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Updated: Aug 15, 2026

Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation
Published on: November 18, 2015
Slow vertical floating velocity and rapid buoyancy loss promote subsurface distribution of Raphidiopsis raciborskii:
Yanhong Chen1, Michele A Burford2, Christopher Keneally3
1College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China; School of Biological Sciences, Faculty of Science, Engineering and Technology, The University of Adelaide, South Australia 5005, Australia.
Abstract:
Raphidiopsis raciborskii (Wołoszyńska) Aguilera et al., a potentially toxic filamentous cyanobacterium, typically forms subsurface aggregations, rather than surface blooms. This contrasts with many other problematic cyanobacteria and makes early detection and management more difficult. We hypothesize that this subsurface distribution arises from the interaction between light-driven buoyancy regulation and trait-dependent factors related to sinking. To test this hypothesis, we quantified changes in cellular density and relative gas vesicle volume under different light irradiances and incorporated these measurements into a light-driven vertical migration model that simulated the diurnal movement of R. raciborskii filaments. Our results highlight that subsurface accumulation is the dominant and robust outcome across a wide range of environmental and trait scenarios. This pattern emerges because high irradiance further reduces gas vesicle volume and buoyancy, while larger form resistance and smaller filament length slow upward migration, together limiting the ability of filaments to reach the surface. Turbulent mixing further enhances subsurface retention by redistributing filaments into deep layers and decreasing the frequency of surface-directed migration. Subsurface accumulations were more often observed in simulations than surface accumulations, which is an emergent property of coupled physiological and physical processes of R. raciborskii. Insights into physiology and trait-based models form the basis for accurate predictions of individual growth, competitiveness and blooms.
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