Wildlife attacks on humans pose a critical challenge to wildlife conservation. Comprehensive information about the conflict cases can be vital for effective wildlife management and conservation. In this study, we assessed the temporal and spatial patterns of wildlife attacks on humans in Chitwan National Park between January 2009 to December 2020 by using the annual reports published by the park. Our analysis revealed that out of the nine-wildlife species involved in conflicts, rhinos, elephants, tigers, sloth bears, and wild boars had significantly higher involvement in conflicts with humans. The findings showed that an average of 42 annual attacks and 10 human fatalities cases were reported annually. Of these species, rhinos exhibited the most frequent involvement in conflicts (38%), while elephants were found to be the most lethal species, causing an average of 3.75 human fatalities per year. The trend line indicated a marginal increase in wildlife attacks on humans by 3.97 per year (adjusted R2=0.36). Our study further revealed that wildlife attacks were mostly concentrated in the winter season (χ2=1.088, df=3, p<0.05), with elephant, rhino, and tiger attacks predominantly occurring in the proximity of human settlements. To evaluate the risk factors of human deaths due to wildlife attacks, we utilized logistic regression analysis and found elephant attacks were associated with the highest probability of causing human fatalities (odd ratio=15.2, p<0.05), followed by tiger attacks (odd ratio=8.41, p<0.05). The study revealed an increasing trend in attacks, predominantly occurring in winter and near human settlements. Elephants and tigers are identified as the highest risk factors for human fatalities. Understanding these patterns is crucial for effective wildlife management and conservation efforts.

Groundwater is the fundamental component of the hydrological system that acts as a major factor in comprehensions of the physical processes in both the land surface and the atmosphere. Determining groundwater, which directly affects the agricultural productivity of semi-arid mountainous regions, is crucial. Mountain ecosystems, once abundant with flowing water, now face immense pressure from a changing climate, evident in the drying of springs and the diminishing flow of groundwater. Ensuring a steady flow of water, fair access to it, and responsible use are the cornerstones of a secure future for mountain communities. This study aims to assess the groundwater potential zones using remote sensing and a geospatial approach in the Mustang Valley's rural municipalities (Thasang and Gharapjhong). Nine factors were assigned to assess the groundwater potential map: slope, drainage density, lineament density, geology, soil, land use/land cover, rainfall, aspect, and soil moisture. The Bayesian weights of evidence model was used to delineate the groundwater potential zone. The study categorized groundwater potential across the region, creating five zones: very high, high, moderate, low, and very low. These zones covered 0.6 %, 12.4 %, 51.2 %, 35.5 %, and 0.3 % of the study area. The accuracy of the groundwater potential map was assessed by comparing its predictions with the actual locations of springs, using the area under the curve metric. The receiver operating characteristics curve analysis yielded an area under the curve of 0.7226, indicating a 72.26 % accuracy in predicting the presence of groundwater. The findings of this paper contribute to a better understanding of groundwater potential zones, which can support policymakers and planners for hydrological, meteorological, and crop planning applications in this climatically vulnerable region.

Soil moisture refers to the water amount present in the soil, which is a critical factor influencing plant growth, nutrient cycling, and groundwater recharge. Accurate information on soil moisture-level is crucial for water resource management, agriculture, land degradation, and ecosystem health assessment in semi-arid mountainous regions. Therefore, this study aims to assess average soil moisture under different land managements of the two rural municipalities (Thasang and Gharapjhong) of the Mustang Valley using remote sensing and a geospatial approach. Sentinel-1 and Sentinel-2 data were processed in Google Earth Engine to derive soil moisture using the modified Dubois and Topp's models. The key findings demonstrated that the spatial distribution of soil moisture ranged from 0.01 to 0.4 m3/m3 with cropland exhibiting the highest values (0.36 m3/m3). The correlation of the average soil moisture with the rainfall showed a strong positive correlation with the coefficient of determination (R2) of 0.94. The findings of this paper contributes for a better understanding of soil moisture dynamics of different land cover types of this study region. Further, research on the modeling of soil moisture based on in-situ field data and other influencing factors is recommended.

The community forestry program of Nepal is one of the leading forest management approaches in the world. Despite several success stories, this program has been criticized for its passiveness or protection-oriented management approach. Though several recommendations from previous researchers have been made to shift the management approach towards active forest management, few studies have been conducted to identify the measurable indicators of it. Therefore, this study aimed to identify measurable indicators of degree of active community forest management using the renowned Delphi survey techniques. The survey consulted ten experts with a minimum of twenty years of direct experience in community forestry projects, either in implementation, research, or policy development, were participated to identify themes, indicators, and verifiers of active community forest management. The study revealed seven themes, thirty indicators, and ninety verifiers for considering the community forest to be managed actively. These seven themes include objectives and management practices, forest health and ecosystem, participation and governance, policy and legal framework, institutional capacity, forest goods and services, and climate change. Among these themes, clarifying management objectives was found to be the major step, followed by the production of forest goods and services. The findings of this study offer a robust framework for assessing the activeness of community forest management and assessing the performance of community forest user groups to identify areas for improvement. Similarly, policymakers and practitioners can utilize these indicators to develop effective monitoring tools and design capacity-building initiatives that directly address key elements of active community forest management for improved outcomes. Further, research exploring the framework's strengths and weaknesses through empirical validation in different settings and under changing socio-economic, policy, and environmental conditions is recommended.