My dad was part of a group of innovators in paleontology who identified as “paleobiologists”—meaning that they approached their science not as a branch of geology, but rather as the study of the biology and evolution of past life. Since Charles Darwin’s time, paleontology—especially the study of the marine invertebrates that make up most of the record—involved descriptive tasks such as classifying or correlating fossils with layers of the Earth (known as stratigraphy). Some invertebrate paleontologists studied evolution, too, but often these studies were regarded by evolutionary biologists and geneticists as little more than “stamp collecting.”
The use of computers to analyze large data sets changed this image—particularly because it allowed paleontologists like my dad, and his colleague David Raup at the University of Chicago, to expose patterns in the history of life that emerged only on very long timescales. One of their signature contributions was the discovery that life has experienced major, catastrophic mass extinctions at least five times in the Earth’s history (this is why many people now refer to today’s plummeting biodiversity as a “sixth extinction”).
By the mid-1980s, what began as a small, iconoclastic movement had achieved fairly stunning success. A vindicating moment came in 1984, when the English geneticist John Maynard Smith—notoriously skeptical of paleontology’s value to evolutionary analysis—published an essay in Nature inviting paleontologists to the “high table” of evolutionary biology (a reference to the Oxbridge practice of seating fellows and professors on a raised platform in the dining hall).
The analytical, data-driven paleobiology pioneered by my father has now become a cottage industry. Much like algorithms are used in genomics to automate data analysis, a group of researchers at the University of Wisconsin at Madison, for example, recently announced a project called “PaleoDeepDive”—a “statistical machine-reading and learning system, to automatically find and extract fossil-occurrence data from the scientific literature.” Paleobiology’s success has paralleled the advent of computing and the internet, and would seem like an obvious example of the determining impact of technology on science.
The real story is somewhat more complicated, however. My father and his colleagues did not, in fact, “invent” the practice of analyzing the history of life using data. That approach was introduced long before the advent of computers, as far back as the 1830s and ’40s, when the discipline of paleontology was still brand-new.
One of the first scientists to explore life’s history with data was the 19th-century German paleontologist Heinrich Georg Bronn. During his lifetime, Bronn was one of the leading naturalists in Europe; his posthumous fame is connected to his status as one of the first translators of Charles Darwin’s On the Origin of Species. But an intriguing feature of Bronn’s work is that he treated the history of life as a history of data. Much as paleontologists do today, he painstakingly amassed something akin to a huge paper “database” of fossil groups, which allowed him to perform quantitative analyses of populations over time. What he found was that the history of life, seen through data, reveals a grand pattern of dynamic succession: As some groups of organisms ascended and thrived, others passed away to extinction, apparently in a coordinated fashion.