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Ocean Science An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/os-2018-21
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-2018-21
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 19 Mar 2018

Research article | 19 Mar 2018

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This discussion paper is a preprint. A revision of the manuscript is under review for the journal Ocean Science (OS).

High resolution in situ measurements of phytoplankton photosynthesis and abundance in the Dutch North Sea

Hedy M. Aardema1, Machteld Rijkeboer1, Alain Lefebvre2, Arnold Veen1, and Jacco C. Kromkamp3 Hedy M. Aardema et al.
  • 1Laboratory for Hydrobiological Analysis, Rijkswaterstaat (RWS), Zuiderwagenplein 2, 8224 AD Lelystad, the Netherlands
  • 2Ifremer, Laboratoire Environnement et Ressources, BP 699, 62321 Boulogne sur Mer, France
  • 3Department of Estuarine and Delta Systems, NIOZ Royal Netherlands Institute for Sea Research and Utrecht University, P.O. box 140, 4400 AC Yerseke, The Netherlands

Abstract. Marine waters can be highly heterogeneous both on a spatial and temporal scale, yet monitoring is currently mainly limited to low-resolution methods. This study explores the use of two high-resolution methods to study phytoplankton dynamics; Fast Repetition Rate fluorometry (FRRf) to study phytoplankton photosynthesis and scanning flowcytometry (FCM) to study phytoplankton biomass and composition. Measurements were conducted during four cruises on the Dutch North Sea in April, May, June, and August of 2017. Both FRRf and FCM data show spatial heterogeneity with monthly variation. Automated unsupervised Hidden Markov Model (uHMM) spatial clustering resulted in the identification of regions with distinct phytoplankton communities. Manual adjustments were necessary to optimize visualization of some distinct phytoplankton communities. Stepwise multiple linear regression (n=61) revealed that photophysiology (alpha), phytoplankton biomass (total red fluorescence) and abiotic predictors (Turbidity, DIN, time of the day and temperature) determined integrated water column gross primary productivity. Apart from spatial heterogeneity, the diurnal trend is a significant predictor exposing clear trends with other photophysiological parameters. Consequently, spatial patterns are difficult as temporal and spatial patterns occur simultaneously. Nevertheless, high-resolution monitoring is a very useful supplement in addition to regular low-resolution monitoring.

Hedy M. Aardema et al.
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Monitoring of marine waters is currently mainly limited to low-resolution methods, while the ocean can be highly variable both in time and space. This study explores the use of two high-resolution methods to study phytoplankton dynamics and uses a model to organize the large amount of data. The results show that the combination of FRR fluorometry and flowcytometry offers an elaborate view of the phytoplankton community and would be a very useful supplement in addition to regular monitoring.
Monitoring of marine waters is currently mainly limited to low-resolution methods, while the...
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