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Lotka-Volterra Predator-Prey Model

The Lotka-Volterra equations model predator-prey dynamics. dPrey/dt = αPrey − βPrey×Predator. dPredator/dt = δPrey×Predator − γPredator. Classic example: Canadian lynx and snowshoe hare cycles (~10yr period). Key parameters: α (prey growth), β (predation rate), γ (predator death), δ (predator reproduction efficiency).

Concept Fundamentals
~10 yrs
Lynx-Hare Cycle
ODE System
Equation Type
1925-1926
Developed
Ecology+Economics
Applications
Simulate Predator-Prey DynamicsLotka-Volterra ODE system

🌍 Why This Matters for the Planet

Why It Matters

Understanding predator-prey dynamics is fundamental to ecology. The Lotka-Volterra model shows how populations oscillate: when prey are abundant, predators thrive; when predators overhunt, prey crash and predators starve. The cycle repeats. Real examples include lynx-hare, wolf-deer, and many marine systems.

How You Can Help

Enter initial prey and predator populations, plus the four parameters α, β, γ, δ. The calculator simulates the ODEs using Euler method (dt=0.01) over 50 time units. You'll see equilibrium values (Prey*=γ/δ, Pred*=α/β), max/min populations, cycle period, and charts: time series, phase portrait, equilibrium bar, parameter sensitivity.

Key Insights

  • Equilibrium: Prey* = γ/δ, Predator* = α/β
  • Cycle period ≈ 2π/√(αγ)
  • Lynx-hare Hudson Bay data shows ~10-year cycles
  • Model applies to economics and epidemiology

📋 Quick Examples — Click to Load

lotka_volterra_model.shCALCULATED
Prey Equilibrium (Prey* = γ/δ)
50.0
Predator Equilibrium (Pred*) = 50.0
🐰
167.9
Max Prey
🐺
124.7
Max Predator
🔄
8.89
Cycle Period
⚖️
50.0
Predator Equilibrium
Prey growth α: 1.0Predation rate β: 0.02Efficiency δ: 0.01

For educational and informational purposes only. Verify with a qualified professional.

🌎 Planet Impact Facts

🐰

Canadian lynx and snowshoe hare show ~10-year cycles in Hudson Bay fur records

— Hudson Bay Company

📊

Lotka and Volterra developed the model independently in 1925-1926

— History of Science

⚖️

At equilibrium Prey* = γ/δ and Predator* = α/β

— Ecology

🔄

Cycle period is approximately 2π/√(αγ)

— Dynamical Systems

🌍

The model has been applied to economics and epidemiology

— Applied Math

📈

The equilibrium is neutrally stable—closed orbits, no damping

— Nonlinear Dynamics

The Lotka-Volterra equations model predator-prey dynamics. dPrey/dt = αPrey − βPrey×Predator. dPredator/dt = δPrey×Predator − γPredator. Classic example: Canadian lynx and snowshoe hare cycles (~10yr period). Key parameters: α (prey growth), β (predation rate), γ (predator death), δ (predator reproduction efficiency). Developed by Lotka (1925) and Volterra (1926).

~10 yrs
Lynx-Hare Cycle
ODE
Equation Type
1925-26
Developed
Ecology+Econ
Applications

Key Takeaways

  • • Equilibrium: Prey* = γ/δ, Predator* = α/β—populations oscillate around this point
  • • Cycle period ≈ 2π/√(αγ)—depends on prey growth and predator death rates
  • • Euler method: Prey(t+dt) = Prey(t) + dt×(αPrey − βPrey×Pred), same for predator
  • • Lynx-hare fur-trade data from Hudson Bay shows ~10-year cycles matching the model

Did You Know?

🐰 Lotka and Volterra developed the model independently in 1925-1926
🦌 Canadian lynx-hare cycles in Hudson Bay fur records are the classic example
📊 The equilibrium is neutrally stable—closed orbits, no damping
🌍 The model applies to economics, epidemiology, and other oscillating systems
⚖️ At equilibrium both dPrey/dt and dPredator/dt are zero
📈 Higher predation rate (β) lowers prey equilibrium; higher δ raises predator equilibrium

How the Equations Work

Prey equation: dPrey/dt = αPrey − βPrey×Predator

Prey grow at rate α when alone; predation removes β×Prey×Predator per unit time.

Predator equation: dPredator/dt = δPrey×Predator − γPredator

Predators gain from eating prey (δ×Prey×Predator) and die at rate γ when prey are scarce.

Euler simulation

Prey(t+dt) = Prey(t) + dt×(αPrey − βPrey×Pred). Pred(t+dt) = Pred(t) + dt×(δPrey×Pred − γPred). With dt=0.01, we simulate over 50 time units.

Expert Tips

Start Near Equilibrium

Use Prey = γ/δ and Predator = α/β to see small oscillations. Try the "Balanced Equilibrium" example.

Compare Species Pairs

Lynx-hare, wolf-deer, fox-rabbit—each has different α, β, γ, δ. Compare cycle periods and amplitudes.

Phase Portrait

The phase portrait (prey vs predator) shows closed orbits. Each orbit is a different initial condition.

Time Lag Effects

Real systems often have time lags (e.g., predator reproduction delay). The basic model ignores these.

Parameter Ranges by System

SystemαβγδPeriod
Lynx-Hare1.00.020.50.01~12.6
Wolf-Deer0.80.0150.40.008~12.5
Fox-Rabbit1.20.0250.60.012~9.1

Frequently Asked Questions

What is the Lotka-Volterra model?

The Lotka-Volterra equations model predator-prey dynamics. dPrey/dt = αPrey − βPrey×Predator. dPredator/dt = δPrey×Predator − γPredator. α = prey growth rate, β = predation rate, γ = predator death rate, δ = predator reproduction efficiency. Developed independently by Lotka (1925) and Volterra (1926).

What is the classic lynx-hare cycle?

Canadian lynx and snowshoe hare populations show ~10-year cycles in Hudson Bay fur-trade data. Hare populations boom, lynx follow; when hares crash from predation, lynx starve and decline. The cycle repeats. This is the textbook example of Lotka-Volterra dynamics in nature.

What is the equilibrium point?

At equilibrium, both populations are constant: Prey* = γ/δ and Predator* = α/β. Neither population grows nor shrinks. The system oscillates around this point; the equilibrium is neutrally stable (closed orbits).

What is the cycle period?

The period of oscillation is approximately T ≈ 2π/√(αγ). It depends on prey growth rate (α) and predator death rate (γ). Higher α or γ shortens the period; lower values lengthen it.

Can Lotka-Volterra apply to economics?

Yes. The model has been adapted to economics (e.g., predator = firms, prey = market share), epidemiology (susceptible-infected), and other fields. The same coupled ODE structure describes many oscillating systems.

Why use Euler method for simulation?

Euler method approximates the ODEs with small time steps: Prey(t+dt) = Prey(t) + dt×(αPrey − βPrey×Pred). With dt=0.01, the simulation is stable and accurate enough for visualization. More sophisticated methods (RK4) give smoother results but Euler is sufficient for educational purposes.

Key Statistics

~10 yrs
Lynx-Hare cycle
ODE
Equation type
1925-26
Developed
Ecology+Econ
Applications

Official Data Sources

⚠️ Disclaimer: The Lotka-Volterra model is a simplified representation of predator-prey dynamics. Real ecosystems have spatial structure, multiple species, stochasticity, and time lags. Use for educational and exploratory purposes. Not a substitute for professional ecological modeling.

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