Science

Machine learning reveals how often fish schooling evolved—and repeatedly disappeared

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Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 09/11/2026, 23:40:24 UTC.

Briefings

A 2026 study published in the Proceedings of the National Academy of Sciences used machine learning to analyze the evolution of fish schooling across thousands of species. The research demonstrates that complex social behaviors can be quantified and studied at a large evolutionary scale, marking a significant shift in how biological behaviors are investigated. The study represents the largest evolutionary analysis of any behavior ever conducted in any group of species, challenging previous limitations in data collection and analysis.

Key points

• Scientists utilized machine learning techniques to investigate the evolution of fish schooling across thousands of species.
• The research shows that behaviors previously difficult to quantify can now be studied at a large evolutionary scale.

Context

This study represents the largest evolutionary analysis of any behavior ever conducted in any group of species, published in the Proceedings of the National Academy of Sciences. It challenges previous limitations in data collection and analysis, allowing researchers to quantify complex social behaviors across thousands of species.

Limitations

The evidence is limited to the findings of a single 2026 study published in the Proceedings of the National Academy of Sciences. No additional background context or historical data is supplied, and the study's scope remains restricted to the specific evolutionary analysis of fish schooling behaviors.

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