Population Uncertainty in Model Ecosystem: Analysis by Stochastic Differential Equation

TL;DR

This paper develops a stochastic differential equation theory to analyze population uncertainty after perturbations, revealing stronger fluctuation enhancement effects and aligning closely with mean-field simulations.

Contribution

A novel stochastic differential equation framework that accurately models population uncertainty and predicts stronger fluctuation effects than previous models.

Findings

Almost perfect agreement between theory and mean-field simulation

Identification of significantly stronger fluctuation enhancement effects

Insights into population uncertainty during species recovery

Abstract

Perturbation experiments are carried out by contact process and its mean-field version. Here, the mortality rate is increased or decreased suddenly. It is known that the fluctuation enhancement (FE) occurs after the perturbation, where FE means a population uncertainty. In the present paper, we develop a new theory of stochastic differential equation. The agreement between the theory and the mean-field simulation is almost perfect. This theory enables us to find much stronger FE than reported previously. We discuss the population uncertainty in the recovering process of endangered species.