Remote sensing of picophytoplankton distribution in the northern South China Sea

By using a global data set (NOMAD), improved algorithms were developed for deducing from ocean color remote sensing data the concentrations of phytoplankton pigments, total chlorophyll alpha (TChl_alpha), zeaxanthin (Zea) and fucoxanthin (Fuco), and the associated primary phytoplankton groups, namely, Prochlorococcus, Synechococcus, haptophytes and diatoms, in the oceans. A modified classification for the waters of the world's ocean based on the dominant phytoplankton group was then devised. By using a local data set from the northern South China Sea (NSCS), algorithms were also developed for assessing the cell abundances of picophytoplankton, Prochlorococcus, Synechococcus and pico-eukaryotes, in this region. These algorithms were then applied to the remotely sensed data from the MODerate-resolution Imaging Spectrometer at Aqua sensor (MODIS-Aqua) to study the abundances and the distributional patterns of picophytoplankton in the entire NSCS. The results agreed well with field observations, which were available only from selected locations in the study area. On a basin scale, the results were consistent with expected variations in phytoplankton pigments, phytoplankton community composition, and picophytoplankton biomass, in response to the major known environmental phenomena in the NSCS, such as the progressive increase in biological productivity towards the coast, the runoff from the Pearl River, higher biological productivity in the wintertime, upwelling around the Taiwan Bank, winter upwelling northwest of the Luzon Island, and the transformation and dissipation of internal waves off the Dongsha Atoll. This work represents the first effort in estimating the cell abundances of the principal picophytoplankton groups in the oceans from space. The general application of this approach to the global ocean needs to be further validated and calibrated with a more extensive data base from field observations in other parts of the oceans. (C) 2012 Elsevier Inc. All rights reserved.