Rare extinction events in cyclic predator-prey games

TL;DR

This paper investigates the rare stochastic extinction events in a cyclic predator-prey model, using a WKB approach to compute mean times to extinction and analyzing how these events depend on system parameters.

Contribution

It introduces a Hamilton-Jacobi framework and numerical methods to analyze rare extinction paths in a three-species cyclic competition model.

Findings

Mean time to extinction depends on bifurcation proximity and system size.

Multiple extinction pathways exist with different intermediate steps.

Analytical predictions align with Gillespie simulation results.

Abstract

In the May-Leonard model of three cyclically competing species, we analyze the statistics of rare events in which all three species go extinct due to strong but rare fluctuations. These fluctuations are from the tails of the probability distribution of species concentrations. They render a coexistence of three populations unstable even if the coexistence is stable in the deterministic limit. We determine the mean time to extinction (MTE) by using a WKB-ansatz in the master equation that represents the stochastic description of this model. This way, the calculation is reduced to a problem of classical mechanics and amounts to solving a Hamilton-Jacobi equation with zero-energy Hamiltonian. We solve the corresponding Hamilton's equations of motion in six-dimensional phase space numerically by using the Iterative Action Minimization Method. This allows to project on the optimal path to extinction, starting from a parameter choice where the three-species coexistence-fixed point undergoes a Hopf bifurcation and becomes stable. Specifically for our system of three species, extinction events can be triggered along various paths to extinction, differing in their intermediate steps. We compare our analytical predictions with results from Gillespie simulations for two-species extinctions, complemented by an analytical calculation of the MTE in which the remaining third species goes extinct. From Gillespie simulations we also analyze how the distributions of times to extinction change upon varying the bifurcation parameter. Even within the same model and the same dynamical regime, the MTE depends on the distance from the bifurcation point in a way that contains the system size dependence in the exponent. It is challenging and worthwhile to quantify how rare the rare events of extinction are.