Quantifying phytoplankton communities using spectral fluorescence: the effects of species composition and physiological state

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Abstract

In situ fluorometers are the optimal means of providing high-frequency estimates of phytoplankton communities. However, they may be subjected to measurement biases originating from variations in the physiological states of cells, the use of spectral fluorescence signatures (SFS) defined on the basis of inappropriate phytoplankton groups and the lack of linear independence between selected sets of SFS. We assessed correction procedures for measurement biases in mono and mixed cultures of five freshwater phytoplankton species. We investigated the impacts of total Chla levels, the lack of linear independence between SFS and varying physiological states on the accuracy of the Chla estimates that were provided by the FluoroProbe (bbe Moldaenke GmbH, Germany). The use of species-specific SFS allowed for the correction of quantification and classification biases. In some cases, the procedure led to a lack of linear independence between SFS, which significantly reduced estimation accuracies. A convenient method to evaluate linear independence between SFS is provided. Differences in the physiological states of phytoplankton cultures following light pre-acclimation and/or N-starvation appeared to be species specific. Light pre-acclimation led to an underestimation of biomass (up to −28.5%) through fluorescence quenching. The responses of the phytoplankton cultures to N-starvation varied depending on the species (from −40.3 to +336% biases in Chla quantification). Overall, the application of appropriate corrective measures increased data accuracy. However, optimal data reliability can only be achieved by estimating phytoplankton community composition and associated environmental conditions.

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