Search

The potential for modern biology to identify new sources for genetical, chemical and biological control of plant disease is remarkably high. Successful implementation of these methods within globally and locally changing agricultural environments demands new approaches to durable control. This, in turn, requires fusion of population genetics and epidemiology at a range of scales from the field to the landscape and even to continental deployment of control measures. It also requires an understanding of economic and social constraints that influence the deployment of control. Here I propose an epidemiological framework to model invasion, persistence and variability of epidemics that encompasses a wide range of scales and topologies through which disease spreads. By considering how to map control methods onto epidemiological parameters and variables, some new approaches towards optimizing the efficiency of control at the landscape scale are introduced. Epidemiological strategies to minimize the risks of failure of chemical and genetical control are presented and some consequences of heterogeneous selection pressures in time and space on the persistence and evolutionary changes of the pathogen population are discussed. Finally, some approaches towards embedding epidemiological models for the deployment of control in an economically plausible framework are presented.

Using a contact-process model for the spread of crop disease over a regional scale, we examine the importance of the time scale for control with respect to the cost of the epidemic. The costs include the direct cost of treating infected sites as well as the indirect costs incurred through lost yield. We first use a mean-field approximation to derive analytical results for the optimal treatment regimes that minimize the total cost of the epidemic. We distinguish short- and long-term epidemics. and show that seasonal control (short time scale) requires extreme treatment, either treating all sites or none or switching between the two at some stage during the season. The optimal long-term strategy requires an intermediate level of control that results in near eradication of the disease. We also demonstrate the importance of incorporating economic constraints by deriving a critical relationship between the epidemiological and economic parameters that determine the qualitative nature of the optimal treatment strategy. The set of optimal strategies is summarized in a policy plot, which can be used to determine the nature of the optimal treatment regime given prior knowledge of the epidemiological and economic parameters. Finally, we test the robustness of the analytical results, derived from the mean-field approximation, on the spatially explicit contact process and demonstrate robustness to implementation errors and misestimation of crucial parameters.

Resistance to chemical control is a major impediment to combating many socially and economically important diseases. Theoretical and experimental studies have shown that reducing the intensity of treatment can slow, or even prevent, the invasion of resistance, yet reducing treatment levels also results in a net increase in disease severity. Clearly there is a need to identify control strategies that balance the conflicting aims of resistance management and disease suppression. Using a mathematical model for the dynamics of fungicide resistance in crop pathogens, we present a broadly applicable measure of the performance of chemical control in the presence of resistant pathogen strains. We illustrate how to optimise fungicide performance with respect to the intensity of treatment as a function of the duration of treatment and the fitness of the resistant strain. We find that in the short term, fungicide performance is optimised at high levels of treatment despite rapid selection for resistance, while the long-term optimum performance is achieved when treatment renders the fungicide-sensitive and fungicide-resistant pathogens equally fit. We further present evidence that under prescribed conditions, the ratio of dose size and frequency, and the fungicide mode of action, can have a significant effect on fungicide performance.

Drug and pesticide resistance are among the most pressing problems facing public, animal and plant health today. In order to design effective resistance management strategies it is imperative to identify criteria for the invasion of resistant forms. Two key determinants of the ability of a resistant pest or pathogen to invade are any inherent fitness costs to the resistant subpopulation, and the effect of treatment on the sensitive and resistant subpopulations. For two generic classes of model which encompass many of the standard models in this field, we summarize relative fitness and treatment efficacy via two simple parameters, and demonstrate that invasion of resistance depends critically on a trade-off between them. Thresholds for invasion are derived when the effect of treatment is a constant reduction in the life-history parameters of the pathogen, and when treatment efficacy varies periodically with the repeated application and subsequent decay of the chemical.

Abstract The mycelial growth form of eucarpic fungi allows for a highly effective spatial exploration of the soil habitat. However, understanding mycelial spread through soil has been limited by difficulties of observation and quantification of fungi as they spread through this matrix. We report on a study on the effects of soil structure by altering the soil bulk density, on the spatial exploration of soil by the fungus Rhizoctonia solani using a soil thin-sectioning technique. First we quantified fungal densities in microscopic images (0.44 mm(2)). At this scale, hyphae were either absent, or present as minor fragments, typically occupying less than 1% surface area of the thin section. From contiguous microscopic images we then produced large-scale (6.21 cm(2)) spatial distribution maps of fungal hyphae. These maps were superimposed onto soil structural maps, which quantify the degree of porosity in each microscopic image. Alterations in soil structure by changing the bulk density are shown to affect the distribution of the fungus within the soil. The volume of soil explored by the fungus increased with increasing bulk density. This was associated with a shift from a few large pore spaces to more evenly distributed small-scale pores. Fungal hyphae were present in all porosity classes within each bulk density, including areas that contain less than 5% visible pore space. However, fungal hyphae were more often found in areas with a higher porosity, in particular at low soil bulk densities. The results show that soil structure is a major component in the spatial exploration of soil by fungi.