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The emergence of automated high-frequency flow cytometry: revealing temporal and spatial phytoplankton variability

The emergence of automated high-frequency flow cytometry: revealing temporal and spatial phytoplankton variability
The emergence of automated high-frequency flow cytometry: revealing temporal and spatial phytoplankton variability
Phytoplankton observation is the product of a number of trade-offs related to sampling processes, required level of diversity and size spectrum analysis capabilities of the techniques involved. Instruments combining the morphological and high-frequency analysis for phytoplankton cells are now available. This paper presents an application of the automated high-resolution flow cytometer Cytosub as a tool for analysing phytoplanktonic cells in their natural environment. High resolution data from a temporal study in the Bay of Marseille (analysis every 30 min over 1 month) and a spatial study in the Southern Indian Ocean (analysis every 5 min at 10 knots over 5 days) are presented to illustrate the capabilities and limitations of the instrument. Automated high-frequency flow cytometry revealed the spatial and temporal variability of phytoplankton in the size range 1–50 µm that could not be resolved otherwise. Due to some limitations (instrumental memory, volume analysed per sample), recorded counts could be statistically too low. By combining high-frequency consecutive samples, it is possible to decrease the counting error, following Poisson’s law, and to retain the main features of phytoplankton variability. With this technique, the analysis of phytoplankton variability combines adequate sampling frequency and effective monitoring of community changes.
0142-7873
333-343
Thyssen, M.
324936c1-6e89-4ccc-92d5-6b2c1a8d053f
Tarran, G.A.
c6e9fb51-321c-4fb6-a2b0-00a58c344d73
Zubkov, M.V.
b1dfb3a0-bcff-430c-9031-358a22b50743
Holland, R.J.
4fa388a7-6f5d-4c05-ae3a-bbf254c04483
Gregori, G.
1c2c8e0a-f53b-4d74-b81b-872c3e642a46
Burkill, P.H.
91175019-8b55-4fb5-84ea-334c12de2557
Denis, M.
f3716fbb-89b5-40b3-b558-bd66e28716fd
Thyssen, M.
324936c1-6e89-4ccc-92d5-6b2c1a8d053f
Tarran, G.A.
c6e9fb51-321c-4fb6-a2b0-00a58c344d73
Zubkov, M.V.
b1dfb3a0-bcff-430c-9031-358a22b50743
Holland, R.J.
4fa388a7-6f5d-4c05-ae3a-bbf254c04483
Gregori, G.
1c2c8e0a-f53b-4d74-b81b-872c3e642a46
Burkill, P.H.
91175019-8b55-4fb5-84ea-334c12de2557
Denis, M.
f3716fbb-89b5-40b3-b558-bd66e28716fd

Thyssen, M., Tarran, G.A., Zubkov, M.V., Holland, R.J., Gregori, G., Burkill, P.H. and Denis, M. (2008) The emergence of automated high-frequency flow cytometry: revealing temporal and spatial phytoplankton variability. Journal of Plankton Research, 30 (3), 333-343. (doi:10.1093/plankt/fbn005).

Record type: Article

Abstract

Phytoplankton observation is the product of a number of trade-offs related to sampling processes, required level of diversity and size spectrum analysis capabilities of the techniques involved. Instruments combining the morphological and high-frequency analysis for phytoplankton cells are now available. This paper presents an application of the automated high-resolution flow cytometer Cytosub as a tool for analysing phytoplanktonic cells in their natural environment. High resolution data from a temporal study in the Bay of Marseille (analysis every 30 min over 1 month) and a spatial study in the Southern Indian Ocean (analysis every 5 min at 10 knots over 5 days) are presented to illustrate the capabilities and limitations of the instrument. Automated high-frequency flow cytometry revealed the spatial and temporal variability of phytoplankton in the size range 1–50 µm that could not be resolved otherwise. Due to some limitations (instrumental memory, volume analysed per sample), recorded counts could be statistically too low. By combining high-frequency consecutive samples, it is possible to decrease the counting error, following Poisson’s law, and to retain the main features of phytoplankton variability. With this technique, the analysis of phytoplankton variability combines adequate sampling frequency and effective monitoring of community changes.

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Published date: March 2008

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Local EPrints ID: 51161
URI: http://eprints.soton.ac.uk/id/eprint/51161
ISSN: 0142-7873
PURE UUID: 69763208-57e5-49a5-a8ee-e4dc5f87dd8c

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Date deposited: 08 May 2008
Last modified: 15 Mar 2024 10:15

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Contributors

Author: M. Thyssen
Author: G.A. Tarran
Author: M.V. Zubkov
Author: R.J. Holland
Author: G. Gregori
Author: P.H. Burkill
Author: M. Denis

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