Seawater carbonate chemistry and phytoplankton and eubacterial community compositions in the northwest subarctic Pacific

On-deck CO2-Fe-manipulated incubation experiments were conducted using surface seawater collected from the Western Subarctic Gyre of the NW Pacific in the summer of 2008 to elucidate the impacts of ocean acidification and Fe enrichment on the abundance and community composition of phytoplankton and eubacteria in the study area. During the incubation, excluding the initial period, the mean partial pressures of CO2 in non-Fe-added bottles were 230, 419, 843, and 1124 µatm, whereas those in Fe-added treatments were 152, 394, 791, and 1008 µatm. Changes in the abundance and community composition of phytoplankton were estimated using HPLC pigment signatures with the program CHEMTAX and flow cytometry. A DGGE fingerprint technique targeting 16S rRNA gene fragments was also used to estimate changes in eubacterial phylotypes during incubation. The Fe addition induced diatom blooms, and subsequently stimulated the growth of heterotrophic bacteria such as Roseobacter, Phaeobacter, and Alteromonas in the post-bloom phase. In both the Fe-limited and Fe-replete treatments, concentrations of 19'-hexanoyloxyfucoxanthin, a haptophyte marker, and the cell abundance of coccolithophores decreased at higher CO2 levels (750 and 1000 ppm), whereas diatoms exhibited little response to the changes in CO2 availability. The abundances of Synechococcus and small eukaryotic phytoplankton (<10 µm) increased at the higher CO2 levels. DGGE band positions revealed that Methylobacterium of Alphaproteobacteria occurred solely at lower CO2 levels (180 and 380 ppm) during the post-bloom phase. These results suggest that increases in CO2 level could affect not only the community composition of phytoplankton but also that of eubacteria. As these microorganisms play critical roles in the biological carbon pump and microbial loop, our results indicate that the progression of ocean acidification can alter the biogeochemical processes in the study area.

Villefranche sur Mer: multistressors experiment March 2012

The effect of ocean warming and acidification was investigated on a natural plankton assemblage from an oligotrophic area, the bay of Villefranche (NW Mediterranean Sea). The assemblage was sampled in March 2012 and exposed to the following four treatments for 12 days: control ( 360 µatm, 14°C), elevated pCO2 ( 610 µatm, 14°C), elevated temperature ( 410 µatm, 17°C), and elevated pCO2 and temperature ( 690 µatm, 17°C). Nutrients were already depleted at the beginning of the experiment and the concentrations of chlorophyll a (chl a), heterotrophic prokaryotes and viruses decreased, under all treatments, throughout the experiment. There were no statistically significant effects of ocean warming and acidification, whether in isolation or combined, on the concentrations of nutrients, particulate organic matter, chl a and most of the photosynthetic pigments. Furthermore, 13C labelling showed that the carbon transfer rates from 13C-sodium bicarbonate into particulate organic carbon were not affected by seawater warming nor acidification. Rates of gross primary production followed the general decreasing trend of chl a concentrations and were significantly higher under elevated temperature, an effect exacerbated when combined to elevated pCO2 level. In contrast to the other algal groups, the picophytoplankton population (cyanobacteria, mostly Synechococcus) increased throughout the experiment and was more abundant in the warmer treatment though to a lesser extent when combined to high pCO2 level. These results suggest that under nutrient-depleted conditions in the Mediterranean Sea, ocean acidification has a very limited impact on the plankton community and that small species will benefit from warming with a potential decrease of the export and energy transfer to higher trophic levels.

Micro- and picoplankton in waters of the Saint Paul Island, Pribilof Islands, Bering Sea

On the basis of materials collected in June-August 1994 characteristic data on microplankton were gathered in three biotopes of the eastern shelf of the Bering Sea: open shelf (coastal zone), the harbor, and the salt lagoon of Saint Paul Island (Pribiof Islands). The following parameters of microplanktonic communities were analyzed: abundance, biomass, and production of autotrophic picoplankton (picoalgae and cyanobacteria); abundance, biomass, growth rate constant, and production of bacterioplankton; role of filiform bacteria in bacterioplankton; species composition of heterotrophic flagellates and ciliates, their abundance, and biomass. Growth rates and consumption rates of picoplankton and bacterioplankton by heterotrophic nano- and microplankton were estimated in the experiments using the dilution method. Temporal dynamics of all structural and functional parameters of microplankton were analyzed. The minor role of autotrophic picoplankton and significant role of bacterioplankton as well as heterotrophic nano- and microplankton in planktonic communities of studied biotopes during summer months was shown. During certain periods, bacterial biomass was as high as 50-65% of phytoplankton biomass, and production of bacteria was as high as 20-40% of primary production. In the middle of the season biomass of nano- and microheterotrophic organisms in different biotopes exceeded biomass of mesozooplankton 2-10 times. Average consumption of bacterial production by nano- and microplankton during the period of observations was 85-94%.

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).

Composition and biomass of phytoplankton in the Northwest Pacific in summer 1990

According to results of Cruise 22 of R/V Akademik Mstislav Keldysh in the Northwest Pacific in July-August 1990, picophytoplankton represented mainly by cyanobacteria (up to 90%) comprised from 70 to 99% of total phytoplankton. Nanophytoplankton constituted substantial part of total biomass (22-37%) and consisted mainly of small phytoflagellates (2-4 ?m), cryptomonades, and coccolithophorids Emiliania huxleyi. Summer species such as Neodenticula seminae prevailed among large phytoplankton. Horizontal and vertical distribution of phytoplankton groups and species was described. Taxonomy and vertical distribution were related to nutrient concentrations in the upper mixed layer.

Freshwater mesocosm experiment 2012 in Vancouver, Canada on effects of increased temperature and food chain length on oxygen fluxes and plankton community structure

Over broad thermal gradients, the effect of temperature on aerobic respiration and photosynthesis rates explains variation in community structure and function. Yet for local communities, temperature dependent trophic interactions may dominate effects of warming. We tested the hypothesis that food chain length modifies the temperature-dependence of ecosystem fluxes and community structure. In a multi-generation aquatic food web experiment, increasing temperature strengthened a trophic cascade, altering the effect of temperature on estimated mass-corrected ecosystem fluxes. Compared to consumer-free and 3-level food chains, grazer-algae (2-level) food chains responded most strongly to the temperature gradient. Temperature altered community structure, shifting species composition and reducing zooplankton density and body size. Still, food chain length did not alter the temperature dependence of net ecosystem fluxes. We conclude that locally, food chain length interacts with temperature to modify community structure, but only temperature, not food chain length influenced net ecosystem fluxes.

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).