During the ADBEX III voyage, many samples were taken of the sea ice and snow. These samples were analysed to determine water density, with the results recorded in a physical note book that is archived at the Australian Antarctic Division. Logbook(s): - Glaciology ADBEX III Water Density Results - Glaciology ADBEX III Oxygen Isotope Sample Record

Metadata record for data from ASAC Project 545 See the link below for public details on this project. From the abstract of the referenced paper: Blood was collected for haematological, red cell enzyme and red cell metabolic intermediate studies from 20 Southern elephant seals Mirounga leonina. Mean haematological values were: haemoglobin (Hb) 22.4 plus or minus 1.4 g/dl, packed cell volume (PCV) 54.2 plus or minus 3.8%, mean cell volume (MCV) 213 plus or minus 5 fl and red cell count (RCC) 2.5 x 10 to power 12 / l. Red cell morphology was unremarkable. Most of the red cell enzymes showed low activity in comparison with human red cells. Haemoglobin electrophoresis showed a typical pinniped pattern, ie two major components. Total leucocyte counts, platelet counts, and coagulation studies were within expected mammalian limits. Eosinophil counts varied from 0.5 x 10 to power 9 / l (5%-49%), and there was a very wide variation in erythrocyte sedimentation rates, from 3 to 60mm/h.

Metadata record for data from ASAC Project 1119 See the link below for public details on this project. A marked bend in the Hawaiian-Emperor seamount chain supposedly resulted from a recent major reorganization of the plate-mantle system there 50 million years ago. Although alternative mantle-driven and plate-shifting hypotheses have been proposed, no contemporaneous circum-Pacific plate events have been identified. We report reconstructions for Australia and Antarctica that reveal a major plate reorganization between 50 and 53 million years ago. Revised Pacific Ocean sea-floor reconstructions suggest that subduction of the Pacific-Izanagi spreading ridge and subsequent Marianas/Tonga-Kermadec subduction initiation may have been the ultimate causes of these events. Thus, these plate reconstructions solve long-standing continental fit problems and improve constraints on the motion between East and West Antarctica and global plate circuit closure.

A geomorphology map of the Australasian seafloor was created as a Geographic Information System layer for the study described in Torres, Leigh G., et al. "From exploitation to conservation: habitat models using whaling data predict distribution patterns and threat exposure of an endangered whale." Diversity and Distributions 19.9 (2013): 1138-1152. The geomorphology map was generated using parameters derived from the General Bathymetric Chart of the World (GEBCO 2008, http://www.gebco.net/), with 30 arc-second grid resolution. Geomorphology features were delineated manually with a consistent spatial resolution. Each feature was assigned a primary attribute of depth zone and a secondary attribute of morphological feature. The following feature classes are defined: shelf, slope, rise, plain, valley, trench, trough, basin, hills(s), mountains(s), ridges(s), plateau, seamount. Further information (methods, definitions and an illustration of the geomorphology map) is provided in Appendix S2 of the paper which is available for download (see related URLs).

Overview The aim of this project was to investigate the genetic connectivity and diversity of Antarctic benthic amphipods over fine (100's of m's), intermediate (10's of km's) and large (1000's of km's) scales, using highly variable molecular markers. To achieve this, we developed seven microsatellite markers specific to the common Antarctic amphipod species Orchomenella franklini. A total of 718 specimens of O. franklini were collected from East Antarctica. Approximately 30 specimens were collected from each site, and sites were spatially hierarchically nested - i.e. sites (separated by 100m) were nested within locations (separated by 1-30km), which were nested within 2 broad regions (separated by approx. 1400km). Each amphipod sample was genotyped for all seven microsatellite loci (although occasionally a locus would not amplify in a given sample). This dataset provides all the resultant genetic data - that is, the size of the two alleles that were amplified for each microsatellite locus, in each of 718 amphipod specimens. Data collection and analysis Please refer to the associated publication (see below) for all relevant methodology. Explanation of worksheet Sample ID- a unique code given to identify each amphipod sample (the code itself has no actual meaning). Region- the broad region of the Antarctic coast from which each sample was collected. The two regions (Casey and Davis station) are separated by approx. 1400km. Location- the locations (within a region) from which each sample was collected. The names of each location reflect actual names registered by the Australian Antarctic Division and therefore their coordinates can be pinpointed on maps held by the Australian Antarctic Division Data Centre. Locations (and corresponding sites) written in italicised typeface are considered polluted (see publication for more information on this classification). Site- the sites sampled within each location. Sites are named simply by a two -letter abbreviation of the location they are from, followed by a lowercase 'a', 'b', 'c' or 'd' representing site 1, 2, 3 etc. Microsatellite data - this provides all the microsatellite genetic data generated for each amphipod specimen. Data are presented as the allele sizes (in number of base pairs) recorded for each of the seven microsatellite loci amplified. The seven microsatellite loci are called Orcfra3, Orcfra4, Orcfra5, Orcfra6, Orcfra12, Orcfra13, Orcfra26. As O. franklini is a diploid organism, each microsatellite locus has two allele sizes (hence why there are two columns underneath each locus). A '0' signifies that a particular locus did not amplify successfully in the corresponding organism (after at least two attempts). Samples were collected from Casey station between January 2009 and March 2009, and from Davis station between November 2009 and April 2010. Genetic data was generated and analysed between April 2009 and November 2009, and between May 2010 and April 2011. Genetic data obtained from the common Antarctic amphipod species Orchomenella franklini - Genetic data obtained from the common Antarctic amphipod species Orchomenella franklini. A total of 718 specimens were collected from sites within 20 km of Casey station or Davis station. Collection dates ranged from 2009 to 2010. Each amphipod sample was genotyped for seven microsatellite loci (although occasionally a locus would not amplify in a given sample).

Metadata record for data from ASAC Project 2535 See the link below for public details on this project. Project 2535 'Variability and stability of Antarctic Bottom Water (AABW)' Metadata description (1) Model analysis of natural AABW variability:- We have assessed the interannual to multi-decadal variability of AABW in a global coupled climate model, focussing on variations in bottom water formation rates, T-S changes on AABW neutral surfaces, and the physical mechanisms controlling this variability. The global coupled climate model used is the CSIRO Mark 3 Coupled Climate Model, which incorporates sub-models of the ocean, atmosphere, sea-ice, and land-surface. The experiments were run over a global grid at approximate resolution of 1.9 degrees x 1.9 degrees x 18 levels in the atmosphere, and 1.875 degrees x 0.94 degrees x 31 levels in the ocean. Variables analysed include oceanic temperature, salinity and circulation on AABW density layers, sea-ice extent and thickness, atmospheric sealevel pressure, temperature, and winds. The model integration considered was run with steady CO2 levels for two hundred years in a quasi-steady state mode. Full details of the CSIRO Mark 3 Coupled Climate Model can be found in Gordon et al. (2002). Gordon, H.B., Rotstayn, L.D., McGregor J.L., Dix M.R., Kowalczyk E.A., O'Farrell S.P., 2002: The CSIRO Mk3 Climate System Model. CSIRO Division of Atmospheric Research Technical Paper, No. 60. 130pp. (2) Model simulations of CO2-induced change in AABW: We also ran simulations of climate change within the Canadian University of Victoria Earth System Climate Model of Intermediate Complexity at a global longitude x latitude resolution of 3.6 degrees x 1.8 degrees. The model includes a primitive equation three-dimensional, 19 level ocean model, a sea-ice model, a simple land and river model and a two dimensional energy-moisture balance atmospheric model. A number of sensitivity experiments on ocean mixing parameters and the sea-ice model were conducted to optimise the Southern Hemisphere climatology for the control experiment. The control case (CTRL) was integrated for 3100 years starting from idealised initial conditions. Three climate change experiments were conducted, in which atmospheric carbon dioxide concentrations are changed to 450 ppm, 750 ppm and 1000 ppm from a pre-industrial level of 280 ppm, over different temporal regimes. Full model experiment descriptions appear in Bates, Sijp, and England (2005).

Access database containing biological and environmental data collected by the Australian Antarctic Division, Human Impacts Benthic Biodiversity group.

This parameter set was developed to provide a plausible implementation for the ecological model described in Bates, M., S Bengtson Nash, D.W. Hawker, J. Norbury, J.S. Stark and R. A. Cropp. 2015. Construction of a trophically complex near-shore Antarctic food web model using the Conservative Normal framework with structural coexistence. Journal of Marine Systems. 145: 1-14. The ecosystem model used in this paper was designed to have the property of structural coexistence. This means that the functional forms used to describe population interactions in the equations were chosen to ensure that the boundary eigenvalues of every population were all always positive, ensuring that no population in the model can ever become extinct. This property is appropriate for models such as this that are implemented to model typical seasonal variations rather than changes over time. The actual parameter values were determined by searching a parameter space for parameter sets that resulted in a plausible distribution of biomass among the trophic levels. The search was implemented using the Boundary Eigenvalue Nudging - Genetic Algorithm (BENGA) method and was constrained by measured values where these were available. This parameter set is provided as an indicative set that is appropriate for studying the partitioning of Persistent Organic Pollutants in coastal Antarctic ecosystems. It should not be used for predictive population modelling without independent calibration and validation.

These are phytoplankton pigment datasets collected on the BROKE voyage of the Aurora Australis during the 1995-1996 summer season. The readme file in the data download states: Data supplied by Dr Simon Wright. Details phytoplankton pigment data from BROKE. "BROKEPIGDBase.xls Contains 5 worksheets. 'Notes' repeats the information presented here. 'Key' describes the column headings, chemical names. 'Raw_Data' is the exact spreadsheet receieved from Dr Wright. 'Standard_sample_source' contains all the phyto-chemical data as taken from the CTD programme. 'Non_standard_sample_source' contains phyto-chemical data that seems to have been collected opportunistically, to test some assumptions. The details of the locations of the opportunistic samples are detailed in the column 'Sample_source'. Note- it is unsure whether the numbers in the CTD column describe the Station Number. This has to be verified. Converted into a MS Access database- 'BROKE_phytoplankton.mdb' by Natalie Kelly. This database contains 3 tables. One is a description of the column names, chemical etc. The other two contain both the Standard and Non-Standard Sample source phytochemical data. Natalie Kelly 19 November 2005"

CAWCR Hindcast* and ECMWF ERA-5** model predictions of wave spectral properties (wave height and period) and corresponding observed data from ACE. Observations are mapped to model grids. Quality control is applied, i.e. cells with a number of points less than 5 and/or with high data variation (Standard Deviation/Mean greater than 0.2) are eliminated. Files are named as follows: WaMoS_vs_CAWCR_Hs.mat WaMoS_vs_CAWCR_Tm.mat WaMoS_vs_ERA5_Hs.mat WaMoS_vs_ERA5_Tp.mat In each file, columns show Latitude (deg.), Longitude (deg.), Time (number of days from January 0, 0000), Model Parameters (Hs, Tp or Tm) and Observed Parameters (Hs, Tp or Tm), respectively. Hs denotes significant wave height in meters, Tp is peak wave period in seconds and Tm is mean wave period based on the first moment of wave spectrum in seconds. The MATLAB file, WaMoSvsModel_FigurePlot.m, can be used to visualise the results. The files dscatter.m and polyfix.m are functions used in the MATLAB script. A sample figure (SampleFigure.png) is also included for users’ reference. * Durrant, T., Greenslade, D., Hemer, M. and Trenham, C., 2014. A global wave hindcast focussed on the Central and South Pacific (Vol. 40, No. 9, pp. 1917-1941). ** Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), Dec. 12, 2018.