Research Articles

Modelling deforestation, carbon stock changes, and identification of optimal forest restoration sites in a rapidly urbanising landscape

2026-05-16T00:00:00Z

Modelling deforestation, carbon stock changes, and identification of optimal forest restoration sites in a rapidly urbanising landscape Mukomberanwa, Nobert Tafadzwa; Kamanga, Talent; Munetsi, Blessing Onias Developing towns and cities worldwide face high deforestation rates, yet accurate information on its spatial extent, dynamics, and potential restoration sites remains limited. Forest ecosystems play a pivotal role in carbon sequestration; however, their degradation disrupts ecological functions, necessitating spatially explicit assessments of carbon stock changes over time. Understanding the spatiotemporal patterns of forest loss is essential for assessing carbon dynamics and guiding targeted restoration interventions across ecologically sensitive and socioeconomically vulnerable landscapes. This study aimed to assess deforestation dynamics, quantify forest cover, and identify potential restoration sites in Chinhoyi, Zimbabwe. Using Geographical Information Systems (GIS), Remote Sensing (RS), and the Random Forest (RF) machine learning algorithm, the study assessed forest cover loss and restoration suitability. Potential restoration sites were identified by evaluating factors such as slope, proximity to roads and settlements, and land use land cover (LULC) patterns using the Weighted Overlay Analysis (WOA) and Analytical Hierarchy Process (AHP). Findings revealed a 54.58 % net reduction in forest cover from 2014 to 2024, largely driven by agricultural expansion, urbanization, and land degradation. However, transition analysis also indicated localized regeneration, with 4.57 %– 15.17 % ha of forest gains observed in different intervals, highlighting natural regrowth and reforestation processes. Carbon stock analysis indicated significant losses, with 45,252 tons of carbon emissions exceeding regional averages over the decade. The study recommends prioritizing reforestation and forest restoration efforts in highly suitable areas to recover forest cover and mitigate the impacts of continued deforestation.

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

2026-05-02T00:00:00Z

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

A comparison of home range estimates using the time local convex hull (T‐LoCoH) and minimum convex polygon (MCP) methods for African savannah elephants in a semi‐arid protected area

2025-09-05T00:00:00Z

A comparison of home range estimates using the time local convex hull (T‐LoCoH) and minimum convex polygon (MCP) methods for African savannah elephants in a semi‐arid protected area Mukomberanwa, Nobert T.; Taru, Phillip; Utete, Beaven; Ngorima, Patmore Knowledge of home ranges (HRs) helps conservationists understand movement patterns and can aid management including avoidance of human‐wildlife conflicts. This study examined the African savannah elephant seasonal HRs and space use using telemetry data in Mana Pools National Park, Zimbabwe. The objectives were to (i) compare the HR sizes and (ii) construct utilization distribution of African savannah elephants using the minimum convex polygon (MCP) method and the time‐local convex hull (T‐LoCoH). The results revealed that the dry, transitional, and wet season HR sizes estimated by the MCP method were significantly larger than those of the T‐LoCoH method. Significant differences were observed between core T‐LoCoH home‐range distributions for the wet, transition, and dry seasons. T‐LoCoH more accurately represented the HR size and nuances of repeated movements and internal spaces than the MCP method. The findings show larger‐scale movements in the transition season, which would enhance the potential for human–elephant conflicts.

Modelling Tree Allometries to Understand the Impact of African Savannah Elephant Herbivory Dynamics on the Vegetation Structure and Tree Cover Change in a Protected Area

2024-09-27T00:00:00Z

Modelling Tree Allometries to Understand the Impact of African Savannah Elephant Herbivory Dynamics on the Vegetation Structure and Tree Cover Change in a Protected Area Mukomberanwa, Nobert Tafadzwa; Taru, Phillip; Utete, Beaven; Ngorima, Patmore In landscapes with high elephant density, trees often exhibit more open canopies with fewer branches and foliage due to browsing pressure. This can result in altered tree morphology, with trees exhibiting stunted growth, multiple stems or unusual branching patterns in response to repeated damage from browsing. The objectives of this research were to (i) model the vegetation structure allometries, (ii) assess the impact of African savannah elephant (Loxodonta africana) herbivory on the vegetation structure and (iii) assess tree cover change and vegetation performance over time in Mana Pools National Park in Zimbabwe. We established 26 plots of 30 × 30 m size. Selection of sampling plots was done following several steps. First, a fish net grid with 30 × 30 m polygons was created and projected on the polygon of Mana Pools National Park. The polygons for exclusion zones were then clipped from the fish net grid using the clip tool in ArcGIS Pro 3.0. Then, selection of sampling plots was done initially by stratified random sampling using the Sampling Design Tool add in for ArcGIS Pro 3.0. Landsat images for the years 2003, 2013 and 2023 were used to assess land use land cover (LULC) time series and to calculate Normalised Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) for the period. A generalised linear model (GLM) was used to analyse tree allometries. Further statistical investigations were performed using Bayesian piecewise regression (BPR) and Bayesian regression modelling (BRM). Basal area, number of stems, height, long canopy, diameter and basal circumference were all significantly different (p < 0.05) across all sampled plots. The change in growing conditions occurring as a tree grows beyond the reach of the African savannah elephant browsing indicates a natural system breakpoint. The best-fitting models were a simple linear model and a two breakpoint model for the plant population exposed to elephant herbivory. LULC, NDVI and SAVI confirm evidence of high tree regeneration over 2 decades. Understanding the dynamics in vegetation and LULC changes is critical for effective conservation and management of the habitats for African savannah elephants, as well as for maintaining the health and resilience of forest ecosystems.