Dan Borchert and Roger Dan Borchert and Roger MagareyMagarey

NCSU/CPHST/PERALNCSU/CPHST/PERAL

NAPPFASTNAPPFASTNorth Carolina State

UniversityAPHIS Plant Pest ForecAST System

History of NAPPFASTHistory of NAPPFAST Created in response to recommendations Created in response to recommendations

from Safeguarding American Plant from Safeguarding American Plant Resources Review of PPQResources Review of PPQ

Designed to predict potential Designed to predict potential establishment of invasive pest species: establishment of invasive pest species: used for risk analysis and to aid CAPS used for risk analysis and to aid CAPS survey and detection effortssurvey and detection efforts

Developed through an APHIS and NCSU Developed through an APHIS and NCSU cooperative agreement- cooperative agreement- Funded by Funded by CAPS ProgramCAPS Program

NAPPFAST NAPPFAST

Uses generic degree day, infection Uses generic degree day, infection and disease models to examine the and disease models to examine the probability of occurrence of plant pest probability of occurrence of plant pest speciesspecies

Models linked through internet Models linked through internet graphical user interface to 30 year graphical user interface to 30 year national climate database (ZedX Inc.)national climate database (ZedX Inc.)

Worldwide climate database to be Worldwide climate database to be established in 2004established in 2004

Degree Day Background Degree Day Background PrimerPrimer

““Phenology and development of most Phenology and development of most organisms follow a temperature organisms follow a temperature dependent time scale” (Allen 1976)dependent time scale” (Allen 1976)

Attempts to integrate temperature Attempts to integrate temperature and time started 250 + years ago and time started 250 + years ago

Development is widely believed to Development is widely believed to follow a sigmoid shapefollow a sigmoid shape

Dev.

Tem

p.

Degree Day Background Degree Day Background Primer Primer

Organisms have base developmental Organisms have base developmental temperature- temperature- minimum temperature minimum temperature below which no development occursbelow which no development occurs

Organisms have set number of units to Organisms have set number of units to complete development - physiological complete development - physiological time: measured in developmental time: measured in developmental units (DU) or degree days (DD) units (DU) or degree days (DD)

Parameters established from lab or Parameters established from lab or field studiesfield studies

Degree Day Background Degree Day Background PrimerPrimer

Example: Example: Ima pesta Ima pesta

base temperature 10 Cbase temperature 10 C

requires 365 DD to complete requires 365 DD to complete developmentdevelopment

(egg, larvae, pupae, adult to egg)(egg, larvae, pupae, adult to egg)

Degree days are typically calculated from Degree days are typically calculated from average of high and low temperature for average of high and low temperature for a 24 hour period above the base a 24 hour period above the base temperaturetemperature

Degree Day Background Degree Day Background PrimerPrimer

Ima pesta Ima pesta base temperature 10 C base temperature 10 C 365 DD for development365 DD for development

If average daily temp was 11C: 1 DD (11-10) If average daily temp was 11C: 1 DD (11-10) is accumulated and it would take 365 days is accumulated and it would take 365 days at that temperature to complete at that temperature to complete developmentdevelopment

If average daily temp was 20C: 10 DD (20-If average daily temp was 20C: 10 DD (20-10) are accumulated and it would take 10) are accumulated and it would take 36.5 days at that temperature to complete 36.5 days at that temperature to complete developmentdevelopment

Degree Day Background Degree Day Background PrimerPrimer

Estimation of Estimation of accumulated DD is accumulated DD is simple in simple in controlled controlled environment, but environment, but becomes more becomes more complicated in complicated in nature as nature as temperature temperature fluctuations occurfluctuations occur

Graph from UC Davis IPM website

What does this mean to What does this mean to me?me?

Through the use of Through the use of degree day models degree day models we can predict the we can predict the occurrence of pests occurrence of pests or their phenologyor their phenology

More More effective/efficient effective/efficient timing of timing of scouting/trapping scouting/trapping for particular stage for particular stage of interestof interest

Helicoverpa armigera Helicoverpa armigera Old world bollwormOld world bollworm

Highly polyphagous pest- corn, Highly polyphagous pest- corn, cotton, citrus, tomatoes and tobaccocotton, citrus, tomatoes and tobacco

Intercepted numerous times in Intercepted numerous times in inspections 280 ± 12 per year, inspections 280 ± 12 per year, 4,431 since 1985 (52 % JFK airport)4,431 since 1985 (52 % JFK airport)

Pictures from CAB , 2003

P. japonica P. japonica general general informationinformation

Univoltine- one generation per yearUnivoltine- one generation per year Overwinters typically as a third instar Overwinters typically as a third instar

larvaelarvae

Model ParametersModel Parameters

Japanese BeetleJapanese Beetle

      StageStageDD in DD in

stagestageFirst First

entryentrysecond second

entryentry

Overwintering Overwintering stagestage 3rd instar3rd instar 400400 00 400400

PupaePupae 124124 401401 525525

Low 10 CLow 10 C AdultAdult 117117 526526 643643

Upper 34 Upper 34 CC egg egg 140140 644644 784784

first instarfirst instar 222222 785785 10071007

Second Second instarinstar 419419 10081008 14271427

third instarthird instar 720720 14281428

Frequency of Occurrence (30year)

0 0       66

6 6       1212

12 12       1818

18 18       2424

24 24       3030

Frequency of Occurrence (30year)

0 0       66

6 6       1212

12 12       1818

18 18       2424

24 24       3030

Adult beetles begin to emerge in central NC 3rd week in May (Fleming 1972)

Frequency of Occurrence (30year)

0 0       66

6 6       1212

12 12       1818

18 18       2424

24 24       3030

Beetles appear in central Virginia in last week of May- first week of June.(Fleming 1972)

Frequency of Occurrence (30year)

0 0       66

6 6       1212

12 12       1818

18 18       2424

24 24       3030

Mountainous Eastern TN beetles appear first week of June (Fleming 1972)

Beetles appear in central Virginia in last week of May- first week of June.(Fleming 1972)

Frequency of Occurrence (30year)

0 0       66

6 6       1212

12 12       1818

18 18       2424

24 24       3030

Adult beetles begin to emerge in Maryland & Delaware mid June (Fleming 1972)

Frequency of Occurrence (30year)

0 0       66

6 6       1212

12 12       1818

18 18       2424

24 24       3030

Adult beetles begin to emerge in Southern NJ and Southeastern PA in 3rd week of June (Fleming 1972)

Frequency of Occurrence (30year)

0 0       66

6 6       1212

12 12       1818

18 18       2424

24 24       3030

Emergence in mountainous regions of NJ and PA 1-2 weeks later (Fleming 1972)

Emergence in Southeastern NY, CT, RI and Southern MA in last week of June (Fleming 1972)

Frequency of Occurrence (30year)

0 0       66

6 6       1212

12 12       1818

18 18       2424

24 24       3030

Emergence begins in Southern NH and VT in first week of July (Fleming 1972)

Frequency of Occurrence (30year)

0 0       66

6 6       1212

12 12       1818

18 18       2424

24 24       3030

Frequency of Occurrence (30year)

0 0       66

6 6       1212

12 12       1818

18 18       2424

24 24       3030

Background PrimerBackground Primer

Plant pathologist Plant pathologist describe describe interactions interactions between between pathogen, host pathogen, host and and environmental environmental conditions as the conditions as the disease triangle. disease triangle.

Infection is often the rate limiting step in Infection is often the rate limiting step in an epidemic because it requires moisture an epidemic because it requires moisture which is often limited in terrestrial which is often limited in terrestrial environmentsenvironments

Infection can be modeled by a temperature Infection can be modeled by a temperature /moisture response function - a /moisture response function - a mathematical function that describes the mathematical function that describes the response of an organism to temperature response of an organism to temperature and moistureand moisture

Generic infection modelGeneric infection model

ParametersParameters

TTminmin = Min. temperature for infection, = Min. temperature for infection, ooC,C,

TTmaxmax = Max. temperature for infection, = Max. temperature for infection, ooC,C,

TTopt opt = Opt. temperature for infection, = Opt. temperature for infection, ooC,C,

WWmin min = Minimum wetness duration = Minimum wetness duration requirement, h requirement, h

Parameters established in laboratory studiesParameters established in laboratory studies

Temperature response Temperature response functionfunction

0

0.2

0.4

0.6

0.8

1

0 5 10 15 20 25 30 35

Tem

pera

ture

Res

pons

e

Temperature C

High ToptLow Topt

Temperature moisture Temperature moisture response functionresponse function

Low Topt

High Wmin

High Topt

Low Wmin

Examples of pathogensExamples of pathogens

Sudden Oak Death, Sudden Oak Death, Phytophthora ramorumPhytophthora ramorum

Fungal disease in Fungal disease in cool wet weathercool wet weather..

Currently in Currently in Western US: Western US: California and California and OregonOregon

Source Ventana Wilderness Society

Model ParametersModel Parameters

Temperature requirement Temperature requirement

3-28 C, 20 C optimum (Werres, 2001; 3-28 C, 20 C optimum (Werres, 2001; Orlikowski, 2002)Orlikowski, 2002)..

Moisture requirement Moisture requirement

12 hours for zoospore infection 12 hours for zoospore infection (Huberli,2003)(Huberli,2003)

Model description Model description

Unpublished infection model uses Unpublished infection model uses Wang et al. (1998 ) temperature response Wang et al. (1998 ) temperature response function scaled to a wetness duration function scaled to a wetness duration requirementrequirement..

Sudden Oak

Death

Infection

January 1

Wetness > 12 h

Infection

Sudden Oak

Death

April 1

Wetness > 12 hWetness > 12 h

Infection

Sudden Oak

Death

Infection

July 1

Wetness > 12 h

Infection

Sudden Oak

Death

Infection

October 1

Wetness > 12 h

Infection

Sudden Oak

Death

Infection > 30 days

Year

Wetness > 12 h

Sudden Oak

Death

Infection > 60 days

Year

Wetness > 12 h

Smith, USDA-FS

Smith, USDA-FS

Infection > 60 days

SOD SummarySOD Summary ‘‘Seasonal snapshots’ show relative Seasonal snapshots’ show relative

infection risk for different locations and infection risk for different locations and seasons. seasons.

Maps need interpretation with respect to Maps need interpretation with respect to forest health and species composition.forest health and species composition.

The methodology provides an alternative The methodology provides an alternative approach to the Smith method.approach to the Smith method.

Once international data becomes available Once international data becomes available it may be possible to pursue additional it may be possible to pursue additional model validation. model validation.

Generic Disease Model Generic Disease Model

Allows for construction of many different Allows for construction of many different models using simple logical and models using simple logical and mathematical equations: mathematical equations:

(X>A, X and Y, X or Y, X and (Y or Z), (X>A, X and Y, X or Y, X and (Y or Z), X≥A and X≤B, A* exp(B * X), etc.)X≥A and X≤B, A* exp(B * X), etc.)

Some examples used to date are: Some examples used to date are: temperature exclusions (high and or low temperature exclusions (high and or low lethal temperatures), frost free days, and lethal temperatures), frost free days, and emergence dates emergence dates

Pine Shoot Beetle (PSB), Pine Shoot Beetle (PSB), Tomicus piniperdaTomicus piniperda

Overwinters as adult, Overwinters as adult, can emerge as soon can emerge as soon as temperatures as temperatures reach 50-54 F reach 50-54 F

Emerges over a Emerges over a relatively short period relatively short period of timeof time

Important to have Important to have traps out in time but traps out in time but not too earlynot too early

http://www.ncrs.fs.fed.us/4401/focus/climatology/tomicus/

0 0       66

6 6      11

22

1122  

    11

88

1188  

    22

44

2244  

    33

00

Frequency of Occurrence (30 year)

> 40 F

> 45 F

> 50 F

January 1-15

PSB

Benefits of NAPPFASTBenefits of NAPPFAST Ability to create Ability to create

desired models and desired models and rapidly provide rapidly provide information for local information for local or nationwide areas: or nationwide areas: as quick as a few as quick as a few hourshours

Relatively small Relatively small amount of information amount of information required to construct required to construct modelsmodels

A tool to assist CAPS A tool to assist CAPS personnelpersonnel

Additional Map FeaturesAdditional Map Features

Maps are geo-Maps are geo-referenced and can referenced and can be exported into be exported into ArcGIS for further ArcGIS for further customizationcustomization

Occ. of 1st gen. adult H. armigera June 1-7 Major growing areas of corn, tomatoes, cotton and tobacco

+

Union of occurrence and crops

Map featuresMap features Zoomable after double Zoomable after double

click enlargementclick enlargement

Ability to overlay Ability to overlay major crop production major crop production informationinformation

((O. melanopusO. melanopus adult and adult and minor spring wheat minor spring wheat April 1-7)April 1-7)

Models Completed to Models Completed to Date*Date*

InsectsInsects Japanese BeetleJapanese Beetle Cereal Leaf BeetleCereal Leaf Beetle Old World BollwormOld World Bollworm European Grapevine European Grapevine

Moth Moth Leek MothLeek Moth Swede MidgeSwede Midge False Codling Moth False Codling Moth

DiseasesDiseases Wheat RustWheat Rust Downy mildew of Downy mildew of

corncorn Sweet Orange Sweet Orange

ScabScab Citrus black spotCitrus black spot Potato wartPotato wart Sudden Oak Death Sudden Oak Death

* Validation of model output currently being conducted

SummarySummary

NAPPFAST can provide information (maps NAPPFAST can provide information (maps and graphs) to aid in survey and detection and graphs) to aid in survey and detection for CAPSfor CAPS

Output information is customizable for end Output information is customizable for end useruser

A relatively new system – operational but A relatively new system – operational but developing developing

Feedback needed for system improvements, Feedback needed for system improvements, development and maximum utilizationdevelopment and maximum utilization

Interested in Learning Interested in Learning More?More?

Hands on Demonstration Hands on Demonstration session of session of NAPPFASTNAPPFAST

Wednesday, December 3:Wednesday, December 3:

4:30-6:30 pm4:30-6:30 pm

Location TBALocation TBA

www.nappfast.orgwww.nappfast.org

Site contains information on GIS databases, weather data collection, case studies of modeling, Examples of pests examined and references

Project CooperatorsProject Cooperators

CPHSTCPHSTGlenn FowlerGlenn Fowler

Dan FieselmannDan Fieselmann

Woody BaileyWoody Bailey

NCSUNCSUTurner SuttonTurner Sutton

Charles ThayerCharles Thayer

Zed X Inc.

Joe RussoAaron Hunt

Matt Dedmon

Comments, Suggestions Comments, Suggestions and Questionsand Questions

Dr. Roger MagareyDr. Roger Magareyroger.magarey@aphis.usda.roger.magarey@aphis.usda.govgov

919-513-5074919-513-5074

1017 Main Campus Dr1017 Main Campus Dr

Suite 1550 Suite 1550

Raleigh, NC 27606Raleigh, NC 27606

Dr. Dan BorchertDr. Dan Borchertdaniel.m.borchert@aphis.daniel.m.borchert@aphis.usda.govusda.gov

919-513-7051919-513-7051

1017 Main Campus Dr1017 Main Campus Dr

Suite 1550 Suite 1550

Raleigh, NC 27606Raleigh, NC 27606