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

Area of Science:

• Ecology
• Complex Systems
• Mathematical Biology

Background:

• Ecological systems exhibit metastable states influenced by nonlinearity and uncertainty.
• Understanding transitions between these states is crucial for predicting ecosystem behavior.
• Nutrient-phytoplankton-zooplankton (NPZ) models are fundamental for studying aquatic ecosystems.

Purpose of the Study:

• To investigate noise-induced transitions in a three-dimensional nutrient-phytoplankton-zooplankton (NPZ) model.
• To analyze the impact of random perturbations on system bistability.
• To develop a framework for predicting regime shifts in plankton communities.

Main Methods:

• Utilized a three-dimensional NPZ model with random perturbations.
• Employed the Onsager-Machlup action functional to analyze transition pathways.
• Applied the neural shooting method to determine transition probabilities and times.

Main Results:

• Demonstrated that random perturbations can induce transitions between a stable equilibrium and a stable limit cycle in the NPZ model.
• Identified the most probable transition pathways, times, and probabilities.
• Quantified the influence of noise on the dynamics of bistable ecological systems.

Conclusions:

• Noise-induced transitions are a significant factor in the dynamics of complex ecological systems.
• The developed framework aids in predicting regime shifts in plankton communities.
• This research enhances the understanding of noise effects in biological systems and critical transitions.