Spatiotemporal heterogeneity in prey abundance and vulnerability shapes the foraging tactics of an omnivore.

Prey abundance and prey vulnerability vary across space and time, but we know little about how they mediate predator-prey interactions and predator foraging tactics. To evaluate the interplay between prey abundance, prey vulnerability and predator space use, we examined patterns of black bear (Ursus americanus) predation of caribou (Rangifer tarandus) neonates in Newfoundland, Canada using data from 317 collared individuals (9 bears, 34 adult female caribou, 274 caribou calves). During the caribou calving season, we predicted that landscape features would influence calf vulnerability to bear predation, and that bears would actively hunt calves by selecting areas associated with increased calf vulnerability. Further, we hypothesized that bears would dynamically adjust their foraging tactics in response to spatiotemporal changes in calf abundance and vulnerability (collectively, calf availability). Accordingly, we expected bears to actively hunt calves when they were most abundant and vulnerable, but switch to foraging on other resources as calf availability declined. As predicted, landscape heterogeneity influenced risk of mortality, and bears displayed the strongest selection for areas where they were most likely to kill calves, which suggested they were actively hunting caribou. Initially, the per-capita rate at which bears killed calves followed a type-I functional response, but as the calving season progressed and calf vulnerability declined, kill rates dissociated from calf abundance. In support of our hypothesis, bears adjusted their foraging tactics when they were less efficient at catching calves, highlighting the influence that predation phenology may have on predator space use. Contrary to our expectations, however, bears appeared to continue to hunt caribou as calf availability declined, but switched from a tactic of selecting areas of increased calf vulnerability to a tactic that maximized encounter rates with calves. Our results reveal that generalist predators can dynamically adjust their foraging tactics over short time-scales in response to changing prey abundance and vulnerability. Further, they demonstrate the utility of integrating temporal dynamics of prey availability into investigations of predator-prey interactions, and move towards a mechanistic understanding of the dynamic foraging tactics of a large omnivore.

Climate change can alter predator-prey dynamics and population viability of prey.

For many organisms, climate change can directly drive population declines, but it is less clear how such variation may influence populations indirectly through modified biotic interactions. For instance, how will climate change alter complex, multi-species relationships that are modulated by climatic variation and that underlie ecosystem-level processes? Caribou (Rangifer tarandus), a keystone species in Newfoundland, Canada, provides a useful model for unravelling potential and complex long-term implications of climate change on biotic interactions and population change. We measured cause-specific caribou calf predation (1990-2013) in Newfoundland relative to seasonal weather patterns. We show that black bear (Ursus americanus) predation is facilitated by time-lagged higher summer growing degree days, whereas coyote (Canis latrans) predation increases with current precipitation and winter temperature. Based on future climate forecasts for the region, we illustrate that, through time, coyote predation on caribou calves could become increasingly important, whereas the influence of black bear would remain unchanged. From these predictions, demographic projections for caribou suggest long-term population limitation specifically through indirect effects of climate change on calf predation rates by coyotes. While our work assumes limited impact of climate change on other processes, it illustrates the range of impact that climate change can have on predator-prey interactions. We conclude that future efforts to predict potential effects of climate change on populations and ecosystems should include assessment of both direct and indirect effects, including climate-predator interactions.

Examining spatial patterns of selection and use for an altered predator guild.

Anthropogenic disturbances have altered species' distributions potentially impacting interspecific interactions. Interference competition is when one species denies a competing species access to a resource. One mechanism of interference competition is aggression, which can result in altered space-use of a subordinate species due to the threat of harm, otherwise known as a 'landscape of fear'. Alternatively, subordinates might outcompete dominant species in resource-poor environments via a superior ability to extract resources. Our goal was to evaluate spatial predictions of the 'landscape of fear' hypothesis for a carnivore guild in Newfoundland, Canada, where coyotes recently immigrated. Native Newfoundland carnivores include red foxes, Canada lynx, and black bears. We predicted foxes and lynx would avoid coyotes because of their larger size and similar dietary niches. We used scat-detecting dogs and genetic techniques to locate and identify predator scats. We then built resource selection functions and tested for avoidance by incorporating predicted values of selection for the alternative species into the best supported models of each species. We found multiple negative relationships, but notably did not find avoidance by foxes of areas selected by coyotes. While we did find that lynx avoided coyotes, we also found a reciprocal relationship. The observed patterns suggest spatial partitioning and not coyote avoidance, although avoidance could still be occurring at different spatial or temporal scales. Furthermore, Newfoundland's harsh climate and poor soils may swing the pendulum of interspecific interactions from interference competition to exploitative competition, where subordinates outcompete dominant competitors through a superior ability to extract resources.

Phase-dependent climate-predator interactions explain three decades of variation in neonatal caribou survival.

Climate can have direct and indirect effects on population dynamics via changes in resource competition or predation risk, but this influence may be modulated by density- or phase-dependent processes. We hypothesized that for ungulates, climatic conditions close to parturition have a greater influence on the predation risk of neonates during population declines, when females are already under nutritional stress triggered by food limitation. We examined the presence of phase-dependent climate-predator (PDCP) interactions on neonatal ungulate survival by comparing spatial and temporal fluctuations in climatic conditions, cause-specific mortality and per capita resource limitation. We determined cause-specific fates of 1384 caribou (Rangifer tarandus) from 10 herds in Newfoundland, spanning more than 30 years during periods of numerical increase and decline, while exposed to predation from black bears (Ursus americanus) and coyotes (Canis latrans). We conducted Cox proportional hazards analysis for competing risks, fit as a function of weather metrics, to assess pre- and post-partum climatic influences on survival on herds in population increase and decline phases. We used cumulative incidence functions to compare temporal changes in risk from predators. Our results support our main hypothesis; when caribou populations increased, weather conditions preceding calving were the main determinants of cause-specific mortality, but when populations declined, weather conditions during calving also influenced predator-driven mortality. Cause-specific analysis showed that weather conditions can differentially affect predation risk between black bears and coyotes with specific variables increasing the risk from one species and decreasing the risk from the other. For caribou, nutritional stress appears to increase predation risk on neonates, an interaction which is exacerbated by susceptibility to climatic events. These findings support the PDCP interactions framework, where maternal body condition influences susceptibility to climate-related events and, subsequently, risk from predation.

Dynamic landscapes of fear: understanding spatiotemporal risk.

The landscape of fear (LOF) concept posits that prey navigate spatial heterogeneity in perceived predation risk, balancing risk mitigation against other activities necessary for survival and reproduction. These proactive behavioral responses to risk can affect individual fitness, population dynamics, species interactions, and coexistence. Yet, antipredator responses in free-ranging prey often contradict expectations, raising questions about the generality and scalability of the LOF framework and suggesting that a purely spatial, static LOF conceptualization may be inadequate. Here, we outline a 'dynamic' LOF framework that explicitly incorporates time to account for predictable spatiotemporal variation in risk-resource trade-offs. This integrated approach suggests novel predictions about predator effects on prey behaviors to refine understanding of the role predators play in ecological communities.

Elevated wildlife-vehicle collision rates during the COVID-19 pandemic.

Wildlife-vehicle collisions threaten both humans and wildlife, but we still lack information about the relationship between traffic volume and wildlife-vehicle collisions. The COVID-19 pandemic allowed us to investigate the effects of traffic volume on wildlife-vehicle collisions in the United States. We observed decreased traffic nationwide, particularly in densely populated states with low or high disease burdens. Despite reduced traffic, total collisions were unchanged; wildlife-vehicle collisions did decline at the start of the pandemic, but increased as the pandemic progressed, ultimately exceeding collisions in the previous year. As a result, nationwide collision rates were higher during the pandemic. We suggest that increased wildlife road use offsets the effects of decreased traffic volume on wildlife-vehicle collisions. Thus, decreased traffic volume will not always reduce wildlife-vehicle collisions.

Understanding predation risk and individual variation in risk avoidance for threatened boreal caribou.

Predation risk is a driver of species' distributions. Animals can increase risk avoidance in response to fluctuations in predation risk, but questions remain regarding individual variability and the capacity to respond to changes in spatial risk across human-altered landscapes. In northeast British Columbia, Canada, boreal caribou populations declined as roads and seismic lines have increased, which are theorized to increase gray wolf predation. Our goal was to model risk and to evaluate individual variability and the development of risk perception by examining individual risk avoidance in response to reproductive status and age. We used locations from collared caribou and wolves to identify landscape features associated with the risk of a potential wolf-caribou encounter and risk of being killed given an encounter. We built resource selection functions to estimate individual responses to risk. We used general linear regressions to evaluate individual risk and linear feature avoidance as a function of age and reproductive status (calf or no calf). Linear features increased the risk of encounter. Older caribou and caribou with calves demonstrated stronger avoidance of the risk of encounter and roads, but weaker avoidance in late summer to the risk of being killed relative to younger and calf-less individuals. Mechanisms explaining the inverse relationships between the risk of encounter and risk of being killed are uncertain, but it is conceivable that caribou learn to avoid the risk of encounter and roads. Responses by females with vulnerable calves to the risk of encounter and risk of being killed might be explained by a trade-off between these two risk types and a prioritization on the risk of encounter. Despite the capacity to alter their responses to risk, the global decline in Rangifer populations (caribou and wild reindeer) suggests these behaviors are insufficient to mitigate the impacts of anthropogenic disturbances.

Evaluating noninvasive genetic sampling techniques to estimate large carnivore abundance.

Monitoring large carnivores is difficult because of intrinsically low densities and can be dangerous if physical capture is required. Noninvasive genetic sampling (NGS) is a safe and cost-effective alternative to physical capture. We evaluated the utility of two NGS methods (scat detection dogs and hair sampling) to obtain genetic samples for abundance estimation of coyotes, black bears and Canada lynx in three areas of Newfoundland, Canada. We calculated abundance estimates using program capwire, compared sampling costs, and the cost/sample for each method relative to species and study site, and performed simulations to determine the sampling intensity necessary to achieve abundance estimates with coefficients of variation (CV) of <10%. Scat sampling was effective for both coyotes and bears and hair snags effectively sampled bears in two of three study sites. Rub pads were ineffective in sampling coyotes and lynx. The precision of abundance estimates was dependent upon the number of captures/individual. Our simulations suggested that ~3.4 captures/individual will result in a < 10% CV for abundance estimates when populations are small (23-39), but fewer captures/individual may be sufficient for larger populations. We found scat sampling was more cost-effective for sampling multiple species, but suggest that hair sampling may be less expensive at study sites with limited road access for bears. Given the dependence of sampling scheme on species and study site, the optimal sampling scheme is likely to be study-specific warranting pilot studies in most circumstances.

Enhanced understanding of predator-prey relationships using molecular methods to identify predator species, individual and sex.

Predator species identification is an important step in understanding predator-prey interactions, but predator identifications using kill site observations are often unreliable. We used molecular tools to analyse predator saliva, scat and hair from caribou calf kills in Newfoundland, Canada to identify the predator species, individual and sex. We sampled DNA from 32 carcasses using cotton swabs to collect predator saliva. We used fragment length analysis and sequencing of mitochondrial DNA to distinguish between coyote, black bear, Canada lynx and red fox and used nuclear DNA microsatellite analysis to identify individuals. We compared predator species detected using molecular tools to those assigned via field observations at each kill. We identified a predator species at 94% of carcasses using molecular methods, while observational methods assigned a predator species to 62.5% of kills. Molecular methods attributed 66.7% of kills to coyote and 33.3% to black bear, while observations assigned 40%, 45%, 10% and 5% to coyote, bear, lynx and fox, respectively. Individual identification was successful at 70% of kills where a predator species was identified. Only one individual was identified at each kill, but some individuals were found at multiple kills. Predator sex was predominantly male. We demonstrate the first large-scale evaluation of predator species, individual and sex identification using molecular techniques to extract DNA from swabs of wild prey carcasses. Our results indicate that kill site swabs (i) can be highly successful in identifying the predator species and individual responsible; and (ii) serve to inform and complement traditional methods.