In the early 1900s, evolutionary biology was split into two camps that barely spoke the same scientific language.
On one side were the Darwinians, who saw evolution as a slow, continuous process shaped by natural selection. On the other were the Mendelians, who had rediscovered Gregor Mendel’s laws of inheritance and believed evolution occurred through sudden, discrete jumps — the appearance and spread of particular alleles.
The question was:
š If genes are passed in discrete packets, how can evolution produce the smooth, continuous traits we see in nature — like height, skin color, or milk yield?
The person who solved this puzzle was Ronald Aylmer Fisher — a statistician, geneticist, and visionary thinker who showed that Darwin and Mendel were not rivals, but partners in the same grand theory.
šÆ The Problem Before Fisher
By 1910, Mendelian genetics had been rediscovered, but it seemed at odds with Darwin’s vision of gradual evolution. Traits like height in humans or seed weight in plants didn’t follow simple Mendelian ratios (3:1, 1:2:1).
Darwin’s defenders argued for continuous change; Mendel’s followers insisted inheritance was discrete.
Both were right — but no one could prove it.
Fisher saw that this apparent conflict wasn’t biological — it was mathematical.
š§® Fisher’s 1918 Breakthrough: A Marriage of Mathematics and Biology
In 1918, at just 28 years old, Fisher published a paper that changed everything:
“The Correlation Between Relatives on the Supposition of Mendelian Inheritance.”
In it, he demonstrated something astonishing:
š If a trait is influenced by many genes (polygenic inheritance), each contributing a small effect, the combined outcome looks continuous — just like the variation Darwin described.
Here’s the intuition:
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Each gene acts like a tiny light switch — it’s either on or off.
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One switch doesn’t change the whole picture much.
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But when you have hundreds or thousands of such switches, their sum produces a smooth gradient of possible outcomes.
In mathematical terms, Fisher showed that:
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The sum of many small, independent genetic effects follows a normal (bell-shaped) distribution.
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This is why traits like height, weight, and intelligence form smooth curves rather than discrete categories.
It was the first quantitative model of heredity — the foundation of modern quantitative genetics.
š Genes Meet Statistics: The Birth of Biometry
Fisher’s insight went beyond biology — he effectively invented a new branch of statistics to handle biological data.
He introduced concepts like variance, heritability, and analysis of variance (ANOVA), tools still used in laboratories and field studies today.
He explained that:
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Phenotypic variance (Vā) — the variation you see in a population — comes from both
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Genetic variance (Vg) and
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Environmental variance (Ve).
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The heritability (h²) of a trait measures how much of that variance is due to genes.
So when you see that children tend to resemble their parents in height or intelligence, Fisher’s framework lets you quantify how much of that similarity is due to shared genes rather than shared environments.
This analytical power allowed biologists to measure evolution, not just describe it.
š± Why Fisher’s Work Mattered for Evolution
Before Fisher, Darwin’s theory was qualitative — it described how natural selection worked, but not how it could operate on real, measurable variation.
After Fisher:
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Selection became a mathematical force that could change allele frequencies over time.
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Mutation and recombination were sources of new variation that selection could act upon.
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Evolution could now be expressed as a change in gene frequency within a population, giving rise to what would soon be called the Modern Synthesis.
Fisher’s ideas were later expanded by J.B.S. Haldane and Sewall Wright, who explored how selection, drift, and gene flow shape evolution.
But it was Fisher who provided the crucial bridge — the equation that joined Mendel’s laws to Darwin’s vision.
š§ Fisher’s Legacy: More Than Genetics
Fisher wasn’t just a biologist. He was one of the founders of modern statistics. His work gave rise to:
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The t-test, F-test, and analysis of variance (ANOVA).
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Experimental design principles like randomization, replication, and blocking.
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The very idea that biological questions can and should be answered through quantitative analysis.
He brought mathematical precision to biology, transforming it from descriptive natural history into a predictive science.
š From Pea Plants to People: The Power of Polygenic Thinking
Today, Fisher’s polygenic model remains at the heart of fields as diverse as:
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Human genetics, where we study polygenic risk scores for diseases.
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Plant and animal breeding, which still relies on variance components and heritability.
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Evolutionary biology, where quantitative models track how traits evolve under selection and drift.
Every time a genome-wide association study (GWAS) links dozens of small-effect genes to a human trait, it confirms Fisher’s century-old insight:
Continuous traits arise from the combined action of many discrete genes.
š§© In Summary
Ronald Fisher’s 1918 paper solved a mystery that had haunted evolutionary biology for decades:
how discrete genes can produce continuous variation.
By merging Mendelian genetics with statistical reasoning, he showed that evolution is a gradual, measurable process driven by many small genetic changes.
It was this insight that allowed Darwin’s theory of natural selection to evolve into a precise, mathematical science — and that’s why Fisher is often called “the father of modern population genetics.”
“Natural selection is not evolution, but it is the mechanism by which evolution becomes intelligible.”
— R.A. Fisher
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