To mulch or to munch: big modelling of big data
African farmers are poorly resourced, highly diverse and aground by poverty traps making them rather impervious to change. As a consequence R4D efforts usually result in benefits but also trade-offs that constraint adoption and change. A typical case is the use of crop residues as mulches or as feedstock. Here we linked a database of household surveys with a dynamic whole farm simulation model, to quantify the diversity of trade-offs from the alternative use of crop residues. Simulating all the households in the survey (n=613) over 99 years of synthetic climate data, showed that benefits and trade offs from “mulching or munching” differ across agro-ecologies, and within agro-ecologies across typologies of households. Even though trade-offs between household production or income and environmental outcomes could be managed; the magnitude of the simulated benefits from the sustainable intensification of maize-livestock systems were small. Our modelling framework shows the benefits from the integration of socio-economic and biophysical approaches to support the design of development programs. Our results support the argument that a greater focus is required on the development and diversification of farmers’ livelihoods within the framework of an improved understanding of the interconnectedness between biophysical, socio-economic and market factors.
