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  • An unreplicated, six-level dose-response experiment was conducted using 650 L incubation tanks (minicosms) adjusted to fugacity of carbon dioxide (fCO2) from 343 to 11641 uatm. The minicosms were filled with near-shore water from Prydz Bay, East Antarctica and the protistan composition and abundance was determined by microscopy analysis of samples collected during the 18 day incubation. Abundant taxa with low variance were examined separately, but rare taxa with high variance were combined into functional groups (descriptions below). Cluster analyses and ordinations were performed on Bray-Curtis resemblance matrixes formed from square-root transformated abundance data. This transformation was assessed as appropriate for reducing the influence of abundance species, as judged from a one-to-one relationship between observed dissimilarities and ordination distances (ie. Shepard diagram, not shown). The Bray-Curtis metric was used as it is recommended for ecological data due to its treatment of joint absences (ie. these do not contribute towards similarity), and giving more weight to abundant taxa rather than rare taxa. The data days 1 to 8 and then days 8 to 18 were analysed separately to distinguish community structure in the acclimation period and in the exponential growth phase during the incubation period of the experiment. Hierarchical agglomerative cluster analyses, based on the Bray-Curtis resemblance matrix, was performed using group-average linkage. Significantly different clusters of samples were determined using SIMPROF (similarity profile permutations method) with an alpha value of 0.05 and based on 1000 permutations. An unconstrained ordination by non-metric multidimensional scaling (nMDS) was performed on the resemblance matrix with a primary (`weak') treatment of ties. This was repeated over 50 random starts to ensure a globally optimal solution according to . Clusters are displayed in the nMDS using colour. Weighted average of sample scores are shown in the nMDS to show the approximate contribution of each species to each sample. The assumption of a linear trend for predictors within the ordination was checked for each covariate, and in all instances was found to be justified. A constrained canonical analysis of principal coordinates (CAP) was conducted according to the Vegan protocol using the Bray-Curtis resemblance matrix. This analysis was used to assess the significance of the environmental covariates, or constraints, in determining the microbial community structure. Unlike the nMDS ordination, the CAP analysis uses the resemblance matrix to partition the total variance in the community composition into unconstrained and constrained components, with the latter comprising only the variation that can be attributed to the constraining variables, fCO2, Si, P and NOx. Random reassignment of sample resemblance was performed over 199 permutations to compute the pseudo-F statistic as a measure of significance of each environmental constraint in the structural change of the microbial community. A forward selection strategy was used to choose a minimum subset of significant constraints that still account for the majority of the variation within the microbial community. All analysis were performed using R v1.0.136 and the add-on package vegan v2.4-2. Protistan taxa and functional group descriptions and abbreviations: Autotrophic Dinoflagellate (AD) - including Gymnodinium sp., Heterocapsa and other unidentified autotrophic dinoflagellates Bicosta antennigera (Ba) Chaetoceros (Cha) - mainly Chaetoceros castracanei and Chaetoceros tortissimus but also other Chaetoceros present including C. aequatorialis var antarcticus, C. cf. criophilus, C. curvisetus, C. dichaeta, C. flexuosus, C. neogracilis, C. simplex Choanoflagellates (except Bicosta) (Cho) - mainly Diaphanoeca multiannulata but also Parvicorbicula circularis and Parvicorbicula socialis present in low numbers Ciliates (Cil) - mostly cf. Strombidium but other ciliates also present Discoid Centric Diatoms greater than 40 microns (DC.l) - unidentified centrics of the genera Thalassiosira, Landeria, Stellarima or similar Discoid Centric Diatoms 20 to 40 microns (DC.m) - unidentified centrics of the genera Thalassiosira, Landeria, Stellarima or similar Discoid Centric Diatoms less than 20 microns (DC.s) - unidentified centrics of the genera Thalassiosira Euglenoid (Eu) - unidentified Fragilariopsis greater than 20 microns (F.l) - mainly Fragilariopsis cylindrus, some Fragilariopsis kerguelensis and potentially some Fragilariopsis curta present in very low numbers Fragilariopsis less than 20 microns (F.s) - mainly Fragilariopsis cylindrus, and potentially some Fragilariopsis curta present in very low numbers Heterotrophic Dinoflagellates (HD) - including Gyrodinium glaciale, Gyrodinium lachryma, other Gyrodinium sp., Protoperidinium cf. antarcticum and other unidentified heterotrophic dinoflagellates Landeria annulata (La) Other Centric Diatoms (OC) - Corethronb pennatum, Dactyliosolen tenuijuntus, Eucampia antarctica var recta, Rhizosolenia imbricata and other Rhizosolenia sp. Odontella (Od) - Odontella weissflogii and Odontella litigiosa Other Flagellates (OF) - Dictyocha speculum, Chrysochromulina sp., unknown haptophyte, Phaeocystis antarctica (flagellate and gamete forms), Mantoniella sp., Pryaminmonas gelidicola, Triparma columaceae, Triparma laevis subsp ramispina, Geminigera sp., Bodo sp., Leuocryptos sp., Polytoma sp., cf. Protaspis, Telonema antarctica, Thaumatomastix sp. and other unidentified nano- and picoplankton Other Pennate Diatoms (OP) - Entomonei kjellmanii var kjellmanii, Navicula gelida var parvula, Nitzschia longissima, other Nitzschia sp., Plagiotropus gaussi, Pseudonitzschia prolongatoides, Synedropsis sp. Phaeocystis antarctica (Pa) - colonial form only Proboscia truncata (Pro) Pseudonitzschia subcurvata (Ps) Pseudonitzschia turgiduloies (Pt) Stellarima microtrias (Sm) Thalassiosira antarctica (Ta) Thalassiosira ritscheri (Tr) *.se = standard error for mean cell per L estimate ie. Tr.se = standard error for the mean cells per L for Thalassiosira ritscheri based on individual FOV estimates as described in methods above.

  • Experimental Set-up: An unreplicated, 6-level, dose-response experiment was conducted on a natural microbial community over a range of pCO2 levels (343, 506, 634, 953, 1140 and 1641 micro atm). Seawater was collected on the 19th November 2014 approximately 1 km offshore from Davis Station, Antarctica (68 degrees 35' S, 77 degrees 58' E) from an area of ice-free water amongst broken fast-ice. The seawater was collected using a thoroughly rinsed 720L Bambi bucket slung beneath a helicopter and transferred into a 7000 L polypropalene reservoir tank. Six 650 L polyethene tanks (minicosms), located in a temperature-controlled shipping container, were immediately filled via teflon lined house via gravity with an in-line 200 micron Arkal filter to exclude metazooplankton. The minicosms were simultaneously filled to ensure they contained the same starting community. The ambient water temperature at time of collection was -1.0 degrees C and the minicosms were maintained at a temperature of 0 degrees C plus or minus 0.5 degrees C. At the centre of each minicosm there was an auger shielded for much of its length by a tube of polythene. This auger was rotated at 15 rpm to gently mix the contents of the tanks. Each minicosm tank was covered with an acrylic air-tight lid to prevent pCO2 off-gasing outside of the minicosm headspace. The minicosm experiment was conducted between the 19th November and the 7th December 2014. Initially, the contents of the tanks were given a day to equibrate to the minicosms. This was followed by a five day acclimation period to increasing pCO2 at low light (0.8 plus or minus 0.2 micro mol m-1 s-1), allowing cell physiology to acclimated to the pCO2 increase (days 1-5). During this period the pCO2 was progressively adjusted over five days to the target level for each tank (343 - 1641 micro atm). Thereafter pCO2 was adjusted daily to maintain the pCO2 level in each treatment (see carbonate chemistry section below). Following acclimation to the various pCO2 treatments light was progressively adjusted to 89 plus or minus 16 micro mol m-2 s-1 at a 19 h light:5 h dark cycle. The community was incubated and allowed to grow for a further 10 days (days 8-18) with target pCO2 adjusted back to target each day (see carbonate chemistry section below). For a more detailed description of minicosm set-up, lighting and carbonate chemistry see; Davidson, A. T., McKinlay, J., Westwood, K., Thomson, P. G., van den Enden, R., de Salas, M., Wright, S., Johnson, R., and Berry, K.:Enhanced CO2 concentrations change the structure of Antarctic marine microbial communities, Mar. Ecol. Prog. Ser., 552, 93-113, 2016. Deppeler, S. L., Petrou, K., Westwood, K., Pearce, I., Pascoe, P., Schulz, K. G., and Davidson, A. T.: Ocean acidification effects on productivity in a coastal Antarctic marine microbial community, Biogeosciences, 2017. Light microscopy sampling and analysis: Samples from each minicosm were collected on days 1, 3, 5, 8, 10, 12, 14, 16 and 18 for microscopic analysis to determine protistan identity and abundance. Approximately 960 mL were collected from each tank, on each day. Samples were fixed with 20 40 mL of Lugol's iodine and allowed to sediment out at 4 degrees C for greater than or equal to 4 days. Once cells had settled the supernatant was gently aspirated till approximately 200 mL remained. This was transferred to a 250 mL measuring cylinder, again allowed to settle (as above), and the supernatant gently aspirated. The remaining 20 mL. This final 20 mL was transferred into a 30 mL amber glass bottle. All samples were stored and transported at 4 degrees C to the Australian Antarctic Division, Hobart, Australia for analysis. Lugols-fixed and sedimented samples were analysed by light microscopy between July 2015 and February 2017. Between 2 to 10 mL (depending on cell-density) of lugols-concentrated samples was placed into a 10 mL Utermohl cylinder (Hydro-Bios, Keil) and the cells allowed to settle overnight. Due to the large variation in size and taxa, a stratified counting procedure was employed to ensure both accurate identification of small cells and representative counts of larger cells. All cells greater than 20 microns were identified and counted at 20x magnification; those less than 20 microns at 40x magnification. For larger cells (greater than 20 microns), 20 randomly chosen fields of view (FOV) at 3.66 x 106 microns2 counted to gain an average cells per L. For smaller cells (less than 20 microns), 20 randomly chosen FOVs at 2.51 x 105 microns2 were counted. Counts were conducted on an Olympus IX 81 microscope with Nomarski interference optics. Identifications were determined using (Scott and Marchant, 2005) and FESEM images. Autotrophic protists were distinguished from heterotrophs via the presence of chloroplasts and based on their taxonomic identity. Electron microscopy sampling and analysis: A further 1 L was taken on days 0, 6, 13 and 18 for analysis by Field Emission Scanning Electron Microscope (FESEM). 25 These samples were concentrated to 5 mL by filtration over a 0.8 micron polycarbonate filter. Cells were resuspended, the concentrate transferred to a glass vial and fixed to a final concentration of 1% EM-grade gluteraldehyde (ProSciTech Pty Ltd). All samples were stored and transported at 4 degrees C to the Australian Antarctic Division, Hobart, Australia for analysis. Gluteraldehyde-fixed samples were prepared for FESEM imaging using a modified polylysine technique (Marchant and Thomas, 30 1983). In brief, a few drops of gluteraldehyde-fixed sample were placed on polylysine coated cover slips and post-fixed with OsO4 (4%) vapour for 30 min, allowing cells to settle onto the coverslips. The coverslips were then rinsed in distilled water and dehydrated through a graded ethanol series ending with emersion in 100% dry acetone before being critically point dried in a Tousimis Autosamdri-815 Critical Point Drier. The coverslips were mounted onto 12.5 mm diameter aluminium stubs and sputter-coated with 7 nm of platinum/palladium in a Cressington 208HRD coater. Imaging of stubs was conducted by JEOL JSM6701F FESEM and protists identified using (Scott and Marchant, 2005). All units are in cells per L estimates from individual field of view counts (FOV) Protistan taxa and functional group descriptions and abbreviations: Autotrophic Dinoflagellate (AD) - including Gymnodinium sp., Heterocapsa and other unidentified autotrophic dinoflagellates Bicosta antennigera (Ba) Chaetoceros (Cha) - mainly Chaetoceros castracanei and Chaetoceros tortissimus but also other Chaetoceros present including C. aequatorialis var antarcticus, C. cf. criophilus, C. curvisetus, C. dichaeta, C. flexuosus, C. neogracilis, C. simplex Choanoflagellates (except Bicosta) (Cho) - mainly Diaphanoeca multiannulata but also Parvicorbicula circularis and Parvicorbicula socialis present in low numbers Ciliates (Cil) - mostly cf. Strombidium but other ciliates also present Discoid Centric Diatoms greater than 40 microns (DC.l) - unidentified centrics of the genera Thalassiosira, Landeria, Stellarima or similar Discoid Centric Diatoms 20 to 40 microns (DC.m) - unidentified centrics of the genera Thalassiosira, Landeria, Stellarima or similar Discoid Centric Diatoms less than 20 microns (DC.s) - unidentified centrics of the genera Thalassiosira Euglenoid (Eu) - unidentified Fragilariopsis greater than 20 microns (F.l) - mainly Fragilariopsis cylindrus, some Fragilariopsis kerguelensis and potentially some Fragilariopsis curta present in very low numbers Fragilariopsis less than 20 microns (F.s) - mainly Fragilariopsis cylindrus, and potentially some Fragilariopsis curta present in very low numbers Heterotrophic Dinoflagellates (HD) - including Gyrodinium glaciale, Gyrodinium lachryma, other Gyrodinium sp., Protoperidinium cf. antarcticum and other unidentified heterotrophic dinoflagellates Landeria annulata (La) Other Centric Diatoms (OC) - Corethronb pennatum, Dactyliosolen tenuijuntus, Eucampia antarctica var recta, Rhizosolenia imbricata and other Rhizosolenia sp. Odontella (Od) - Odontella weissflogii and Odontella litigiosa Other Flagellates (OF) - Dictyocha speculum, Chrysochromulina sp., unknown haptophyte, Phaeocystis antarctica (flagellate and gamete forms), Mantoniella sp., Pryaminmonas gelidicola, Triparma columaceae, Triparma laevis subsp ramispina, Geminigera sp., Bodo sp., Leuocryptos sp., Polytoma sp., cf. Protaspis, Telonema antarctica, Thaumatomastix sp. and other unidentified nano- and picoplankton Other Pennate Diatoms (OP) - Entomonei kjellmanii var kjellmanii, Navicula gelida var parvula, Nitzschia longissima, other Nitzschia sp., Plagiotropus gaussi, Pseudonitzschia prolongatoides, Synedropsis sp. Phaeocystis antarctica (Pa) - colonial form only Proboscia truncata (Pro) Pseudonitzschia subcurvata (Ps) Pseudonitzschia turgiduloies (Pt) Stellarima microtrias (Sm) Thalassiosira antarctica (Ta) Thalassiosira ritscheri (Tr) *.se = standard error for mean cell per L estimate ie. Tr.se = standard error for the mean cells per L for Thalassiosira ritscheri based on individual FOV estimates as described in methods above. Davis Station Antarctica Experiment conducted between 19th November and 7th December 2014.

  • The absolute abundances (cells per ml) of 22 hard-shelled phytoplankon taxa (comprised of species, genera or higher taxonomic groups) estimated from Scanning Electron Microscope survey of 52 samples collected through 11 austral spring-summers (2002/3 to 2012/13) (part of the L' Astrolabe collection) from the seasonal ice zone of the Southern Ocean (between latitude 62 and 64.4 degrees south, and longitude 135.8 and 150 degrees east) also included are environmental covariables for each sample: three constructed SAM indices, SST, Salinity, NOx, PO4, SiO4, and the sampling date, time, and location. Fifty-two surface-water samples were collected from the seasonal ice zone (SIZ) of the Southern Ocean (SO) across 11 consecutive austral spring-summers from 2002/03 to 2012/13. The samples were collected aboard the French re-supply vessel MV L’Astrolabe during resupply voyages between Hobart, Tasmania, and Dumont d’Urville, Antarctica between the 20th October and the 1st March. Most samples were collected from ice-free water, although some were collected south of the receding ice-edge. The sampled area was in the high latitude SO (Figure 1b) in the south-east corner of the Australian Antarctic Basin, spanning 270 km of latitude between 62°S and 64.5°S, and 625km of longitude between 136°E and 148°E. The area lies greater than 100 km north of the Antarctic continental shelf, in waters greater than 3,000 m depth. Samples were obtained from the clean seawater line of the re-supply ship from around 3 m depth. Each sample represented 250 ml of seawater filtered through a 25 mm diameter polycarbonate-membrane filter with 0.8 µm pores (Poretics). The filter was then rinsed with two additions of approximately 2 ml of MilliQ water to remove salt, then air dried and stored in a sealed container containing silica gel desiccant. Samples were prepared for scanning electron microscope (SEM) survey by mounting each filter onto metal stubs and sputter coating with 15 nm gold or platinum. Only organisms possessing hard siliceous or calcareous shells were sufficiently well preserved through the sample preparation technique that they could be identified by SEM, and included diatoms, coccolithophores, silicoflagellates, Pterosperma, parmales, radiolarians, and armoured dinoflagellates. The composition and abundance the phytoplankton community of each sample was determined using a JEOL JSM 840 Field Emission SEM. Cell numbers for each phytoplankton taxon were counted in randomly selected digital images of SEM fields taken at x400 magnification (Figure 2). Each image represented an area of 301 x 227 µm (0.068 mm2) of each sample filter, which was captured at a resolution 8.5 pixels/µm. A minimum of three SEM fields were assessed for each sample, with more fields assessed when cell densities were lower. On average, 387 cells were counted for each sample. Taxa were classified with the aid of Scott and Marchant (2005), Tomas (1997), and expert opinion. Cell counts per image were converted to volume-specific abundances (cells/ml) by dividing by 0.0348 ml of sea-water represented by each image. A total of 19,943 phytoplankton organisms were identified and counted: 18,872 diatoms, 322 Parmales, 173 coccolithophores, 81 silicoflagellates, and 45 Petasaria. A total of 48 phytoplankton taxa were identified, many to species level. Because the diatoms Fragilariopsis curta (Van Heurck) Hustedt and F. cylindrus (Grunow ex Cleve) Helmcke and Krieger could not be reliably discriminated at the microscope resolution employed, they were pooled into a single taxa-group. Other taxa were also grouped, namely Nitzschia acicularis (Kützing) W.Smith with N. decipiens Hustedt to a single group, and discoid centric diatoms of the genera Thalassiosira, Actinocyclus and Porosira to another. Rare species, with maximum relative abundance less than 2%, were removed from the data prior to analysis as they were not considered to be sufficiently abundant to warrant further analysis (Webb and Bryson 1972, Taylor and Sjunneskog 2002, Swilo et al. 2016). After pooling taxa and deleting rare taxa, twenty-two taxa and taxonomic-groups (species, groups of species and families) remained to describe the composition of the phytoplankton community. Phytoplankton abundances were related to a range of environmental covariates available at the time of sampling. These included the SAM, sea surface temperature (SST), salinity, time since sea ice cover (DaysSinceSeaIce, defined below), minimum latitude of sea ice in the preceding winter, latitude and longitude of sample collection, the days since 1st October that a sample was collected (DaysAfter1Oct), the year of sampling (year, being the year that each spring-summer sampling season began), the time of day that a sample was collected, and macro-nutrient concentrations: phosphate (PO4), silicate (SiO4) and nitrate + nitrite (hereafter nitrate, NOx). Water samples for dissolved macro-nutrients were collected, frozen on ship, and later analysed at CSIRO in Hobart using standard spectrophotometric methods (Hydes et al. 2010). Daily estimates of SAM were obtained from the US NWS Climate Prediction Center's website and are the NOAA Antarctic Oscillation Index values based on 700-hPa geopotential height anomalies (NOAA 2017). The variable DaysSinceSeaIce was defined as the time since sea ice had melted to 20% cover (after Wright et al. 2010) as determined from daily Special Sensor Microwave/Imager (SSM/I) sea ice concentration data distributed by the University of Hamburg (Spreen et al. 2008). To examine the lag in the expression of the SAM on phytoplankton community composition, two response surfaces were constructed relating the variance in phytoplankton community composition explained by the SAM to the temporal positioning of the period over which daily SAM was averaged. These were derived by evaluating separate CAP analyses (described below) based on daily SAM averaged across a range of days {1, 3, 5, … 365} centred on (i) each calendar day individually (1 Jan – 31 Dec) through the year associated with each sample; and (ii) lagged from 1 to 365 days prior to each sample collection date. Empirical identification of the time between variation in the SAM and the manifestation of this variation in the phytoplankton community structure revealed three modes (maxima) in phytoplankton community composition explained by the SAM. The first was an autumn seasonal SAM mode, which was determined to be the average of 57 daily SAM estimates centred on the preceding 11th March (11th Feb – 8th Apr). This mode explained up to 13.3% of the variance in taxonomic composition (SAM autumn). The second was a spring seasonal mode, which was determined to be the average of 75 daily SAM estimates centred on 25th October (20th Sep – 3rd Dec). This mode explained up to 10.3% of variance in taxonomic composition (SAM spring). Unlike the other modes that were related to the time of year, the third mode was timed relative to the date of sample collection for each sample and comprised the average of the 97 daily SAM estimates centred 102 days prior to each sample collection date. It explained 9.9% of the variance in phytoplankton composition (SAM prior). The mean standard error on estimates of SAM were 0.14 SAM index units for SAM autumn and SAM spring, and 0.13 for SAM prior. Note that SAM prior and SAM spring temporally overlapped to varying extents across the 52 samples and so were not entirely independent covariates: for example, a sample collected in the summer had previous days contributing to both SAM prior and SAM spring.

  • The BROKE-West survey was conducted from 30 degrees E and 80 degrees E between January and March 2006. It consisted of 1 east-west transect at the northernmost limit of the survey between 60 degrees S and 62 degrees S between the 10 and 19 of January, followed by 11 meridional transects separated by 5 degrees of longitude and extending from approximately 62 degrees S to the Antarctic continental shelf between the 19 January and 3 March. This dataset details research undertaken to determine the identity, composition and abundance of protists in the survey area. Some explanations for terms used in the dataset are as follows: 1. Group is the taxonomic Phylum, Class and occasionally Order to which the taxa belongs. The abbreviations are: a. Diatom - Diatomophyceae/Bacillariophyceae. These are subdivided into the taxonomic Orders Centrales (centric) and Pennales (pennate) b. Chryso - Chrysophyceae c. Dino - Dinophyceae d. Eugleno - Euglenophyceae e. Hapto - Haptophyceae f. Prasino - Prasinophyceae g. Silico - Dictyochales (silicoflagellates) h. Choano - Craspedophyceae /Choanoflagellida i. Ciliate - Phylum Ciliophora j. Tintinnid - Phylum Ciliophora , Order Spirotrichea, Class Tintinnida k. Protozoa - refers to grouped rare taxa belonging to a number of Classes 2. Autotroph/Heterotroph refers to the trophic status of the taxa, indicating whether they are autotrophic (plant) or heterotrophic (animal). 3. CTD Station Number refers to the station at which samples were collected. Type indicates whether the samples were collected at the surface "surf" or at the point at which there was maximum chlorophyll fluorescence detected from the CTD flurometer trace "ChlMax". The data are all cell concentration numbers. For more information, see the other metadata records related to ASAC project 40 (ASAC_40), ASAC project 2655 (ASAC_2655) and ASAC project 2679 (ASAC_2679).

  • Metadata record for data from ASAC Project 2720 See the link below for public details on this project. The overall objective is to characterize Southern Ocean marine ecosystems, their influence on carbon dioxide exchange with the atmosphere and the deep ocean, and their sensitivity to past and future global change including climate warming, ocean stratification, and ocean acidification from anthropogenic CO2 emissions. In particular we plan to take advantage of naturally-occurring, persistent, zonal variations in Southern Ocean primary production and biomass in the Australian Sector to investigate the effects of iron addition from natural sources, and CO2 addition from anthropogenic sources, on Southern Ocean plankton communities of differing initial structure and composition. These samples were collected on the SAZ-SENSE scientific voyage of the Australian Antarctic Program (Voyage 3 of the Aurora Australis, 2006-2007 season). SAZ-SENSE is a study of the sensitivity of Sub-Antarctic Zone waters to global change. A 32-day oceanographic voyage onboard Australia's ice-breaker Aurora Australis was undertaken in mid-summer (Jan 17 - Feb. 20) 2007 to examine microbial ecosystem structure and biogeochemical processes in SAZ waters west and east of Tasmania, and also in the Polar Frontal Zone south of the SAZ. The voyage brought together research teams from Australasia, Europe, and North America, and was led by the ACE CRC, CSIRO Marine and Atmospheric Research, and the Australian Antarctic Division. The overall goal is to understand the controls on Sub-Antarctic Zone productivity and carbon cycling, and to assess their sensitivity to climate change. The strategy is to compare low productivity waters west of Tasmania (areas with little phytoplankton) with higher productivity waters to the east, with a focus on the role of iron as a limiting micro-nutrient. The study also seeks to examine the effect of rising CO2 levels on phytoplankton - both via regional intercomparisons and incubation experiments. The data described in this metadata record are for seawater samples collected for HPLC pigments, microscopy and flow cytometry. Samples were collected either by Niskin Bottles (on a CTD), from the ocean surface with a bucket, or via a clean seawater line (at a depth of 7 metres), directly into the onboard laboratories. Samples for microscopy were examined either with an electron microscope, or a light microscope (lugol samples). The data are presented in an excel spreadsheet, available for download at the URL given below. The 'Notes' worksheet provides further information about the data contained in the spreadsheet, including a description of column headings, units used, etc. The fields used in this dataset are: Tube Label Site CTD Niskin bottle Depth (m) Date (UT) Start Time (UT) Stop Time (UT) Latitude Longitude Lugols Glutaraldehyde fixed samples Flow Coccolithophorids Volume HPLC Volume Turner Fluorometer reading (PAR) Photosynthetically Active Radiation Temperature (degrees C) Comment

  • Antarctic sediments and sea-ice are important regulators in global biogeochemical and atmospheric cycles. These ecosystems contain a diverse range of bacteria whose biogeochemical roles remains largely unknown and which inhabit what are continually low temperature habitats. An integrated molecular and chemical approach will be used to investigate the coupling of microbial biogeochemical processes with community structure and cold adaptation within coastal Antarctic marine sediments and within sea-ice. Overall the project expects to make an important contribution to our understanding of biological processes within low temperature habitats. DATA SET ORGANISATION: The dataset is organised on the basis of publication and is organised on the basis of the following sections: 1. SEDIMENT SAMPLES and ISOLATES Samples collected are described in terms of location, type and where data were obtained chemical features. The designation, source, media used for cultivation and isolation and availability of sediment and other related isolates are provided. Samples included are from the following locations: Clear Lake, Pendant Lake, Scale Lake, Ace Lake, Burton Lake, Ekho Lake, Organic Lake, Deep lake and Taynaya Bay (Burke Basin), Vestfold Hills region; and the Mertz Glacier Polynya region. 2. BIOMASS and ENZYME ACTIVITY DATA Biomass, numbers and extracellular enzyme activity data are provided for Bacteria and Archaea populations from Mertz Glacier Polynya shelf sediments. 3. FATTY ACID and TETRAETHER LIPID DATA Phospholipid and tetraether lipid data are provided for Mertz Glacier Polynya shelf sediments. Whole cell fatty acid data are provided for various bacterial isolates described officially as new genera or species. 4. RNA HYBRIDISATION DATA RNA hybridisation data for Mertz Glacier Polynya sediment samples is provided, including data for oligonucleotide probes specifc for total Bacteria, Archaea, the Desulfosarcina group (class Deltaproteobacteria, sulfate reducing bacterial clade), phylum Planctomycetes, phylum Bacteroidetes (Cytophaga-Flavobacterium-Bacteroides), class Gammaproteobacteria, sulfur-oxidizing and related bacteria (a subset of class Gammaproteobacteria) and Eukaryota. 5. PHYLOGENETIC DATA 16S rRNA gene sequence data are indicated including aligned datasets for three clone libraries derived from the Mertz Glacier Polynya including GenBank accession numbers. Sequence accession numbers are provided for Vestfold Hills lake sediment samples. In addition GenBank numbers are provided for denaturing gradient gel electrophoresis band sequence data from Mertz Glacier Polynya shelf sediment. Other forms of this DGGE data (banding profile analysis) are available in reference Bowman et al. 2003 (AAD ref 10971).