4.5 Article

Weekly flow cytometric analysis of riverine phytoplankton to determine seasonal bloom dynamics

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ENVIRONMENTAL SCIENCE-PROCESSES & IMPACTS
卷 16, 期 3, 页码 594-603

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ROYAL SOC CHEMISTRY
DOI: 10.1039/c3em00657c

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  1. NERC for Ecology & Hydrology National Capability through the CEH Thames Initiative
  2. Natural Environment Research Council [CEH010021] Funding Source: researchfish

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Understanding the relative role of anthropogenic and environmental drivers on the timing, magnitude and composition of algal and cyanobacterial blooms is vitally important for the effective management of river catchments. Whilst taxonomic identification and enumeration of algal species can provide valuable insights, the time and specialist skills needed for this approach makes it prohibitive for high frequency and multiple-site studies. Other proxies for phytoplankton, such as total chlorophyll concentration provide little information on community composition. Here we demonstrate the use of flow cytometry (FCM) as a viable alternative approach for monitoring the changing seasonal patterns of abundance, composition and biovolume of phytoplankton in rivers. A FCM assay was set up and calibrated using a range of pure algal cultures and then applied to a year-long, weekly sampling campaign on the River Thames at Wallingford, UK. Ten groups of phytoplankton representing diatoms, chlorophytes, cryptophytes and cyanobacteria were monitored over the course of the year and examined in relation to river physiochemical parameters. Major diatom blooms occurred in spring and autumn, correlating with depletion of soluble reactive phosphorus and dissolved silicon concentrations and we also observed a significant and sustained cyanobacteria bloom between July and October. Pico-chlorophytes (0.2-2.0 mu m in diameter) dominated the community throughout the summer period but were not detected using traditional colorimetric chlorophyll analysis, suggesting underestimates of actual phytoplankton standing stocks by traditional methods. We demonstrate high resolution sampling and FCM as a sensitive method for river ecosystem monitoring and that FCM data may be used as an indicator of riverine health.

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