Marine debris records from beaches on Heard and Macquarie Islands and floating debris spotted on voyages. Data were collected by observers surveying beaches either methodically or opportunistically, and by observers spotting debris as it floated past ships. The data were originally collated into a searchable database, but the application is no longer supported by the Australian Antarctic Data Centre. An extract of the data is attached to this metadata record. The extract is in Excel format, and each worksheet is a copy of a database table.

Experiments were done to quantify the Total Hydrocarbon Content (THC) in water accommodated fractions (WAF) of three fuels; Special Antarctic Blend diesel (SAB), Marine Gas Oil diesel (MGO) and an intermediate grade of marine bunker Fuel Oil (IFO 180).These tests measured the hydrocarbon content in freshly decanted WAFs and the resulting loss of hydrocarbons over time when WAFs were exposed in temperature controlled cabinets at 0°C. These tests are detailed in Dataset AAS_3054_THC_WAF. The results of hydrocarbon WAF tests were used to calculate integrated concentration from measured hydrocarbon concentrations weighted to time to be used as the exposure concentrations for toxicity tests with Antarctic invertebrates. Exposure concentrations used to model sensitivity estimates were derived by calculating the time weighted mean THC between pairs of successive measurements in the 100% WAFs and dilutions to give overall exposure concentrations for each time point.These modelled concentrations integrated the loss of hydrocarbons over time, and renewal of test solutions at 4 d intervals Exposure concentrations of THC in µg/L are shown for endpoints from 24 h to 21 d

This dataset contains observations of ice conditions taken from the bridge of the RV Aurora Australis during SIPEX 2012, following the Scientific Committee on Antarctic Research/CliC Antarctic Sea Ice Processes and Climate [ASPeCt] protocols. See aspect.antarctica.gov.au Observations include total and partial concentration, ice type, thickness, floe size, topography, and snow cover in each of three primary ice categories; open water characteristics, and weather summary. The dataset is comprised of the scanned pages of a single logbook, which holds hourly observations taken by observers while the ship was moving through sea-ice zone. The following persons assisted in the collection of these data: Dr R. Massom, AAD, Member of observation team Mr A. Steer, AAD, Member of observation team Prof S. Warren, UW(Seattle), USA, Member of observation team Dr J. Hutchings, IARC, UAF, USA, Member of observation team Dr T. Toyota, Inst Low Temp Science, Japan, Member of observation team Dr T. Tamura, NIPR, Japan, Member of EM observation team Dr G. Dieckmann, AWI, Germany, Member of observation team Dr E. Maksym, WHOI, USA, Member of observation team Mr R. Stevens, IMAS, Trainee on observation team Dr J. Melbourne-Thomas, ACE CRC, Trainee on observation team Dr A. Giles, ACE CRC, Trainee on observation team Ms M. Zhia, IMAS, Trainee on observation team Ms J. Jansens, IMAS, Trainee on observation team Mr R. Humphries, Univ Wollengong, Trainee on observation team Mr C. Sampson, Univ Utah, USA, Trainee on observation team Mr Olivier Lecomte, Univ Catholique, Louvain-la-Neuve, Belgium, Trainee on observation team Mr D. Lubbers, Univ Utah, USA, Trainee on observation team Ms M. Zatko, UW(Seattle), USA, Trainee on observation team Ms C. Gionfriddo, Uni Melbourne, Trainee on observation team Mr K. Nakata, EES, Japan, Trainee on observation team

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).

Untreated, macerated wastewater effluent has been discharged to the sea at Davis Station since 2005, when the old wastewater treatment infrastructure was removed. This environmental assessment was instigated to guide the choice of the most suitable wastewater treatment facility at Davis. The assessment will support decisions that enable Australia to meet the standards set for the discharge of wastewaters in Antarctica in national legislation (Waste Management Regulations of the Antarctic Treaty Environmental Protection Act - ATEP) and to meet international commitments (the Madrid Protocol) and to meet Australia's aspirations to be a leader in Antarctic environmental protection. The overall objective was to provide environmental information in support of an operational infrastructure project to upgrade wastewater treatment at Davis. This information is required to ensure that the upgrade satisfies national legislation (ATEP/Waste Management Regulations), international commitments (the Madrid Protocol) and maintain the AAD's status as an international leader in environmental management. The specific objectives were to: 1. Wastewater properties: Determine the properties of discharged wastewater (contaminant levels, toxicity, microbiological hazards) as the basis for recommendations on the required level of treatment and provide further consideration of what might constitute adequate dilution and dispersal for discharge to the nearshore marine environment 2. Dispersal and dilution characteristics of marine environment: Assess the dispersing characteristics of the immediate nearshore marine environment in the vicinity of Davis Station to determine whether conditions at the existing site of effluent discharge are adequate to meet the ATEP requirement of initial dilution and rapid dispersal. 3. Environmental impacts: Describe the nature and extent of impacts to the marine environment associated with present wastewater discharge practices at Davis and determine whether wastewater discharge practices have adversely affected the local environment. 4. Evaluate treatment options: Evaluate the different levels of treatment required to mitigate and/or prevent various environmental impacts and reduce environmental risks.

Depth related changes in sediment characteristics and the composition of infaunal invertebrate communities were investigated at two sites in the Windmill Islands around Casey station, East Antarctica, during the 2006/07 summer. Sediment characteristics were investigated via sediment cores (5cm deep x 5cm diameter) collected from 4 depths (7m, 11m, 17, and 22m) from each of three transects at two sites (McGrady Cove and O'Brien Bay 1). Measured sediment characteristics included grain size distribution, total organic carbon and the concentration of a range of heavy metals. This work was conducted as part of ASAC 2201 (ASAC_2201).

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.

This work was completed as part of the SIPEX - Sea Ice Physics and Ecosystem eXperiment - voyage. Adapted from the SIPEX website: During SIPEX we investigated the biogeochemistry of iron (Fe), including a comprehensive examination of its distribution, speciation (i.e. the different forms of Fe), cycling and its role in fuelling sea ice-based and pelagic algal communities. A major part of this research concentrated on the influence of organic exopolysaccharides (EPS) on Fe solubility and its bio-availability. The distribution of other bioactive trace elements was also examined as a means of fingerprinting the source(s) of Fe, as well as indicating their biological requirements. ######### Data on the small- to medium scale (0.1-1000 m) spatial and temporal distribution of Fe and EPS in sea ice cores, surface snow, brine and underlying seawater were determined in each sampled medium by the interdisciplinary team working on the SIPEX project (AAS 3026) in the East Antarctic sector in September/October 2007. Data include Chlorophyll a, salinity, temperature, sea-ice thickness, ice texture analysis, macro-nutrients (nitrate, phosphate, silicate), oxygen stable isotopes, POC and DOC, EPS, iron. This work was completed as part of AAS (ASAC) project 3026. See the parent metadata record (ASAC_3026) for more information.

Water samples for dissolved trace metal measurements were collected from the surface (15m) down to the 1000m using an autonomous intelligent rosette system (General Ocanics, USA) specially adapted for trace metal work and deployed on a Dyneema rope. The rosette was equipped with 12x10-L Niskin-1010X bottles specially modified for trace metal water sampling. This system has been successfully deployed on the RSV Aurora Australis during voyages au0703 and au0806. Care was taken to avoid any contamination from the ship and the operating personnel. Water samplers were processed aboard under an ISO class 5 trace-metal-clean laminar flow bench in to a trace-metal-clean laboratory container on the ship's trawl deck. All transfer tubes, filtering devices and sample containers were rinsed liberally with sample before final collection. Samples were then drawn through C-Flex tubing (Cole Parmer) and filtered in-line through 0.2 micron pore-size acid-washed capsules (Pall Supor membrane, Acropak 200). Regular sampling depths were as follows: 1000m, 750m, 500m, 300m, 200m, 150m, 125m, 100m, 75m, 50m, 30m, 15m. Samples were analysed within a minute of filtration. Iron(II) was detected with the luminol method combining the experimental set-up of Hansard et al. (2009) with the chemistry as described by Croot and Laan (2002). Samples were not acidified prior to analysis and were pumped directly into the flow cell without an injection valve. Care was taken to maintain a stable light field during measurements as the luminol reagent was found to be extremely sensitive to changes in light intensity. Photons from the reaction of luminol with iron(II) were counted with a Hamamatsu photomultiplier tube housed in a light-tight box. The signal was recorded using FloZ software (GlobalFIA) and the data for each run is stored in a separate file. There is a folder for each profile that contains all the files (automatically generated by the software), which are numbered. The file numbers (e.g. sample1, sample2,...) correspond to the runs as noted in the lab book (see scans). P.L. Croot, P. Laan (2002). Analytica Chimica Acta 466: 261-273. S.P. Hansard et al. (2009). Deep-Sea Res. I 56: 1117-1129.