Abstract. Phytoplankton light absorption properties were investigated at the surface and subsurface chlorophyll a maximum (SCM) layer in the East China Sea (ECS), a marginal sea which is strongly influenced by the Changjiang discharge in summer. Results from ECS were compared with those from the Tsushima Strait (TS) where the influence of Changjiang discharge is less. The probable controlling factors, packaging effect (cell size) and pigment composition of total chlorophyll a (Tchl a)-specific absorption coefficient (a * ph (λ)) were examined by the corresponding measurements of pigments identified by high-performance liquid chromatography. We observed distinct phytoplankton size structure and thereby absorption properties between ECS and TS. At the surface, mixed populations of micro-, nanoand pico-phytoplankton were recorded in ECS while picophytoplankton dominated in TS, generating a lower average a * ph (λ) in ECS than in TS. Within SCM, average a * ph (λ) was higher in ECS than in TS because of the dominance of nano-and micro-phytoplankton in ECS and TS, respectively. By pooling surface and SCM samples, we found regular trends in phytoplankton size-fraction versus Tchl a; and correlations between a * ph (λ) and Tchl a consistent with previous observations for the global ocean in TS but not in ECS. In ECS phytoplankton size-fraction was not correlated with Tchl a, which consequently caused poor relationships between a * ph (λ) and Tchl a. The abnormal values mainly originated from the surface low-salinity waters and SCM waters beneath them. At high Tchl a, a * ph (λ) of these samples was substantially higher compared to the values in TS and from the global regressions, which was attributable to the lower micro-phytoplankton fraction, and higher nano-and/or pico-phytoplankton fractions in ECS. These observations indicated that the distinct light absorption properties of phytoplankton in ECS were possibly influenced by the Changjiang discharge. Our findings imply that general bio-optical algorithms proposed based on the correlations between a * ph (λ) and Tchl a or the patterns in size-fraction versus Tchl a are not applicable in ECS, and need to be carefully considered when using these general algorithms in river-influenced regions.

A new efficient synthesis of 2-substituted tetrahydroquinolines has been achieved by the domino reaction of N-indanyl(methoxy)amines, which consists of three types of reactions: elimination of an alcohol, the rearrangement of an aryl group, and the addition of an organolithium or magnesium reagent. The synthetic utility of this approach is demonstrated by the stereoselective formal synthesis of (+/-)- martinellic acid.

Phytoplankton size structure plays an important role in ocean biogeochemical processes. The light absorption spectra of phytoplankton provide a great potential for retrieving phytoplankton size structure because of the strong dependence on the packaging effect caused by phytoplankton cell size and on different pigment compositions related to phytoplankton taxonomy. In this study, we investigated the variability in light absorption spectra of phytoplankton in relation to the size structure. Based on this, a new approach was proposed for estimating phytoplankton size fractions. Our approach use the spectral shape of the normalized phytoplankton absorption coefficient (a(ph)(λ)) through principal component analysis (PCA). Values of a(ph)(λ) were normalized to remove biomass effects, and PCA was conducted to separate the spectral variance of normalized a(ph)(λ) into uncorrelated principal components (PCs). Spectral variations captured by the first four PC modes were used to build relationships with phytoplankton size fractions. The results showed that PCA had powerful ability to capture spectral variations in normalized a(ph)(λ), which were significantly related to phytoplankton size fractions. For both hyperspectral a(ph)(λ) and multiband a(ph)(λ), our approach is applicable. We evaluated our approach using wide in situ data collected from coastal waters and the global ocean, and the results demonstrated a good and robust performance in estimating phytoplankton size fractions in various regions. The model performance was further evaluated by a(ph)(λ) derived from in situ remote sensing reflectance (R(rs)(λ)) with a quasi-analytical algorithm. Using R(rs)(λ) only at six bands, accurate estimations of phytoplankton size fractions were obtained, with R(2) values of 0.85, 0.61, and 0.76, and root mean-square errors of 0.130, 0.126, and 0.112 for micro-, nano-, and picophytoplankton, respectively. Our approach provides practical basis for remote estimation of phytoplankton size structure using a(ph)(λ) derived from satellite observations or rapid field instrument measurements in the future.

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