City divided: Unveiling family ties and genetic structuring of coyotes in Seattle.

Linear barriers pose significant challenges for wildlife gene flow, impacting species persistence, adaptation, and evolution. While numerous studies have examined the effects of linear barriers (e.g., fences and roadways) on partitioning urban and non-urban areas, understanding their influence on gene flow within cities remains limited. Here, we investigated the impact of linear barriers on coyote (Canis latrans) population structure in Seattle, Washington, where major barriers (i.e., interstate highways and bodies of water) divide the city into distinct quadrants. Just under 1000 scats were collected to obtain genetic data between January 2021 and December 2022, allowing us to identify 73 individual coyotes. Notably, private allele analysis underscored limited interbreeding among quadrants. When comparing one quadrant to each other, there were up to 16 private alleles within a single quadrant, representing nearly 22% of the population allelic diversity. Our analysis revealed weak isolation by distance, and despite being a highly mobile species, genetic structuring was apparent between quadrants even with extremely short geographic distance between individual coyotes, implying that Interstate 5 and the Ship Canal act as major barriers. This study uses coyotes as a model species for understanding urban gene flow and its consequences in cities, a crucial component for bolstering conservation of rarer species and developing wildlife friendly cities.

White-tailed deer population dynamics in a multipredator landscape shaped by humans.

Large terrestrial mammals increasingly rely on human-modified landscapes as anthropogenic footprints expand. Land management activities such as timber harvest, agriculture, and roads can influence prey population dynamics by altering forage resources and predation risk via changes in habitat, but these effects are not well understood in regions with diverse and changing predator guilds. In northeastern Washington state, USA, white-tailed deer (Odocoileus virginianus) are vulnerable to multiple carnivores, including recently returned gray wolves (Canis lupus), within a highly human-modified landscape. To understand the factors governing predator-prey dynamics in a human context, we radio-collared 280 white-tailed deer, 33 bobcats (Lynx rufus), 50 cougars (Puma concolor), 28 coyotes (C. latrans), and 14 wolves between 2016 and 2021. We first estimated deer vital rates and used a stage-structured matrix model to estimate their population growth rate. During the study, we observed a stable to declining deer population (lambda = 0.97, 95% confidence interval: 0.88, 1.05), with 74% of Monte Carlo simulations indicating population decrease and 26% of simulations indicating population increase. We then fit Cox proportional hazard models to evaluate how predator exposure, use of human-modified landscapes, and winter severity influenced deer survival and used these relationships to evaluate impacts on overall population growth. We found that the population growth rate was dually influenced by a negative direct effect of apex predators and a positive effect of timber harvest and agricultural areas. Cougars had a stronger effect on deer population dynamics than wolves, and mesopredators had little influence on the deer population growth rate. Areas of recent timber harvest had 55% more forage biomass than older forests, but horizontal visibility did not differ, suggesting that timber harvest did not influence predation risk. Although proximity to roads did not affect the overall population growth rate, vehicle collisions caused a substantial proportion of deer mortalities, and reducing these collisions could be a win-win for deer and humans. The influence of apex predators and forage indicates a dual limitation by top-down and bottom-up factors in this highly human-modified system, suggesting that a reduction in apex predators would intensify density-dependent regulation of the deer population owing to limited forage availability.

Are we telling the same story? Comparing inferences made from camera trap and telemetry data for wildlife monitoring.

Estimating habitat and spatial associations for wildlife is common across ecological studies and it is well known that individual traits can drive population dynamics and vice versa. Thus, it is commonly assumed that individual- and population-level data should represent the same underlying processes, but few studies have directly compared contemporaneous data representing these different perspectives. We evaluated the circumstances under which data collected from Lagrangian (individual-level) and Eulerian (population-level) perspectives could yield comparable inference to understand how scalable information is from the individual to the population. We used Global Positioning System (GPS) collar (Lagrangian) and camera trap (Eulerian) data for seven species collected simultaneously in eastern Washington (2018-2020) to compare inferences made from different survey perspectives. We fit the respective data streams to resource selection functions (RSFs) and occupancy models and compared estimated habitat- and space-use patterns for each species. Although previous studies have considered whether individual- and population-level data generated comparable information, ours is the first to make this comparison for multiple species simultaneously and to specifically ask whether inferences from the two perspectives differed depending on the focal species. We found general agreement between the predicted spatial distributions for most paired analyses, although specific habitat relationships differed. We hypothesize the discrepancies arose due to differences in statistical power associated with camera and GPS-collar sampling, as well as spatial mismatches in the data. Our research suggests data collected from individual-based sampling methods can capture coarse population-wide patterns for a diversity of species, but results differ when interpreting specific wildlife-habitat relationships.

Species interactions in the Anthropocene.

Research Highlight: Van Scoyoc, A., Smith, J. A., Gaynor, K. M., Barker, K., & Brashares, J. S. (2023) The influence of human activity on predator-prey spatiotemporal overlap. Journal of Animal Ecology, https://doi.org/10.1111/1365-2656.13892. Few corners of the globe remain untouched by humans, and thus nearly all wildlife communities are influenced by human activity. Van Scoyoc et al. (2023) present a framework that places predator-prey interactions explicitly within an anthropogenic context, revealing that predator-prey dyads fall into one of four categories depending on whether predators and prey are attracted to or avoid human activity. These responses can either increase or decrease overlap among species via divergent pathways, which can help to make sense of seemingly conflicting patterns from prior studies. Their framework facilitates hypothesis testing, which they demonstrate with a meta-analysis of 178 predator-prey dyads from 19 camera trap studies. With evidence for each of the four pathways, yet some unexpected outcomes for temporal overlap among dyads, this review generates exciting questions and lays out a productive path forward to improve our understanding of species interactions in the Anthropocene.

Successional patterns of terrestrial wildlife following deglaciation.

Disturbance is a key driver of community assembly and patterns of diversity. Whereas successional changes in vegetation have been well-studied, postdisturbance successional patterns of wildlife communities remain poorly understood. Here, we investigated the roles of site age and habitat in shaping community assembly and the diversity of terrestrial mammals in Glacier Bay National Park, Alaska (GBNP), which has undergone the most rapid and extensive deglaciation in the world since the Little Ice Age. Deglaciation has extensively altered the landscape, opening up new habitat for recolonization by plants and animals. We used camera traps, small mammal trapping and vegetation surveys to investigate the patterns of mammalian succession and beta diversity following deglaciation, using a space-for-time substitution across 10 sites during summers 2017 and 2018. Site age and habitat characteristics were not strongly correlated (r < 0.46), allowing the influences of time since disturbance and habitat changes to be distinguished. PERMANOVA analyses indicated that mammal community assembly was more strongly influenced by site age than habitat, whereas habitat and age had similar effects on beta (between site) diversity. Beta diversity was higher for smaller, less mobile mammals than larger, more mobile mammals and was primarily driven by species turnover among sites, whereas relative turnover was much lower for larger mammals. A comprehensive review of historical distributions of mammals in GBNP supported our findings that species turnover is a driving influence of community assembly for smaller mammals. Our results indicate that body size of mammals may play an important role in shaping colonization patterns postdisturbance, likely via size-related differences in mobility. Patterns of wildlife community assembly may therefore not track vegetation succession following disturbances if there are barriers to movement or if dispersal ability is limited, highlighting the importance of incorporating landscape connectivity and species traits into wildlife conservation efforts following disturbances. This knowledge may improve predictions of mammalian community assembly following major disturbance events.

Interactive effects of wildfires, season and predator activity shape mule deer movements.

Wildfires are increasing in size, frequency and severity due to climate change and fire suppression, but the direct and indirect effects on wildlife remain largely unresolved. Fire removes forest canopy, which can improve forage for ungulates but also reduce snow interception, leading to a deeper snowpack and potentially increased vulnerability to predation in winter. If ungulates exhibit predator-mediated foraging, burns should generally be selected for in summer to access high-quality forage and avoided in winter to reduce predation risk in deep snow. Fires also typically increase the amount of deadfall and initiate the growth of dense understory vegetation, creating obstacles that may confer a hunting advantage to stalking predators and a disadvantage to coursing predators. To minimize risk, ungulates may therefore avoid burns when and where stalking predators are most active, and use burns when and where coursing predators are most active. We used telemetry data from GPS-collared mule deer (Odocoileus hemionus), cougars (Puma concolor) and wolves (Canis lupus) to develop step selection functions to examine how mule deer navigated species-specific predation risk across a landscape in northern Washington, USA, that has experienced substantial wildfire activity during the past several decades. We considered a diverse array of wildfire impacts, accounting for both the severity of the fire and time since the burn (1-35 years) in our analyses. We observed support for the predator mediating foraging hypothesis: mule deer generally selected for burned areas in summer and avoided burns in winter. In addition, deer increased use of burned areas when and where wolf activity was high and avoided burns when and where cougar use was high in winter, suggesting the hunting mode of resident predators mediated the seasonal response of deer to burns. Deer were not more likely to die by predation in burned than in unburned areas, indicating that they adequately manage fire-induced changes to predation risk. As fire activity increases with climate change, our findings indicate the impact on ungulates will depend on trade-offs between enhanced summer forage and functionally reduced winter range, mediated by characteristics of the predator community.

Disturbance type and species life history predict mammal responses to humans.

Human activity and land use change impact every landscape on Earth, driving declines in many animal species while benefiting others. Species ecological and life history traits may predict success in human-dominated landscapes such that only species with "winning" combinations of traits will persist in disturbed environments. However, this link between species traits and successful coexistence with humans remains obscured by the complexity of anthropogenic disturbances and variability among study systems. We compiled detection data for 24 mammal species from 61 populations across North America to quantify the effects of (1) the direct presence of people and (2) the human footprint (landscape modification) on mammal occurrence and activity levels. Thirty-three percent of mammal species exhibited a net negative response (i.e., reduced occurrence or activity) to increasing human presence and/or footprint across populations, whereas 58% of species were positively associated with increasing disturbance. However, apparent benefits of human presence and footprint tended to decrease or disappear at higher disturbance levels, indicative of thresholds in mammal species' capacity to tolerate disturbance or exploit human-dominated landscapes. Species ecological and life history traits were strong predictors of their responses to human footprint, with increasing footprint favoring smaller, less carnivorous, faster-reproducing species. The positive and negative effects of human presence were distributed more randomly with respect to species trait values, with apparent winners and losers across a range of body sizes and dietary guilds. Differential responses by some species to human presence and human footprint highlight the importance of considering these two forms of human disturbance separately when estimating anthropogenic impacts on wildlife. Our approach provides insights into the complex mechanisms through which human activities shape mammal communities globally, revealing the drivers of the loss of larger predators in human-modified landscapes.

Enemies with benefits: integrating positive and negative interactions among terrestrial carnivores.

Interactions among terrestrial carnivores involve a complex interplay of competition, predation and facilitation via carrion provisioning, and these negative and positive pathways may be closely linked. Here, we developed an integrative framework and synthesized data from 256 studies of intraguild predation, scavenging, kleptoparisitism and resource availability to examine global patterns of suppression and facilitation. Large carnivores were responsible for one third of mesocarnivore mortality (n = 1,581 individuals), and intraguild mortality rates were superadditive, increasing from 10.6% to 25.5% in systems with two vs. three large carnivores. Scavenged ungulates comprised 30% of mesocarnivore diets, with larger mesocarnivores relying most heavily on carrion. Large carnivores provided 1,351 kg of carrion per individual per year to scavengers, and this subsidy decreased at higher latitudes. However, reliance on carrion by mesocarnivores remained high, and abundance correlations among sympatric carnivores were more negative in these stressful, high-latitude systems. Carrion provisioning by large carnivores may therefore enhance suppression rather than benefiting mesocarnivores. These findings highlight the synergistic effects of scavenging and predation risk in structuring carnivore communities, suggesting that the ecosystem service of mesocarnivore suppression provided by large carnivores is strong and not easily replaced by humans.

Navigating snowscapes: scale-dependent responses of mountain sheep to snowpack properties.

Winters are limiting for many terrestrial animals due to energy deficits brought on by resource scarcity and the increased metabolic costs of thermoregulation and traveling through snow. A better understanding of how animals respond to snow conditions is needed to predict the impacts of climate change on wildlife. We compared the performance of remotely sensed and modeled snow products as predictors of winter movements at multiple spatial and temporal scales using a data set of 20,544 locations from 30 GPS-collared Dall sheep (Ovis dalli dalli) in Lake Clark National Park and Preserve, Alaska, USA from 2005 to 2008. We used daily 500-m MODIS normalized difference snow index (NDSI), and multi-resolution snow depth and density outputs from a snowpack evolution model (SnowModel), as covariates in step selection functions. We predicted that modeled snow depth would perform best across all scales of selection due to more informative spatiotemporal variation and relevance to animal movement. Our results indicated that adding any of the evaluated snow metrics substantially improved model performance and helped characterize winter Dall sheep movements. As expected, SnowModel-simulated snow depth outperformed NDSI at fine-to-moderate scales of selection (step scales < 112 h). At the finest scale, Dall sheep selected for snow depths below mean chest height (<54 cm) when in low-density snows (100 kg/m3 ), which may have facilitated access to ground forage and reduced energy expenditure while traveling. However, sheep selected for higher snow densities (>300 kg/m3 ) at snow depths above chest height, which likely further reduced energy expenditure by limiting hoof penetration in deeper snows. At moderate-to-coarse scales (112-896 h step scales), however, NDSI was the best-performing snow covariate. Thus, the use of publicly available, remotely sensed, snow cover products can substantially improve models of animal movement, particularly in cases where movement distances exceed the MODIS 500-m grid threshold. However, remote sensing products may require substantial data thinning due to cloud cover, potentially limiting its power in cases where complex models are necessary. Snowpack evolution models such as SnowModel offer users increased flexibility at the expense of added complexity, but can provide critical insights into fine-scale responses to rapidly changing snow properties.

Fatal Attraction? Intraguild Facilitation and Suppression among Predators.

Competition and suppression are recognized as dominant forces that structure predator communities. Facilitation via carrion provisioning, however, is a ubiquitous interaction among predators that could offset the strength of suppression. Understanding the relative importance of these positive and negative interactions is necessary to anticipate community-wide responses to apex predator declines and recoveries worldwide. Using state-sponsored wolf (Canis lupus) control in Alaska as a quasi experiment, we conducted snow track surveys of apex, meso-, and small predators to test for evidence of carnivore cascades (e.g., mesopredator release). We analyzed survey data using an integrative occupancy and structural equation modeling framework to quantify the strengths of hypothesized interaction pathways, and we evaluated fine-scale spatiotemporal responses of nonapex predators to wolf activity clusters identified from radio-collar data. Contrary to the carnivore cascade hypothesis, both meso- and small predator occupancy patterns indicated guild-wide, negative responses of nonapex predators to wolf abundance variations at the landscape scale. At the local scale, however, we observed a near guild-wide, positive response of nonapex predators to localized wolf activity. Local-scale association with apex predators due to scavenging could lead to landscape patterns of mesopredator suppression, suggesting a key link between occupancy patterns and the structure of predator communities at different spatial scales.

Precipitation alters interactions in a grassland ecological community.

Climate change is transforming precipitation regimes world-wide. Changes in precipitation regimes are known to have powerful effects on plant productivity, but the consequences of these shifts for the dynamics of ecological communities are poorly understood. This knowledge gap hinders our ability to anticipate and mitigate the impacts of climate change on biodiversity. Precipitation may affect fauna through direct effects on physiology, behaviour or demography, through plant-mediated indirect effects, or by modifying interactions among species. In this paper, we examined the response of a semi-arid ecological community to a fivefold change in precipitation over 7 years. We examined the effects of precipitation on the dynamics of a grassland ecosystem in central California from 2007 to 2013. We conducted vegetation surveys, pitfall trapping of invertebrates, visual surveys of lizards and capture-mark-recapture surveys of rodents on 30 plots each year. We used structural equation modelling to evaluate the direct, indirect and modifying effects of precipitation on plants, ants, beetles, orthopterans, kangaroo rats, ground squirrels and lizards. We found pervasive effects of precipitation on the ecological community. Although precipitation increased plant biomass, direct effects on fauna were often stronger than plant-mediated effects. In addition, precipitation altered the sign or strength of consumer-resource and facilitative interactions among the faunal community such that negative or neutral interactions became positive or vice versa with increasing precipitation. These findings indicate that precipitation influences ecological communities in multiple ways beyond its recognized effects on primary productivity. Stochastic variation in precipitation may weaken the average strength of biotic interactions over time, thereby increasing ecosystem stability and resilience to climate change.

Impacts of breeder loss on social structure, reproduction and population growth in a social canid.

The importance of individuals to the dynamics of populations may depend on reproductive status, especially for species with complex social structure. Loss of reproductive individuals in socially complex species could disproportionately affect population dynamics by destabilizing social structure and reducing population growth. Alternatively, compensatory mechanisms such as rapid replacement of breeders may result in little disruption. The impact of breeder loss on the population dynamics of social species remains poorly understood. We evaluated the effect of breeder loss on social stability, recruitment and population growth of grey wolves (Canis lupus) in Denali National Park and Preserve, Alaska using a 26-year dataset of 387 radiocollared wolves. Harvest of breeding wolves is a highly contentious conservation and management issue worldwide, with unknown population-level consequences. Breeder loss preceded 77% of cases (n = 53) of pack dissolution from 1986 to 2012. Packs were more likely to dissolve if a female or both breeders were lost and pack size was small. Harvest of breeders increased the probability of pack dissolution, likely because the timing of harvest coincided with the breeding season of wolves. Rates of denning and successful recruitment were uniformly high for packs that did not experience breeder loss; however, packs that lost breeders exhibited lower denning and recruitment rates. Breeder mortality and pack dissolution had no significant effects on immediate or longer term population dynamics. Our results indicate the importance of breeding individuals is context dependent. The impact of breeder loss on social group persistence, reproduction and population growth may be greatest when average group sizes are small and mortality occurs during the breeding season. This study highlights the importance of reproductive individuals in maintaining group cohesion in social species, but at the population level socially complex species may be resilient to disruption and harvest through strong compensatory mechanisms.

Does moonlight increase predation risk? Meta-analysis reveals divergent responses of nocturnal mammals to lunar cycles.

The risk of predation strongly affects mammalian population dynamics and community interactions. Bright moonlight is widely believed to increase predation risk for nocturnal mammals by increasing the ability of predators to detect prey, but the potential for moonlight to increase detection of predators and the foraging efficiency of prey has largely been ignored. Studies have reported highly variable responses to moonlight among species, calling into question the assumption that moonlight increases risk. Here, we conducted a quantitative meta-analysis examining the effects of moonlight on the activity of 59 nocturnal mammal species to test the assumption that moonlight increases predation risk. We examined patterns of lunarphilia and lunarphobia across species in relation to factors such as trophic level, habitat cover preference and visual acuity. Across all species included in the meta-analysis, moonlight suppressed activity. The magnitude of suppression was similar to the presence of a predator in experimental studies of foraging rodents (13.6% and 18.7% suppression, respectively). Contrary to the expectation that moonlight increases predation risk for all prey species, however, moonlight effects were not clearly related to trophic level and were better explained by phylogenetic relatedness, visual acuity and habitat cover. Moonlight increased the activity of prey species that use vision as their primary sensory system and suppressed the activity of species that primarily use other senses (e.g. olfaction, echolocation), and suppression was strongest in open habitat types. Strong taxonomic patterns underlay these relationships: moonlight tended to increase primate activity, whereas it tended to suppress the activity of rodents, lagomorphs, bats and carnivores. These results indicate that visual acuity and habitat cover jointly moderate the effect of moonlight on predation risk, whereas trophic position has little effect. While the net effect of moonlight appears to increase predation risk for most nocturnal mammals, our results highlight the importance of sensory systems and phylogenetic history in determining the level of risk.

Cougars, wolves, and humans drive a dynamic landscape of fear for elk.

To manage predation risk, prey navigate a dynamic landscape of fear, or spatiotemporal variation in risk perception, reflecting predator distributions, traits, and activity cycles. Prey may seek to reduce risk across this landscape using habitat at times and in places when predators are less active. In multipredator landscapes, avoiding one predator could increase vulnerability to another, making the landscape of fear difficult to predict and navigate. Additionally, humans may shape interactions between predators and prey, and induce new sources of risk. Humans can function as a shield, providing a refuge for prey from human-averse carnivores, and as a predator, causing mortality through hunting and vehicle collisions and eliciting a fear response that can exceed that of carnivores. We used telemetry data collected between 2017 and 2021 from 63 Global Positioning System-collared elk (Cervus canadensis), 42 cougars (Puma concolor), and 16 wolves (Canis lupus) to examine how elk habitat selection changed in relation to carnivores and humans in northeastern Washington, USA. Using step selection functions, we evaluated elk habitat use in relation to cougars, wolves, and humans, diel period (daytime vs. nighttime), season (summer calving season vs. fall hunting season), and habitat structure (open vs. closed habitat). The diel cycle was critical to understanding elk movement, allowing elk to reduce encounters with predators where and when they would be the largest threat. Elk strongly avoided cougars at night but had a near-neutral response to cougars during the day, whereas elk avoided wolves at all times of day. Elk generally used more open habitats where cougars and wolves were most active, rather than altering the use of habitat structure depending on the predator species. Elk avoided humans during the day and ~80% of adult female mortality was human caused, suggesting that humans functioned as a "super predator" in this system. Simultaneously, elk leveraged the human shield against wolves but not cougars at night, and no elk were confirmed to have been killed by wolves. Our results add to the mounting evidence that humans profoundly affect predator-prey interactions, highlighting the importance of studying these dynamics in anthropogenic areas.

Animal-mediated plant niche tracking in a changing climate.

Over half of plant species are animal-dispersed, and our understanding of how animals can help plants move in response to climate change - a process known as niche tracking - is limited, but advancing rapidly. Recent research efforts find evidence that animals are helping plants track their niches. They also identify key conditions needed for animal-mediated niche tracking to occur, including alignment of the timing of seed availability, the directionality of animal movements, and microhabitat conditions where seeds are deposited. A research framework that measures niche tracking effectiveness by considering all parts of the niche-tracking process, and links together data and models from multiple disciplines, will lead to further insight and inform actions to help ecosystems adapt to a changing world.

Fear of large carnivores amplifies human-caused mortality for mesopredators.

The challenge that large carnivores face in coexisting with humans calls into question their ability to carry out critical ecosystem functions such as mesopredator suppression outside protected areas. In this study, we examined the movements and fates of mesopredators and large carnivores across rural landscapes characterized by substantial human influences. Mesopredators shifted their movements toward areas with twofold-greater human influence in regions occupied by large carnivores, indicating that they perceived humans to be less of a threat. However, rather than shielding mesopredators, human-caused mortality was more than three times higher than large carnivore-caused mortality. Mesopredator suppression by apex predators may thus be amplified, rather than dampened, outside protected areas, because fear of large carnivores drives mesopredators into areas of even greater risk from human super predators.

Partitioning the effects of an ecosystem engineer: kangaroo rats control community structure via multiple pathways.

1. Ecosystem engineers impact communities by altering habitat conditions, but they can also have strong effects through consumptive, competitive and other non-engineering pathways. 2. Engineering effects can lead to fundamentally different community dynamics than non-engineering effects, but the relative strengths of these interactions are seldom quantified. 3. We combined structural equation modelling and exclosure experiments to partition the effects of a keystone engineer, the giant kangaroo rat (Dipodomys ingens), on plants, invertebrates and vertebrates in a semi-arid California grassland. 4. We separated the effects of burrow creation from kangaroo rat density and found that kangaroo rats increased the diversity and abundance of other species via both engineering and non-engineering pathways. 5. Engineering was the primary factor structuring plant and small mammal communities, whereas non-engineering effects structured invertebrate communities and increased lizard abundance. 6. These results highlight the importance of the non-engineering effects of ecosystem engineers and shed new light on the multiple pathways by which strong-interactors shape communities.

Permanent daylight saving time would reduce deer-vehicle collisions.

Overlap between wildlife and human activity is key to causing wildlife-vehicle collisions, a globally pervasive and growing source of wildlife mortality.1,2 Policies regarding clock time often involve abrupt seasonal shifts in human activity, potentially influencing rates of human-wildlife conflict. Here, we harness the biannual shift between standard and daylight saving time as a natural experiment to reveal how the timing of human activity influences deer-vehicle collisions. Based on 1,012,465 deer-vehicle collisions and 96 million hourly traffic observations across the United States, we show that collisions are 14 times more frequent 2 hours after sunset than before sunset, highlighting the importance of traffic during dark hours as a key determinant of deer-vehicle collision risk. The switch from daylight saving to standard time in autumn causes peak traffic volumes to shift from before sunset to after sunset, leading to a 16% spike in deer-vehicle collisions. By reducing traffic after dark, our model predicts that year-round daylight saving time would prevent 36,550 deer (Odocoileus sp.) deaths, 33 human deaths, 2,054 human injuries, and US$1.19 billion in collision costs annually. In contrast, permanent standard time is predicted to increase collisions by an even larger magnitude, incurring an additional US$2.39 billion in costs. By targeting the temporal dimension of wildlife-vehicle collisions, strategies such as year-round daylight saving time that reduce traffic during dark hours, especially during the breeding season of abundant ungulates, would yield substantial benefits for wildlife conservation and reduce the social and economic costs of deer-vehicle collisions.

Effect of habitat area and isolation on fragmented animal populations.

Habitat destruction has driven many once-contiguous animal populations into remnant patches of varying size and isolation. The underlying framework for the conservation of fragmented populations is founded on the principles of island biogeography, wherein the probability of species occurrence in habitat patches varies as a function of patch size and isolation. Despite decades of research, the general importance of patch area and isolation as predictors of species occupancy in fragmented terrestrial systems remains unknown because of a lack of quantitative synthesis. Here, we compile occupancy data from 1,015 bird, mammal, reptile, amphibian, and invertebrate population networks on 6 continents and show that patch area and isolation are surprisingly poor predictors of occupancy for most species. We examine factors such as improper scaling and biases in species representation as explanations and find that the type of land cover separating patches most strongly affects the sensitivity of species to patch area and isolation. Our results indicate that patch area and isolation are indeed important factors affecting the occupancy of many species, but properties of the intervening matrix should not be ignored. Improving matrix quality may lead to higher conservation returns than manipulating the size and configuration of remnant patches for many of the species that persist in the aftermath of habitat destruction.

Seasonal influence of snow conditions on Dall's sheep productivity in Wrangell-St Elias National Park and Preserve.

Dall's sheep (Ovis dalli dalli) are endemic to alpine areas of sub-Arctic and Arctic northwest America and are an ungulate species of high economic and cultural importance. Populations have historically experienced large fluctuations in size, and studies have linked population declines to decreased productivity as a consequence of late-spring snow cover. However, it is not known how the seasonality of snow accumulation and characteristics such as depth and density may affect Dall's sheep productivity. We examined relationships between snow and climate conditions and summer lamb production in Wrangell-St Elias National Park and Preserve, Alaska over a 37-year study period. To produce covariates pertaining to the quality of the snowpack, a spatially-explicit snow evolution model was forced with meteorological data from a gridded climate re-analysis from 1980 to 2017 and calibrated with ground-based snow surveys and validated by snow depth data from remote cameras. The best calibrated model produced an RMSE of 0.08 m (bias 0.06 m) for snow depth compared to the remote camera data. Observed lamb-to-ewe ratios from 19 summers of survey data were regressed against seasonally aggregated modelled snow and climate properties from the preceding snow season. We found that a multiple regression model of fall snow depth and fall air temperature explained 41% of the variance in lamb-to-ewe ratios (R2 = .41, F(2,38) = 14.89, p<0.001), with decreased lamb production following deep snow conditions and colder fall temperatures. Our results suggest the early establishment and persistence of challenging snow conditions is more important than snow conditions immediately prior to and during lambing. These findings may help wildlife managers to better anticipate Dall's sheep recruitment dynamics.