Lotka-Volterra predator-prey model with periodically varying carrying capacity

TL;DR

This study investigates how periodic environmental changes influence predator-prey dynamics in a stochastic spatial Lotka-Volterra model, revealing enhanced coexistence and resonance effects through simulations and mean-field analysis.

Contribution

It introduces a detailed analysis of predator-prey interactions under periodically varying carrying capacity, combining stochastic lattice simulations with mean-field theory to uncover new dynamical behaviors.

Findings

Coexistence region is enlarged under periodic carrying capacity.

Resonance effects lead to prolonged spatial correlations.

Mean-field predictions of period-doubling are suppressed by noise.

Abstract

We study the stochastic spatial Lotka-Volterra (LV) model for predator-prey interaction subject to a periodically varying carrying capacity. The LV model with on-site lattice occupation restrictions that represent finite food resources for the prey exhibits a continuous active-to-absorbing phase transition. The active phase is sustained by spatio-temporal patterns in the form of pursuit and evasion waves. Monte Carlo simulations on a two-dimensional lattice are utilized to investigate the effect of seasonal variations of the environment on species coexistence. The results of our simulations are also compared to a mean-field analysis. We find that the parameter region of predator and prey coexistence is enlarged relative to the stationary situation when the carrying capacity varies periodically. The stationary regime of our periodically varying LV system shows qualitative agreement between the stochastic model and the mean-field approximation. However, under periodic carrying capacity switching environments, the mean-field rate equations predict period-doubling scenarios that are washed out by internal reaction noise in the stochastic lattice model. Utilizing visual representations of the lattice simulations and dynamical correlation functions, we study how the pursuit and evasion waves are affected by ensuing resonance effects. Correlation function measurements indicate a time delay in the response of the system to sudden changes in the environment. Resonance features are observed in our simulations that cause prolonged persistent spatial correlations. Different effective static environments are explored in the extreme limits of fast- and slow periodic switching. The analysis of the mean-field equations in the fast-switching regime enables a semi-quantitative description of the stationary state.