Fall Armyworm Density-Dependent Predation in West African Maize Intercropping Systems: Agricultural Entomology Split-Plot Experiment Estimating Parasitoid-Mediated Yield Loss Uncertainty for Food-Security Planning

Fall armyworm invasion of African maize after 2016 exposed a persistent weakness in pest management advice, namely the absence of density-dependent loss functions that link larval pressure, natural enemy action and yield under intercropping. Main plots contrast sole maize, maize–cowpea, maize–groundnut and climate-adapted push–pull arrangements, while subplots impose standardised fall armyworm density cohorts for functional-response and parasitism assessment through sentinel larvae, exclusion cages and timed predator observations. Landscape stratification uses a composite spatial index integrating Slope, Drainage density, Rainfall intensity, Land cover, Soil permeability, Elevation and Distance to channels, calibrated on Moroccan administrative units as a transferable dryland geography before application in the Guinea savanna. The geographic information systems workflow combines kernel density estimation, buffer analysis and network connectivity to locate trial blocks and interpret refuge effects. The framework proposes parasitoid-mediated yield-loss functions with explicit uncertainty propagation to support threshold design and food-security planning.