Understanding smallholder farmer decision making in forest land restoration using agent-based modeling

Success of forest restoration at farm level depends on the farmer´s decision-making and the constraints to farmers’ actions. There is a gap between the intentions and the actual behavior towards restoration in Sub-Saharan Africa and the Global South. To understand this discrepancy, our study uses empirical household survey data to design and parameterize an agent-based model. WEEM (Woodlot Establishment and Expansion Model) has been designed based on household socio-demographics and projects the temporal dynamics of woodlot numbers in Uganda. The study contributes to a mechanistic understanding of what determines the current gap between farmer’s intention and actual behavior. Results reveal that an increase in knowledge of the current forest policies laws and regulations (PLRs) from 18% to 50% and to 100% reduces the average number of woodlots by 18% and 79% respectively. Lack of labor reduces the number of woodlots by 80%. Increased labor requirement from 4 to 8 and to 12 man-days, reduces the number of woodlots by 26% and 61% respectively. WEEM indicates that absence of household labor and de facto misconception of PLRs “perceived tenure insecurity” constrains the actual behavior of farmers. We recommend forest PLRs to provide full rights of use and ownership of trees established on private farmland. Tree fund in the case of Uganda should be operationalized to address the transaction costs and  to achieve the long-term targets of forest land restoration.