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

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