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Non‐consumptive effects of predation can strongly impact reproduction and demography of prey species. Still, the underlying mechanisms that drive non‐consumptive effects are not fully understood, and the circumstances under which chronic physiological stress may mediate these effects remain unclear. Benefiting from over 23 years of environmental, physiological and demographic data, we tested the hypothesis that predation risk may impair reproduction of mountain goats through chronic elevation of physiological stress. We conducted path analyses to assess the relationships between predation risk, faecal glucocorticoid metabolites and hair cortisol concentration, and reproduction, while taking into account the potential effects of age class, sex, body mass, season and within individual variation in glucocorticoid concentration. Predation risk had a direct positive effect on the average annual faecal glucocorticoid concentration in the population, which, in turn, negatively affected the proportion of reproductive females. The same pattern was observed with hair cortisol concentration, but these results were inconclusive potentially due to methodological challenges in estimating annual average of hair cortisol at the population level. Our study presents one of the first robust evidence that stress‐mediated breeding suppression can occur in a wild ungulate following increased predation risk, thereby providing a major insight on the mechanisms underlying non‐consumptive effects of predation in wild mammals. A free Plain Language Summary can be found within the Supporting Information of this article. A free Plain Language Summary can be found within the Supporting Information of this article.

The probability of encountering conspecifics shapes animal behaviour, particularly for territorial individuals which often increase vigilance and scent marking when approaching home range boundaries. However, whether the foraging behaviours of territorial predators also vary with the probability of encountering neighbouring territory owners is poorly understood. We monitored 23 Arctic foxes occupying neighbouring home ranges during 2 years of contrasting resource availability on Bylot Island, Nunavut, Canada. First, based on simultaneous GPS tracking of individuals, we established which individuals used a territory by estimating the spatial distribution of the probability of encountering a neighbour within their home range. Second, using GPS and accelerometry data, we evaluated if the probability of encountering a neighbour influenced foraging behaviours, and whether this relationship differed between territorial and non‐territorial individuals. When resources were abundant, only breeding individuals excluded other foxes from a part of their home range and were thus territorial. When resources were rare, none of the foxes reproduced, and all but one were territorial. Non‐territorial individuals were less likely to cache prey in areas with a high probability of encounter, possibly to reduce cache pilfering. Territorial individuals were slightly more likely to cache prey as the probability of encountering neighbours increased, suggesting that they do not actively avoid interactions while foraging. We suggest Arctic foxes use different tactics to secure resources based on their degree of territoriality. The presence of non‐territorial predators, whose home ranges overlap those of territorial neighbours, may influence the distribution of predation risk by creating zones where predator density is high, potentially influencing predator–prey interactions. We monitored the movements and behaviours of Arctic foxes using neighbouring home ranges and evaluated if conspecific interactions influenced where they foraged. The probability of encountering conspecifics influenced non‐territorial Arctic foxes, which favoured caching prey where encounters were less likely to occur. Territorial individuals were less affected, suggesting territoriality is enough to secure the necessary resources for survival.

Predation shapes communities through consumptive and non‐consumptive effects. In the latter case, prey respond to perceived predation risk through proactive or reactive risk management strategies occurring at different spatial and temporal scales. The predator–prey space race and landscape of fear concepts are useful to better understand how predation risk affects prey behavioral decisions and distribution. We assessed predation risk effects in a terrestrial Arctic community, where the arctic fox is the main predator of ground‐nesting birds. Using high‐frequency GPS data, we estimated a predator activity landscape corresponding to fox space use patterns and validated with an artificial prey experiment that this predator activity landscape correlated with the predation risk landscape. We then investigated the effects of the fox activity landscape on multiple prey species, by assessing the anti‐predator behavior of a main prey (snow goose) actively searched for by foxes, and the nest distribution of several incidental prey species. We first found that snow geese showed a stronger level of nest defense in areas highly used by foxes, possibly responding with a reactive strategy to variation in predation risk. Then, nests of incidental prey reproducing in habitats easily accessed by foxes had a lower probability of occurrence in areas highly used by foxes, suggesting these birds may use a proactive risk management strategy by shifting their distribution away from risky areas. For incidental prey species nesting in microhabitat refuges difficult to access by foxes, probability of nest occurrence was independent of predation risk in the surrounding area, as they avoid risk at a finer spatial scale. By tracking all individuals of the dominant predator species in our study area, we demonstrated the value of using predator space use patterns to infer spatial variation in predation risk. Overall, we highlight the diversity of risk management strategies in prey sharing a common predator, hence refining our understanding of the mechanisms driving species distribution and community structure.

As sea-ice cover is shrinking, polar bears ( Ursus maritimus, Phipps, 1774) face decreased access to seals, their primary prey, resulting in a greater dependence on terrestrial food sources. Whether polar bears can benefit from these terrestrial food sources, however, depends on their ability to find and capture prey items without expending more energy than is acquired. Here, we report one of the northernmost observations of polar bear predation on adult birds. The bear used a dive-hunting technique, which consisted of submerging itself, approaching underwater, and catching flightless greater snow geese ( Anser caerulescens caerulescens (Linnaeus, 1758)) from beneath the surface of a tundra pond. After evaluating energy expenditures during swimming and energy intakes from consuming geese, we estimated that this rarely documented dive-hunting technique could be energetically profitable for a certain range of pursuit durations. This observation highlights the behavioral plasticity that polar bears can deploy to punctually exploit land-based food sources.

Predator–prey interactions are a fundamental aspect of ecology that has generated sustained research interests. Progress in the field stems from a diverse range of approaches, from highly controlled yet simplified mathematical and agent‐based models, to grounded but data‐limited field studies. As a compromise between mathematical and observation‐oriented methods, we introduce an original approach based on an outdoor game. In this game, biologged human players follow simple rules to impersonate predators and prey in a natural landscape augmented with synthetic resource patches and refuges. We investigated the behaviour, movement, functional response and spatial organization of over 25 players simultaneously monitored during nine simulations to determine whether the game could replicate realistic predator–prey dynamics. Results derived from our real‐life simulations were consistent with ecological patterns expected in natural systems. We found that (a) predator and prey movements were driven by risk and reward trade‐offs, (b) predators took advantage of linear features to travel at higher speed, making these areas risky for prey, (c) prey had nonlinear and risk‐sensitive functional responses and (d) consumer–resource interactions were spatially modular and defined by players' movement rates and landscape features. Moreover, the comprehensive dataset generated through the game allowed for the exploration of phenomena that are challenging to study in natural settings, such as spatial memory and the influence of satiety on resource acquisition rates. The approach offers a simple, computationally accessible and genuinely amusing way to explore the complex ramifications of predator–prey interactions and test otherwise data‐deficient hypotheses. The strength and originality of the method lies in the use of living agents—players—making decisions in a real‐world setting. This aspect alleviates the computational and empirical burden of defining and estimating decision‐related parameters needed to build simulators, while generating extensive datasets in a flexible experimental framework that is generally out of reach for empirical studies. It also offers immersive insights into predator–prey interactions, making it an engaging pedagogical tool that encourages creative thinking. The numerous possible scenarios that can be explored are only constrained by the investigator's creativity in adapting game rules and the players' desire to win.

Effective approaches are needed to conserve the planet's remaining wildlife and wilderness landscapes, especially concerning global biodiversity conservation targets. Here, we present a new software system called EarthRanger: an open‐source platform built to help monitor, research and manage ecosystems. EarthRanger consists of seven main components (Core Server, API, Storage, Gundi, Web App, Mobile App, Ecoscope) that provide functionality for data (i) aggregation & collection, (ii) storage & management, (iii) real‐time and post hoc analysis, (iv) visualisation and (v) dissemination. The mobile application provides field‐based data recording and visualisation tools. EarthRanger may be deployed for single project use or can aggregate across multiple geographies as a centralised hub. EarthRanger can be used to collect standardised tracking data (e.g. from wildlife collars, vehicles and ranger patrols) and configurable event information (e.g. a singular recording with associated user‐defined attribute information such as a wildlife sighting or encounter with a poacher). Since development began in 2015, the platform has (at the time of writing) been deployed at over 500 sites across 70 countries and with myriad configurations and objectives. EarthRanger has improved the ability to monitor data feeds and manage conservation‐related operations in real time. For instance, the deployment of EarthRanger by African Parks has led to the removal of over 50,000 snares, steady population growth of key species of concern and near cessation of poaching. In Liwonde's protected area, enhanced mitigation efforts supported by EarthRanger reduced the number of deaths from wildlife conflict by more than 91%. EarthRanger is also providing a platform to enhance standardisation, aggregation, transfer and long‐term storage of ecological information and promote collaboration between groups conducting protected area management and ecology and biodiversity research.

As sea-ice cover is shrinking, polar bears (Ursus maritimus, Phipps 1774) face decreased access to seals, their primary prey, resulting in a greater dependance on terrestrial food sources. Whether polar bears can benefit from these terrestrial food sources however depends on their ability to find and capture prey items without expending more energy than is acquired. Here, we report one of the northernmost observations of polar bear predation on adult birds. The bear used a dive-hunting technique, which consisted of submerging itself, approaching underwater and catching flightless greater snow geese (Anser caerulescens caerulescens) from beneath the surface of a tundra pond. After evaluating energy expenditures during swimming and energy intakes from consuming geese, we estimated that this rarely documented dive-hunting technique could be energetically profitable for a certain range of pursuit duration. This observation highlights the behavioral plasticity that polar bears can deploy to punctually exploit land-based food sources.

The probability of encountering conspecifics shapes multiple dimensions of animal behaviour. For example, territorial individuals increase vigilance, scent marking and alarm calling when approaching home range boundaries. Whether territorial predators modify their foraging behaviours with respect to the probability of encountering neighbouring territory owners is poorly understood. However, this could strongly influence the landscape of predation risk and therefore modulate predator-prey interactions. We studied the movements and behaviours of 23 resident Arctic foxes occupying neighbouring home ranges during two years of contrasting resource availability (abundant resources in 2019, scarce resources in 2022) on Bylot Island, Nunavut, Canada. First, based on simultaneous GPS tracking of individuals, we established which individuals used a territory (an exclusive area) by estimating the spatial distribution of the probability of encountering a neighbour within their home range. Second, using GPS and accelerometry data, we evaluated if the probability of encountering a neighbour influenced the spatial distribution of foraging behaviours, and whether this relationship differed between territorial and non-territorial individuals. When resources were abundant, only breeding individuals excluded other foxes from a part of their home range and were thus territorial. When resources were rare, none of the foxes reproduced and all but one were territorial. Non-territorial individuals in 2019 were less likely to cache prey in areas with a high probability of encounter, possibly reducing the risk of cache pilfering. We found no effect of the probability of encounter on the behaviours of the non-territorial individual in 2022. The probability to cache prey of territorial individuals however did not depend on the probability of encountering a neighbour, suggesting they have no benefit of modulating the distribution of their caches according to potential encounters in a partly exclusive area. Our results thus suggest that Arctic foxes use different tactics to secure resources based on their degree of territoriality and the availability of resources. We highlight how the presence of resident, but non-territorial predators, whose home ranges overlap those of their territorial neighbours, may influence the distribution of predation risk by creating zones where predator density is high, potentially influencing predator-prey interactions.

Predator-prey interactions in natural communities are complex, with predators often exploiting multiple prey types and generating indirect interactions among them. Ecological theory has traditionally modeled these interactions using functional responses models which are based on foraging rates, not energy transfers. This approach overlooks how the energy acquisition rate of a predator can alter its behavior and, in turn, the strength of species interactions. Here, we integrate predator energetics into a functional response model to represent trade-offs predators face when foraging on prey that vary in risk and abundance across heterogeneous landscapes. We compared model predictions to 20 years of prey species density and reproductive success data. The mechanistic model was parameterized for an Arctic tundra vertebrate community, where the Arctic fox feeds on cyclic lemmings and eggs of sandpipers (non-risky prey) and gulls (risky prey that often nest in partial refuge like islands). In this system, predator-mediated interactions generate apparent mutualism between lemmings and birds, but its strength varies between species, and the mechanisms underlying this interaction remain unclear. We found that fox energetic balance was highly related to lemming density, with a threshold of 89 lemmings per km2 required for a positive energetic balance. Model-predicted gull nest acquisition rates were lowest on islands when the energetic balance of foxes was positive, and highest for nests on the shore when foxes were in deficit. The model that incorporated predator risk-taking behavior and energetic balance produced variation in gull hatching success that most closely matched empirical observations. We documented for the first time that a shift in predator energetic balance, triggering changes in attack and capture probabilities on a risky prey, can be a key mechanism underlying the apparent mutualism between lemmings and gulls. In contrast, for non-risky prey, the indirect effect can be essentially driven by changes in predator movement. These findings highlight how prey characteristics can lead to different mechanisms behind similar indirect interactions. Taken together, our results indicate that mechanistic models integrating species traits, landscape features, and energy-dependent behavioral adjustments can improve our ability to quantify interaction strengths in natural communities.

1. Predator-prey interactions are universal, governing the flow of energy between trophic levels and shaping ecological communities. Despite >70 years of research, our knowledge of the mechanisms modulating the strength of these interactions is limited. 2. To untangle proximate mechanisms governing species interactions and improve our ability to quantify interaction strength, we developed a mechanistic model that integrates predator risk-taking behavior, predator energetic balance and anti-predator refuges in a natural vertebrate community. 3. Our model, based on species traits and behavior, was inspired by the Arctic tundra, where the main predator (the arctic fox) feeds primarily on cyclic small rodents (lemmings) and eggs of various tundra-nesting bird species such as sandpipers eggs(non-risky prey) and gulls eggs (risky prey). We confront the model predictions with 20 years of data on species density and reproductive success. 4. According to the energetic model, lemmings are the most important contributor to the energetic balance of foxes, with a threshold density of 89 lemmings per km2 required to switch to a positive energetic balance. When the fox energetic balance goes from positive (high lemming density) to negative (low lemming density), the acquisition rate of gull eggs increases 1.7 times on shores and 9.5 times on islands, a partial refuge and riskier habitat for the predator. Variation in gull hatching success generated by the mechanistic model aligned with empirical observations for both habitat. 5. Our results show that changes in predator energetic balance, translating into a change in attack and capture probabilities, can be a major mechanism underlying predator-mediated effect of lemmings on gulls hatching success. 6. This study is a critical step towards the integration of energetic and landscape characteristics into predator-multiprey models and presents one of the rare mechanistic models parameterized in a natural vertebrate community. Such a model can strongly improve our ability to quantify interaction strengths in multi-species communities.Competing Interest StatementThe authors have declared no competing interest.