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Throughout the world, livestock predation by mammalian carnivores causes significant economic losses to poor farmers, and leads to human–wildlife conflicts. These conflicts result in a negative attitude towards carnivore conservation and often trigger retaliatory killing. In northern Pakistan, we investigated livestock depredation by large carnivores between 2014 and 2019, and subsequent Human–wildlife conflict, through questionnaire-based surveys (n = 100 households). We used a semi-structured questionnaire to collect data on livestock population, depredation patterns, predation count, and conservation approaches. We found a statistically significant increasing pattern of predation with influential factors such as age, gender, occupation, education of respondents, population of predators, threats index for predators and conservation efforts. Some 310 livestock heads with an average of 51 animals per year out of the total 9273 heads were killed by predators, and among them 168 (54%) were attributed to the wolf and 142 (45.8%) to snow leopard. Major threats to carnivores in the area included retaliatory killing, habitat destruction and climate change. Incentivization against depredation losses, guarded grazing and construction of predator-proof corral may reduce Human–wildlife conflict and both livelihood and predator can be safeguarded in the study area. [ABSTRACT FROM AUTHOR]

The simultaneous development of technology (e.g. camera traps) and statistical methods, particularly spatially capture–recapture (SCR), has improved monitoring of large mammals in recent years. SCR estimates are known to be sensitive to sampling design, yet existing recommendations about trap spacing and coverage are often not achieved, particularly for sampling wide-ranging and rare species in landscapes that allow for limited accessibility. Consequently, most camera trap studies on large wide-ranging carnivores relies on convenience or judgmental sampling, and often yields compromised results. This study attempts to highlight the importance of carefully considered sampling design for large carnivores that, because of low densities and elusive behavior, are challenging to monitor. As a motivating example, we use two years of snow leopard camera trapping data from the same areas in the high mountains of Pakistan but with vastly different camera configurations, to demonstrate that estimates of density and space use are indeed sensitive to the trapping array. A compact design, one in which cameras were placed much closer together than generally recommended and therefore have lower spatial coverage, resulted in fewer individuals observed, but more recaptures, and estimates of density and space use were inconsistent with expectations for the region. In contrast, a diffuse design, one with larger spacing and spatial coverage and more consistent with general recommendations, detected more individuals, had fewer recaptures, but generated estimates of density and space use that were in line with expectations. Researchers often opt for compact camera configurations while monitoring wide-ranging and rare species, in an attempt to maximize the encounter probabilities. We empirically demonstrate the potential for biases when sampling a small area approximately the size of a single home range—this arises from exposing fewer individuals than deemed sufficient for estimation. The smaller trapping array may also underestimate density by significantly inflating σ . On the other hand, larger trapping array with fewer detectors and poor design induces uncertainties in the estimates. We conclude that existing design recommendations have limited utility on practical grounds for devising feasible sampling designs for large ranging species, and more research on SCR designs is required that allows for integrating biological and habitat traits of large carnivores in sampling framework. We also suggest that caution should be exercised when there is a reliance on convenience sampling. [ABSTRACT FROM AUTHOR]

Pakistan's northern expanses have rich diversity of mammalian carnivores, but majority of them are either threatened or endangered due to habitat degradation and conflict with humans. This study was conducted between May and June 2014 with the aim of determining the diversity of mammalian carnivores and their conflict with humans in Musk Deer National Park (MDNP), Azad Jammu and Kashmir (AJK). Forty motion-triggered cameras (Reconyx) were installed in different watersheds of MDNP to determine carnivore species diversity. A human-carnivore conflict study was conducted through semi-structured questionnaires where 149 respondents were randomly selected from 18 villages in the park. A total of nine carnivore species were documented, namely snow leopard ( Panthera uncia), common leopard ( Panthera pardus), leopard cat ( Prionailurus bengalensis), brown bear ( Ursus arctos), Asiatic black bear ( Ursus thibetinus), grey wolf ( Canis lupus), red fox ( Vulpes vulpes), stone marten ( Martes foina), and yellow-throated marten ( Martes flavigula). During the past year, a total of 817 livestock were lost to disease and carnivore predation. Carnivores were held responsible for 276 livestock losses which translated into an annual economic loss of USD 28,145 (USD 189 per household). Both Asiatic black bear and brown bear also damaged maize and potato crops causing economic losses of USD 16,330 (USD 110 per household). Depredation of livestock was greatly affected by four factors: prey type, season of depredation, location of depredation, and livestock guarding practices. Based on the responses, the people of Folwai village showed the most negative perception towards carnivores. Majority of the respondents declared grey wolf, brown bear, and Asiatic black bear to be the most dangerous carnivores in the park. Our results showed that MDNP has rich diversity of carnivores but their survival in the park is in danger due to conflict with humans over excessive livestock depredations and crop raiding. Active livestock guarding practices can reduce carnivore attacks. Educating local people, vaccinating their livestock, and compensating affected families can greatly reduce negative perceptions. [ABSTRACT FROM AUTHOR]