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Ecology & Conservation Biology

Food webs, population cycles, epidemic spread and evolutionary pressure — the dynamics of life modelled from individual agents to whole ecosystems.

8 simulations Agent-Based · ODE Lotka–Volterra · SEIR · Genetic

Category Simulations

Open a simulation — it runs right in your browser

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★★☆ Moderate New
Coral Bleaching
Thermal stress accumulates as Degree Heating Weeks above the bleaching threshold; zooxanthellae fall, coral pales then bleaches white, recovering if temperatures drop. Trigger a marine heatwave.
Coral BleachingDegree Heating WeeksClimate StressCanvas 2D
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New★★☆ Moderate
Trophic Cascade — Food Web & Population Dynamics
3-level Lotka–Volterra ODE model: plants → herbivores → carnivores. Remove the apex predator with one click and watch herbivore populations explode while plant biomass collapses — the hallmark trophic cascade.
Lotka–VolterraFood WebODE
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Popular ★★☆ Moderate
Prey–Predator (Lotka–Volterra)
Classic coupled ODE simulation of oscillating rabbit and fox populations. Adjust birth rates, predation efficiency and carrying capacity to explore stability and collapse.
ODE Lotka–Volterra Population Dynamics
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★☆☆ Beginner New
Fox & Rabbits — Grid World
Agent-based ecosystem on a 2D grid: rabbits graze grass, foxes hunt rabbits, both reproduce and age. Emergent boom-and-bust cycles without any global equations.
Agent-Based Canvas 2D Emergence
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★★☆ Moderate Popular
Disease Spread — SEIR
SEIR compartmental model with agent-based spread on a 2D map. Adjust R₀, vaccine rollout speed and social-distancing to see epidemic curves in real time.
SEIR Agent-Based Epidemiology
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★☆☆ Beginner
SIR Epidemic Model
Classic Susceptible–Infected–Recovered ODE model. Charts show epidemic flattening as you tune transmission rate β, recovery γ and initial immune fraction.
ODE SIR Chart.js
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★★☆ Moderate
Ant Colony — Pheromone Trails
Thousands of ants find shortest paths to food using pheromone stigmergy. Emergent foraging behaviour from three simple rules: wander, follow scent, deposit trail.
Agent-Based Pheromones Swarm Intelligence
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★☆☆ Beginner
Butterflies & Flowers
Pollinators seeking flowers, resting and flying on a windy meadow. Simple agent rules produce realistic-looking foraging patterns and flower visit frequencies.
Three.js Pollination Agent-Based
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★★☆ Moderate
L-Systems — Procedural Plants
Lindenmayer grammars grow branching plant structures: ferns, trees, algae, seaweed. Edit production rules live and watch the morphology evolve in 2D and 3D.
L-Systems Turtle Graphics Morphogenesis
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★★★ Advanced
Genetic Algorithm
Evolution in action: a population of solutions competing to solve the Travelling Salesman Problem. Selection, crossover and mutation improve fitness generation by generation.
Genetic Algorithm Evolution TSP
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New ★★☆ Moderate
Food Web Simulator
Six-species ecosystem driven by extended Lotka-Volterra equations. Toggle plants, herbivores and carnivores on/off. Watch trophic cascades, competitive exclusion and predator collapse unfold.
Lotka-Volterra Predator-Prey Trophic Cascade
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New ★★☆ Moderate
Wolf–Sheep Predation
Agent-based predator-prey simulation on a 50×50 grid. Wolves hunt sheep, sheep graze grass. Watch population cycles, boom-and-bust dynamics and spatial pattern formation emerge in real time.
Agent-Based Predator-Prey Grid
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★★☆ Moderate
Population Dynamics — Logistic Growth & Predator-Prey
Explore logistic population growth and Lotka-Volterra predator-prey oscillations. Adjust birth rates, death rates and carrying capacity to observe stable equilibria and limit cycles.
Logistic Growth Lotka-Volterra Carrying Capacity Ecology
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New ★★☆ Moderate
Ocean Trophic Web Dynamics
Multi-level ocean food web: phytoplankton → zooplankton → fish → apex predators. Nutrient cycling cl...
Ocean Trophic Web Food Web Marine Ecology

Learning Resources

Articles and tutorials about the algorithms in this category

Article Lotka–Volterra: Predator–Prey Oscillations Derivation of coupled ODEs, phase-plane analysis, equilibrium stability and real-world limitations. → Article SIR Model & Epidemic Curves Basic reproduction number R₀, herd immunity threshold and how interventions shift the epidemic timeline. → Article Boids: Emergent Flocking from Three Rules Reynolds' separation, alignment and cohesion rules — why global behaviour emerges from local agent interactions. →
All articles →

About Ecology & Ecosystem Simulations

Predator-prey dynamics, food webs, and population ecology — modelled

Ecology and ecosystem simulations model the interactions between organisms and their environment. Lotka–Volterra predator-prey simulations show the coupled oscillations of rabbit and fox populations, producing the characteristic population cycles observed in lynx-hare historical records. Agent-based ecosystem models place herbivores and carnivores on a shared landscape with finite food resources, generating emergent territory, migration, and extinction dynamics.

Food-web simulations model energy flow through trophic levels, demonstrating the ten-percent-rule energy loss at each step and the consequences of removing keystone species. Dispersal and competition models show how niche partitioning and habitat fragmentation affect biodiversity. These are the same computational approaches used in conservation biology, fisheries management, and the modelling of coral reef decline under climate change.

Ecological simulations connect individual behaviour to population and ecosystem dynamics. The same mathematics that models fox-rabbit cycles in a meadow also describes lynx-hare oscillations in the Canadian boreal forest, boom-bust cycles in insect pest populations, and the dynamics of marine fisheries under harvesting pressure. Understanding these models is essential for wildlife conservation, sustainable resource management, and climate change impact assessment.

Key Concepts

Topics and algorithms you'll explore in this category

Lotka-VolterraPrey-predator population oscillation equations
Carrying CapacityMaximum sustainable population for a habitat
Food WebTrophic level energy transfer efficiency
SuccessionPrimary and secondary ecological succession stages
Biodiversity IndexShannon entropy as a measure of species diversity
Habitat FragmentationEdge effects and island biogeography theory

Frequently Asked Questions

Common questions about this simulation category

Why do predator and prey populations oscillate?
The Lotka-Volterra equations produce periodic oscillations: prey grow exponentially when predators are rare, predators increase as food becomes abundant, prey decline under predation pressure, and predators decline as food becomes scarce — completing the cycle. Real populations also show this pattern but with added stochasticity.
What is the carrying capacity simulation?
Carrying capacity K appears in the logistic growth equation: dN/dt = rN(1 − N/K). As population N approaches K, growth rate slows to zero. The simulation shows how environmental carrying capacity determines population equilibrium and how disturbances cause recovery trajectories.
How does disease spread relate to ecology?
The SIR (Susceptible-Infected-Recovered) model from epidemiology is mathematically identical to predator-prey dynamics. 'Infection' spreads like a predator consuming prey (susceptible individuals). The basic reproduction number R₀ = β/γ determines whether an outbreak grows or declines.

Other Categories

Every Ecology simulation here runs free in your browser, letting you experiment with each interactive Ecology model — predator-prey dynamics, forest fire spread, coral reef bleaching, carbon cycle feedback and species competition — without installing anything. Adjust population growth rates, carrying capacities and disturbance frequencies to observe real-time results and learn Ecology online at your own pace, whether you are a student, educator or curious researcher. Ecology explores the feedback loops that regulate ecosystems at every scale, from microbial soil communities to global biomes, and the mathematics of these interactions underpins conservation biology, climate modelling and fisheries management. Understanding tipping points and resilience in these simulations builds intuition directly applicable to real-world environmental decision-making.