Modeling smallholder agricultural systems to manage Striga in the semi-arid tropics.
Across southern Africa (SA), significant maize yield losses are attributed to invasive and parasitic weeds. Abundance of Striga (Striga asiatica) has become more frequent in smallholder farms (<2 ha) in the past decade. Various Striga control practices (SCPs) have been disseminated across SA, yet often, without decision support tools to inform extension officers and researchers which ones are most appropriate for smallholder contexts. System dynamics modeling (SDM) provides an opportunity to evaluate the efficacy of SCPs across multiple seasons in different agroecosystems and their associated environments. We developed a SDM to evaluate the long-term efficacy of four SCPs popularly used in maize-based cropping systems. Observations from studies outlining local soil seedbanks, emergence and flowering rates in farmer fields were used to calibrate the SDM. Model simulations indicate that while a combination of SCPs are necessary to manage the weed, future research should focus on developing smallholder-adapted SCPs that address the attachment stage of the weed's lifecycle (e.g., timely manure application) rather than its germination, emergence or flowering stages. Given the devastating effects S. asiatica has had on food security in Malawi and across SA, it is imperative to develop decision support tools like systems models to evaluate SCPs for smallholders. Models that do not capture the underlying mechanisms driving S. asiatica infestations may provide extension officers with potentially misleading information, and subsequently, the delivery of ineffective SCPs.