Grazers and grass: Monte Carlo simulations.

Area of Science:

• Ecological modeling
• Population dynamics
• Computational biology

Background:

• Understanding the complex interactions between grazers and vegetation is crucial for ecological stability.
• Conventional models often simplify spatial dynamics and environmental dependencies, limiting their predictive power.

Purpose of the Study:

• To develop a novel Monte Carlo model simulating grass-grazer interplay with environmental dependencies.
• To investigate population dynamics, including stable regimes and oscillations, under non-mean-field conditions.

Main Methods:

• A novel Monte Carlo model incorporating grass-island growth, grazer consumption, and grazer life-cycle processes (birth, migration, death).
• The model accounts for environmental dependencies affecting process rates and spatial behaviors (e.g., grass growth on boundaries, grazer mobility).

Main Results:

• The model predicts both stable population regimes and irregular oscillations in grass-island area and grazer populations.
• Observed patterns differ from conventional prey-predator models, notably showing no tendency for grazers and grass to segregate.

Conclusions:

• The developed model offers a more realistic simulation of grass-grazer ecosystems by incorporating spatial and environmental factors.
• The absence of segregation suggests unique emergent properties in this ecological system not captured by simpler models.