BIO 202 — Evolution

Interactive simulations · Coe College

These are short, self-contained lessons. Each one asks you to make a prediction before you touch any controls, then lets you test that prediction against a simulation and against real data.

Lessons

Unit 1 — How variation gets measured

Adding up coin flips until a bell appears

Stack many small independent events and watch the bell shape emerge. Discover that the mean is the best single guess when you have no other information. End at y ~ Normal(μ, σ).

Resampling to ask if new data still belongs

A draw stream where the population silently switches mid-way. Build a typical range from the early data, then watch new draws either stay inside it or land outside. NHANES vs. NBA heights anchor the empirical step.

Subtracting the line and reading what's left

Best constant guess becomes a best linear guess. Subtract the fit and read what the model didn't explain. Five-round residual-pattern drill across mammals, birds, finches, fossils. Beren and Cyrus's growth data for the sick-day reveal.

Finding the cloud of lines that all fit the data

Drag a line and chase the OLS R². Find 20 different (α, β) pairs that all match. Bootstrap the cloud. The "single best fit" is one realization from a wider landscape of nearly-as-good fits.

Shuffling the predictor to see what chance can do

Fit the regression, then break the relationship by shuffling the predictor. Watch how often the broken version still produces a coefficient as big as the real one. Two scenarios + a five-round real-data drill.

Watching the same biology give four different verdicts

Four scenarios where the same shuffle-the-predictor machine returns a different answer when you change sample size, within-group noise, or what you asked it to compare. Non-transitivity, sample-size dominance, effect-vs-precision, equal means with unequal variances.

Tracing how much of a parent ends up in their child

Couple two simulated traits and watch the cloud tilt as parents pass more (or less) of their deviation to their children. Fit a line — its slope has a name. Reproduce the same slope from Galton's 1885 family data. Bridge into Unit 2.

Unit 2 — How traits pass between generations · draft skeletons

Lesson 8 · draft

Counting the ratios that breed true

Mendel's peas. Monohybrid 3:1, dihybrid 9:3:3:1, chi-squared on observed counts. Why dominant/recessive aren't properties of genes.

Lesson 9 · draft

Building the population where nothing changes

Hardy-Weinberg as the null. Turn off the assumptions one at a time; see what each violation does to genotype frequencies. Italian sparrow loci anchor the empirical step.

Lesson 10 · draft

Watching alleles wander in a finite population

Wright-Fisher drift. Absorbing boundaries, fixation probability, time to fixation. Buri's 107 fly lines anchor the empirical fit.

Lesson 11 · draft

Reading drift in the wild when a population gets small

Florida Scrub Jay. Heterozygosity decay, two-epoch demography, fitting Nₑ from observed allele-frequency time courses.

Lesson 12 · draft

Pushing the allele frequency with selection

Selection coefficient, deterministic vs drift-perturbed trajectories, reading s off Δp. LTEE allele frequencies anchor the empirical step.

Lesson 13 · draft

Where deleterious alleles get held in place

Mutation-selection balance: q ≈ μ/(hs). The formula's failure on cystic fibrosis as the empirical reveal.

Unit 3 — How populations organize themselves · draft skeletons

Lesson 14 · draft

Counting heterozygote deficits

The F statistic. F = 1 means you don't have one population — you have two. F_IS / F_ST / F_IT decomposition.

Lesson 15 · draft

The response to selection is a regression line in disguise

R = h²·S. The breeder's equation as the Galton slope. Grant finches year by year, with the direction flipping between droughts and wet El Niño years.

Lesson 16 · draft

Spreading or staying — populations connected by migration

F_ST and migration as drift's mirror image. Italian sparrow hybrid zone. Genes flow even when individuals don't.

Lesson 17 · draft

Helping relatives when cooperation can spread

Hamilton's rule, r·b > c. Why worker bees don't reproduce — the math of inclusive fitness drives sterility.

Lesson 18 · draft

Reading trees with rotated nodes

The horizontal order of the tips means nothing. MRCA-finding drill. The "primitive" trap. Anolis tree as the empirical anchor.

Lesson 19 · draft

Removing the family resemblance before comparing species

PGLS. Species are not independent observations. The same earthworm regression flips sign when ancestry is subtracted. AVONET birds, hand-wing index vs migration distance.

Unit 4 — How long-timescale change accumulates · draft skeletons

Lesson 20 · draft

Measuring rates across sliding intervals

Gingerich's rate-vs-interval decline. Why rates fall with longer intervals. LTEE, Grant finches, Hyopsodus all land on the same curve.

Lesson 21 · draft

Mutation target size and the parallel evolution it produces

Hox genes change almost not at all over half a billion years. Microsatellites change fast. The rate is set by how big a target the mutation has and how badly it hurts when it lands.

Lesson 22 · draft

Reading selection off codon ratios

dN/dS. Below 1, purifying selection. Above 1, positive selection. Sliding-window analysis on MHC, GULO, SARS-CoV-2 spike.

Lesson 23 · draft

The Dobzhansky–Muller incompatibility snowball

Hybrid incompatibilities accumulate as pairs, not singletons. The n² snowball. Stop the wedding, kill the baby.

Lesson 24 · draft

Convergence vs drift vs shared ancestry

Same trait, three histories. Pangolins and armadillos. Penguins and hummingbirds. Anolis ecomorphs reaching the same form on every Caribbean island.

Lesson 25 · draft

Deciding one species or two — and what would change your mind

Species is a hypothesis about future independence. Ring species, Rhagoletis flies, F2 breakdown. The 120 textbook definitions are 120 methods for testing the same claim.

Unit 5 — The emergence of privileged levels · draft skeletons (branching tree)

Lesson 26 · CORE · draft

The Price equation — splitting Δz̄ into two covariances

The master equation. One level, then two nested. Hamilton's rule (Lesson 17) falls out as a special case. Required spine of Unit 5.

Lesson 27 · branch · draft

When the chromosome becomes the unit

Gene → chromosome. A locus is just a chunk of DNA that selection hasn't recombined apart yet. Dachshund FGFR3 sweep — 20 Mb of zero diversity.

Lesson 28 · branch · draft

When the genome wins out over the gene

Chromosome → genome. Meiotic drive, transposons, suppressors. The rules of meiosis are themselves evolving, which means they can be cheated.

Lesson 29 · branch · draft

When the cell wins out over the genome

Genome → cell. Endosymbiosis, somatic mosaicism, cancer initiation. Differential reproduction can be hidden inside one cell.

Lesson 30 · CORE · draft

When cells stop competing — the body emerges

Cell → individual. Your body is a bee colony. Volvox, cancer, kin selection on cells. Required core lesson — the canonical transition.

Lesson 31 · branch · draft

When workers stop reproducing — the colony emerges

Individual → superorganism. Honeybees, naked mole rats. Same algebra as Lesson 30, one scale up.

Lesson 32 · branch · draft

When species outpersist each other

Superorganism → lineage. Speciation rate as a heritable species trait. Fairy wrens speciate; platypus doesn't. Selection above the individual.

Lesson 33 · branch · draft

Beyond the species — when the unit doesn't have a name yet

Lineage → ? Memes (Dawkins 1976), holobionts, prions, hypothetical alien biology. The student picks a candidate unit and runs the diagnostic.

Lesson 34 · CORE · draft

Capstone — What is an Individual?

The seven cascades side by side. Same algebra at every scale. We exist at our level because that level is special — not the reverse. Course bookend with Lesson 1's "evolution is motion." Required synthesis.

Scaffolds — small, repeated practice

Short guess-and-check exercises. Each one drills a single concept across five rounds with different data or parameters. The concept is named only after you have produced it yourself five times. Read the top of each page for the rhythm.

"No trend" is a distribution

Predict the 95% half-width of a shuffle-null for slope. Fortis beak depth (two windows), LTEE (two windows), PETS Hyopsodus.

Residual reading across datasets

Classify residual patterns as clean / curvature / two clouds / heteroskedasticity. Pantheria mammals, Avonet birds, LTEE.

HWE genotype counting

Given p and N, predict the heterozygote count. Panmictic, pedigreed wild pop, inbred colony, Wahlund, plus one reverse-direction round.

Fixation probability

Predict the fraction of Wright–Fisher replicates that will fix the allele. Five (p₀, Nₑ) combinations.

Time to fixation scales with Nₑ

Predict the median generations until fixation-or-loss. Nₑ sweeps 20, 50, 200; p₀ sweeps 0.1, 0.5, 0.9.

Drift, selection, or both?

Classify five trajectories: three simulated at different (s, Nₑ), plus LTEE fitness and an FSJ SNP.

Breeder's equation, year by year

Predict R = h² · S for five different Grant-finch years. Drought, wet El Niño, character displacement, quiet years.

Selection coefficient from Δp

Given (p₀, pₜ, t, Nₑ), estimate s. Likelihood profile with 95% CI. Some rounds give tight estimates, some CIs span zero.

Mutation–selection balance

Predict q̂ for recessive lethals, additive lethals, and near-recessive edge cases — plus cystic fibrosis, where the formula visibly fails.

F and the heterozygote deficit

From genotype counts, compute F. Panmictic, pedigreed wild pop, sibling mating, Wahlund, heterozygote excess.

F_ST and migration

Three forward rounds (guess F_ST from Nₑ and m) and two inverse rounds using Atlantic cod from open-coast vs. inner-fjord populations.

Hamilton's rule across levels

Predict whether helping spreads when rB > C. Prairie dog siblings and cousins, turkey helpers, bacterial cooperation, plus an unrelated-strangers control.

Reading trees with rotated nodes

Click the sister pair in five phylogenies whose layouts are designed to fool you. After each answer, see the same tree redrawn.

Rates of evolution across intervals

Predict the median rate of change across sliding windows. LTEE at three interval lengths, Grant finches at 1 year, Hyopsodus at 0.5 MY — Gingerich's decline.

Phylogenetic non-independence

Predict naïve vs. clade-centered slopes across four Avonet trait pairs plus one Simpson's-paradox synthetic case.

The Dobzhansky–Muller snowball

Predict the number of hybrid incompatibilities as divergence time doubles. Rates grow as t², and the tally shows the log-log line.

Mutation target size and parallel evolution

Classify five phenotypes by effective mutation rate. Webbed feet, cave eye loss, lactase persistence, the placenta, hinged jaws.

dN/dS classification

Classify five genes by selection regime. MHC, Histone H3, the GULO pseudogene, SARS-CoV-2 spike, mitochondrial cytochrome b.

Convergence vs. drift vs. shared ancestry

Classify five repeated-pattern cases. Anolis ecomorphs, stickleback armor, Kolbe founders, cave eye loss, human mtDNA.

Species as hypotheses

Decide one species or two — and name the observation that would flip your call. Ring species, Rhagoletis, F2 breakdown, color polymorphism.