Pore water geochemistry of Håkon Mosby mud volcano sediments measured at station PS74/169-1_PUC-15 (Z1-S1, new flow surface)

Pore water and turnover rates were determined for surface sediment cores obtained in 2009 and 2010. The pore water was extracted with Rhizons (Rhizon CSS: length 5 cm, pore diameter 0.15 µm; Rhizosphere Research Products, Wageningen, Netherlands) in 1 cm-resolution and immediately fixed in 5% zinc acetate (ZnAc) solution for sulfate, and sulfide analyses. The samples were diluted, filtered and the concentrations measured with non-suppressed anion exchange chromatography (Waters IC-Pak anion exchange column, waters 430 conductivity detector). The total sulfide concentrations (H2S + HS- + S**2-) were determined using the diamine complexation method (doi:10.4319/lo.1969.14.3.0454). Samples for dissolved inorganic carbon (DIC) and alkalinity measurements were preserved by adding 2 µl saturated mercury chloride (HgCl2) solution and stored headspace-free in gas-tight glass vials. DIC and alkalinity were measured using the flow injection method (detector VWR scientific model 1054) (doi:10.4319/lo.1992.37.5.1113). Dissolved sulfide was eliminated prior to the DIC measurement by adding 0.5 M molybdate solution (doi:10.4319/lo.1995.40.5.1011). Nutrient subsamples (10 - 15 ml) were stored at - 20 °C prior to concentration measurements with a Skalar Continuous-Flow Analyzer (doi:10.1002/9783527613984).

Pore water geochemistry of Håkon Mosby mud volcano sediments measured at station MSM16/2_847-1 (Z2-S2, aged flow surface)

Pore water and turnover rates were determined for surface sediment cores obtained in 2009 and 2010. The pore water was extracted with Rhizons (Rhizon CSS: length 5 cm, pore diameter 0.15 µm; Rhizosphere Research Products, Wageningen, Netherlands) in 1 cm-resolution and immediately fixed in 5% zinc acetate (ZnAc) solution for sulfate, and sulfide analyses. The samples were diluted, filtered and the concentrations measured with non-suppressed anion exchange chromatography (Waters IC-Pak anion exchange column, waters 430 conductivity detector). The total sulfide concentrations (H2S + HS- + S**2-) were determined using the diamine complexation method (doi:10.4319/lo.1969.14.3.0454). Samples for dissolved inorganic carbon (DIC) and alkalinity measurements were preserved by adding 2 µl saturated mercury chloride (HgCl2) solution and stored headspace-free in gas-tight glass vials. DIC and alkalinity were measured using the flow injection method (detector VWR scientific model 1054) (doi:10.4319/lo.1992.37.5.1113). Dissolved sulfide was eliminated prior to the DIC measurement by adding 0.5 M molybdate solution (doi:10.4319/lo.1995.40.5.1011). Nutrient subsamples (10 - 15 ml) were stored at - 20 °C prior to concentration measurements with a Skalar Continuous-Flow Analyzer (doi:10.1002/9783527613984).

Pore water geochemistry of arctic deep sea sediments measured at station MSM16/2_809-1 (REF, Reference)

Pore water and turnover rates were determined for surface sediment cores obtained in 2009 and 2010. The pore water was extracted with Rhizons (Rhizon CSS: length 5 cm, pore diameter 0.15 µm; Rhizosphere Research Products, Wageningen, Netherlands) in 1 cm-resolution and immediately fixed in 5% zinc acetate (ZnAc) solution for sulfate, and sulfide analyses. The samples were diluted, filtered and the concentrations measured with non-suppressed anion exchange chromatography (Waters IC-Pak anion exchange column, waters 430 conductivity detector). The total sulfide concentrations (H2S + HS- + S**2-) were determined using the diamine complexation method (doi:10.4319/lo.1969.14.3.0454). Samples for dissolved inorganic carbon (DIC) and alkalinity measurements were preserved by adding 2 µl saturated mercury chloride (HgCl2) solution and stored headspace-free in gas-tight glass vials. DIC and alkalinity were measured using the flow injection method (detector VWR scientific model 1054) (doi:10.4319/lo.1992.37.5.1113). Dissolved sulfide was eliminated prior to the DIC measurement by adding 0.5 M molybdate solution (doi:10.4319/lo.1995.40.5.1011). Nutrient subsamples (10 - 15 ml) were stored at - 20 °C prior to concentration measurements with a Skalar Continuous-Flow Analyzer (doi:10.1002/9783527613984).

Pore water geochemistry of Håkon Mosby mud volcano sediments measured at station MSM16/2_838-1 (Z1-S3, new flow surface)

Pore water and turnover rates were determined for surface sediment cores obtained in 2009 and 2010. The pore water was extracted with Rhizons (Rhizon CSS: length 5 cm, pore diameter 0.15 µm; Rhizosphere Research Products, Wageningen, Netherlands) in 1 cm-resolution and immediately fixed in 5% zinc acetate (ZnAc) solution for sulfate, and sulfide analyses. The samples were diluted, filtered and the concentrations measured with non-suppressed anion exchange chromatography (Waters IC-Pak anion exchange column, waters 430 conductivity detector). The total sulfide concentrations (H2S + HS- + S**2-) were determined using the diamine complexation method (doi:10.4319/lo.1969.14.3.0454). Samples for dissolved inorganic carbon (DIC) and alkalinity measurements were preserved by adding 2 µl saturated mercury chloride (HgCl2) solution and stored headspace-free in gas-tight glass vials. DIC and alkalinity were measured using the flow injection method (detector VWR scientific model 1054) (doi:10.4319/lo.1992.37.5.1113). Dissolved sulfide was eliminated prior to the DIC measurement by adding 0.5 M molybdate solution (doi:10.4319/lo.1995.40.5.1011). Nutrient subsamples (10 - 15 ml) were stored at - 20 °C prior to concentration measurements with a Skalar Continuous-Flow Analyzer (doi:10.1002/9783527613984).

Pore water geochemistry of Håkon Mosby mud volcano sediments measured at station MSM16/2_855-1 (Z2-S3, aged flow surface)

Pore water and turnover rates were determined for surface sediment cores obtained in 2009 and 2010. The pore water was extracted with Rhizons (Rhizon CSS: length 5 cm, pore diameter 0.15 µm; Rhizosphere Research Products, Wageningen, Netherlands) in 1 cm-resolution and immediately fixed in 5% zinc acetate (ZnAc) solution for sulfate, and sulfide analyses. The samples were diluted, filtered and the concentrations measured with non-suppressed anion exchange chromatography (Waters IC-Pak anion exchange column, waters 430 conductivity detector). The total sulfide concentrations (H2S + HS- + S**2-) were determined using the diamine complexation method (doi:10.4319/lo.1969.14.3.0454). Samples for dissolved inorganic carbon (DIC) and alkalinity measurements were preserved by adding 2 µl saturated mercury chloride (HgCl2) solution and stored headspace-free in gas-tight glass vials. DIC and alkalinity were measured using the flow injection method (detector VWR scientific model 1054) (doi:10.4319/lo.1992.37.5.1113). Dissolved sulfide was eliminated prior to the DIC measurement by adding 0.5 M molybdate solution (doi:10.4319/lo.1995.40.5.1011). Nutrient subsamples (10 - 15 ml) were stored at - 20 °C prior to concentration measurements with a Skalar Continuous-Flow Analyzer (doi:10.1002/9783527613984).

Pore water geochemistry of Håkon Mosby mud volcano sediments measured at station PS74/168-1 (Z1-S2, new flow surface)

Pore water and turnover rates were determined for surface sediment cores obtained in 2009 and 2010. The pore water was extracted with Rhizons (Rhizon CSS: length 5 cm, pore diameter 0.15 µm; Rhizosphere Research Products, Wageningen, Netherlands) in 1 cm-resolution and immediately fixed in 5% zinc acetate (ZnAc) solution for sulfate, and sulfide analyses. The samples were diluted, filtered and the concentrations measured with non-suppressed anion exchange chromatography (Waters IC-Pak anion exchange column, waters 430 conductivity detector). The total sulfide concentrations (H2S + HS- + S**2-) were determined using the diamine complexation method (doi:10.4319/lo.1969.14.3.0454). Samples for dissolved inorganic carbon (DIC) and alkalinity measurements were preserved by adding 2 µl saturated mercury chloride (HgCl2) solution and stored headspace-free in gas-tight glass vials. DIC and alkalinity were measured using the flow injection method (detector VWR scientific model 1054) (doi:10.4319/lo.1992.37.5.1113). Dissolved sulfide was eliminated prior to the DIC measurement by adding 0.5 M molybdate solution (doi:10.4319/lo.1995.40.5.1011). Nutrient subsamples (10 - 15 ml) were stored at - 20 °C prior to concentration measurements with a Skalar Continuous-Flow Analyzer (doi:10.1002/9783527613984).

Pore water geochemistry of Håkon Mosby mud volcano sediments measured at station PS74/172-1_PUC-136 (Z3-S2, old flow surface)

Pore water and turnover rates were determined for surface sediment cores obtained in 2009 and 2010. The pore water was extracted with Rhizons (Rhizon CSS: length 5 cm, pore diameter 0.15 µm; Rhizosphere Research Products, Wageningen, Netherlands) in 1 cm-resolution and immediately fixed in 5% zinc acetate (ZnAc) solution for sulfate, and sulfide analyses. The samples were diluted, filtered and the concentrations measured with non-suppressed anion exchange chromatography (Waters IC-Pak anion exchange column, waters 430 conductivity detector). The total sulfide concentrations (H2S + HS- + S**2-) were determined using the diamine complexation method (doi:10.4319/lo.1969.14.3.0454). Samples for dissolved inorganic carbon (DIC) and alkalinity measurements were preserved by adding 2 µl saturated mercury chloride (HgCl2) solution and stored headspace-free in gas-tight glass vials. DIC and alkalinity were measured using the flow injection method (detector VWR scientific model 1054) (doi:10.4319/lo.1992.37.5.1113). Dissolved sulfide was eliminated prior to the DIC measurement by adding 0.5 M molybdate solution (doi:10.4319/lo.1995.40.5.1011). Nutrient subsamples (10 - 15 ml) were stored at - 20 °C prior to concentration measurements with a Skalar Continuous-Flow Analyzer (doi:10.1002/9783527613984).

Sea surface and the sea floor regionalization of the Southern Ocean by multivariate cluster analysis, links to ArcGIS project files

This study subdivides the Weddell Sea, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis uses 28 environmental variables for the sea surface, 25 variables for the seabed and 9 variables for the analysis between surface and bottom variables. The data were taken during the years 1983-2013. Some data were interpolated. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared for the identification of the most reasonable method. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested. For the seabed 8 and 12 clusters were identified as reasonable numbers for clustering the Weddell Sea. For the sea surface the numbers 8 and 13 and for the top/bottom analysis 8 and 3 were identified, respectively. Additionally, the results of 20 clusters are presented for the three alternatives offering the first small scale environmental regionalization of the Weddell Sea. Especially the results of 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

Environmental variables and multivariate seabed classification maps via k means clustering of Potter Cove, Antarctica, link to input and result files in GeoTIFF format

This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

Geochemical data from pore water and solids from cores GS08-153-91GC12 and GS08-153-53-GC6, Arctic Mid-Ocean Ridge

Microbial communities and their associated metabolic activity in marine sediments have a profound impact on global biogeochemical cycles. Their composition and structure are attributed to geochemical and physical factors, but finding direct correlations has remained a challenge. Here we show a significant statistical relationship between variation in geochemical composition and prokaryotic community structure within deep-sea sediments. We obtained comprehensive geochemical data from two gravity cores near the hydrothermal vent field Loki's Castle at the Arctic Mid-Ocean Ridge, in the Norwegian-Greenland Sea. Geochemical properties in the rift valley sediments exhibited strong centimeter-scale stratigraphic variability. Microbial populations were profiled by pyrosequencing from 15 sediment horizons (59,364 16S rRNA gene tags), quantitatively assessed by qPCR, and phylogenetically analyzed. Although the same taxa were generally present in all samples, their relative abundances varied substantially among horizons and fluctuated between Bacteria- and Archaea-dominated communities. By independently summarizing covariance structures of the relative abundance data and geochemical data, using principal components analysis, we found a significant correlation between changes in geochemical composition and changes in community structure. Differences in organic carbon and mineralogy shaped the relative abundance of microbial taxa. We used correlations to build hypotheses about energy metabolisms, particularly of the Deep Sea Archaeal Group, specific Deltaproteobacteria, and sediment lineages of potentially anaerobic Marine Group I Archaea. We demonstrate that total prokaryotic community structure can be directly correlated to geochemistry within these sediments, thus enhancing our understanding of biogeochemical cycling and our ability to predict metabolisms of uncultured microbes in deep-sea sediments.

Medem Channel profiles based on stand-alone model simulation and corrections with nudging

State-of-the-art process-based models have shown to be applicable to the simulation and prediction of coastal morphodynamics. On annual to decadal temporal scales, these models may show limitations in reproducing complex natural morphological evolution patterns, such as the movement of bars and tidal channels, e.g. the observed decadal migration of the Medem Channel in the Elbe Estuary, German Bight. Here a morphodynamic model is shown to simulate the hydrodynamics and sediment budgets of the domain to some extent, but fails to adequately reproduce the pronounced channel migration, due to the insufficient implementation of bank erosion processes. In order to allow for long-term simulations of the domain, a nudging method has been introduced to update the model-predicted bathymetries with observations. The model-predicted bathymetry is nudged towards true states in annual time steps. Sensitivity analysis of a user-defined correlation length scale, for the definition of the background error covariance matrix during the nudging procedure, suggests that the optimal error correlation length is similar to the grid cell size, here 80-90 m. Additionally, spatially heterogeneous correlation lengths produce more realistic channel depths than do spatially homogeneous correlation lengths. Consecutive application of the nudging method compensates for the (stand-alone) model prediction errors and corrects the channel migration pattern, with a Brier skill score of 0.78. The proposed nudging method in this study serves as an analytical approach to update model predictions towards a predefined 'true' state for the spatiotemporal interpolation of incomplete morphological data in long-term simulations.