A steady “snowfall” of tiny particles carries carbon, nutrients and pollution from the ocean’s surface toward the deep sea.
A steady “snowfall” of tiny particles carries carbon, nutrients and pollution from the ocean’s surface toward the deep sea. Scientists can see those particles sinking, but determining exactly what they contain is much harder. URI Graduate School of Oceanography Research Professor Melissa Omand is turning to artificial intelligence to help solve that problem.
Omand, along with collaborators at the University of Maine, is developing AI tools that could determine the chemical contents of “marine snow,” particles made up of organic matter, minerals, and other materials that continually sink through the ocean.
“Marine snow is a term used to describe the small sinking particles that are produced when phytoplankton die, or are excreted by larger organisms,” said Omand. “These particles are rich in carbon and other nutrients and provide a key food source for deep-living marine life, as well as having an important role in marine carbon sequestration.”
Underwater cameras can capture large numbers of marine snow particles and reveal characteristics such as their size, shape, and transparency. Images alone, however, generally cannot tell scientists what the particles are made of. If successful, the approach could help scientists learn more from the underwater images they already collect, while reducing the time spent manually classifying particles and improving estimates of how material moves through the ocean.
Read More: University of Rhode Island
