Wildlife persists in the Midlands Black Rhino Conservancy, Zimbabwe, but requires an emergency conservation plan

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.

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Publication Details

Journal
Geocarto International
Published
2026-05-02
DOI
https://doi.org/10.1080/10106049.2026.2666476
Primary Topic
Wildlife Ecology and Conservation
Type
article
Field-Weighted Citation Impact
0.00
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article

Wildlife persists in the Midlands Black Rhino Conservancy, Zimbabwe, but requires an emergency conservation plan

Ellen Boys, Nobert Tafadzwa Mukomberanwa, Honest Komborero Madamombe, Last Keche et al.
Geocarto International
Wildlife Ecology and Conservation
article

Wildlife persists in the Midlands Black Rhino Conservancy, Zimbabwe, but requires an emergency conservation plan

Ellen Boys, Nobert Tafadzwa Mukomberanwa, Honest Komborero Madamombe, Last Keche, Makanaka Muradzi, Tinotenda Nyasha Mukinya, Thembeka Sopuka, Briliant Makuwe Chibura, Tadiwanashe Blessed Gwara, Munyaradzi Kadzere, Mitchell Chido Mugaviri, Kudakwashe Manyika, Dexter Farai Chigumira, Amon Diwa, Innocent Maradza, Maxwell Parirewa, Tsitsi Tamia Muchepa, Takudzwa Chirambasadza, Tafadzwa Nyamahumba, Blessings Moyo, Andrew Takunda Bangwayo, Courtney Mapuranga, Akasha Alice Alison, Trevor Tinashe Chipfu, Nichol Mudzimiri, Jeremiah Thabeti, Delight Panashe Mandiyanike, Takudzwa Praisegod Murwadzi, Taurai Allan Taru, Olinda Samantha Bisenti, Mitchell Tendesai Zimunya, Wellington Muradzikwa, Mutsawashe Tadiwanashe Muzari, Triumph Mugove Mukume, Michael Gwenzi, Kelvin Charles Muredzi, Charlotte Tadiwa Taruvinga, Archiford Takaindisa, Nyasha Chelsea Madanhe, Diarson Ishmael Tsuro, Zvikomborero Samuel Mboto, Brendon Mharakurwa, Brian Chinyanga, Isheanopa Pasco Gatsi, Melody Mutasa, Wesley Tanatswa Mandonye, Fidelis Duncan Dzambo, Munashe Manyika, Munyaradzi Chirova, Osley Mudzanirwa, Mercy Joyline Mbarami, Florence Guchu, Sarah Mudiwa Chikowero, Active Farai Moses Nyamadzawo, Trevor Muchenjekwa
article en

Abstract

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.

Geocarto InternationalVol. 41(1)
Chinhoyi University of Technology (ZW), Ocean Conservancy (US)
Life in Land
Openalex Percentile: Top 8%
Wildlife Ecology and Conservation
DOIOpen Access PDFOpenAlex
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