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OSU/IPPC/NPDN/NRI - Pest Epidemiology Models, Maps and Reports NPDN Epidemiology Committee Leonard Coop & Paul Jepson Oregon State & Purdue University.

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Presentation on theme: "OSU/IPPC/NPDN/NRI - Pest Epidemiology Models, Maps and Reports NPDN Epidemiology Committee Leonard Coop & Paul Jepson Oregon State & Purdue University."— Presentation transcript:

1 OSU/IPPC/NPDN/NRI - Pest Epidemiology Models, Maps and Reports NPDN Epidemiology Committee Leonard Coop & Paul Jepson Oregon State & Purdue University June 07-08, 2007

2  Host  Pathogen  Environment - Local - Local and regional field monitoring and regional field monitoring - First responders - Plant quarantine - Watch lists - Spore trapping - PCR rapid diagnosis - Remote sensing  NPDN database - Modes of transport - Aerobiology - Storm reconstruction - Pest and disease models The Epidemiologist's Diagnostic Toolbox  Host

3 Types of pest epidemiological models Insects/plants: - phenological/degree-day - population and dispersal - crop loss simulation Pathogens: - infection risk - epidemiological and dispersal - crop loss simulation All airborn pests - aerobiology * most amenable to use of generic modeling approaches

4  Currently 52+ IPM and crop models, generic calculator linked to weather data; online since 1996 (52 wea stations)  10,500+ weather station (most hourly or better) data accessed at 15 minute intervals from NOAA + grower networks  Free access; no user fees  Open source computing technologies (LAMP (Linux/Apache/MySQL/Perl-PHP), GRASS GIS/spatial modeling, UMN MapServer/GRASSLinks web user interface  Missing max min temperature data estimated using PRISM near real-time weather interpolation Online IPM Models - IPPC

5 Plant disease risk models:  Risk models generally signal periods when infection can occur, assuming inoculum is present.  Like insects, plant pathogens respond to temperature in a more-or less linear fashion.  Unlike insects, we can measure infection events using degree-hours rather than degree-days.  In addition, many plant pathogens also require moisture at least to begin an infection cycle.

6 Online Models - IPPC NPDN plant disease risk models online: multiple generic risk models + 7,500+ weather stations Model outputs shown w/input weather data for veracity GIS user interface

7 Online IPM Models - IPPC Disease models online – e. g. grass seed stem rust simulator (w/Bill Pfender, USDA) Fungicide efficacy submodel Automatic help window Graphs of disease and crop development Single screen user interface Field sample inputs

8 Weather and Degree-day Concepts  Degree-day models: accumulate a daily "heat unit index" (DD total) until some event is expected (e. g. egg hatch) 38 20 18 32 14 22 20 26 daily: cumulative: 20 70 84 106 126 152 Eggs hatch: 152 cumulative DDs Eggs start developing: 0 DDs 70 o(avg) - 50 o(threshold) =20 DD

9 DD Models map – select weather station from map (example for South Central Region – codling moth model) Weather station selected

10 48-state US Degree-day mapping calculator

11

12 US Degree-day mapping calculator (cont.) Steps used to create degree-day maps

13 Online IPM Models - IPPC - PRISM climate maps used for real-time degree-day modeling since 1999. - A process known as “delta correction” is used to spatialize temperature and degree-day accumulations

14 Example 700 degree-day event for 2006

15 Online IPM Models - IPPC New - date of event phenology maps – we will test if “date” prediction maps are easier to use than “degree-day” prediction maps

16 Integrated GIS Platforms Distributed Integrated Interfaced National Database, Managed locally, distributed nationally

17 - Purdue/CERIS: national NPDN database/repository - Multi-level authorization and security protocols - Dynamic maps linked to reports; custom queries for any keywords - Contact Mike Hill at Purdue Univ. if you don't yet have access

18 Online IPM Models - IPPC Ability to use GWR (geographically weighted regression) to downscale e. g. from medium (4km) to high (100m) resolution

19 Screen shots from interactive CERIS NPDN server showing map layer ported from DD 50 F lay generated at OSU to and ported over to CERIS. at Purdue in Indiana overlayed with SBR observations

20 And the 41 degree day layer

21 And for 32 degree day layer

22 Online IPM Models - IPPC Daily and custom degree-day maps and calculator access available for coterminous USA by state and region

23 Online Pest Models - NPDN/IPPC Thumbnail index pages to base 32, 41, 50 maps of all regions within 48-state US Current year-to-date Deviations from normals year-to- date 30 year historical (normals) year- to-date

24 Online Pest Models - NPDN/IPPC GIF version of daily degree-day maps

25 Online Pest Models - NPDN/IPPC Updated online GIS interface –

26 Online Pest Models - NPDN/IPPC Online GIS interface – new features for 2007: zoom box, layers depend on zoom level Zoom box

27 Online Pest Models - NPDN/IPPC Additional zoom layers: National highways, railroads, higher resolution topography

28 Online Pest Models - NPDN/IPPC Zoom box

29 Online Pest Models - NPDN/IPPC Added zoom layers: major roads, rivers, enclosed water, urban areas, 90 m topography, weather station and place name labels

30 Online Pest Models - NPDN/IPPC Select site DD calculator form Site specific degree- days

31 Online Pest Models - NPDN/IPPC Degree-day and disease risk models available from online GIS interface Forecast weather data

32  IPPC phenology models used increasingly in IPM decision making since the first degree-day calculator went online in 1996.  Example - tree fruit models usage in 2005 > 3,000 runs (table)  Total usage for all cropping systems now over 14,000 model runs/yr  Species – tree fruit pests 1999 2000 2002 2003 2004 2005 (Oct 10)  =====================================================================================  codling moth [apple & pear] 83 1123 2019 2053 2428 1811  western cherry fruit fly 5 120 186 187 230 213  fire blight [apple & pear] 17 300 699 1115 778 560  obliquebanded leafroller 15 108 557 320 271 110  apple scab infection season 11 101 139 130 78 81  pear scab infection season 0 0 368 343 330 268  Apple maggot 1st emerge 0 0 0 0 40 72  Apple maggot percent emerge 0 0 0 0 20 40

33 Future Online Models Full proposed system for a multi-crop National biosecurity and IPM weather-driven pest and disease risk alert system, Western Region Weather Systems Workgroup, NRI Plant Biosecurity funding

34 Online Models - IPPC New modified fuzzy logic leaf wetness estimation for disease risk models – contract with Fox Weather LLC Blue-sensor Yellow-FLLW Red-FLLW+down-slope drying+rain effects

35 MtnRTemps (wea. forecast model) Mean dewpoint, temp. + + => Gridded maplayers (to 5-7 days) of: 1. Hourly leaf wetness (LW) 2. Tmean for each hour of LW periodneeded for input into Spatialized disease risk forecasts (w/ Fox Weather LLC) Spatialized Disease Model Forecasts CALMET (wind model) PRISM (climate maps) + Fuzzy Logic Leaf Wetness model (Kim et al, Fox weather LLC)

36 IPPC Weather Modeling system description  Open source computing technologies (LAMP (Linux/Apache/MySQL/Perl-PHP) web serving, GRASS GIS/spatial modeling, UMN MapServer/GRASSLinks web user interface)  State-of-the-art models: climate data sets (PRISM, modified PRISM), several global dynamic forecast models (GFS, NAM, AVN), orographic/terrain modification models (CALMET, MtnRTemps, mesoscale weather models), modified Fuzzy Logic Leaf Wetness estimation model  Algorithms include PRISM-based delta correction and geographically weighted regression interpolation and downscaling, hi-resolution elevation data (30 & 100 m)  Developed and maintained by OSU IPPC (Integrated Plant Protection Center), which has a long history of providing free online agricultural decision support tools

37 The epidemiologist's investigative toolbox has potential to help detect anomalies/solve problems (when, where & how) of pest invasions. Adding environmental factors from disease triangle (for our needs) requires effort. CERIS NPDN data and numerous pest and disease models are now available separately and together for custom queries and to explore the influence of environmental (weather related) factors on pest outbreaks. Some pest model categories (especially degree-day and plant disease infection risk) are amenable to generic, widely applicable uses. Expertise from different groups can be complementary and combined for most efficient use of resources. Recent improvements to our Grasslinks web GIS interface bring more power to associate NPDN records with geophysical attributes such as land use, topography, and transportation routes. Summary: Epidemiology maps and reports:


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