Biomathematics and Bioinformatics Division, Rothamsted Research, Harpenden, Herts. AL5 2JQ, UK
We first show how to estimate the exponential epidemic growth rate, r, for different combinations of three weather variables. Then we derive a method to quantify the sensitivity of r to a weather variable as a function of the pathogen life cycle variables of latent period, basic reproductive number, and the mean and standard deviation of the sporulation curve. The method can be used to identify the most important weather variable and pathogen life cycle component in terms of epidemic progress. The method is applied to yellow rust, caused by Puccinia striiformis, on winter wheat. We conclude that the most important weather variable for the progress of yellow rust is temperature, followed by dew period and light quantity. By far, the most important pathogen life cycle component is the basic reproductive number, especially at low and high temperatures. This disagrees with the general view that latent period is the most important variable at low temperatures. We discuss explanations of this.
exponential growth rate,