Soybeans as a non-Bt refuge for Helicoverpa zea in maize-cotton agroecosystems

Geospatial models are crucial for identifying likely ‘hot-spots’ of Bt resistance evolution in Helicoverpa zea (Lepidoptera: Noctuidae), thereby improving regional insecticide management (IRM) strategies and planted refuge compliance. To characterize H. distributions relation to land use , we used historical trapping data collected from 2008 2019 North Carolina model the spatial temporal abundance populations across -dominated landscapes. was standardized site-year observations, candidate landscape composition configuration predictors were obtained. Spatiotemporal Bayesian hierarchical developed make posterior predictions environmental covariates, results generate interpolation prediction maps visualize sampled region. Our suggest inverse distance weighted (IDW) soybeans is most important predictor through time row crop agroecosystems Carolina. Soybeans southeastern U.S. serves as a critical non- delaying toxins landscapes dominated by maize cotton. Moreover, soybean can be predict this Results applied understand population dynamics genetically engineered (GE) crops expressing will enable development sound insect GE targeting noctuid pests This work also drive future geospatial studies investigating arthropod technologies production systems. Landscape-level variation predicts refugia cotton agroecosystems. • relate drivers associate with increased serve