We present a stochastic approach to modeling the dynamics of coexistence of
prey and predator populations. It is assumed that the space of coexistence is
explicitly subdivided in a grid of cells. Each cell can be occupied by only one
individual of each species or can be empty. The system evolves in time
according to a probabilistic cellular automaton composed by a set of local
rules which describe interactions between species individuals and mimic the
process of birth, death and predation. By performing computational simulations,
we found that, depending on the values of the parameters of the model, the
following states can be reached: a prey absorbing state and active states of
two types. In one of them both species coexist in a stationary regime with
population densities constant in time. The other kind of active state is
characterized by local coupled time oscillations of prey and predator
populations. We focus on the self-organized structures arising from
spatio-temporal dynamics of the coexistence. We identify distinct spatial
patterns of prey and predators and verify that they are intimally connected to
the time coexistence behavior of the species. The occurrence of a prey
percolating cluster on the spatial patterns of the active states is also
examined.Comment: 19 pages, 11 figure
