Invasive insect pests present a significant threat to agricultural production in the United States, yet tools that can accurately predict their population dynamics, activities, and potential to become established and further expand have not yet been fully developed and utilized. Here we present our relatively new spatial modeling platform known as DDRP (Degree-Days, Risk, and Phenological event mapping), which was designed to provide regularly updated predictions of the potential distribution (risk of establishment) and timing of seasonal activities (phenology) of insects. DDRP is distinctive from other pest modeling tools in that it integrates phenology and risk map products, it conducts risk mapping based on current climate data (instead of long-term climate averages), and it uses species and stage-specific parameters for increased model realism. Currently we are using DDRP to produce regularly updated (every three days) model outputs for 15 high-risk pest insects for the USDA APHIS Cooperative Agricultural Pest Survey program (http://uspest.org/dd/maps). We discuss example applications of DDRP using two invasive insect species which threaten agricultural biosecurity in the United States: light brown apple moth, Epiphyas postvittana, and emerald ash borer, Agrilus planipennis. In particular, we show how model outputs such as predictions of first emergence in climatically suitable areas can provide insights into where and when to expect pests over a growing season, which can help to prevent new establishments and manage existing populations. We conclude with a summary of current work to increase DDRP’s capacity to model moisture-sensitive pests (certain insects, plant pathogens and weeds).
