Modeling the long-term variability of phytoplankton functional groups and primary productivity in the South China Sea
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Primary productivity (PP) and phytoplankton structure play an important role in regulating oceanic carbon cycle. The unique seasonal circulation and upwelling pattern of the South China Sea (SCS) provide an ideal natural laboratory to study the response of nutrients and phytoplankton dynamics to climate variation. In this study, we used a three-dimensional (3D) physical–biogeochemical coupled model to simulate nutrients, phytoplankton biomass, PP, and functional groups in the SCS from 1958 to 2009. The modeled results showed that the annual mean carbon composition of small phytoplankton, diatoms, and coccolithophores was 33.7, 52.7, and 13.6 %, respectively. Diatoms showed a higher seasonal variability than small phytoplankton and coccolithophores. Diatoms were abundant during winter in most areas of the SCS except for the offshore of southeastern Vietnam, where diatom blooms occurred in both summer and winter. Higher values of small phytoplankton and coccolithophores occurred mostly in summer. Our modeled results indicated that the seasonal variability of PP was driven by the East Asian Monsoon. The northeast winter monsoon results in more nutrients in the offshore area of the northwestern Luzon Island and the Sunda Shelf, while the southwest summer monsoon drives coastal upwelling to bring sufficient nutrients to the offshore area of southeastern Vietnam. The modeled PP was correlated with El Niño/Southern Oscillation (ENSO) at the interannual scale. The positive phase of ENSO (El Niño conditions) corresponded to lower PP and the negative phase of ENSO (La Niña conditions) corresponded to higher PP.
KeywordsPhytoplankton functional groups Primary productivity Nutrient dynamics East Asian Monsoon ENSO South China Sea ROMS–CoSiNE model
Funding for this research was provided by the NSFC (Grant No. 41206033, 91128208 40976024). This research was also sponsored by Shanghai Shuguang Program (11SG24) and program for New Century Excellent Talents in University (NCET-08-0401). The computation is facilitated by the University of Maine High Performance Computing Center. We are grateful to the two anonymous reviewers for their constructive comments.
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