Factors Affecting Adaptation to Climate Change through Agroforestry in Kenya

Abstract

The environmental effects of climate change have significantly decreased agricultural productivity. Agroforestry technologies have been applied as a solution to promote sustainable agricultural systems. This study evaluates the factors influencing the adoption of agroforestry technology in Kenya. A multistage sampling technique was employed to collect data from 239 households in West Pokot County, Kenya. A Probit model and K-means algorithm were used to analyze the factors affecting farmers’ agroforestry technology adoption decisions based on the sampled households’ socio-economic, demographic, and farm characteristics. The study found that the total yield for maize crop, farm size, extension frequency, off-farm income, access to training, access to credit, access to transport facilities, group membership, access to market, gender, distance to nearest trading center, and household education level had significant effects on the adoption of agroforestry technologies. The findings of this study are important in informing policy formulation and implementation that promotes agroforestry technologies adoption.

Keywords

• climate change
• agroforestry-based technology
• probit model
• <i>K-</i>means