Seasonal variability of the carbon export in the central South China Sea
The South China Sea (SCS) is strongly influenced by the East Asian monsoon system with seasonal reversal. Measurements from a 7-year continuous sediment trap located in the central SCS showed a clear seasonal pattern. The particulate organic carbon (POC) export flux at the depth of 1200 m was considerably higher in monsoon seasons. The driving dynamics leading to this seasonal variability of POC export, however, remains inadequately understood. Here, a one-dimensional physical-biogeochemical coupled model was developed to simulate the temporal variability of a lower-trophic planktonic ecosystem. The modeled POC export flux compared reasonably well with the 7-year time series from moored sediment trap. Model results showed that the POC export flux at 1200 m is highly correlated with the 0–100 m integrated primary productivity and with the export flux at 100 m, implying that the seasonal variability of sediment trap data could be induced by changes in phytoplankton production and its vertical export. Further model analysis suggested that the annual mean export ratio (e-ratio) at 100 m and transfer efficiency at 1200 m in the central SCS were 0.19 and 0.07, respectively, which are lower than those in high latitudes. The winter monsoon favors not only surface carbon fixation but also export to the deep ocean. The heat flux is the dominant factor regulating the seasonal cycle of mixed layer depth, nutrient supply, and the growth of phytoplankton in this region. The wind-driven mixing can further facilitate upward nutrient transport to the surface and amplify the seasonal amplitude of the POC export flux.
KeywordsMarine ecosystem model Sediment trap POC flux Primary productivity South China Sea
Constructive comments from the editor and reviewers improved the quality of this paper. We thank Dr. Yunwei Yan and Dr. Bingxu Geng for valuable discussions. We are grateful to Dr. Zuojun Yu for her editing service. Satellite and reanalysis data were downloaded from the internet (the NCEP Reanalysis dataset, https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html, the OC-CCI V3.1, http://www.esa-oceancolour-cci.org/, the Blended Sea Wind dataset, ftp://eclipse.ncdc.noaa.gov/pub/seawinds/, WOA13 V2, https://www.nodc.noaa.gov/OC5/woa13/).
We also thank financial support from the National Key Research and Development Program of China (Grant No. 2016YFA0601101), National Natural Science Foundation of China (Grant No. 41876123, 41890805, 41576002, 41730536), the Scientific Research Fund of the Second Institute of Oceanography, Ministry of Natural Resources (Grant No. 14283).
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