Submitted to: Meeting Abstract
Publication Type: Abstract only
Publication Acceptance Date: 11/18/2003
Publication Date: 1/14/2004
Citation: French, B.W. 2004. Spatial distribution of diabrotica in the south dakota areawide management site. Abstracts, 10th IWGO Diabrotica Subgroup Meeting, January 14-16, 2004, Engleberg, Switzerland. p. 61. Interpretive Summary:
Technical Abstract: Western corn rootworms (WCR, Diabrotica virgifera virgifera LeConte) are serious economic pests of maize (Zea mays L.) in the U.S. Corn Belt, and have adapted to traditional management strategies such as crop rotation and insecticides. Even so, soil insecticides often are used indiscriminately to control WCR. In order to minimize the use of insecticides and protect the environment, the United States Department of Agriculture, Agricultural Research Service implemented a corn rootworm areawide pest management program in 1996. This program was established in five geographic locations, four in the U. S. Corn Belt (Iowa, Illinois/Indiana, Kansas, and South Dakota) and one in Texas. We used Geographical Information Systems (GIS) to study the spatial relationships of WCR in the South Dakota Areawide Management Site from 1997 ' 2001. Each field was georeferenced using global positioning systems (GPS). Pherocon AM yellow sticky traps were used to capture WCR. We also used GPS to georeference all sticky traps. For each year, we calculated landscape metrics on continuous maize, first year maize, and all maize. These metrics included number of patches, percent of landscape, cumulative area, mean area, proximity index, and nearest neighbor distance. Based on WCR captured in the sticky traps, we used the inverse distance weighted interpolation technique to create raster map layers of WCR spatial distribution, and focused our analyses on the interpolated maps in relation to topography, soil type, crop type, and landscape metrics. We found significant relationships of WCR spatial distribution with crop type, soil type, and elevation. We also found significant correlations of WCR distribution with several landscape metrics. Our research emphasizes the potential role for GIS and landscape analyses in insect pest management. Larger geographic areas can easily be incorporated into GIS and managed by finding patterns in the landscape that promote high pest population densities.