Scientific publications

Here we report on our studies of chlorophyll-a in the South China Sea (SCS) and its structural features based solely on merged satellite ocean color data (Ocean Color Climate Change Initiative – OC-СCI). The SCS is largely oligotrophic, and its primary production predominantly comes from picophytoplankton. Short-term changes in the SCS p icophytoplankton community structure driven by typhoon Wind Pump (WP) are studied against the background of long-term (1998–2016) space-borne OC-СCI observation data. Two ocean color data processing algorithms were applied permitting to reveal (a) the SCS total phytoplankton size structure (in terms of its contribution to chlorophyll-a (chl-a) concentration), and (b) the picophytoplankton community structure. The first algorithm is for partitioning the total chl-a in water into micro-, nano-, and picophytoplankton. The second algorithm quantifies the cell abundances of two species of prokaryotic algae – Prochlorococcus (Pro) and Synechococcous (Syn), and the entire community of eukaryotic picophytoplankton (Peuk) in the SCS. In general, a longterm trend toward an increase in chl-a of all phytoplankton size classes was observed, although the relative share of micro- and nanophytoplankton in the total amount of chl-a was minor, while the share of picophytoplankton was somewhat more pronounced. Within the picophytoplankton size class, the numbers of Syn and Peuk cells also showed a slight upward trend, whereas Pro showed a definite decrease in their numbers. The short-term dynamics caused by the passing typhoons was marked by a strong growth of chl-a along the cyclone’s footprint path, with the potential to eventually promote massive phytoplankton blooms. Within the picophytoplankton size fraction, Syn and Peuk cell numbers showed some increase, while Pro cells, which proved to be resistant to poor nutrient conditions, decreased when the typhoon wind pump effect provided nutrients. The typhoon WP temporal effect on phytoplankton community structure was shown to last not more than 1 month, but usually 2-3 weeks. Our results indicate that the above two data processing algorithms are instrumental in establishing the phytoplankton community structure status and its dynamics in the SCS