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Direct and indirect interactions among predators affect predator fitness, distribution, and overall community structure. Yet, outside of experimental settings, such interactions are difficult to observe and thus poorly understood. Patterns of niche overlap among predators reflect and shape community interactions and may therefore help elucidate the nature and intensity of intraguild interactions. To better understand the coexistence of two apex predators, snow leopards (Panthera uncia) and wolves (Canis lupus), we investigated their spatial, temporal, and dietary niche overlap in summer in the Pamir Mountains of Tajikistan. We estimated population-level space use via spatial capture–recapture models based on noninvasive genetics and camera traps, diel activity patterns based on camera trap detections, and diet composition from prey remains in carnivore scats, from which we estimated coefficients between 0 and 1 for overlap in space, time, and diet, respectively. Snow leopards and wolves displayed moderate spatial partitioning (0.26, 95% confidence interval [CI]: 0.17–37), but overlapping temporal (0.77, 95% CI: 0.64–0.90) and dietary (0.97, 95% CI: 0.80–0.99) niches. Both predators relied on seasonally abundant marmots (Marmota caudata) rather than wild ungulates, their typical primary prey, suggesting that despite patterns of overlap that were superficially conducive to exploitation competition and predator facilitation, prey were likely not a limiting factor. Therefore, prey-mediated interactions, if present, were unlikely to be a major structuring force in the ecosystem. By implication, carnivore conservation planning and monitoring in the mountains of Central Asia should more fully account for the seasonal importance of marmots in the ecosystem.

 

Current video database management systems (VDBMSs) fail to support the growing number of video datasets in diverse domains because these systems assume clean data and rely on pretrained models to detect known objects or actions. Existing systems also lack good support for compositional queries that seek events con- sisting of multiple objects with complex spatial and temporal rela- tionships. In this paper, we propose VOCAL, a vision of a VDBMS that supports efficient data cleaning, exploration and organization, and compositional queries, even when no pretrained model exists to extract semantic content. These techniques utilize optimizations to minimize the manual effort required of users. 

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.

 

Extreme climatic events (ECEs) and predator removal represent some of the most widespread stressors to ecosystems. Though species interactions can alter ecological effects of climate change (and vice versa), it is less understood whether, when and how predator removal can interact with ECEs to exacerbate their effects. Understanding the circumstances under which such interactions might occur is critical because predator loss is widespread and ECEs can generate rapid phase shifts in ecosystems which can ultimately lead to tropicalization.

Our goal was to determine whether loss of predation risk may be an important mechanism governing ecosystem responses to extreme events, and whether the effects of such events, such as tropicalization, can occur even when species range shifts do not. Specifically, our goal was to experimentally simulate the loss of an apex predator, the tiger sharkGaleocerdo cuviereffects on a recently damaged seagrass ecosystem of Shark Bay, Australia by applying documented changes to risk‐sensitive grazing of dugongDugong dugonherbivores.

Using a 16‐month‐field experiment established in recently disturbed seagrass meadows, we used previous estimates of risk‐sensitive dugong foraging behaviour to simulate altered risk‐sensitive foraging densities and strategies of dugongs consistent with apex predator loss, and tracked seagrass responses to the simulated grazing.

Grazing treatments targeted and removed tropical seagrasses, which declined. However, like in other mixed‐bed habitats where dugongs forage, treatments also incidentally accelerated temperate seagrass losses, revealing that herbivore behavioural changes in response to predator loss can exacerbate ECE and promote tropicalization, even without range expansions or introductions of novel species.

Our results suggest that changes to herbivore behaviours triggered by loss of predation risk can undermine ecological resilience to ECEs, particularly where long‐lived herbivores are abundant. By implication, ongoing losses of apex predators may combine with increasingly frequent ECEs to amplify climate change impacts across diverse ecosystems and large spatial scales.

 

Apex predators can influence ecosystems through density and behaviorally mediated effects on herbivores and mesopredators. In many parts of the world, apex predators live in, or are returning to, landscapes that have been modified by people; so, it is important to understand their ecological role in anthropogenic landscapes. We used motion-activated game cameras to compare the activity patterns of humans and 2 mesopredators, coyotes (Canis latrans) and bobcats (Lynx rufus), in areas with and without an apex predator, the gray wolf (Canis lupus), in a multiuse landscape of the northwestern United States. In areas with wolves, there was a significant increase in temporal niche overlap between the mesopredators owing to higher levels of coyote activity at all time periods of the day. Temporal overlap between mesopredators and humans also increased significantly in the presence of wolves. Coyotes exposed to wolves increased their activity during dawn, day, and dusk hours. The increase in coyote activity was greatest during the day, when wolves were least active. The direction of change in bobcat activity in areas with wolves was opposite to coyotes, suggesting a behaviorally mediated cascade between wolves, coyotes, and bobcats, although these findings would need to be confirmed with further research. Our findings suggest that mesopredators in human-dominated systems may perceive humans as less dangerous than apex predators, that humans may be more likely to encounter mesopredators in areas occupied by top predators, and that behaviorally mediated effects of apex predators on mesopredators persist in human-dominated landscapes.

 

Top predators have cascading effects throughout the food web, but their impacts on scavenger abundance are largely unknown. Gray wolves (Canis lupus) provide carrion to a suite of scavenger species, including the common raven (Corvus corax). Ravens are wide‐ranging and intelligent omnivores that commonly take advantage of anthropogenic food resources. In areas where they overlap with wolves, however, ravens are numerous and ubiquitous scavengers of wolf‐acquired carrion. We aimed to determine whether subsidies provided through wolves are a limiting factor for raven populations in general and how the wolf reintroduction to Yellowstone National Park in 1995–1997 affected raven population abundance and distribution on the Yellowstone's Northern Range specifically. We counted ravens throughout Yellowstone's Northern Range in March from 2009 to 2017 in both human‐use areas and wolf habitat. We then used statistics related to the local wolf population and the winter weather conditions to model raven abundance during our study period and predict raven abundance on the Northern Range both before and after the wolf reintroduction. In relatively severe winters with greater snowpack, raven abundance increased in areas of human use and decreased in wolf habitat. When wolves were able to acquire more carrion, however, ravens increased in wolf habitat and decreased in areas with anthropogenic resources. Raven populations prior to the wolf reintroduction were likely more variable and heavily dependent on ungulate winter‐kill and hunter‐provided carcasses. The wolf recovery in Yellowstone helped stabilize raven populations by providing a regular food supply, regardless of winter severity. This stabilization has important implications for effective land management as wolves recolonize the west and global climate patterns change.