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Research on the ecology of fear has highlighted the importance of perceived risk from predators and humans in shaping animal behavior and physiology, with potential demographic and ecosystem-wide consequences. Despite recent conceptual advances and potential management implications of the ecology of fear, theory and conservation practices have rarely been linked. Many challenges in animal conservation may be alleviated by actively harnessing or compensating for risk perception and risk avoidance behavior in wild animal populations. Integration of the ecology of fear into conservation and management practice can contribute to the recovery of threatened populations, human–wildlife conflict mitigation, invasive species management, maintenance of sustainable harvest and species reintroduction plans. Here, we present an applied framework that links conservation interventions to desired outcomes by manipulating ecology of fear dynamics. We discuss how to reduce or amplify fear in wild animals by manipulating habitat structure, sensory stimuli, animal experience (previous exposure to risk) and food safety trade-offs to achieve management objectives. Changing the optimal decision-making of individuals in managed populations can then further conservation goals by shaping the spatiotemporal distribution of animals, changing predation rates and altering risk effects that scale up to demographic consequences. We also outline future directions for applied research on fear ecology that will better inform conservation practices. Our framework can help scientists and practitioners anticipate and mitigate unintended consequences of management decisions, and highlight new levers for multi-species conservation strategies that promote human–wildlife coexistence. 

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.

 

While the functional response of predators is commonly measured, recent work has revealed that the age and sex composition of prey killed is often a better predictor of prey population dynamics because the reproductive value of adult females is usually higher than that of males or juveniles.

Climate is often an important mediating factor in determining the composition of predator kills, but we currently lack a mechanistic understanding of how the multiple facets of climate interact with prey abundance and demography to influence the composition of predator kills.

Over 20 winters, we monitored 17 wolf packs in Yellowstone National Park and recorded the sex, age and nutritional condition of kills of their dominant prey—elk—in both early and late winter periods when elk are in relatively good and relatively poor condition, respectively.

Nutritional condition (as indicated by per cent marrow fat) of wolf‐killed elk varied markedly with summer plant productivity, snow water equivalent (SWE) and winter period. Moreover, marrow was poorer for wolf‐killed bulls and especially for calves than it was for cows.

Wolf prey composition was influenced by a complex set of climatic and endogenous variables. In early winter, poor plant growth in either yeartort − 1, or relatively low elk abundance, increased the odds of wolves killing bulls relative to cows. Calves were most likely to get killed when elk abundance was high and when the forage productivity they experienced in utero was poor. In late winter, low SWE and a relatively large elk population increased the odds of wolves killing calves relative to cows, whereas low SWE and poor vegetation productivity 1 year prior together increased the likelihood of wolves killing a bull instead of a cow.

Since climate has a strong influence on whether wolves prey on cows (who, depending on their age, are the key reproductive components of the population) or lower reproductive value of calves and bulls, our results suggest that climate can drive wolf predation to be more or less additive from year to year.

 

Imperfect detection is ubiquitous among wildlife research and is therefore commonly included in abundance estimation. Yet, the factors that affect observation success are largely unknown for rare and elusive species, such as large carnivores. Here, we took advantage of intensive ground‐based monitoring effort and an extensive GPS data set (2000–2018) and developed a winter sightability model for gray wolves (Canis lupus) in northern Yellowstone National Park, Wyoming, USA. Our resulting sightability model indicated that observation success was positively affected by the topographic nature of where wolves were in relation to observer locations (viewshed), areas being less forested (openness), and wolf group size, and negatively affected by distance from observer locations. Of these, viewshed had the strongest effect on the probability of observing a wolf, with the odds of observing a wolf being four times more likely when wolves were in the predicted viewshed. Openness was the next most influential covariate, and group size was the least influential. We also tested whether a wolf being harvested from a pack when they were outside of Yellowstone National Park had an effect on wolf sightability. We did not, however, find support for human‐induced mortality affecting wolf sightability inside of Yellowstone National Park. Our results indicate that the ability to observe wolves was greatly affected by ecological and landscape‐level factors, a finding that is likely to generally extend to other large carnivores. As such, our sightability model highlights the importance of considering landscape structure and variation in large carnivore use of the landscape when conducting observational‐based studies.

 

The extent to which prey space use actively minimizes predation risk continues to ignite controversy. Methodological reasons that have hindered consensus include inconsistent measurements of predation risk, biased spatiotemporal scales at which responses are measured and lack of robust null expectations.

We addressed all three challenges in a comprehensive analysis of the spatiotemporal responses of adult female elk (Cervus elaphus) to the risk of predation by wolves (Canis lupus) during winter in northern Yellowstone,USA.

We quantified spatial overlap between the winter home ranges ofGPS‐collared elk and three measures of predation risk: the intensity of wolf space use, the distribution of wolf‐killed elk and vegetation openness. We also assessed whether elk varied their use of areas characterized by more or less predation risk across hours of the day, and estimated encounter rates between simultaneous elk and wolf pack trajectories. We determined whether observed values were significantly lower than expected if elk movements were random with reference to predation risk using a null model approach.

Although a small proportion of elk did show a tendency to minimize use of open vegetation at specific times of the day, overall we highlight a notable absence of spatiotemporal response by female elk to the risk of predation posed by wolves in northern Yellowstone.

Our results suggest that predator–prey interactions may not always result in strong spatiotemporal patterns of avoidance.