Taylor, BB et al. (2011): Contiunous surface water uncorrected and quench-corrected active fluorescence and derived chlorophyll a concentration using calibration by HPLC pigments during POLARSTERN cruise ANT-XXV/1. doi:10.1594/PANGAEA.819099, Supplement to:Taylor, Bettina B; Torrecilla, Elena; Bernhardt, Anja; Taylor, Marc H; Peeken, Ilka; Röttgers, Rüdiger; Piera, Jaume; Bracher, Astrid (2011): Bio-optical provinces in the eastern Atlantic Ocean and their biogeographical relevance. Biogeosciences, 8, 3609-3629, doi:10.5194/bg-8-3609-2011
The relationship between phytoplankton assemblages and the associated optical properties of the water body is important for the further development of algorithms for large-scale remote sensing of phytoplankton biomass and the identification of phytoplankton functional types (PFTs), which are often representative for different biogeochemical export scenarios. Optical in-situ measurements aid in the identification of phytoplankton groups with differing pigment compositions and are widely used to validate remote sensing data. In this study we present results from an interdisciplinary cruise aboard the RV Polarstern along a north-to-south transect in the eastern Atlantic Ocean in November 2008. Phytoplankton community composition was identified using a broad set of in-situ measurements. Water samples from the surface and the depth of maximum chlorophyll concentration were analyzed by high performance liquid chromatography (HPLC), flow cytometry, spectrophotometry and microscopy. Simultaneously, the above- and underwater light field was measured by a set of high spectral resolution (hyperspectral) radiometers. An unsupervised cluster algorithm applied to the measured parameters allowed us to define bio-optical provinces, which we compared to ecological provinces proposed elsewhere in the literature. As could be expected, picophytoplankton was responsible for most of the variability of PFTs in the eastern Atlantic Ocean. Our bio-optical clusters agreed well with established provinces and thus can be used to classify areas of similar biogeography. This method has the potential to become an automated approach where satellite data could be used to identify shifting boundaries of established ecological provinces or to track exceptions from the rule to improve our understanding of the biogeochemical cycles in the ocean.