Read a probability distribution of drift rather than one lucky trajectory
Genetic drift is variation in inherited frequencies due to finite sampling. It can occur without a selective advantage. Different replicate populations started from the same frequency can move in opposite directions, so one realized increase does not establish that an allele was favored.
Learning outcome: Compare Ne2,4 and10 at p0.4. Record the distribution spread, immediate loss/fixation and expected heterozygosity. Explain why the horizontal axis must be next-generation frequency rather than generation number.
Starting recap
Distinguish population mechanisms using explicit allele, genotype, life-cycle and sampling denominators; compare conditional explanations and independent falsifying evidence.
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Try
With Ne4 and p0.4, eight copies are drawn. Mean next frequency0.4, variance0.24/8=0.03 and immediate loss0.6^8=0.01679616. Immediate fixation0.4^8=0.00065536, not0.4;0.4 describes a different eventual neutral-fixation result under additional continuing-model assumptions.
Open the experimentPredict
If the average frequency across many replicates is unchanged, can drift still reduce diversity?
Experiment
Compare Ne2,4 and10 at p0.4. Record the distribution spread, immediate loss/fixation and expected heterozygosity. Explain why the horizontal axis must be next-generation frequency rather than generation number.
Inspect an entire one-generation drift distribution
Worked teaching model · synthetic values · Ideal Wright–Fisher sampling:2Ne independent allele draws with replacement, constant pool p, no selection or mutation. Ne is a model sampling parameter, not automatically the census size.
Reset keeps your prediction, captures and practice history.
Neutral sampling has no directional mean change, yet individual replicate populations vary and can lose alleles.
This graph is a distribution across hypothetical replicate populations, not a time trajectory. Loss/fixation probabilities are for one generation, not eventual fixation; the latter requires a separate model and time horizon.
Solid: Exact binomial sampling probabilities. Axes rescale to the current range; use labeled values rather than comparing graph heights across settings.
| Next A frequency | Exact binomial sampling probabilities (Probability mass) |
|---|---|
| 0 | 0.01679616 |
| 0.125 | 0.08957952 |
| 0.25 | 0.2090189 |
| 0.375 | 0.2786918 |
| 0.5 | 0.2322432 |
| 0.625 | 0.1238630 |
| 0.75 | 0.04128768 |
| 0.875 | 0.007864320 |
| 1 | 0.0006553600 |
| Quantity | Value | Unit |
|---|---|---|
| Expected next-generation A frequency | 0.4000000 | fraction |
| Variance of next-generation frequency | 0.03000000 | frequency squared |
| Immediate loss probability | 0.01679616 | probability |
| Immediate fixation probability | 0.0006553600 | probability |
| Expected heterozygosity after one sample | 0.4200000 | fraction |
Retain prior predictions, settings and quantities in the notebook. These are original supplied/calculated comparisons, not physical specimen observations or laboratory participation.
Neutral sampling has no directional mean change, yet individual replicate populations vary and can lose alleles.
This graph is a distribution across hypothetical replicate populations, not a time trajectory. Loss/fixation probabilities are for one generation, not eventual fixation; the latter requires a separate model and time horizon.
Captures preserve recipes and replay their calculated results. They are synthetic model evidence, not physical measurements.
Understand
Apply
Public practice checks a specific claim. It does not establish independent mastery.
For Ne5,p0.5, find variance, one-generation loss probability and expected heterozygosity.
Continue
Completion requires a saved prediction, at least one capture and a reflection. Presence checks do not grade your reasoning.
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