762 resultados para Synechococcus blooms

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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. 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. 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).

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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.

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The effects of CO2-induced seawater acidification on plankton communities were also addressed in a series of 3 mesocosm experiments, called the Pelagic Ecosystem CO2 Enrichment (PeECE I-III) studies, which were conducted in the Large-Scale Mesocosm Facilities of the University of Bergen, Norway in 2001, 2003 and 2005, respectively. Each experiment consisted of 9 mesocosms, in which CO2 was manipulated to initial concentrations of 190, 350 and 750 µatm in 2001 and 2003, and 350, 700 and 1050 µatm in 2005. The present dataset concerns PeECE I.

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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).

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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).

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A mesocosm experiment was conducted to investigate the impact of rising fCO2 on the build-up and decline of organic matter during coastal phytoplankton blooms. Five mesocosms (~38 m³ each) were deployed in the Baltic Sea during spring (2009) and enriched with CO2 to yield a gradient of 355-862 µatm. Mesocosms were nutrient fertilized initially to induce phytoplankton bloom development. Changes in particulate and dissolved organic matter concentrations, including dissolved high-molecular weight (>1 kDa) combined carbohydrates, dissolved free and combined amino acids as well as transparent exopolymer particles (TEP), were monitored over 21 days together with bacterial abundance, and hydrolytic extracellular enzyme activities. Overall, organic matter followed well-known bloom dynamics in all CO2 treatments alike. At high fCO2, higher dPOC:dPON during bloom rise, and higher TEP concentrations during bloom peak, suggested preferential accumulation of carbon-rich components. TEP concentration at bloom peak was significantly related to subsequent sedimentation of particulate organic matter. Bacterial abundance increased during the bloom and was highest at high fCO2. We conclude that increasing fCO2 supports production and exudation of carbon-rich components, enhancing particle aggregation and settling, but also providing substrate and attachment sites for bacteria. More labile organic carbon and higher bacterial abundance can increase rates of oxygen consumption and may intensify the already high risk of oxygen depletion in coastal seas in the future.

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The effects of CO2-induced seawater acidification on plankton communities were also addressed in a series of 3 mesocosm experiments, called the Pelagic Ecosystem CO2 Enrichment (PeECE I-III) studies, which were conducted in the Large-Scale Mesocosm Facilities of the University of Bergen, Norway in 2001, 2003 and 2005, respectively. Each experiment consisted of 9 mesocosms, in which CO2 was manipulated to initial concentrations of 190, 350 and 750 µatm in 2001 and 2003, and 350, 700 and 1050 µatm in 2005. The present dataset concerns PeECE III.

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The cruise with RV Tydeman was devoted to study permanently stratified plankton systems in the (sub)tropical ocean, which are characterised by a deep chlorophyll peak between 80 and 150 m. To minimise lateral effects by horizontal transport of nutrients and organic matter from river outflow and upwelling regions, stations were selected in the middle of the North Atlantic Ocean between the continents of America and Africa. (5 - 35° N and 50 - 15° W). Here the vertical distributions of light and nutrients control the abundance and growth of autotrophic algae in the thermically stratified water column. This phytoplankton is numerically dominated by the prokaryotic picoplankters Synechococcus spp. and Prochlorococcus spp., which are smaller than 2 ?m. The productivity of the 100 to 150 m deep euphotic zone can be high, because a high heterotrophic/autotrophic biomass ratio induces a rapid regeneration of nutrients and inorganic carbon. Primary grazers are mainly micro-organisms such as heterotrophic nannoflagellates and ciliates, which feed on the small algae and on bacteria. Heterotrophic bacteria can outnumber the autotrophic algae, because their number is related to the substrate pools of dissolved and particulate dead organic matter. These DOC and detritus pools reach equilibrium at a concentration, where the rate of their production (proportional to algal biomass) equals their mineralisation and sinking rate (proportional to the concentration and weight of POC and detritus). At a relatively low value of the weight-specific loss rates, the equilibrium concentration of these carbon pools and their load of bacteria can be high. The bacterial productivity is proportional to the mineralisation rate, which in a steady state can never be higher than the rate of primary production. Hence the ratio in turnover rate of bacteria and autotrophs tends to be reciprocally proportional to their biomass ratio.

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Harmful algal blooms are mainly caused by marine dinoflagellates and are known to produce potent toxins that may affect the ecosystem, human activities and health. Such events have increased in frequency and intensity worldwide in the past decades. Numerous processes involved in Global Change are amplified in the Arctic, but little is known about species specific responses of arctic dinoflagellates. The aim of this work was to perform an exhaustive morphological, phylogenetical and toxinological characterization of Greenland Protoceratium reticulatum and, in addition, to test the effect of temperature on growth and production of bioactive secondary metabolites. Seven clonal isolates, the first isolates of P. reticulatum available from arctic waters, were phylogenetically characterized by analysis of the LSU rDNA. Six isolates were further characterized morphologically and were shown to produce both yessotoxins (YTX) and lytic compounds, representing the first report of allelochemical activity in P. reticulatum. As shown for one of the isolates, growth was strongly affected by temperature with a maximum growth rate at 15 °C, a significant but slow growth at 1 °C, and cell death at 25 °C, suggesting an adaptation of P. reticulatum to temperate waters. Temperature had no major effect on total YTX cell quota or lytic activity but both were affected by the growth phase with a significant increase at stationary phase. A comparison of six isolates at a fixed temperature of 10 °C showed high intraspecific variability for all three physiological parameters tested. Growth rate varied from 0.06 to 0.19 per day, and total YTX concentration ranged from 0.3 to 15.0 pg YTX/cell and from 0.5 to 31.0 pg YTX/cell at exponential and stationary phase, respectively. All six isolates performed lytic activity; however, for two isolates lytic activity was only detectable at higher cell densities in stationary phase.