The separation and identification of phytoplankton pigments from the adjacent waters of Great Wall Station，Antarctica

This paper presents separation and identification of the pigments of the phytoplankton samples collected from the adjacent waters (62°12. 5'S, 58°53' W～62°14. 5' S, 58°57' W) of Great Wall Station, Antarctica during March 1988～February 1989 by using thin-layer chromatographic techniques. Of the 15 kinds of phytoplankton pigments separated, 13 were identified according to the R. values of the various marine algal pigments. The features of seasonal variations of phytoplankton pigments in the studied area are also discussed.

Phytoplankton pigment pattern in the subsurface chlorophyll maximum in the South Java coastal upwelling system, Indonesia

Upwelling occurs on the coast of Java between June and October, forced by local alongshore winds associated with the southeasterly monsoon. This causes variations in phytoplankton community composition in the upwelling zone compared with the surrounding offshore area. Based on pigments analysis with subsequent calculations of group contributions to total chlorophyll a(Chl a) using CHEMTAX, we studied the distribution and composition of phytoplankton assemblages in the subsurface chlorophyll maximum along the south coast of Java and the influence of upwelling. Nineteen phytoplankton pigments were identified using high-performance liquid chromatography, and CHEMTAX analysis associated these to ten major phytoplankton groups. The phytoplankton community in the coastal area influenced by upwelling was characterized by high Chl a and fucoxanthin concentrations, indicating the dominance of diatoms. In contrast, in the offshore area, the Chl a and fucoxanthin concentrations declined to very low levels and the community was dominated by haptophytes represented by 19′-Hexanoyloxyfucoxanthin. Accordingly, microphytoplankton was found to be the major size class in the coastal area influenced by upwelling, while nanophytoplankton was most abundant in the offshore area. Low concentrations of other accessory pigments indicated less contribution from dinoflagellates,prasinophytes, chlorophytes and cryptophytes. Photo-pigment indices revealed that photosynthetic carotenoids(PSCs) were the largest component of the pigment pool, exceeding the proportion of Chl a, with the average PSCTP up to 0.62. These distribution trends can mainly be explained by phytoplankton adaption strategies to upwelling and subsurface conditions by changing species composition and adjusting the pigment pool.

Assessing the uncertainties of phytoplankton absorption-based model estimates of marine net primary productivity

Satellite-derived phytoplankton pigment absorption （aph） has been used as a key predictor of phytoplankton photosynthetic efficiency to estimate global ocean net primary production （NPP）. In this study, an aph-based NPP model （AbPM） with four input parameters including the photosynthetically available radiation （PAR）, diffuse attenuation at 490 nm （Ka（490））, euphotic zone depth （Zeu） and the phytoplankton pigment absorption coefficient （aph） is compared with the chlorophyll-based model and carbon-based model. It is found that the AbPM has significant advantages on the ocean NPP estimation compared with the chlorophyll-based model and carbon- based model. For example, AbPM greatly outperformed the other two models at most monitoring sites and had the best accuracy, including the smallest values of RMSD and bias for the NPP estimate, and the best correlation between the observations and the modeled NPPs. In order to ensure the robustness of the model, the uncertainty in NPP estimates of the AbPM was assessed using a Monte Carlo simulation. At first, the frequency histograms of simple difference （fi）, and logarithmic difference （~LOG） between model estimates and in situ data confirm that the two input parameters （Zeu and PAR） approximate the Normal Distribution, and another two input parameters （aph and Ka（490）） approximate the logarithmic Normal Distribution. Second, the uncertainty in NPP estimates in the AbPM was assessed by using the Monte Carlo simulation. Here both the PB （percentage bias）, defined as the ratio of ANPP to the retrieved NPP, and the CV （coefficient of variation）, defined as the ratio of the standard deviation to the mean are used to indicate the uncertainty in the NPP brought by input parameter to AbPM model. The uncertainty related to magnitude is denoted by PB and the uncertainty related to scatter range is denoted by CV. Our investigations demonstrate that PB of NPP uncertainty brought by all parameters with an annual mean of 5.5% covered a range of -5%-15% for the global ocean. The PB uncertainty of AbPM model was mainly caused by aph; the PB of NPP uncertainty brought by aph had an annual mean of 4.1% for the global ocean. The CV brought by all the parameters with an annual mean of 105% covered a range of 98%-134% for global ocean. For the coastal zone of Antarctica with higher productivity, the PB and CV of NPP uncertainty brought by all parameters had annual means of 7.1% and 121%, respectively, which are significantly larger than those obtained in the global ocean. This study suggests that the NPPs estimated by AbPM model are more accurate than others, but the magnitude and scatter range of NPP errors brought by input parameter to AbPM model could not be neglected, especially in the coastal area with high productivity. So the improving accuracy of satellite retrieval of input parameters should be necessary. The investigation also confirmed that the SST related correction is effective for improving the model accuracy in low temperature condition.

Phytoplankton community dynamics during Alexandrium blooms in 2019 off the Qinhuangdao coast,Bohai Sea,China

Alexandrium blooms in the northwest area of the Bohai Sea(Qinhuangdao coastal area),China,produce large amounts of toxins that could be enriched in shellfish and consequently harm human bodies.To understand the succession of the phytoplankton community structure during Alexandrium bloom events in the northwest area of the Bohai Sea off Qinhuangdao from April 2 to May 7,2019,microscopy observations and high-performance chromatography(HPLC)-pigment analysis were performed.Sixty species of phytoplankton were identified,mainly diatoms and dinofl agellates.The abundance of Alexandrium reached the maximum on April 16(3.3×10^(3) cells/L).HPLC-pigment CHEMTAX analysis showed that the phytoplankton community was composed mainly of diatoms,dinofl agellates,prasinophytes,and cryptophytes.Diatoms were the main contributor to the total Chl-a pool.There was a downward trend for the proportion of diatom biomass to the total Chl-a pool,followed by an upward trend.The proportion of dinoflagellate biomass showed the opposite trend,whereas that of the prasinophyte biomass presented an obvious increasing trend.Temperature,nutrients,and nutrient structures were the main factors on the distribution of different phytoplankton groups in the study area as shown in the redundancy analysis.This work illustrates the succession of phytoplankton community structures during Alexandrium blooms and provided a theoretical basis for studies on the mechanism underlying the outbreak of harmful algal blooms in sea areas.