Wolf-Sheep Predation Dashboard: Agent-Based Modeling of Ecological Dynamics

Overview of Wolf-Sheep Predation

The simulation models a meadow ecosystem where wolves hunt sheep. Sheep graze on logistic growth grass, which replenishes at a rate that depends on the current population size and environmental conditions. Wolves track scent trails left by sheep to locate them for hunting.

This model incorporates various behaviors such as flocking in sheep and scent-based hunting strategies in wolves, providing a rich environment for studying predator-prey dynamics.

Agent-Based Modeling Techniques

The simulation employs agent-based modeling (ABM) to simulate individual entities like sheep and wolves. Each agent follows simple rules that determine its behavior based on its current state and the environment.

This approach allows for emergent behaviors, such as flocking in sheep and cooperative hunting strategies among wolves, which are not explicitly programmed but arise from the interactions of many agents.

Ecological Dynamics and Cycles

The Lotka-Volterra equations describe the predator-prey dynamics within this ecosystem. These equations predict oscillations in population sizes, reflecting the balance between predation pressure and resource availability.

By observing the phase plots of these populations over time, one can see how changes in initial conditions or parameter values affect the stability and periodicity of the cycles.

Interactive Features

The simulation includes a minimap that provides an overview of the meadow, four different terrains with varying environmental factors, and live population counts for both sheep and wolves.

Users can also adjust parameters such as wolf hunting efficiency, sheep flocking behavior, and grass growth rates to observe how these changes impact the ecosystem dynamics.

Frequently asked questions

Try it live

Everything above runs in your browser — open Wolf-Sheep Predation Dashboard: Agent-Based Flocking, Scent Hunting, Lotka-Volterra Phase Plot, Minimap and Four Terrains Lab and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.