Artificial intelligence helped University of South Florida and National Oceanic and Atmospheric Administration scientists produce the first comprehensive global assessment of floating algae, using 1.2 million satellite images to show that blooms are spreading across much of the world’s ocean. The ScienceDaily report, based on a University of South Florida release dated August 2, 2026, says the growth is likely influenced by changes in ocean temperatures, currents, and nutrient levels, with consequences for marine ecosystems, tourism, public health, and coastal economies.

Chuanmin Hu, professor of oceanography at the USF College of Marine Science and senior author of the Nature Communications paper, said the research gives the first global picture of floating algae, including macroalgal mats and microalgal scum. Macroalgae (large algae such as seaweed) can create open-ocean habitats and nursery grounds for marine species, but large coastal arrivals can decay, damage marine environments, threaten human and animal health, discourage tourism, and create financial losses for coastal communities.

The researchers found that both microalgal scum and macroalgal mats increased globally between 2003 and 2022. Microalgae floating at the ocean surface grew at a statistically significant rate of one percent per year, while macroalgae in the tropical Atlantic and western Pacific increased by 13.4 percent annually. The cumulative area covered by microalgal blooms reached 43.8 million square kilometers (16.9 million square miles), a clear departure from historical patterns.

The study identified a major turning point for macroalgae blooms around 2010. The first large bloom of green seaweed Ulva appeared in the Yellow Sea in 2008, a major sargassum bloom developed in the tropical Atlantic in 2011, and another major bloom followed in the East China Sea in 2012. Hu said that before 2008, no major macroalgae blooms had been reported except sargassum in the Sargasso Sea, and that the global ocean appears to be shifting from macroalgae-poor to macroalgae-rich.

Hu and colleagues analyzed 1.2 million satellite images across 13 geographic zones and five categories of algae. The team trained a deep learning model to detect subtle surface algae signals that often spread across many pixels while accounting for less than one percent of an individual pixel. Lin Qi, an oceanographer at NOAA’s Center for Satellite Applications and Research and first author of the study, modified a previous computer model from the same research group so it could process two decades of global satellite observations.

Training the model took several months and used millions of image features. USF’s Research Computing facility supplied high-performance computing systems that processed several sets of satellite images at the same time, but the full 1.2 million-image analysis still required several months. The study linked the algae expansion to human activity and natural climate variation, including nutrient runoff, warming waters, and other climate-related changes that may differ by region.

Artificial intelligence helped University of South Florida and National Oceanic and Atmospheric Administration scientists produce the first comprehensive global assessment of floating algae, using 1.2 million satellite images to show that blooms are spreading across much of the world’s ocean. The ScienceDaily report, based on a University of South Florida release dated August 2, 2026, says the growth is likely influenced by changes in ocean temperatures, currents, and nutrient levels, with consequences for marine ecosystems, tourism, public health, and coastal economies.

Chuanmin Hu, professor of oceanography at the USF College of Marine Science and senior author of the Nature Communications paper, said the research gives the first global picture of floating algae, including macroalgal mats and microalgal scum. Macroalgae (large algae such as seaweed) can create open-ocean habitats and nursery grounds for marine species, but large coastal arrivals can decay, damage marine environments, threaten human and animal health, discourage tourism, and create financial losses for coastal communities.

The researchers found that both microalgal scum and macroalgal mats increased globally between 2003 and 2022. Microalgae floating at the ocean surface grew at a statistically significant rate of one percent per year, while macroalgae in the tropical Atlantic and western Pacific increased by 13.4 percent annually. The cumulative area covered by microalgal blooms reached 43.8 million square kilometers (16.9 million square miles), a clear departure from historical patterns.

The study identified a major turning point for macroalgae blooms around 2010. The first large bloom of green seaweed Ulva appeared in the Yellow Sea in 2008, a major sargassum bloom developed in the tropical Atlantic in 2011, and another major bloom followed in the East China Sea in 2012. Hu said that before 2008, no major macroalgae blooms had been reported except sargassum in the Sargasso Sea, and that the global ocean appears to be shifting from macroalgae-poor to macroalgae-rich.

Hu and colleagues analyzed 1.2 million satellite images across 13 geographic zones and five categories of algae. The team trained a deep learning model to detect subtle surface algae signals that often spread across many pixels while accounting for less than one percent of an individual pixel. Lin Qi, an oceanographer at NOAA’s Center for Satellite Applications and Research and first author of the study, modified a previous computer model from the same research group so it could process two decades of global satellite observations.

Training the model took several months and used millions of image features. USF’s Research Computing facility supplied high-performance computing systems that processed several sets of satellite images at the same time, but the full 1.2 million-image analysis still required several months. The study linked the algae expansion to human activity and natural climate variation, including nutrient runoff, warming waters, and other climate-related changes that may differ by region.