Development of a regional empirical algorithm for estimating biopolymeric carbon from satellite ocean color in the...

The eastern Yellow Sea (EYS) is a semi-enclosed marginal sea characterized by high turbidity from strong tidal mixing and riverine inputs, creating an optically complex environment that challenges satellite remote sensing applications. Biopolymeric carbon (BPC), comprising the labile and metabolically active fraction of particulate organic carbon (POC) derived from phytoplankton biochemical components (proteins, carbohydrates, and lipids), serves as a critical indicator of food quality and energy transfer efficiency in marine ecosystems. This study developed a regional empirical algorithm for estimating BPC concentrations from satellite ocean color measurements in the EYS. Using 354 in situ measurements collected from 2017 to 2024, a multiple linear regression (MLR) model was developed with POC and chlorophyll-a (Chl-a) as predictors, achieving moderate yet meaningful validation performance, given the non-optical and composite nature of the target variable. Analysis of a decade of satellite ocean color data (2015-2024) revealed distinct spatial patterns, with higher BPC concentrations in nearshore waters than in offshore regions. These patterns were driven by distinct mechanisms: riverine discharge influencing nearshore dynamics, and seasonal stratification controlling offshore variability. Time-series analysis demonstrated climate-driven phenological shifts in BPC dynamics, consistent with global warming trends. This regional algorithm provides valuable information for monitoring BPC distributions in the EYS, enabling assessment of autochthonous carbon sources and trophic food availability within marine ecosystems under ongoing environmental changes.