Upper and lower bounds for the solution of a stochastic prey-predator system with foraging arena scheme

TL;DR

This paper establishes explicit upper and lower bounds for the solutions of a stochastic prey-predator system, analyzing their moments and distributions using comparison theorems and noise characteristics.

Contribution

It provides new probabilistic bounds and estimates for a stochastic prey-predator model, linking parameters to solution behavior and extending existing asymptotic results.

Findings

Explicit bounds for prey and predator populations over time

Estimates for joint moments and distribution functions

Analysis of noise effects on system dynamics

Abstract

We investigate some probabilistic aspects of the unique global strong solution of a two dimensional system of stochastic differential equations describing a prey-predator model perturbed by Gaussian noise. We first establish, for any fixed $t> 0$, almost sure upper and lower bounds for the components $X(t)$ and $Y(t)$ of the solution vector: these explicit estimates emphasize the interplay between the various parameters of the model and agree with the asymptotic results found in the literature. Then, standing on the aforementioned bounds, we derive upper and lower estimates for the joint moments and distribution function of $(X(t),Y(t))$. Our analysis is based on a careful use of comparison theorems for stochastic differential equations and exploits several peculiar features of the noise driving the equation.