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.

Rewilding by Wolf Recolonisation, Consequences for Ungulate Populations and Game Hunting.

The ongoing recolonisations of human-transformed environments in Europe by large carnivores like the wolf Canis lupus means that conservation conflicts could re-surface, among other reasons, due to predation on ungulate game species. We estimated the effect of wolves on ungulate species using data on wolf prey selection, kill rates and territory size to build a hypothetical case of future expansion. We extrapolated results on predation from the current wolf distribution in central Sweden and eastern Poland to the eventual wolf recolonisation of southern Sweden. We then calculated the proportion of five ungulate game species killed annually by wolves, and the ratio between the predicted annual predation by wolves given future colonization and the number of ungulates currently harvested by hunters. Results showed that wolf recolonization in southern Sweden would have a minor impact on the estimated population densities of red deer Cervus elaphus, fallow deer Dama dama and wild boar Sus scrofa, but is likely to lead to a significant reduction in human captures of moose Alces alces and roe deer Capreolus capreolus. The current five-ungulate species system in southern Sweden suggests a potential for two to four times higher wolf density than the two-ungulate species system in the northern part of their current distribution. Management and conservation of recolonizing large carnivores require a better understanding of the observed impact on game populations under similar ecological conditions to ameliorate conservation conflicts and achieve a paradigm of coexistence. Integrating these predictions into management is paramount to the current rewilding trend occurring in many areas of Europe or North America.