Chaos in Biological Control Systems

It has been known for some time that the population densities of insect pests in nature show wide fluctuations over time, but whether these fluctuations represent chaotic dynamics or are the result of environmental noise superimposed on steady cycles remains open to question. We have carried out a theoretical case study of the dynamics of European corn borer populations, using field and laboratory data to construct models that simulate field conditions to learn which variables govern chaotic behavior. We show that small changes in parameters affected by weather can cause a steady cycle to become wild and unpredictable. Most importantly, from a practical point of view, when the chaotic state is reached the population of corn borers can reach values higher than it does in a stable cycle. We find this to be true whether the biological control agent is a natural pathogen of the corn borer (Model I) or the same, widely occurring pathogen plus a toxin, produced either by a genetically engineered plant parasite or a genetically engineered host plant (Model II). This behavior might not be observable in limited field trials, depending on the particular environmental conditions. Before releasing new biological control agents into large open fields, it would seem advisable to investigate their behavior in laboratory microcosms where the variables, including those shown in our models to be capable of inducing chaos in corn borer populations, can be controlled at will.