integrating technology to assist the weed risk assessment process
DESCRIPTION
Plant Epidemiology and Risk Analysis Laboratory, Center for Plant Health Science and Technology (CPHST), USDA-APHIS-PPQ. Larry Fowler, Anthony Koop, Brian Spears, and Barney Caton. Integrating Technology to Assist the Weed Risk Assessment Process. Overview. PERAL Weed Team - PowerPoint PPT PresentationTRANSCRIPT
Plant Epidemiology and Risk Analysis Laboratory, Plant Epidemiology and Risk Analysis Laboratory, Center for Plant Health Science and Technology (CPHST), Center for Plant Health Science and Technology (CPHST),
USDA-APHIS-PPQUSDA-APHIS-PPQ
Integrating Technology to Integrating Technology to Assist the Weed Risk Assist the Weed Risk Assessment ProcessAssessment Process
Larry Fowler, Anthony Koop, Brian Larry Fowler, Anthony Koop, Brian Spears, and Spears, and Barney CatonBarney Caton
OverviewOverview
PERAL Weed TeamPERAL Weed Team
Technologies to support Technologies to support the WRA processthe WRA process
Caveat: Caveat: Invasive Invasive plant = weedplant = weed
Mission statement:Mission statement:
To provide scientific and To provide scientific and analytical support for PPQ analytical support for PPQ regulatory programs regulatory programs requiring decisions requiring decisions associated with invasive associated with invasive plants.plants.
PERAL Weed TeamPERAL Weed Team
Importation:Importation: Help complete WRAs to Help complete WRAs to support decision making related to imports support decision making related to imports
Exportation: Exportation: Provide technical assistance to Provide technical assistance to guard against US exports being unduly guard against US exports being unduly restricted by trading partnersrestricted by trading partners
Domestic:Domestic: Support surveying, monitoring, Support surveying, monitoring, and managementand management
Activity areasActivity areas
1.1. Identify invasive plant Identify invasive plant problems/issuesproblems/issues
2. Set priorities2. Set priorities3. Gather data (not research)3. Gather data (not research)4. Perform weed risk assessments 4. Perform weed risk assessments
(WRAs) (WRAs) 5. Recommend risk management 5. Recommend risk management
strategiesstrategies
Weed Team activitiesWeed Team activities
We work cooperatively withWe work cooperatively with● Other CPHST labs● Other CPHST labs● National APHIS Weed Team● National APHIS Weed Team
Technologies to assist WRAs Technologies to assist WRAs
PrioritizationPrioritization
Pathway monitoring/verificationPathway monitoring/verification
Potential for geographic spreadPotential for geographic spread
1. Prioritization1. Prioritization Project with Weed Science Society AmericaProject with Weed Science Society America Model ranking of global weeds not known to Model ranking of global weeds not known to
occur in U.S.occur in U.S. 550+ weeds scored comprehensively550+ weeds scored comprehensively Includes spp. Includes spp.
present but present but
not naturalizednot naturalized
## Scientific nameScientific name Common nameCommon name
11 Echinochloa pyramidalisEchinochloa pyramidalis antelope grassantelope grass
22 Ludwigia hyssopifoliaLudwigia hyssopifolia seedbox, primrose willowseedbox, primrose willow
33 Rubus alceifoliusRubus alceifolius giant bramblegiant bramble
44 Lygodium flexuosumLygodium flexuosum maidenhair creepermaidenhair creeper
55 Actinoscirpus grossusActinoscirpus grossus giant bulrushgiant bulrush
66 Sagittaria pygmaeaSagittaria pygmaea pygmy arrowheadpygmy arrowhead
77 Hakea salicifoliaHakea salicifolia willow-leaved hakeawillow-leaved hakea
88 Ligustrum robustumLigustrum robustum tree privettree privet
99 Wikstroemia indicaWikstroemia indica tiebush, Indian stringbushtiebush, Indian stringbush
1010 Senecio inaequidensSenecio inaequidens narrow-leaved ragwortnarrow-leaved ragwort
Prioritization: applicationsPrioritization: applications
Choose best candidates for possible listing as Choose best candidates for possible listing as noxious weeds (WRAs)noxious weeds (WRAs)
Rapid scoring (relatively) for newly Rapid scoring (relatively) for newly emerging/introduced speciesemerging/introduced species
Identify likely target species for surveying, Identify likely target species for surveying, especially species in cultivationespecially species in cultivation
2. Pathway monitoring/verification2. Pathway monitoring/verification
Problem: Problem:
Pathway monitoring/verificationPathway monitoring/verification AIMS: Agricultural Internet Monitoring AIMS: Agricultural Internet Monitoring
SystemSystem• NC State: Center for Integrated Pest Mgt.NC State: Center for Integrated Pest Mgt.• Identify regulated species of interest Identify regulated species of interest • Secure web applicationSecure web application
Semi-automates:Semi-automates:• Webcrawling Webcrawling • Evaluating sites for riskEvaluating sites for risk• Sending information lettersSending information letters• Archiving and retrieving informationArchiving and retrieving information
Pathway monitoring/verificationPathway monitoring/verification
Monitored organismsMonitored organisms• APHIS-regulatedAPHIS-regulated
Insects/mollusks/weeds/fruits and vegetablesInsects/mollusks/weeds/fruits and vegetables Animal products & byproductsAnimal products & byproducts
• APHIS-nonregulated organisms (esp. invasive APHIS-nonregulated organisms (esp. invasive plants)plants)
Application to WRAsApplication to WRAs• Identify presence in the U.S.Identify presence in the U.S.• Identify trade pathways from overseasIdentify trade pathways from overseas
AIMS and FAST technologyAIMS and FAST technology 1496 names = 599 species + 897 common/syns1496 names = 599 species + 897 common/syns Manual searchManual search
• 2 min 2 min × × 10 hits10 hits × × 2 min processing2 min processing = 549 person hr= 549 person hr FASTFAST
• 3 d to search the net and build index (software)3 d to search the net and build index (software)• 12.5 min12.5 min to process index list to process index list• Simultaneous search for Simultaneous search for commerce keywordscommerce keywords• Thus, person hr only for processing very likely hitsThus, person hr only for processing very likely hits
3. Potential geographic spread3. Potential geographic spread Model to predict extent of plant invasions in U.S.Model to predict extent of plant invasions in U.S.
• NAPPFAST: NAPPFAST: NNCSU/CSU/AAPHIS PHIS PPlant lant PPest est FForecorecASTAST• 10 year climate database (1994-2004)10 year climate database (1994-2004)
Typical parametersTypical parameters• Optimal growing daysOptimal growing days• High T growth inhibitionHigh T growth inhibition• Cold T exclusion areaCold T exclusion area
Output = Probability mapOutput = Probability map
Example applicationExample application Preliminary assessment for kikuyugrass Preliminary assessment for kikuyugrass
((Pennisetum clandestinumPennisetum clandestinum))D. Borchert, B. Nietschke, C. Thayer and L. FowlerD. Borchert, B. Nietschke, C. Thayer and L. Fowler
YOU AREHERE
Potential spread: applicationsPotential spread: applications Assess consequences of introductionAssess consequences of introduction
• Higher risk = greater, contiguous, or special areasHigher risk = greater, contiguous, or special areas• Lower risk = lesser or non-contiguous areasLower risk = lesser or non-contiguous areas
Factor in invasiveness scoringFactor in invasiveness scoring Survey targeting (if WRA-related)Survey targeting (if WRA-related) Identification of weed-free areasIdentification of weed-free areas
But, often lack relevant biological dataBut, often lack relevant biological data
Technologies to assist WRAsTechnologies to assist WRAs
Prioritization – Prioritization –
Plant invasiveness Plant invasiveness
ranking modelranking model Pathway monitoring – Pathway monitoring –
AIMS searchesAIMS searches Potential spread – Potential spread –
NAPPFAST geographic NAPPFAST geographic
modelmodel