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A model of the evolution of polygenically controlled fungicide resistance
Author(s) -
SHAW M. W.
Publication year - 1989
Publication title -
plant pathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.928
H-Index - 85
eISSN - 1365-3059
pISSN - 0032-0862
DOI - 10.1111/j.1365-3059.1989.tb01426.x
Subject(s) - fungicide , biology , heritability , population , toxicology , botany , genetics , demography , sociology
A simple model of the evolution of polygenically controlled fungicide resistance is presented. The basic model contains four parameters, all of which are experimentally measurable. The first, β , describes how much a given change in fungicide sensitivity alters the fitness of a clone of the organism in the presence of fungicide. The second, γ , describes the strength of stabilizing selection, which tends to restore sensitivity to an optimal value. The third, σ 2 , specifies the variance in fungicide sensitivity existing among genotypes in the population. The fourth parameter is the heritability, h 2 . of fungicide sensitivity; it applies only to pathogens reproducing sexually. The model suggests that changes in sensitivity of populations to fungicide will only be weakly dependent on the concentration applied, but will be mainly controlled by the slope of the graph for fungicide sensitivity against fitness in the presence of fungicide. Unless stabilizing selection is very strong, it will only slightly modify the rate at which sensitivity changes. Loss of resistance in the absence of the fungicide will be, at most, half as fast as its initial gain. If the heritability, h 2 , is close to 1, annual sexual reproduction will scarcely affect the conclusions drawn above; if h 2 , is small, long‐term changes will be substantially slowed down and a cycle in population fungicide sensitivity may occur within each year. In suitable fungi, limits could be placed on the strength of stabilizing selection by looking for changes in variance in fungicide sensitivity between clones before and after sexual reproduction. Data to test the model are sparse, but do not contradict it.