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Analysis of the Spatial Patterns of Pierce's Disease Incidence in the Lower San Joaquin Valley in California

First and second authors: U.S. Department of Agriculture-Agricultural Research Service (USDA-ARS), San Joaquin Valley Research Center, Parlier, CA; third author: USDA Animal and Plant Health Inspection Service (APHIS), Mission, TX; and fourth and fifth authors: University of California Cooperative and Extension, Bakersfield

The incidence of Pierce's disease (PD), caused by Xylella fastidiosa, was monitored in 11 naturally infested commercial vineyards to determine the presence of an X. fastidiosa vector, Homalodisca coagulata (glassy-winged sharpshooter [GWSS]), to examine the spatial patterns of the disease and elucidate possible influences of surrounding environments. Disease incidence ranged from <1 to 65% among vineyards in 2001. Our efforts to trap or capture potential disease vectors have indicated that the GWSS is the most likely vector. Disease incidence doubled in most vineyards during the 2002 production season. Spatial patterns of symptomatic vines in 2001 and 2002, as determined by ordinary runs analysis, showed strong evidence for within- and across-row aggregation of infected vines. In most fields, they were no disease gradients observed relative to GWSS source (e.g., citrus). Within fields, however, disease incidence displayed strong spatial dependence and a high degree of anisotropy, indicating strongly aggregated patterns of disease with distinct directional orientation. The within-row (0°) and across-row (90°) orientations generally were the predominant directions of increased disease incidence, consistent with vine-to-vine spread of X. fastidiosa. We concluded that the distribution of PD in vineyards reflected the feeding pattern of vectors carrying X. fastidiosa. Based on these results, effective PD management is likely to be based on practices that reduce significant insect vector populations and remove infected vines as soon as identified and on the use of resistant cultivars.

Additional keyword: geostatistics.