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The release of dissolved organic matter (DOM) from sediments serves as an important part of the carbon cycle. Here, we address pore water DOM quality and its release from shallow sediments (0-10 cm) of the central and southern Baltic Sea - Gdansk, Bornholm, and Eastern Gotland Basins - using excitation-emission matrix spectroscopy and size-exclusion chromatography. DOM release from sediments displayed spatial variability, with diffusive DOC fluxes ranging from 0.02 to 1.06 mmol m-2 d-1, and basin-averaged fluxes increased in the order Gotland < Bornholm < Gdansk. DOM qualitative characteristics also varied among investigated basins. In the oxygen-limited study sites from the Gdansk Basin, we observed elevated abundances of low apparent molecular weight DOM fraction and proteinaceous-like fluorescent DOM, while in the Bornholm Basin, pore water DOM was generally more humic-like and of higher apparent molecular weight. Pore waters from the deepest study sites in the Gotland Basin were qualitatively very similar to those of the pore waters from the upper sediment layers (0-4 cm) from all other investigated sites, suggesting little organic matter reworking at depth at those stations. Our results suggest that the spatial variability in the magnitude of DOM release may be linked to the qualitative differences of DOM in sediments. [ABSTRACT FROM AUTHOR]

This study aimed to detect non-conservative processes that affect the distribution of fluorescent dissolved organic matter (FDOM) in the Baltic Sea. An extensive data set comprised of 408 FDOM data, optical and physical profiles, and the development of a water masses balance model allowed us to ascertain the sources of mixing anomalies. These were seen as second-order deviations in the FDOM distribution as a function of salinity in three layers: surface water, Baltic Sea Winter Water, and deep water. The difference between modeled and measured FDOM values at three different excitation/emission wavelengths allowed to show the strength of non-conservative processes, such as photochemical and microbial decomposition (negative residual values) or extracellular release of dissolved organic matter from phytoplankton, heterotrophic uptake and release from anoxic sediments (positive residual values). Humic-like FDOMfractions displayed positive residuals in all seasons for intermediate and deep layers and negative residuals in surface waters. Largest accumulation rates of humic-like fractions were reached in the Gulf of Gdańsk during summer in intermediate and deep layers, while the greatest removal in surface waters was observed during spring in the Bornholm and Gotland Basins and during summer in the Gulf of Gdańsk, probably due to photodegradation. Positive residuals of the protein-like fraction were observed at the surface in summer and autumn in the Gulf of Gdańsk, probably linked to the abundance of phytoplankton and also due to the low molecular weight by-products of photodegradation of humic-like components. Spatial transects revealed an increase in humic-like residuals with depth and a strong correlation with apparent oxygen utilization, increasing with higher fluorescence and exhibiting an asymptotic trend. A relationship was found between the protein-like fractions and phytoplankton biomass proxies. A generalized concept for FDOM cycling in the Baltic Sea was proposed, highlighting photobleaching as the dominant non-linear process determining the efficiency of humic-like FDOM removal. The protein-like component was found to be more efficiently taken up by aerobic prokaryotes at the surface. Microbial utilization and reworking of organic matter, release from sediments, and a decade-long stagnation of bottom water masses, all contribute to the observed accumulation of FDOM in mesohaline deep waters below the permanent pycnocline in the Baltic Sea. [ABSTRACT FROM AUTHOR]

Phytoplankton are responsible for releasing half of the World's oxygen and for removing large amounts of carbon dioxide from the surface waters. Despite many studies on the topic conducted in the past decades, we are still far from a good understanding of ongoing rapid changes in the Arctic Ocean, and how they will affect phytoplankton and the whole ecosystem. An example is the difference in net primary production modeling estimates, which differ two times globally and fifty times when only the Arctic region is considered. Here we aim to improve the quality of Greenland Sea primary production estimates, by testing different versions of primary production model against in-situ data, and then calculating regional estimates and trends for 1998–2022 for those performing best. As a baseline we chose the commonly used global primary production model and tested it with different combinations of empirical relationships and input data. Local empirical relationships were taken from literature and derived from the unpublished Institute of Oceanology of Polish Academy of Sciences measurements across the Fram Strait. For validation we took historical net primary production 14C data from literature, and added to it our own gross primary production O2 measurements to extend the limited validation dataset. The field data showed expected elevated values at the frontal zone together with differences between Arctic and Atlantic-dominated waters, and unexpected good agreement between primary production measured with 14C and O2 evolution methods. From all the model setups, those including local chlorophyll-a profile and local absorption spectrum and using Level 2 photosynthetically active radiation data, reproduced in-situ data best. Our modeled regional annual primary production estimates equal 346 TgC/year for the Nordic Seas region and 342 TgC/year for the Greenland Sea sector of the Arctic defined as 45° W–15° E, 66°33′N–90° N. These values are higher those previously reported. Monthly values show a seasonal cycle with less monthly variability than previously reported, and with peak values observed in May. No significant increase or decrease in primary production was observed when studying regionally averaged trends. The accuracy of the selected here model setups to reproduce the field data in terms of Root Mean Square Difference is poorer than in the related global studies, but better than in the related Arctic studies. [ABSTRACT FROM AUTHOR]