Chimera States in Ecological Network Under Weighted Mean-Field Dispersal of Species

Abstract

In ecological landscapes, species tend to migrate between patches in search of a better survivability condition. By this dispersal process, they form connectivity between the patches and thereby may develop various correlated or partially correlated population dynamics among species living in the patches. We explore various possible emergent collective population patterns using a simple ecological network model of all-to-all connected patches where we use a particular type of dispersal process that is controlled by a weighted mean-field diffusion to include the failed migration between the interacting patches. We represent the population dynamics of both the predator and prey in each patch by a modified Rosenzweig-MacArthur (mRM) model that incorporates an additional effect of habitat complexity. Our investigation on the network dynamics shows various interesting collective patterns, namely, clustered states and chimera states, besides synchrony and homogeneous steady states (HSS) of species. An important observation is that habitat complexity enhances survival probabilities of interacting species and thus increases population persistence in a natural ecosystem.