Validating spatiotemporal predictions of western corn rootworm at the regional scale (Tuscany, central Italy)

New invasive pest species are dif!cult to manage, because researchers, advisors, and farmers in the newly invaded areas lack advanced understanding in how and when managing them. The aim of this study was to test selected models that could reliably predict the phenology of Diabrotica virgifera virgifera (LeConte), an important insect pest of maize. We compared the results of three years monitoring activity in three areas of Tuscany with the output of two different models, in order to predict adult emergence from air temperature measurements. The best results were achieved with the model that utilized the date of maize planting as starting date for the accumulation of degree-days, con!rming a strict connection between crop and pest phenology. Model output for the predicted day of the year for start and peak of the pest cumulative emergence was mapped over the administrative boundaries of Tuscany with a regression model run with temperatures derived from WorldClim on-line database. These results will be integrated in a Decision Support System for containment and management strategies of maize pests in Tuscany.