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Joint AESAN/EFSA Workshop ‘Science Supporting Risk Surveillance of Imports’ - 10 February 2010, Seville (Spain)
Risk analysis applications of the NCSU APHIS
Plant Pest Forecasting System (NAPPFAST)
Fowler, Glenn A
Magarey, Roger D
Plant Epidemiology and Risk Analysis Laboratory, Animal and Plant Health Inspection
Service (APHIS) North Carolina State University (NCSU) Raleigh (United States)
The North Carolina State University (NCSU) Animal and Plant Health Inspection Service (APHIS) Plant Pest Forecasting System (NAPPFAST) is an internet based mapping system (www.nappfast.org). The system is maintained by the data management company ZedX, Inc. NAPPFAST allows users to rapidly access extensive climate data, run predictive models and export maps that can inform regulatory decisions. NAPPFAST consists of three components: 1) a graphical user interface, 2) databases and 3) model templates. The graphical user interface allows a user to construct models, generate predictive maps and export map outputs as pdfs or geotiffs. The databases include global daily climate data grids, a North American station database, and derived climate grids such as plant hardiness zones and landcover. Available model templates include: 1) degree day for phenology models, 2) infection for plant pathogens, 3) generic for Boolean climate parameter queries and 4) climate tool for selecting upper and lower climate variable limits. NAPPFAST generates climate maps at resolutions of 10 km for North America and 32 km globally. The maps are generated based on user defined start and end dates. NAPPFAST has four types of outputs: 1) history maps, 2) probability maps, 3) average history maps and 4) climate tool maps. The history maps visualize model results for a specific year from 1978 to present. The probability maps generate model results in terms of frequency of occurrence based on 10, 20 or 30 climatology. The average history maps visualize model results based on average 10, 20 or 30 year climatology. The climate tool maps visualize global areas of climate match based on selected parameters. NAPPFAST is applicable to many areas of regulation including: 1) survey and detection, 2) climate characterization for risk assessment, 3) pathway analysis, 4) organism and economic analysis, and 5) emergency operations. Future NAPPFAST developments include: 1) a new interface (NAPPFAST-OBS) that allows for model output and pest occurrence overlays, 2) 10 km global mapping resolution and 3) a global analyst application with improved climate matching tools. For information on accessing NAPPFAST please contact: Dr. Roger Magarey ([email protected]) and/or Dr. Dan Borchert ([email protected]).
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Risk Analysis Applications of the NCSU APHIS Plant P t F ti S t (NAPPFAST)Pest Forecasting System (NAPPFAST)
Glenn Fowler and Roger MagareyUSDA-APHIS-PPQ-CPHST-PERAL
Raleigh, NC
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
I. Introduction to NAPPFASTConcept of the late Dr. Jack Bailey
Cooperative agreement between NCSU and APHIS
System is maintained by ZedX, Inc.
Dr. Roger Magarey and Dr. Dan Borchert spearheaded its creation and continuing evolution
www.nappfast.org
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Components and Operation
1) Graphical User InterfaceInterface
2) Databases
3) Templates
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Graphical User InterfaceSetup: model creationHistory: model requests and resultsObservation: combines pest occurrence with model outputs (now on new site)Forecast: not activeTools: additional data l d f tilayers and functions
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
DatabasesClimate data comes from NOAAPORT
North America: daily climate d t t 10 k l tidata at a 10 km resolution
Global: daily climate grid data atGlobal: daily climate grid data at 32 km resolution (NCEP reanalysis II)y )
Generate maps using 1, 10, 20 or 30 year climatology
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Template: Degree Day
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Template: Infection
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Template: Generic
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Template: Climate Tool
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Outputs1) History map: model output for a specified year’s
selected date range
2) Probability Map: frequency of selected events over 10, 20 or 30 years for a selected date range20 or 30 years for a selected date range
3) Average History Map: average accumulated model ) g y p goutput for 10, 20, or 30 years for a selected date range
4) Climate Tool Map: climate match map shows areas that match selected parameters
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Output: History Map
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Output: Probability Map
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Output: Average History Map
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Output: Climate Tool
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
II. NAPPFAST Applications
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Survey and Detection
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Climate Characterization for Risk Assessment
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Pathway AnalysisM ean = 10.526 95% <=245% <=2
0.06
0.07
0.08
0.04
0.05
Prob
abili
ty
0.01
0.02
0.03 P
0.000 5 10 15 20 25 30 35 40 45 50 55
Ships
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Organism and Economic Analysis
0.8
0.9
1.0
0.5
0.6
0.7
e P
roba
bilit
y
Pear Mean = 4 890 000
0.2
0.3
0.4
Cum
ulat
ive Pear Mean = 4,890,000
Apple Mean = 23,437,000Grape Mean = 30,760,000Orange Mean = 45,194,000
0.0
0.1
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80
C t i MilliCost in Millions
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Emergency Operations
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
III. Future Developments
1) NAPPFAST-OBS Interface
2) 10 km Global Database
3) Global Analyst: tools for climate matchingmatching
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
IV. Access and ContactsDr. Roger [email protected]
Dr. Dan [email protected]
United States Department of AgricultureAnimal and Plant Health Inspection Service
Plant Protection and Quarantine
Acknowledgements• Dan Borchert: USDA-APHIS-PPQ• Turner Sutton: NCSU• Matt Dedmon: ZedX, Inc.
• Xu Yan: USDA-APHIS-IS• Gary Lougee: USDA-APHIS-PPQ• Yu Takeuchi: USDA-APHIS-PPQ,
• Joe Russo: ZedX, Inc.• Eric Hudish: ZedX, Inc.• Jack Simpson: Biosecurity Australia
• Jonathan Jones: USDA-APHIS-PPQ• Lynn Evans-Goldner: USDA-APHIS-PPQ• Claude Knighten: USDA APHIS PPQ• Jack Simpson: Biosecurity Australia
• Manuel Colunga-Garcia: MSU• Dan Fieselmann: USDA-APHIS-PPQ
• Claude Knighten: USDA-APHIS-PPQ
• Alison Neeley: USDA-APHIS-PPQ• Brian Spears: USDA-APHIS-PPQ• Bill Smith: U.S. Forest Service• Ross Meentemeyer: UNCC• Ron Sequeira: USDA-APHIS-PPQ• Michael Simon: USDA-APHIS-PPQMichael Simon: USDA APHIS PPQ• Weyman Fussell: USDA-APHIS-PPQ• Andrea Sato: USDA-APHIS-PPQ