Abstract: We surveyed the urial Ovis vignei and Siberian ibex Capra sibirica in the Hindu Kush mountain range of Wakhan National Park in north-eastern Afghanistan to determine their population status and identify potential drivers of population change. We conducted two double- observer ground surveys, in April–May 2015 and 2018, in 10 areas (total = 288 km2). Urial herds were mostly com- posed of both sexes (78% of observed herds), the mean adult sex ratio (females:males) was 100:70, and the mean female:juvenile ratio was 100:53. In 2018 we calculated a urial density of 35/100 km2, compared to 72/100 km2 in 2015. Ibex herds were mostly (79%) composed of both sexes, the mean adult sex ratio (females:males) was 100:103, and the mean female:juvenile ratio was 100:58. Ibex density estimates were similar in 2015 and 2018 (c. 250/100 km2). We discuss the usefulness of the double-observer methods for ungulate surveys, highlight the value of viewshed calculations and discuss the possible causes of urial population decline. To ensure the conservation of these ungulate populations, we recommend continued regular monitoring, measures to address poaching and research to clarify the taxonomical status of urials in Wakhan.

Abstract: Foreword: Field monitoring of wild animal species is rarely accomplished without challenges. Logistical, environmental, and ecological factors dictate the need for appropriate sampling regardless of location, taxa, or objectives. With regards to felids there is no questioning their popularity when it comes to field research. Their role and impact on the ecosystems combined with their “hypercarnivore” lifestyle and cultural significance have resulted in an extensive and historical resume of field studies across the globe. Despite the vast number of studies on felids, there is a significant skew toward the big cats with the scientific knowledge base for small-bodied cat species, including the Pallas’s cat or manul (Otocolobus manul), much smaller. Given the solitary and elusive nature of most small cats, like the manul, that inhabit remote environments, it is not difficult to understand this gap in field research.
Recognising this gap and following years of field research and conservation, the Pallas’s cat International Conservation Alliance (PICA) and their conservation partners identified the need for targeted and easy to follow guidance on best practices for monitoring the manul in the wild. This guide details an extensive compilation of data collection methods and monitoring techniques for the manul that will help practitioners deliver more effective conservation and research efforts.
This guide was edited by Ehsan Moqanaki and Gustaf Samelius that, in close collaboration with a number of co-authors, have brought together a wealth of knowledge on surveying and monitoring manul populations. Each chapter compiles tried and tested techniques from a range of carnivore research projects over the last few decades, with a focus on the manul. In doing so this guide provides a detailed insight into the most effective data collection methods to enhance future conservation and research efforts for the species. We are grateful to all involved in the development of this book and hope that it serves as a valuable practical guide to current and future conservation and researcher efforts, while contributing to long-term conservation actions for this amazing small cat.
The Pallas’s cat International Conservation Alliance

Abstract: We provide body measurements of snow leopards collected from 55 individuals sampled in five of the major mountain ranges within the species distribution range; the Altai, Hindu Kush, Himalayas, Pamirs and Tien Shan mountains. Snow leopards appear to be similarly sized across their distribution range with mean body masses of 36 kg and 42 kg for adult females and adult males, respectively. In contrast to other large felids, we found little variation in body size and body mass between the sexes; adult males were on average 5% longer and 15% heavier than adult females.

Abstract: Snow leopards (Panthera uncia) have long co-existed with livestock herding people across Asia’s high mountains. Multiple use landscapes however imply potential competition for shared resources, livestock predation, and the risk of retaliatory killing of predators. Community-based conservation is a central pillar for supporting people’s livelihoods and safeguarding predators and their habitat. Based on the theory of planned behavior, we examined the factors that shape herders’ tolerance of snow leopards. Our questionnaire-based study was conducted in the Sanjiangyuan Region, China, encompassing four communities with varying livelihoods, experiences with live- stock depredation and levels of exposure to community conservation interventions. Our results showed that respondents generally held positive views towards snow leopards, although women tended to have relatively more negative views towards snow leopards compared with men. Current household income was largely dependent on caterpillar fungus rather than livestock. Social norms around religion and the role of community leaders in our study area seemed to be the main determinants of the generally benign association of people with wildlife, overshadowing potential influences of community-based conservation interventions. Our work suggests that conservations programs will be aided through collaborations with communities and religious institutions, and that conservationists must proactively engage with women as significant actors in conservation.

Abstract: Camera trapping is the most widely used data collection method for estimating snow leopard (Panthera uncia) abundance; however, the accuracy of this method is limited by human observer errors from misclassifying individuals in camera trap images. We evaluated the extent Whiskerbook (www.whiskerbook.org), an artificial intelligence (AI) software, could reduce this error rate and enhance the accuracy of capture-recapture abundance estimates. Using 439 images of 34 captive snow leopard individuals, classification was performed by five observers with prior experience in individual snow leopard ID (“experts”) and five observers with no such experience (“novices”). The “expert” observers classified 35 out of 34 snow leopard individuals, on average erroneously splitting one individual into two, thus resulting in a higher number than true individuals. The success rate of experts was 90 %, with less than a 3 % error in estimating the population size in capture-recapture modeling. However, the “novice” observers successfully matched 71 % of encounters, recognizing 25 out of 34 individuals, underestimating the population by 25 %. It was found that expert observers significantly outperformed novice observers, making statistically fewer errors (Mann Whitney U test P = 0.01) and finding the true number of individuals (P = 0.01). These differences were contrasted with a previous study by Johansson et al. 2020, using the same subset of 16 individuals from European zoos. With the help of AI and the Whiskerbook platform, “experts” were able to match 87 % of encounters and identify 15 out of 16 individuals, with modeled estimates of 16 ± 1 individuals. In contrast, “novices” were 63 % accurate in matching encounters and identified 12 out of 16 individuals, modeling 12 ± 1 individuals that underestimated the population size by 12 %. When comparing the performance of observers using AI and the Whiskerbook platform to observers performing the tasks manually, we found that observers using Whiskerbook made significantly fewer errors in splitting one individual into two (P = 0.04). However, there were also a significantly higher number of combination errors, where two individuals were combined into one (P = 0.01). Specifically, combination errors were found to be made by “novices” (P = 0.04). Although AI benefited both expert and novice observers, expert observers outperformed novices. Our results suggest that AI effectively reduced the misclassification of individual snow leopards in camera trap studies, improving abundance estimates. However, even with AI support, expert observers were needed to obtain the most accurate estimates.