Unraveling environmental drivers of chlorophyll seasonal and interannual variability in the East China Sea

Phytoplankton, the dominant marine primary producers, are considered highly sensitive indicators of ecosystem conditions and changes. The East China Sea (ECS) includes a variety of oceanic and coastal domains that collectively challenge our understanding of phytoplankton dynamics and controls. This study evaluates the seasonal and interannual variability of phytoplankton in the ECS and the underlying environmental determinants based on 22-year satellite chlorophyll (Chl-a) data and concurrent environmental variables. A seasonal spring bloom was found in the ECS, classically driven by increased stratification, which is associated with increases in sea surface temperature (SST), photosynthetically available radiation (PAR), net heat flux (NHF), and reduced wind mixing. The most significant Chl-a interannual variability was present in a triangular area surrounded by three SST fronts in the southern ECS during springtime. Anomalously high Chl-a (similar to 30% increase) occurred with increased SST and NHF and enhanced wind mixing during negative Pacific Decadal Oscillation (PDO) and El Nino-Southern Oscillation (ENSO) modes. This seems to be contrary to the stratification control model, which fits the seasonal spring bloom observed in this region. More front activities during the negative PDO and ENSO could be associated with Chl-a increase in this triangular area. Contrary to this mixing control scenario, a significant Chl-a increase (similar to 36% increase) also developed during the positive PDO and ENSO modes after 2014 under conditions of higher SST, NHF, and weaker wind mixing following the stratification control scenario. This study used biologically relevant objective regionalization of a heterogeneous area to elucidate phytoplankton bloom dynamics and controls. Our analyses highlight the triangular area in the ECS for its region-specific linkages between Chl-a and multiple climate-sensitive environmental drivers, as well as the potential structural and functional variability in this region.