Aristocratic family trees became scientific model

1 October 2019

Before the French Revolution, family trees were reserved for the feudal upper classes, who used them to consolidate their social status. While feudalism broke down and family trees lost their old roles, the trees gained new functions as scientific models. This is shown by a new thesis in the history of science and ideas.

Today, family trees are self-evident metaphors and models for anyone wishing to visualise evolutionary relations and development. Tree charts and arboreal metaphors are particularly pertinent in biology, genetics and linguistics. They are routinely used in data simulation and computer modelling, academic and non-specialist writing, museum displays and teaching.

Despite its overwhelming presence, the tree model is subject to lively debate in the research community. Critics argue that the tree model gives a misleading picture of evolutionary history. Given the greater complexity of molecular-level evolutionary processes than is allowed for by the tree model, criticism has intensified in step with the rapid advances in molecular biology.

French scholarship after the revolution

In a new Uppsala University thesis in the history of ideas, Petter Hellström examines the early history of family trees in the modern sciences. The focus of the thesis is on French scholarship around 1800, i.e. shortly after the French Revolution had abolished the monarchy, aristocracy, and more generally the feudal system.

The thesis builds on historical research showing that genealogy and family trees, in pre-revolutionary France, were employed by the aristocracy to safeguard their family’s social status and access to offices, titles and land. In 1790, however, all inheritance privileges were abolished.

“While French revolutionaries abolished genealogy as a principle of social order, French scientists were discovering genealogy as a principle of natural order. It is hard to say exactly how these events were linked, but the connection in terms of time and place is remarkable,” Hellström says.

In previous research, the histories of evolutionary theory and of the tree model have often been blended together, with the tree model described as virtually a consequence of Darwin’s theory. Hellström’s study shows that the connection was the exact opposite: family trees were used in scientific classification for at least half a century before Darwin adopted the family tree model in his ground-breaking book, On the Origin of Species, first published in 1859.

An order created by God

As Hellström shows in his study, there was no connection between using the family tree as a scientific model and regarding the order of nature as a product of evolutionary processes or development over time – at least not in the first half of the 19th century. Most people who used the tree model during this period had in mind an order created by God.

“The first known family tree of the natural order was drawn by Augustin Augier,” Hellström says. “Augier was both a nobleman and a priest – one of the Revolution’s losers. It is striking that, only a few years after the Revolution, he claimed to have discovered how the order of nature reflected the feudal order in which he himself had grown up.”

Another important result of the study is that the early use of family trees was not confined to natural sciences and language studies. Family trees were used in various fields of knowledge where they are no longer in use today, such as music theory, medicine, and economics.

“Previous research looked backwards from the present, therefore finding trees only in the disciplines where they are used today. I decided, instead, on a time and place, and did a broad search. In the French archives, I found a range of previously overlooked tree charts from completely different fields. I had to fundamentally rewrite the history of trees in science,” Hellström says.



Hellström, P. Trees of Knowledge. Science and the Shape of Genealogy. Uppsala Studies in History of Ideas 51. Uppsala: Acta Universitatis Upsaliensis, 2019. 339 p.

A full-text PDF of the thesis is available upon request. The abstract is available here.