Long-term management of Striga hermonthica: strategy evaluation with a spatio-temporal population model

The parasitic weed Striga hermonthica poses a serious threat to cereal production in sub-Saharan Africa. Striga hermonthica seedbanks are long-lived; therefore, long-term effects of control strategies on the seedbank only emerge after several years. We developed a spatially explicit, stochastic model to study the effectiveness of control strategies in preventing invasion of S. hermonthica into previously uninfested fields and in reducing established infestations. Spatial expansion of S. hermonthica and decrease in millet yield in a field was slower, on average, when stochasticity of attachment of seedlings to the host was included and compared to the deterministic model. The spatial patterns of emerged S. hermonthica plants 4-7 years after point inoculation (e.g. seeds in a dung patch) in the spatial-stochastic model resembled the distribution typically observed in farmers' fields. Sensitivity analysis showed that only three out of eight life cycle parameters were of minor importance for seedbank dynamics and millet yield. Weeding and intercropping millet with sesame or cowpea reduced the seedbank in the long term, but rotations of millet with trap crops did not. High seedbank replenishment during years of millet monoculture was not sufficiently offset by seedbank depletion in years of trap crop cultivation. Insight from simulations can be employed in a participatory learning context with farmers to have an impact on S. hermonthica control in practice.