EARTH SCIENCE > OCEANS > MARINE ENVIRONMENT MONITORING
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Metadata record for data from AAS (ASAC) project 3051. Public Environmental change is by far one of the major crises facing our planet in recent times. This project will contribute specifically to understanding the effects of climate change and other human-induced impacts on marine species in Antarctica. Through studying key ecological and biological processes in marine benthic invertebrates we will better understand the spatial scale of populations, the nature of the processes that maintain those populations, how environmental change will affect those processes, and the levels of genetic diversity and resilience in Antarctic marine communities. Taken together this information will enable better, more informed management of Antarctic marine ecosystems. Project objectives: The project objectives, as stated in the project application round 2008/09, appear below: This project will combine experimental tests of demographic change with genetic tests of population isolation and diversity to enable predictions of the resilience of Antarctic marine invertebrates to current and predicted environmental change. The specific objectives of the project are; 1. Effects of change. Understand the effects of environmental change on reproduction (fecundity, reproductive success) and the early life history (larval behaviour, survivorship, and recruitment) of key Antarctic marine benthic invertebrates. 2. Isolation. Determine the degree of isolation/connectivity among populations as well as the levels of genetic diversity of key Antarctic marine benthic invertebrates. 3. Resilience. Assess the resilience (ability to cope with or adapt) of Antarctic marine benthic invertebrates to environmental change. 4. Practical Outcomes. Develop improved predictive capacity to contribute towards the development of management strategies for the conservation of Antarctic marine benthic invertebrates. Taken from the 2008-2009 Progress Report: Progress against objectives: This project commenced in 2008/9. Objective 1 - Effects of change - Collected live echinoderms (Abatus spp, Sterechinus numeyeri, Diploasterias) from around Casey Station and transported these on the A319 back to Kingston. A preliminary fertilisation trial has been run using Sterechinus individuals, and the remaining individuals are now being maintained in aquaria for future reproductive studies. Objective 2 - Isolation - Tissue samples from over 200 Sterechinus numeyeri were collected from 5 sites around Casey Station. These will form the foundation for genetic connectivity studies, and will complement exisiting Abatus samples from the same location. Laboratory processing of these samples has commenced, and development of microsatellite markers for both species is underway. Objectives 3 and 4 represent late-stage components of the project, so no progress can be reported on these at this stage. Taken from the 2009-2010 Progress Report: Progress against the objectives: Objective 1 - Effects of change - Collected live urchins (Abatus spp and Sterechinus numeyeri) from around Davis Station. Ran a series of spawning trials, although these were largely unsuccessful, with most individuals having spawned prior to the beginning of the season. We ran one successful fertilisation trial with S. neumeyeri to look at the effects of water temperature and salinity on fertilisation success. Preliminary analysis of the data indicates these environmental parameters do have an effect on fertilisation. Objective 2 - Isolation - Tissue samples from over 350 Sterechinus numeyeri were collected from 12 sites around Davis Station. These will be used for genetic connectivity studies, and will complement samples collected from Casey in the previous season. Larval Sterechinus were also collected from the water column and preserved for genetic analysis along with adult and juvenile Abatus ingens. Microsatellite markers (11 polymorphic loci) have now been developed for Sterechinus, and microsatellite deveopment is partially completed for Abatus ingens; the library has been created but optimisation of loci still needs to be done. We have completed DNA sequencing for Sterechinus and Abatus from Casey Station for 1 gene region (16S) and are optimising an additional 2 regions. This will be used to compare populations from Davis and Casey to understand large-scale connectivity. Objectives 3 and 4 represent late-stage components of the project. As this is only the second year of a 5-year programme, no progress can be reported on these at this stage.
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These data describe the field deployments of the trace-metal passive sampling tools, diffusive gradients in thin-films (DGT). Deployments occurred over the summer 2017/2018 season in the coastal region adjacent to Casey and Wilkes stations. Deployments of DGT to the nearshore marine environment was achieved with small watercraft and shallow (less than 5m deep) moorings, which were left in situ for 21-37 days, depending on the site.
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Metadata record for data from ASAC Project 2946. Public Shallow nearshore marine habitats are rare in the Antarctic but human activities have led to their contamination. Preliminary studies suggest the characteristics of Antarctica nearshore sediments are different to elsewhere and that contaminant partitioning and absorption, and hence bioavailability, will also be very different. Predictive exposure-dose-response (effects) models need to be established to provide the theoretical basis for the development of sediment quality guidelines to guide remediation activities. Such a model will be possible through the development of an artificial 'living' sediment, which can be used to understand physical and chemical properties that control partitioning and absorption of contaminants. Taken from the 2009-2010 Progress Report: Project objectives: 1. Collate and review existing knowledge on sediment properties in nearshore marine sediments in Antarctica to determine their physical, chemical and microbiological properties and identify gaps in our knowledge of sediment characteristics 2. Construct a range of artificial sterile sediments taking into account characteristics of naturally occurring nearshore sediments in the Antarctic. Examine physical and chemical properties of these sediments and understand the properties that control partitioning of contaminants by manipulation of bulk sediment composition and measuring the adsorption isotherms of important metal contaminants (Cu, Cd, Pb, As, Sn, Sb) in these artificial sediments 3. Produce 'living' sediments by inoculation of sterile sediments with Antarctic bacteria and diatoms that will support natural microbial communities. Examine physical and chemical properties of these sediments and understand the properties that control the partitioning and absorption of contaminants by manipulation of the bulk sediment composition and spiking metal contaminants into these artificial sediments. Progress against objectives: Using published literature the approximate composition of Antarctic sediments was determined. Representative sediment phases were collected form a uncontaminated environment, the chemical composition measured and absorption capacities of Cd and Pb established. The download file contains several excel spreadsheets. Some information about them is provided below: My =ref is reference in thesis EN =is endnote reference Nearby station = is closest known reference point to where samples collected TOC = total organic carbon TOM = Total organic matter BPC =biogenic particulate carbon TN = total nitrogen TP = Total phosphorus BSi = biogenic silica Ci = initial aqueous phase concentration qe = solid phase equilibrium concentration
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This study assessed the performance of diffusive gradients in thin-films (DGT) with a binding resin that used Chelex-100 (iminodiacetic acid functional groups) to measure cadmium, copper, nickel, lead, and zinc contaminants in Antarctic marine conditions. To do this, three sets of experiments were done: (I) the uptake of metals to DGT samplers was assessed over time when deployed to three metal mixtures of known concentrations (DGT performance page). This allowed for the determination of metal diffusion coefficients in Antarctic marine conditions and demonstrated when metal competition for binding sites were likely to occur. (II) the DGT were deployed in the presence of the microalga Phaeocystis antarctica at a concentration of 1000-3000 cells/mL to investigate how environmentally realistic concentrations of an Antarctic marine microalgae affect the uptake of metals (DGT uptake with algae page). Finally, the DGT-labile concentrations from part (II) were used in reference toxicity mixture models to predict toxicity to the microalgae so they could be compared to a previous study that investigated the toxicity of metal mixtures to Phaeocystis antarctica and Cryothecomonas armigera (DGT toxicity modelling page).
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Metadata record for data expected from ASAC Project 2767 See the link below for public details on this project. A multidisciplinary survey of the processes linking sea ice with biological elements of Antarctic marine ecosystems was conducted in winter 2007. The survey provided large-scale information on sea ice biological and physical parameters in the 100-130 degree East sector off East Antarctica. The distribution of sea ice algae and krill were measured using various methods including ice coring surveys and trawls. These measurements were complemented by shipborne measurements and an intensive sea ice sampling program. Use of an ROV was attempted but did not result in quantitative/geo-referenced data. Under-ice video files are available from the Chief-Investigator. Individual word documents are available from this metadata record for each ice station. These contain information on the ice station number, date and time of record and the parameters/ samples.
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This bibliography is a selected list of scientific papers collected by scientists in the ACE-CRC's Antarctic Marine Ecosystem research programme.
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Purpose of future metagenomic (DNA), metaproteomic (protein) and metatranscriptomic (RNA) analysis: For each sample, two drums (~200L each) of seawater were collected. Samples were taken from CTD sites, and surface samples (2m depth) taken at each of these sites. At most of these CTD sites, a deeper sample was taken according to the location of the DCM at that site. The 200L seawater is pumped through a 20 micron mesh to remove the largest particles, then the biomass is collected on three consecutive filters corresponding to decreasing pore size (3.0 microns, 0.8 microns, 0.1 microns). This is repeated for each sample using the second 200L of seawater to generate duplicates for each sample. The overall aim is to determine the identity of microbes present in the Southern Ocean, and what microbial metabolic processes are in operation. In other words: who is there, and what they are doing. Special emphasis was placed on the SR3 transect. Samples were collected as below. For each sample, a total of six filters were obtained (3x pore sizes, 2x replicates). Each filter is stored in a storage buffer in a 50mL tube, and placed at -80 degrees C for the remainder of the voyage.
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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
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In this data set we examined whether eDNA samples can detect similar numbers of species and community compositions as genetic continuous plankton recorder (CPR) samples. On the V4 voyage 2018 from Hobart to Macquarie island, small and large volume eDNA samples as well as genetic CPR samples were collected. All samples were sequenced with a metazoan specific cytochrome c oxidase I marker (folder "2018_08_28 eDNA V4 COI" contains all genetic CPR and small volume eDNA samples, folder "2019_05_08_eDNA_V4_CBR_Repeats_COI" contains some repeated small volume eDNA samples and all large volume eDNA samples (also called CBR samples)). Additionally, all eDNA samples were sequenced using an 18S rRNA marker (folder "2018_09_19 eDNA V4 18s Ramaciotti") to assess overall biodiversity. Each folder contains the raw sequencing data (fastq format) as well as data indexes and readme files. Please contact us if you are planning on using this data (leonie.suter@aad.gov.au). More information about these datasets are contained in the readme files in the dataset.
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Metadata record for data from ASAC Project 2665 See the link below for public details on this project. The Antarctic environment with its harsh climatic conditions, minimal human activity and its unique ecosystems is unlike any of the World's other environments. As such, it is important that an understanding of the Antarctic environment is developed in order to gain a full appreciation of the impacts of human activities in Antarctica and to determine the most effective means to remediate and protect the Antarctic environment. To achieve these goals, new sensitive and selective techniques for sampling metal contaminant levels in marine sediments are being developed. The project is not an environmental study of the Antarctic environment (ie no metal concentrations in water or sediments), but rather the development of an analytical technique for use in Antarctica. We are still in the process of developing this technique and much of the development phase has involved qualitative assessment rather than generating quantitative data. We are currently trialling the technique in the lab and will conduct field trials in the Derwent Estuary. Taken from the abstract of the referenced paper: A novel binding phase was developed for use in diffusive gradients in thin-film (DGT) sampling for Cu(II) by employing methylthymol blue as a chelating and chromogenic agent. Methylthymol blue was adsorbed onto beads of Dowex 1x8 resin (200-400 mesh) and the resin beads were then immobilised onto an adhesive disc. Analysis of exposed binding discs by either UV-vis spectrophotometry or computer imaging densitometry provided robust quantification of adsorbed Cu(II) in the 0.2-1 micro gcm-2 range, allowing detection at micro gL-1 concentrations in the test solution (ca. 17 micro gL-1 for a 24 h deployment), and in good agreement with established DGT theory. The method was shown to be a potential replacement for binding phases based on Chelex 100 where a colorimetric response to a specific metal is desired.