GPSeqClus: An R package for sequential clustering of animal location data for model building, model application and field site investigations

Wolf Predation on White-tailed Deer Before, During, and After a Historically Mild Winter in Northern Minnesota

In many southern boreal ecosystems of North America, wolves are the primary predators of white-tailed deer, and white-tailed deer are the primary prey of wolves. Furthermore, wolf-deer systems have and will continue to become more common as white-tailed deer range continues expanding northward in North America. Despite this, there is little information on kill rates of wolves on deer (i.e., the number of deer killed per wolf per unit of time)-a fundamental metric of wolf predation on deer-and how kill rates vary with deer density, wolf density, and environmental conditions. We estimated kill rates of wolves on deer before, during, and after a historically mild winter in the Greater Voyageurs Ecosystem, Minnesota, USA. Kill rates of wolves on deer were low (0.009-0.018 deer/wolf/day) in fall, peaked in February (0.050 deer/wolf/day), and quickly declined to 0 deer/wolf/day by April. The kill rates of wolves on deer we observed in winter were some of the lowest kill rates of wolves on deer that have been documented. Wolves in the Greater Voyageurs Ecosystem appeared unable to catch and kill a sufficient number of deer to meet their daily energetic requirements during Winter 2023-2024, and thus most wolves likely lost weight during winter, a period when wolves are typically in peak physical condition. The rates of wolf predation we observed appeared to be well below those needed to decrease deer population density in the GVE. Thus, our work, in combination with numerous other studies, indicates winter conditions are the primary driver of deer population change in northern climates.

Tradeoffs between resources and risks shape the responses of a large carnivore to human disturbance

Wide-ranging carnivores experience tradeoffs between dynamic resource availabilities and heterogeneous risks from humans, with consequences for their ecological function and conservation outcomes. Yet, research investigating these tradeoffs across large carnivore distributions is rare. We assessed how resource availability and anthropogenic risks influence the strength of lion (Panthera leo) responses to disturbance using data from 31 sites across lions' contemporary range. Lions avoided human disturbance at over two-thirds of sites, though their responses varied depending on site-level characteristics. Lions were more likely to exploit human-dominated landscapes where resources were limited, indicating that resource limitation can outweigh anthropogenic risks and might exacerbate human-carnivore conflict. Lions also avoided human impacts by increasing their nocturnal activity more often at sites with higher production of cattle. The combined effects of expanding human impacts and environmental change threaten to simultaneously downgrade the ecological function of carnivores and intensify human-carnivore conflicts, escalating extinction risks for many species.

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.

Mapping the "catscape" formed by a population of pet cats with outdoor access

The domestic cat (Felis catus) is among the most popular companion animals and most abundant carnivores globally. It is also a pet with an immense ecological footprint because even non-feral and food-subsidized cats can be prolific predators. Whereas knowledge about the spatial behavior of individual domestic cats is growing, we still know little about how a local population of free-ranging pet cats occupies the landscape. Using a citizen science approach, we GPS-tagged 92 pet cats with outdoor access living in a residential area in southern Norway. The resulting position data allowed us to construct both individual home range kernels and a population-level utilization distribution. Our results reveal a dense predatory blanket that outdoor cats drape over and beyond the urban landscape. It is this population-level intensity surface—the “catscape”—that potential prey have to navigate. There were few gaps in the catscape within our residential study area and therefore few terrestrial refuges from potential cat predation. However, cats spent on average 79% of their outdoor time within 50 m to their owner’s home, which suggests that the primary impact is local and most acute for wildlife in the vicinity to homes with cats. We discuss the catscape as a conceptual and quantitative tool for better understanding and mitigating the environmental impact of domestic cats.