Predicting kill sites of an apex predator from GPS data in different multiprey systems.

Kill rates are a central parameter to assess the impact of predation on prey species. An accurate estimation of kill rates requires a correct identification of kill sites, often achieved by field-checking GPS location clusters (GLCs). However, there are potential sources of error included in kill-site identification, such as failing to detect GLCs that are kill sites, and misclassifying the generated GLCs (e.g., kill for nonkill) that were not field checked. Here, we address these two sources of error using a large GPS dataset of collared Eurasian lynx (Lynx lynx), an apex predator of conservation concern in Europe, in three multiprey systems, with different combinations of wild, semidomestic, and domestic prey. We first used a subsampling approach to investigate how different GPS-fix schedules affected the detection of GLC-indicated kill sites. Then, we evaluated the potential of the random forest algorithm to classify GLCs as nonkills, small prey kills, and ungulate kills. We show that the number of fixes can be reduced from seven to three fixes per night without missing more than 5% of the ungulate kills, in a system composed of wild prey. Reducing the number of fixes per 24 h decreased the probability of detecting GLCs connected with kill sites, particularly those of semidomestic or domestic prey, and small prey. Random forest successfully predicted between 73%-90% of ungulate kills, but failed to classify most small prey in all systems, with sensitivity (true positive rate) lower than 65%. Additionally, removing domestic prey improved the algorithm's overall accuracy. We provide a set of recommendations for studies focusing on kill-site detection that can be considered for other large carnivore species in addition to the Eurasian lynx. We recommend caution when working in systems including domestic prey, as the odds of underestimating kill rates are higher.

Large carnivores avoid humans while prioritizing prey acquisition in anthropogenic areas.

Large carnivores are recovering in many landscapes where the human footprint is simultaneously growing. When carnivores encounter humans, the way they behave often changes, which may subsequently influence how they affect their prey. However, little research investigates the behavioural mechanisms underpinning carnivore response to humans. As a result, it is not clear how predator-prey interactions and their associated ecosystem processes will play out in the human-dominated areas into which carnivore populations are increasingly expanding. We hypothesized that humans would reduce predation risk for prey by disturbing carnivores or threatening their survival. Alternatively, or additionally, we hypothesized that humans would increase predation risk by providing forage resources that congregate herbivorous prey in predictable places and times. Using grey wolves Canis lupus in Jackson Hole, Wyoming, USA as a study species, we investigated 170 kill sites across a spectrum of human influences ranging from heavily restricted human activities on protected federal lands to largely unregulated activities on private lands. Then, we used conditional logistic regression to quantify how the probability of predation changed across varied types and amounts of human influences, while controlling for environmental characteristics and prey availability. Wolves primarily made kills in environmental terrain traps and where prey availability was high, but predation risk was significantly better explained with the inclusion of human influences than by environmental characteristics alone. Different human influences had different, and even converse, effects on the risk of wolf predation. For example, where prey were readily available, wolves preferentially killed animals far from motorized roads but close to unpaved trails. However, wolves responded less strongly to humans, if at all, where prey were scarce, suggesting they prioritized acquiring prey over avoiding human interactions. Overall, our work reveals that the effects of large carnivores on prey populations can vary considerably among different types of human influences, yet carnivores may not appreciably alter predatory behaviour in response to humans if prey are difficult to obtain. These results shed new light on the drivers of large carnivore behaviour in anthropogenic areas while improving understanding of predator-prey dynamics in and around the wildland-urban interface.