Year: 2026
Type: article
Abstract: Habitat conversion threatens the Greater Kafue Ecosystem (GKE), Zambia, one of southern Africa’s most important protected-area landscapes, yet its spatial predictors remain poorly quantified. We used a Random Forest classifier to map susceptibility to natural-habitat conversion across Kafue National Park (KNP) and its surrounding Game Management Areas (GMAs). The binary response was derived from Landsat classifications for 1984 and 2024, treating natural-to-anthropogenic cover transitions as conversion and fourteen socio-economic, climatic, topographic, proximity, and conservation predictors were evaluated. Because most predictors are contemporary, the model characterises spatial correlates of cumulative conversion rather than temporal drivers. On an independent, spatially blocked test set ( n = 1,751), it achieved an accuracy of 0.77, AUC-ROC of 0.83, F1-score of 0.81, and Cohen’s Kappa of 0.53, remaining stable under ten-fold spatial cross-validation (accuracy = 0.84 ± 0.07). A higher false-positive rate (0.34) than false-negative rate (0.14) indicated a precautionary bias suited to screening. Percentage cultivated land was the strongest predictor (mean decrease in impurity = 33.6%; univariate AUC = 0.91). Model-derived cut-points near 10% cultivated cover, 0.036 persons ha⁻¹, 4 km from settlements, and 898 mm rainfall discriminated higher- from lower-susceptibility conditions, though these are screening values, not validated ecological thresholds. Susceptibility mapping identified Bilili, Namwala, and Mumbwa as the principal high-susceptibility GMAs, whereas KNP remained predominantly low. The results support targeted monitoring and conservation prioritisation across the GKE and comparable Miombo landscapes.
Source: Discover Forests
Institution: Copperbelt University
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDGs: Life on land, Climate action
Open Access status: diamond
OpenAlex ID: W7222870066