Detecting the most probable transition phenomenon of a nutrient-phytoplankton-zooplankton system

TL;DR

This paper investigates the most probable transition phenomena in a stochastic nutrient-phytoplankton-zooplankton ecosystem model, analyzing transition pathways and probabilities between stable states under noise perturbations.

Contribution

It introduces a novel application of the Onsager-Machlup functional and neural shooting method to identify transition pathways in a stochastic NPZ model, advancing understanding of ecosystem dynamics.

Findings

Identified the most probable transition pathways between stable states.

Calculated transition times and probabilities under stochastic perturbations.

Provided insights into ecosystem stability and regime shifts.

Abstract

The population biology model holds a significant position within ecosystems. Introducing stochastic perturbations into the model can more accurately depict real biological processes. In this paper, we primarily investigate the most probable transition phenomenon in a three-dimensional nutrient-phytoplankton-zooplankton (NPZ) plankton model. With appropriate parameter values, the system coexists with a stable equilibrium point and a stable limit cycle. Under noise perturbations, transitions occur between these two steady states. Based on the Onsager-Machlup action functional and the neural shooting method, we have studied the most probable transition time, the most probable transition pathway and the most probable transition probability of the NPZ system. The transition between these metastable states plays a crucial role in stochastic ecosystems, providing guidance for a better understanding of complex biological processes.