•The 6 parameters (four CDOM fluorescence components, Chl-a and DO), which could be measured in situ and quickly, were selected to predict the eutrophication status.•A hybrid GS optimized SVM was proposed for developing eutrophication status evaluation model.•The developed SVM-based approach was successful applied to evaluate the eutrophication status of coastal waters in the Yellow Sea and the East China Sea.The development of techniques for real-time monitoring of the eutrophication status of coastal waters is of great importance for realizing potential cost savings in coastal monitoring programs and providing timely advice for marine health management. In this study, a GS optimized SVM was proposed to model relationships between 6 easily measured parameters (DO, Chl-a, C1, C2, C3 and C4) and the TRIX index for rapidly assessing marine eutrophication states of coastal waters. The good predictive performance of the developed method was indicated by the R2 between the measured and predicted values (0.92 for the training dataset and 0.91 for the validation dataset) at a 95% confidence level. The classification accuracy of the eutrophication status was 86.5% for the training dataset and 85.6% for the validation dataset. The results indicated that it is feasible to develop an SVM technique for timely evaluation of the eutrophication status by easily measured parameters.

Marine organisms have usually been viewed as sources of environmentally friendly compounds with antifouling activity. We performed a series of operations to investigate the antifouling potential of the marine microalga Dunaliella salina. For the ethyl acetate crude extract, the antialgal activity was significant, and the EC50 value against Skeletonema costatum was 58.9 μg ml−1. The isolated purified extract was tested for antifouling activity, the EC50 value against S. costatum was 21.2 μg ml−1, and the LC50 against Balanus amphitrite larvae was 18.8 μg ml−1. Subsequently, both UHR–TOF–MS and GC–MS were used for the structural elucidation of the compounds, and a series of unsaturated and saturated 16- and 18-carbon fatty acids were detected. The data suggested that the fatty acid extracts from D. salina possess high antifouling activity, and could be used as substitutes for potent, toxic antifouling compounds.

The 3D fluorescence discrimination of phytoplankton classes was investigated by SA4 multiwavelet, GHM multiwavelet, and coifman-2(coif2) wavelet analysis. Belonging to 35 genera of 7 major phytoplankton divisions in the inshore area of China Sea, Single species cultures of 51 phytoplankton species were employed. The second scale vector (Ca2) of SA4, Ca2 of GHM and the third scale vector (Ca3) of coif2 were selected as feature spectra by Bayesian discriminate analysis (BDA). The reference spectra were obtained via hierarchical cluster analysis (HCA). With average high correct discrimination ratios (CDRs), reference spectra were representative to phytoplankton species. For one-algae samples, the average CDRs were 95.6% at genus level and 86.7% at division level. For the laboratory mixed samples, the average CDRs (one division accounted for 25%, 75% or 100% of the total biomass) were 86.6%, 91.4% and 100% at division level. Moreover, the average CDRs of the dominant species (accounted for 75%) was 79.8% at genus level. Results for the in situ samples were coincided with the microscopic ones at division level with the relative contents of 54.3%–96.5%. The fluorometric discriminating technique was further tested during the cruise in Bohai Sea recently.

Samples of chromophoric dissolved organic matter (CDOM) in the East China Sea in autumn (October in 2011) were analyzed by excitation emission matrix (EEM) fluorescence spectroscopy combined with parallel factor analysis (PARAFAC). Three terrestrial humic-like components (C1, C2 and C3) and one protein-like component (C4) were identified. Based on spatial distributions, as well as relationships with salinity, the following assignments were made. The three humic-like components (C1, C2 and C3) showed conservative mixing behavior and came mainly from riverine input. The protein-like component (C4) was considered a combination of autochthonous production and terrestrial inputs and a biologically labile component. Path analysis of samples from the middle and bottom layers revealed that the causal effects on C1 were −78.46% for salinity, and −21.54% for apparent oxygen utilization (AOU); those on C2 were −76.43% for salinity, and −23.57% for AOU; those on C3 were −70.49% for salinity, 7.01% for Chl-a, and −22.50% for AOU; those on C4 were −55.54% for salinity, 14.6% for Chl-a, and −29.86% for AOU in middle layer; and those on C4 were −57.37% for salinity, 29.02% for Chl-a, and −13.61% for AOU in bottom layer. Results indicated that CDOM in the East China Sea was mainly affected by terrestrial inputs, and microbial activities also played a key role in biogeochemical processes of CDOM. The application of the EEM-PARAFAC model presented a unique opportunity to observe compositional changes in CDOM in the East China Sea. In addition, the humification index (HIX) suggested that CDOM from the East China Sea was less stable and stayed shorter in the environment.

In this study we have successfully characterized the fluorescent components of chromophoric dissolved organic matter (CDOM) in the Yellow Sea and the East China Sea in autumn using excitation-emission matrix fluorescence spectroscopy (EEMs) combined with parallel factor analysis (PARAFAC). PARAFAC aids the characterization of fluorescence CDOM by decomposing the fluorescence matrices into individual components. Four humic-like components (C1, C2, C3, and C4), one marine biological production component (C6), and two protein-like components (C5 and C7) were identified by PARAFAC. We researched the distributional patterns of fluorescence intensity, regression analyses between salinity, chlorophyll a concentration and fluorescence intensities of individual fluorophore, and regression analysis between salinity and fluorescence intensities percent of individual fluorophore. The results revealed that C2 and C4 showed conservative mixing behavior, while C1 and C3 possessed conservative mixing behavior in high salinity region and additional behavior in low and middle salinity region, which were considered to be derived from riverine and degradation of organic matter from resuspended and/or sinking particles and show non-conservative mixing behavior. In addition to riverine sources, the tryptophan-like C5 may receive widespread addition (likely from photo-degradation or biodegradation), while the most likely sources for the one marine humic-like C6 and tyrosine-like C7 were biological activity and microbial processing of plankton-derived CDOM, which were suggested to be of autochthonous origin and biologically labile. The application of EEM-PARAFAC modeling presents a unique opportunity to observe compositional changes, different mixing behavior and temporal variability in CDOM in the Yellow Sea and the East China Sea.

•Three humic-like components and one protein-like component were identified.•CDOM increased by about 16–39%, 26–61% in summer than that in spring and autumn.•CDOM increased by about 9–19% in spring compared to the autumn.•The key issues influencing CDOM were terrestrial input, hydrodynamics and bioactivities.Samples of chromophoric dissolved organic matter (CDOM) from the Southern Yellow Sea (SYS) and the East China Sea (ECS) were evaluated by fluorescent Excitation Emission Matrix (EEM) combined with Parallel Factorial Analysis (PARAFAC). Three terrestrial humic-like components (C1, C2 and C3) and one autochthonous protein-like component (C4) were identified. As for seasonal variations, CDOM displayed the following order on the whole: summer > spring > autumn. The C1, C2 and C3 components were mainly dominated by terrestrial inputs and their spatial distributions and temporal variations also can be influenced by primary productivity of phytoplankton, microbial activities and photobleaching. C4 was produced by phytoplankton and microorganisms and consumed by marine bacteria, and besides its distribution was attributed to the influence of riverine inputs. Terrestrial inputs were the dominant sources of CDOM in the SYS and ECS.