The persistence of wildlife in the Midlands Black Rhino Conservancy (MBRC), Zimbabwe, highlights both species resilience and landscape value, yet escalating anthropogenic pressures demand urgent conservation action. This study aimed to: (i) model land use/land cover (LULC) changes from 1985–2055 using multi-decadal Landsat imagery; (ii) assess the frequency, distribution and impact of fires between 2010–2025; (iii) evaluate vegetation disturbance from mining through a Bayesian framework; and (iv) determine the status and abundance of key wildlife via systematic transect surveys. Future scenarios were predicted using cellular automata–artificial neural networks (CA-ANN). Fire regimes were analysed using Landsat, FIRMS and dNBR indices, while Bayesian regression models quantified mining impacts. Species distribution was modelled with MaxEnt. Results show shrinking suitable habitats, with many species increasingly confined to fragmented populations. Despite these challenges, the findings underscore opportunities for proactive biodiversity management through robust local and international conservation policies.
Mukomberanwa et al. (Tue,) studied this question.