In a groundbreaking study, researchers from the HUN-REN Centre for Ecological Research have developed a novel three-dimensional modeling method that accurately quantifies how microalgae affect underwater light conditions—one of the most critical factors in aquatic ecosystem health.
Published in Water Research, the study addresses a longstanding challenge in hydrobiology: measuring the projected area—the light-blocking surface—of diverse microalgae species, many of which form colonies or have intricate shapes. These projected areas determine how much light penetrates water columns, directly influencing photosynthesis, oxygen production, and ecological balance in freshwater bodies.
"Algal blooms are not just about biomass," says the lead author, Dr. Gábor Borics. "The shape and structure of the algae matter just as much. Two species with the same volume can differ sixfold in how much light they block."
Using 3D models of 844 common freshwater microalgae—including cyanobacteria, diatoms, and green algae—the team performed over 2,000 virtual simulations per organism to calculate how each species shades its environment under various orientations. The method, validated against analytical models for convex shapes, achieved a projection accuracy of over 95%.
The result: the world's first comprehensive Projected Area Database for freshwater microalgae, now publicly accessible at https://shiny.freshwater-ecology.com/Projected_Area . Researchers and water managers can now estimate how phytoplankton communities alter light regimes using a new metric called the Shading Factor (Fsh)—a potential game-changer in water quality assessment and ecosystem modeling.
Importantly, the study reveals how different morphological adaptations—such as filament length, colony spacing, or spiral structures—can influence species' ecological success under varying light conditions. It also explains why simplified biomass metrics often fail to capture the true ecological impact of algal blooms.
"This is more than an academic advance," says co-author Dr. Gábor Várbíró. "We now have a tool that can reinterpret decades of phytoplankton monitoring data in terms of actual ecological function—not just numbers, but effects."
The research was supported by the Hungarian Scientific Research Fund and leverages the HUN-REN Cloud infrastructure. It sets a new benchmark for trait-based aquatic ecology and provides a foundation for developing light-informed bioindicators for freshwater health.
