This study first explored the rate of forest deforestation in Shamva resettlement areas. It then identified and estimated the extent to which these resettled farmers depend on forest for their livelihoods. Evaluation of farmer perceptions on management issues and willingness to participate in indigenous forest conservation and the socio-economic and institutional factors which affect their willingness to participate were also done. Finally the study sought to identify incentives for forests conservation. The study was conducted in Shamva district in Mashonaland Central province. And the respondents were stratified into three groups: A1, A2 and Old resettlement models. The three models differ on how they were implemented and supported which might render them to have different deforestation rates, livelihood strategies and forest dependency. A total of 247 respondents were surveyed, consisting of 98 A1 farmers, 50 A2 farmers and 99 Old resettled farmers. The data was collected using GIS and remote sensing, structured questionnaire interviews and direct observation. The data was analysed using descriptive analysis, KAP analytic framework and binary logistic regression analysis. The land cover/changes results revealed that both deforestation and afforestation are taking place in Shamva resettlement. Woodland and bushland were decreasing, croplands were also decreasing. However woodland dense and grasslands were increasing. Deforestation was found to be as a result of the resettled farmers’ livelihood strategies which were found to be diverse and agriculture being dominant in all models. All the farmers depended on the forest but at varying levels of 19 percent for Old and 14 percent forA1 and 0.02 percent for A2 resettle farmers. 84 percent of the interviewed farmers however, indicated that they are willing to conserve forest with A1 farmers being the highest followed by A2 86 percent and lastly Old resettled farmers at 76.8 percent. Results of the binary regression model revealed that the significant factors which explain willingness to participate in indigenous forest conservation are age, marital status, education, gender, institution, culture and belief, employment and household size. The highest preferred incentive was the provision of free seedlings and the lowest was out grower scheme. The study recommends that GIS and remote sensing should be used to monitor deforestation, off farm projects be encouraged, exotic and indigenous trees be promoted and forest conservation education be promoted in resettlement areas.

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)

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)