Large carnivore response to human road use suggests a landscape of coexistence

Demographic effects of road mortality on mammalian populations: a systematic review

In light of rapidly expanding road networks worldwide, there is increasing global awareness of the growing amount of mammalian roadkill. However, the ways in which road mortality affects the population dynamics of different species remains largely unclear. We aimed to categorise the demographic parameters in mammalian populations around the world that are directly or indirectly affected by road mortality, as well as identify the most effective study designs for quantifying population-level consequences of road mortality. We conducted a comprehensive systematic review to synthesise literature published between 2000 and 2021 and out of 11,238 unique studies returned, 83 studies were retained comprising 69 mammalian species and 150 populations. A bias towards research-intensive countries and larger mammals was apparent. Although searches were conducted in five languages, all studies meeting the inclusion criteria were in English. Relatively few studies (13.3%) provided relevant demographic context to roadkill figures, hampering understanding of the impacts on population persistence. We categorised five direct demographic parameters affected by road mortality: sex- and age-biased mortality, the percentage of a population killed on roads per year (values up to 50% were reported), the contribution of roadkill to total mortality rates (up to 80%), and roadkill during inter-patch or long-distance movements. Female-biased mortality may be more prevalent than previously recognised and is likely to be critical to population dynamics. Roadkill was the greatest source of mortality for 28% of studied populations and both additive and compensatory mechanisms to roadkill were found to occur, bringing varied challenges to conservation around roads. In addition, intra-specific population differences in demographic effects of road mortality were common. This highlights that the relative importance of road mortality is likely to be context specific as the road configuration and habitat quality surrounding a population can vary. Road ecology studies that collect data on key life parameters, such as age/stage/sex-specific survival and dispersal success, and that use a combination of methods are critical in understanding long-term impacts. Quantifying the demographic impacts of road mortality is an important yet complex consideration for proactive road management.

Partial COVID-19 closure of a national park reveals negative influence of low-impact recreation on wildlife spatiotemporal ecology

Human presence exerts complex effects on the ecology of species, which has implications for biodiversity persistence in protected areas experiencing increasing human recreation levels. However, the difficulty of separating the effect on species of human presence from other environmental or disturbance gradients remains a challenge. The cessation of human activity that occurred with COVID-19 restrictions provides a 'natural experiment' to better understand the influence of human presence on wildlife. Here, we use a COVID-19 closure within a heavily visited and highly protected national park (Glacier National Park, MT, USA) to examine how 'low-impact' recreational hiking affects the spatiotemporal ecology of a diverse mammal community. Based on data collected from camera traps when the park was closed and then subsequently open to recreation, we found consistent negative responses to human recreation across most of our assemblage of 24 species, with fewer detections, reduced site use, and decreased daytime activity. Our results suggest that the dual mandates of national parks and protected areas to conserve biodiversity and promote recreation have potential to be in conflict, even for presumably innocuous recreational activities. There is an urgent need to understand the fitness consequences of these spatiotemporal changes to inform management decisions in protected areas.

Distribution model transferability for a wide-ranging species, the Gray Wolf

Using existing data can be a reliable and cost-effective way to predict species distributions, and particularly useful for recovering or expanding species. We developed a current gray wolf (Canis lupus) distribution model for the western Great Lakes region, USA, and evaluated the spatial transferability of single-state models to the region. This study is the first assessment of transferability in a wide-ranging carnivore, as well as one of few developed for large spatial extents. We collected 3500 wolf locations from winter surveys in Minnesota (2017–2019), Wisconsin (2019–2020), and Michigan (2017–2020). We included 10 variables: proportion of natural cover, pastures, and crops; distance to natural cover, agriculture, developed land, and water; major and minor road density; and snowfall (1-km res.). We created a regional ensemble distribution by weight-averaging eight models based on their performance. We also developed single-state models, and estimated spatial transferability using two approaches: state cross-validation and extrapolation. We assessed performance by quantifying correlations, receiver operating characteristic curves (ROC), sensitivities, and two niche similarity indices. The regional area estimated to be most suitable for wolves during winter (threshold = maximum sensitivity/specificity) was 106,465 km² (MN = 48,083 km², WI = 27,757 km², MI = 30,625 km²) and correctly predicted 88% of wolf locations analyzed. Increasing natural cover and distance to crops were consistently important for determining regional and single-state wolf distribution. Extrapolation (vs. cross-validation) produced results with the greatest performance metrics, and were most similar to the regional model, yet good internal performance was unrelated to greater extrapolation performance. Factors influencing species distributions are scale-dependent and can vary across areas due to behavioral plasticity. When extending inferences beyond the current occurrence of individuals, assessing variation in ecology such as habitat selection, as well as methodological factors including model performance, will be critical to avoid poor scientific interpretations and develop effective conservation applications. In particular, accurate distribution models for recovering or recovered carnivores can be used to develop plans for habitat management, quantify potential of unoccupied habitat, assess connectivity modeling, and mitigate conflict, facilitating long-term species persistence.

Human recreation impacts seasonal activity and occupancy of American black bears (Ursus americanus) across the anthropogenic-wildland interface

Protected areas serve an important role in wildlife conservation, yet most wildlife occur outside these areas, subject to varying degrees of human disturbance. In the Upper Peninsula of Michigan, American black bears (Ursus americanus), a highly mobile, opportunistic species, are common despite an extensive outdoor recreation industry with the potential to affect black bear spatial and temporal activity. We investigated how environmental and anthropogenic factors influence black bear occupancy, detection, and diel activity patterns across the anthropogenic–wildland interface before and after hibernation. Using 30 camera traps deployed across a rural–wildland interface, we captured black bears at 23 camera sites (~ 77%), which exhibited co-occurrence with humans at 10 sites (~ 33%), revealing that human presence and human population density exert negative effects on black bear seasonal occupancy. Bears were more nocturnal during the hunting season, before hibernation. Human recreational activity increased ~ 38% after hibernation, but bear diurnal activity also increased ~ 36%, except when cubs were present. Our results suggest bears prioritize avoiding humans spatially, rather than temporally, except during the hunting season and when cubs are present. Understanding black bear responses to human recreation patterns and environmental variation is essential for minimizing human-mediated disturbance, and fueling conservation efforts of large, charismatic carnivores.

White-tailed deer exploit temporal refuge from multi-predator and human risks on roads

Although most prey have multiple predator species, few studies have quantified how prey respond to the temporal niches of multiple predators which pose different levels of danger. For example, intraspecific variation in diel activity allows white-tailed deer (Odocoileus virginianus) to reduce fawn activity overlap with coyotes (Canis latrans) but finding safe times of day may be more difficult for fawns in a multi-predator context. We hypothesized that within a multi-predator system, deer would allocate antipredation behavior optimally based on combined mortality risk from multiple sources, which would vary depending on fawn presence. We measured cause-specific mortality of 777 adult (>1-year-old) and juvenile (1-4-month-old) deer and used 300 remote cameras to estimate the activity of deer, humans, and predators including American black bears (Ursus americanus), bobcats (Lynx rufus), coyotes, and wolves (Canis lupus). Predation and vehicle collisions accounted for 5.3 times greater mortality in juveniles (16% mortality from bears, coyotes, bobcats, wolves, and vehicles) compared with adults (3% mortality from coyotes, wolves, and vehicles). Deer nursery groups (i.e., ≥1 fawn present) were more diurnal than adult deer without fawns, causing fawns to have 24-38% less overlap with carnivores and 39% greater overlap with humans. Supporting our hypothesis, deer nursery groups appeared to optimize diel activity to minimize combined mortality risk. Temporal refuge for fawns was likely the result of carnivores avoiding humans, simplifying diel risk of five species into a trade-off between diurnal humans and nocturnal carnivores. Functional redundancy among multiple predators with shared behaviors may partially explain why white-tailed deer fawn predation rates are often similar among single- and multi-predator systems.

Quantifying anthropogenic wolf mortality in relation to hunting regulations and landscape attributes across North America

Understanding the types and magnitude of human‐caused mortality is essential for maintaining viable large carnivore populations. We used a database of cause‐specific mortality to examine how hunting regulations and landscape configurations influenced human‐caused mortality of North American gray wolves (Canis lupus). Our dataset included 21 studies that monitored the fates of 3564 wolves and reported 1442 mortalities. Human‐caused mortality accounted for 61% of mortality overall, with 23% due to illegal harvest, 16% due to legal harvest, and 12% the result of management removal. The overall proportion of anthropogenic wolf mortality was lowest in areas with an open hunting season compared to areas with a closed hunting season or mixed hunting regulations, suggesting that harvest mortality was neither fully additive nor compensatory. Proportion of mortality from management removal was reduced in areas with an open hunting season, suggesting that legal harvest may reduce human‐wolf conflicts or alternatively that areas with legal harvest have less potential for management removals (e.g., less livestock depredation). Proportion of natural habitat was negatively correlated with the proportion of anthropogenic and illegal harvest mortality. Additionally, the proportion of mortality due to illegal harvest increased with greater natural habitat fragmentation. The observed association between large patches of natural habitat and reductions in several sources of anthropogenic wolf mortality reiterate the importance of habitat preservation to maintain wolf populations. Furthermore, effective management of wolf populations via implementation of harvest may reduce conflict with humans. Effective wolf conservation will depend on holistic strategies that integrate ecological and socioeconomic factors to facilitate their long‐term coexistence with humans.

Smartphone app reveals that lynx avoid human recreationists on local scale, but not home range scale

Outdoor recreation is increasing and affects habitat use and selection by wildlife. These effects are challenging to study, especially for elusive species with large spatial requirements, as it is hard to obtain reliable proxies of recreational intensity over extensive areas. Commonly used proxies, such as the density of, or distance to, hiking paths, ignore outdoor recreation occurring on other linear feature types. Here we utilized crowdsourced data from the Strava training app to obtain a large-scale proxy for pedestrian outdoor recreation intensity in southeast Norway. We used the proxy and GPS-tracking data from collared Eurasian lynx (Lynx lynx) to investigate how recreation affects habitat selection at the home range scale and local scale by lynx during summer. We fitted resource selection functions at the two scales using conditional logistic regression. Our analysis revealed that lynx avoided areas of recreational activity at the local scale, but not at home range scale. Nonetheless, lynx frequently used areas associated with recreation, and to a greater degree at night than during the day. Our results suggest that local-scale avoidance of recreation and temporal adjustments of habitat use by lynx mitigate the need for a home range-scale response towards recreation. Scale-dependent responses and temporal adjustments in habitat use may facilitate coexistence between humans and large carnivores.