Traditional monitoring depends on a counting method developed in 1958. A technician identifies each cell under a microscope. The technique is slow, demands scarce expertise and, most importantly, cannot tell a harmless alga from its toxic twin.

"Under the microscope, a harmless alga and its toxic relative can look identical," Andrei said. "Their DNA likely holds the key to telling them apart."

How was the atlas built?

The researchers analyzed 3,400 DNA datasets. They filtered lake water, sequenced every piece of DNA caught on the membrane and used a machine-learning tool to isolate mitochondrial sequences. Mitochondrial genomes are small and easy to reconstruct. They also evolve faster than nuclear DNA, so even closely related species carry clearly different versions.

To keep species assignments consistent across lakes, seasons and studies, the team set a fixed rule: two mitochondrial genomes at least 98.1 percent identical count as the same species.

Could this replace microscope monitoring?

Not yet. The atlas is a reference library, not a finished monitoring tool. Existing DNA tests use molecular "baits" designed for specific groups, so other organisms slip through. The new approach should capture a wider range of species, but it still needs validation against the older methods.

Andrei said the broader goal is faster, more accurate surveillance of lakes and reservoirs. "For more than 60 years, we have seen only a fraction of the life in the lakes and reservoirs that provide drinking water to more than 180 million Europeans," he said. "Soon, a single bottle of lake water could reveal who lives in it, what's new and what's changing."

The authors describe the work as a foundation. As more genomes are added to the dataset, identification should grow faster, cheaper and more reliable. For now, the atlas makes one thing clear: a great deal of the life in our lakes has yet to be named.