Technology adoption and weed emergence dynamics: social ecological modeling for maize-legume systems across Africa

Abstract

Ecological practices such as intercropping maize (Zea mays) with cowpea (Vigna unguiculata L.) have been promoted to combat parasitic weeds like Striga (Striga asiatica). Intercropping has been promoted across Africa as a Striga control practice (SCP) and food security measure. Despite past efforts, millions of smallholder farmers (cultivating < 2 ha of maize) still struggle to implement SCPs. Social and ecological factors that prevent SCP implementation are well documented in the literature, but their underlying interactions have remained elusive. System dynamics modeling can uncover these interactions and assess their effect on intercropping rates as well as Striga emergence. This study presents a participatory mixed methods approach to build a system dynamics model based on two theories: diffusion of innovations and resource pool dynamics. The model estimates the population of fields where Striga emerged in response to intercropped fields when various interventions were implemented. According to model simulations, if new policies are not enacted to support intercropping, Striga is likely to spread to 2,625,000 maize fields, parasitizing almost 75% of smallholder farms across Central Malawi by 2036. The participatory approach allowed us to evaluate several policies, one of which sustained enough adopters to limit Striga emergence to < 500,000 fields, reducing the weed’s threat to food security. This policy considers how input costs and erratic rainfall can lead to disadoption, therefore, supporting the implementation of five to six consecutive years of intercropping by providing both fertilizer subsidies and demonstration plots. In this study, our participatory approach has shown to develop a model that can highlight interactions in social ecological systems, their leverage points, and how they can be exploited to develop effective food security policies.

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