ITHACA, N.Y. — Scientists have used new machine learning techniques to investigate a topic no one has ever found a way to study: the evolution of fish moving together in schools across thousands of species.
The new paper, published in the Proceedings of the National Academy of Sciences , is among the largest studies of the evolution of any behavior ever conducted in any group of species, according to the authors. The Cornell University research shows that behaviors, which have previously been difficult to quantify, can be studied at a large evolutionary scale.
The study reports that fish species have independently gained the capacity to move together as a unit some 60 times — and lost it some 320 times — across the evolutionary tree of life for fish over the last 350 million years. Species can gain a trait when genetic mutations lead to changes that favor fitness and survival. Once that trait exists, it can be inherited by many descendant species, which can later lose it should it become no longer beneficial.
“Independently, many lineages of fish went from not engaging in collective movement behavior to schooling,” said Andrew Hein , associate professor of computational biology. Hein is senior author of the study; Jay Love, a postdoctoral researcher in Hein’s lab, is first author.
Perhaps what was more surprising is that the behavior was lost so many times, Hein said.
“There were hundreds of examples across the tree where a lineage that engaged in collective movement left a daughter species that was solitary,” he said. “If you had asked me or other evolution of behavior experts before this study, we’d tell you that losses of collective behavior are probably very rare, but that’s simply not true.”
Thanks to advances in machine learning, the researchers were able to classify both written descriptions of species behaviors as well as citizen science images of fish from iNaturalist and other sources to help quantify and analyze schooling behavior from an evolutionary perspective.
For images, the team used a series of machine learning techniques to analyze photos and videos, convert them into three dimensions, and assess the direction that individual fish were headed and pair their alignment with other individuals to determine if they were moving as a group.
The techniques allowed the researchers to test two main hypotheses for why collective movement has evolved.
“One is that it’s related to predator avoidance or collective defense, and that’s never been broadly tested,” Love said. The idea is that there is safety in numbers. To test this, the team examined where species that school occurred in the food chain. They hypothesized that a species low in the food chain with many predators might benefit from schooling. Similarly, one might expect a predator higher in the food chain to be a solitary species.
“We did find this correlation exists,” Hein said. “There, in the data, species that are lower in the food chain are more likely to engage in collective behavior.” But, he added, the relationship isn’t ironclad, as many species low in the food chain don’t school, and many high in the food chain do, suggesting many factors influence whether a species gains or loses collective behavior.
Another hypothesis is that schooling evolved to help individuals find scarce resources, Love said. “It would make sense to follow your neighbors around if they are eating the same thing,” he said.
In fact, predators that move around in groups virtually all eat prey that also move in groups, Hein said.
In addition, the researchers found that lineages where all the species engaged in schooling behavior were far more diverse, developing new species at a higher rate than lineages that didn’t school.
For additional information, read this Cornell Chronicle story .
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Proceedings of the National Academy of Sciences
Evolutionary dynamics of collective behavior across the tree of ray-finned fishes
6-Nov-2026