The negative impact of large carnivore presence in human‐dominated landscapes manifests as livestock depredation and in extreme cases as attacks on humans. In the case of conflict with leopards in Nepal, attacks resulting in human fatality have become more frequent over time, thus creating an urgent socio‐ecological and management issue. We estimated the occurrence of leopard attacks in Nepal from human‐leopard conflict cases reported in the media. We used occupancy models to analyse data collected from online news reports on incidents of leopard attacks on humans to explore drivers of leopard attacks on a landscape scale. Our results suggest that the probability of occurrence of leopard attack is associated with human population density, terrain ruggedness and livestock density. The human population density effect may be indicative of a density‐dependent relationship, where attacks are more likely in areas where an increased abundance of humans increases encounter rates with leopards. The positive effect of livestock density suggests that livestock may be drawing leopards into human settlements, and consequently increasing the likelihood of attacks on humans. Terrain ruggedness might be offering ideal conditions to facilitate attacks on humans, for example remoteness and high amounts of cover to launch ambush attacks. We provide inference and insights into key determinants of leopard attacks on humans on a landscape scale. These insights can be used to guide future research, inform mitigation measures to reduce leopard attacks and foster a better understanding of the interaction between people and leopards. This study demonstrates the applicability and novelty of using a hierarchical modelling framework applied to freely and publicly available media reports to inform the applied management of human‐wildlife conflict at a national scale. Read the free Plain Language Summary for this article on the Journal blog.

Nepal is highly vulnerable to climate change with increased fire occurrences and fire burned areas in recent years; therefore, we accessed the climatic drivers for its variability using fire burned areas product of Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 and 2020. The peak fire burned areas were observed in the spring season (~91%) from March to May, especially higher in the lowlands of the western and central parts. At the interannual timescale, low precipitation, humidity, soil moisture, and high temperature supported the existence of spring fire. Combining these factors induces drought conditions, enhancing evapotranspiration from vegetation and providing more combustible fuels. Furthermore, the El Niño phase in the central‐eastern Pacific Ocean is related to the weakened westerly moisture transport and moisture divergence that creates dry and warm conditions leading to increased fire activities. Thus, this study could be helpful for preparedness, management, and policy‐making to limit the multi‐dimensional losses in the ecosystem and society due to fire.

Swamp Deer is a globally threatened large-sized deer species confined within small patches of the Indian subcontinent. Historically, Swamp Deer occurred in Chitwan National Park, Nepal but was extirpated in the 1960s primarily due to widespread hunting. We assessed the habitat suitability at present for the Swamp Deer in Chitwan National Park using multi-criteria analysis in GIS and vegetation assessment using frequency, dominance, and cover. Within the 952.63km2 area of the national park, the habitat suitability analysis identified 14.57km2 as highly suitable, 134.87km2 as suitable, and 803.19km2 as moderate to least suitable area. Most of the national park’s grassland is suitable for Swamp Deer. Grassland is dominated by Saccharum spp.; Imperata cylindrica is the most widely distributed grass species followed by Saccharum spp., Narenga porphyrocoma, and Apluda mutica. Grass species of the Poaceae family are the most preferred species by Swamp Deer, which are found within short grasslands. The study revealed that Padampur Phanta could be the most suitable site for the reintroduction of Swamp Deer due to its highest proportion of short grass and availability of preferred food species and good habitat in comparison to other blocks. Invasion of swamps of Chitwan by Mikania micrantha and Eichornia crassipes could be a limiting factor for the habitat suitability of Swamp Deer.

The development of the tertiary industry is of great significance for promoting industrial structure, optimizing and upgrading it, and achieving regional energy conservation and emission reduction goals. This study adopts a quantitative method to analyze the spatio-temporal pattern of carbon emissions from China’s tertiary industry from 2004 to 2019. In order to analyze emissions from aspects such as energy structure, energy intensity, energy carrying capacity, industrial structure, level of industrial development, income level, consumption capacity, energy consumption intensity, and population size, this study establishes a hybrid factor decomposition model called the “energy-industry-consumption” research framework. The study shows that carbon emissions from China’s tertiary industry have been increasing year by year from 2004 to 2019, with a growth rate of 353.10%. Transportation is the largest contributor to the increase in carbon emissions from China’s tertiary industry. The carbon emissions from the tertiary industry in each province show four types: high-speed growth, low-speed growth, fluctuating growth, and stable growth. During the study period, carbon emissions produce a spatial heterogeneity with the highest emissions in the south and lowest in the northwestern part of China. The spatial pattern of per capita carbon emissions is not significant. Guangdong has the highest carbon emissions, and Shanghai and Beijing have higher per capita carbon emissions. Industrial factors and consumption factors have a positive effect on carbon emissions in China’s tertiary industry, while energy factors have a negative effect. The leading factor of carbon emissions in China’s tertiary industry has gradually shifted from energy to industry.