Deforestation rate and causes in Upper Manyame Sub-Catchment, Zimbabwe: Implications on achieving national climate change mitigation targets

The signing of the Paris Agreement at the UNFCCC Conference of the Parties (COP) 21 repositioned the global agenda toward sustainable forest management to address the threats of global warming. However, deforestation rates in many parts of the world continue to accelerate. The study evaluates the ra...

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Main Authors: Luckson Zvobgo, Jonathan Tsoka
Format: Article
Language:English
Published: Elsevier 2021-09-01
Series:Trees, Forests and People
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2666719321000297
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author Luckson Zvobgo
Jonathan Tsoka
author_facet Luckson Zvobgo
Jonathan Tsoka
author_sort Luckson Zvobgo
collection DOAJ
description The signing of the Paris Agreement at the UNFCCC Conference of the Parties (COP) 21 repositioned the global agenda toward sustainable forest management to address the threats of global warming. However, deforestation rates in many parts of the world continue to accelerate. The study evaluates the rate and causes of deforestation in Upper Manyame Sub-Catchment (UMSC) due to land use land cover (LULC) changes between 1990 and 2020. Landsat imagery analysis augmented by household questionnaire survey and key stakeholder interviews were used to assess the rate and cause of deforestation in UMSC. Over the 30 years, the sub-catchment lost 9.4% of its vegetation area due to land use changes. Vegetation loss was mainly due to urban expansion of Harare and its dormitory towns and the extensive peri‑urban agriculture mainly tobacco harvesting. Using the Markov Chain Cellular Automata model, the study estimated that in 2030 the catchment will lose approximately 3.3% of the current vegetation land cover area. This means a further reduction of the vegetation area from 20.1% to 16.8% in 2030. There is need for harmonisation of infrastructure development in Harare and the peri‑urban farming activities with policies that conserve forests such as the use of charcoal and eucalyptus plantations for curing tobacco instead of indigenous trees. This is critical if Zimbabwe is to meet its climate change mitigation targets in the Nationally Determined Contribution that promotes the implementation of Reducing Emissions from Deforestation and Forest Degradation (REDD+).
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spelling doaj.art-2e3b744c0b75472c8fc1313c1829b3612022-12-21T22:31:49ZengElsevierTrees, Forests and People2666-71932021-09-015100090Deforestation rate and causes in Upper Manyame Sub-Catchment, Zimbabwe: Implications on achieving national climate change mitigation targetsLuckson Zvobgo0Jonathan Tsoka1Climate System Analysis Group (CSAG), Department of Environmental and Geographical Science, University of Cape Town, Rondebosch 7701, Cape Town, South Africa; Climate Risk Laboratory, African Climate and Development Initiative (ACDI), University of Cape Town, Rondebosch 7701, Cape Town, South Africa; Corresponding author.School of Civil and Environmental Engineering, University of the Witwatersrand, Wits 2050, Johannesburg, South AfricaThe signing of the Paris Agreement at the UNFCCC Conference of the Parties (COP) 21 repositioned the global agenda toward sustainable forest management to address the threats of global warming. However, deforestation rates in many parts of the world continue to accelerate. The study evaluates the rate and causes of deforestation in Upper Manyame Sub-Catchment (UMSC) due to land use land cover (LULC) changes between 1990 and 2020. Landsat imagery analysis augmented by household questionnaire survey and key stakeholder interviews were used to assess the rate and cause of deforestation in UMSC. Over the 30 years, the sub-catchment lost 9.4% of its vegetation area due to land use changes. Vegetation loss was mainly due to urban expansion of Harare and its dormitory towns and the extensive peri‑urban agriculture mainly tobacco harvesting. Using the Markov Chain Cellular Automata model, the study estimated that in 2030 the catchment will lose approximately 3.3% of the current vegetation land cover area. This means a further reduction of the vegetation area from 20.1% to 16.8% in 2030. There is need for harmonisation of infrastructure development in Harare and the peri‑urban farming activities with policies that conserve forests such as the use of charcoal and eucalyptus plantations for curing tobacco instead of indigenous trees. This is critical if Zimbabwe is to meet its climate change mitigation targets in the Nationally Determined Contribution that promotes the implementation of Reducing Emissions from Deforestation and Forest Degradation (REDD+).http://www.sciencedirect.com/science/article/pii/S2666719321000297DeforestationLand Use Land Cover changesGIS and Remote SensingCellular Automata Markov ChainParis Agreement
spellingShingle Luckson Zvobgo
Jonathan Tsoka
Deforestation rate and causes in Upper Manyame Sub-Catchment, Zimbabwe: Implications on achieving national climate change mitigation targets
Trees, Forests and People
Deforestation
Land Use Land Cover changes
GIS and Remote Sensing
Cellular Automata Markov Chain
Paris Agreement
title Deforestation rate and causes in Upper Manyame Sub-Catchment, Zimbabwe: Implications on achieving national climate change mitigation targets
title_full Deforestation rate and causes in Upper Manyame Sub-Catchment, Zimbabwe: Implications on achieving national climate change mitigation targets
title_fullStr Deforestation rate and causes in Upper Manyame Sub-Catchment, Zimbabwe: Implications on achieving national climate change mitigation targets
title_full_unstemmed Deforestation rate and causes in Upper Manyame Sub-Catchment, Zimbabwe: Implications on achieving national climate change mitigation targets
title_short Deforestation rate and causes in Upper Manyame Sub-Catchment, Zimbabwe: Implications on achieving national climate change mitigation targets
title_sort deforestation rate and causes in upper manyame sub catchment zimbabwe implications on achieving national climate change mitigation targets
topic Deforestation
Land Use Land Cover changes
GIS and Remote Sensing
Cellular Automata Markov Chain
Paris Agreement
url http://www.sciencedirect.com/science/article/pii/S2666719321000297
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