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Marginal seas influenced by large rivers are characterized by complex hydrodynamic and organic matter cycling processes. However, the impacts of hydrodynamics on the composition and reactivity of particulate organic matter (POM) remain unclear. Here we conducted a comprehensive study on the bulk, molecular and biological properties of suspended POM in the Changjiang Estuary and adjacent area subjected to strong currents, eddies as well as typhoons during spring and autumn. D/L‐enantiomers of particulate amino acids (PAA) were analyzed to evaluate the bioreactivity of POM and quantify bacterial‐derived organic carbon. We found that POM bioavailability as indicated by carbon‐normalized yields of PAA (PAA‐C%) reflected the ecosystem productivity. Relatively high PAA‐C% values (20−35%) were observed in productive areas influenced by Changjiang River plume, cyclonic eddies and typhoons, likely related to the enhanced nutrient availability arising from hydrodynamic processes. In contrast, the oligotrophic Taiwan Warm Current‐influenced regions featured relatively low POM bioavailability (PAA‐C% < 10%) despite typhoons facilitating water mixing. The PAA‐C% values showed a significant positive correlation with extracellular enzyme activity, indicating that bioavailable POM can rapidly stimulate heterotrophic transformation. Hot spots of elevated bioavailable POM showed high contributions of bacterial organic carbon. A large portion (∼2/3) of bacterial organic carbon was present in the form of bacterial detritus, suggesting that patches of these biological hot spots represent important sites of carbon sequestration. Together, our findings indicate that fresh POM production is largely controlled by nutrient supply driven by hydrodynamic processes, with important implications for carbon sequestration in the dynamic ocean margins. Plain Language Summary Marginal seas are subject to complex hydrodynamic processes and play an important role in carbon sequestration. Disentangling

The TetraEther indeX of 86 carbon atoms (TEX86) is widely used as a proxy to reconstruct past sea surface temperatures. Most current applications of TEX86 are primarily based on analyzing the composition of isoprenoid glycerol dialkyl glycerol tetraethers (isoGDGTs) that comprise TEX86 in sediments, with the assumption that the sedimentary isoGDGTs are mainly derived from the surface mixed layer. Here we report on the variations in the isoGDGT distribution, archaeal abundance and community through the water column of the Western Pacific Ocean, directly testing the export depth of isoGDGTs and constraining the temperature records of TEX86. Our data show that maximum isoGDGT concentrations occurred in subsurface waters (150–200 m) with maximum archaeal abundances. The ratio between isoGDGTs bearing 2 vs. 3 cyclopentane moieties, i.e. [2/3] ratio, increased with depth, which is likely related to the shift of the archaeal community from Ca. Nitrosopelagicus-dominance to norank_f__Nitrosopumilaceae-dominance. Models based on the [2/3] ratios in the water column predicted an average export depth of isoGDGTs to sediments of around 150–200 m, consistent with the robust relationship between the compiled sedimentary TEX86 and the annual mean subsurface temperature. Taken together, our findings support that TEX86 records subsurface rather than surface temperatures in the open ocean.

Concentrations of particulate organic carbon (POC) and total hydrolyzable amino sugars (THAS) were measured along a transect of the dynamic South Yellow Sea (SYS) to investigate the bioreactivity and bacterial reworking of particulate organic matter (POM). Results showed that POM bioavailability was linked with primary production, as revealed by the significant correlation between chlorophyll-a concentrations and the diagenetic indicator glucosamine/galactosamine (GlcN/GalN). Production of bioavailable POM could rapidly stimulate microbial activity, generating hot spots of heterotrophic alteration. Lower GlcN/GalN ratios (<3) observed in the entire SYS indicate that POM underwent extensive microbial alteration. In particular, extremely low GlcN/GalN ratios (∼0.7) were found in the Yellow Sea Cold Water Mass, reflecting high bacterial alteration of POM. Estimates based on the bacterial biomarker muramic acid showed that on average ∼13% of POM in the SYS was of bacterial origin. Elevated bacterial contributions were found in both nearshore and offshore areas. Strong mixing in the nearshore and the presence of cyclonic eddies in offshore waters may increase the residence time of POM in the water column and thus promote bacterial transformation of POM. Overall, our findings indicate that bacterial reworking of POM varies with productivity and that the extensive bacterial transformation of the remaining POM observed in the water column probably enhances long-term carbon sequestration.

Various machine learning methods were attempted in the global mapping of surface ocean partial pressure of CO2 (pCO(2)) to reduce the uncertainty of the global ocean CO2 sink estimate due to undersampling of pCO(2). In previous research, the predictors of pCO(2) were usually selected empirically based on theoretic drivers of surface ocean pCO(2), and the same combination of predictors was applied in all areas except where there was a lack of coverage. However, the differences between the drivers of surface ocean pCO(2) in different regions were not considered. In this work, we combined the stepwise regression algorithm and a feed-forward neural network (FFNN) to select predictors of pCO(2) based on the mean absolute error in each of the 11 biogeochemical provinces defined by the self-organizing map (SOM) method. Based on the predictors selected, a monthly global 1 circle x 1 circle surface ocean pCO(2) product from January 1992 to August 2019 was constructed. Validation of different combinations of predictors based on the Surface Ocean CO2 Atlas (SOCAT) dataset version 2020 and independent observations from time series stations was carried out. The prediction of pCO(2) based on region-specific predictors selected by the stepwise FFNN algorithm was more precise than that based on predictors from previous research. Applying the FFNN size-improving algorithm in each province decreased the mean absolute error (MAE) of the global estimate to 11.32 mu atm and the root mean square error (RMSE) to 17.99 mu atm. The script file of the stepwise FFNN algorithm and pCO(2) product are distributed through the Institute of Oceanology of the Chinese Academy of Sciences Marine Science Data Center (IOCAS, , Zhong, 2021.