  We study a stochastic predator-prey model on a square lattice, where each of
the six species has two superior and two inferior partners. The invasion
probabilities between species depend on the predator-prey pair and are
supplemented by Gaussian noise. Conditions are identified that warrant the
largest impact of noise on the evolutionary process, and the results of Monte
Carlo simulations are qualitatively reproduced by a four-point cluster
dynamical mean-field approximation. The observed noise-guided evolution is
deeply routed in short-range spatial correlations, which is supported by
simulations on other host lattice topologies. Our findings are conceptually
related to the coherence resonance phenomenon in dynamical systems via the
mechanism of threshold duality. We also show that the introduced concept of
noise-guided evolution via the exploitation of threshold duality is not limited
to predator-prey cyclical interactions, but may apply to models of evolutionary
game theory as well, thus indicating its applicability in several different
fields of research.
