The Himalayan region is a fragile high mountain landscape where the population experiences acute vulnerability within a complex coupled human–natural system due to environmental, social, and economic linkages. The lack of significant regional and spatial knowledge of multi-faceted vulnerabilities hinders any potential recommendations to address these vulnerabilities. We systematically reviewed the literature to recommend mitigation interventions based on the region’s socio-economic and ecological vulnerability research to date. We applied the PRISMA (Preferred Reporting of Items for Systematic Review and Meta-Analysis) criteria to search for results from four comprehensive databases. For our assessment, we compiled a final sample (n = 59) of vulnerability research papers to examine the vulnerability types, spatial variation, assessment methodology, and significant drivers of change. Our study represented all Himalayan countries, namely, India, Nepal, Pakistan, China, and Bhutan. More than half of the vulnerability studies were conducted in the central Himalayan region, a quarter in the western Himalayas, and a few in the eastern Himalayas. Our review revealed that the primary drivers of change were climate change, land use/land cover, and glacial lake formation. The vulnerability assessments in the Himalayan region primarily used social science methods as compared to natural science methods. While the vulnerability studies seldom assessed mitigation interventions, our analysis identified fourteen recommendations. The recommended interventions mainly included policy interventions, livelihood improvement, and adaptation measures. This study emphasized that sustainable development requires cross-sectoral interventions to manage existing resources and mitigate the confronting vulnerabilities of the region.

Trophy hunting and mass tourism are the two major interventions designed to provide various socioeconomic and ecological benefits at the local and regional levels. However, these interventions have raised some serious concerns that need to be addressed. This study was conducted in Khunjerab National Park (KNP) with an aim to analyze comparatively the socioeconomic and ecological impacts of trophy hunting and mass tourism over the last three decades within the context of sustainability. Focus Group Discussions (FGDs) with key stakeholders and household interviews were conducted to collect data on trophy hunting and mass tourism, and on local attitudes towards these two interventions in and around KNP. The results revealed that 170 Ibex (Capra sibirica) and 12 Blue sheep (Pseudois nayaur) were hunted in the study area over the past three decades, and trophy hunting was not based on a sustainable harvest level. Trophy hunting on average generated USD 16,272 annual revenue, which was invested in community development. However, trophy hunting has greatly changed the attitudes of local residents towards wildlife: a positive attitude towards the wild ungulates and strongly negative attitude towards wild carnivores. In addition, trophy hunting has reduced the availability of ungulate prey species for Snow leopards (Panthera uncia), and consequently, Snow leopards have increased their predation on domestic livestock. This has, in turn, increased human–snow leopard conflict, as negative attitudes towards carnivores result in retaliatory killing of Snow leopards. Furthermore, according to official record data, the number of tourists to KNP has increased tremendously by 10,437.8%, from 1382 in 1999 to 145,633 in 2018. Mass tourism on average generated USD 33,904 annually and provided opportunities for locals to earn high incomes, but it caused damages to the environment and ecosystem in KNP through pollution generation and negative impacts on wildlife. Considering the limited benefits and significant problems created by trophy hunting and mass tourism, we suggest trophy hunting should be stopped and mass tourism should be shifted to ecotourism in and around KNP. Ecotourism could mitigate human–Snow leopard conflicts and help conserve the fragile ecosystem, while generating enough revenue incentives for the community to protect biodiversity and compensate for livestock depredation losses to Snow leopards. Our results may have implications for management of trophy hunting and mass tourism in other similar regions that deserve further investigation.

This study explores the spatio-temporal distribution and trends on monthly, seasonal, and annual scales of rainfall in the central Punjab districts of Punjab province in Pakistan by using observation and satellite data products. The daily observed data was acquired from the Pakistan Metrological Department (PMD) between 1983 and 2020, along with one reanalysis, namely the Climate Hazard Infrared Group Precipitation Station (CHIRPS) and one satellite-based daily Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks climate data record (PERSIANN-CDR) using the Google Earth Engine (GEE) web-based API platform to investigate the spatio-temporal fluctuations and inter-annual variability of rainfall in the study domain. Several statistical indices were employed to check the data similarity between observed and remotely sensed data products and applied to each district. Moreover, non-parametric techniques, i.e., Mann–Kendall (MK) and Sen’s slope estimator were applied to measure the long-term spatio-temporal trends. Remotely sensed data products reveal 422.50 mm (CHIRPS) and 571.08 mm (PERSIANN-CDR) mean annual rainfall in central Punjab. Maximum mean rainfall was witnessed during the monsoon season (70.5%), followed by pre-monsoon (15.2%) and winter (10.2%). Monthly exploration divulges that maximum mean rainfall was noticed in July (26.5%), and the minimum was in November (0.84%). The district-wise rainfall estimation shows maximum rainfall in Sialkot (931.4 mm) and minimum in Pakpattan (289.2 mm). Phase-wise analysis of annual, seasonal, and monthly trends demonstrated a sharp decreasing trend in Phase-1, averaging 3.4 mm/decade and an increasing tendency in Phase-2, averaging 9.1 mm/decade. Maximum seasonal rainfall decreased in phase-1 and increased Phase-2 during monsoon season, averaging 2.1 and 4.7 mm/decade, whereas monthly investigation showed similar phase-wise tendencies in July (1.1 mm/decade) and August (2.3 mm/decade). In addition, as district-wise analyses of annual, seasonal, and monthly trends in the last four decades reveal, the maximum declined trend was in Sialkot (18.5 mm/decade), whereas other districts witnessed an overall increasing trend throughout the years. Out of them, Gujrat district experienced the maximum increasing trend in annual terns (50.81 mm/decade), and Faisalabad (25.45 mm/decade) witnessed this during the monsoon season. The uneven variability and trends have had a crucial imprint on the local environment, mainly in the primary activities.

The snow leopard (Panthera uncia) is a cryptic and rare big cat inhabiting Asia’s remote and harsh elevated areas. Its population has decreased across the globe for various reasons, including human–snow leopard conflicts (HSCs). Understanding the snow leopard’s distribution range and habitat interactions with human/livestock is essential for understanding the ecological context in which HSCs occur and thus gives insights into how to mitigate HSCs. In this study, a MaxEnt model predicted the snow leopard’s potential distribution and analyzed the land use/cover to determine the habitat interactions of snow leopards with human/livestock in Karakoram–Pamir, northern Pakistan. The results indicated an excellent model performance for predicting the species’ potential distribution. The variables with higher contributions to the model were the mean diurnal temperature range (51.7%), annual temperature range (18.5%), aspect (14.2%), and land cover (6.9%). The model predicted approximately 10% of the study area as a highly suitable habitat for snow leopards. Appropriate areas included those at an altitude ranging from 2721 to 4825 m, with a mean elevation of 3796.9 ± 432 m, overlapping between suitable snow leopard habitats and human presence. The human encroachment (human settlements and agriculture) in suitable snow leopard habitat increased by 115% between 2008 and 2018. Increasing encroachment and a clear overlap between snow leopard suitable habitat and human activities, signs of growing competition between wildlife and human/livestock for limited rangeland resources, may have contributed to increasing HSCs. A sound land use plan is needed to minimize overlaps between suitable snow leopard habitat and human presence to mitigate HSCs in the long run.

The high-altitude region of Asia is prone to natural resource degradation caused by a variety of natural and anthropogenic factors that also threaten the habitat of critical top predator species, the snow leopard (Panthera uncia). The snow leopard’s landscape encompasses parts of the twelve Asian countries and is dominated by pastoral societies within arid mountainous terrain. However, no investigation has assessed the vulnerability and pathways towards long-term sustainability on the global snow leopard landscape scale. Thus, the current study reviewed 123 peer-reviewed scientific publications on the existing knowledge, identified gaps, and proposed sustainable mitigation options for the longer term and on larger landscape levels in the range countries. The natural resource degradation in this region is caused by various social, economic, and ecological threats that negatively affect its biodiversity. The factors that make the snow leopard landscapes vulnerable include habitat fragmentation through border fencing, trade corridor infrastructure, non-uniform conservation policies, human–snow leopard conflict, the increasing human population, climatic change, land use and cover changes, and unsustainable tourism. Thus, conservation of the integrated Socio-Ecological System (SES) prevailing in this region requires a multi-pronged approach. This paper proposes solutions and identifies the pathways through which to implement these solutions. The prerequisite to implementing such solutions is the adoption of cross-border collaboration (regional cooperation), the creation of peace parks, readiness to integrate transnational and cross-sectoral conservation policies, a focus on improving livestock management practices, a preparedness to control human population growth, a readiness to mitigate climate change, initiating transboundary landscape-level habitat conservation, adopting environment-friendly trade corridors, and promoting sustainable tourism. Sustainable development in this region encompasses the political, social, economic, and ecological landscapes across the borders.