Toward near-real-time forecasts of airborne crop pests: Aphid invasions of cereal grains in North America

Abstract Airborne invasions of crop pests pose a significant challenge in agriculture. Novel infestations, such as the recently observed invasion of sugarcane aphid [Melanaphis sacchari (Zehntner) (Hemiptera:Aphididae)] on sorghum [Sorghum bicolor (L.) Moench] in the Great Plains of the U.S., emerge rapidly and require fast management actions to mitigate economic losses. Areawide integrated pest management has been a recognized strategic response to such problems. Management tactics may benefit from analysis of pest infestation data and from predictive simulation modeling. Within such a framework, a predictive simulation model could provide short- and long-term decision support. We describe a prototype of a computational framework that could be used to forecast sugarcane aphid invasions of sorghum in near-real-time, as supported by timely field reports on current aphid infestation status. Within the framework, a modeling platform that simulates spread of aphid infestations of sorghum is linked to EDDMapS, a web-based mapping system for documenting invasive species and agronomic pest distributions. The interconnectivity of the modeling process and sorghum field sampling through EDDMapS allows for regular updates of the internal states of the model, which support short-term infestation forecasts based on field data feeds. Practical application of the system could support informed short-term decisions on pesticide application and field sampling, as well as longer-term decisions regarding crop variety deployment.