Title: Stochastic population dynamics in spatially extended predator-prey systems,
Abstract: Spatially extended population dynamics models that incorporate intrinsic
noise serve as case studies for the role of fluctuations and correlations in
biological systems. Including spatial structure and stochastic noise in
predator-prey competition invalidates the deterministic Lotka-Volterra picture
of neutral population cycles. Stochastic models yield long-lived erratic
population oscillations stemming from a resonant amplification mechanism. In
spatially extended predator-prey systems, one observes noise-stabilized
activity and persistent correlations. Fluctuation-induced renormalizations of
the oscillation parameters can be analyzed perturbatively. The critical
dynamics and the non-equilibrium relaxation kinetics at the predator extinction
threshold are characterized by the directed percolation universality class.
Spatial or environmental variability results in more localized patches which
enhances both species densities. Affixing variable rates to individual
particles and allowing for trait inheritance subject to mutations induces fast
evolutionary dynamics for the rate distributions. Stochastic spatial variants
of cyclic competition with rock-paper-scissors interactions illustrate
connections between population dynamics and evolutionary game theory, and
demonstrate how space can help maintain diversity. In two dimensions,
three-species cyclic competition models of the May-Leonard type are
characterized by the emergence of spiral patterns whose properties are
elucidated by a mapping onto a complex Ginzburg-Landau equation. Extensions to
general food networks can be classified on the mean-field level, which provides
both a fundamental understanding of ensuing cooperativity and emergence of
alliances. Novel space-time patterns emerge as a result of the formation of
competing alliances, such as coarsening domains that each incorporate
rock-paper-scissors competition games.