Understanding human-tiger conflict risk in the Eastern Terai Arc Landscape
Project Title
Understanding human-tiger conflict risk in the Eastern Terai Arc Landscape
Project Location
Eastern Terai Arc Landscape
Project Client
WWF Nepal, Baluwatar, Kathmandu
Completion Date
Feb 2025
This study, commissioned by WWF Nepal and conducted in the Eastern Terai Arc Landscape, assessed community-level vulnerabilities and drivers of human-tiger conflict (HTC) outside protected areas using mixed social and spatial methods. The findings aim to generate evidence-based insights to support adaptive management strategies that mitigate HTC risks and promote human–tiger coexistence through context-specific conservation interventions.
WWF is the world’s leading independent conservation organization originated in Switzerland in 1961, initiated work in Nepal with a rhino conservation program in Chitwan in 1967 while the WWF Nepal set up its office formally on 19 May 1993. Currently, WWF Nepal works in five thematic areas- Wildlife, Freshwater, Forests. Climate and Energy and Governance. Human-wildlife conflict has been a major area of work for WWF Nepal. In general, the interaction between humans and wild animals has had a negative impact on people, their resources, and to wild species, which is understood as human-wildlife conflict (HWC). Terai arc landscape (TAL) is a highly prioritized landscape that stretches from Bagmati river in the east of Nepal to Yamuna River in the west of India and connects 16 protected areas of both countries. It is a globally significant area that hosts a number of endangered species, especially Bengal tiger. WWF Nepal contracted with Niyatra Consult Pvt. Ltd. to generate evidence that supports adaptive management practices, ensuring that conservation interventions are both context-specific and effective in mitigating human-tiger conflict while promoting coexistence.
The main objective of the assessment was to find out the risks and vulnerability and its drivers perceived by residents about human-tiger conflict in settlements located outside protected areas. The study was conducted in four districts of Eastern Tarai Arc Landscape (TAL) namely Makawanpur, Bara, Parsa and Rautahat. The primary methods used for the survey were questionnaire surveys of ~800 households which has been selected by using stratified sampling.
The increasing number of tigers in protected areas is raising concerns about rising human–tiger conflict (HTC) in surrounding regions. This conflict is primarily driven by local dependence on forest resources such as livestock grazing, fodder, fuelwood, and fishing. To assess perceived HTC risks and inform mitigation strategies, the study combined social and geo-spatial methods, surveying 792 respondents—mostly male and Hill Janajati—with low education levels and a reliance on agriculture and livestock.
Structural Equation Modeling (SEM) was used to examine relationships among latent socio-psychological constructs, with interaction modeled using principal component analysis (PCA) and polychoric correlations. Vulnerability was assessed through the formula: Vulnerability = Exposure + Sensitivity – Adaptive Capacity. ANOVA and spatial methods (dbMEM and RDA) accounted for spatial autocorrelation.
Findings revealed widespread livestock vulnerability due to poorly protected sheds and extensive grazing. Forest use was mostly livestock-related, while NTFP and fishing activities were limited. Though only 6% had directly encountered tigers, and 20% saw signs, risk perception was high—especially regarding livestock and human safety. Despite generally positive beliefs about tigers, 75% supported tiger removal, while 68% favored HTC mitigation. However, only 38% believed long-term adaptation was feasible, and 75% reported inadequate risk communication.
SEM results showed strong measurement reliability. Cognitive risk and risk communication positively influenced support for future tiger populations, while apparent risk negatively influenced cognitive risk but positively impacted beliefs. The SEM model showed an acceptable fit (CFI = 0.88, TLI = 0.86, RMSEA = 0.109). RDA confirmed district-level spatial variation, while ANOVA revealed significant links between vulnerability and livestock ownership.
The main objective of the assessment was to find out the risks and vulnerability and its drivers perceived by residents about human-tiger conflict in settlements located outside protected areas. The study was conducted in four districts of Eastern Tarai Arc Landscape (TAL) namely Makawanpur, Bara, Parsa and Rautahat. The primary methods used for the survey were questionnaire surveys of ~800 households which has been selected by using stratified sampling.
The increasing number of tigers in protected areas is raising concerns about rising human–tiger conflict (HTC) in surrounding regions. This conflict is primarily driven by local dependence on forest resources such as livestock grazing, fodder, fuelwood, and fishing. To assess perceived HTC risks and inform mitigation strategies, the study combined social and geo-spatial methods, surveying 792 respondents—mostly male and Hill Janajati—with low education levels and a reliance on agriculture and livestock.
Structural Equation Modeling (SEM) was used to examine relationships among latent socio-psychological constructs, with interaction modeled using principal component analysis (PCA) and polychoric correlations. Vulnerability was assessed through the formula: Vulnerability = Exposure + Sensitivity – Adaptive Capacity. ANOVA and spatial methods (dbMEM and RDA) accounted for spatial autocorrelation.
Findings revealed widespread livestock vulnerability due to poorly protected sheds and extensive grazing. Forest use was mostly livestock-related, while NTFP and fishing activities were limited. Though only 6% had directly encountered tigers, and 20% saw signs, risk perception was high—especially regarding livestock and human safety. Despite generally positive beliefs about tigers, 75% supported tiger removal, while 68% favored HTC mitigation. However, only 38% believed long-term adaptation was feasible, and 75% reported inadequate risk communication.
SEM results showed strong measurement reliability. Cognitive risk and risk communication positively influenced support for future tiger populations, while apparent risk negatively influenced cognitive risk but positively impacted beliefs. The SEM model showed an acceptable fit (CFI = 0.88, TLI = 0.86, RMSEA = 0.109). RDA confirmed district-level spatial variation, while ANOVA revealed significant links between vulnerability and livestock ownership.
key Achivements
Robust Evidence Generation for Adaptive Conservation:
Collected high-quality primary data from 792 households across four HTC-prone districts using stratified sampling, enabling comprehensive analysis of perceived risks and vulnerabilities.
Advanced Analytical Techniques:
Utilized Structural Equation Modeling (SEM), Principal Component Analysis (PCA), ANOVA, and spatial methods (dbMEM, RDA) to understand complex socio-psychological and spatial relationships influencing conflict perception.
Clear Identification of Conflict Drivers:
Identified livestock grazing and inadequate shed protection as major contributors to HTC vulnerability, along with limited adaptive capacity and risk communication.
Policy-Relevant Insights:
Revealed that although only a small fraction directly encountered tigers, over 75% of respondents favored tiger removal due to high perceived risk—highlighting the need for targeted communication and mitigation programs.
Community Perception and Adaptive Capacity Mapping:
Mapped spatial variations in vulnerability and perception across districts, offering WWF Nepal actionable data to design location-specific interventions.
Quantified Impact of Risk Communication:
Found that better cognitive risk understanding and communication positively influence public support for long-term tiger conservation despite prevailing fears.
Collected high-quality primary data from 792 households across four HTC-prone districts using stratified sampling, enabling comprehensive analysis of perceived risks and vulnerabilities.
Advanced Analytical Techniques:
Utilized Structural Equation Modeling (SEM), Principal Component Analysis (PCA), ANOVA, and spatial methods (dbMEM, RDA) to understand complex socio-psychological and spatial relationships influencing conflict perception.
Clear Identification of Conflict Drivers:
Identified livestock grazing and inadequate shed protection as major contributors to HTC vulnerability, along with limited adaptive capacity and risk communication.
Policy-Relevant Insights:
Revealed that although only a small fraction directly encountered tigers, over 75% of respondents favored tiger removal due to high perceived risk—highlighting the need for targeted communication and mitigation programs.
Community Perception and Adaptive Capacity Mapping:
Mapped spatial variations in vulnerability and perception across districts, offering WWF Nepal actionable data to design location-specific interventions.
Quantified Impact of Risk Communication:
Found that better cognitive risk understanding and communication positively influence public support for long-term tiger conservation despite prevailing fears.
