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Author: Chemura, Abel × End date: 2024 × Start date: 2020 × DDC: 600 × WGL Institute: PIK ×

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    Wildlife-vehicle collisions in hurungwe safari area, northern zimbabwe
    (Amsterdam [u.a.] : Elsevier, 2020) Gandiwa, Edson; Mashapa, Clayton; Muboko, Never; Chemura, Abel; Kuvaoga, Phillip; Mabika, Cheryl T.
    This study is the first to assess wildlife-vehicle collisions (WVC) in Zimbabwe. The study analysed the impact and factors that influence vehicle collisions with large wild mammals along the Harare-Chirundu road section in the protected Hurungwe Safari Area, northern Zimbabwe. Data were retrieved from the Hurungwe Safari Area records and covered the period between 2006 and 2013. Descriptive statistics were used to analyse the recorded variables across the sampled area and to show trends of the prevalence of large wild mammals roadkill over time. Using STATISTICA version 10 for Windows, a two-tailed Mann-Whitney U test was used to determine differences between the number of wild mammal animal roadkills and seasons. A total of 47 large wild mammal animals were killed between 2006 and 2013. The large wild mammal animals that died as a result of vehicle collisions constituted a total of 11 species, with the African buffalo and spotted hyena being the most hit and killed animal species. Most WVC involved heavy haulage trucks and passenger buses. There was no significance difference (P = 0.936) between number of large wild mammal animals killed from WVC between dry and wet seasons. The large wild mammal animals were mostly killed in areas near water sources. We recommend for the inclusion of wildlife protection safeguards in road infrastructure network design and development, particularly on roads that traverse across protected areas in Zimbabwe and beyond. © 2020 The Author(s)
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    Climate change and specialty coffee potential in Ethiopia
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2021) Chemura, Abel; Mudereri, Bester Tawona; Yalew, Amsalu Woldie; Gornott, Christoph
    Current climate change impact studies on coffee have not considered impact on coffee typicities that depend on local microclimatic, topographic and soil characteristics. Thus, this study aims to provide a quantitative risk assessment of the impact of climate change on suitability of five premium specialty coffees in Ethiopia. We implement an ensemble model of three machine learning algorithms to predict current and future (2030s, 2050s, 2070s, and 2090s) suitability for each specialty coffee under four Shared Socio-economic Pathways (SSPs). Results show that the importance of variables determining coffee suitability in the combined model is different from those for specialty coffees despite the climatic factors remaining more important in determining suitability than topographic and soil variables. Our model predicts that 27% of the country is generally suitable for coffee, and of this area, only up to 30% is suitable for specialty coffees. The impact modelling showed that the combined model projects a net gain in coffee production suitability under climate change in general but losses in five out of the six modelled specialty coffee growing areas. We conclude that depending on drivers of suitability and projected impacts, climate change will significantly affect the Ethiopian speciality coffee sector and area-specific adaptation measures are required to build resilience.