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Integrating Technology to Assist the Weed Risk Assessment Process

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

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Integrating Technology to Assist the Weed Risk Assessment Process

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  1. 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

  2. Overview • PERAL Weed Team • Technologies to support the WRA process • Caveat: Invasive plant = weed

  3. Mission statement:To provide scientific and analytical support for PPQ regulatory programs requiring decisions associated with invasive plants. PERAL Weed Team

  4. Activity areas Importation: Help complete WRAs to support decision making related to imports Exportation: Provide technical assistance to guard against US exports being unduly restricted by trading partnersDomestic: Support surveying, monitoring, and management

  5. Weed Team activities • Identify invasive plant problems/issues • 2. Set priorities • 3. Gather data (not research) • 4. Perform weed risk assessments (WRAs) • 5. Recommend risk management strategies We work cooperatively with● Other CPHST labs● National APHIS Weed Team

  6. Technologies to assist WRAs • Prioritization • Pathway monitoring/verification • Potential for geographic spread

  7. 1. Prioritization • Project with Weed Science Society America • Model ranking of global weeds not known to occur in U.S. • 550+ weeds scored comprehensively • Includes spp. present but not naturalized

  8. Prioritization: applications • Choose best candidates for possible listing as noxious weeds (WRAs) • Rapid scoring (relatively) for newly emerging/introduced species • Identify likely target species for surveying, especially species in cultivation

  9. 2. Pathway monitoring/verification • Problem:

  10. Pathway monitoring/verification • AIMS: Agricultural Internet Monitoring System • NC State: Center for Integrated Pest Mgt. • Identify regulated species of interest • Secure web application • Semi-automates: • Webcrawling • Evaluating sites for risk • Sending information letters • Archiving and retrieving information

  11. Pathway monitoring/verification • Monitored organisms • APHIS-regulated • Insects/mollusks/weeds/fruits and vegetables • Animal products & byproducts • APHIS-nonregulated organisms (esp. invasive plants) • Application to WRAs • Identify presence in the U.S. • Identify trade pathways from overseas

  12. AIMS and FAST technology • 1496 names = 599 species + 897 common/syns • Manual search • 2 min × 10 hits × 2 min processing= 549 person hr • FAST • 3 d to search the net and build index (software) • 12.5 min to process index list • Simultaneous search for commerce keywords • Thus, person hr only for processing very likely hits

  13. 3. Potential geographic spread • Model to predict extent of plant invasions in U.S. • NAPPFAST: NCSU/APHIS Plant Pest ForecAST • 10 year climate database (1994-2004) • Typical parameters • Optimal growing days • High T growth inhibition • Cold T exclusion area • Output = Probability map

  14. YOU ARE HERE Example application • Preliminary assessment for kikuyugrass (Pennisetum clandestinum) D. Borchert, B. Nietschke, C. Thayer and L. Fowler

  15. Potential spread: applications • Assess consequences of introduction • Higher risk = greater, contiguous, or special areas • Lower risk = lesser or non-contiguous areas • Factor in invasiveness scoring • Survey targeting (if WRA-related) • Identification of weed-free areas • But, often lack relevant biological data

  16. Technologies to assist WRAs • Prioritization – Plant invasiveness ranking model • Pathway monitoring – AIMS searches • Potential spread – NAPPFAST geographic model

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