Description: The Arctic Ocean plays a key role in regulating the global climate, while being highly sensitive to climate change. Temperature in the Arctic increases faster than the global average, causing a loss of multiyear sea-ice and affecting marine ecosystem structure and functioning. As a result, Arctic primary production and biogeochemical cycling are changing. Here, we investigated inter-annual changes in the concentrations of particulate and dissolved organic carbon (POC, DOC) together with biological drivers, such as phyto- and bacterioplankton abundance in the Fram Strait, the Atlantic gateway to the Central Arctic Ocean. Data have been collected in summer at the Long-Term Ecological Research observatory HAUSGARTEN during eight cruises from 2009 to 2017. Our results suggest that the dynamic physical system of the Fram Strait induces strong heterogeneity of the ecosystem that displays considerable intra-seasonal as well as inter-annual variability. Over the observational period, DOC concentrations were significantly negatively related to temperature and salinity, suggesting that outflow of Central Arctic waters carrying a high DOC load is the main control of DOC concentration in this region. POC concentration was not linked to temperature or salinity but tightly related to phytoplankton biomass as estimated from chlorophyll-a concentrations (Chl-a). For the years 2009–2017, no temporal trends in the depth-integrated (0–100 m) amounts of DOC and Chl-a were observed. In contrast, depth-integrated (0–100 m) amounts of POC, as well as the ratio [POC]:[TOC], decreased significantly over time. This suggests a higher partitioning of organic carbon into the dissolved phase. Potential causes and consequences of the observed changes in organic carbon stocks for food-web structure and CO2 sequestration are discussed.

Description: Assessing the role of sea ice algal biomass and primary production for polar ecosystems remains challenging due to the strong spatio-temporal variability of sea ice algae. Therefore, the spatial representativeness of sea ice algal biomass and primary production sampling remains a key issue in large-scale models and climate change predictions of polar ecosystems. To address this issue, we presented two novel approaches to up-scale ice algal chl a biomass and net primary production (NPP) estimates based on profiles covering distances of 100 to 1,000 s of meters. This was accomplished by combining ice core-based methods with horizontal under-ice spectral radiation profiling conducted in the central Arctic Ocean during summer 2012. We conducted a multi-scale comparison of ice-core based ice algal chl a biomass with two profiling platforms: a remotely operated vehicle and surface and under ice trawl (SUIT). NPP estimates were compared between ice cores and remotely operated vehicle surveys. Our results showed that ice core-based estimates of ice algal chl a biomass and NPP do not representatively capture the spatial variability compared to the remotely operated vehicle-based estimates, implying considerable uncertainties for pan-Arctic estimates based on ice core observations alone. Grouping sea ice cores based on region or ice type improved the representativeness. With only a small sample size, however, a high risk of obtaining non-representative estimates remains. Sea ice algal chl a biomass estimates based on the dominant ice class alone showed a better agreement between ice core and remotely operated vehicle estimates. Grouping ice core measurements yielded no improvement in NPP estimates, highlighting the importance of accounting for the spatial variability of both the chl a biomass and bottom-ice light in order to get representative estimates. Profile-based measurements of ice algae chl a biomass identified sea ice ridges as an underappreciated component of the Arctic ecosystem because chl a biomass was significantly greater in this unique habitat. Sea ice ridges are not easily captured with ice coring methods and thus require more attention in future studies. Based on our results, we provide recommendations for designing an efficient and effective sea ice algal sampling program for the summer season.

Description: We derive the chlorophyll a concentration (Chla) for three main phytoplankton functional types (PFTs) – diatoms, coccolithophores and cyanobacteria – by combining satellite multispectral-based information, being of a high spatial and temporal resolution, with retrievals based on high resolution of PFT absorption properties derived from hyperspectral satellite measurements. The multispectral-based PFT Chla retrievals are based on a revised version of the empirical OC-PFT algorithm applied to the Ocean Color Climate Change Initiative (OC-CCI) total Chla product. The PhytoDOAS analytical algorithm is used with some modifications to derive PFT Chla from SCIAMACHY hyperspectral measurements. To combine synergistically these two PFT products (OC-PFT and PhytoDOAS), an optimal interpolation is performed for each PFT in every OC-PFT sub-pixel within a PhytoDOAS pixel, given its Chla and its a priori error statistics. The synergistic product (SynSenPFT) is presented for the period of August 2002 March 2012 and evaluated against PFT Chla data obtained from in situ marker pigment data and the NASA Ocean Biogeochemical Model simulations and satellite information on phytoplankton size. The most challenging aspects of the SynSenPFT algorithm implementation are discussed. Perspectives on SynSenPFT product improvements and prolongation of the time series over the next decades by adaptation to Sentinel multi- and hyperspectral instruments are highlighted.

Description: Carbon flow through pelagic food webs is an expression of the composition, biomass and activity of phytoplankton as primary producers. In the near future, severe environmental changes in the Arctic Ocean are expected to lead to modifications of phytoplankton communities. Here, we used a combination of linear inverse modeling and ecological network analysis to study changes in food webs before, during, and after an anomalous warm water event in the eastern Fram Strait of the West Spitsbergen Current (WSC) that resulted in a shift from diatoms to flagellates during the summer (June–July). The model predicts substantial differences in the pathways of carbon flow in diatom- vs. Phaeocystis/nanoflagellate-dominated phytoplankton communities, but relatively small differences in carbon export. The model suggests a change in the zooplankton community and activity through increasing microzooplankton abundance and the switching of meso- and macrozooplankton feeding from strict herbivory to omnivory, detritivory and coprophagy. When small cells and flagellates dominated, the phytoplankton carbon pathway through the food web was longer and the microbial loop more active. Furthermore, one step was added in the flow from phytoplankton to mesozooplankton, and phytoplankton carbon to higher trophic levels is available via detritus or microzooplankton. Model results highlight how specific changes in phytoplankton community composition, as expected in a climate change scenario, do not necessarily lead to a reduction in carbon export.

Description: A corrigendum on Synergistic Exploitation of Hyper- and Multi-Spectral Precursor Sentinel Measurements to Determine Phytoplankton Functional Types (SynSenPFT) by Losa, S. N., Soppa, M. A., Dinter, T., Wolanin, A., Brewin, R. J. W., Bricaud, A., et al. (2017). Front. Mar. Sci. 4:203. doi: 10.3389/fmars.2017.00203. In the original article, we neglected, but would like to acknowledge the North-German Supercomputing Alliance (HLRN) for providing HPC resources that have contributed to the research results reported in this paper. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way.