1. Effective management of charismatic large carnivores requires robust monitoring of their population at local, regional and global scales. While enormous progress has been made to estimate carnivore populations at local scales, estimates at regional and global scales remain elusive. In the first systematic effort at a large regional scale, we estimated the population of the elusive snow leopard Panthera uncia over an area of 26,112 km 2 in the Indian state of Himachal Pradesh.2. We stratified the entire snow leopard habitat in Himachal Pradesh based on an occupancy survey. Subsequently, we conducted camera trapping surveys at 10 sites distributed proportionately, that is with similar coverage probability across the three strata. We conducted simulations to understand how unidentified captures could affect our model estimate. We also assessed populations of the primary wild ungulate prey of snow leopards -blue sheep Pseudois nayaur and Siberian ibex Capra sibirica.3. Our results yielded a mean estimated density of 0.19 (95% confidence interval [CI]: 0.12-0.31) snow leopards per 100 km 2 and population size of 51 (95% CI: 34-73) snow leopards in Himachal Pradesh. The density estimates for individual sites ranged from 0.08 to 0.37 snow leopards per 100 km 2 . Simulations showed that unidentified snow leopard captures did not seem to affect the accuracy of our model estimate but could have affected the precision. Wild ungulate prey density ranged from 0.11 to 1.09 per km 2 . Snow leopard density showed a positive linear relationship with prey density (slope = 0.25, SE = 0.08, P = 0.01, R 2 = 0.51).4. Our study shows the earlier opinion-based estimate for Himachal Pradesh to have been significantly positively biased. Using occupancy surveys to stratify large areas in order to design camera trap surveys addresses one of the common spatial sampling biases, that is limited sampling of only prime snow leopardThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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We describe a pilot community-based conservation initiative for wolves Canis lupus that involves (i) voluntary deactivation of traditional trapping pits called Shandong, (ii) commitment to wildlife conservation by the local community, and (iii) collaborative construction and consecration of a Stupa (Buddhist shrine) in the vicinity of the Shandong as a symbol of conservation and repentance for past hunting. People and wolves have a complex relationship, in part shaped by predation on livestock, which can have severe impacts on livelihoods in pastoral societies. Consequently, wolf conservation often evokes strong and polarizing reactions. To control wolf populations, livestock herders across the Trans- Himalayan and Tibetan regions use different types of traps. Shandong is a relatively large, widely used traditional trapping pit with inverted funnel-shaped stone walls, usually built near villages or herder camps. Typically, a live domestic animal is placed in the pit to attract the wolves. Once the wolves jump into the pit, the funnel shaped walls prevent them from escaping, and trapped wolves are usually stoned to death. In an extensive survey covering over 25,000 sq. km, we enumerated 94 Shandong in 58 of the 64 surveyed villages in Ladakh between June 2019 and March 2020. Thirty of these had been used to kill wolves within the past 10 years, while 7 had been destroyed. Shandong that were not in use were of poorer condition. Since 2017, we have worked with community members, local monks, and the region’s religious leaders to support the neutralization of the Shandong while preserving their structure, and assisted the communities to build Stupas and to consecrate them. Our pilot efforts with three communities appear to generate pride locally, and hold promise for promoting wolf conservation in Ladakh and in large parts of Trans-Himalayan and Tibetan regions that share similar cultural settings.

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When a strong selection pressure, such as predation risk, varies widely in space and time, how should prey respond? When risk varies predictably, prey are hypothesized to respond in a risksensitive manner. It is less clear how prey should respond when risk varies unpredictably.Additionally, prey response may also depend on how predation risk interacts with other selection pressures. Our understanding of the complex action of multiple and variable selection pressures on prey traits is still comparatively poor. Here, we examine how predictable and unpredictable aspects of predation risk act together with another important selection pressure to influence prey behaviour in the rock pool breeding mosquito, Aedes vexans. Through the selection of sites for oviposition, female mosquitoes can influence the predation risk faced by their offspring. We tested how females select oviposition sites, when encountering pools that vary in larval predation risk and desiccation risk. We comprehensively quantified spatial and temporal variation in predation risk by measuring densities of predatory dragonfly nymphs in rock pools of different sizes, along the mosquito breeding season. We also measured hydroperiod length. We next conducted manipulative experiments in rock pools and measured female oviposition responses to variation in predation and desiccation risks. Predation risk varied widely in space and time. Desiccation risk only appeared important for the small pools. Ovipositing females appeared to respond to these multiple aspects of variation in selection pressures. Females seemed to respond to predictable variation by avoiding large pools that permanently harboured predators in natural settings. Female responses were more variable to medium-sized pools with naturally stochastic predator densities, highlighting the role of unpredictability in predation risk in shaping behaviour. Females did not clearly prefer small pools that were naturally devoid of predators but carried high desiccation risk, suggesting that they balance multiple risks -predation versus desiccation -when choosing oviposition sites. Our study suggests that wild populations may commonly experience multiple and variable selection pressures that can favour seemingly puzzling trait variation. We highlight the need to quantify variation in selection pressures and investigate how such variation, especially the unpredictable aspects, shapes 2 4 6

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Amidst Bollywood’s romanticized landscapes and grandeur settings, depiction of the flora and fauna, roaring rivers and drought prone lands, is difficult to locate. But the new millennium has witnessed some new generation filmmakers, sensitized towards the ecological concerns, thus marking a shift from the illustration of idealised landscapes to the representation of nature’s wrath. Since, cinema in India, has a deep-rooted impact on the masses, these creators employ films as tools to sensitize the population towards the climate change threat which though as perilous as the COVID-19 crisis, is often ignored by a significant amount of population. Dawning upon themselves the responsibility of environmental awakening, Nila Madhab Panda and Abhishek Kapoor highlight in their movies, Kadvi Hawa(2017) and Kedarnath(2018), respectively, the horrors of human callousness, leading to drastic change in Climatic condition in India. Panda’s Kadavi Hawa, dealing with non-repayment of loans followed by suicides, portrays the heart-wrenching imagery of environmental degradation and Climate change that has rendered the Village of Mahua, arid and infertile. Kapoor’s Kedarnath on the other hand, appeals for action through horrifying imagery of the catastrophic floods that disrupted the holy town of Kedarnath, in 2013. Through a detailed analysis of the aforementioned visual portrayals, this article aims to emphasise as to how Films can play an important role in effectively addressing dealing with the issues related to Climate. Further, the rationale of this paper is to underscore the possibility of more such storylines, as a tool towards effective engagement and levitation of conscience.