Temporal Analysis Using GIS and Remote Sensing for Adaptive Forest Resource Management: A Human-Tiger Conflict Case Study from Nagarahole Tiger Reserve

Background: India supports ~70% of the world’s wild tigers, underscoring its conservation significance. Human-Tiger conflict, manifested through livestock depredation and retaliatory killings, is driven by habitat encroachment and inadequate livestock protection. Such conflicts impose severe economic costs on forest-adjacent communities and erode support for conservation. Aim: This study investigates the temporal patterns of human-tiger conflict in Nagarahole Tiger Reserve (NTR), India (2019–2023), focusing on allocation of forest department resources to reduce conflict with informed targeted mitigation strategies. Study Design: Longitudinal Observational Study. Place and Duration of Study: NTR, Karnataka India; 5 years (2019–2023). Methodology: We analyzed 210 verified livestock predation incidents using Geographic Information System (GIS) mapping and conducted household surveys across 57 buffer-zone villages. Results: Geospatial analysis identified Anechowkur (40.95% of incidents) and Veeranahosalli (16.67%) as primary conflict epicentres, with secondary clustering in Hunsur (11.43%) collectively representing 69.05% of all livestock predation events. Temporal analysis revealed peak conflict in January–March (76 incidents) and September (34 incidents), with lowest rates during monsoon (June: 9 incidents). It was also observed that temporal data-guided forest staff/resource deployment in Anechowkur and Veeranahosalli yielded a reduction in livestock predation during high-risk months (January to March) in 2022 and 2023. Conclusion: Livestock predation is driven by proximity to reserve edges, seasonal prey scarcity, and inadequate protection. The northwestern sector requires urgent interventions due to perennial hotspot status. Mitigation must prioritize: (1) temporally-targeted patrols during high-risk months January–March/September and (2) subsidized predator-proof enclosures, which could reduce conflicts.

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Publication Details

Journal
Asian Journal of Education and Social Studies
Published
2025-09-01
DOI
https://doi.org/10.9734/ajess/2025/v51i92404
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Temporal Analysis Using GIS and Remote Sensing for Adaptive Forest Resource Management: A Human-Tiger Conflict Case Study from Nagarahole Tiger Reserve

Vijaya Kumara, P.S.C. Sri Harsha
Asian Journal of Education and Social Studies
Remote Sensing in Agriculture
article

Temporal Analysis Using GIS and Remote Sensing for Adaptive Forest Resource Management: A Human-Tiger Conflict Case Study from Nagarahole Tiger Reserve

Vijaya Kumara, P.S.C. Sri Harsha
article en

Abstract

Background: India supports ~70% of the world’s wild tigers, underscoring its conservation significance. Human-Tiger conflict, manifested through livestock depredation and retaliatory killings, is driven by habitat encroachment and inadequate livestock protection. Such conflicts impose severe economic costs on forest-adjacent communities and erode support for conservation. Aim: This study investigates the temporal patterns of human-tiger conflict in Nagarahole Tiger Reserve (NTR), India (2019–2023), focusing on allocation of forest department resources to reduce conflict with informed targeted mitigation strategies. Study Design: Longitudinal Observational Study. Place and Duration of Study: NTR, Karnataka India; 5 years (2019–2023). Methodology: We analyzed 210 verified livestock predation incidents using Geographic Information System (GIS) mapping and conducted household surveys across 57 buffer-zone villages. Results: Geospatial analysis identified Anechowkur (40.95% of incidents) and Veeranahosalli (16.67%) as primary conflict epicentres, with secondary clustering in Hunsur (11.43%) collectively representing 69.05% of all livestock predation events. Temporal analysis revealed peak conflict in January–March (76 incidents) and September (34 incidents), with lowest rates during monsoon (June: 9 incidents). It was also observed that temporal data-guided forest staff/resource deployment in Anechowkur and Veeranahosalli yielded a reduction in livestock predation during high-risk months (January to March) in 2022 and 2023. Conclusion: Livestock predation is driven by proximity to reserve edges, seasonal prey scarcity, and inadequate protection. The northwestern sector requires urgent interventions due to perennial hotspot status. Mitigation must prioritize: (1) temporally-targeted patrols during high-risk months January–March/September and (2) subsidized predator-proof enclosures, which could reduce conflicts.

Asian Journal of Education and Social StudiesVol. 51(9)
Openalex Percentile: Top 77%
Remote Sensing in Agriculture
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