Determinants Of Agroforestry Technologies’ Adoption For Climate Change Adaptation In Muooni Watershed, Machakos County, Kenya

ABSTRACT 

Agroforestry presents opportunities for adaptation to the impacts of climate change and variability in food security and livelihood development systems.According to Intergovernmental Panel on Climate Change, Kenya is experiencing climate change and projections suggest that there would be more extreme weather conditions by the year 2030 and beyond. This would worsen the food insecurity and poverty situation currently observed in arid and semi-arid districts such as Machakos County. Though farmers in Muooni Watershed of Machakos County are practicing agroforestry for livelihood diversification and climate change adaptation, full scale production is yet to be achieved.This study sought to assess the determinants of agroforestry technologies‟ adoption for climate change adaptation by smallholder farmers in Muooni watershed of Machakos County, Kenya with the following specific objectives: (1) to determine the agroforestry based climate change adaptation technologies used by smallholder farmers in Muooni watershed; (2) to evaluate the level of adoption of agroforestry based climate change adaptation technologies; (3) to evaluate factors influencing the adoption of agroforestry based climate change adaptation technologies and (4) to evaluate the opportunities and barriers in the adoption of agroforestry based climate change adaptation technologies by smallholder farmers in Muooni watershed. The study employed transects and cross-sectional surveys where observational guide and questionnaires were used respectively in surveying the catchment. Descriptive statistics was used to determine the agroforestry technologies employed in the watershed while adoption formula and probit model were used to evaluate the level of adoption and the factors influencing the adoption respectively.Strengths, Weaknesses, Opportunities and Threat analysis were conducted to establish the challenges and opportunities in adoption of agroforestry technologies in the watershed. The study revealed 14 agroforestry based climate change adaptation technologies in the watershed. It was established that, there is difference in means of level of adoption between male (mean=42.4451, SD=17.80319) and female agroforestry farmers (mean=41.2202, SD=18.29936) in the study. However, independent-sample t-test showed no statistically significant difference in the level of adoption of agroforestry based climate change adaptation technologies by male and females agroforestry farmers in Muooni watershed as hypothesised (t= 0.339, df= 98, p=0.735). Through probit regression analysis, it was found that age, membership in cooperative group and monthly income were statistically significant at probability level of 1% (p < .01), while sex, education, farming experience, family size and access to training were statistically significant at probability level of 5% (p < .05) . The overall result of the probit model shows a significant difference at 5% level of probability. Through Strengths, Weaknesses, Opportunities and Threat matrix analysis and Quantitative Strategy Planning Matrix analysis, it was evident that the challenges in the watershed can be averted if the available opportunities are harnessed. The study recommends introduction of other agroforestry technologies to farmers andimprovement in government and institutional support systems focusing on factors that influence adoption of agroforestry technologies. Finally, the watershed managers must prioritise activities and interventions in the watershed in order to maximize the opportunities for climate change adaptation through agroforestry in the watershed.