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Zbl 1190.34064
Ji, Chunyan; Jiang, Daqing; Shi, Ningzhong
Analysis of a predator-prey model with modified Leslie-Gower and Holling-type II schemes with stochastic perturbation.
(English)
[J] J. Math. Anal. Appl. 359, No. 2, 482-498 (2009). ISSN 0022-247X

Consider the predator-prey models $$dx = [a x - b x^2 - c_1 \varphi (x,y) x] dt + \alpha x dW_1,$$ $$dy = [r y - c_2 \varphi (x,y) y] dt + \beta y dW_2,$$ where $x$ and $y$ represent the population densities of prey and predator at time $t \ge 0$; $a$ and $r$, $b$, and $c_i$ are positive constants of prey and predator intrinsic growth rates, death rate measuring the strength of competition among the prey individuals and conversion rates of the predator-prey model, respectively. Moreover, $\varphi (x,y)$ models the functional response of the predator to the prey density per unit time. In this paper, the authors are interested in the study of the case of modified Leslie-Gower and Holling-type-II functionals of the form $$\varphi (x,y) = y / (m+x),$$ where $m\ge 0$ measures the extent to which the environment provides protection to the prey $x$. Now, suppose these models are perturbed by independent standard Wiener processes $W_i$ in the parameters $a$ and $b$ with variance parameters $\alpha$ and $\beta$. Thus, one arrives at nonlinear stochastic differential equations with linear multiplicative noise and quadratic nonlinearities. First, the authors prove the existence of unique, positive global solutions to these systems with positive initial values $x_0, y_0 > 0$. Second, they study its long-time behavior. Third, the system is investigated with respect to extinction and persistence conditions. As their major proof technique, the authors apply well-known comparison theorems on upper and lower solution bounds and the knowledge on explicit solutions of stochastic logistic equations with linear multiplicative white noise in $\bbfR^1$. Finally, standard Milstein methods are used for some numerical simulations to illustrate their findings.
[Henri Schurz (Carbondale)]
MSC 2000:
*34F05 ODE with randomness
60H30 Appl. of stochastic analysis
34C60 Applications of qualitative theory of ODE
34D05 Asymptotic stability of ODE
37H10 Random and stochastic difference and differential equations
60H10 Stochastic ordinary differential equations
92D25 Population dynamics

Keywords: predator-prey model; Lotka-Volterra equations; stochastic differential equations; logistic equations; nonlinear stochastic systems; Wiener process; Gaussian perturbations; comparison technique; monotonicity; extinction; persistence time; global stability; existence; uniqueness; positivity; Ito formula

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