Taming Uncertainties in Multi-Scale Pest and Disease Model and Decision Support Tools for Plant Biosecurity

Award number: 2006-55605-16662Period of Funding: Jan. 2006 – Dec. 2008

Primary Institution: Oregon State UniversityProject Director: Leonard B. Coop

Other Principle Investigators:Chris Daly Oregon State University daly@coas.oregonstate.eduAlan Fox Fox Weather alan@foxweather.comDave Gent USDA-ARS gentd@onid.orst.eduGary Grove Washington State University grove@wsu.eduDoug Gubler University California, Davis wdgubler@ucdavis.eduPaul Jepson Oregon State University jepsonp@science.oregonstate.eduWalter Mahaffee USDA-ARS mahaffew@science.oregonstate.eduWilliam Pfender USDA-ARS pfenderw@onid.orst.eduGeorge Taylor Oregon State University taylor@oce.orst.edu

Taming Uncertainties in Multi-Scale Pest and Disease Model and Decision Support Tools for Plant Biosecurity

Goal: To document the uncertainties and errors associated with all aspects of disease modeling, while building a system that can serve both plant biosecurity and integrated pest management (IPM) needs in the Western US. - We are presently 18 months into this 3-year program, and have made significant progress in the areas of

1) Spatialized weather forecasting systems relevant to plant disease modeling needs

2) Infrastructure for pest and plant disease modeling3) Targeted climatologies4) Field validations and uncertainty analyses.

1) Spatialized weather forecasting systems relevant to plant disease modeling needs

Forecast #1 – IPPC server S. WA + OR

Forecast #2 – Fox weather server – N. Calif.

Current Forecast Extent

.

10,000+ public weather station data

QA

NOAA GFS/NAMmodel forecasts

Fox Weather/IPPC models+

PRISM Climate models WRF mesoscale model

Kim et al. leaf wetness model

Database of modular pest models

Site-specific pest and disease model-relevant weather forecasts

Web GISUser Interface

1. Plant Biosecurity2. IPM

Process

Inputs

Outputs

1. Plant Disease Forecast System Overview

Uncertainties reports

Uncertainties analysis

100 km 6hr -> 7 days

800m 1hr

36km

Disease model and forecast infrastructure – building upon IPPC/NPDN website tools

Disease

weather

system

prototype

(NPDN)

Fox Weather/IPPC plant

disease weatherforecast

verification system

- day0 to day6 forecasts- near real time entire forecast region

(ex. OR + S. WA)

Online Plant Disease Model Forecast + Evaluation Tool – e. g. comparison of 3 days Fox Weather forecast with actual data for: -apple scab-powdery mildew -temperature-leaf wetness

I grant permission to USDA/CSREES to use this information for communicating about this project.

NRI PRISM-Aided Downscaling Methods and Activities

PRISM GroupPRISM GroupOregon State UniversityOregon State University

An analysis and prediction system is being developed that taps the ability of long-term climatological patterns to inform estimates of current and forecast weather patterns

1971-2000, all-day monthly PRISM Climatologies1971-2000, all-day monthly PRISM Climatologies

E flow example: cyclonic curvatureJune 5, 19931200 UTC

NE flow example:cyclonic curvature February 5, 1989 0000 UTC

Relative importance of 700-mb flow direction in NWOR

Frequency

Precipitation

NW Flow 1971-2000 all-day mean annual precipitationexpressed as a percentage of the domain-wide mean precipitation itation

Percent of the normalized all-day mean annual precipitation

Climo PRISM S (Southerly) 700-mb flow 1971-2000 mean annual precipitation

Percent of the domain-wide precipitation

NW flow 1971-2000 mean annual precipitation climatology (Expressed as percent of the domain-wide precipitation)

700-mb NW flow

Example Targeted Climatology - January 31, 1990 0000 UTC

I grant permission to USDA/CSREES to use this information for communicating about this project.

Field Validation Work(1 of 6 validation partners funded; others seeking additional support)

Crop Coordinating Plant PathologistHops Dave Gent USDA-ARSCherries Gary Grove Washington State UniversityWinegrapes Doug Gubler University California, DavisStrawberries Walter Mahaffee USDA-ARS Grass Seed William Pfender USDA-ARS

-weather data are collected in canopy and at standard heights and positions out of canopy

-for error and uncertainties analysis and development of correction curves for each weather parameter

Taming Uncertainties in Multi-Scale Pest and Disease Model and Decision Support Tools for Plant Biosecurity

1) Spatialized weather forecasting systems relevant to plant disease modeling needs

2) Infrastructure for pest and plant disease modeling3) Targeted climatologies4) Field validations and uncertainty analyses.

Additional and Future efforts: - Planning operational tests of forecasts/models for 2008 in selected tree fruit and grass seed regions- Test of first targeted climatologies system for 2008 in Oregon grass seed- Submitted Areawide IPM proposal to greatly expand operational capability of the system in numerous commodities and regions- Check out APS posters for Western Weather Systems Workgroup, Grass Seed Stem Rust model and uncertainties analysis