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Development and application of an algorithm for detecting Phaeocystis globosa blooms in the Case 2 Southern North Sea waters
Astoreca, R.; Rousseau, V.; Ruddick, K.; Knechciak, C.; Van Mol, B.; Parent, J.-Y.; Lancelot, C. (2009). Development and application of an algorithm for detecting Phaeocystis globosa blooms in the Case 2 Southern North Sea waters. J. Plankton Res. 31(3): 287-300.
In: Journal of Plankton Research. Oxford University Press: New York,. ISSN 0142-7873; e-ISSN 1464-3774, more
Peer reviewed article  

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    Absorption (physics) > Light absorption
    Algal blooms
    Aquatic communities > Plankton > Phytoplankton
    Chemical compounds > Organic compounds > Carbohydrates > Glycosides > Pigments
    Data processing
    Environmental effects > Light effects
    Models > Mathematical models
    Organic compounds > Carbohydrates > Glycosides > Pigments > Photosynthetic pigments > Chlorophylls
    Remote sensing
    Water > Sea water
    Phaeocystis globosa Scherffel, 1899 [WoRMS]
    ANE, North Sea [Marine Regions]

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    While mapping algal blooms from space is now well-established, mapping undesirable algal blooms in eutrophicated coastal waters raises further challenge in detecting individual phytoplankton species. In this paper, an algorithm is developed and tested for detecting Phaeocystis globosa blooms in the Southern North Sea. For this purpose, we first measured the light absorption properties of two phytoplankton groups, P. globosa and diatoms, in laboratory-controlled experiments. The main spectral difference between both groups was observed at 467 nm due to the absorption of the pigment chlorophyll c3 only present in P. globosa, suggesting that the absorption at 467 nm can be used to detect this alga in the field. A Phaeocystis-detection algorithm is proposed to retrieve chlorophyll c3 using either total absorption or water-leaving reflectance field data. Application of this algorithm to absorption and reflectance data from Phaeocystis-dominated natural communities shows positive results. Comparison with pigment concentrations and cell counts suggests that the algorithm can flag the presence of P. globosa and provide quantitative information above a chlorophyll c3 threshold of 0.3 mg m-3 equivalent to a P. globosa cell density of 3 × 106 cells L-1. Finally, the possibility of extrapolating this information to remote sensing reflectance data in these turbid waters is evaluated.

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