441 resultados para Cyanobacteria


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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.

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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.

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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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Bacterial biofilms provide cues for the settlement of marine invertebrates such as coral larvae, and are therefore important for the resilience and recovery of coral reefs. This study aimed to better understand how ocean acidification may affect the community composition and diversity of bacterial biofilms on surfaces under naturally reduced pH conditions. Settlement tiles were deployed at coral reefs in Papua New Guinea along pH gradients created by two CO2 seeps, and upper and lower tiles surfaces were sampled 5 and 13 months after deployment. Automated Ribosomal Intergenic Spacer Analysis were used to characterize more than 200 separate bacterial communities, complemented by amplicon sequencing of the bacterial 16S rRNA gene of 16 samples. The bacterial biofilm consisted predominantly of Alpha-, Gamma- and Deltaproteobacteria, as well as Cyanobacteria, Flavobacteriia and Cytophaga, whereas putative settlement-inducing taxa only accounted for a small fraction of the community. Bacterial biofilm composition was heterogeneous with approximately 25% shared operational taxonomic units between samples. Among the observed environmental parameters, pH only had a weak effect on community composition (R² ~ 1%) and did not affect community richness and evenness. In contrast, there were strong differences between upper and lower surfaces (contrasting in light exposure and grazing intensity). There also appeared to be a strong interaction between bacterial biofilm composition and the macroscopic components of the tile community. Our results suggest that on mature settlement surfaces in situ, pH does not have a strong impact on the composition of bacterial biofilms. Other abiotic and biotic factors such as light exposure and interactions with other organisms may be more important in shaping bacterial biofilms than changes in seawater pH.

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