The Southern Ocean is one the most significant regions on earth for regulating the build up of anthropogenic CO2 in the atmosphere, and the capacity for carbon uptake in the region could be altered by climate change. The project aims to establish a time series of anthropogenic carbon accumulation. The work will be used to identify processes regulating the CO2 uptake and to test models that predict future uptake. These data were collected on the VMS voyage of the Aurora Australis in the 2010-2011 field season. Data include pH, carbon dioxide, alkalinity and spectrometer data.

Metadata record for data from ASAC Project 2592 See the link below for public details on this project. The Southern Ocean is one the most significant regions on earth for regulating the build up of anthropogenic carbon in the atmosphere, and the capacity for carbon uptake in the region could be altered by climate change. The project aims to use repeat ocean sections to detect anthropogenic carbon storage, identify key processes regulating the amount of storage, and to test models that predict future uptake. The data are broken down by season and voyage, and a word document providing further details about the project is also available as part of the download file.

This dataset contains Ffilter samples of known volume of sea water for - PIC (Particulate Inorganic Carbon) - POC (Particulate Organic Carbon) - BGSi (BioGenic Silicon) The dataset also contains transmissometer data. The transmissometer is an attempt at developing a correlation between the PIC filter samples and the transmissometer readings. This is development of methods. The data collection times are logged in the file and filter log sheets.

Water samples of 1 to 2L from Niskin bottles filled close to the surface, mid mixed layer depth and bottom of the mixed layer were drawn cleanly through a 210um mesh to exclude zooplankton. All samples were filtered as two size fractions, 1.2 to 20um (larger particles excluded by 20um Nitex mesh) and a separate 1.2 to 210um total sample. The filters were 1.2um silver membranes (Sterlitech) 13mm diameter. The samples were preserved by drying at 60C in a dedicated clean oven. Prior to encapsulation, a 5mm diameter subsample was taken for biogenic silica analysis, which is delayed until there has been evaluation of the particle data from the flow cam and UVP. Samples were encapsulated in silver (Sercon sc0037) after acidification and drying. The decarbonated encapsulated POC samples were analysed by elemental analyser at the CSL UTAS by Dr Thomas Rodemann (EA TCD 960C, single point standardisation every 12 samples).  EA detection limit 0.001umol POC. POC and PON are presented as molar units. Blanks were process blanks (seawater) and 7% of the average for the combined data n=177. 1sd=0.12uM. The ctd casts were all given the prefix K, so K001, K002 etc. Not all stations were sampled due to budget constraints. Niskin is the Niskin bottle number.

Overview of the project and objectives: To investigate whether the Nitrogen - Silicon - Carbon biogeochemical system functions in the Antarctic Marginal Ice Zone and shows spatial variability possibly induced by varying availability of Fe and other parameters in the region. This toolbox is part of project 4051 - samples were taken (1) on the same sea-ice site or very close than the one used for Trace Metal sampling; (2) via Trace Metal Rosette TMR; (3) via Conductivity Temperature and Depth CTD Rosette. It is also part of project 4073 since some intercalibration studies were conducted in collaboration with the primary production team. Three main tools were used which can be either independently or intricately studied. For this reason the complete set of sampling done for this stable isotope toolbox is summarized in one excel file which is duplicated and attached to three child metadata records. Same reasoning for raw data acquired on boar and on field information. This parent metadata record has thus three child metadata records. Each of the child metadata files explain individually the different approaches which were treated together by the same team to resolve the main question of sea-ice biogeochemical system functioning via the use of stable isotope ratio tools. The details of each are in the respective metadata records. The data are attached to this metadata record. METADATA FILES are: - 13C, 15N, 30Si in-situ incubation experiments during SIPEX 2 - Nitrogen and oxygen isotopic composition of nitrate during SIPEX 2 - Delta13C signal of brassicasterol and cholesterol in the Antarctic Sea-ice / Is there particulate barium in sea-ice?

This dataset is a collection of marine environmental data layers suitable for use in Southern Ocean species distribution modelling. All environmental layers have been generated at a spatial resolution of 0.1 degrees, covering the Southern Ocean extent (80 degrees S - 45 degrees S, -180 - 180 degrees). The layers include information relating to bathymetry, sea ice, ocean currents, primary production, particulate organic carbon, and other oceanographic data. An example of reading and using these data layers in R can be found at https://australianantarcticdivision.github.io/blueant/articles/SO_SDM_data.html. The following layers are provided: 1. Layer name: depth Description: Bathymetry. Downloaded from GEBCO 2014 (0.0083 degrees = 30sec arcmin resolution) and set at resolution 0.1 degrees. Then completed with the bathymetry layer manually corrected and provided in Fabri-Ruiz et al. (2017) Value range: -8038.722 - 0 Units: m Source: This study. Derived from GEBCO URL: https://www.gebco.net/data_and_products/gridded_bathymetry_data/ Citation: Fabri-Ruiz S, Saucede T, Danis B and David B (2017). Southern Ocean Echinoids database_An updated version of Antarctic, Sub-Antarctic and cold temperate echinoid database. ZooKeys, (697), 1. 2. Layer name: geomorphology Description: Last update on biodiversity.aq portal. Derived from O'Brien et al. (2009) seafloor geomorphic feature dataset. Mapping based on GEBCO contours, ETOPO2, seismic lines). 27 categories Value range: 27 categories Units: categorical Source: This study. Derived from Australian Antarctic Data Centre URL: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data Citation: O'Brien, P.E., Post, A.L., and Romeyn, R. (2009) Antarctic-wide geomorphology as an aid to habitat mapping and locating vulnerable marine ecosystems. CCAMLR VME Workshop 2009. Document WS-VME-09/10 3. Layer name: sediments Description: Sediment features Value range: 14 categories Units: categorical Source: Griffiths 2014 (unpublished) URL: http://share.biodiversity.aq/GIS/antarctic/ 4. Layer name: slope Description: Seafloor slope derived from bathymetry with the terrain function of raster R package. Computation according to Horn (1981), ie option neighbor=8. The computation was done on the GEBCO bathymetry layer (0.0083 degrees resolution) and the resolution was then changed to 0.1 degrees. Unit set at degrees. Value range: 0.000252378 - 16.94809 Units: degrees Source: This study. Derived from GEBCO URL: https://www.gebco.net/data_and_products/gridded_bathymetry_data/ Citation: Horn, B.K.P., 1981. Hill shading and the reflectance map. Proceedings of the IEEE 69:14-47 5. Layer name: roughness Description: Seafloor roughness derived from bathymetry with the terrain function of raster R package. Roughness is the difference between the maximum and the minimum value of a cell and its 8 surrounding cells. The computation was done on the GEBCO bathymetry layer (0.0083 degrees resolution) and the resolution was then changed to 0.1 degrees. Value range: 0 - 5171.278 Units: unitless Source: This study. Derived from GEBCO URL: https://www.gebco.net/data_and_products/gridded_bathymetry_data/ 6. Layer name: mixed layer depth Description: Summer mixed layer depth climatology from ARGOS data. Regridded from 2-degree grid using nearest neighbour interpolation Value range: 13.79615 - 461.5424 Units: m Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data 7. Layer name: seasurface_current_speed Description: Current speed near the surface (2.5m depth), derived from the CAISOM model (Galton-Fenzi et al. 2012, based on ROMS model) Value range: 1.50E-04 - 1.7 Units: m/s Source: This study. Derived from Australian Antarctic Data Centre URL: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data Citation: see Galton-Fenzi BK, Hunter JR, Coleman R, Marsland SJ, Warner RC (2012) Modeling the basal melting and marine ice accretion of the Amery Ice Shelf. Journal of Geophysical Research: Oceans, 117, C09031. http://dx.doi.org/10.1029/2012jc008214, https://data.aad.gov.au/metadata/records/polar_environmental_data 8. Layer name: seafloor_current_speed Description: Current speed near the sea floor, derived from the CAISOM model (Galton-Fenzi et al. 2012, based on ROMS) Value range: 3.40E-04 - 0.53 Units: m/s Source: This study. Derived from Australian Antarctic Data Centre URL: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data Citation: see Galton-Fenzi BK, Hunter JR, Coleman R, Marsland SJ, Warner RC (2012) Modeling the basal melting and marine ice accretion of the Amery Ice Shelf. Journal of Geophysical Research: Oceans, 117, C09031. http://dx.doi.org/10.1029/2012jc008214, https://data.aad.gov.au/metadata/records/polar_environmental_data 9. Layer name: distance_antarctica Description: Distance to the nearest part of the Antarctic continent Value range: 0 - 3445 Units: km Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data 10. Layer name: distance_canyon Description: Distance to the axis of the nearest canyon Value range: 0 - 3117 Units: km Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data 11. Layer name: distance_max_ice_edge Description: Distance to the mean maximum winter sea ice extent (derived from daily estimates of sea ice concentration) Value range: -2614.008 - 2314.433 Units: km Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data 12. Layer name: distance_shelf Description: Distance to nearest area of seafloor of depth 500m or shallower Value range: -1296 - 1750 Units: km Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data 13. Layer name: ice_cover_max Description: Ice concentration fraction, maximum on [1957-2017] time period Value range: 0 - 1 Units: unitless Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis 14. Layer name: ice_cover_mean Description: Ice concentration fraction, mean on [1957-2017] time period Value range: 0 - 0.9708595 Units: unitless Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis 15. Layer name: ice_cover_min Description: Ice concentration fraction, minimum on [1957-2017] time period Value range: 0 - 0.8536261 Units: unitless Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis 16. Layer name: ice_cover_range Description: Ice concentration fraction, difference maximum-minimum on [1957-2017] time period Value range: 0 - 1 Units: unitless Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis 17. Layer name: ice_thickness_max Description: Ice thickness, maximum on [1957-2017] time period Value range: 0 - 3.471811 Units: m Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis 18. Layer name: ice_thickness_mean Description: Ice thickness, mean on [1957-2017] time period Value range: 0 - 1.614133 Units: m Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis 19. Layer name: ice_thickness_min Description: Ice thickness, minimum on [1957-2017] time period Value range: 0 - 0.7602701 Units: m Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis 20. Layer name: ice_thickness_range Description: Ice thickness, difference maximum-minimum on [1957-2017] time period Value range: 0 - 3.471811 Units: m Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis 21. Layer name: chla_ampli_alltime_2005_2012 Description: Chlorophyll-a concentrations obtained from MODIS satellite data. Amplitude of pixel values (difference between maximal and minimal value encountered by each pixel during all months of the period [2005-2012]) Value range: 0 - 77.15122 Units: mg/m^3 Source: https://oceandata.sci.gsfc.nasa.gov/MODIS-Aqua/Mapped/Monthly/9km/chlor_a/ URL: https://modis.gsfc.nasa.gov/data/dataprod/chlor_a.php 22. Layer name: chla_max_alltime_2005_2012 Description: Chlorophyll-a concentrations obtained from MODIS satellite data. Maximal value encountered by each pixel during all months of the period [2005-2012] Value range: 0 - 77.28562 Units: mg/m^3 Source: https://oceandata.sci.gsfc.nasa.gov/MODIS-Aqua/Mapped/Monthly/9km/chlor_a/ URL: https://modis.gsfc.nasa.gov/data/dataprod/chlor_a.php 23. Layer name: chla_mean_alltime_2005_2012 Description: Chlorophyll-a concentrations obtained from MODIS satellite data. Mean value of each pixel during all months of the period [2005-2012] Value range: 0 - 30.42691 Units: mg/m^3 Source: https://oceandata.sci.gsfc.nasa.gov/MODIS-Aqua/Mapped/Monthly/9km/chlor_a/ URL: https://modis.gsfc.nasa.gov/data/dataprod/chlor_a.php 24. Layer name: chla_min_alltime_2005_2012 Description: Chlorophyll-a concentrations obtained from MODIS satellite data. Minimal value encountered by each pixel during all months of the period [2005-2012] Value range: 0 - 29.02929 Units: mg/m^3 Source: https://oceandata.sci.gsfc.nasa.gov/MODIS-Aqua/Mapped/Monthly/9km/chlor_a/ URL: https://modis.gsfc.nasa.gov/data/dataprod/chlor_a.php 25. Layer name: chla_sd_alltime_2005_2012 Description: Chlorophyll-a concentrations obtained from MODIS satellite data. Standard deviation value of each pixel during all months of the period [2005-2012] Value range: 0 - 27.9877 Units: mg/m^3 Source: https://oceandata.sci.gsfc.nasa.gov/MODIS-Aqua/Mapped/Monthly/9km/chlor_a/ URL: https://modis.gsfc.nasa.gov/data/dataprod/chlor_a.php 26. Layer name: POC_2005_2012_ampli Description: Particulate organic carbon, model Lutz et al. (2007). Amplitude value (difference maximal and minimal value, see previous layers) all seasonal layers [2005-2012] Value range: 0 - 1.31761 Units: g/m^2/d Source: This study. Following Lutz et al. (2007) URL: https://data.aad.gov.au/metadata/records/Particulate_carbon_export_flux_layers Citation: Lutz MJ, Caldeira K, Dunbar RB and Behrenfeld MJ (2007). Seasonal rhythms of net primary production and particulate organic carbon flux to depth describe the efficiency of biological pump in the global ocean. Journal of Geophysical Research: Oceans, 112(C10). 27. Layer name: POC_2005_2012_max Description: Particulate organic carbon, model Lutz et al. (2007). Maximal value encountered on each pixel among all seasonal layers [2005-2012] Value range: 0.00332562 - 1.376601 Units: g/m^2/d Source: This study. Following Lutz et al. (2007) URL: https://data.aad.gov.au/metadata/records/Particulate_carbon_export_flux_layers Citation: Lutz MJ, Caldeira K, Dunbar RB and Behrenfeld MJ (2007). Seasonal rhythms of net primary production and particulate organic carbon flux to depth describe the efficiency of biological pump in the global ocean. Journal of Geophysical Research: Oceans, 112(C10). 28. Layer name: POC_2005_2012_mean Description: Particulate organic carbon, model Lutz et al. (2007). Mean all seasonal layers [2005-2012] Value range: 0.003184335 - 0.5031364 Units: g/m^2/d Source: This study. Following Lutz et al. (2007) URL: https://data.aad.gov.au/metadata/records/Particulate_carbon_export_flux_layers Citation: Lutz MJ, Caldeira K, Dunbar RB and Behrenfeld MJ (2007). Seasonal rhythms of net primary production and particulate organic carbon flux to depth describe the efficiency of biological pump in the global ocean. Journal of Geophysical Research: Oceans, 112(C10). 29. Layer name: POC_2005_2012_min Description: Particulate organic carbon, model Lutz et al. (2007). Minimal value encountered on each pixel among all seasonal layers [2005-2012] Value range: 0.003116508 - 0.1313119 Units: g/m^2/d Source: This study. Following Lutz et al. (2007) URL: https://data.aad.gov.au/metadata/records/Particulate_carbon_export_flux_layers Citation: Lutz MJ, Caldeira K, Dunbar RB and Behrenfeld MJ (2007). Seasonal rhythms of net primary production and particulate organic carbon flux to depth describe the efficiency of biological pump in the global ocean. Journal of Geophysical Research: Oceans, 112(C10). 30. Layer name: POC_2005_2012_sd Description: Particulate organic carbon, model Lutz et al. (2007). Standard deviation all seasonal layers [2005-2012] Value range: 3.85E-08 - 0.4417001 Units: g/m^2/d Source: This study. Following Lutz et al. (2007) URL: https://data.aad.gov.au/metadata/records/Particulate_carbon_export_flux_layers Citation: Lutz MJ, Caldeira K, Dunbar RB and Behrenfeld MJ (2007). Seasonal rhythms of net primary production and particulate organic carbon flux to depth describe the efficiency of biological pump in the global ocean. Journal of Geophysical Research: Oceans, 112(C10). 31. Layer name: seafloor_oxy_1955_2012_ampli Description: Amplitude (difference maximum-minimum) value encountered for each pixel on all month layers of seafloor oxygen concentration over [1955-2012], modified from WOCE Value range: 0.001755714 - 5.285187 Units: mL/L Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 32. Layer name: seafloor_oxy_1955_2012_max Description: Maximum value encountered for each pixel on all month layers of oxygen concentration over [1955-2012], modified from WOCE Value range: 3.059685 - 11.52433 Units: mL/L Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 33. Layer name: seafloor_oxy_1955_2012_mean Description: Mean seafloor oxygen concentration over [1955-2012] (average of all monthly layers), modified from WOCE Value range: 2.836582 - 8.858084 Units: mL/L Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 34. Layer name: seafloor_oxy_1955_2012_min Description: Minimum value encountered for each pixel on all month layers of seafloor oxygen concentration over [1955-2012], modified from WOCE Value range: 0.4315577 - 8.350794 Units: mL/L Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 35. Layer name: seafloor_oxy_1955_2012_sd Description: Standard deviation seafloor oxygen concentration over [1955-2012] (of all monthly layers), modified from WOCE Value range: 0.000427063 - 1.588707 Units: mL/L Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 36. Layer name: seafloor_sali_2005_2012_ampli Description: Amplitude (difference maximum-minimum) value encountered for each pixel on all month layers of seafloor salinity over [2005-2012], modified from WOCE Value range: 0.000801086 - 4.249901 Units: PSU Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 37. Layer name: seafloor_sali_2005_2012_max Description: Maximum value encountered for each pixel on all month layers of seafloor salinity over [2005-2012], modified from WOCE Value range: 32.90105 - 35.3997 Units: PSU Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 38. Layer name: seafloor_sali_2005_2012_mean Description: Mean seafloor salinity over [2005-2012] (average of all monthly layers), modified from WOCE Value range: 32.51107 - 35.03207 Units: PSU Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 39. Layer name: seafloor_sali_2005_2012_min Description: Minimum value encountered for each pixel on all month layers of seafloor salinity over [2005-2012], modified from WOCE Value range: 29.8904 - 34.97735 Units: PSU Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 40. Layer name: seafloor_sali_2005_2012_sd Description: Standard deviation seafloor salinity over [2005-2012] (of all monthly layers), modified from WOCE Value range: 0.000251834 - 1.36245 Units: PSU Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 41. Layer name: seafloor_temp_2005_2012_ampli Description: Amplitude (difference maximum-minimum) value encountered for each pixel on all month layers of seafloor temperature over [2005-2012], modified from WOCE Value range: 0.0086 - 8.625669 Units: degrees C Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 42. Layer name: seafloor_temp_2005_2012_max Description: Maximum value encountered for each pixel on all month layers of seafloor temperature over [2005-2012], modified from WOCE Value range: -2.021455 - 15.93171 Units: degrees C Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 43. Layer name: seafloor_temp_2005_2012_mean Description: Mean seafloor temperature over [2005-2012] (average of all monthly layers), modified from WOCE Value range: -2.085796 - 13.23161 Units: degrees C Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 44. Layer name: seafloor_temp_2005_2012_min Description: Minimum value encountered for each pixel on all month layers of seafloor temperature over [2005-2012], modified from WOCE Value range: -2.1 - 11.6431 Units: degrees C Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 45. Layer name: seafloor_temp_2005_2012_sd Description: Standard deviation seafloor temperature over [2005-2012] (of all monthly layers), modified from WOCE Value range: 0.002843571 - 2.877084 Units: degrees C Source: Derived from World Ocean Circulation Experiment 2013 URL: https://www.nodc.noaa.gov/OC5/woa13/woa13data.html 46. Layer name: extreme_event_max_chl_2005_2012_ampli Description: Amplitude (difference maximum-minimum) number of the number of extreme events calculated between 2005 and 2012 Value range: integer values 0 - 3 Units: unitless Source: derived from chlorophyll-a concentration layers 47. Layer name: extreme_event_max_chl_2005_2012_max Description: Maximum number of extreme events calculated between 2005 and 2012 Value range: integer values 0 - 5 Units: unitless Source: derived from chlorophyll-a concentration layers 48. Layer name: extreme_event_max_chl_2005_2012_mean Description: Mean of the number of extreme events calculated between 2005 and 2012 Value range: 0 - 3.875 Units: unitless Source: derived from chlorophyll-a concentration layers 49. Layer name: extreme_event_max_chl_2005_2012_min Description: Minimum number of extreme events calculated between 2005 and 2012 Value range: integer values 0 - 5 Units: unitless Source: derived from chlorophyll-a concentration layers 50. Layer name: extreme_event_min_chl_2005_2012_ampli Description: Amplitude (difference maximum-minimum) number of the number of extreme events calculated between 2005 and 2012 Value range: integer values 0 - 9 Units: unitless Source: derived from chlorophyll-a concentration layers 51. Layer name: extreme_event_min_chl_2005_2012_max Description: Maximum number of extreme events calculated between 2005 and 2012 Value range: integer values 0 - 11 Units: unitless Source: derived from chlorophyll-a concentration layers 52. Layer name: extreme_event_min_chl_2005_2012_mean Description: Mean of the number of extreme events calculated between 2005 and 2012 Value range: 0 - 11 Units: unitless Source: derived from chlorophyll-a concentration layers 53. Layer name: extreme_event_min_chl_2005_2012_min Description: Minimum number of extreme events calculated between 2005 and 2012 Value range: integer values 0 - 11 Units: unitless Source: derived from chlorophyll-a concentration layers 54. Layer name: extreme_event_min_oxy_1955_2012_nb Description: Number of extreme events (minimal seafloor oxygen concentration records) that happened between January and December of the year Value range: integer values 0 - 12 Units: per year Source: derived from seafloor oxygen concentration layers 55. Layer name: extreme_event_max_sali_2005_2012_nb Description: Number of extreme events (maximal seafloor salinity records) that happened between January and December of the year Value range: integer values 0 - 12 Units: per year Source: derived from seafloor salinity layers 56. Layer name: extreme_event_min_sali_2005_2012_nb Description: Number of extreme events (minimal seafloor salinity records) that happened between January and December of the year Value range: integer values 0 - 12 Units: per year Source: derived from seafloor salinity layers 57. Layer name: extreme_event_max_temp_2005_2012_nb Description: Number of extreme events (maximal seafloor temperature records) that happened between January and December of the year Value range: integer values 0 - 12 Units: per year Source: derived from seafloor temperature layers 58. Layer name: extreme_event_min_temp_2005_2012_nb Description: Number of extreme events (minimal seafloor temperature records) that happened between January and December of the year Value range: integer values 0 - 12 Units: per year Source: derived from seafloor temperature layers

This metadata record is the parent umbrella under which data from the 2008/09, 2013/14 and 2014/15 summer will be housed. See the child records for access to the data. Manmade CO2 has increased ocean acidity by 30% and it is projected to rise 300% by 2100. Antarctic waters will be amongst the earliest and most severely affected by this increase. Microbes are the base of the marine food chain and primary drivers of the biological pump. This project will incubate natural communities of Antarctic marine microbes in minicosms at a range of CO2 concentrations to quantify changes in their structure and function, the physiological responses that drive these changes, and provide input to models that predict effects on biogeochemical cycles and Antarctic food webs

Metadata record for data from ASAC Project 2751 See the link below for public details on this project. Public Viruses are tiny particles that cannot reproduce by themselves. To reproduce they have to parasitise a bacterial cell, or another organism. In the sea viruses infect bacteria and phytoplankton cells and can cause those cells to die and break open, thereby liberating more virus particles into the environment to re-infect more host cells. They effectively short-circuit the carbon cycle - recycling carbon to the pool of dissolved and particulate organic carbon before it can be eaten by organisms higher in the food chain. Our research will elucidate the role of viruses in the water column and sea-ice over a year. Taken from the 2008-2009 Progress Report: Project objectives: BACKGROUND Since the microbial loop was first described, a wealth of data has appeared on the species composition and interactions among bacterioplankton and Protozoa, both heterotrophic and mixotrophic, and their role in biogeochemical cycling in marine and lacustrine environments. An additional dimension to the microbial loop was discovered when high concentrations of viruses (bacteriophage) were first described from marine samples. The supposition was that infected bacteria might be lysed, and their carbon returned to the pool before it could be grazed by Protozoa, short-circuiting the microbial loop. Both heterotrophic bacteria and cyanobacteria were found to be infected by viruses and later work revealed that viruses may also attack algae and protists, but the database on the viruses of these groups is far less detailed than for bacteriophages. Viruses are now the focus of considerable attention in aquatic environments. The role of viruses is more complex than simply causing the mortality of bacteria and phytoplankters. Viruses also play a role in maintaining the clonal diversity of host communities through gene transmission (transduction), and indirectly by causing the mortality of dominant host species. Moreover, viruses can act as a potential source of food for heterotrophic and mixotrophic flagellates. Based on decay rates an ingestion of 3.3 viruses per flagellate h-1 was calculated, and experiments with fluorescently labelled microspheres demonstrated that nanoflagellates may gain significant carbon through ingesting viruses. Early studies suggested that the majority of viruses in marine waters were lytic. More recently lysogeny has been found in both marine and freshwater systems ranging up to 71% in both marine and freshwaters. Thus aquatic viruses may exist in a lysogenic condition within their hosts where they replicate and are passed on in the host's progeny during division. This condition may continue until a factor, or a combination of factors, initiates the lytic cycle. Clearly it is disadvantageous to embark on a lytic cycle when the concentration of potential hosts is low. Long term seasonal studies of viruses and their potential hosts are relatively few, and have focussed on a specific aspects, for example the abundance of lysogenic bacteria in an estuary and Lake Superior and viral control of bacterial production in the River Danube. A recent study of annual patterns of viral abundance and seasonal microbial plankton dynamics in two lakes in the French Massif Central, suggested that a weakened correlation between viruses and bacteria in the more productive of the two lakes was indicative of an increase in non-bacterial hosts as trophic status increased. We have conducted a year long study of virus dynamics in three of the saline lakes in the Vestfold Hills, our hypothesis being that they may be regarded as a proxy for the marine environment, but with the difference that top-down control is lacking in food webs that are microbially dominated. Our results revealed that virus numbers showed no clear seasonal pattern and were high in winter and summer (range 0.89 x 107 plus or minus 0.038 mL-1 to 12.017 x 107 plus or minus 1.28 mL-1). However, the lysogenic cycle was predominant in winter (up to 73% of the bacteriophage were lysogenic), while in summer the lytic cycle dominated. There was a strong negative correlation between virus numbers and photosynthetically active radiation. Viruses are subject to destruction or decay when subjected to full sunlight, even when UV- B radiation is excluded. During summer in Antarctica there is 24 hour daylight as well as significant UV-B radiation in spring and early summer when one might expect high levels of viral decay. UV-B radiation penetrates lake ice and the water column, though attenuation is rapid. PAR and UV-B penetration to the water column increases as the ice thins. It is likely that low decay rates in winter allowed the survival and build up of VLP numbers, while in summer when the lytic cycle predominated, decay rates were high. Seasonal variation in decay rates may in part account for the poor correlation between bacterial numbers and VLP in our study. High virus to bacteria ratios in the saline lakes (reaching 115 in Pendant Lake) and viral production rates comparable to those seen in temperate lakes suggest that viruses may play an important role in these microbially dominated extreme environments. Data from Antarctic marine waters are limited. Bacteria to virus ratios ranged between 15 - 40 in the sea-ice region, but were lower (3-15) in the open ocean. Higher ratios under ice may indicate that ice and its impact on light climate, reduces viral decay rates and enhances the ratios between bacteria and viruses. The sea-ice itself provides another habitat for bacteria and their viral parasites with abundances of viruses reaching 109 mL-1. OVERALL AIM We wish to undertake a year long study in the inshore marine environment in Prydz Bay focussing on viral dynamics in relation to microbial loop functioning. We will investigate the water column and the communities within the sea-ice. Within the context of the International Polar Year it is important that we further knowledge of microbial processes in the Southern Ocean. Changes in the length and thickness of ice-cover in response to climate warming and the impact on the sea-ice community, may have knock on impacts on water column microbial community and carbon cycling. SPECIFIC OBJECTIVES: 1. The quantify viral dynamics (numbers, production and levels of lysogeny) within the context of the microbial loop processes in the water column and sea-ice of Prydz Bay over an annual cycle. 2. To link viral/bacterial dynamics to physical and chemical parameters such as temperature, UV radiation, Photosynthetically Active Radiation, dissolved organic carbon (DOC) and total organic carbon (TOC) and inorganic nutrients. (N and P). 3. To ascertain linkages between microbial processes iin the sea-ice and water column, particularly during the melt phase. 4. To ascertain the effects of UV-B on viral decay rates below ice and in the open water phase. Progress against objectives: Detailed time series sampling of the sea ice in Prydz Bay has been completed. Bacterial production and viral production, along with the level of lysogeny were conducted. Abundances of viruses, bacterial and nanoflagellates have been completed. Chlorophyll, DOC and TOC, inorganic nutrients also completed. Ciliate samples are still to analysed as are frozen preparations from viral production and lysogeny experiments.

The Sub-Antarctic Zone (SAZ) in the Southern Ocean provides a significant sink for atmospheric CO2 and quantification of this sink is therefore important in models of climate change. During the SAZ-Sense (Sub-Antarctic Sensitivity to Environmental Change) survey conducted during austral summer 2007, we examined CO2 sequestration through measurement of gross primary production rates using 14C. Sampling was conducted in the SAZ to the south-west and south-east of Tasmania, and in the Polar Frontal Zone (PFZ) directly south of Tasmania. Despite higher chlorophyll biomass off the south-east of Tasmania, production measurements were similar to the south-west with rates of 986.2 plus or minus 500.4 and 1304.3 plus or minus 300.1 mg C m-2 d-1, respectively. Assimilation numbers suggested the onset of cell senescence by the time of sampling in the south-east, with healthy phytoplankton populations to the south-west sampled three week earlier. Production in the PFZ (475.4 plus or minus 168.7 mg C m-2 d-1) was lower than the SAZ, though not significantly. The PFZ was characterised by a defined deep chlorophyll maximum near the euphotic depth (75 m) with low production due to significant light limitation. A healthy and less light-limited phytoplankton population occupied the mixed layer of the PFZ, allowing more notable production there despite lower chlorophyll. A hypothesis that iron availability would enhance gross primary production in the SAZ was not supported due to the seasonal effect that masked possible responses. However, highest production (2572.5 mg C m-2 d-1) was measured nearby in the Sub-Tropical Zone off south-east Tasmania in a region where iron was likely to be non-limiting (Bowie et al., 2009). Table 1:Gross primary production at each CTD station and associated data; Mixed layer depth (Zm, m), incoming PAR (mol m-2 d-1), vertical light attenuation (Kd, m-1), euphotic depth (Zeu, m), differences between euphotic depth and mixed layer depth (Zeu-Zm, m), column-integrated chlorophyll a (0 to 150 m, mg m-2), column-integrated production (0 to 150 m, mg C m-2 d-1), production within the mixed layer (mg C m-2 d-1), production below the mixed layer (mg C m-2 d-1), production within the euphotic zone (1% PAR, mg C m-2 d-1), production below the euphotic zone (mg C m-2 d-1). Kd values that were calculated from chlorophyll a v PAR regressions are marked with an asterisk. At some stations there was a surface mixed layer as well as a secondary mixed layer and both depths are indicated. Table 2:Photosynthetic attributes of phytoplankton with depth at each CTD station; Mixed layer depth (m), euphotic depth (Zeu, m), maximum photosynthetic rate [Pmax, mg C (mg chl a)-1 h-1], maximum photosynthetic rate corrected for photoinhibition [Pmaxb, mg C (mg chl a)-1 h-1], initial slope of the light-limited section of the P-I curve [alpha, mg C (mg chl a)-1 h-1 (micro-mol m-2 s-1)-1], rate of photoinhibition [beta, mg C (mg chl a)-1 h-1 (micro-mol m-2 s-1)-1], intercept of the P-I curve with the carbon uptake axis [c, mg C (mg chl a)-1 h-1], light intensity at which carbon-uptake became saturated (Ek, micro-mol m-2 s-1), and chlorophyll a measured using HPLC (mg m-3).

Metadata record for data from ASAC Project 133 See the link below for public details on this project. Surface carbon dioxide (CO2) observations are integral to understanding the role of the Southern Ocean in the global carbon cycle, and to developing reliable predictions of biogeochemical responses to altered climatic conditions. Carbon dioxide (CO2) observations made in surface waters of the Australian sector of the Southern Ocean between the years 1991 and 2002 were used to estimate the seasonal variability in the fugacity of CO2 (fCO2) and net air-sea carbon fluxes. The results showed a net annual uptake of CO2 by the surface ocean over the entire region. The greatest seasonal uptake and lowest fCO2 values were observed in Spring/Summer in the sub-Antarctic zone (SAZ: 44 degrees S-50 degrees S) and in the Seasonal Sea-ice Zone (SIZ: south of 62 degrees S). The seasonal maximum in uptake for these regions is consistent with increased phytoplankton biomass and shoaling mixed layers over the Spring/Summer period. The High Nutrient Low Chlorophyll waters between 50 degrees S and 62 degrees S, also had maximum uptake in summer, but less compared to the SAZ and SIZ regions. Winter surface waters were close to or slightly above equilibrium, with respect to atmospheric CO2. The reduced uptake in winter appeared due to deeper mixing, lower biomass, and air-sea CO2 exchange. The highest fCO2 values in Winter were observed under or near the seasonal sea-ice where entrainment of deeper CO2-rich waters and ice cover would maintain high surface fCO2 values. The smallest seasonal amplitude in the surface fCO2 and net air-sea fluxes was found from 51 degrees S to 54 degrees S, a region on the southern edge of the SAZ and between the North sub-Antarctic Front and North Polar Front. The uptake estimates derived from the data were in good agreement with the CO2 flux climatology of Takahashi (2002), except in the SAZ and SIZ where we observed greater and less uptake, respectively. Data for this project are available for download - the dataset consists of a data files, and some excel files, which provide further information about each data file (cruise, dates, etc). Furthermore, the column headings used in the data files are as follows: Cruise - name of the cruise which collected the data Date - UTC Time - in UTC Latitude - decimal Longitude - decimal Sst - Sea Surface Temperature in degrees C Teq - Temperature of surface water at which the CO2 measurement is made. Sal - Salinity Patm - atmospheric pressure in hectopascals Shipspd - ship speed in knots Windspd - wind speed in knots Winddir - wind direction in degrees xCO2 - Mole fraction of CO2 in air (dry) equilibrated with surface water and at equilibrator water temperature xCO2air - Mole fraction of CO2 in atmosphere, dry pCO2 - partial pressure of carbon dioxide in surface water