MST-Department of Environmental Science

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Browsing MST-Department of Environmental Science by Subject "Agroforestry Technologies"

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    Impact of Agroforestry Technologies on Livelihood Improvement among Smallholder Farmers in Southern Province Of Rwanda
    (Kenyatta University, 2021) Mukundente, Liliane; Ezekiel Ndunda; Gladys Gathuru
    The natural forest of Rwanda is under threat as a result of rising rural population and subsistence cultivation. As a result, the Rwanda Ministry of Agriculture has deployed agroforestry technologies in forest-dependent communities in order to reduce forest pressures and improve the livelihoods of local people. This study mainly focuses on the agroforestry practices adopted by smallholder farmers; assess socioeconomic and institutional factors that impact adoption of agroforestry and finally, evaluate the impression of adopting agroforestry practices on livelihood improvement of smallholder farmers in Southern Province of Rwanda. This study was carried out in four districts in southern province of Rwanda. A descriptive survey design was used in this study. Semi-structured questionnaires used to collect primary data from a sample of smallholder. The study used both quantitative and qualitative methods. Descriptive method of analysis was used to identify the different agroforestry technologies adopted by smallholder farmers in study area. A binary logit model used to assess the socioeconomic factors that influence the adoption of agroforestry in the study area. Propensity score matching model was used to determine the impact of agroforestry on livelihoods. The results of this study illustrated the different agroforestry practices adopted by the farmers in this area but the most farmers in study area had adopted boundary planting(68%) agroforestry followed by home garden(14%), alley cropping(11%) and scattered trees on farm(7%). Propensity score matching model demonstrated positive significant association between adoption of agroforestry and annual farmer income and consumption expenditure) of the respondents. Farmers adopted agroforestry had more annual income compare to non-adopters and also consumption expenditure of adopters was higher than consumption expenditure of non-adopter’s farmers. Therefore, agroforestry adoption had a significant impact on the livelihood of most farmers and their households. Finally, Binary regression model showed no significant association between the adoption of agroforestry practices and respondent’s age, gender, marital status, farming experience or income range of the respondents. On the other hand, there is a positive significant association between the adoption of agroforestry practices and household size as well as the farm size of the respondents, soil fertility and soil erosion. It is concluded that farmers with larger household size are more likely to adopt agroforestry practices than farmers with smaller household size and also shows that most of the farmers who were more likely to adopt agroforestry had a bigger land acreage for planting more trees.