Invasive species threaten agricultural productivity and public health, and may further destabilize the species composition of certain native ecosystems. An invading species' population, by definition, must advance from its point of introduction. Consequently, ecologists and conservation biologists seek a predictive understanding of a successful invader's pattern of spatial growth. The proposed research will address biological invasion as a front moving, with some random variation, through a two-dimensional environment. Both the theory and experimentation will explicitly consider an ecologically superior invader competing with a native, resident species. Details of the model for spatially clustered growth of the two species permit application of the theory of kinetic roughening, developed in statistical physics, to predict the quantitative behavior of the invasion process. The results generate novel hypotheses concerning both the velocity of the invasive front's advance and the relative position of the furthest invasive incursion into the resident's habitat. Expected values of these quantities depend on the length of the invading front; hence they depend predictably on the linear size of the habitat invaded. Once results for a constant physical environment have been identified, spatial competition in a time-varying environment will be investigated. Field experiments, using a rye grass-clover system, will be used to test hypotheses generated by the models.
A greater understanding of links between individual-level interactions and a population's spatial growth will increase our ability to predict how invasive species, emerging infections, and evolutionary adaptations spread across ecological landscapes. The research plan emphasizes education and training of young scientists at both graduate and undergraduate levels. The collaborative, interdisciplinary nature of the research will enhance quantitative skills of ecology students, and will introduce contemporary challenges in ecology and conservation to physics students.
