Home page and directory of selected Degree-Day, establishment Risk, and Pest event maps (DDRP)

Abstract Rapidly detecting and responding to new invasive species and the spread of those that are already established is essential for reducing their potential threat to food production, the economy, and the environment. We describe a new multi-species spatial modeling platform that integrates mapping of phenology and climatic suitability in real-time to provide timely and comprehensive guidance for stakeholders needing to know both where and when invasive insect species could potentially invade the conterminous United States. The Degree-Days, Risk, and Phenological event mapping (DDRP) platform serves as an open-source and relatively easy-to-parameterize decision support tool to help detect new invasive threats, schedule monitoring and management actions, optimize biological control, and predict potential impacts on agricultural production. DDRP uses a process-based modeling approach in which degree-days and temperature stress are calculated daily and accumulate over time to model phenology and climatic suitability, respectively. Products include predictions of the number of completed generations, life stages present, dates of phenological events, and climatically suitable areas based on two levels of climate stress. Species parameters can be derived from laboratory and field studies, and from published and newly fitted CLIMEX models. DDRP is written entirely in R, making it flexible and extensible, and capitalizes on multiple R packages to generate gridded and graphical outputs. We illustrate the DDRP modeling platform and the process of model parameterization using two invasive insect species as example threats to United States agriculture: the light brown apple moth, Epiphyas postvittana, and the small tomato borer, Neoleucinodes elegantalis. We then discuss example applications of DDRP as a decision support tool, review its potential limitations and sources of model error, and outline some ideas for future improvements to the platform.

Full paper at: Barker et al. (preprint). Open source code at: https://github.com/bbarker505/ddrp_v2.

Species directory link documentation	First spring adults	First egg hatch	No. of generations per year
1. ALB asian longhorned beetle Anoplophora glabripennis model spreadsheet
2. CGN honeydew moth Cryptoblabes gnidiella model spreadsheet white paper
3. EAB emerald ash borer Agrilus planipennis model spreadsheet
4. FCM false codling moth Thaumatotibia leucotreta model spreadsheet white paper
5. JPSB Japanese pine sawyer beetle Monochamis alternatus model spreadsheet white paper
6. LBAM light brown apple moth Epiphyas postvittana model spreadsheet peer-review pub.
7. OAB oak ambrosia beetle Platypus quercivorus model spreadsheet white paper
8. OWBW old world bollworm Helicoverpa armigera model spreadsheet
9. PTLM pine tree lappet moth Dendrolimus pini model spreadsheet white paper
10. SLI cotton cutworm Spodoptera litura model spreadsheet
11. STB small tomato borer Neoleucinodes elegantalis model spreadsheet white paper peer-review pub.
12. SLYM silver Y moth Autographa gamma model spreadsheet
13. TABS tomato leafminer Tuta absoluta model spreadsheet white paper

Acknowledgements This work was funded by grants including the USDA APHIS PPQ Cooperative Agricultural Pest Survey (CAPS) and Center for Plant Health Science and Technology (CPHST) programs, the USDA National Institute of Food and Agriculture, 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.