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MEPS
Marine Ecology Progress Series

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MEPS 370:69-85 (2008)  -  DOI: https://doi.org/10.3354/meps07647

Multivariate analysis of phytoplankton spectral in vivo fluorescence: estimation of phytoplankton biomass during a mesocosm study in the Baltic Sea

Jukka Seppälä1,3,*, Kalle Olli2

1Finnish Institute of Marine Research, Erik Palménin aukio 1, PO Box 2, 00561 Helsinki, Finland
2Institute of Botany and Ecology, University of Tartu, Lai st. 40, 51005 Tartu, Estonia
3Present address: Finnish Environment Institute, PO Box 140, 00251 Helsinki, Finland

ABSTRACT: Multivariate calibration methods were compared for the retrieval of phytoplankton biomass in different taxonomic groups from the spectral fluorescence signal of a living phytoplankton community. During a mesocosm experiment in the northern Gulf of Finland (Baltic Sea), the natural phytoplankton community was manipulated by additions of nutrients and fish. The changes in phytoplankton biomass and species structure were followed using traditional microscopic methods and examination of the spectral fluorescence of living cells. Based on the pigmentation of photosystem II, phytoplankton were divided into 4 groups: (1) cyanobacteria with phycobilins, (2) cryptophytes with phycobilins, chlorophyll a (chl a), chlorophyll c (chl c) and carotenoids, (3) chromophytes with chl a, chl c and carotenoids, and (4) chlorophytes with chl a and chlorophyll b (chl b) and a small amount of carotenoids. The phytoplankton biomass in these groups was predicted from the spectral fluorescence signal using classical least squares, principal component regression, and partial least squares (PLS) regression. The prediction ability of the models was compared using the root mean square error of prediction during full cross validation, partial cross validation and external validation. Regarding relevancy for the operational monitoring of phytoplankton community dynamics using spectral data, the PLS model gave the closest predictions for all taxonomic groups and with the accuracy needed for phytoplankton bloom detection.


KEY WORDS: Multivariate calibration · Partial least squares · Spectral fluorescence signal · Phytoplankton pigments · Baltic Sea


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Cite this article as: Seppälä J, Olli K (2008) Multivariate analysis of phytoplankton spectral in vivo fluorescence: estimation of phytoplankton biomass during a mesocosm study in the Baltic Sea. Mar Ecol Prog Ser 370:69-85. https://doi.org/10.3354/meps07647

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