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Dan Borchert- Entomologist CPHST/PERAL Raleigh, NC

Dan Borchert- Entomologist CPHST/PERAL Raleigh, NC. The Purpose of NAPPFAST. To assist the CAPS Program determine where and when to survey for invasive pest species To provide information on pests (potential distribution, etc.) for risk assessment purposes

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Dan Borchert- Entomologist CPHST/PERAL Raleigh, NC

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  1. Dan Borchert- Entomologist CPHST/PERAL Raleigh, NC

  2. The Purpose of NAPPFAST • To assist the CAPS Program determine where and when to survey for invasive pest species • To provide information on pests (potential distribution, etc.) for risk assessment purposes • To assist APHIS by providing relevant information in Emergency Response situations

  3. The Development of NAPPFAST • Idea originated at NCSU: Dr. Jack Bailey- method for forecasting peanut diseases in NC and the flexible template for disease modeling- 1990’s • Dan Fieselmann and Glenn Fowler worked with Dr. Bailey for several years on project development • Roger Magarey developed the connection between ZedX Inc and NAPPFAST • Dan Borchert joins the NAPPFAST Team

  4. NAPPFAST System Overview • Internet-based Pest Prediction System • Biological model (Degree day, Disease Infection, or Multi-function) templates paired with large climate database • Produce geo-referenced output maps • Designed to assist pest survey detection efforts: predict when and where

  5. Development of Risk Maps • Risk maps developed for CAPS program • Utilize host and biology information to create risk maps • Maps are available for use in development of survey plans • These are the recognized maps for use in the CAPS program • Can be found at www.nappfast.org

  6. CAPS TOP 50 PEST RISK MAPS

  7. Primary Hosts Acreage Divided by Acres per County Secondary Hosts Acreage Divided by Acres per County + *0.34 *0.66 Relative Proportion of Hosts per County 0= No Hosts per county 5= 0.05-0.075 of each acre in that county is composed of host crop 10= 0.75-1.0 of each acre in that county is composed of host crop

  8. NAPPFAST Map: Spodoptera lituraFive Generations and Inverse of Cold Days

  9. Risk Map Spodoptera lituraEqual Weighting of Host and NAPPFAST

  10. NAPPFAST Model Creation Folder system, but less information More Complex More applicable for extensive users NAPPFAST-MAPVIEW Map Viewer Folder System with details Easy to Navigate More applicable for casual users NAPPFAST

  11. NAPPFAST Map View • Easy, rapid site navigation designed for users interested in quick access to information • Contains series of “Canned Probability Maps” for approx. 30 pests • User can zoom in, add commodity overlays, county outlines, interstates and cities to map • Converts the custom map to PDF for easy printing • Map View site can be automatically accessed through the GPDD for coincidental pests Username:aphismap Password:maps2004

  12. NAPPFAST MAPVIEWImportant Points • What models are used to make the maps? • What organisms can be modeled? • What are the different types of maps? • Why use different types of maps? • How do I read and interpret the maps?

  13. NAPPFAST MAPVIEWImportant Points • What models are used to make the predictive maps in NAPPFAST? • Degree Day • Infection • Generic

  14. Temp. Dev. Degree Day Model: Theory • “Phenology and development of most organisms follow a temperature dependent time scale” (Allen 1976) • Attempts to integrate temperature and time started 250 + years ago • Development is widely believed to follow a sigmoid shape

  15. Degree Day Model: Theory • Organisms have base developmental temperature- minimum temperature below which no development occurs • Organisms have set number of units to complete development - physiological time: measured in developmental units (DU) or degree days (DD) • Parameters established from lab or field studies

  16. Degree Day Model • Example: Light Brown Apple Moth base temperature 7.5 C requires ~640 DD to complete development (egg, larvae, pupae, adult to egg) • Degree days are typically calculated from average of high and low temperature for a 24 hour period above the base temperature

  17. Degree Day Model Light Brown Apple Moth: Base temperature 7.5 C 640 DD for generation development If average daily temp was 11C: 3.5 DD (11-7.5) are accumulated and it would take 182 days at that temperature to complete development If average daily temp was 20C: 12.5 DD (20-7.5) are accumulated and it would take 51.2 days at that temperature to complete development

  18. NAPPFAST MAPVIEWImportant Points • What models are used to make the maps in NAPPFAST? • Degree Day • Infection

  19. Disease Infection Model • Plant pathologist describe interactions between pathogen, host and environmental conditions as the disease triangle.

  20. Infection is often the rate limiting step in an epidemic because it requires moisture which is often limited in terrestrial environments Infection can be modeled by a temperature /moisture response function - a mathematical function that describes the response of an organism to temperature and moisture Disease infection model

  21. Disease Infection Parameters • Tmin = Min. temperature for infection, oC, • Tmax = Max. temperature for infection, oC, • Topt = Opt. temperature for infection, oC, • Wmin = Minimum wetness duration requirement, h Parameters established in laboratory studies

  22. Temperature response function Low Topt High Topt

  23. Temperature moisture response function Low Topt High Wmin High Topt Low Wmin

  24. NAPPFAST MAPVIEWImportant Points • What models are used to make the maps in NAPPFAST? • Degree Day • Infection • Generic- Multi-function Model

  25. Multi-function Model • Allows for construction of many different models using simple logical and mathematical equations: (X>A, X and Y, X or Y, X and (Y or Z), X≥A and X≤B, A* exp(B * X), etc.) • Some examples used to date are: temperature exclusions (high and or low lethal temperatures), frost free days, and emergence dates

  26. NAPPFAST MAPVIEWImportant Points • What models are used to make the predictive maps? • What organisms can be modeled? • Which model is used?

  27. Modeling- Point to Consider “ A model is always wrong, but it can help you see the truth” Dr. Fred Gould William Neal Reynolds Professor North Carolina State University Entomology Department

  28. NAPPFAST MAPVIEWImportant Points • What models are used to make the predictive maps? • What organisms can be modeled? • What are the different types of maps?

  29. Map Types: History • History Maps- A snap shot of information Provides detailed information on the pest for the period of time specified (day, month, or year) Do not provide information about other years occurrence Are often used for validation of models or examining a specific years output

  30. Insect Stage 3rd Pupae Adult Egg 1st 2nd JB Watch Observation 3rd June 7 2004

  31. Insect Stage 3rd Pupae Adult Egg 1st 2nd JB Watch Observation 3rd June 14 2004

  32. Map Types: Probability • Probability- Utilizes data from multiple years Information is less detailed, but provides insight into frequency of occurrence through many years for a specific event

  33. Frequency of Occurrence 0  2 2  4 6 4  6   8  10 8  JB Watch Observation Probability Maps • Allow for spatial examination of a particular stage through multiple years for a specified time period • i.e. Where is the adult stage most likely to be occurring during the second week (8-14) in June?

  34. Frequency of Occurrence 0  2 2  4 6 4  6   8  10 8  JB Watch Observation Probability Map for the Third Week of June

  35. Probability of One Generation> 940 DD

  36. Probability of Two Generations> 1580 DD

  37. Probability of Three Generations> 2220 DD

  38. NAPPFAST MAPVIEWImportant Points • What models are used to make the maps? • What organisms can be modeled? • What are the different types of maps? • Why use different types of maps?

  39. Why Different Types? • Able to answer different questions? • What question are you trying to answer? • Establishment • Risk • Time for survey • Start • Optimum • Stop

  40. NAPPFAST MAPVIEWImportant Points • What models are used to make the maps? • What organisms can be modeled? • What are the different types of maps? • Why use different types of maps? • How do I read and interpret the maps?

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