Persistent uncertainty about the economic implications of agroforestry presents a significant barrier to adoption. Despite this, most research to date ignores the impact of uncertainty on land allocation decisions, with studies commonly relying on simplistic scenarios involving a dichotomous choice between switching entirely to agroforestry or retaining the status quo system. For a more realistic decision problem, we explored...

Sustainable intensification of agricultural lands might reconcile the conservation of tropical forest with food production, but in-depth assessments considering uncertainty and extreme values are missing. Uncertainty prohibits mapping probabilities to potential future states or ranking these states in terms of their likelihood. This in turn hampers the assessment of possible decision outcomes. Here, we use simulations to inves...

Models are essential to assess the socio-economic credentials of new agroforestry systems. In this study, we showcase robust optimisation as a tool to evaluate agroforestry’s potential to meet farmers’ multiple goals. Our modelling approach has three parts. First, we use a discrete land-use model to evaluate two agroforestry systems (alley cropping and silvopasture) and conventional land uses against five socio-economic object...

Understanding farmers’ perceptions of and preferences towards agroforestry is essential to identify systems with the greatest likelihood of adoption to inform successful rural development projects. In this study we offer a novel approach for evaluating agroforestry systems from the farmer perspective. The approach couples rapid rural appraisal and normative optimisation techniques to determine favourable land-use compositions...