April 10, 2026 — As climate change intensifies harmful algal blooms worldwide, an international team led by Hiroshima University has developed a hybrid modeling approach that combines algal movement simulations, AI, and long-term monitoring data to sharpen forecasts of these bloom events—linked to environmental damage, mass fish die-offs, economic losses, and risks to human health.
Harmful algal blooms (HABs)—responsible for environmental damage, mass fish die-offs, economic downfalls, and even human deaths—are increasing in frequency and severity as Earth warms.
While some computer models can forecast potential blooms, their accuracy is limited by the number of algae species that can bloom harmfully under different environmental triggers, as well as how different species may overlap with one another. However, an international team has demonstrated that coupling three models and accounting for how different algae species interact can significantly improve predictions.
The researchers, led by Fumito Maruyama, a professor with the Center for Planetary Health and Innovation Science at Hiroshima University’s The IDEC Institute, published their work in Ecological Informatics.