Relative influence of wild prey and livestock abundance on carnivore‐caused livestock predation

Abstract

Conservation conflict over livestock depredation is one of the key drivers of large mammalian carnivore declines worldwide. Mitigating this conflict requires strategies informed by reliable knowledge of factors influencing livestock depredation. Wild prey and livestock abundance are critical factors influencing the extent of livestock depredation. We compared whether the extent of livestock predation by snow leopards Panthera uncia differed in relation to densities of wild prey, livestock, and snow leopards at two sites in Shey Phoksundo National Park, Nepal. We used camera trap‐based spatially explicit capture–recapture models to estimate snow leopard density; double‐observer surveys to estimate the density of their main prey species, the blue sheep Pseudois nayaur ; and interview‐based household surveys to estimate livestock population and number of livestock killed by snow leopards. The proportion of livestock lost per household was seven times higher in Upper Dolpa, the site which had higher snow leopard density (2.51 snow leopards per 100 km 2 ) and higher livestock density (17.21 livestock per km 2 ) compared to Lower Dolpa (1.21 snow leopards per 100 km 2 ; 4.5 livestock per km 2 ). The wild prey density was similar across the two sites (1.81 and 1.57 animals per km 2 in Upper and Lower Dolpa, respectively). Our results suggest that livestock depredation level may largely be determined by the abundances of the snow leopards and livestock and predation levels on livestock can vary even at similar levels of wild prey density. In large parts of the snow leopard range, livestock production is indispensable to local livelihoods and livestock population is expected to increase to meet the demand of cashmere. Hence, we recommend that any efforts to increase livestock populations or conservation initiatives aimed at recovering or increasing snow leopard population be accompanied by better herding practices (e.g., predator‐proof corrals) to protect livestock from snow leopard.

Estimating snow leopard and prey populations at large spatial scales

“…We used a stratified random sampling design based on an occupancy survey for our camera trap-based abundance estimation, and estimated snow leopard density for an area that was 1.5 times larger than the cumulative size of the study areas of all the previously published studies put together (Chetri et al, 2019;Khanal et al, 2020;Suryawanshi et al, 2019). Johansson et al (2016) showed that 40%…”

“…We assessed snow leopard abundance in a large landscape of over 26,112 km 2 comprising the entire snow leopard habitat in the state of Himachal Pradesh in India (Figure 1). The size of our study area was one and half times the size of the entire area covered cumulatively by all published snow leopard population estimation studies conducted so far across its range (Chetri et al 2019;Khanal et al, 2020;Suryawanshi et al, 2019). The primary goal of our study was to demonstrate a two-step sampling approach for estimating the population of snow leopards at a large spatial scale.…”

Snow Leopard Dietary Preferences and Livestock Predation Revealed by Fecal DNA Metabarcoding: No Evidence for Apparent Competition Between Wild and Domestic Prey

“…We found that livestock consumption by snow leopards (both per sample RRA and total amount) was strongly correlated with local livestock biomass, but not with livestock density (Figure 5). Livestock density is a common index used to assess wild predator depredation response to domestic prey availability (Chetri et al, 2017;Pimenta et al, 2018;Khanal et al, 2020). However, we argue that spatial distribution of livestock, compared with wild prey, is more heterogeneous and often clustered near resources and shelters, thus making average density across large areas an inappropriate measure of livestock availability.…”

Applying the double observer methodology for assessing blue sheep population size in Nar Phu valley, Annapurna Conservation Area, Nepal

“…This study indicated high detection probabilities at 0.94 and 0.91 for O1 and O2 respectively, comparable to those of Thinely et al (2018). By contrast, Khattak et al (2019) reported lower detection rates in Pakistan's isolated blue sheep population (0.78 and 0.47); Khanal et al (2020) estimated detection rates of 0.67 and 0.70 in Lower Dolpa and 0.78 and 0.75 in the Upper Dolpa sector of Nepal's SPNP. Khanyari et al (2021) reported similar ranges (0.36–0.74) in the central Tien Shan landscape of Kyrgyzstan.…”