Dynamically Generated Variability in Plant-pathogen Systems with Biological Control

SUMMARY Using a combination of replicated microcosm experiments, simple nonlinear modelling and model tting we show that unexpected levels of variability can be detected and described in the dynamics of plant disease. Temporal development of damping{oo disease of radish seedlings caused by an economically important plant pathogen, Rhizoctonia solani, is quan-tiied, 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 amongst 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 ampliied as the pathogen spreads from plant to plant. The eeect 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 diierent replicates settle on asymptotes that depend on initial conditions and parameter values. The eeect is further magniied by nonlinear terms in the infection force in the models. A generalisation of the Lyapunov exponent is introduced to quantify the ampliication. 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 ampliication of plant to plant infection, where the control by the antagonist is locally unsuccessful.