Bathymetric Contours and height range polygons of approaches to Casey Station, derived from RAN Fair sheet, Aurora Australis and GEBCO soundings.

Metadata record for data from ASAC Project 2385 See the link below for public details on this project. ---- Public Summary from Project ---- Facilities for chemical analysis of environmental samples in Antarctica are limited, with samples frequently shipped at great expense to Australia for analysis. Development of a technique to concentrate metals from environmental samples into a thin film which can be easily transported to a laboratory for analysis is currently underway. DGT stands for Diffusive gradients in thin films, they are a passive sampling technique for trace metals based on Fick's First Law of diffusion. Basically the theory being the method: Zhang, H. and Davison, W., Anal Chem, 1995, 67, 3391-400 and Davison, W. and Zhang, H., Nature (London), 1994, 367, 546-8. Description of spreadsheets: All data were collected using DGT sediment probes or water samplers prepared from polyacrylamide diffusion layer (0.8 mm thickness, covered with a 0.13 mm thick membrane filter) and Chelex 100 binding layer (0.4 mm thick). Metadata 0304 sediment - DGT sediment probes were deployed during the 0304 summer. Samples were deployed in a 3 x 2 back-to-back array at the inner and outer sites in Brown and O'Brien Bay. ie 1.1 and 1.2 are back to back pair. All samplers were deployed for 34 days. More accurate date are on the attached s'sheet. Results shown are nanograms of metals per square centimetre accumulated in the samplers at a resolution of 2 cm. The detection limits of the metals for the samplers are based on 3 x stdev of the field blank probes. Where value = &nd& the value was less than the method detection limit. Metadata 0304 sediment Characterisation - Cores were sampled in Dec 2003 - Jan 2004 from Casey Station region. All characterisation was performed on the same 1 cm slices of core. Cores were sampled and analysed in anoxic conditions. Latitudes and Longitudess Brown Bay inner66.2803 S, 110.5414 E Brown Bay outer66.2802 S, 110.5451 E O'Brien Bay inner66.3122 S, 110.5147 E O'Brien Bay outer66.3113 S, 110.5162 E Metadata 0203 sediment - Results shown are sediment profile in nanograms of metals per square centimetre accumulated in the samplers at a resolution of 1 m. Samples 1.x were deployed for 5 days before the summer melt, 2.x were deployed for 10 days before the melt, 3.x were deployed for 15 days before the melt, 4.x were deployed for 21 days before the melt, 5.x were deployed for 28 days before the melt, 6.x were deployed for 5 days during the melt and 7.x were deployed for 20 days during the melt. The detection limits of the metals for the samplers are based on 3 x stdev of the field blank probes. Where value = 'nd' the value was less than the method detection limit. Metadata 0304 water - Results show metals in DGT water samplers deployed for 28 days. Actual times are on spreadsheet attached. Samplers were deployed in triplicate at three depths in the water column, with the depth from the sed bed meaning metres above the sea bed in the water column. Values in the original spreadsheet is nanograms of metals accumulated in sampler of 3.14cm2 area. The detection limits of the metals for the samplers are based on 3 x stdev of the field blank. Where value = 'nd' the value was less than the method detection limit. Metadata 0203 water - Results show metals in DGT water samplers deployed for 8 days. Samplers were deployed in triplicate at three depths in the water column. Depth from seabed is a measure of distance from the sea bed to the deployment depth in the water column. Values in the original spreadsheet is nanograms of metals accumulated in sampler of 3.14cm2 area. The detection limits of the metals for the samplers are based on 3 x stdev of the field blank. Where value = 'nd' the value was less than the method detection limit. ---- One thing to note, although the metal isotopes are listed, ie Cd111(LR), this is still a measure of the elemental Cd (ie all isotopes), it is just how the ICP-MS analyst presents the data when I get the raw data back. I probably should have corrected this by remove the number to remove any ambiguity involved. A pdf file of supplementary figures created from the raw data are also included as a download file. Explanations of the figures are presented below. Supplementary Data Figure Captions Figure S1. 2002 - 03 DGT water sampling results for Cd, Fe and Ni, before the melt (upper) and during the melt (lower). BB Brown Bay, OBB O'Brien Bay, top top depth, mid middle depth, bot bottom depth. Error bars represent minimum and maximum values based on three replicates and horizontal line is the detection limit based on 3s Figure S2. 2002 - 03 DGT uptake results for Mn, Fe and As in Brown Bay (upper) and O'Brien Bay (lower) for various deployment times Figure S3. 2003 - 04 DGT sediment probes results for Brown Bay outer. Upper axis represents maximum porewater concentration assuming no resupply; symbols are for 6 replicate DGT probes. Detection limit, based on 3s is represented by vertical line Figure S4. 2003 - 04 DGT sediment probes results for O'Brien Bay inner. Upper axis represents maximum porewater concentration assuming no resupply; symbols are for 6 replicate DGT probes. Detection limit, based on 3s is represented by vertical line Figure S5. 2003 - 04 DGT sediment probes results for O'Brien Bay outer. Upper axis represents maximum porewater concentration assuming no resupply; symbols are for 6 replicate DGT probes. Detection limit, based on 3s is represented by vertical line Figure S6. Sediment porewater concentrations from replicate Brown Bay outer cores Figure S7. Sediment porewater concentrations for O'Brien Bay inner (open circles) and outer (closed circles)

The salinity of seawater at four sites around Casey was recorded during summer 2003/04 by a salinity probe (TPS Australia, WP-84 Conductivity Meter) attached to experimental mesocosms suspended below the sea ice. Data are salinity in parts per thousand (ppk) automatically logged every 30 minutes over the two two week long runs of the experiment. The period over which data were recorded varies between sites and is fragmentary within these periods at some sites due to power lose to the loggers caused by faulty batteries and adverse weather conditions. Mesocosms were suspended two to three metres below the bottom edge of the sea ice through a 1 metre diameter hole and were periodically raised to the surface for short periods (~1 hour). Mesocosms were deployed at Brown Bay Inner (S66 16.811 E110 32.475), Brown Bay Outer (S66 16.811 E110 32.526), McGrady Cove (S66 16.556 E110 34.392) and O'Brien Bay 1 (S66 18.730 E110 30.810). This experiment was part of the short-term biomonitoring program for the Thala Valley Tip Clean-up at Casey during summer 2003/04. These data were collected as part of ASAC project 2201 (ASAC_2201 - Natural variability and human induced change in Antarctic nearshore marine benthic communities). See also other metadata records by Glenn Johnstone for related information.

The concentration of heavy metals in seawater at four sites around Casey was determined via Diffusive Gradients in Thin films (DGT) loggers attached to experimental mesocosms suspended below the sea ice. Data are the concentration of heavy metals in micrograms per litre (ug/l), equivalent to parts per billion (ppb)/litre Two loggers were attached to each mesocosm (perforated 20 litre food buckets) at each site; one at the top and one at the bottom of each mesocosm. Mesocosms were suspended two to three metres below the bottom edge of the sea ice through a 1 metre diameter hole and were periodically raised to the surface for short periods (~1 hour). This experiment was part of the short-term biomonitoring program for the Thala Valley Tip Clean-up at Casey during summer 2003/04. During Runs 1 and 2 of the experiment mesocosms were deployed at Brown Bay Inner (S66 16.811 E110 32.475), Brown Bay Outer (S66 16.811 E110 32.526), McGrady Cove (S66 16.556 E110 34.392) and O'Brien Bay 1 (S66 18.730 E110 30.810). In Run 3 mesocosm were deployed in open water with no sea ice covering at Brown Bay Inner (S66 16.807 E110 32.556), Brown Bay Outer (S66 16.805 E110 32.607), McGrady Cove (S66 16.520 E110 34.257) and O'Brien Bay (S66 17.607 E110 31.247). These data were collected as part of ASAC project 2201 (ASAC_2201 - Natural variability and human induced change in Antarctic nearshore marine benthic communities). See also other metadata records by Glenn Johnstone for related information.

Metadata record for data from ASAC Project 2518 See the link below for public details on this project. Global climate change will lead to a reduction in the duration and thickness of sea ice in coastal areas. We will determine whether this will lead to a decrease in primary production and food value to higher predators. Project objectives: Our primary objective is to determine what effect will declining sea ice cover have on Antarctic coastal primary production? Hypotheses to be tested - A decrease in sea ice algal production will lead to a net reduction in total primary production. - A decrease in sea ice will result in less water column stratification which will reduce the significance of phytoplankton blooms. - Less sea ice will lead to a change in phytoplankton bloom composition away from diatoms towards un-nutritious nuisance blooms such as Phaeocystis - Benthic microalgal production will increase - Seaweed production will increase slightly - A decrease in sea ice thickness will increase ice algal production (as they are generally light limited) - Ice algae, benthic microalgae, and phytoplankton will acclimate to an elevated light climates by changing their photosynthetic efficiency and capacity - Ice algae, benthic microalgae, and phytoplankton will acclimate to an altered light quality. To answer these questions we will also need to determine: - What is the total annual primary production at coastal Antarctic sites; this consists of the contributions from the sea ice algal mats, benthic microalgal, seaweed and phytoplankton? - What is the effect of major environmental variables, such as UV, salinity, currents oxygen toxicity, cloud cover, nutrient availability and temperature on production. - What is the inter-annual variability in primary production? A broader scale issue that our data will contribute to providing answers to is the question - What effect will changing primary production have on higher trophic levels? Taken from the 2009-2010 Progress Report: Progress against objectives: The 2009/10 field and laboratory season focused on the second of our primary questions, i.e. 'What is the effect of major environmental variables, such as UV, salinity, currents oxygen toxicity, cloud cover, nutrient availability and temperature on production'. In particular we focused on light and light transmission though the sea ice. The science program AAS2518 was executed at Casey station from 11 Nov to 5 Dec 2009. The project was split into a field and a lab-based component. In situ spectral light transmission data were collected on first year sea ice within the vicinity of Jack's Hut. Ice cores were collected and transported to the laboratory at Casey station for spectral attenuation profiles within sea ice, and for measurements of spectral absorption by particulate and dissolved organic matter. Overall, the program was successful: in situ sea-ice spectral transmission data was collected in combination with vertical profiles of absorption coefficients of particulate (algae and detritus) and dissolved organic matter. Samples for analysis of photosynthetic pigments were collected and shipped to Sydney. Their analysis is underway. Due to logistical issues associated with the collection and transport of sea ice cores, the protocol for vertical profiling of spectral attenuation was modified (see below) and analysis of the data is currently underway. The field component of the program was successful as spectral transmission data was collected for first year sea-ice, and the chosen site contained a thriving sea ice algal community for bio-optical measurements. It was initially planned to sample multiple sites offering a range of varying sea-ice thickness, but this was not possible during this campaign. Many sites in the vicinity of Casey station had already started to melt and break up, so that for logistical and safety reasons the area around Jack's hut was the only workable option. The field period instead spanned ~ 20 days during the melt period at Jack's, during which the porosity of sea ice increased but thickness remained constant. Ice cores destined for spectral transmission profiles were to be collected whole and intact, but due to the presence of fractures in the sea ice, drilling (manual as well as motor powered) resulted in fractured core samples. The protocol was therefore modified: cores were sectioned in 20 cm sections and spectral transmission measured for each section. Spectral transmission profiles across the entire thickness of sea ice are to be re-constructed from the discrete data points. The accuracy of the approach will be assessed against the in situ spectral transmission data. The download file contains three spreadsheets (two of them are csv files), and a readme document which provides detailed information about the three spreadsheets.

Two 16S rDNA clone libraries, one from a Brown Bay sample and one from an O'Brien Bay sample were generated. These samples were originally collected as part of ASAC project 868 and the microbiology of the samples is now being investigated as part of ASAC 1228. Two data files are included in the download. Both are in "fasta" format, a text-based format for representing either nucleotide sequences or peptide sequences, in which base pairs or amino acids are represented using single-letter codes. Further information about the dataset can also be found in the referenced paper.

This dataset contains records of ice thickness and snow thickness from Casey, Antarctica. Measurements were attempted on a weekly basis and were recorded between 1979 and 1992. The observations are not continuous however. The dataset is available via the provided URL. This data were also collected as part of ASAC projects 189 and 741. The Casey fast ice thickness data are no longer being collected.

Database Description The files represent the 41 different Weddell seal (Leptonychotes weddellii) call types identified at either Mawson, Davis, and/or Casey. They were collected between 60 degrees 49' E and 110o 40' E in longitude, and between 66 degrees 12' S and 68 degrees 34' S in latitude. Each call type name includes two elements. The first is a three-digit number starting at 301 to identify the call type. The second is a one to three-letter code referring to the call category that each type falls into. The 13 different possible call categories are: SymbolNameDescription OToneConstant-frequency, predominantly sinusoidal call. LGrowlConstant-frequency, broad bandwidth, long call. QWhoopConstant-frequency call with a terminal upsweep. SSqueakBrief call with constant frequency or rising frequency and an irregular waveform. WAWhistle AscendingAscending frequency, sinusoidal waveform. TCTrill Constant-FrequencyNarrow bandwidth trill with a constant-frequency beginning, sinusoidal or frequency-modulated waveform. TTrillNarrow to broad bandwidth, containing a frequency downsweep, greater than 2 seconds. WDWhistle DescendingDescending frequency, sinusoidal waveform (less than 2 seconds). MMewAbruptly descending frequency followed by a long constant-frequency ending. CChugAbruptly descending frequency followed by a brief constant-frequency ending. GGuttural Glug (Grunt)Descending-frequency call that was lower than a Chug and had a brief duration. WAGWhistle Ascending - GruntBrief Ascending Whistle followed by a Guttural Glug (Grunt), the two types alternate in a regular pattern. KKnockAbrupt, brief-duration broadband sound (from: Pahl, B.C., Terhune, J.M. and Burton, H.R. 1997). The 41 call types were divided into two sections, the first 33 (301-O to 333-K) being common call types and the last 8 (334-Q to 341-WD) being rare call types. In each call type folder, one to five different samples of each call type are provided. They are identified by a small case letter added at the end of the call type name. Each sample includes both a .WAV audio sample and a .JPG image of the call type spectrogram showing call shape, i.e., changes in call frequency (vertical) over time (horizontal). These call types were used to identify: (a) unique call types or call categories, (b) differences in call type or call category usage (the frequency of occurrence of each call type or category), and (c) differences in call features (number of elements, start frequency, frequency shift and first element duration) among the three stations. The download file also includes a spreadsheet of data and a text file explaining how to interpret the data. Analysis of this dataset is ongoing.

This indicator is no longer maintained, and is considered OBSOLETE. INDICATOR DEFINITION Regular measurements of the thickness of the fast ice, and of the snow cover that forms on it, are made through drilled holes at several sites near both Mawson and Davis. TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system. This indicator is one of: CONDITION RATIONALE FOR INDICATOR SELECTION Each season around the end of March, the ocean surface around Antarctica freezes to form sea ice. Close to the coast in some regions (e.g. near Mawson and Davis stations) this ice remains fastened to the land throughout the winter and is called fast ice. The thickness and growth rate of fast ice are determined purely by energy exchanges at the air-ice and ice-water interfaces. This contrasts with moving pack ice where deformational processes of rafting and ridging also determine the ice thickness. The maximum thickness that the fast ice reaches, and the date on which it reaches that maximum, represent an integration of the atmospheric and oceanic conditions. Changes in ice thickness represent changes in either oceanic or atmospheric heat transfer. Thicker fast ice reflects either a decrease in air temperature or decreasing oceanic heat flux. These effects can be extrapolated to encompass large-scale ocean-atmosphere processes and potentially, global climate change. DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial Scale: At sites near Australian Antarctic continental stations: Davis; Mawson. Frequency: at least weekly, reported annually Measurement Technique: Tape measurements through freshly drilled 5 cm diameter holes in the ice at marked sites. RESEARCH ISSUES To more effectively analyse the changes in Antarctic fast ice a detailed long-term dataset of sea ice conditions needs to be established. This would provide a baseline for future comparisons and contribute important data for climate modelling and aid the detection of changes that may occur due to climate or environmental change. LINKS TO OTHER INDICATORS SOE Indicator 1 - Monthly mean air temperatures at Australian Antarctic stations SOE Indicator 40 - Average sea surface temperatures in latitude bands 40-50oS, 50-60oS, 60oS-continent SOE Indicator 41 - Average sea surface salinity in latitude bands: 40-50oS, 50-60oS, 60oS-continent SOE Indicator 42 - Antarctic sea ice extent and concentration The fast ice data are also available as a direct download via the url given below. The data are in word documents, and are divided up by year and site (there are three sites (a,b,c) at each station). Snow thickness data have also been included. A pdf document detailing how the observations are collected is also available for download.

The ANARE Health Register, which has been in operation since 1987, is designed to gather, store, analyse and report on all health related events occurring in the ANARE population. The principal aims of the project are to: - quantify the occurrence of ill health in Antarctic personnel. - compare the incidence rates with those in the domestic population. - assess any trends in health events. - identify high risk groups, in order to modify conditions accordingly. - assess the role of pre-existing health conditions. - examine the causes of injury. - quantify the procedures performed and drugs administered. The results of all medical consultations are coded according to the International Classification of Diseases and analysed on both a monthly and an annual basis in order to assess any emerging trends. In addition to serving as a long-term data base for epidemiological studies, the Health Register is proving to be a useful tool in the day-to-day operations of the Polar Medicine Branch of the Australian Antarctic Division.