangifer tarandus caribou) in a system where they are under high predation pressure from gray wolves (Canis lupus) and black bears (Ursus americanus). Using telemetry data collected on 28 caribou, 31 wolves, and 12 bears, we investigated whether caribou adjusted their level of predator avoidance with passing monitoring years, a proxy of increasing experience. We observed an increase in the avoidance of areas suitable to wolves (during two study periods) and bears (during all study periods) with passing years. Periods during which caribou did not adjust their behavior toward wolves (winter and calving) were characterized by persistent—potentially innate—avoidance. Our results suggest that, in most circumstances, caribou became more efficient at avoiding areas selected by their predators as they gained experience. Future work should attempt to demonstrate whether such tactics are heritable; if so, our results would suggest that, given time, caribou living in disturbed environments would have the potential to adapt to changing levels of risk. This would give hope for the conservation of caribou, a species at risk in Canada, provided levels of risk do not surpass the limits of their behavioral plasticity.

To develop effective management to maintain or restore populations of large herbivores, wildlife managers require sound empirical data on their variations in size and associated parameters. Many studies have highlighted links between morphological traits of individuals and population density; however, less attention has been devoted to whether or not morphological traits can reliably inform on population size in years when no population estimates are available. We evaluated the relationships between three morphological traits (hind foot length, body mass, and body fat) and population size interpolated over three decades, for four migratory caribou (Rangifer tarandus) herds in northern Canada and Alaska. Our sample included 8865 measurements of 4473 individuals. We used a Bayesian modeling approach to evaluate the relationships between morphology and population size across different sex and age classes, considering different temporal scales and, when possible, phases of population growth or decline. We found that morphological traits were not consistently linked to population size. Statistically significant relationships existed for some combinations of herd and age classes, but weak to absent relationships were more common. Our study suggests that morphological traits alone cannot replace data obtained from aerial surveys to approximate population size when population trends are unknown. We discuss the usefulness of morphological traits to explain population size, and recognize their role as complementary metrics to inform the management and conservation of large herbivores, but conclude that morphological data should not be used to predict population size without information on population trends. We tested the relationships between three morphological traits and population size in four Rangifer tarandus herds in northern Canada and Alaska. Based on 8865 measurements of 4473 individuals over four decades, we conclude that without prior information on population trends, morphological data in most cases should not be used to predict population size.

Understanding animal movements across heterogeneous landscapes is of great interest because it helps explain the dynamic processes influencing the distribution of individuals in space. Research on how animals move relative to short-range environmental characteristics are scarce. Our objective was to determine the variables influencing movement of a large ungulate, the moose Alces alces, ranging across a boreal landscape, and to link movement behaviour with limiting factors at a fine scale. We assessed 7 candidate models composed of vegetation, solar energy, and topography variables using step selection functions (SSF) for male and female moose across daily and annual periods. We selected and weighted models using the Bayesian Information Criterion. Variables influencing small-scale movements of moose differed among periods and between sexes, likely in response to corresponding changes in the importance of limiting factors. Best models often combined many types of variables, although simpler models composed of only vegetation or topography variables explained male's movements during rut and early winter. Moose steps were observed in good feeding stands from summer to early winter for females and from spring to early winter for males, supporting other studies of moose habitat selection. From summer to early winter, females alternatively selected and avoided cover stands during day and night, respectively. Solar energy reaching the ground was important, particularly during late winter and spring, likely due to its effect on snow cover, air temperature, or plant phenology. Moose generally moved in gentle slopes and variable elevation, which may have increased their chances of finding high quality forage, or improved their search of suitable calving sites or mates. Our study revealed the great complexity and dynamic aspects of animal movements in a heterogeneous landscape. Analysis of animal movement provides complementary information to more static habitat selection analyses and helps understanding the spatial variations in the distribution of individuals through time.

Animal migrations influence key ecological processes such as predator–prey dynamics, nutrient and energy cycling, and community structure. Long‐distance migrations are declining worldwide, and a better understanding of the factors influencing animal space use during migrations is essential to maintain this behavior in the wild. We mapped the spring migration routes used by female caribou of the declining Rivière‐aux‐Feuilles herd in northern Québec, Canada, from 1994 to 2019. We used resource selection functions to determine the effect of remotely sensed measures of snow depth, precipitation, elevation, and land cover classes on habitat selection along 811 migration routes used by 304 individuals. We further explored whether observed trends in the geographic position of migration routes (e.g., mean longitude, mean variance of longitude) influenced calf recruitment the following fall. Female caribou selected areas with deeper snow, less precipitation, and lower elevation, avoided forest and lichen heath, and selected more strongly erect‐shrub tundra and waterbodies than the reference category, shrub tundra. A cluster analysis revealed different migration patterns, with migration routes in the early 2000s being more restricted in space and located further inland than routes in the 2010s. The location of spring migration routes was unrelated to changes in calf recruitment. The characterization of migration routes used by caribou will help inform management and could be used to predict future herd movements in response to different climate change scenarios.

Decision making in conservation science relies on the best available information. This may include using models that were not designed for purpose and are not accompanied by an assessment of limitations. To begin addressing these issues, we sought to reproduce and evaluate the spatial transferability of the two best available models for predicting impacts of proposed mining on boreal woodland caribou (Rangifer tarandus caribou) in northern Ontario. We evaluated their suitability for projecting the impacts of development in the Ring of Fire region. To aid in accessibility, we developed an R package for data preparation, modeling of resource selection, and demographic modeling. We found models were either ill‐suited or lacking for ongoing regional planning. The specificity of the regional resource selection model limited its usefulness for predicting impacts of development, and the high variability across caribou ranges limited the usefulness of a national aspatial demographic model for predicting range‐specific impacts. These existing models are not enough to provide spatially explicit information needed to minimize detrimental effects of anthropogenic development on caribou recovery in northern Ontario. Models designed for forecasting that are regularly updated with range‐specific demographic and habitat information are required. Decision making in conservation science often relies on the best available information, but existing models are rarely reproducible, transferrable, or accessible. We sought to reproduce and evaluate the suitability of the two best available models for predicting impacts of proposed mining on boreal woodland caribou (Rangifer tarandus caribou) in northern Ontario and evaluated their suitability for projecting the impacts of development in the Ring of Fire region. Neither model was sufficient to provide the spatially explicit information needed to minimize detrimental effects of anthropogenic development on caribou recovery in northern Ontario; models designed for forecasting are required.

Warming temperatures and advancing spring are affecting annual snow and ice cycles, as well as plant phenology, across the Arctic and boreal regions. These changes may be linked to observed population declines in wildlife, including barren‐ground caribou (Rangifer tarandus), a key species of Arctic environments. We quantified how barren‐ground caribou, characteristically both gregarious and migratory, synchronize births in time and aggregate births in space and investigated how these tactics are influenced by variable weather conditions. We analyzed movement patterns to infer calving dates for 747 collared female caribou from seven herds across northern North America, totaling 1255 calving events over a 15‐year period. By relating these events to local weather conditions during the 1‐year period preceding calving, we examined how weather influenced calving timing and the ability of caribou to reach their central calving area. We documented continental‐scale synchrony in calving, but synchrony was greatest within an individual herd for a given year. Weather conditions before and during gestation had contrasting effects on the timing and location of calving. Notably, a combination of unfavorable weather conditions during winter and spring, including the pre‐calving migration, resulted in a late arrival on the calving area or a failure to reach the greater calving area in time for calving. Though local weather conditions influenced calving timing differently among herds, warm temperatures and low wind speed, which are associated with soft, deep snow, during the spring and pre‐calving migration, generally affected the ability of female caribou to reach central calving areas in time to give birth. Delayed calving may have potential indirect consequences, including reduced calf survival. Overall, we detected considerable variability across years and across herds, but no significant trend for earlier calving by caribou, even as broad indicators of spring and snow phenology trend earlier. Our results emphasize the importance of monitoring the timing and location of calving, and to examine how weather during summer and winter are affecting calving and subsequent reproductive success.

In boreal forests of North America, land managers often carry out preventive treatments of forest fuel for the protection of human infrastructure from wildfires. However, these treatments may negatively affect other ecosystem services, such as the capacity to sustain wildlife populations. Here, we examine the efficacy of a strategy aimed at preserving a critical movement corridor for boreal woodland caribou ( Rangifer tarandus caribou ) in northern Québec, Canada, by raising high-voltage power line conductors above the forest canopy. To assess the interplay between the caribou protection objectives and a reduction in power line's exposure to wildfires, we developed an optimization model that combines the objectives of protecting the power line from wildfires via fuel treatments and maintaining a suitable movement corridor for caribou. The model combines a critical node detection (CND) problem with a habitat connectivity problem that allocates a minimum-resistance fixed-width habitat corridor between isolated wildlife refuges. Our results identify the best locations to perform fire fuel treatments to lessen the threat of fire damage to human infrastructure while maintaining a connectivity corridor for caribou in present and future climate scenarios. The selected fuel treatment locations aimed to mitigate wildfire exposure to a power line. In small-budget solutions, the exposure of power line infrastructure to wildfires was reduced by 36–39% in current climate conditions and by 20–31% in future climate, compared with no-treatment scenarios. Despite the detrimental effects of wildfire on both the industrial asset and caribou habitat, the approach provides strategies that help achieve a compromise between these two values. Such knowledge is timely to help mitigate the negative impacts of climate change on human livelihoods and natural ecosystems.

Protected areas are needed to conserve nature and biodiversity worldwide. The province of Québec (Canada) recently established a large wilderness area affording significant habitat protection for boreal woodland caribou (Rangifer tarandus caribou), a wide‐ranging species at risk. We describe a decision support framework combining ecological modeling with socioeconomic constraints that ultimately led to the creation of this protected area. Multiple criteria were used to identify candidate protected areas for boreal caribou. These had to be large in size (>10,000 km2) and located in regions where available high‐quality habitat was threatened by development pressures. Candidate areas also had to contribute substantively to the maintenance of functional habitat connectivity, be exempt from major industrial developments and recent fires, and required evidence of recent use by caribou. Five candidate protected areas emerged from this exercise. Key regional stakeholders were consulted, thereby strengthening advocacy for land designation, and boundaries were refined through their input, which helped further reduce socioeconomic conflicts. This process involved difficult compromises, but eventually led to the legal designation on March 4, 2021 of a new protected area for boreal caribou known as the Caribous‐Forestiers‐de‐Manouane‐Manicouagan. We show how our science‐informed decision support framework was instrumental in the success of this endeavor, and describe the obstacles overcame in the process, so that other jurisdictions may draw from this experience in their efforts to achieve similar conservation goals. We describe a decision support framework for the identification of protected areas. Our approach employs criteria pertaining to size, geographic location, habitat suitability, functional connectivity, and the feasibility of different scenarios considering multiple socioeconomic and geophysical constraints. We show how this framework led to the successful identification of a protected area for boreal woodland caribou, a wide‐ranging species at risk in Canada.

Raptors are important environmental indicators because they are apex predators and can be sensitive to disturbance. Few studies have addressed habitat preferences of tundra-nesting raptors, and those that exist have focused on fine-scale characteristics. With increasing economic development predicted to occur throughout the Canadian Arctic, the investigation of raptor breeding habitat at broad spatial scales is required. We modeled breeding habitat selection for two raptor species on north Baffin Island, NU, Canada. During aerial surveys conducted over six breeding seasons, we documented 172 peregrine falcon (Falco peregrinus tundrius) and 160 rough-legged hawk (Buteo lagopus) nesting sites. We used these locations in conjunction with remote sensing data to build habitat selection models at three spatial scales. Topography, distance to water, and normalized difference vegetation index explained selection at all scales; slope aspect was also important at the finest scale. To validate landscape scale models, we conducted a validation survey that resulted in the detection of 45 new nests (peregrine falcon n = 21, rough-legged hawk n = 24). We did not detect any new nests in areas where model-predicted occurrence was expected to be low. Conversely, we found more than half of previously undetected nests in areas where model-predicted occurrence was expected to be high.