Abstract
Cyanobacteria are an important part of phytoplankton communities, however, they are also known for forming massive blooms with potentially deleterious effects on recreational use, human and animal health, and ecosystem functioning. Emerging high-frequency imaging flow cytometry applications, such as Imaging FlowCytobot (IFCB), are crucial in furthering our understanding of the factors driving bloom dynamics, since these applications provide community composition information at frequencies impossible to attain using conventional monitoring methods. However, the proof of applicability of automated imaging applications for studying dynamics of filamentous cyanobacteria is still scarce. In this study we present the first results of IFCB applied to a Baltic Sea cyanobacterial bloom community using a continuous flow-through setup. Our main aim was to demonstrate the pros and cons of the IFCB in identifying filamentous cyanobacterial taxa and in estimating their biomass. Selected environmental parameters (water temperature, wind speed and salinity) were included, in order to demonstrate the dynamics of the system the cyanobacteria occur in and the possibilities for analyzing high-frequency phytoplankton observations against changes in the environment. In order to compare the IFCB results with conventional monitoring methods, filamentous cyanobacteria were enumerated from water samples using light microscopical analysis. Two common bloom forming filamentous cyanobacteria in the Baltic Sea, Aphanizomenon flosaquae and Dolichospermum spp. dominated the bloom, followed by an increase in Oscillatoriales abundance. The IFCB results compared well with the results of the light microscopical analysis, especially in the case of Dolichospermum. Aphanizomenon biomass varied slightly between the methods and the Oscillatoriales results deviated the most. Bloom formation was initiated as water temperature increased to over 15°C and terminated as the wind speed increased, dispersing the bloom. Community shifts were closely related to movements of the water mass. We demonstrate how using a high-frequency imaging flow cytometry application can help understand the development of cyanobacteria summer blooms.
Highlights
Cyanobacteria are among the oldest organisms in the world, and were involved in the process of the Earth evolving into a planet with an oxygen-rich atmosphere
We demonstrate how the taxon-specific high-frequency data, combined with environmental data, provide new possibilities to study the insights of the Baltic Sea cyanobacterial bloom dynamics
Our study demonstrates that IFCB can help in resolving taxon-specific community dynamics during cyanobacterial blooms on a time scale impossible to attain using conventional monitoring methods, and that it can potentially shed light on some unresolved questions concerning the driving environmental forces
Summary
Cyanobacteria are among the oldest organisms in the world, and were involved in the process of the Earth evolving into a planet with an oxygen-rich atmosphere. They are an important component of phytoplankton communities, producing oxygen and recycling nutrients. Harmful cyanobacterial blooms influence the whole ecosystem via production of toxins that are released to the water or transferred to higher trophic levels by grazing zooplankton (Ibelings and Chorus, 2007; Ibelings and Havens, 2008; Sopanen et al, 2009). Massive blooms cause anoxic bottom conditions through sedimentation of a high amount of decaying organic matter as the bloom declines (Vahtera et al, 2007)
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