Lotka-Volterra Equations Calculator

Model predator-prey population dynamics using the Lotka-Volterra equations. Simulate oscillating populations, explore equilibria, and visualize classic ecological cycles.

Prey Equilibrium (N*)
20.0
N* = γ / δ
Predator Equilibrium (P*)
10.0
P* = α / β
Approx. Period
62.8 time units
T ≈ 2π / √(αγ)
Prey Range
0 – 190
Amplitude: 190
Predator Range
0 – 104
Amplitude: 104
Final Populations
N=0, P=14
At t=250

Population Timeline

t=0
N=100 P=20
t=21
N=0 P=15
t=41
N=1 P=2
t=62
N=4 P=0
t=82
N=28 P=0
t=103
N=121 P=29
t=123
N=0 P=16
t=144
N=0 P=2
t=164
N=1 P=0
t=185
N=4 P=0
t=205
N=32 P=0
t=226
N=187 P=19
t=246
N=0 P=21
t=250
N=0 P=14
■ Prey   ■ Predator

Simulation Data

TimePrey (N)Predators (P)dN/dtdP/dt
0.0100.020.0-10.00+8.00
20.50.314.8-0.01-1.45
41.00.61.9+0.05-0.18
61.53.90.3+0.38-0.02
82.028.00.1+2.76+0.00
102.5120.629.3-23.33+14.76
123.00.015.7-0.00-1.56
143.50.11.9+0.01-0.19
164.00.60.2+0.06-0.02
184.54.30.0+0.43-0.00
205.031.90.0+3.19+0.00
225.5187.118.8-16.48+15.72
246.00.021.0-0.00-2.10
250.00.014.0-0.00-1.40
Planning notes, formulas, and examples

About the Lotka-Volterra Equations Calculator

The Lotka-Volterra equations are the foundational mathematical model of predator-prey dynamics in ecology. Published independently by Alfred Lotka (1925) and Vito Volterra (1926), these coupled differential equations describe how two interacting populations—a prey species and its predator—oscillate in perpetual, out-of-phase cycles. When prey are abundant, predators thrive and multiply; their growing numbers then deplete the prey; with fewer prey, predators decline; reduced predation allows prey to recover; and the cycle repeats.

The classic equations are: dN/dt = αN - βNP (prey growth minus predation) and dP/dt = δNP - γP (predator reproduction from consumption minus natural death). The four parameters—prey growth rate (α), predation rate (β), predator reproduction efficiency (δ), and predator death rate (γ)—determine the amplitude, period, and equilibrium of the oscillations.

This calculator numerically solves the Lotka-Volterra system using Euler's method, letting you explore how parameter changes affect population dynamics. Model classic examples like lynx-hare cycles, wolf-deer interactions, or abstract ecological scenarios. Visualize the time series, identify equilibrium populations, and understand the sensitivity of ecosystems to parameter perturbations.

When This Page Helps

The Lotka-Volterra equations are a cornerstone of mathematical ecology. Use this calculator to explore how prey growth, predation, and predator mortality interact to shape population cycles. It is useful for comparing scenarios, teaching feedback loops, and building intuition about equilibrium and oscillation in predator-prey systems.

How to Use the Inputs

  1. Set initial populations for prey and predators.
  2. Adjust the four Lotka-Volterra parameters: prey growth rate, predation rate, predator efficiency, and predator death rate.
  3. Choose the simulation length (time steps) and step size.
  4. Click a preset to explore classic ecological scenarios.
  5. Review the population time series and equilibrium values.
  6. Examine the phase portrait showing the population cycle.
  7. Experiment with parameters to see how stability changes.
Formula used
dN/dt = αN − βNP (prey), dP/dt = δNP − γP (predator). Equilibrium: N* = γ/δ, P* = α/β. Period ≈ 2π/√(αγ). Parameters: α = prey intrinsic growth rate, β = predation rate coefficient, δ = predator reproduction efficiency per prey consumed, γ = predator natural death rate. Solved via Euler method: N(t+dt) = N(t) + dt × (αN − βNP).

Example Calculation

Result: Oscillating populations: prey peaks ~120, predator peaks ~25

With prey growth α=0.1, predation β=0.01, predator efficiency δ=0.005, and predator death γ=0.1, the equilibrium is N*=γ/δ=20, P*=α/β=10. Starting at N=100, P=20 (far from equilibrium), both populations oscillate with ~60-step period. Prey peaks about 2.5× higher than predators due to higher turnover.

Tips & Best Practices

  • The equilibrium prey population N* = γ/δ depends only on predator parameters—not prey growth rate.
  • Increasing prey growth rate α raises the predator equilibrium P* but not the prey equilibrium.
  • Starting far from equilibrium produces large oscillations; starting near equilibrium gives small cycles.
  • The Lotka-Volterra system conserves a quantity analogous to energy—orbits never spiral in or out.
  • Adding carrying capacity to prey gives the Lotka-Volterra competition model with damped oscillations.
  • Real ecosystems add complexity: prey refugia, predator satiation, multiple species, and spatial heterogeneity.

Mathematical Properties

The classic Lotka-Volterra system has a remarkable mathematical property: it conserves a quantity V = δN - γ ln(N) + βP - α ln(P). This conservation means orbits in the N-P phase plane are closed loops—populations cycle forever without damping or amplification. This is analogous to conservation of energy in physics and means the model is "structurally unstable": any modification (adding carrying capacity, functional responses, or stochasticity) changes the qualitative behavior.

The period of oscillation is approximately 2π/√(αγ), depending on the prey growth rate and predator death rate. The amplitude depends on the starting conditions—orbits further from equilibrium have larger oscillations. Unlike a simple pendulum, the oscillations are not sinusoidal; prey peaks are sharper and predator peaks are broader.

Extensions and Realism

Ecologists have developed numerous extensions to the basic model. The Rosenzweig-MacArthur model adds logistic prey growth (carrying capacity K) and a Type II functional response (predator satiation). This produces damped oscillations converging to a stable equilibrium at low K, but paradoxically destabilizes as K increases (the "paradox of enrichment"—adding resources can cause population crashes).

The competitive Lotka-Volterra equations model two competing species rather than predator-prey, leading to outcomes including competitive exclusion (one species wins), stable coexistence, or bistability (outcome depends on initial conditions). These models underpin the competitive exclusion principle—two species competing for the same niche cannot stably coexist.

Conservation Applications

Modern conservation biology uses Lotka-Volterra-derived models extensively. Wolf reintroduction in Yellowstone, deer population management, marine predator-prey dynamics (sharks and prey fish), and invasive species control all rely on understanding predator-prey dynamics. The Lotka-Volterra framework helps predict: How will removing a predator affect prey populations? What happens when prey habitat is reduced? How does introducing a new predator reshape the ecosystem?

Sources & Methodology

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Frequently Asked Questions

  • They model the simplest predator-prey interaction: prey grow exponentially in the absence of predators, predation is proportional to encounters between prey and predators (proportional to both populations), predators reproduce in proportion to prey consumed, and predators die at a constant per-capita rate. This produces characteristic oscillating population cycles.