Confronted with climate change, farmers are increasingly resorting to sustainable agricultural practices like agroforestry as an adaptation measure to the adverse effects of climate change. In this perspective, this study assessed different agroforestry systems and the components there in, as well as the factors affecting farmers' choice of agroforestry systems as adaptation measures to climate change in Cameroon. Mainly primary data were collected through household and field surveys. The factors affecting smallholder farmers' choice of agroforestry systems faced with climate change were analysed using the multinomial logistic regression model. Findings revealed that the agroforestry systems practiced by farmers as adaptation measures to climate change were agrosilvicultural system (43.71%), silvipastoral agroforestry system (11.43%) and agrosilvipastoral system (24.28%). Three main components, namely crops, trees/shrubs and livestock, were integrated in these agroforestry systems by small-scale farmers to enhance adaptation when confronted with climate change adversities. The multinomial logistic regression model revealed the existence of a cause-effect relationship (p < 0.05) between farmers' agroforestry systems and independent variables like household income, access to land and access to information. This shows that access to land, household income and access to information contribute significantly towards influencing farmers' choice of agroforestry systems as adaptation measures to climate change. It is recommended that, when formulating policies, policy makers seeking to enhance farmers' adaptation to climate change through sustainable farming systems like agroforestry should take a keen look at different agroforestry systems and their components, and factor in the determinants of farmers' preference for particular agroforestry systems as an adaptation option.
Awazi, NP; Tchamba, MN; Temgoua, LF; Tientcheu-Avana, ML
Agroforestry as an Adaptation Option to Climate Change in Cameroon: Assessing Farmers' Preferences
Agricultural Research