1 expect the best dan borchert- entomologist usda/aphis/ppq/cphst/peral raleigh, nc
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1Expect The Best
Dan Borchert- EntomologistUSDA/APHIS/PPQ/CPHST/PERAL
Raleigh, NC
http://www.nappfast.org
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NAPPFAST System Overview• Internet-based Pest Prediction System• Biological model (Degree day, Disease Infection,
or Multi-function) templates paired with large climate database (~2000 stations in NA)
• Produce geo-referenced output maps• Designed to assist pest
survey detection efforts:
predict when and where
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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
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The Purpose of NAPPFAST
• To assist the Cooperative Agricultural Pest Survey (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
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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
Dev.
Tem
p.
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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
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Infection Model
• Plant pathologist describe interactions between pathogen, host and environmental conditions as the
disease triangle.
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• 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 (Magarey et al. 2005, Yin et al. 1995, Wang and Engel, 1998)
Generic infection model
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NAPPFAST Summary
• NAPPFAST is a flexible easy to use system with the ability to map multiple organisms
• Combines simple models with large amounts of high quality data
• Model Output is exportable (Geo-tiff) for easy incorporation with other types of Geo-referenced data/Spatial analysis
• Development of Global climate data and additional tools/capabilities will improve the system
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NAPPFAST and Spatial Analysis
Dan Borchert- EntomologistUSDA/APHIS/PPQ/CPHST/PERAL
Raleigh, NC
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Terms and Definitions• GIS: Geographic Information System
• an analytic framework for managing and integrating data; solving a problem; or understanding a past, present, or future situation.
• GPS: Global Positioning System• is a worldwide radio-navigation system formed
from a constellation of 24 satellites and their ground stations
• Spatial Analysis:• Area of GIS that utilizes multiple methods, from
simple to complex
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The Real Life Very Hungry Caterpillar
• Light Brown Apple Moth, Epiphyas postvittana• Feeds on: Apple, Citrus, Tomato, Grape, Potato,
Strawberry, Peach, Carrot, Beans, Broccoli, Pears, many forest types (HUNDREDS of hosts)
• Recently detected • Can we make a risk map to assist in
management efforts? • Quickly?
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Counties with Apples Grown
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Counties with Pears Grown
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Counties with Plums Grown
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Counties with Strawberries Grown
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Counties with Citrus Grown
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All Commodities Added
+ +++
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LBAM Host Density
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Are Hosts the Only Answer?
• Do we need to account for pest biology in addition to host?
• How can that be accomplished?
• Biological event modeling such as Degree day or infection
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Five Generations Averaged
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Standardized Global Plant Hardiness Zones
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LBAM Risk Map
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Observed distribution of Kikuyu grass observations (GBIF green points; literature records black diamonds)
Kikuyu Grass
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NAPPFAST Climate Match for Kikuyu Grass
Kikuyu Grass
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Spatial modeling as a PRA Tool
• The information (data) is becoming more readily available in spatial format
• The ability to combine and utilize multiple types of data for decision support and analysis is a rapidly developing technology
• The ability to view data in a spatial context aids in rapid understanding
