Colored dissolved organic matter (cDOM) absorption measurements in Antarctic lakes

The datasets present measurements of cDOM absorption of lakes located in Antarctic oasis during the summer periods from 2013 to 2016. In summer season of 2013 water samples were collected on Fildes Peninsula (King George Island, West Antarctica) - Bellingshausen Station, Russia. Investigated lakes on Fides Peninsula were completely or partly free from ice cover during water sampling. In summer seasons of 2014-2016 water samples were collected on Vestfold Hills, Reuer Island and Larsemann Hills Oasis (East Antarctica) - Progress station, Russia. During 2014-2016 summer season part of lakes on Larsemann Hills Oasis were free from ice cover, some of the lakes were completely covered by ice and were drilled before sampling. Part of the water samples from Progress Station (2015) has not been filtered. cDOM is operationally defined by the chosen filter pore size. Samples have been consistently filtrated through 0.7 µm pore size glas fibre filters. cDOM filtrates have been stored in darkness and have been measured after the expedition using the dual-beam Specord200 laboratory spectrometer (Jena Analytik) at the Otto Schmidt Laboratory OSL, Arctic and Antarctic Research Institute, St. Petersburg, Russia. The OSL cDOM protocol (Heim and Roessler, 2016) prescribes 3 Absorbance (A) measurements per sample from UV to 750 nm against ultra-pure water. The absorption coefficient, a, is calculated by a = 2.303A/L, where L is the pathlength of the cuvette [m], and the factor 2.303 converts log10 to loge. The output of the calculation is a continuous spectrum of a. The cDOM a spectra are used to determine the exponential slope value for specific wavelength ranges, S by fitting the data between min and max wavelength to an exponential function. We provide cDOM absorption coefficients for the wavelengths 254, 260, 350, 375, 400, 412, 440, 443 nm [1/m] and Slope values for three different UV, VIS, wavelength ranges: 275 to 295 nm, 350 to 400 nm, 300 to 500 nm [1/nm]. All data were carried out by scientists from Arctic and Antarctic Research Institute and Saint Petersburg State University of Russia during Russian Antarctic Expedition in 2013-2016.

Colored dissolved organic matter (cDOM) absorption measurements in terrestrial water objects of Yamal, Yavai and Gydan Peninsula

The datasets present measurements of cDOM absorption in lakes, rivers and streams of Yamal and Gydan Peninsula area during the summer periods from 2012-2014 and 2016. In summer seasons of 2012 - 2013 water samples was collected during "Yamal-Arctic" Expedition. All of the research areas were located near the coastline of Yamal, Yavay, and Gydan Peninsula and Bely Island. In 2012 water samples from rivers, lakes and streams were taken near New Port, Cape Kamenny and Tambey settlements and in basins (water catchments) of the Sabetta, Seyakha, Yuribey (Baydaratskaya Bay, Gydan Peninsula) and Mongocheyakha rivers. In 2013 water samples from rivers, lakes and streams were taken in the Yavai Peninsula, Yayne Vong bay and in the basins (water catchments) of the Sabetta, Mongocheyakha and Yuribey (Gydan Peninsula) rivers. In 2014 lakes were sampled in the Erkuta River basin, south of Yamal Peninsula. In 2016 lakes and rivers were sampled it the Erkuta River basin and Polar Ural area. cDOM is operationally defined by the chosen filter pore size. Samples have been consistently filtrated through 0.7 µm pore size glas fibre filters. cDOM filtrates have been stored in darkness and have been measured after the expedition using the dual-beam Specord200 laboratory spectrometer (Jena Analytik) at the Otto Schmidt Laboratory OSL, Arctic and Antarctic Research Institute, St. Petersburg, Russia. The OSL cDOM protocol (Heim and Roessler, 2016) prescribes 3 Absorbance (A) measurements per sample from UV to 750 nm against ultra-pure water. The absorption coefficient, a, is calculated by a = 2.303A/L, where L is the pathlength of the cuvette [m], and the factor 2.303 converts log10 to loge. The output of the calculation is a continuous spectrum of a. The cDOM a spectra are used to determine the exponential slope value for specific wavelength ranges, S by fitting the data between min and max wavelength to an exponential function. We provide cDOM absorption coefficients for the wavelengths 254, 260, 350, 375, 400, 412, 440, 443 nm [1/m] and Slope values for three different UV, VIS, wavelength ranges: 275 to 295 nm, 350 to 400 nm, 300 to 500 nm [1/m]. All data were carried out by scientists from Arctic and Antarctic Research Institute and Saint Petersburg State University of Russia during "Yamal-Arctic" expeditions in 2012-2013, RFBR project No 14-04-10065 in 2014, No 14-05-00787 in 2016.

Near-UV observation of exoplanet HAT-P-16b

please provide abstract

Nitrate limitation and ocean acidification interact with UV-B to reduce photosynthetic performance in the diatom

It has been proposed that ocean acidification (OA) will interact with other environmental factors to influence the overall impact of global change on biological systems. Accordingly we investigated the influence of nitrogen limitation and OA on the physiology of diatoms by growing the diatom Phaeodactylum tricornutum Bohlin under elevated (1000 µatm; high CO2- HC) or ambient (390 µatm; low CO2-LC) levels of CO2 with replete (110 µmol/L; high nitrate-HN) or reduced (10 ?mol/L; low nitrate-LN) levels of NO3- and subjecting the cells to solar radiation with or without UV irradiance to determine their susceptibility to UV radiation (UVR, 280-400 nm). Our results indicate that OA and UVB induced significantly higher inhibition of both the photosynthetic rate and quantum yield under LN than under HN conditions. UVA or/and UVB increased the cells' non-photochemical quenching (NPQ) regardless of the CO2 levels. Under LN and OA conditions, activity of superoxide dismutase and catalase activities were enhanced, along with the highest sensitivity to UVB and the lowest ratio of repair to damage of PSII. HC-grown cells showed a faster recovery rate of yield under HN but not under LN conditions. We conclude therefore that nutrient limitation makes cells more prone to the deleterious effects of UV radiation and that HC conditions (ocean acidification) exacerbate this effect. The finding that nitrate limitation and ocean acidification interact with UV-B to reduce photosynthetic performance of the diatom P. tricornutum implies that ocean primary production and the marine biological C pump will be affected by OA under multiple stressors.

Ocean acidification mediates photosynthetic response to UV radiation and temperature increase in the diatom Phaeodactylum tricornutum

Increasing atmospheric CO2 concentration is responsible for progressive ocean acidification, ocean warming as well as decreased thickness of upper mixing layer (UML), thus exposing phytoplankton cells not only to lower pH and higher temperatures but also to higher levels of solar UV radiation. In order to evaluate the combined effects of ocean acidification, UV radiation and temperature, we used the diatom Phaeodactylum tricornutum as a model organism and examined its physiological performance after grown under two CO2 concentrations (390 and 1000 µatm) for more than 20 generations. Compared to the ambient CO2 level (390 µatm), growth at the elevated CO2 concentration increased non-photochemical quenching (NPQ) of cells and partially counteracted the harm to PS II (photosystem II) caused by UV-A and UV-B. Such an effect was less pronounced under increased temperature levels. The ratio of repair to UV-B induced damage decreased with increased NPQ, reflecting induction of NPQ when repair dropped behind the damage, and it was higher under the ocean acidification condition, showing that the increased pCO2 and lowered pH counteracted UV-B induced harm. As for photosynthetic carbon fixation rate which increased with increasing temperature from 15 to 25 °C, the elevated CO2 and temperature levels synergistically interacted to reduce the inhibition caused by UV-B and thus increase the carbon fixation.

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).