Angela K. Fuller

The negative impact of large carnivore presence in human‐dominated landscapes manifests as livestock depredation and in extreme cases as attacks on humans. In the case of conflict with leopards in Nepal, attacks resulting in human fatality have become more frequent over time, thus creating an urgent socio‐ecological and management issue. We estimated the occurrence of leopard attacks in Nepal from human‐leopard conflict cases reported in the media. We used occupancy models to analyse data collected from online news reports on incidents of leopard attacks on humans to explore drivers of leopard attacks on a landscape scale. Our results suggest that the probability of occurrence of leopard attack is associated with human population density, terrain ruggedness and livestock density. The human population density effect may be indicative of a density‐dependent relationship, where attacks are more likely in areas where an increased abundance of humans increases encounter rates with leopards. The positive effect of livestock density suggests that livestock may be drawing leopards into human settlements, and consequently increasing the likelihood of attacks on humans. Terrain ruggedness might be offering ideal conditions to facilitate attacks on humans, for example remoteness and high amounts of cover to launch ambush attacks. We provide inference and insights into key determinants of leopard attacks on humans on a landscape scale. These insights can be used to guide future research, inform mitigation measures to reduce leopard attacks and foster a better understanding of the interaction between people and leopards. This study demonstrates the applicability and novelty of using a hierarchical modelling framework applied to freely and publicly available media reports to inform the applied management of human‐wildlife conflict at a national scale. Read the free Plain Language Summary for this article on the Journal blog.

In heterogeneous landscapes, resource selection constitutes a crucial link between landscape and population‐level processes such as density. We conducted a non‐invasive genetic study of white‐tailed deer in southern Finland in 2016 and 2017 using fecal DNA samples to understand factors influencing white‐tailed deer density and space use in late summer prior to the hunting season. We estimated deer density as a function of landcover types using a spatial capture‐recapture (SCR) model with individual identities established using microsatellite markers. The study revealed second‐order habitat selection with highest deer densities in fields and mixed forest, and third‐order habitat selection (detection probability) for transitional woodlands (clear‐cuts) and closeness to fields. Including landscape heterogeneity improved model fit and increased inferred total density compared with models assuming a homogenous landscape. Our findings underline the importance of including habitat covariates when estimating density and exemplifies that resource selection can be studied using non‐invasive methods.