Fort Collins and Phoenix Lab Director
CAPS Survey and Diagnostic Methods
CPHST scientists developed an interactive table of approved methods for survey and identification/diagnostics for Cooperative Agricultural Pest Survey (CAPS) target pests. The information was compiled by performing comprehensive literature searches and consulting with U.S. and international subject matter experts. The table includes 119 pest datasheets; each datasheet includes specific survey and identification information and relevant references for each pest. Cooperators at Purdue University developed the table into a web-based format which is posted on the CAPS website. The interactive table will provide guidance to CAPS surveyors by providing the most effective methods for an early detection survey and will increase the homogeneity of the CAPS survey dataset. In addition, the information can be used by the National CAPS Committee and CPHST to identify gaps in survey and diagnostic tools.
Revision of Exotic Wood Borer and Bark Beetle (EWB/BB) National Survey Manual
CPHST is in the process of revising the EWB/BB Survey Manual, which is a key survey for the Cooperative Agricultural Pest Survey (CAPS) program. The revision includes a review of the pest list, including the addition of 12 new pests. CPHST is providing additional information to the pest datasheets within the manual, including developing species-specific visual survey protocols for target pests that do not have chemical attractants identified. In addition, CPHST is adding new sections to the existing pest datasheets to provide more detailed information to the surveyors.
CAPS Commodity-based Survey Documents
A series of survey references and survey guidelines are being developed for the Cooperative Agricultural Pest Survey (CAPS) program. The Commodity-based Survey References consist of a series of pest sections containing detailed information on the biology, host-range, distribution, survey, and identification of the pest in appropriate detail for CAPS surveyors. The second document, the Commodity-based Survey Guidelines, provides guidelines for survey and identification for a smaller number of pests, determined by a subcommittee of the CAPS National Committee. The methods are intended to increase homogeneity of the national data set and increase the statistical confidence in negative data (e.g., demonstration of “free from” status). Commodity documents for cotton, potatoes, and stone fruits are currently under development.
Trap and Lure Statements of Work for CAPS Target Species
CPHST scientists completed statements of work for five lure combinations and four trap designs for target species in the Cooperative Agricultural Pest Survey (CAPS) program. Statements of work outline product specifications that ensure that the correct product is being purchased for the program and that quality assurance and quality controls are met. Scientists at the CPHST Gulfport Lab are in the process of developing chemical testing protocols to ensure the quality of lures used by PPQ. CPHST will continue to write statements of work for new products and review older documents to ensure that CAPS and other PPQ programs have effective products for surveys.
Asian Gypsy Moth Trapping Survey
Asian gypsy moth ( Lymantria dispar ssp., AGM) is an exotic pest that has been detected, but not established in the United States. The threat to American agriculture is significant due to AGMs broad range of host plants, including 500 species of trees and shrubs, and the female moths' ability to fly. A primary pathway of introduction into America is via ship and cargo traffic from the Far East. These trade patterns place the western United States in high risk of AGM introduction. The states of Washington, Oregon, and California has comprehensive surveillance systems in place to identify (and eradicate if necessary), any moths prior to establishment. The trapping system is organized and managed with expert local knowledge, and places higher trap densities near major shipping ports and population centers. To enhance the placement of traps in these states, a geospatial model has been developed to predict areas with the highest AGM introduction risk based on maritime, transportation, population, and environmental variables.