Ash layer characteristics and major element oxide content of glasses from ODP Sites 162-982 and 162-985

The Cenozoic volcanic activity on Iceland has been recorded in North Atlantic sediments drilled during several Ocean Drilling Program (ODP)/Deep Sea Drilling Project legs (Legs 104, 151, 152, 162, and 163). Leg 162 (North Atlantic-Arctic Gateways II) recovered ash layers at Sites 982, 985, and 907 (Jansen, Raymo, Blum, et al., 1996, doi:10.2973/odp.proc.ir.162.1996). The revisited Site 907 was first drilled during Leg 151, and the ash from this site has been described in detail by Lacasse et al. (1996, doi:10.2973/odp.proc.sr.151.122.1996) and Werner et al. (1996, doi:10.2973/odp.proc.sr.151.123.1996). Site 982 is located within the Hatton-Rockall Basin on the Rockall Plateau, which is situated west of the British Isles. Site 985 is located northeast of Iceland at the foot of the eastern slope of the Iceland Plateau, adjacent to the Norwegian Basin. Here we report chemical analyses of Neogene tephra layers from Holes 982A, 983B, 982C, 985A, and 985B. The sedimentary sequence at Site 982 spans the lower Miocene-Holocene; Site 985 recovered sediments spanning the upper Oligocene-Holocene. Twenty-two distinct ash layers and ash-bearing sediments were sampled in Holes 982A-982C (Cores 162-982A-16H through 24H, 162-982B-14H through 56X, and 162-982C-15H through 27H), and 59 ash layers were sampled in Holes 985A and 985B (Cores 162-985A-11H through 59X, and 162-985B-11H through 14H). Almost 50% of the sampled ash is strongly altered (predominantly from Site 985). A cluster of altered thin layers in the lower Pliocene of Site 985 (top of Unit III) is remarkable.

Villefranche MedSeA mesocosm experiment 2013: perturbation studies and field studies

A joint mesocosm experiment took place in February/March 2013 in the bay of Villefranche in France as part of the european MedSeA project. Nine mesocosms (52 m**3) were deployed over a 2 weeks period and 6 different levels of pCO2 and 3 control mesocosms (about 450 µatm), were used, in order to cover the range of pCO2 anticipated for the end of the present century. During this experiment, the potential effects of these perturbations on chemistry, planktonic community composition and dynamics including: eucaryotic and prokaryotic species composition, primary production, nutrient and carbon utilization, calcification, diazotrophic nitrogen fixation, organic matter exudation and composition, micro-layer composition and biogas production were studied by a group of about 25 scientists from 8 institutes and 6 countries. This is one of the first mesocosm experiments conducted in oligotrophic waters. A blog dedicated to this experiment can be viewed at: http://medseavillefranche2013.obs-vlfr.fr.

Stareso MedSeA mesocosm experiment: field and perturbation studies 2012

A joint mesocosm experiment took place in June/July 2012 in Corsica (bay of Calvi, Stareso station;http://www.stareso.com/) as part of the european MedSeA project. Nine mesocosms (52 m**3) were deployed over a 20 days period and 6 different levels of pCO2 and 3 control mesocosms (about 450 µatm), were used, in order to cover the range of pCO2 anticipated for the end of the present century. During this experiment, the potential effects of these perturbations on chemistry, planktonic community composition and dynamics including: eucaryotic and prokaryotic species composition, primary production, nutrient and carbon utilization, calcification, diazotrophic nitrogen fixation, organic matter exudation and composition, micro-layer composition and biogas production were studied by a group of about 25 scientists from 8 institutes and 6 countries. This is one of the first mesocosm experiments conducted in oligotrophic waters. A blog dedicated to this experiment can be viewed at: http://medseastareso2012.wordpress.com/.

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).

Ciliates abundance in the eastern Mediterranean Sea in March and April 2008 during SES_GR1

The dataset is based on samples collected in the framework of the project SESAME, in the Ionian, Libyan and Aegean Sea during March- April 2008. 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).

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).

Data compilation of dinoflagellates growth rate, grazing rate and gross gowth efficiency from field and labratory experiments

The present data compilation includes dinoflagellates growth rate, grazing rate and gross growth efficiency determined either in the field or in laboratory experiments. From the existing literature, we synthesized all data that we could find on dinoflagellates. Some sources might be missing but none were purposefully ignored. We did not include autotrophic dinoflagellates in the database, but mixotrophic organisms may have been included. This is due to the large uncertainty about which taxa are mixotrophic, heterotrophic or symbiont bearing. Field data on microzooplankton grazing are mostly comprised of grazing rate using the dilution technique with a 24h incubation period. Laboratory grazing and growth data are focused on pelagic ciliates and heterotrophic dinoflagellates. The experiment measured grazing or growth as a function of prey concentration or at saturating prey concentration (maximal grazing rate). When considering every single data point available (each measured rate for a defined predator-prey pair and a certain prey concentration) there is a total of 801 data points for the dinoflagellates, counting experiments that measured growth and grazing simultaneously as 1 data point.