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🧪 Evolution Of Life

A population of organisms evolves a continuous trait under a tunable fitness landscape: watch the breeder's equation (R = h²S) drive the trait mean toward a single optimum under stabilizing selection, or split the population into two distinct species when the landscape turns disruptive.

Biology2DModerate60 FPS

This simulator models real quantitative-genetics evolution: a population of 240 organisms each carrying one continuous trait evolves generation by generation under a fitness landscape you shape. Selection picks parents in proportion to fitness, offspring traits regress toward the mean by the heritability h² plus a random mutation draw — the same breeder's-equation math (R = h²S) biologists use to predict how a population's trait mean shifts under selection. Keep the landscape's two resource peaks close together and the population converges on a single optimum (stabilizing selection). Pull the peaks apart past a critical separation and the fitness valley between them makes the average phenotype the worst-performing one — the population splits into two persistent trait clusters, a real model of sympatric speciation through disruptive selection.

⚙ Under the hood

This simulation demonstrates the process of evolution through natural selection. It allows users to manipulate environmental factors and observe how species adapt over time.

Evolutionary AlgorithmPopulation Genetics

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install