Evolution occurs through changes in allele frequencies over generations. This simulation demonstrates key evolutionary mechanisms including natural selection, genetic drift, and mutation.
About This Simulation
Create a Baldwin effect simulation where learned traits become genetically encoded over generations.
Key Concepts
- Fitness Landscapes: Populations navigate through "fitness landscapes" - conceptual maps where height represents reproductive success. Rugged landscapes have multiple peaks separated by valleys of lower fitness.
- Genetic Drift: Random changes in allele frequencies, especially important in small populations. Can cause alleles to become fixed or lost regardless of their fitness effects.
- Natural Selection: Differential survival and reproduction based on heritable traits. Drives adaptation but can be overwhelmed by drift in small populations.
- Epistasis: Gene interactions where the effect of one gene depends on others. Creates rugged fitness landscapes with multiple local optima.
Why It Matters
Understanding evolutionary dynamics is crucial for conservation biology, disease evolution, antibiotic resistance, and breeding programs.
How to Explore
- Adjust the sliders to modify simulation parameters and observe how the system responds
- Look for emergent patterns that arise from agent interactions
- Try extreme parameter values to find phase transitions and tipping points
- Compare the simulation behavior to real-world phenomena
Category: Evolutionary Dynamics — Exploring evolutionary biology and population genetics