This research assesses Climate Change Adaptation Technologies (CCATs) and Crop Productivity (CP) in the Coffee-Based Farming Systems of Uganda. The Coffee-Based Farming System sustains many households for income and food. However, its sustainability is threatened by the uncertainty in the severity and timing of Climate Change/Variability (CCV) impacts. Despite farmers’ autonomous adaptation approaches to such impacts, many remain food insecure and with low incomes. Compelled by the determinants of adoption, farmers also opt to trade-off among CCATs with respect to income or food security, which makes them more vulnerable. The main objective of this study is to evaluate CCATs within the Coffee-Based Farming Systems of Uganda in terms of CP across different geographical locations, rainfall/altitudinal gradients and temporal scales. The purpose is to provide location and context specific information to farmers in the lowlands (Greater Luwero - central region) and highlands (Mt. Elgon - eastern region); about CCATs that contribute to household welfare in order to plan for Climate Change Adaptation and ensure sustained agricultural production. The specific objectives are to determine the drivers of adoption of farmer’s incremental, systemic and transformational CCATs at household level; establish their effect on CP; and analyse the trade-offs among the technologies with respect to household income and food security. Farmers will be randomly sampled from sub-counties that will be purposively identified within stratas of rainfall/altitudinal gradients in the lowlands and highlands. The Multinomial Endogenous Switching Regression Model will be applied to determine the drivers of choice of CCATs and their effect on CP while the Trade-Off Analysis Multi- Dimensional model will be adopted to analyse the trade-offs. It is believed that the findings will contribute to the realization of Uganda’s Vision 2040 and the Sustainable Development Goals by identifying decision making pathways along which smallholder farmers’ adaptive capacity to climate change could be enhanced.
Name: Catherine Mulinde