Isotopic composition and chemistry of pore waters from ODP Site 195-1201 sediments, West Philippine Basin

This report summarizes chemical and isotopic data from Ocean Drilling Program Leg 195 Site 1201. Pore water is divided into three intervals based on the rate of chemical change with depth. The shallowest interval is the red clay unit between 1.26 and 56.40 meters below seafloor (mbsf). In this section, there are overall decreases in the concentrations of alkalinity, boron, lithium, magnesium, potassium, sodium, and sulfate, whereas concentrations of calcium and chloride increase. Values of d18O and dD plot near standard mean ocean water to the right of the global meteoric water line (GMWL). Five samples from 72.60 and 83.33 mbsf yielded pore water for analyses. These samples help define a trend in the second interval, which is between 56.4 and 238.98 mbsf. Here, concentrations of magnesium, potassium, sodium, and sulfate decease, whereas concentrations of boron, calcium, and chloride increase. Concentrations of alkalinity and lithium remain roughly constant. The deepest interval, between 238.04 and 504.8 mbsf, has comparatively slower decreases of sodium and sulfate, increases of calcium and chloride, slow increases of alkalinity and lithium, and roughly constant concentrations of magnesium, potassium, and boron. Values of d18O and dD in pore water between 146.98 and 504.80 mbsf plot in a linear trend to the right of the GMWL.

Individual dinoflagellate cysts species of surface sediment samples from the Mediterranean Sea

To determine the relationship between the spatial dinoflagellate cyst distribution and oceanic environmental conditions, 34 surface sediments from the Eastern and Western Mediterranean Sea have been investigated for their dinoflagellate cyst content. Multivariate ordination analyses identified sea-surface temperature, chlorophyll-a , nitrate concentration, salinity, and bottom oxygen concentration as the main factors affecting dinoflagellate cyst distribution in the region. Based on the relative abundance data, two associations can be distinguished that can be linked with major oceanographic settings. (1) An offshore eastern Mediterranean regime where surface sediments are characterized by oligotrophic, warm, saline surface water, and high oxygen bottom water concentrations (Impagidinium species, Nematosphaeropsis labyrinthus, Pyxidinopsis reticulata and Operculodinium israelianum). Based on the absolute abundance, temperature is positively related to the cyst accumulation of Operculodinium israelianum. Temperature does not form a causal factor influencing the accumulation rate of the other species in this association. Impagidinium species and Nematosphaeropsis labyrinthus show a positive relationship between cyst accumulation and nitrate availability in the upper waters. (2) Species of association 2 have highest relative abundances in the Western Mediterranean Sea, Strait of Sicily/NW Ionian Sea, and/or the distal ends of the Po/Nile/Rhône River plumes. At these stations, surface waters are characterized by (relative to the other regime) higher productivity associated with lower sea-surface temperature, salinity, and lower bottom water oxygen concentrations (Selenopemphix nephroides, Echinidinium spp., Selenopemphix quanta, Quinquecuspis concreta, Brigantedinium spp. and Lingulodinium machaerophorum). Based on both the absolute and relative abundances, Selenopemphix nephroides is suggested to be a suitable indicator to trace changes in the trophic state of the upper waters. The distribution of Lingulodinium machaerophorum is related to the presence of river-influenced surface waters, notably the Nile River. We suggest that this species might form a suitable marker to trace past variations in river discharge, notably from the Nile.

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).