ArticleScientific reports2020
Landscape predictors of human-leopard conflicts within multi-use areas of the Himalayan region.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- A global review of Livestock Guardian Donkeys (LGDks) in the prevention of carnivore depredation.PeerJ · 2026Review
- Claws in the Capital: Human-Leopard Conflict Hotspots and Community Perceptions in Kathmandu Valley, Nepal.Ecology and evolution · 2025Article
- Assessing the implications of habitat transformations on human-large carnivore interactions outside protected areas.Scientific reports · 2025Article
- Evaluation of the social-economic impacts of hyena attacks on humans and livestock in the Nyang'whale district of Tanzania.BMC ecology and evolution · 2024Article
- Article
- Article
- Article
- Potential risk zone for anthropogenic mortality of carnivores in Gandaki Province, Nepal.Ecology and evolution · 2022Article
- Tracking forest loss and fragmentation between 1930 and 2020 in Asian elephant (Elephas maximus) range in Nepal.Scientific reports · 2021Article
- Movement behavior of a solitary large carnivore within a hotspot of human-wildlife conflicts in India.Scientific reports · 2021Article
- Characterization and management of human-wildlife conflicts in mid-hills outside protected areas of Gandaki province, Nepal.PloS one · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Conflict with humans is a significant source of mortality for large carnivores globally. With rapid loss of forest cover and anthropogenic impacts on their habitats, large carnivores are forced to occupy multi-use landscapes outside protected areas. We investigated 857 attacks on livestock in eastern Himalaya and 375 attacks in western Himalaya by leopards between 2015 and 2018. Multivariate analyses were conducted to identify the landscape features which increased the probability of livestock depredation by leopards. The risk of a leopard killing livestock increased within a heterogeneous landscape matrix comprising of both closed and open habitats (very dense forests, moderate dense forests, open forests, scrubland and non-forests). We used the results to map potential human-leopard conflict hotspots across parts of the Indian Himalayan region. Our spatial risk maps indicate pockets in the eastern, central and western part of eastern Himalaya and the central, northern part of western Himalaya as hotspots of human-leopard conflicts. Most of the attacks occurred when livestock were grazing freely within multi-use areas without supervision of a herder. Our results suggest that awareness about high risk areas, supervised grazing, and removing vegetation cover around human settlements should be initiated to reduce predation by leopards.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.