Sewall Green Wright ForMemRS HonFRSE (December 21, 1889 – March 3, 1988) was an American scientist who studied genetics. He is best known for his important work on evolutionary theory and for developing a method called path analysis. He helped create the field of population genetics with scientists Ronald Fisher and J. B. S. Haldane. This work was a major step in the modern synthesis, which combines genetics with the study of evolution. Wright discovered the inbreeding coefficient and created methods to calculate it in animals with known family histories. He later expanded this research to populations, calculating how inbreeding occurs between members of populations due to random genetic drift. Along with Fisher, he developed methods to determine how gene frequencies change in populations because of natural selection, mutation, migration, and genetic drift. Wright also made important contributions to the study of mammalian and biochemical genetics.
Biography
Sewall Wright was born in Melrose, Massachusetts, to Philip Green Wright and Elizabeth Quincy Sewall Wright. His parents were first cousins, which was interesting because Wright later studied inbreeding. The family moved three years later after Philip accepted a teaching job at Lombard College, a Universalist college in Galesburg, Illinois.
As a child, Wright helped his father and brother print and publish an early book of poems by his father’s student, Carl Sandburg. At age seven in 1897, he wrote his first book, Wonders of Nature. He published his last paper in 1988, making him the scientist with the longest career of science writing.
He was the oldest of three talented brothers—the others being the aeronautical engineer Theodore Paul Wright and the political scientist Quincy Wright. From an early age, Wright had a love and talent for mathematics and biology. He attended Galesburg High School and graduated in 1906. He then went to Lombard College, where his father taught, to study mathematics. He was greatly influenced by Professor Wilhelmine Key, one of the first women to receive a Ph.D. in biology.
Wright earned his Ph.D. from Harvard University, where he worked at the Bussey Institute with the pioneering mammalian geneticist William Ernest Castle, studying the inheritance of coat colors in mammals. He worked for the U.S. Department of Agriculture until 1925, when he joined the Department of Zoology at the University of Chicago. He remained there until his retirement in 1955, when he moved to the University of Wisconsin–Madison.
During his long career, Wright received many honors, including the National Medal of Science (1966), the Balzan Prize (1984), and the Darwin Medal of the Royal Society (1980). He was a member of the National Academy of Sciences, the American Philosophical Society, the American Academy of Arts and Sciences, and a Foreign Member of the Royal Society. The American Mathematical Society selected him as the Josiah Willards Gibbs lecturer for 1941. For his work on the genetics of evolutionary processes, Wright was awarded the Daniel Giraud Elliot Medal from the National Academy of Sciences in 1945.
He died in Madison, Wisconsin, on March 3, 1988.
Wright married Louise Lane Williams (1895–1975) in 1921. They had three children: Richard, Robert, and Elizabeth.
Sewall Wright worshipped as a Unitarian.
Scientific achievements and credits
Sewall Wright's work on inbreeding, mating systems, and genetic drift helped him become one of the main founders of theoretical population genetics, along with R. A. Fisher and J. B. S. Haldane. Their research formed the basis of the modern evolutionary synthesis, also called the neo-Darwinian synthesis. Wright developed the inbreeding coefficient and F-statistics, which are important tools in population genetics. He also created the mathematical theory of genetic drift, a process sometimes called the Sewall Wright effect. This effect describes how random events, such as births, deaths, and Mendelian inheritance, can cause changes in gene frequencies over time. Wright also introduced the concept of effective population size. He believed that genetic drift and other evolutionary forces, such as natural selection, work together to influence how species adapt. He used the idea of "fitness surfaces" or "evolutionary landscapes" to show how population fitness relates to genetic traits. On these surfaces, the height represents average fitness, while the horizontal axes show allele frequencies or average traits in a population. Natural selection might guide a population toward the nearest peak on the landscape, while genetic drift could cause random movement. Wright disagreed with Fisher's theory of dominance, arguing instead that dominance arises from biochemical processes. Though his ideas were not widely accepted for many years, they now form the foundation of modern understanding of dominance.
Wright explained evolutionary stasis by saying that species often remain on adaptive peaks. To move to a higher peak, a species must pass through a valley of less favorable traits. This might happen through genetic drift if the population is small. If a species splits into smaller groups, some populations might reach higher peaks. If there is gene flow between these groups, their improvements could spread to the rest of the species. This idea is known as Wright's shifting balance theory of evolution. Many scientists have questioned whether the conditions required for this theory are common in natural populations. Wright had a long and heated debate with Fisher, who believed that most natural populations are too large for genetic drift to have a major impact.
Wright developed a statistical method called path analysis in 1921. This was one of the first methods to use a graphical model, and it is still used today in social sciences. He was also a highly influential reviewer of scientific papers, especially for the journal Genetics.
Wright greatly influenced Jay Lush, who played a key role in applying quantitative genetics to animal and plant breeding. From 1915 to 1925, Wright worked for the Animal Husbandry Division of the U.S. Bureau of Animal Husbandry. His main project studied inbreeding in livestock breeds used for beef production. He also conducted experiments with 80,000 guinea pigs to study physiological genetics. He analyzed traits in 40,000 guinea pigs across 23 strains of brother-sister matings compared to a random-bred group. These studies led to the shifting balance theory and the concept of "surfaces of selective value" in 1932.
Wright made significant contributions to the genetics of guinea pigs, and many of his students became important figures in mammalian genetics. As early as 1917, he recognized that genes control enzymes. A story, which Wright himself did not confirm, describes him holding a guinea pig under his armpit during a lecture instead of his usual chalkboard eraser. After the lecture, he reportedly used the guinea pig to erase the blackboard.
The statistical coefficient of determination, used to assess regression analyses, was first introduced by Wright in 1921. This metric is still widely used in computational statistics and machine learning.
Wright was one of the few geneticists of his time who explored philosophy. He collaborated with Charles Hartshorne, a lifelong friend, and supported a form of panpsychism. He believed that consciousness is an inherent property of matter, not a result of increasing complexity. He suggested that even the smallest particles may possess this property.
Legacy
Wright, Fisher, and J.B.S. Haldane were important people in the modern synthesis, which combined genetics and evolution. Their work helped other scientists like Dobzhansky, Mayr, Simpson, Julian Huxley, and Stebbins. The modern synthesis was the most important development in evolutionary biology after Darwin. Wright also made major contributions to mammalian genetics and biochemical genetics.
In The Book of Why (2018), Judea Pearl and Dana Mackenzie explain how Wright's work on path analysis was not quickly accepted by some fields, including statistics and formal causal analysis.
OpenMx uses a picture of Wright's piebald guinea pig as its symbol.