PHYTOPLANKTON FUNCTIONAL TYPES

COMPARISON OF GLOBAL PFT DISTRIBUTIONS OBTAINED WITH VARIOUS EXISTING ALGORITHMS

MOULIN, Cyril¹; ALVAIN, Severine²; BRICAUD, Annick³; CIOTTI, Aurea⁴; CLAUSTRE, Hervé³; DESSAILLY, David²; GENTILI, Bernard³; LOISEL, Hubert²; UITZ, Julia<sup>5

1</sup>LSCE/IPSL (CEA-CNRS-UVSQ) CEA Saclay - bat. 712, Gif-sur-Yvette, --, 91191, France; ²LOG (CNRS-ULCO-USTL), Wimereux, Nord, 62930, France; ³LOV (CNRS-UPMC), Villefranche-sur-Mer, Sud, 06238, France; ⁴AQUARELA, Sao Vicente, n, n, Brazil; ⁵SIO (UCSD), La Jolla, Ca, 92093, United States

Recently, several bio-optical algorithms have been proposed to detect or characterize Phytoplankton Functional Types (PFT) from global ocean color measurements. Despite their common goal, these algorithms are very different in terms of both approach and products, so that dedicated processing are required to perform a quantitative comparison of these new parameters. Two of these algorithms allow retrieving information about the phytoplankton size. The Uitz et al. (2006) algorithm relies on statistical relationships to spread the total chlorophyll-a concentration (Chl-a) into three classes of cell size (i.e., micro-, nano- and pico-phytoplankton), whereas the Ciotti and Bricaud (2006) algorithm examines the phytoplankton absorption spectrum to estimate a continuous size index that gives the ratio between micro- and pico-phytoplankton. Here we have used this index to spread Chl-a between the two classes in order to allow the comparison with the Uitz et al. (2006) product. The third algorithm that has been considered is that of Alvain et al. (2005), PHYSAT, which allows the identification of the dominant phytoplankton group among nanoeukaryotes, prochlorococcus, Synechococcus and diatoms. In order to compare these various PFT to the Inherent Optical Properties (IOP) of the waterbody, we also used the Loisel and Stramski (2000) algorithm to compute the absorption and particulate backscattering coefficients. The spectral slope of the backscattering coefficient, gamma, is known to be a proxy of the particle size. We present here a comparison of all these products for different regions. Despite the difference in terms of approaches, there is generally a remarkable similarity between the two “size” algorithms, in terms of both seasonal cycle and geographical distribution. The comparison with the PHYSAT results is more complicated. For most periods and for most regions, there are good agreements between the micro-phytoplankton class and Diatoms, especially during the periods of maximum Chl-a, and between the pico-phytoplankton class and Prochlorococcus or Synechococcus during the periods of minimum Chl-a. On the contrary, less correlation is observed between the nano-phytoplankton class and nanoeukaryotes, suggesting that this latter PFT might account for phytoplankton cells of various size. The comparison with IOP products shows that gamma is related to the variation of the relative proportion between small and larger particles (including phytoplankton as well as other particles, like detritus) and that its variability is well correlated with that of the phytoplankton size classes.

GLOBAL OBSERVATION OF DIFFERENT PHYTOPLANKTON GROUPS USING PHYTODOAS WITH SCIAMACHY DATA

Bracher, Astrid ¹; Schmitt, Bettina¹; Vountas, Marco ²; Dinter, Tilman ²; Burrows, John Phillip²; Röttgers, Rüdiger ³; Gehnke, Steffen³; Ilka, Peeken<sup>4

1</sup>Alfred-Wegener-Institut Bussestr. 24, Bremerhaven, --, 27570, Germany; ²Institute of Environmental Physics, University of Bremen, Bremen, --, 28334 , Germany; ³Institute of Coastal Research, GKSS, Geesthacht Research Center, Geesthacht, --, 21502, Germany; ⁴IFM Geomar, Kiel, --, 24105, Germany

In order to understand the marine phytoplankton’s role in the global marine ecosystem and biogeochemical cycles it is necessary to derive global information on the distribution of major functional phytoplankton types (PFT) in the world oceans. We use the PhytoDOAS method, the Differential Optical Absorption Spectroscopy used with input of phytoplankton differential absorption spectra, on hyperspectral satellite sensor’s SCIAMACHY ( Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) to retrieve information on the distribution and absorption of different phytoplankton groups, in particular cyanobacteria. SCIAMACHY measures back scattered solar radiation in the UV-Vis-NIR spectral region with a high spectral resolution (0.2 to 1.5 nm). We used in-situ measured phytoplankton absorption spectra taken on five meridional transects across the Atlantic Ocean where different phytoplankton groups were representing or dominating the phytoplankton composition in order to identify these characteristic absorption spectra in SCIAMACHY data in the range of 430 to 500 nm. In addition also SCIAMACHY data were analysed with DOAS in the range of 530 to 590 where absorption from cyanobacterial photosynthetic pigment phycoerythrin was identified. Our results show clearly these phytoplankton assemblage absorptions in the SCIAMACHY data. Phytoplankton concentrations have been determined for three monthly periods (Feb-March 2004, Oct-Nov 2005 and Oct-Nov 2007). The information retrieved by DOAS from SCIAMACHY on phytoplankton groups is compared to collocated in-situ measurements and to the global model analysis with the NASA Ocean Biogeochemical Model (NOBM from http://reason.gsfc.nasa.gov/OPS/Giovanni/) according to Gregg and Casey 2006 and Gregg 2006. Results are of great importance for global modelling of marine ecosystem and climate change studies regarding changes in the ocean.

OPTICAL APPROACH TO DERIVE PHYTOPLANKTON SIZE CLASSES USING OCEAN COLOUR REMOTE SENSING

Hirata, Takafumi¹; Hardman-Mountford, Nick¹; Smyth, Tim¹; Barlow, Ray²; Aiken, Jim<sup>1

1</sup>Plymouth Marine Laboratory Prospect Place, The Hoe, Plymouth, --, PL1 3DH, United Kingdom; ²Marine and Coastal Management / Private Bag X2, Cape Town, Rogge Bay, 8012, South Africa

An optical model to classify dominant phytoplankton size classes is developed for satellite ocean colour application. The model uses a single variable, the optical absorption by phytoplankton at 443 nm, aph(443), that can be derived by ocean colour inversion. Rationale is based on the observation that the absolute magnitude of aph(443) co-varies with the spectral slope of the phytoplankton absorption that is characteristic of the related size classes. Comparison of the model with in situ data taken over the Atlantic transect showed a good agreement especially in open ocean. A global 10-year time series of phytoplankton community composition is produced from SeaWiFS ocean colour data, and used to estimate size-specific primary production. The size-specific primary production showed different seasonal cycles, depending on size classes and regions considered. Use of the results for validation of ecosystem models is also discussed.

DERIVATION OF PHYTOPLANKTON CELL SIZE FROM OCEAN COLOUR RADIOMETRY: APPLICATION TO MERIS DATA

Devred, Emmanuel¹; Sathyendranath, Shubha²; Platt, Trevor<sup>3

1</sup>Dalhousie University 1355 Oxford Street, Halifax, NS, B3H 4J1, Canada; ²Remote Sensing Group, Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth, Devon, PL1 3DH, United Kingdom; ³Ocean Science Division, Bedford Institute of Oceanography, 1 Challenger Drive, Dartmouth, NS, B2Y 4A2, Canada

Cell size is a key property of phytoplankton, informative for marine biogeochemistry. The optical signature of phytoplankton depends, to a certain degree, on cell size distribution. A bio-optical model (Sathyendranath et al. 2001) was applied to phytoplankton absorption measured in situ to infer phytoplankton cell size as the fraction of microphytoplankton in total chlorophyll biomass and the results compared with size fractions obtained from pigment composition (Devred et al., 2006). Here, an inversion algorithm to retrieve the inherent optical properties of marine constituents is used to derive phytoplankton absorption from remote-sensing reflectance. The inversion procedure is tailored to the visible wavebands of the MERIS sensor. A sensitivity study shows that phytoplankton absorption can be retrieved successfully from remote-sensing reflectance with a minimum of three wavelengths in the visible. The satellite-derived phytoplankton absorption is then coupled to our bio-optical model to map microphytoplanton distribution in the North West Atlantic.