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).

This is a parent record for data collected from AAS project 4102. Project 4102 also follows on from ASAC project 2683, "Passive acoustic monitoring of antarctic marine mammals" (see the related metadata record at the provided URL). Public Summary: Half a century ago the Antarctic blue whale was perilously close to extinction. Over 350,000 were killed before the remaining few were fully protected. A decade ago this elusive and poorly understood species was estimated to be less than 5% of its pre-whaling abundance. This multi-national, circumpolar project will develop and apply powerful new techniques to survey these rare whales and gain an insight into their recovery and ecology. The project is the flagship of the Southern Ocean Research Partnership - an International Whaling Commission endorsed collaborative program.

This record contains the source, gridded data used to produce the maps described in the metadata record with the ID "SIPEX_II_NAME". See the provided URL. The UK Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME) is used to model a wide range of atmospheric dispersion events. These data were collected during the SIPEX II voyage of the Aurora Australis, 2012. The use of NAME and the NWP met data was provided by the UK Met Office for free for research purposes. The analysed wind fields used for the running of NAME are calculated using the Met Office's Unified Model (UM). These are calculated by incorporating all observational site data at six hourly intervals into a forecasting system +/- 3 hours of the observation time. This is continuously repeated to produce a 3D analysis of the state of the atmosphere defined by meteorological variables. It is these variables that are incorporated into NAME and are used to calculate wind vectors, particle position, etc. The global resolution for these fields is 25 km. Model Descriptor Inert particles released for two hours each day between 01:00 - 03:00. The lat/lon for the ship was taken at 02:00 every day. The particles were tracked backwards in time for ten days. The NAME output grid comprised of 267 by 165 boxes of 0.5652 degrees longitude and 0.375 degrees latitude. The lat/lon minimum was 60.0,-85.0 and the max was 210,-23. The plots show the daily particle densities in g s m-3 per grid box for the whole of the back run. There are four different types of plots showing surface influence (0-100m), whole troposphere influence (0-16000m) and below the avg boundary layer (BL). The BL heights have also been plotted at the time of release for each of the backruns.

This dataset is daily passive microwave-derived Advanced Microwave Scanning Radiometer 2 (AMSR2) Antarctic sea ice motion dataset, which is the version of rectified two problems exist in Kimura et al. (2013) sea ice motion product, with ascending (ASC), descending (DES) and combined datasets, which format is DAT file. It is produced at 60×60 km resolution on a regular 127×134 grid covering the entire Southern Ocean (40°~ 90° S, -180°~180° E), for the period of 2017-05-20 to 2017-11-26 (186 days) and 2018-04-08 to 2018-08-20 (135 days). These were calculated by applying the MCC method to 36 GHz, 10 km resolution AMSR2 Level-3 36 GHz TB images (both vertical and horizontal polarization) from the Japan Aerospace Exploration Agency (JAXA). Included datasets: latitude - description: latitude of each gridded pixel - dimensions: 2 - size: [127, 134] longitude - description: longitude of each gridded pixel - dimensions: 2 - size: [127, 134] u_weddell - description: daily ASC, DES and combined u component of sea ice velocity on each pixel, from 2018-04-08 to 2018-08-20 covered entire central Weddell Sea buoy trajectory time-span, 135 days in total. - dimensions: 4 - size: [127, 134, 135, 3] ([x coordinate, y coordinate, days, ASC/DES/combined]) v_weddell - description: daily ASC, DES and combined v component of sea ice velocity on each pixel, from 2018-04-08 to 2018-08-20 covered entire central Weddell Sea buoy trajectory time-span, 135 days in total. - dimensions: 4 - size: [127, 134, 135, 3] ([x coordinate, y coordinate, days, ASC/DES/combined]) u_ross - description: daily ASC, DES and combined u component of sea ice velocity on each pixel, from 2017-05-20 to 2017-11-26 covered entire Ross Sea buoy trajectory time-span, 186 days in total. - dimensions: 4 - size: [127, 134, 186, 3] ([x coordinate, y coordinate, days, ASC/DES/combined]) v_ross - description: daily ASC, DES and combined v component of sea ice velocity on each pixel, from 2017-05-20 to 2017-11-26 covered entire Ross Sea buoy trajectory time-span, 186 days in total. - dimensions: 4 - size: [127, 134, 186, 3] ([x coordinate, y coordinate, days, ASC/DES/combined]) Study domain: 40°~ 90° S, -180°~180° E Time-scale: 24 h (for ASC and DES datasets) and 39 h (for combined dataset). Time period: from 2017-05-20 to 2017-11-26 (186 days) and from 2018-04-08 to 2018-08-20 (135 days). Variables and geographic projection detail are saved in the dataset as Readme.txt

These data represent the results of the first study to use Earth System Model (ESM) outputs of SST and chlorophyll-a to simulate circumpolar krill growth potential for the recent past (1960-1989) and future climate change scenarios (2070-2099). Growth potential is obtained using an empirically-derived krill growth model (Atkinson et al. 2006, Limnol. Oceanogr.), where growth is modeled as a function of SST and chlorophyll-a. It serves as an approximation of habitat quality, as areas that support high growth rates are assumed to be good habitat (see Murphy et al., 2017, Sci Rep). To increase confidence in the future projections, ESMs were selected and weighted for each season based on their skill at reproducing observation-based krill growth potential for the recent past. First, eleven ESMs which provided SST and chlorophyll-a outputs were obtained from the Coupled Model Inter-comparison Project 5 archive. These included: CanESM2, CMCC-CESM, CNRM-CM5, GFL-ESM2G, GFDL-ESM2M, GISS-E2-H-CC, HadGEM2-CC, IPSL-CM5A-LR, MPI-ESM-MR, MRI-ESM1 and NorESM1-ME. For each ESM, seasonal surface averages of SST and chlorophyll-a were used to calculate growth potential for the historical scenario (1960-1989), which was then bilinearly interpolated on to the same 1°x1° grid. Satellite observation-based datasets for SST and chlorophyll-a were used to calculate observation-based growth potential for the recent past (1997-2010). These comprised seasonal surface averages of SST (from the OISST v2 daily dataset, 1/4⁰ horizontal resolution) and chlorophyll-a (the mean of the SeaWiFS and Johnson et al. (2013) corrected estimate of SeaWiFS daily datasets, 1/12⁰ horizontal resolution). Observation-based growth potential was then bilinearly interpolated onto the same grid as the ESMs. ESM skill for each season was subsequently assessed against observation-based growth potential using a Taylor Diagram. The ESMs were selected and weighted according to their performance to produce a weighted subset (see "ESM_weighting_method.pdf" file). Of the netcdfs provided, "hist_mean_ensemble.nc" represents the unweighted mean of seasonal growth potential, calculated from the initial ensemble of eleven ESMs for the historical scenario. The "hist_mean_subset.nc" file represents the analogous output of the weighted subset. Future projections of seasonal growth potential for Representative Concentration Pathways (RCPs) 4.5 and 8.5 were obtained using the weighted subset for the period of 2070-2099. These projected seasonal surface averages are provided in the "rcp45_mean_subset.nc" and "rcp85_mean_subset.nc" files. RCPs represent standard climate change scenarios developed by the Intergovernmental Panel on Climate Change, with 4.5 reflecting some mitigation of carbon emissions, and 8.5 being the "business as usual" scenario. Analogous netcdfs for the weighted subset outputs of chlorophyll-a (chl) and SST (tos) for the historical and RCP scenarios are also provided in the "chl_tos_netcdfs.zip" file so that the driving environmental variables underlying growth potential can be examined.

The impact of freeze-thaw cycling on a ZVI and inert medium was assessed using duplicated Darcy boxes subjected to 42 freeze-thaw cycles. This dataset consists of particle sizing during the decommissioning process of the experiment. Two custom built Perspex Darcy boxes of bed dimensions: length 362 mm, width 60 mm and height 194 mm were filled with a mixture of 5 wt% Peerless iron (Peerless Metal Powders and Abrasive, cast iron aggregate 8-50 US sieve) and 95 wt% glass ballotini ground glass (Potters Industries Inc. 25-40 US sieve). This ratio of media was selected to ensure that most aqueous contaminant measurements were above the analytical limit of quantification (LOQ) for feed solutions at a realistic maximum Antarctic metal contaminant concentration at a realistic field water flow rate. All solutions were pumped into and out of the Darcy boxes using peristaltic pumps and acid washed Masterflex FDA vitron tubing. Dry media was weighed in 1 kg batches and homogenised by shaking and turning end over end in a ziplock bag for 1 minute. To ensure that the media was always saturated, known amounts of Milli-Q water followed by the homogenised media were added to each box in approximately 1 cm layers. 20 mm of space was left at the top of the boxes to allow for frost heave and other particle rearrangement processes. On completion of freeze-thaw cycling and solution flow (refer to Statham 2014), an additional series of assessments was conducted. The media from between the entry weir and the first sample port was removed in five approximately 400 g samples of increasing depth. This procedure was repeated between the last sample port and the exit weir. These samples were left to dry in a fume cabinet before duplicated particle sizing using a Endcotts minor sieve shaker.

Metadata record for data from ASAC Project 2547 See the link below for public details on this project. Pue (greater than 90% as determined by SDS-PAGE) samples of nitrate reductase have been isolated from the Antarctic bacterium, Shewanella gelidimarina (ACAM 456T; Accession number U85907 (16S rDNA)). The protein is ~90 kDa (similar to nitrate reductase enzymes characterised from alternate bacteria) and stains positive in an in-situ nitrate reduction (native) assay technique. The protein may be N-terminal blocked, although further sequencing experiments are required to confirm this. This work is based upon phenotyped Antarctic bacteria (S. gelidimarina; S.frigidimarina) that was collected during other ASAC projects. (Refer: Psychrophilic Bacteria from Antarctic Sea-ice and Phospholipids of Antarctic sea ice algal communities new sources of PUFA [ASAC_708] and Biodiversity and ecophysiology of Antarctic sea-ice bacteria [ASAC_1012]). The download file contains 4 scientific papers produced from this work - one of these papers also contains a large set of accession numbers for data stored at GenBank.

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 dataset is a time series of sea ice freeboard proxy estimation based on ASCAT C-band backscatter measurements. File format is unformatted binary, with each file 632*664 pixels, and 32 bits per pixel (floating point). Two datasets are presented here, as detailed in University of Tasmania Honours thesis by Nicola Ramm: "unmasked", i.e., no attempt to mask multiyear and marginal sea ice, and "masked", where these are masked based on backscatter. The grid used by this dataset is described here: https://nsidc.org/data/polar-stereo/ps_grids.html The methods are described in an honours thesis by Nicola Ramm, University of Tasmania.

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"