Estimating the spatial and temporal distribution of suitable habitats for the African elephant (Loxodonta africana) in Hwange National Park

Abstract

Introduction: African elephants (Loxodonta Africana) are keystone species whose survival is increasingly threatened by habitat loss, climate change, and human-elephant conflict. Understanding their habitat preferences and how these may shift under future climate conditions is vital for effective conservation planning. Methods: This study assessed the current and future distribution of suitable habitats for African elephant in Hwange National Park, Zimbabwe, using Species Distribution Models (SDMs), including MaxEnt, Random Forest, and an Ensemble model. Presence data derived from GPS-collared elephants (2015–2018) were combined with environmental variables such as NDVI, slope, elevation, distance to water and park boundary, and 19 bioclimatic variables for the current, 2050, and 2070 periods. Variable selection was guided by multicollinearity tests (VIF < 5), and models were evaluated using metrics such as AUC and TSS. Results: Results showed that Random Forest and ensemble models outperformed MaxEnt in predictive performance. Seasonal modeling revealed minimal shifts between wet and dry seasons, while future projections indicated a decline and fragmentation of highly suitable habitat, particularly along the southern and eastern edges of the park. Key predictors included temperature and precipitation-related variables, especially maximum temperature of the warmest month and annual precipitation. Discussion: These findings highlight the need to apply robust species distribution modelling tools to enhance actionable conservation and spatial planning strategies that incorporate climate projections to support long term survival of the threatened elephant population in the Hwange National Park ecosystem.