Spatiotemporal Variability of Surface Phytoplankton Carbon and Carbon-to-Chlorophyll a Ratio in the South China Sea Based on Satellite Data

Abstract

The spatiotemporal variability of phytoplankton biomass has been widely studied because of its importance in biogeochemical cycles. Chlorophyll a (Chl-a)—an essential pigment present in photoautotrophic organisms—is widely used as an indicator for oceanic phytoplankton biomass because it could be easily measured with calibrated optical sensors. However, the intracellular Chl-a content varies with light, nutrient levels, and temperature and could misrepresent phytoplankton biomass. In this study, we estimated the concentration of phytoplankton carbon—a more suitable indicator for phytoplankton biomass—using a regionally adjusted bio-optical algorithm with satellite data in the South China Sea (SCS). Phytoplankton carbon and the carbon-to-Chl-a ratio (θ) exhibited considerable variability spatially and seasonally. Generally, phytoplankton carbon in the northern SCS was higher than that in the western and central parts. The regional monthly mean phytoplankton carbon in the northern SCS showed a prominent peak during December and January. A similar pattern was shown in the central part of SCS, but its peak was weaker. Besides the winter peak, the western part of SCS had a secondary maximum of phytoplankton carbon during summer. θ exhibited significant seasonal variability in the northern SCS, but a relatively weak seasonal change in the western and central parts. θ had a peak in September and a trough in January in the northern and central parts of SCS, whereas in the western SCS the minimum and maximum θ was found in August and during October–April of the following year, respectively. Overall, θ ranged from 26.06 to 123.99 in the SCS, which implies that the carbon content could vary up to four times given a specific Chl-a value. The variations in θ were found to be related to changing phytoplankton community composition, as well as dynamic phytoplankton physiological activities in response to environmental influences; which also exhibit much spatial differences in the SCS. Our results imply that the spatiotemporal variability of θ should be considered, rather than simply used a single value when converting Chl-a to phytoplankton carbon biomass in the SCS, especially, when verifying the simulation results of biogeochemical models.

Seasonal variability of satellite-derived primary production in the South China Sea from an absorption-based model

“…In comparison with the seasonal clustering results for the surface CHL (Xu et al, 2020), there are relatively few typical subdivisions of the NPP in the deeper than 200 m region. Under the same clustering conditions, only northwestern Luzon was the common characteristic area, and the seasonality of surface CHL was far more complex (three more feature areas) in deeper water than the seasonality of NPP.…”

“…Except for the region LS, the spatial distribution of NPP seasonality differs from both the surface CHL (Yu et al, 2019) and surface carbon-to-CHL ratio (Xu et al, 2020) at least in waters deeper than 200 m in the SCS. This study suggests that there are two main reasons for this discordance: on the one hand, unlike NPP, surface CHL and surface carbon-to-CHL ratio do not contain vertical information, while there are still some errors in these two parameters obtained by satellite remote sensing.…”

“…The linkage algorithm was based on initial calculation of the cosine distance between the objects, which has the advantage of emphasizing mainly differences in the seasonal shape. Specifically, similar to Xu et al (2020), a monthly climatological time series of the NPP was first created for each pixel of the SCS. The resulting climatological time series were normalized to a maximum value for each specific pixel.…”