Evidence map›Paper›PMID 42186474›Full record

ArticlePeerJ2026

Landscape determinants of human-elephant conflict in Assam, India: insights from two decades of spatial analysis.

Athira N G, Ramesh Kumar Pandey, Kalpana Roy, Ananya Dutta, Dheeraj Mittal, Parag Nigam, Anukul Nath, Bilal Habib

Abstract read
In one paragraph

Article in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Athira N G *Wildlife Institute of India, Dehradun, Uttarakhand, India.
Ramesh Kumar Pandey *Wildlife Institute of India, Dehradun, Uttarakhand, India.
Kalpana RoyWildlife Institute of India, Dehradun, Uttarakhand, India.
Ananya DuttaWildlife Institute of India, Dehradun, Uttarakhand, India.
Dheeraj MittalMinistry of Envioronment Forest and Climate Change, Delhi, India.
Parag NigamWildlife Institute of India, Dehradun, Uttarakhand, India.
Anukul NathWildlife Institute of India, Dehradun, Uttarakhand, India.
Bilal HabibWildlife Institute of India, Dehradun, Uttarakhand, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human-elephant conflict (HEC) presents an escalating conservation and socio-economic challenge across Assam, India, where a dense human population overlaps with critical elephant habitats. This study investigates human mortality patterns linked to HEC over 23 years (2000-2023), analysing 1,806 incidents, including 1,468 human fatalities and 337 human injuries. The data for this study were collected from 21 forest divisions of Assam and included detailed information (with gender specific details). Using spatial analyses, kernel density mapping, and generalised linear modelling (GLMs), this study identified key ecological and anthropogenic drivers of conflict. Conflict hotspots were predominantly located near fragmented forests, elephant reserves, and agricultural landscapes adjoining forests, with more incidents occurring during the monsoon and post-harvest seasons. Villages with limited or reduced forest connectivity and expanding built-up areas exhibited higher conflict intensity. Fragmentation metrics such as the Largest Patch Index and the Edge Density of the forest were significantly associated with the probability of HEC occurrence. Our findings highlight the importance of integrating ecological restoration, seasonal risk forecasting, and community-driven mitigation strategies such as buffer cropping and early warning systems. This study provides critical insights for prioritising high-risk areas and proposes practical interventions to promote coexistence between humans and elephants in a rapidly transforming landscape.

Indexed as

Conservation of Natural ResourcesElephantsAgricultureAnimalsEcosystemFemaleForestsHumansIndiaMaleSeasonsSpatial AnalysisAsian elephantCorridorElectrocutionFragmentationTea gardensVillage level prioritisation

Identifiers

PMID42186474
PMCPMC13198851

What OpenQuestion holds

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LicenceCC BY
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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.