Low trait value High trait value Fitness landscape W(z)
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Adaptive Landscape: Trait Evolution & Sympatric Speciation

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.