This is a 3 minute movie (with production music), to be played in the background during the October 28th 2010 Geoscience Australia Parlimentary Breakfast. The video shows a wide range of the types of activities that GA is involved in. These images include GA people doing GA activities as well as some of the results of offshore surveys; continental mapping; eath monitoring etc. The movie will be played as a background before and after GA's CEO (Chris Pigram) presentation.

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.

OzCoasts is a web-based database and information system managed by Geoscience Australia that draws together a diverse range of data and information on Australia's coasts and estuaries. Maps, images, reports and data can be downloaded and there are tools to assist with coastal science, monitoring, management and policy. A Tropical Rivers module is the newest major feature of the website and was developed in partnership with the Griffith University node of the Tropical Rivers and Coastal Knowledge (TRaCK) consortium and Boab Interactive. The module contains the Australian Riverine Landscape Classifier (AURICL) and provides links to the TRaCK Digital Atlas. AURICL will assist researchers and policy makers make better decisions about riverine landscapes. It is a dynamic and flexible system (i.e. can be updated as new data layers become available) for classifying and comparing tropical catchments and their rivers based on the similarity, or dissimilarity, of a wide range of parameters. Importantly, AURICL provides researchers with: (i) data-sets to link stream segments from the National Catchment Boundaries database to estuary point locations for north Australia; (ii) a collection of riverine attribute data that sum their upstream contributions to an estuary; and (iii) an amalgamation of inputs for estuaries with multiple contributing streams. To date, researchers have only had access to very general data on the catchments that feed estuaries (e.g. catchment areas). The Mangroves and Coastal Saltmarsh of Victoria: Distribution, Condition, Threats and Management report is new to the Habitat Mapping module, and constitutes the first State-wide assessment of Victoria's coastal wetlands. The 514 page report, led by Prof. Paul Boon (Victoria University), examines the diversity of wetland types and plant communities along the Victorian coast and provides analysis of the ecological condition and major threats to coastal wetlands in Victoria. OzCoasts will also soon deliver the Coastal Eutrophication Risk Assessment Tool (CERAT) for the NSW Office of Environment and Heritage. CERAT will help identify and prioritise land use planning decisions to protect and preserve the health of NSW estuaries. A partnership between OzCoasts and the coastal facility of the TERN (Terrestrial Ecosystem Research Network) is also currently under negotiation.

Explaining spatial variation and habitat complexity of benthic habitats from underwater video through the use of maps. Different methodologies currently used to process and analyse percent cover of benthic organisms from underwater video will be addressed and reviewed.

This dataset contains species identifications of molluscs collected during survey SOL4934 (R.V. Solander, 27 August - 24 September, 2009). Animals were collected from the Joseph Bonaparte Gulf with a benthic sled. Specimens were lodged at Northern Territory Museum on the 8 February 2010. Species-level identifications were undertaken by Richard Willan at the Northern Territory Museum and were delivered to Geoscience Australia on the 15 March 2010. See GA Record 2010/09 for further details on survey methods and specimen acquisition. Data is presented here exactly as delivered by the taxonomist, and Geoscience Australia is unable to verify the accuracy of the taxonomic identifications.<p><p>This dataset is not to be used for navigational purposes.

The National Geochemical Survey of Australia (NGSA) project (www.ga.gov.au/ngsa) was part of Geoscience Australia's Onshore Energy Security Program 2006-2011 and was carried out in collaboration with the geological surveys of all States and the Northern Territory. It delivered (1) Australia's first national geochemical atlas, (2) an underpinning geochemical database, and (3) a series of reports. Catchment outlet sediments (similar to floodplain sediments in most cases) were sampled in 1186 catchments covering ~80% of the country (average sample density 1 sample per 5500 km2). Samples were collected at 2 depths each sieved to 2 grain size fractions. Chemical analyses carried out on the samples fall into 3 main categories: (1) total (using mainly XRF and total digestion ICP-MS), (2) aqua regia, and (3) Mobile Metal Ion® (MMI) element contents. The MMI analyses were conducted on the surface (0-10 cm) samples sieved to <2 mm, in one single batch, by ICP-MS. Concentrations of 54 elements (Ag, Al, As, Au, Ba, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Er, Eu, Fe, Ga, Gd, Hg, K, La, Li, Mg, Mn, Mo, Nb, Nd, Ni, P, Pb, Pd, Pr, Pt, Rb, Sb, Sc, Se, Sm, Sn, Sr, Ta, Tb, Te, Th, Ti, Tl, U, V, W, Y, Yb, Zn and Zr) were determined. Maps and quality assessment of these data are presented in reports available from the project website. Preliminary interpretations of the MMI dataset suggest that it potentially has significant value in geological, mineral exploration and agronomic (e.g., bioavailability) applications.

Spatial interpolation methods for generating spatially continuous data from point locations of environmental variables are essential for ecosystem management and biodiversity conservation. They can be classified into three groups (Li and Heap 2008): 1) non-geostatistical methods (e.g., inverse distance weighting), 2) geostatistical methods (e.g., ordinary kriging: OK) and 3) combined methods (e.g. regression kriging). Machine learning methods, like random forest (RF) and support vector machine (SVM), have shown their robustness in data mining fields. However, they have not been applied to the spatial prediction of environmental variables (Li and Heap 2008). Given that none of the existing spatial interpolation methods is superior to the others, several questions remain, namely: 1) could machine learning methods be applied to the spatial prediction of environmental variables; 2) how reliable are their predictions; 3) could the combination of these methods with the existing interpolation methods improve the predictions; and 4) what contributes to their accuracy? To address these questions, we conducted a simulation experiment to compare the predictions of several methods for mud content on the southwest Australian marine margin. In this study, we discuss results derived from this experiment, visually examine the spatial predictions, and compare the results with the findings in previous publications. The outcomes of this study have both practical and theoretical importance and can be applied to the spatial prediction of a range of environmental variables for informed decision making in environmental management. This study reveals a new direction in and provides alternative methods for spatial interpolation in environmental sciences.

Catchment outlet sediments (0-10 cm depth, sieved to <2 mm) collected at a very low density over most of the Australian continent have been analysed using the Mobile Metal Ion (MMI®) partial extraction technique. Of the 54 elements analysed, eight are generally regarded as essential nutrients for plant growth: Ca, Cu, Fe, K, Mg, Mn, P and Zn. For these, 'bioavailability', defined here as the ratio of the partial digest concentration to the total concentration, has been investigated. This estimation of 'bioavailability' gives results comparable with standard agricultural measurements. Average 'bioavailability' ranges from 15.0% for Ca to 0.1% for Fe. Smoothed (kriged) colour contour maps for continental Australia have been produced for these eight nutrients and interpreted in terms of lithology (e.g., presence of carbonates in the MMI® Ca map), mineralization (e.g., well known and possibly less known mineral districts in the Cu, P and Zn maps), environmental processes (e.g., salinity in K map, weathering and acid generation in Fe map) and agricultural practices (e.g., application of fertilizers in P and Zn maps). This first application of a partial extraction technique at the scale of a continent has yielded meaningful, coherent and interpretable results.

Demands are being made of the marine environment that threaten to erode the natural, social and economic benefits that human society derives from the oceans. Expanding populations ensure a continuing increase in the variety and complexity of marine based activities - fishing, power generation, tourism, mineral extraction, shipping etc. The two most commonly acknowledged purposes for habitat mapping in the case studies contained in this book are to support government spatial marine planning, management and decision-making and to support and underpin the design of marine protected areas (MPAs; see Ch. 64).

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.