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Ecology and Epidemiology

Spatial Heterogeneity of the Incidence of Grape Downy Mildew. L. V. Madden, Department of Plant Pathology, Ohio Agricultural Research and Development Center, The Ohio State University, Wooster 44691; G. Hughes(2), and M. A. Ellis(3). (2)Institute of Ecology and Resource Management, University of Edinburgh, W. Mains Rd., Edinburgh EH9 3JG, Scotland; (3)Department of Plant Pathology, Ohio Agricultural Research and Development Center, The Ohio State University, Wooster 44691. Phytopathology 85:269-275. Accepted for publication 18 November 1994. Copyright 1995 by The American Phytopathological Society. DOI: 10.1094/Phyto-85-269.

Heterogeneity of the incidence of downy mildew of grape, caused by Plasmopara viticola, was quantified in an experimental Ohio vineyard. The proportion of diseased leaves on each of 15 shoots (sampling units) per plot was determined for 18 separate plots at two times (generally August and September) during each of 3 yr. The binary data analogue of Taylorís power law, in which the logarithm of the observed variance is regressed on the logarithm of the theoretical variance for a binomial (random) distribution, provided strong and consistent evidence that diseased leaves were aggregated. Year and assessment time did not affect power law parameters. The estimate of the regression slope (b), an overall measure of heterogeneity, was 1.30 (SE = 0.04). Heterogeneity in individual plots was measured with variance ratio and C(α) tests and with the aggregation parameter (θ) of the beta-binomial distribution fitted to the data. Except for mean incidence less than 0.05, the majority of the plots had significant heterogeneity, and the data were better described by the beta-binomial than by the binomial distribution. Estimates of θ were variable but were highest in the middle range of disease incidence. Using the modified power law, sampling curves were generated to precisely estimate disease incidence.

Additional keywords: extra-binomial variation, overdispersion, quantitative epidemiology, spatial analysis.