Bacterial production of humic-like fluorescent dissolved organic matter (FDOM H ) was examined in a 90 d culture experiment using a bacterial assemblage collected from coastal water with artificial seawater amended by glucose. A rapid decrease in dissolved organic carbon concentration was noticed during Days 1 to 5, and this coincided with an increase in bacterial numbers. The increase in FDOM H , which was determined by Excitation-Emission Matrix Spectroscopy (EEMS), was observed by Day 20, showing the production of FDOM H by bacteria. This increase lagged behind the increase in bacterial numbers, suggesting that the production of

An experimental study was conducted to assess the difference in humic-like fluorescence characteristics (excitation/emission = 290 to 360 /370 to 460 nm) of dissolved organic matter produced by bacteria isolated from coastal seawater. Ten bacterial strains were isolated, and 1 additional strain was obtained from the Japan Collection of Microorganisms. The strains' nearest phylogenetic neighbors were identified using 16S rRNA gene analysis. Eleven bacterial strains were inoculated in experimental liquid medium and incubated for 7 d. In this incubation experiment, the excitation-emission matrixes of the culture media were analyzed to elucidate the production of humic-like fluorescent dissolved organic matter (FDOM) between Day 0 and Day 7 of the incubation. The production of humic-like FDOM was found in 8 of the 11 culture media, with a total of 14 humic-like fluorescence peaks detected. Of these peaks, 10 exhibited different fluorescence characteristics. These findings indicate that the fluorescence characteristics of bacterialderived humic-like FDOM differed among the bacterial groups. Several cultures of bacterial strains contained FDOM, with peaks occurring in the spectral region often associated with humiclike material of terrestrial origin. One bacterial strain showed productivity of humic-like FDOM that was 1 order of magnitude higher than most of the bacterial strains. This result implies that the relative importance of humic-like FDOM production is different among bacterial genera in the ocean. KEY WORDS: Fluorescent dissolved organic matter · Bacteria · Excitation-emission matrix · SpectroscopyResale or republication not permitted without written consent of the publisher

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Direct measurements of gross primary productivity (GPP) in the water column are essential, but can be spatially and temporally restrictive. Fast repetition rate fluorometry (FRRf) is a bio-optical technique based on chlorophyll a (Chl-a) fluorescence that can estimate the electron transport rate (ETRPSII) at photosystem II (PSII) of phytoplankton in real time. However, the derivation of phytoplankton GPP in carbon units from ETRPSII remains challenging because the electron requirement for carbon fixation (Фe,C), which is mechanistically 4 mol e− mol C−1 or above, can vary depending on multiple factors. In addition, FRRf studies are limited in freshwater lakes where phosphorus limitation and cyanobacterial blooms are common. The goal of the present study is to construct a robust Фe,C model for freshwater ecosystems using simultaneous measurements of ETRPSII by FRRf with multi-excitation wavelengths coupled with a traditional carbon fixation rate by the 13C method. The study was conducted in oligotrophic and mesotrophic parts of Lake Biwa from July 2018 to May 2019. The combination of excitation light at 444, 512 and 633 nm correctly estimated ETRPSII of cyanobacteria. The apparent range of Фe,C in the phytoplankton community was 1.1–31.0 mol e− mol C−1 during the study period. A generalised linear model showed that the best fit including 12 physicochemical and biological factors explained 67% of the variance in Фe,C. Among all factors, water temperature was the most significant, while photosynthetically active radiation intensity was not. This study quantifies the in situ FRRf method in a freshwater ecosystem, discusses core issues in the methodology to calculate Фe,C, and assesses the applicability of the method for lake GPP prediction.

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