Douglas J. Bailey

Dynamically Generated Variability in Plant-Pathogen Systems with Biological Control

Using a combination of replicated microcosm experiments, simple nonlinear modelling and model fitting we show that unexpected levels of variability can be detected and described in the dynamics of plant disease. Temporal development of damping-off disease of radish seedlings caused by an economically important plant pathogen, Rhizoctonia solani, is quantified, with and without the addition of an antagonistic fungus, Trichoderma viride. The biological control agent reduces the average amount of disease but also greatly enhances the variability among replicates. The results are shown to be consistent with predictions from a nonlinear model that exhibits dynamically generated variability in which small differences in the initiation of infection associated with the antagonist are later amplified as the pathogen spreads from plant to plant. The effect of dynamically generated variability is mediated by the interruption of transient disease progress curves for separate replicates by an exponential decrease in susceptibility of the host over time. The decay term essentially ‘freezes’ the dynamics of the transient behaviour so that the solutions for different replicates settle on asymptotes that depend on initial conditions and parameter values. The effect is further magnified by nonlinear terms in the infection force in the models. A generalization of the Lyapunov exponent is introduced to quantify the amplification. The observed behaviour has profound consequences for the design and interpretation of ecological experiments, and can also account for the notorious failure of many biological control strategies through the creation of ‘hot spots’, created by the amplification of plant to plant infection, where the control by the antagonist is locally unsuccessful.

QUANTIFICATION AND ANALYSIS OF TRANSMISSION RATES FOR SOILBORNE EPIDEMICS

The rates of transmission of infection from inoculum or infecteds to susceptible hosts are critical determinants of epidemics, yet no formal experimental methods have been described for their quantification and analysis in spatially explicit epidemics. Replicated microcosms of >400 radish seedlings and with tight control of environmental conditions were exposed to known amounts of inoculum of the fungal plant pathogen Rhizoctonia solani. Spatiotemporal maps of disease progress were used to distinguish between primary and secondary infections and to count changes with time in the number of infected plants and the number of contacts between susceptible and neighboring infected plants. Transmission rates were defined within a compartmental S–I (susceptible–infected) model for plant epidemics and estimated empirically using counts from spatial maps. The transmission rate for primary infection declined with time; the transmission rate for secondary infection rose initially and then declined. We discuss the mec...

The Effect of Heterogeneity on Invasion in Spatial Epidemics: From Theory to Experimental Evidence in a Model System

Heterogeneity in host populations is an important factor affecting the ability of a pathogen to invade, yet the quantitative investigation of its effects on epidemic spread is still an open problem. In this paper, we test recent theoretical results, which extend the established “percolation paradigm” to the spread of a pathogen in discrete heterogeneous host populations. In particular, we test the hypothesis that the probability of epidemic invasion decreases when host heterogeneity is increased. We use replicated experimental microcosms, in which the ubiquitous pathogenic fungus Rhizoctonia solani grows through a population of discrete nutrient sites on a lattice, with nutrient sites representing hosts. The degree of host heterogeneity within different populations is adjusted by changing the proportion and the nutrient concentration of nutrient sites. The experimental data are analysed via Bayesian inference methods, estimating pathogen transmission parameters for each individual population. We find a significant, negative correlation between heterogeneity and the probability of pathogen invasion, thereby validating the theory. The value of the correlation is also in remarkably good agreement with the theoretical predictions. We briefly discuss how our results can be exploited in the design and implementation of disease control strategies.

An Epidemiological Analysis of the Role of Disease-Induced Root Growth in the Differential Response of Two Cultivars of Winter Wheat to Infection by Gaeumannomyces graminis var. tritici

ABSTRACT Epidemiological modeling combined with parameter estimation of experimental data was used to examine differences in the contribution of disease-induced root production to the spread of take-all on plants of two representative yet contrasting cultivars of winter wheat, Ghengis and Savannah. A mechanistic model, including terms for primary infection, secondary infection, inoculum decay, and intrinsic and disease-induced root growth, was fitted to data describing changes in the numbers of infected and susceptible roots over time at a low or high density of inoculum. Disease progress curves were characterized by consecutive phases of primary and secondary infection. No differences in root growth were detected between cultivars in the absence of disease and root production continued for the duration of the experiment. However, significant differences in disease-induced root production were detected between Savannah and Genghis. In the presence of disease, root production for both cultivars was characterized by stimulation when few roots were infected and inhibition when many roots were infected. At low inoculum density, the transition from stimulation to inhibition occurred when an average of 5.0 and 9.0 roots were infected for Genghis and Savannah, respectively. At high inoculum density, the transition from stimulation to inhibition occurred when an average of 4.5 and 6.7 roots were infected for Genghis and Savannah, respectively. Differences in the rates of primary and secondary infection between Savannah and Genghis also were detected. At a low inoculum density, Genghis was marginally more resistant to secondary infection whereas, at a high density of inoculum, Savannah was marginally more resistant to primary infection. The combined effects of differences in disease-induced root growth and differences in the rates of primary and secondary infection meant that the period of stimulated root production was extended by 7 and 15 days for Savannah at a low and high inoculum density, respectively. The contribution of this form of epidemiological modeling to the better management of take-all is discussed.

Epidemiological Analysis of Take-All Decline in Winter Wheat

Take-all dynamics within crops differing in cropping history (the number of previous consecutive wheat crops) were analyzed using an epidemiological model to determine the processes affected during take-all decline. The model includes terms for primary infection, secondary infection, inoculum decay, and root growth. The average rates of root production did not vary with cropping history. The force of primary infection increased from a low level in 1st wheat crops, to a maximum in 2nd to 4th wheat crops, and then to intermediate levels thereafter. The force of secondary infection was low but increased steadily during the season in first wheat crops, was delayed but rose and fell sharply in 2nd to 4th wheat crops, and for 5th and 7th wheat crops returned to similar dynamics as that for 1st wheat crops. Chemical seed treatment with silthiofam had no consistent effect on the take-all decline process. We conjecture that these results are consistent with (i) low levels of particulate inoculum prior to the first wheat crop leading to low levels of primary infection, low levels of secondary infection, and little disease suppression; (ii) net amplification of inoculum during the first wheat crop and intercrop period; (iii) increased levels of primary and secondary infection in subsequent crops, but higher levels of disease suppression; and (iv) an equilibrium between the pathogen and antagonist populations by the 5th wheat, reflected by lower overall rates of primary infection, secondary infection, disease suppression and hence, disease severity.

Percolation-based risk index for pathogen invasion: application to soilborne disease in propagation systems

Propagation systems for seedling growth play a major role in agriculture, and in notable cases (such as organic systems), are under constant threat from soil and seedborne fungal plant pathogens such as Rhizoctonia solani or Pythium spp. Yet, to date little is known that links the risk of disease invasion to the host density, which is an agronomic characteristic that can be readily controlled. We introduce here, for the first time in an agronomic system, a percolation framework to analyze the link. We set up an experiment to study the spread of the ubiquitous fungus R. solani in replicated propagation systems with different planting densities, and fit a percolation-based epidemiological model to the data using Bayesian inference methods. The estimated probability of pathogen transmission between infected and susceptible plants is used to calculate the risk of invasion. By comparing the transmission probability and the risk values obtained for different planting densities, we are able to give evidence of a nonlinear relationship between disease invasion and the inter-plant spacing, hence to demonstrate the existence of a spatial threshold for epidemic invasion. The implications and potential use of our methods for the evaluation of disease control strategies are discussed.

A non-destructive immunoblotting technique for visualisation and analysis of the growth dynamics of Rhizoctonia solani

Immunoblotting combined with computer imaging and a simple, non-linear mathematical model were used to demonstrate the potential of a technique for non-destructive visualisation and analysis of fungal growth of Rhizoctonia solani over the surface of non-sterile sand. Immunoblotting detected actively growing regions of mycelium enabling visualisation of individual hyphae at the colony edge. A zone of active growth was detected expanding radially over time. Active growth did not continue in the centre of the fungal colony leading to the development of a ring of mycelium surrounding the inoculum. Change in the density of actively growing mycelium with distance from the inoculum unit was summarised for each colony at each time by a Gaussian function, describing a wave of actively growing mycelium, symmetrical in density about its centre but differing amongst replicate colonies. The effectiveness of the immunoblotting technique to detect differences in colony growth was tested by comparing the growth of replicate colonies for two contrasting isolates of R. solani. When both isolates of R. solani were grown at 23 °C the amplitude of the wave increased to a maximum and then decayed over time, the location of the centre of the wave moved outwards at a constant rate, whilst the width of the wave increased. Increasing the temperature to 28°, accelerated this intrinsic growth process for one isolate, but retarded growth of the other.