VIEW ARTICLE

Ecology and Epidemiology

Spatial Dynamics of Phymatotrichum Root Rot in Row Crops in the Blackland Region of North Central Texas. M. J. Jeger, Department of Plant Pathology and Microbiology, Texas Agricultural Experiment Station, The Texas A&M University System, College Station 77843, Present address: Tropical Development and Research Institute, London, WC1X 8LU, UK; C. M. Kenerley(2), T. J. Gerik(3), and D. O. Koch(4). (2)(4)Department of Plant Pathology and Microbiology, Texas Agricultural Experiment Station, The Texas A&M University System, College Station 77843; (3)Blackland Research Center, Texas Agricultural Experiment Station, Temple 76501. Phytopathology 77:1647-1656. Accepted for publication 11 May 1987. Copyright 1987 The American Phytopathological Society. DOI: 10.1094/Phyto-77-1647.

The spatial dynamics of Phymatotrichum root rot were mapped in field plots of cotton and soybean at Temple and cotton only at Brandon in the Blackland region of north central Texas in 1984. First symptoms of Phymatotrichum root rot were observed in mid-June, and assessments were made until mid-August. Analysis of the spatial dynamics indicated that the expansion of runs (sequences of diseased plants within rows) was a major component of increase. The spatial patterns of increase were consistent with plant-to-plant spread by hyphal strands in addition to a time-dependent symptom expression corresponding to an underlying distribution of sclerotia. Various analyses were used to describe and quantify the spatial patterns and dynamics of Phymatotrichum root rot. Spatial autocorrelation analyses were used to test the hypotheses of nonrandom spatial patterns of diseased plants within and across rows. The patterns observed indicated that plant-to-plant spread within rows was more important than spread across rows. The influence of neighboring 1-m row segments of plants, both contiguous (within rows) and adjacent (across rows), was evaluated by calculating the relative frequencies that a disease-free segment contained at least one diseased plant after a 7-day interval. A linear regression model was derived to predict the relative frequency of transition in terms of the status (diseased or healthy) of its nearest neighbors. The regression coefficients indicated that the influence of contiguous neighbors was more important than that of adjacent neighbors. The relative frequencies that a run of a given length class extended to a longer class during a 7-day interval were calculated and found to be inversely related to the difference in length between length classes.