High-resolution analysis of a North Sea phytoplankton community structure based on in situ flow cytometry observations and potential implication for remote sensing

[摘要] Phytoplankton observation in the ocean can be a challenge in oceanography.Accurate estimations of its biomass and dynamics will help to understandocean ecosystems and refine global climate models. Relevant data sets ofphytoplankton defined at a functional level and on a sub-meso- and daily scale are thus required. In order to achieve this, an automated,high-frequency, dedicated scanning flow cytometer (SFC, Cytobuoy b.v., the Netherlands) has beendeveloped to cover the entire size range of phytoplankton cells whilstsimultaneously taking pictures of the largest of them. This cytometer wasdirectly connected to the water inlet of a PocketFerryBox during a cruisein the North Sea, 08–12 May 2011 (DYMAPHY project, INTERREG IV A "2 Seas"),in order to identify the phytoplankton community structure of near surfacewaters (6 m) with a high spatial resolution basis (2.2 ± 1.8 km). Tengroups of cells, distinguished on the basis of their optical pulse shapes,were described (abundance, size estimate, red fluorescence per unit volume).Abundances varied depending on the hydrological status of the traversedwaters, reflecting different stages of the North Sea blooming period.Comparisons between several techniques analysing chlorophyll a and thescanning flow cytometer, using the integrated red fluorescence emitted byeach counted cell, showed significant correlations. For the first time, thecommunity structure observed from the automated flow cytometry data set wascompared with PHYSAT reflectance anomalies over a daily scale. The number ofmatchups observed between the SFC automated high-frequency in situ sampling andremote sensing was found to be more than 2 times better than when usingtraditional water sampling strategies. Significant differences in thephytoplankton community structure within the 2 days for which matchupswere available suggest that it is possible to label PHYSAT anomalies usingautomated flow cytometry to resolve not only dominant groups but also communitystructure.

[学科分类] 地球化学与岩石