A History-Dependent Stochastic Predator-Prey Model : Chaos and its Elimination
Disordered Systems and Neural Networks
2009-10-31 v1 Statistical Mechanics
q-bio
Abstract
A non-Markovian stochastic predator-prey model is introduced in which the prey are immobile plants and predators are diffusing herbivors. The model is studied by both mean-field approximation (MFA)and computer simulations. The MFA results a series of bifurcations in the phase space of mean predator and prey densities, leading to a chaotic phase. Because of emerging correlations between the two species distributions, the interaction rate alters and if it is set the value which is obtained from the simulation, then the chaotic phase disappears.
Keywords
Cite
@article{arxiv.cond-mat/9908079,
title = {A History-Dependent Stochastic Predator-Prey Model : Chaos and its Elimination},
author = {Rouzbeh Gerami and Mohammad R. Ejtehadi},
journal= {arXiv preprint arXiv:cond-mat/9908079},
year = {2009}
}
Comments
11 Pages (Latex File), 16 Figures (JPEG Files), To appear in Eur. Phys. J. B