Using GIS technologies to monitor and prevent Phytophthora diseases in southern Middle Tennessee nurseries
The purpose of this thesis project was to develop a geospatial model to determine which nurseries in southern Middle Tennessee would be most at risk for development of Phytophthora diseases. Specific objectives of the project were: to create two geospatial rule-based ecological niche models for Phytophthora species severity risk for nurseries in the southern Middle Tennessee counties of Cannon, Coffee, DeKalb, Franklin, Grundy, Sequatchie, Van Buren, Warren and White, based on the environmental factors of host vegetation, soil drainage, proximity to roads, and integrated moisture index; to validate these models using Phytophthora species isolation occurrences; to create a disease forecast model from an analysis of optimal weather conditions favorable to Phytophthora occurrence and the actual occurrence and non-occurrence at different sampling dates so as to guide the most appropriate integrated pest management techniques. Two rule-based environmental niche models were created to determine areas where Phytophthora diseases would be expected to be the most severe based on host vegetation, soil drainage, proximity to roads, and integrated moisture index. A weighted overlay model gave an overall low risk to the study area, as high risk areas for the different parameters did not overlap. However an accumulative model put a large portion of the study area at moderate and high severity risk of Phytophthora diseases. Samples collected from nine nurseries in Warren County tested the accuracy of the models and the relationship of the individual parameters. Phytophthora was recovered from only five isolates from three nurseries. Four of the five isolates were recovered from host stands outside the nursery. Analysis of the mean number of days for the optimum climate conditions showed no statistical significance between occurrence and nonoccurrence sampling dates. The results of this study showed that a large portion of the study area was at a moderate risk for Phytophthora diseases, however, this region might not have as large a problem of Phytophthora diseases as originally anticipated. Additional research will be needed to validate the accuracy of the models and to determine if Phytophthora species found in surrounding areas pose a threat to field grown ornamentals.
Geographic information science|Plant sciences|Plant Pathology
Katherine A Kilbourne,
"Using GIS technologies to monitor and prevent Phytophthora diseases in southern Middle Tennessee nurseries"
ETD Collection for Tennessee State University.