Modeling Habitat Suitability for African Elephants (Loxodonta Africana) in a Savannah Ecosystem, Kenya
Abstract
Effective conservation of African elephants requires clear understanding of the environmental factors influencing their habitat distribution, particularly in the face of climate change. This study assessed current and future habitat suitability for African elephants in the Nasalot-South Turkana-Kerio Valley ecosystem. The Maximum Entropy (MaxEnt) model was developed using 133 spatially independent occurrence records, 12 non-correlated environmental variables, a Linear–Quadratic feature combination, and a regularization multiplier of 3.5. Species occurrence data were obtained from field surveys and spatial data on various environmental variables were sourced from multiple online sources, including WorldClim, United States Geological Survey (USGS), ASTER Global DEM, HydroSHEDS and OpenStreetMap. Bias correction involved removing redundant records, spatial filtering of occurrence points, selecting background points, and eliminating highly correlated variables. Area Under the Curve (AUC) was used to evaluate the model. Model performance was high (AUC = 0.868 ± 0.006), with Precipitation of the Coldest Quarter (bio_19) contributing the most (62.5%), followed by land use/land cover (14.6%). Results indicate that currently, low suitability habitats dominate the landscape (~41.10%) while highly suitable habitats occupy only ~8.71%. Under future climate scenarios SSP245 and SSP585, unsuitable habitats are projected to expand significantly, covering between 67.09% and 70.93% of the region. In comparison, moderate and low suitability classes are expected to decline by 53.73% and 68.21%, respectively. The findings indicate significant shifts in elephant habitat suitability under future climate scenarios, underscoring the urgent need for adaptive conservation.
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