Assessment of mineral potential in the Regional Forest Agreement Areas (RFAs) required collating mineral potential tract maps of individual deposit styles to produce composite, cumulative and weighted composite and cumulative maps. To achieve that an Avenue-script based ArcView extension was created to combine grids of mineral potential tract maps. The grids were combined to generate maps which showed either the highest (weighted or non-weighted) or cumulated (weighted or non-weighted) values. Resources and Advice Decision Support System (RADSS) combines features of the ArcView extension used in mineral potential assessments in RFAs and ASSESS. It is an ArcView extension with a 'Wizard'-like main dialog that leads the user through the process of creating an output. The system has the capacity to combine GIS-layers (raster and vector) to produce various mineral potential and other suitability maps.

Models of seabed sediment mobilisation by waves and currents over Australia's continental shelf environment are used to examine whether disturbance regimes exist in the context of the intermediate disturbance hypothesis (IDH). Our study shows that it is feasible to model the frequency and magnitude of seabed disturbance in relation to the dominant energy source (wave-dominated shelf, tide-dominated shelf or tropical cyclone dominated shelf). Areas are mapped where the recurrence interval of disturbance events is comparable to the rate of ecological succession, which meets criteria defined for a disturbance regime. We focus our attention on high-energy, patch-clearing events defined as exceeding the Shields (bed shear stress) parameter value of 0.25. Using known rates of ecological succession for different substrate types (gravel, sand, mud), predictions are made of the spatial distribution of a dimensionless ecological disturbance index (ED), given as: ED = FA (ES/RI), where ES is the ecological succession rate for different substrates, RI is the recurrence interval of disturbance events and FA is the fraction of the frame of reference (surface area) disturbed. Maps for the Australian continental shelf show small patches of ED-seafloor distributed around the continent, on both the inner and outer shelf. The patterns are different for wave-dominated (patches on the outer shelf trending parallel to the coast), tide-dominated (patches crossing the middle-shelf trending normal to the coast) and cyclone-dominated (large oval-shaped patches crossing all depths). Only a small portion of the shelf (perhaps ~10%) is characterised by a disturbance regime as defined here. To our knowledge, this is the first time such an analysis has been attempted for any continental shelf on the earth.

The World Summit on Sustainable Development implementation plan requires, by 2012, a representative system of marine protected areas (RSMPA) for the purposes of long-term conservation of marine biodiversity. A great challenge for meeting this goal, particularly in data-poor regions, is to avoid inadvertant failure while giving science the time and resources to provide better knowledge. A staged process is needed for identifying areas in data-poor regions that would enable the objectives to be achieved in the long term. We elaborate a procedure that would satisfy the first stage of identifying a RSMPA, including areas suitable as climate change refugia and as reference areas for monitoring change without direct interference of human activities. The procedure is based on the principles of systematic conservation planning. The first step involves the identification of ecologically-separated provinces along with the physical heterogeneity of habitats within those provinces. Ecological theory is then used to identify the scale and placement of MPAs, aiming to be the minimum spatial requirements that would satisfy the principles for a representative system: comprehensiveness, adequacy and representativeness (CAR). We apply the procedure to eastern Antarctica, a region with spatially-restricted sampling of most biota. We use widely available satellite and model data to identify a number of large areas that are likely to encompass important areas for inclusion in a RSMPA. Three large areas are identified for their pelagic and benthic values as well as their suitability as climate change refugia and reference areas. Four other areas are identified specifically for their benthic values. These areas would need to be managed to maintain these values but we would expect them to be refined over time as more knowledge becomes available on the specific location and spatial extent of those values.

Concern about the impact of ocean acidification on organisms secreting high magnesium calcite skeletons has led to renewed interest in the mineralogy of these organisms. The identification of minerals making up the skeletons of tropical coralline algae, and in particular the determination of the Mg-content of calcite, is most commonly performed with X-ray diffraction. This method, based on XRD peak position, attracted criticism in the past because it produced Mg-contents that were in some cases lower compared to those based on chemical analyses of the bulk sample (in solution). The recent discovery of dolomite and magnesite in living coralline algae skeletons in addition to Mg-calcite explained this issue, and it is our goal in the present study to reinstate XRD as a reliable, quick and affordable method for the study of the mineral make-up of coralline algae species. In this paper we review the history of mineralogical analyses on tropical coralline algae and identify physical preparation methods that can affect results. We build on existing XRD methods to develop simple sampling and analytical methods to identify the presence of dolomite and magnesite, and numerically assess peak asymmetry that is caused by the overlapping reflections of calcite, dolomite and magnesite. These methods do not require specialist crystallographic knowledge or expensive or time consuming processes. The additional information our methods produce can be used to study intra-cellular calcification, and helps to rapidly assess and compare the mineral make-up of large numbers of samples. We conclude that XRD should be an integral part of any mineralogical analysis of coralline algae skeletons, which may be composed of not only Mg-calcite (Ca1.0-0.6Mg0-0.4CO3), but also dolomite (Ca0.5Mg0.5CO3), magnesite (MgCO3) and aragonite (CaCO3).

There is growing awareness of the scientific and intrinsic value of Antarctic geological features, including sites containing rare, and in some cases, globally unique mineral occurrences, mineral assemblages, and unusual rocks features (e.g. ventifacts) and rare fossils. However, the global economic value of the mineral and fossil trade is also considerable and growing, with prized specimens being sold for prices per gram equivalent to that of gold. Locations of geological value, once considered 'protected' by virtue of the logistical complexity and prohibitive cost involved in collection, are becoming increasingly vulnerable as the interest of collectors grows and the inaccessibility of Antarctica diminishes with more frequent visits by private and adventure travellers. Thus the need for proactive intervention, protection and management of 'geo-heritage' sites is becoming increasingly urgent. Wider recognition of the geological values of sites achieved by invoking the provisions for area management of the Madrid Protocol will also help mitigate casual souveniring and accidental or deliberate damage caused by ill-advised construction or other human activity, such as use of heavy machinery.

Mean monthly and mean annual maximum, minimum & mean temperature grids. The grids show the temperature values across Australia in the form of two-dimensional array data. The mean data are based on the standard 30-year period 1961-1990. Gridded data were generated using the ANU (Australian National University) 3-D Spline (surface fitting algorithm). As part of the 3-D analysis process a 0.025 degree resolution digital elevation model (DEM) was used. The grid point resolution of the data is 0.025 degrees (approximately 2.5km). Approximately 600 stations were used in the analysis over Australia. All input station data underwent a high degree of quality control before analysis, and conform to WMO (World Meteorological Organisation) standards for data quality.

From 1995 to 2000 information from the federal and state governments was compiled for Comprehensive Regional Assessments (CRA), which formed the basis for Regional Forest Agreements (RFA) that identified areas for conservation to meet targets agreed by the Commonwealth Government with the United Nations. This CD was created as part of GA's contribution to the Central Highlands CRA. It contains final versions of all data coverages and shapefiles used in the project, Published Graphics files in ArcInfo (.gra), postscript (.ps) and Web ready (.gif) formats, all Geophysical Images and Landsat data and final versions of documents provided for publishing.

Geoscience Australia and CO2CRC have constructed a greenhouse gas controlled release facility to simulate surface emissions of CO2 (and other greenhouse gases) from the soil into the atmosphere under controlled conditions. The facility is located at an experimental agricultural station maintained by CSIRO Plant Industry at Ginninderra, Canberra. The design of the facility is modelled on the ZERT controlled release facility in Montana. The facility is equipped with a 2.5 tonne liquid CO2 storage vessel, vaporiser and mass flow controller unit with a capacity for 6 individual metered CO2 gas streams (up to 600 kg/d capacity in total). Injection of CO2 into the soil is via a 120m long slotted HDPE pipe installed horizontally 2m underground. This is equipped with a packer system to partition the well into six CO2 injection chambers. The site is characterised by the presence of deep red and yellow podsolic soils with the subsoil containing mainly kaolinite and subdominant illite. Injection is above the water table. The choice of well orientation based upon the effects of various factors such as topography, wind direction, soil properties and ground water depth will be discussed. An above ground release experiment was conducted from July - October 2010 leading to the development of an atmospheric tomography technique for quantifying and locating CO2 emissions1. An overview of monitoring experiments conducted during the first subsurface release (January-March 2012), including application of the atmospheric tomography technique, soil flux surveys, microbiological surveys, and tracer studies, will be presented. Additional CO2 release experiments are planned for late 2012 and 2013. Poster presented at 11th Annual Conference on Carbon Capture Utilization & Sequestration, April 30 - May 3, 2012, Pittsburgh, Pennsylvania

Monitoring changes in the spatial distribution and health of biotic habitats requires spatially extensive surveys repeated through time. Although a number of habitat distribution mapping methods have been successful in clear, shallow-water coastal environments (e.g. aerial photography and Landsat imagery) and deeper (e.g. multibeam and sidescan sonar) marine environments, these methods fail in highly turbid and shallow environments such as many estuarine ecosystems. To map, model and predict key biotic habitats (seagrasses, green and red macroalgae, polychaete mounds [Ficopamatus enigmaticus] and mussel clumps [Mytilus edulis]) across a range of open and closed estuarine systems on the south-west coast of Western Australia, we integrated post-processed underwater video data with interpolated physical and spatial variables using Random Forest models. Predictive models and associated standard deviation maps were developed from fine-scale habitat cover data. Models performed well for spatial predictions of benthic habitats, with 79-90% of variation explained by depth, latitude, longitude and water quality parameters. The results of this study refine existing baseline maps of estuarine habitats and highlight the importance of biophysical processes driving plant and invertebrate species distribution within estuarine ecosystems. This study also shows that machine-learning techniques, now commonly used in terrestrial systems, also have important applications in coastal marine ecosystems. When applied to video data, these techniques provide a valuable approach to mapping and managing ecosystems that are too turbid for optical methods or too shallow for acoustic methods.

Geoscience Australia is supporting the exploration and development of offshore oil and gas resources and establishment of Australia's national representative system of marine protected areas through provision of spatial information about the physical and biological character of the seabed. Central to this approach is prediction of Australia's seabed biodiversity from spatially continuous data of physical seabed properties. However, information for these properties is usually collected at sparsely-distributed discrete locations, particularly in the deep ocean. Thus, methods for generating spatially continuous information from point samples become essential tools. Such methods are, however, often data- or even variable- specific and it is difficult to select an appropriate method for any given dataset. Improving the accuracy of these physical data for biodiversity prediction, by searching for the most robust spatial interpolation methods to predict physical seabed properties, is essential to better inform resource management practises. In this regard, we conducted a simulation experiment to compare the performance of statistical and mathematical methods for spatial interpolation using samples of seabed mud content across the Australian margin. Five factors that affect the accuracy of spatial interpolation were considered: 1) region; 2) statistical method; 3) sample density; 4) searching neighbourhood; and 5) sample stratification by geomorphic provinces. Bathymetry, distance-to-coast and slope were used as secondary variables. In this study, we only report the results of the comparison of 14 methods (37 sub-methods) using samples of seabed mud content with five levels of sample density across the southwest Australian margin. The results of the simulation experiment can be applied to spatial data modelling of various physical parameters in different disciplines and have application to a variety of resource management applications for Australia's marine region.