Predictive Modelling of Human - Elephant Conflicts in Shimba Hills Ecosystem
Abstract
Human-elephant conflict (HEC) is a key example of the growing competition between people and wildlife for space and resources in Kenya. To effectively implement mitigation measures, understanding of the underlying factors that determine HEC is required. This study mapped the conflict prone areas in Shimba Hills (SH) Ecosystem. The study used questionnaires, group discussions and available Shimba Hills National Reserve (SHNR) conflict records to gather information on the nature, type and conflict locations (presence data). GIS-based stepwise logistic regression were used to analyze the relationship between the conflict areas and the selected habitat factors including distance to roads, distances to fenced and unfenced areas, distance to water, distance to settlements, slope, elevation and the land cover types. Binary logistic regression was used to determine the presence data of conflict sites and absence data (non-conflict sites). Random points were generated in the study area to represent absence data of conflicts. Results showed that distances to water (β= -0.0012, P=0.000), fence (β= -0.0006, P=0.000), roads (β=0.0005, P=0.016) and settlements (β=0.0002, P=0.037) were significant determinants of HEC. Areas near water, near fence, away from road and settlements were prone to conflicts. The four significant variables were used to generate conflict prone area map. The study successfully identi fied and mapped prone areas for elephant. Such maps are of practical and strategic use to wildlife managers in the SHNR. The study recommended community awareness programs. The programs will educate and involve the community on early detection of HEC and the necessary mitigation measure required
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