Species directory link documentation	First adult emergence	First egg hatch	Current stages and generations	No. of generations per year
1. ALB Asian longhorned beetle Anoplophora glabripennis model spreadsheet
2. ASRB Asiatic rice borer Chilo suppressalis model spreadsheet
3. CGN Honeydew moth Cryptoblabes gnidiella model spreadsheet white paper
4. EAB2 Emerald ash borer Agrilus planipennis model spreadsheet peer-review pub.
5. ECW Egyptian cottonworm Spodoptera littoralis model spreadsheet white paper
6. FCM False codling moth Thaumatotibia leucotreta model spreadsheet white paper
7. JPB Japanese beetle Popillia japonica model spreadsheet white paper
8. JPSB Japanese pine sawyer beetle Monochamis alternatus model spreadsheet white paper
9. LBAM Light brown apple moth Epiphyas postvittana model spreadsheet peer-review pub.
10. OAB Oak ambrosia beetle Platypus quercivorus model spreadsheet white paper
11. OWBW Old world bollworm Helicoverpa armigera model spreadsheet
12. PTLM Pine tree lappet moth Dendrolimus pini model spreadsheet white paper
13. SLF Spotted lanternfly Lycorma delicatula model spreadsheet white paper
14. SLI Cotton cutworm Spodoptera litura model spreadsheet
15. SLYM Silver Y moth Autographa gamma model spreadsheet white paper
16. STB Small tomato borer Neoleucinodes elegantalis model spreadsheet white paper peer-review pub.
17. SUNP Sunn pest Eurygaster integriceps model spreadsheet white paper
18. TABS Tomato leafminer Tuta absoluta model spreadsheet white paper

Summary An improved understanding of where an invasive species could potentially establish as well as when developmental stages are expected to occur have the potential to support and dramatically improve strategic and tactical pest surveillance and management decisions. We have developed a spatial modeling platform that integrates mapping of phenology and climatic suitability in real-time to provide timely and comprehensive guidance on where and when invasive insect species could potentially invade the conterminous United States. The DDRP platform serves as an open-source and relatively easy-to-parameterize decision support tool that can predict the potential distribution, number of generations, life stages present, and dates of phenological events of a target species.

About DDRP is written entirely in R, making it flexible and extensible, and capitalizes on multiple R packages to generate gridded and graphical outputs. Currently we are using DDRP to model 15 high-priority invasive insect species (see below), but its process-based modeling approach may be adapted for a broad spectrum of organisms with temperature-dependent development. The DDRP platform will enhance efforts to prevent, monitor, and manage new and emerging invasive pests in the United States.

Publications

1. DDRP: Real-time phenology and climatic suitability modeling of invasive insects, PLoS One. Barker et al. (2020)  
2. Surveillance for early detection of high-consequence pests and pathogens, [Chap. 5] in: Tactical Sciences for Biosecurity of Animal and Plant Systems, Cardwell and Bailey, eds. Bowers et al. 2022
3. An integrative phenology and climatic suitability model for emerald ash borer, Frontiers in Insect Science. Barker et al. (2023)
4. Phenological mapping of invasive insects: Decision support for surveillance and management, MDPI Insects. Barker and Coop (2024)

Selected Presentations

1. Barker, B. S. 2023. Real-time forecasts of phenology and climate suitability for emerald ash borer. Webinar for the EAB University, Apr. 13, 2023. 1 hr presentation
2. Barker, B. S., L. Coop, and T. Crimmins. 2022. DDRP: a modeling tool to forecast insect phenology and risk of establishment. Oral presentation at the Ecological Forecasting Initiative conference, May 23, 2022. 8 min. presentation
3. Coop, L. and B. Barker. 2022. Boxwood blight management: a decision support tool for infection and establishment risk. American Phytopathological Society Annual Meeting. Pittsburgh, PA. Aug 7, 2022. 10 min. presentation

Acknowledgements This work was funded by grants including the USDA APHIS PPQ Cooperative Agricultural Pest Survey (CAPS) and Science and Technology programs, the USDA National Institute of Food and Agriculture (NIFA) AFRI grant no. 2022-68013-37138, the NIFA Crop Protection and Pest Management, Applied Research and Development Program (NIFA-CPPM-ARDP), grant no. 2014-70006-22631, the Western Region IPM Center as a Signature program, and the Department of Defense Strategic Environmental Research and Development Program (SERDP), project no. RC01-035. Dan Upper provided spatial weather data processing and systems administration for the project.

Last updated on Apr 11 2025