Abundance and Biomass from heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus in the eastern Mediteranean Sea in October 2008 during SES_GR2

The HCMR_SES_LAGRANGIAN_GR2_ MICROBIAL PARAMETERS dataset is based on samples collected in the framework of the project SESAME, in the North Aegean Sea during October 2008. The objectives were to measure the standing stocks and calculate the production of the microbial compartment of the food web, describe the vertical distribution pattern and characterize its structure and function through the water column as influenced by the BSW. Heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus abundance: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Heterotrophic Nanoflagellate abundance: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6?m and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Ciliate abundance: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Heterotrophic bacteria, Synechococcus, Prochlorococcus bacteria: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Abundance data were converted into C biomass using 250 fgC cell-1 (Kana & Glibert 1987) for Synechococcus, 50 fgC cell-1 (Campbell et al. 1994) for Prochlorococcus and 20fgC cell-1 (Lee & Fuhrman 1987) for heterotrophic bacteria. Heterotrophic Nanoflagellate biomass: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6µm and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Abundance data were converted into C biomass using 183 fgC µm**3 (Caron et al. 1995). Ciliate biomass: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Ciliate cell sizes were measured and converted into cell volumes using appropriate geometric formulae using image analysis. For biomass estimation, the conversion factor 190 fgC µm**3 was used (Putt and Stoecker 1989).

Abundance and Biomass from heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus in the Aegean Sea in April 2008 during SES_GR1

The HCMR_SES_LAGRANGIAN_GR1_ MICROBIAL PARAMETERS dataset is based on samples collected in the framework of the project SESAME, in the North Aegean Sea during April 2008. The objectives were to measure the standing stocks and calculate the production of the microbial compartment of the food web, describe the vertical distribution pattern and characterize its structure and function through the water column as influenced by the BSW. Heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus abundance: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Heterotrophic Nanoflagellate abundance: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6µm and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Ciliate abundance: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Heterotrophic bacteria, Synechococcus, Prochlorococcus biomass: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Abundance data were converted into C biomass using 250 fgC cell-1 (Kana & Glibert 1987) for Synechococcus, 50 fgC cell-1 (Campbell et al. 1994) for Prochlorococcus and 20fgC cell-1 (Lee & Fuhrman 1987) for heterotrophic bacteria. Heterotrophic Nanoflagellate biomass: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6µm and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Abundance data were converted into C biomass using 183 fgC µm**3 (Caron et al. 1995). Ciliate biomass: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Ciliate cell sizes were measured and converted into cell volumes using appropriate geometric formulae using image analysis. For biomass estimation, the conversion factor 190 fgC µm**3 was used (Putt and Stoecker 1989).

Methane concentrations and methane oxidation rates from June 2012 - June 2013 in the Elbe Estuary, from Hamburg to Cuxhaven, Germany

Rivers represent a transition zone between terrestric and aquatic environments, and between methane rich and methane poor environments. The Elbe River is one of the important rivers draining into the North Sea and with the Elbe potentially high amounts of methane could be imported into the water column of the North Sea. Twelve cruises from October 2010 until June 2013 were conducted from Hamburg towards the Elbe mouth at Cuxhaven. The dynamic of methane concentration in the water column and its consumption via methane oxidation was measured. In addition, physico-chemical parameters were used to estimate their influence on the methanotrophic activity. We observed high methane concentrations at the stations in the area of Hamburg harbor ("inner estuary") and about 10 times lower concentrations in the outer estuary (median of 416 versus 40 nmol/L). The methane oxidation (MOX) rate mirrowed the methane distribution with high values in the inner estuary and low values in the outer estuary (median of 161 versus 10 nmol/L/d respectively) Methane concentrations were significantly influenced by the river hydrology (falling water level) and the trophic state of the water (biological oxygen demand). In contrast to other studies no clear relation to the amount of suspendended particulate matter (SPM) was found. Methane oxidation rates were significantly influenced by methane concentration and to a weaker extent by temperature. Methane oxidation accounted for 41 ± 12% of the total loss of methane in summer/fall, but only for 5 ± 3% of the total loss in winter/spring. We applied a modified box model taking into account the residence times of a water parcel depending on discharge and tidal impact. We observed almost stable methane concentrations in the outer estuary, despite a strong loss of methane through diffusion and oxidation. Thus we postulate that in the outer Elbe estuary a strong additional input of methane is required, which could be provided by the extensive salt marshes near the river mouth.

(Table S1) Trace element and isotopic compositions of anhydrites sampled in the Manus Basin, Papua New Guinea

Microchemical analyses of rare earth element (REE) concentrations and Sr and S isotope ratios of anhydrite are used to identify sub-seafloor processes governing the formation of hydrothermal fluids in the convergent margin Manus Basin, Papua New Guinea. Samples comprise drill-core vein anhydrite and seafloor massive anhydrite from the PACMANUS (Roman Ruins, Snowcap and Fenway) and SuSu Knolls (North Su) active hydrothermal fields. Chondrite-normalized REE patterns in anhydrite show remarkable heterogeneity on the scale of individual grains, different from the near uniform REEN patterns measured in anhydrite from mid-ocean ridge deposits. The REEN patterns in anhydrite are correlated with REE distributions measured in hydrothermal fluids venting at the seafloor at these vent fields and are interpreted to record episodes of hydrothermal fluid formation affected by magmatic volatile degassing. 87Sr/86Sr ratios vary dramatically within individual grains between that of contemporary seawater and that of endmember hydrothermal fluid. Anhydrite was precipitated from a highly variable mixture of the two. The intra-grain heterogeneity implies that anhydrite preserves periods of contrasting hydrothermal versus seawater dominant near-seafloor fluid circulation. Most sulfate d34S values of anhydrite cluster around that of contemporary seawater, consistent with anhydrite precipitating from hydrothermal fluid mixed with locally entrained seawater. Sulfate d34S isotope ratios in some anhydrites are, however, lighter than that of seawater, which are interpreted as recording a source of sulfate derived from magmatic SO2 degassed from underlying felsic magmas in the Manus Basin. The range of elemental and isotopic signatures observed in anhydrite records a range of sub-seafloor processes including high-temperature hydrothermal fluid circulation, varying extents of magmatic volatile degassing, seawater entrainment and fluid mixing. The chemical and isotopic heterogeneity recorded in anhydrite at the inter- and intra-grain scale captures the dynamics of hydrothermal fluid formation and sub-seafloor circulation that is highly variable both spatially and temporally on timescales over which hydrothermal deposits are formed. Microchemical analysis of hydrothermal minerals can provide information about the temporal history of submarine hydrothermal systems that are variable over time and cannot necessarily be inferred only from the study of vent fluids.