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Light is essential for primary production and, therefore, its attenuation controls the vertical distribution of plants and phytoplankton over the water column. The diffuse attenuation of irradiance (K) is mainly governed by the attenuation by the water itself and the concentrations of optically active substances (e.g., phytoplankton, inorganic particles and colored dissolved molecules), which makes it an important parameter for eutrophication monitoring. Over the past century, Denmark has had recurrent eutrophication events, with extreme episodic cases where anoxic conditions were observed. Since the 1980’s, eutrophication in Danish waters has been monitored with regards to the diffuse attenuation coefficient of scalar irradiance (Ko) of photosynthetically active radiation (PAR, 400–700 nm), Ko(PAR). However, radiometric measurements in Denmark are difficult in winter due to low solar zenith angle and only few light hours. On top of that, radiometric measurements in the first meters of the water column are highly affected by light refraction influenced by waves, compromising the monitoring of shallow turbid waters as in Denmark. Therefore, we developed a semi-analytical model based on data to from a spectral AC instrument (AC-S, Sea-Bird Scientific) that can estimate the underwater light field and the diffuse attenuation coefficient of downwelling irradiance, Kd(PAR). We tested two distinct approaches based on equations from the literature for estimation of Kd(PAR). The results show that modeled PAR profiles follow the overall shape of in situ radiometric profiles but with smoother profiles, especially in the surface layer (2–5 m). Along with that, the method provided robust Kd(PAR) estimates, that were strongly correlated to the reference Ko(PAR) values from in situ profiles and with low root mean square error (RMSE). Thus, AC-S data can be used to estimate the underwater light field and Ko(PAR). This will make possible to retrieve Ko(PAR) in the absence of daylight and, therefore, allow for environmental monitoring outside the daylight hours, making environmental monitoring more efficient. In addition, the method provides valuable insights into the factors controlling light attenuation.

The land-to-ocean flux of organic carbon is increasing in glacierized regions in response to increasing temperatures in the Arctic (Hood et al., 2015). In order to understand the response of the coastal ecosystem metabolism to the organic carbon input it is essential to determine the bioavailability of the different carbon sources in the system. We quantified the bacterial turnover of organic carbon in a high Arctic fjord system (Young Sound, NE Greenland) during the ice-free period (July-October 2014) and assessed the quality and quantity of the 3 major organic carbon sources; (1) local phytoplankton production (2) runoff from land-terminating glaciers and a lowland river and (3) inflow from the ocean shelf. We found that despite relatively low concentrations of DOC in the rivers, the bioavailability of the river–DOC was significantly higher than in the fjord, and characterized by high cell-specific bacterial production and low C:N ratios. In contrast, the DOC source entering via inflow of coastal shelf waters had high DOC concentrations with high C:N and low specific bacterial production. The phytoplankton production in the fjord could not sustain the bacterial carbon demand, but was still the major source of organic carbon for bacterial growth. We assessed the bacterial community composition and found that communities were specific for the different water types i.e., the bacterial community of the coastal inflow water could be traced mainly in the subsurface water, while the glacial river community strongly dominated the surface water in the fjord.

Bacterioplankton play a key role in marine waters facilitating processes important for carbon cycling. However, the influence of specific bacterial populations and environmental conditions on bacterioplankton community performance remains unclear. The aim of the present study was to identify drivers of bacterioplankton community functions, taking into account the variability in community composition and environmental conditions over seasons, in two contrasting coastal systems. A Least Absolute Shrinkage and Selection Operator (LASSO) analysis of the biological and chemical data obtained from surface waters over a full year indicated that specific bacterial populations were linked to measured functions. Namely, Synechococcus (Cyanobacteria) was strongly correlated with protease activity. Furthermore, seasons exerted a profound effect on the substrate utilization capacity and composition of the communities. However, the pattern of substrate utilization capacity could not be directly linked to the community dynamics. The overall importance of dissolved organic matter (DOM) parameters in the LASSO models indicate that bacterioplankton respond to the present substrate landscape, with a particular importance of nitrogenous DOM. The analyses exemplifies that high taxonomic resolution can reveal links between individual populations and bulk bacterioplankton functions, and that for some taxa rRNA analyses are a necessary descriptor when attempting to correlate functions with communities. The reconciliation of patterns from two different systems indicates that the identified drivers of bacterioplankton community functions may be of broader relevance in coastal temperate waters.