Stochastic Predator-prey System Research Articles

Analysis of Stochastic Delay Predator-Prey System with Impulsive Toxicant Input in Polluted Environments

A stochastic delay predator-prey model in a polluted environment with impulsive toxicant input is proposed and studied. The thresholds between stability in time average and extinction of each population are obtained. Some recent results are extended and improved greatly. Several simulation figures are introduced to support the conclusions.

A remark on a stochastic predator–prey system with time delays

An autonomous stochastic predator–prey model with time delays is investigated. Almost sufficient and necessary conditions for stability in the mean and extinction of each population are established. Numerical simulations are introduced to support the results.

Dynamics of a stochastic predator–prey system with Beddington–DeAngelis functional response

Some dynamical properties of a stochastic non-autonomous predator–prey system with Beddington–DeAngelis functional response are studied. Firstly, we show the existence, the uniqueness and the positivity of the solution. Secondly, we study the boundedness of moments and the upper-growth rate of the solution. Then we investigate the global attractivity of the system. Finally we introduce some figures to illustrate our main results.

Population oscillations in spatial stochastic Lotka–Volterra models: a field-theoretic perturbational analysis

Field theory tools are applied to analytically study fluctuation and correlation effects in spatially extended stochastic predator–prey systems. In the mean-field rate equation approximation, the classic Lotka–Volterra model is characterized by neutral cycles in phase space, describing undamped oscillations for both predator and prey populations. In contrast, Monte Carlo simulations for stochastic two-species predator–prey reaction systems on regular lattices display complex spatio-temporal structures associated with persistent erratic population oscillations. The Doi–Peliti path integral representation of the master equation for stochastic particle interaction models is utilized to arrive at a field theory action for spatial Lotka–Volterra models in the continuum limit. In the species coexistence phase, a perturbation expansion with respect to the nonlinear predation rate is employed to demonstrate that spatial degrees of freedom and stochastic noise induce instabilities toward structure formation, and to compute the fluctuation corrections for the oscillation frequency and diffusion coefficient. The drastic downward renormalization of the frequency and the enhanced diffusivity are in excellent qualitative agreement with Monte Carlo simulation data.

On a stochastic predator‐prey system with modified functional response

A stochastic predator–prey system with modified functional response is investigated. We show that there is a unique positive solution to the model for any positive initial value by comparison theorem. Moreover, under some conditions, we conclude that the stochastic model is persistent in mean and extinct. Copyright © 2011 John Wiley & Sons, Ltd.

Nonlinear functional response parameter estimation in a stochastic predator-prey model

Parameter estimation for the functional response of predator-prey systems is a critical methodological problem in population ecology. In this paper we consider a stochastic predator-prey system with non-linear Ivlev functional response and propose a method for model parameter estimation based on time series of field data. We tackle the problem of parameter estimation using a Bayesian approach relying on a Markov Chain Monte Carlo algorithm. The efficiency of the method is tested on a set of simulated data. Then, the method is applied to a predator-prey system of importance for Integrated Pest Management and biological control, the pest mite Tetranychus urticae and the predatory mite Phytoseiulus persimilis. The model is estimated on a dataset obtained from a field survey. Finally, the estimated model is used to forecast predator-prey dynamics in similar fields, with slightly different initial conditions.

Stochastic population oscillations in spatial predator-prey models

It is well-established that including spatial structure and stochastic noise in models for predator-prey interactions invalidates the classical deterministic Lotka–Volterra picture of neutral population cycles. In contrast, stochastic models yield long-lived, but ultimately decaying erratic population oscillations, which can be understood through a resonant amplification mechanism for density fluctuations. In Monte Carlo simulations of spatial stochastic predator-prey systems, one observes striking complex spatio-temporal structures. These spreading activity fronts induce persistent correlations between predators and prey. In the presence of local particle density restrictions (finite prey carrying capacity), there exists an extinction threshold for the predator population. The accompanying continuous non-equilibrium phase transition is governed by the directed-percolation universality class. We employ field-theoretic methods based on the Doi–Peliti representation of the master equation for stochastic particle interaction models to (i) map the ensuing action in the vicinity of the absorbing state phase transition to Reggeon field theory, and (ii) to quantitatively address fluctuation-induced renormalizations of the population oscillation frequency, damping, and diffusion coefficients in the species coexistence phase.

Asymptotic Behavior of Predator-Prey Systems Perturbed by White Noise

In this paper, we develop the results in Rudnicki (Stoch. Process. Appl. 108:93–107, 2003) to a stochastic predator-prey system where the random factor acts on the coefficients of environment. We show that there exists the density functions of the solutions and then, study the asymptotic behavior of these densities. It is proved that the densities either converges in L1 to an invariant density or converges weakly to a singular measure on the boundary.

Existence and Uniqueness for Stochastic Predator-Prey System of Two Species with Age-Structured

In this paper we introduce a stochastic age-dependent predator-prey system. Existence and uniqueness of strong solution for a stochastic population system of two species with age-dependent are proved. The analysis uses Barkholder-Davis-Gundy’s inequality,ItÔ's formula and some special inequalities to achieve our purpose.

Asymptotic properties of a stochastic predator–prey system with Holling II functional response

A stochastic predator–prey system with Holling II functional response is proposed and investigated. We show that there is a unique positive solution to the model for any positive initial value. And we show that the positive solution to the stochastic system is stochastically bounded. Moreover, under some conditions, we conclude that the stochastic model is stochastically permanent and persistent in mean.

Global stability of a nonlinear stochastic predator–prey system with Beddington–DeAngelis functional response

Stochastically asymptotic stability in the large of a predator–prey system with Beddington–DeAngelis functional response with stochastic perturbation is considered. The result shows that if the positive equilibrium of the deterministic system is globally stable, then the stochastic model will preserve this nice property provided the noise is sufficiently small. Some simulation figures are introduced to support the analytical findings.

Characterization of multiple spiral wave dynamics as a stochastic predator-prey system.

A perspective on systems containing many action potential waves that, individually, are prone to spiral wave breakup is proposed. The perspective is based on two quantities, "predator" and "prey," which we define as the fraction of the system in the excited state and in the excitable but unexcited state, respectively. These quantities exhibited a number of properties in both simulations and fibrillating canine cardiac tissue that were found to be consistent with a proposed theory that assumes the existence of regions we call "domains of influence," each of which is associated with the activity of one action potential wave. The properties include (i) a propensity to rotate in phase space in the same sense as would be predicted by the standard Volterra-Lotka predator-prey equations, (ii) temporal behavior ranging from near periodic oscillation at a frequency close to the spiral wave rotation frequency ("type-1" behavior) to more complex oscillatory behavior whose power spectrum is composed of a range of frequencies both above and, especially, below the spiral wave rotation frequency ("type-2" behavior), and (iii) a strong positive correlation between the periods and amplitudes of the oscillations of these quantities. In particular, a rapid measure of the amplitude was found to scale consistently as the square root of the period in data taken from both simulations and optical mapping experiments. Global quantities such as predator and prey thus appear to be useful in the study of multiple spiral wave systems, facilitating the posing of new questions, which in turn may help to provide greater understanding of clinically important phenomena such as ventricular fibrillation.

Bayesian Inference for Functional Response in a Stochastic Predator–Prey System

We present a Bayesian method for functional response parameter estimation starting from time series of field data on predator-prey dynamics. Population dynamics is described by a system of stochastic differential equations in which behavioral stochasticities are represented by noise terms affecting each population as well as their interaction. We focus on the estimation of a behavioral parameter appearing in the functional response of predator to prey abundance when a small number of observations is available. To deal with small sample sizes, latent data are introduced between each pair of field observations and are considered as missing data. The method is applied to both simulated and observational data. The results obtained using different numbers of latent data are compared with those achieved following a frequentist approach. As a case study, we consider an acarine predator-prey system relevant to biological control problems.

Numerical optimization of certain dynamical stochastic systems

Two-dimensional dynamical (dynamical stochastic) predator-prey systems are optimized numerically by calculating the variation of the functional of the steady-state solution to the Fokker-Plank equation. Numerical algorithms are used to construct systems with a prescribed response to a certain external action.