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).

(Table 1) Nutrient concentrations and carbon isotopes of sea ice segments and brine sampled during Nathaniel B. Palmer cruises NBP98-07 and NBP06-08, Ross Sea

We examined controls on the carbon isotopic composition of sea ice brines and organic matter during cruises to the Ross Sea, Antarctica in November/December 1998 and November/December 2006. Brine samples were analyzed for salinity, nutrients, total dissolved inorganic carbon (sum CO2), and the 13C/12C ratio of Sum CO2 (d13C(sum CO2)). Particulate organic matter from sea ice cores was analyzed for percent particulate organic carbon (POC), percent total particulate nitrogen (TPN), and stable carbon isotopic composition (d13C(POC)). Sum CO2 in sea ice brines ranged from 1368 to 7149 µmol/kg, equivalent to 1483 to 2519 µmol/kg when normalized to 34.5 psu salinity (s sum CO2), the average salinity of Ross Sea surface waters. Sea ice primary producers removed up to 34% of the available sum CO2, an amount much higher than the maximum removal observed in sea ice free water. Carbonate precipitation and CO2 degassing may reduce s sum CO2 by a similar amount (e.g., 30%) in the most hypersaline sea ice environments, although brine volumes are low in very cold ice that supports these brines. Brine d13C(sum CO2) ranged from -2.6 to +8.0 per mil while d13C(POC) ranged from -30.5 to -9.2 per mil. Isotopic enrichment of the sum CO2 pool via net community production accounts for some but not all carbon isotopic enrichment of sea ice POC. Comparisons of s sum CO2, d13C(sum CO2), and d13C(POC) within sea ice suggest that epsilon p (the net photosynthetic fractionation factor) for sea ice algae is ~8 per mil smaller than the epsilon p observed for phytoplankton in open water regions of the Ross Sea. These results have implications for modeling of carbon uptake and transformation in the ice-covered ocean and for reconstruction of past sea ice extent based on stable isotopic composition of organic matter in sediment cores.

Effect of simulated ocean acidification on the acute toxicity of Cu and Cd to Tigriopus japonicus

Heavy metals pollution in marine environments has caused great damage to marine biological and ecological systems. Heavy metals accumulate in marine creatures, after which they are delivered to higher trophic levels of marine organisms through the marine food chain, which causes serious harm to marine biological systems and human health. Additionally, excess carbon dioxide in the atmosphere has caused ocean acidification. Indeed, about one third of the CO2 released into the atmosphere by anthropogenic activities since the beginning of the industrial revolution has been absorbed by the world's oceans, which play a key role in moderating climate change. Modeling has shown that, if current trends in CO2 emissions continue, the average pH of the ocean will reach 7.8 by the end of this century, corresponding to 0.5 units below the pre-industrial level, or a three-fold increase in H+ concentration. The ocean pH has not been at this level for several millions of years. Additionally, these changes are occurring at speeds 100 times greater than ever previously observed. As a result, several marine species, communities and ecosystems might not have time to acclimate or adapt to these fast changes in ocean chemistry. In addition, decreasing ocean pH has the potential to seriously affect the growth, development and reproduction reproductive processes of marine organisms, as well as threaten normal development of the marine ecosystem. Copepods are an important part of the meiofauna that play an important role in the marine ecosystem. Pollution of the marine environment can influence their growth and development, as well as the ecological processes they are involved in. Accordingly, there is important scientific value to investigation of the response of copepods to ocean acidification and heavy metals pollution. In the present study, we evaluated the effects of simulated future ocean acidification and the toxicological interaction between ocean acidity and heavy metals of Cu and Cd on T. japonicus. To accomplish this, harpacticoids were exposed to Cu and Cd concentration gradient seawater that had been equilibrated with CO2 and air to reach pH 8.0, 7.7, 7.3 and 6.5 for 96 h. Survival was not significantly suppressed under single sea water acidification, and the final survival rates were greater than 93% in both the experimental groups and the controls. The toxicity of Cu to T. japonicus was significantly affected by sea water acidification, with the 96h LC50 decreasing by nearly threefold from 1.98 to 0.64 mg/L with decreasing pH. The 96 h LC50 of Cd decreased with decreasing pH, but there was no significant difference in mortality among pH treatments. The results of the present study demonstrated that the predicted future ocean acidification has the potential to negatively affect survival of T. japonicus by exacerbating the toxicity of Cu. The calculated safe concentrations of Cu were 11.9 (pH 7.7) and 10.5 (pH 7.3) µg/L, which were below the class I value and very close to the class II level of the China National Quality Standard for Sea Water. Overall, these results indicate that the Chinese coastal sea will face a

Adaptive variability to low-pH river discharges in Acartia tonsa and stress responses to high PCO2 conditions

Environmental transitions leading to spatial physical-chemical gradients are of ecological and evolutionary interest because they are able to induce variations in phenotypic plasticity. Thus, the adaptive variability to low-pH river discharges may drive divergent stress responses [ingestion rates (IR) and expression of stress-related genes such as Heat shock protein 70 (Hsp70) and Ferritin] in the neritic copepod Acartia tonsa facing changes in the marine chemistry associated to ocean acidification (OA). These responses were tested in copepod populations inhabiting two environments with contrasting carbonate system parameters (an estuarine versus coastal area) in the Southern Pacific Ocean, and assessing an in situ and 96-h experimental incubation under conditions of high pressure of CO2 (PCO2 1200 ppm). Adaptive variability was a determining factor in driving variability of copepods' responses. Thus, the food-rich but colder and corrosive estuary induced a traits trade-off expressed as depressed IR under in situ conditions. However, this experience allowed these copepods to tolerate further exposure to high PCO2 levels better, as their IRs were on average 43% higher than those of the coastal individuals. Indeed, expression of both the Hsp70 and Ferritin genes in coastal copepods was significantly higher after acclimation to high PCO2 conditions. Along with other recent evidence, our findings confirm that adaptation to local fluctuations in seawater pH seems to play a significant role in the response of planktonic populations to OA-associated conditions. Facing the environmental threat represented by the inter-play between multiple drivers of climate change, this biological feature should be examined in detail as a potential tool for risk mitigation policies in coastal management arrangements.

Phytomass and soil carbon storage of different land cover classes in the Usa river basin

This study describes detailed partitioning of phytomass carbon (C) and soil organic carbon (SOC) for four study areas in discontinuous permafrost terrain, Northeast European Russia. The mean aboveground phytomass C storage is 0.7 kg C/m**2. Estimated landscape SOC storage in the four areas varies between 34.5 and 47.0 kg C/m**2 with LCC (land cover classification) upscaling and 32.5-49.0 kg C/m**2 with soil map upscaling. A nested upscaling approach using a Landsat thematic mapper land cover classification for the surrounding region provides estimates within 5 ± 5% of the local high-resolution estimates. Permafrost peat plateaus hold the majority of total and frozen SOC, especially in the more southern study areas. Burying of SOC through cryoturbation of O- or A-horizons contributes between 1% and 16% (mean 5%) of total landscape SOC. The effect of active layer deepening and thermokarst expansion on SOC remobilization is modeled for one of the four areas. The active layer thickness dynamics from 1980 to 2099 is modeled using a transient spatially distributed permafrost model and lateral expansion of peat plateau thermokarst lakes is simulated using geographic information system analyses. Active layer deepening is expected to increase the proportion of SOC affected by seasonal thawing from 29% to 58%. A lateral expansion of 30 m would increase the amount of SOC stored in thermokarst lakes/fens from 2% to 22% of all SOC. By the end of this century, active layer deepening will likely affect more SOC than thermokarst expansion, but the SOC stores vulnerable to thermokarst are less decomposed.

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).