Seawater carbonate chemistry and processes during experiments with Emiliania huxleyi (PML B93/11A)

The formation of calcareous skeletons by marine planktonic organisms and their subsequent sinking to depth generates a continuous rain of calcium carbonate to the deep ocean and underlying sediments. This is important in regulating marine carbon cycling and ocean-atmosphere CO2 exchange. The present rise in atmospheric CO2 levels causes significant changes in surface ocean pH and carbonate chemistry. Such changes have been shown to slow down calcification in corals and coralline macroalgae, but the majority of marine calcification occurs in planktonic organisms. Here we report reduced calcite production at increased CO2 concentrations in monospecific cultures of two dominant marine calcifying phytoplankton species, the coccolithophorids Emiliania huxleyi and Gephyrocapsa oceanica . This was accompanied by an increased proportion of malformed coccoliths and incomplete coccospheres. Diminished calcification led to a reduction in the ratio of calcite precipitation to organic matter production. Similar results were obtained in incubations of natural plankton assemblages from the north Pacific ocean when exposed to experimentally elevated CO2 levels. We suggest that the progressive increase in atmospheric CO2 concentrations may therefore slow down the production of calcium carbonate in the surface ocean. As the process of calcification releases CO2 to the atmosphere, the response observed here could potentially act as a negative feedback on atmospheric CO2 levels.

Seawater carbonate chemistry, calcification rate, oxygen production, maximum quantum yield, symbiont density, chlorophyll concentration and crystal width of Halimeda macroloba, Halimeda cylindracea and Marginopora vertebralis during experiments, 2011

The effects of elevated CO2 and temperature on photosynthesis and calcification in the calcifying algae Halimeda macroloba and Halimeda cylindracea and the symbiont-bearing benthic foraminifera Marginopora vertebralis were investigated through exposure to a combination of four temperatures (28°C, 30°C, 32°C, and 34°C) and four CO2 levels (39, 61, 101, and 203 Pa; pH 8.1, 7.9, 7.7, and 7.4, respectively). Elevated CO2 caused a profound decline in photosynthetic efficiency (FV : FM), calcification, and growth in all species. After five weeks at 34°C under all CO2 levels, all species died. Chlorophyll (Chl) a and b concentration in Halimeda spp. significantly decreased in 203 Pa, 32°C and 34°C treatments, but Chl a and Chl c2 concentration in M. vertebralis was not affected by temperature alone, with significant declines in the 61, 101, and 203 Pa treatments at 28°C. Significant decreases in FV : FM in all species were found after 5 weeks of exposure to elevated CO2 (203 Pa in all temperature treatments) and temperature (32°C and 34°C in all pH treatments). The rate of oxygen production declined at 61, 101, and 203 Pa in all temperature treatments for all species. The elevated CO2 and temperature treatments greatly reduced calcification (growth and crystal size) in M. vertebralis and, to a lesser extent, in Halimeda spp. These findings indicate that 32°C and 101 Pa CO2, are the upper limits for survival of these species on Heron Island reef, and we conclude that these species will be highly vulnerable to the predicted future climate change scenarios of elevated temperature and ocean acidification.

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).

Global macrozoobenthos production and energy budget data base V150731, with link to database

I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.

The effects of elevated CO2 on the growth and toxicity of field populations and cultures of the saxitoxin-producing dinoflagellate, Alexandrium fundyense

The effects of coastal acidification on the growth and toxicity of the saxitoxin-producing dinoflagellate Alexandrium fundyense were examined in culture and ecosystem studies. In culture experiments, Alexandrium strains isolated from Northport Bay, New York, and the Bay of Fundy, Canada, grew significantly faster (16-190%; p < 0.05) when exposed to elevated levels of PCO2 ( 90-190 Pa=900-1900 µatm) compared to lower levels ( 40 Pa=400 µatm). Exposure to higher levels of PCO2 also resulted in significant increases (71-81%) in total cellular toxicity (fg saxitoxin equivalents/cell) in the Northport Bay strain, while no changes in toxicity were detected in the Bay of Fundy strain. The positive relationship between PCO2 enrichment and elevated growth was reproducible in natural populations from New York waters. Alexandrium densities were significantly and consistently enhanced when natural populations were incubated at 150 Pa PCO2 compared to 39 Pa. During natural Alexandrium blooms in Northport Bay, PCO2 concentrations increased over the course of a bloom to more than 170 Pa and were highest in regions with the greatest Alexandrium abundances, suggesting Alexandrium may further exacerbate acidification and/or be especially adapted to these acidi-fied conditions. The co-occurrence of Alexandrium blooms and elevated PCO2 represents a previously unrecognized, compounding environmental threat to coastal ecosystems. The ability of elevated PCO2 to enhance the growth and toxicity of Alexandrium indicates that acidification promoted by eutrophication or climate change can intensify these, and perhaps other, harmful algal blooms.

Phosphate d18O pore-water profiles of sediment core GeoB11807-2 and GeoB11804-4

Phosphorus cycling in the ocean is influenced by biological and geochemical processes that are reflected in the oxygen isotope signature of dissolved inorganic phosphate (Pi). Extending the Pi oxygen isotope record from the water column into the seabed is difficult due to low Pi concentrations and small amounts of marine porewaters available for analysis. We obtained porewater profiles of Pi oxygen isotopes using a refined protocol based on the original micro-extraction designed by Colman (2002). This refined and customized method allows the conversion of ultra-low quantities (0.5 - 1 µmol) of porewater Pi to silver phosphate (Ag3PO4) for routine analysis by mass spectrometry. A combination of magnesium hydroxide co-precipitation with ion exchange resin treatment steps is used to remove dissolved organic matter, anions, and cations from the sample before precipitating Ag3PO4. Samples as low as 200 µg were analyzed in a continuous flow isotope ratio mass spectrometer setup. Tests with external and laboratory internal standards validated the preservation of the original phosphate oxygen isotope signature (d18OP) during micro extraction. Porewater data on d18OP has been obtained from two sediment cores of the Moroccan margin. The d18OP values are in a range of +19.49 to +27.30 per mill. We apply a simple isotope mass balance model to disentangle processes contributing to benthic P cycling and find evidence for Pi regeneration outbalancing microbial demand in the upper sediment layers. This highlights the great potential of using d18OP to study microbial processes in the subseafloor and at the sediment water interface.

Integrated values of heterotrophic picoplankton and primary production (euphotic zone) in the Antarctic polar frontal region during POLARSTERN cruises ANT-XIII/2 and ANT-XVI/3

We assessed relationships between phytoplankton standing stock, measured as chlorophyll a (Chl a), primary production (PP), and heterotrophic picoplankton production (HPP), in the epipelagic zone (0-100 m) as well as in the mesopelagic zone (100-1,000 m) in the polar frontal zone of the Atlantic sector of the Southern Ocean in austral summer (late December to January) and fall (March to early May). Integrated epipelagic HPP was positively correlated to integrated PP in summer (data for fall are not available) but not to integrated Chl a. However, integrated mesopelagic HPP was positively correlated to Chl a in summer as well as fall. The mesopelagic fraction of HPP as a percentage of total HPP was also positively correlated to Chl a, whereas the epipelagic fraction of HPP was negatively correlated to it. These results indicate that with increasing phytoplankton standing stock, constituted mainly of highly silicified diatoms, the focus of its consumption by heterotrophic picoplankton shifts from epipelagic to mesopelagic waters. With a growth efficiency of 30%, our HPP data indicate that in both the epipelagic and mesopelagic zone heterotrophic picoplankton consume 20% of PP. Mesopelagic heterotrophic picoplankton consumed around 80% of the sinking flux, measured from depletion of 234Th, which is a lower fraction than that reported from the central and subarctic Pacific. Our analysis indicates that it is important to include mesopelagic HPP in comprehensive assessments of the microbial consumption of PP, phytoplankton biomass, and particulate organic matter in cold oceanic systems with high rates of export production.

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).