Impact of temperature and species interaction on filamentous cyanobacteria may be more important than salinity and increased pCO2 levels

A future business-as-usual scenario (A1FI) was tested on two bloom-forming cyanobacteria of the Baltic Proper, Nodularia spumigena and Aphanizomenon sp., growing separately and together. The projected scenario was tested in two laboratory experiments where (a) interactive effects of increased temperature and decreased salinity and (b) interactive effects of increased temperature and elevated levels of pCO2 were tested. Increased temperature, from 12 to 16 °C, had a positive effect on the biovolume and photosynthetic activity (F v/F m) of both species. Compared when growing separately, the biovolume of each species was lower when grown together. Decreased salinity, from 7 to 4, and elevated levels of pCO2, from 380 to 960 ppm, had no effect on the biovolume, but on F v/F m of N. spumigena with higher F v/F m in salinity 7. Our results suggest that the projected A1FI scenario might be beneficial for the two species dominating the extensive summer blooms in the Baltic Proper. However, our results further stress the importance of studying interactions between species.

Seawater carbonate chemistry and photosystem II photoinactivation of the coastal diatom Thalassiosira pseudonana in a laboratory experiment

We studied the interactive effects of pCO2 and growth light on the coastal marine diatom Thalassiosira pseudonana CCMP 1335 growing under ambient and expected end-of-the-century pCO2 (750 ppmv), and a range of growth light from 30 to 380 µmol photons/m**2/s. Elevated pCO2 significantly stimulated the growth of T. pseudonana under sub-saturating growth light, but not under saturating to super-saturating growth light. Under ambient pCO2 susceptibility to photoinactivation of photosystem II (sigma i) increased with increasing growth rate, but cells growing under elevated pCO2 showed no dependence between growth rate and sigma i, so under high growth light cells under elevated pCO2 were less susceptible to photoinactivation of photosystem II, and thus incurred a lower running cost to maintain photosystem II function. Growth light altered the contents of RbcL (RUBISCO) and PsaC (PSI) protein subunits, and the ratios among the subunits, but there were only limited effects on these and other protein pools between cells grown under ambient and elevated pCO2.

Seawater carbonate chemistry, nutrients, particulate carbon and growth rate of Emiliania huxleyi (AC472), Calcidiscus leptoporus (AC370) and Syracosphaera pulchra (AC418) during experiments, 2011

The response of Emiliania huxleyi (Lohmann) W. W. Hay et H. Mohler, Calcidiscus leptoporus (G. Murray et V. H. Blackman) J. Schiller, andSyracosphaera pulchra Lohmann to elevated partial pressure of carbon dioxide (pCO2) was investigated in batch cultures. We reported on the response of both haploid and diploid life stages of these three species. Growth rate, cell size, particulate inorganic carbon (PIC), and particulate organic carbon (POC) of both life stages were measured at two different pCO2 (400 and 760 parts per million [ppm]), and their organic and inorganic carbon production were calculated. The two life stages within the same species generally exhibited a similar response to elevated pCO2, the response of the haploid stage being often more pronounced than that of the diploid stage. The growth rate was consistently higher at elevated pCO2, but the response of other processes varied among species. Calcification rate of C. leptoporusand of S. pulchra did not change at elevated pCO2, whereas it increased in E. huxleyi. POC production and cell size of both life stages of S. pulchra and of the haploid stage of E. huxleyi markedly decreased at elevated pCO2. It remained unaltered in the diploid stage of E. huxleyi and C. leptoporus and increased in the haploid stage of the latter. The PIC:POC ratio increased in E. huxleyi and was constant in C. leptoporus and S. pulchra. Elevated pCO2 has a significant effect on these three coccolithophore species, the haploid stage being more sensitive. This effect must be taken into account when predicting the fate of coccolithophores in the future ocean.

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).