Simulate population dynamics and find equilibrium points for predator-prey interactions.
Enter model parameters and initial populations to analyze dynamics.
Intrinsic growth rate of prey
Rate at which predators consume prey
Conversion of prey to predator growth
Natural death rate of predators
Starting number of prey individuals
Starting number of predator individuals
Stable Oscillation
Populations cycle around equilibrium
Unstable/Trivial
One population may go extinct
dx/dt = αx - βxy
dy/dt = δxy - γy
Equilibrium: x* = γ/δ, y* = α/β
Period ≈ 2π / √(αγ)
Growth minus predation loss.
Gain from predation minus death.
The Lotka-Volterra model is a foundational tool in ecology for understanding cyclic population fluctuations between predators and prey. This calculator computes equilibrium points and stability to predict long-term behavior.
Developed by Alfred Lotka and Vito Volterra, it models how predator and prey populations interact over time, leading to oscillatory cycles without external factors.
Key assumption: Predators depend solely on prey, and prey grow logistically without predators.
Useful for fisheries, wildlife management, and theoretical ecology.
The core differential equations and derived metrics:
Differential Equations: dx/dt = αx - βxy (Prey growth - predation) dy/dt = δxy - γy (Predator gain - death) Equilibrium Points: x* = γ / δ y* = α / β Oscillation Period (small perturbations): T ≈ 2π / √(α γ) Stability: Stable if x* > 0 and y* > 0 (neutral cycles)
Follow these steps to model predator-prey dynamics:
Step 1: Enter prey growth rate (α) and predation rate (β).
Step 2: Input predator efficiency (δ) and death rate (γ).
Step 3: Provide initial populations for prey (x₀) and predators (y₀).
Step 4: Click calculate to find equilibrium, stability, and period.
Step 5: Interpret results for cyclic behavior and management insights.
Example 1: Classic Rabbit-Wolf Model
α=0.5, β=0.02, δ=0.01, γ=0.3, x₀=40, y₀=9
x*=30, y*=25, Period=5.44, Stable Oscillation
👉 Populations cycle sustainably around equilibrium.
Example 2: Unstable Over-Predation
α=1.0, β=0.5, δ=0.01, γ=0.1, x₀=10, y₀=20
x*=10, y*=2, Period=6.28, Unstable
👉 High predation may lead to prey collapse.
Q1. What do the parameters α, β, δ, γ represent?
α: Prey reproduction rate; β: Encounter success; δ: Prey-to-predator conversion; γ: Predator mortality.
Q2. What are the assumptions of this model?
No environmental carrying capacity, constant rates, closed system, no migration or age structure.
Q3. How accurate is it for real ecosystems?
Idealized; real systems need extensions like logistic growth or stochasticity for better fit.
Q4. What if equilibrium is unstable?
One population may drive the other to extinction; adjust parameters for balance.
Q5. Can this model include more factors?
Yes, extensions add carrying capacity, multiple species, or time delays; use software like MATLAB for simulations.
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For further understanding and validation of the formulas used above, we recommend exploring these authoritative resources: