Short-term forecasts of insect phenology inform pest management
Insect pests cost billions of dollars per year globally, negatively impacting food crops and infrastructure, and contributing to the spread of disease. Timely information regarding developmental stages of pests can facilitate early detection and control, increasing efficiency and effectiveness. In 2018, the U.S. National Phenology Network (USA-NPN) released a suite of ‘Pheno Forecast’ map products relevant to science and management. The Pheno Forecasts include real-time maps and short-term forecasts of insect pest activity at management-relevant spatial and temporal resolutions and are based on accumulated temperature thresholds associated with critical life-cycle stages of economically important pests. Pheno Forecasts indicate, for a specified day, the status of the insect’s target life-cycle stage in real time across the contiguous United States. The maps are available for 12 pest species including the invasive emerald ash borer (Agrilus planipennis Fairmaire [Coleoptera: Buprestidae]), hemlock woolly adelgid (Adelges tsugae Annand), and gypsy moth (Lymantria dispar Linnaeus [Lepidoptera: Erebidae]). Preliminary validation based on in-situ observations for hemlock woolly adelgid egg and nymph stages in 2018 indicated the maps to be ≥93% accurate depending on phenophase. Since their release in early 2018, these maps have been adopted by tree care specialists and foresters across the United States. Using a consultative mode of engagement, USA-NPN staff have continuously sought input and critique of the maps and delivery from end users. Based on feedback received, maps have been expanded and modified to include additional species, improved descriptions of the phenophase event of interest, and e-mail-based notifications to support management decisions.
|Publication Subtype||Journal Article|
|Title||Short-term forecasts of insect phenology inform pest management|
|Series title||Annals of the Entomological Society of America|
|Contributing office(s)||National Phenology Network|
|Google Analytic Metrics||Metrics page|