Information on deforestation and forest management is limited due to lack of understanding as to how socioeconomic factors affect deforestation. Without adequate data, it is difficult to manage deforestation; particularly in Chipuriro where deforestation is occurring at a rapid rate. This research was carried out to address the problem. Surveys and landsat images were used to collect data. To quantify deforestation, images were processed using Geographical Information System. Pearson’s Correlation Coefficient was used to deduce the relationship between socioeconomic factors and deforestation. Socioeconomic factors were obtained through household surveys and focus group discussions. Results indicated high rates of deforestation in Ward 18 (4.7% per annum) while in Ward 16 woodland cover increased throughout the study period (7.7% per annum). Population growth with its demand on fuel wood, settlement and agricultural land caused a significant decrease in woodland cover in Ward 18. Plantations increased the area under woodlands in Ward 16. / Environmental Sciences / M. Sc. (Environmental Management)

The survey has been carried out in North West Province within Rustenburg Local Municipality. This is an Urban Forestry research in which six sites including peri-urban, urban, suburban and semi-rural areas were selected for the study. The aim of the study was to determine the relationship between households and their local trees and forests. Forest in this context included community gardens, vegetation cover, open spaces, soil, water, productive sites and animals that form part of forest. Data collection was mainly based on questionnaires and covered sample of 272 households. Statistical Package of Social Sciences (SPSS) 15.0 using 5% sampling intensity (confidence level) was used in which the data has been represented by numbers. Analysis was based on determining households’ relationship with their trees and local forest, and how they influence forest productivity or development. With SPSS two techniques, regression model and descriptive statistics were applied to analyze quantitative and qualitative data. Regression model was significant in prediction of the dependent variable (Y) using independent variables (X), and proved to be a good model to analyze data for fuelwood, timber and forest food production. Descriptive statistics was important in counting number of times each category or variable is used. Participants had varying perceptions regarding the use of forest due to factors such as availability of forest resource, type of residence, and their living standard. Generally, households in suburban and urban areas value the forests for economic and environmental benefit, while the peri-urban and semi-rural households utilized their trees and forest to meet their energy demand. A large number of households consume forest food as compared to timber and fuelwood due to the availability of the resources. The Municipality as a whole is undergoing rapid development expected to continue throughout years. These developments are stimulated by mining activities and influx of people in the area. All these factors threaten the existing natural resources especially forest areas and water. Areas of these resources are declining due to the current demand for housing, new mining sites and continuous establishment of informal settlements. Trees and forest within peri-urban and semi-rural areas are in poor conditions as compared to urban and suburban areas. Poor waste management and poverty are issues aggravating the situation especially in poor developing sites that have been studied. Most agricultural sites have been transformed into residential areas, and thus exacerbating problems of food insecurity in the whole country. Household size has major influence in fuelwood, timber and forest food production as an increase or decrease in the size will determine the amount of consumption, production or development. Value for forest, access to forest, level of interaction and restrictions regarding the use of forest are also significant aspects contributing to forest productivity and development as they show the relationship that exists between forest and households. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2007.

Doctorat en philosophie et lettres / info:eu-repo/semantics/nonPublished

Information on deforestation and forest management is limited due to lack of understanding as to how socioeconomic factors affect deforestation. Without adequate data, it is difficult to manage deforestation; particularly in Chipuriro where deforestation is occurring at a rapid rate. This research was carried out to address the problem. Surveys and landsat images were used to collect data. To quantify deforestation, images were processed using Geographical Information System. Pearson’s Correlation Coefficient was used to deduce the relationship between socioeconomic factors and deforestation. Socioeconomic factors were obtained through household surveys and focus group discussions. Results indicated high rates of deforestation in Ward 18 (4.7% per annum) while in Ward 16 woodland cover increased throughout the study period (7.7% per annum). Population growth with its demand on fuel wood, settlement and agricultural land caused a significant decrease in woodland cover in Ward 18. Plantations increased the area under woodlands in Ward 16. / Environmental Sciences / M. Sc. (Environmental Management)

MPM / Oliver Tambo Institute of Governance and Policy Studies