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.

pH is one of the more fundamental soil properties governing nutrient availability, metal mobility, elemental toxicity, microbial activity and plant growth. The field pH of topsoil (0-10 cm depth) and subsoil (~60-80 cm depth) was measured on floodplain soils collected near the outlet of 1186 catchments covering over 6 M km2 or ~80% of Australia. Field pH duplicate data, obtained at 124 randomly selected sites, indicates a precision of 0.5 pH unit (or 7%) and mapped pH patterns are consistent and meaningful. The median topsoil pH is 6.5, while the subsoil pH has a median pH of 7 but is strongly bimodal (6-6.5 and 8-8.5). In most cases (64%) the topsoil and subsoil pH values are similar, whilst, among the sites exhibiting a pH contrast, those with more acidic topsoils are more common (28%) than those with more alkaline topsoils (7%). The distribution of soil pH at the national scale indicates the strong controls exerted by precipitation and ensuing leaching (e.g., low pH along the coastal fringe, high pH in the dry centre), aridity (e.g., high pH where calcrete is common in the regolith), vegetation (e.g., low pH reflecting abundant soil organic matter), and subsurface lithology (e.g., high pH over limestone bedrock). The new data, together with existing soil pH datasets, can support regional-scale decision-making relating to agricultural, environmental, infrastructural and mineral exploration decisions.

Random forest (RF) is one of the top performed methods in predictive modelling. Because of its high predictive accuracy, we introduced it into spatial statistics by combining it with the existing spatial interpolation methods, resulting a few hybrid methods and improved prediction accuracy when applied to marine environmental datasets (Li et al., 2011). The superior performance of these hybrid methods was partially attributed to the features of RF, one component of the hybrids. One of these features inherited from its trees is to be able to deal with irrelevant inputs. It is also argued that the performance of RF is not much influenced by parameter choices, so the hybrids presumably also share this feature. However, these assumptions have not been tested for the spatial interpolation of environmental variables. In this study, we experimentally examined these assumptions using seabed sand and gravel content datasets on the northwest Australian marine margin. Four sets of input variables and two choices of 'number of variables randomly sampled as candidates at each split' were tested in terms of predictive accuracy. The input variables vary from six predictors only to combinations of these predictors and derived variables including the second and third orders and/or possible two-way interactions of these six predictors. However, these derived predictors were regarded as redundant and irrelevant variables because they are correlated with these six predictors and because RF can do implicit variable selection and can model complex interactions among predictors. The results derived from this experiment are analysed, discussed and compared with previous findings. The outcomes of this study have both practical and theoretical importance for predicting environmental variables.

Geoscience Australia often produces spatially continuous marine environmental information products using spatial interpolation methods. The accuracy of such information is critical for well-informed decisions for marine environmental management and conservation. Improving the accuracy of these data products by searching for robust methods is essential, but it is a vexed task since no method is best for all variables. Therefore, we experimentally compared the performance of 32 methods/sub-methods using seabed gravel content data from the Australian continental EEZ. In this study, we have identified and developed several novel and robust methods that significantly increase the accuracy of interpolated spatial information. Moreover, these methods can be applied to various environmental properties in both marine and terrestrial disciplines.

In this study, we aim to identify the most appropriate methods for spatial interpolation of seabed sand content for the AEEZ using samples extracted on August 2010 from Geoscience Australia's Marine Samples Database. The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region but the choice of mtry. No single method performs best for all the tested scenarios. Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall, of the 36 combinations of input secondary variables, methods and regions, RFIDS, 6RFIDS and RFOK were among the most accurate methods in all three regions. Model averaging further improved the prediction accuracy. The most accurate methods reduced the prediction error by up to 7%. RFOKRFIDS, with a search window size of 5, an mtry of 4 and more realistic predictions in comparison with the control, is recommended for predicting sand content across the AEEZ if a single method is required. This study provides suggestions and guidelines for improving the spatial interpolations of marine environmental data.

The Rowley Shoals/Offshore Canning and Roebuck basins survey was conducted on the RV Southern Surveyor survey SS06/2006 (GA-2408) between the 29th May and 22 June 2006. The primary aim of the survey was to identify any sites of natural hydrocarbon seepage, that may provide direct evidence for an active petroleum system within the sub‐surface. A secondary objective was to contribute to the understanding of the modern sedimentary and oceanographic processes influencing this part of the shelf, and to assess the nature of the benthic habitats. Underwater video was captured at 12 sites, with a minimum of 10 minutes to 60 minutes at each site, which totalled approximately 5.5 hours of footage. Video was recorded to mini DV tapes and copied to digital format. Descriptions of footage acquired during the underwater video tows are provided in the post-survey report (GA Record 2007/21 - Geocat # 65453). Please note that the underwater video is unclipped, contains descent and ascent through the water column, laser points in the video are reported to be spaced at 25 cm, and start locations of the underwater video camera stations are found in the Post-survey report.

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. These 5 CDs were created as part of GA's contribution to the NE Victoria CRA. CD1 contains ArcView Legends and Projects, data coverages, shapefiles, final Exec. Summary and Minerals Technical Reports, and final figures and maps. CD2 contains final reports, metadata, model descriptions, and all associated maps and figures. CD3 contains Landsat, Magnetic and Radiometric images, AcrInfo grids, and unused ArcInfo AMLs and Graphic files that were intended for map creation. CD4 contains original data supplied by custodians, staff versions of data and projects, and various edited versions of covers and shapefiles. CD5 contains integration data used during Directions report analysis.

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. These 3 CDs were created as part of GA's contribution to the SW Western Australia CRA. CD1 contains final versions of all data coverages, images and shapefiles used in the project. CD2 contains the final CRA report, Executive Summary, and associated maps and figures in Arcinfo (.gra), postscript (.ps) and Web ready (.gif) formats. CD3 contains the final Minerals Assessment report and associated maps and figures in Arcinfo, postscript and Web ready formats.

Introduction Low-density geochemical surveys provide a cost-effective means to assess the composition of near-surface materials over large areas. Many countries in the world have already compiled geochemical atlases based on such data. These have been used for a number of applications, including: - establish baselines from which future changes can be measured - design geologically sensible targets for remediation of contaminated sites - support decision-making regarding appropriate land-use - explore for natural resources - study links between geology and plant/animal health (geohealth) A first pilot project was initiated to help establish sampling and analytical protocols relevant to Australian landscapes and climates. The Riverina region was chosen for this study because of its crucial economic, environmental and societal importance within the Murray-Darling basin. The region is a prime agricultural area, is bordered to the south by the Victorian goldfields, and is home to 11% of the Australian population. Results of this study are presented here. Methods Using a hydrological analysis, 142 sites near the outlets of large catchments were selected within the 123,000 km2 survey area (1 site per 866 km2 on average). At each site, two 10-cm thick overbank sediment samples were taken, one at the surface ('top overbank sediment', TOS) and the other between 60 and 90 cm depth (`bottom overbank sediment', BOS). These were described, dried, sieved (<180 m) and analysed chemically for 62 elements. Exploratory data analysis was undertaken and geochemical maps (various styles are shown here) were prepared. Results and discussion The geology of the area is dominated by Cainozoic sediments found in low-relief plains over the vast majority of the Riverina. The eastern and southern fringes of the area form higher relief landforms developed on outcropping or subcropping Palaeozoic sedimentary, mafic and felsic volcanic and felsic intrusive rocks. The geochemical results of the survey are independently corroborated by the good match between the distributions of K, U and Th concentrations in TOS and airborne gamma-ray maps. The distribution of Ca in BOS indicates generally higher concentrations in the northern part of the study area, which is also reflected in higher soil pH values there. Such data have implications for soil fertility and management in agricultural areas. In terms of applications to mineral exploration, dispersion trains of typical pathfinder elements for gold mineralisation, like As and Sb are clearly documented by the smoothly decreasing concentrations from south (near the Victorian goldfields) to north (over sediments from the Murray basin). Chromium is an element that can be associated with ill-health in animals and humans when present over certain levels. There is a smooth increase in Cr concentration from north to south, and the two sites with the highest values can be correlated with a ridge of Cambrian mafic volcanics. High total Cr concentrations in the Riverina are unlikely, however, to lead to serious health problems as only a very small proportion of Cr will be bioavailable. Conversely, some elements can be present at concentrations that are too low for optimum plant growth, such as potentially Mo. The distribution map for this element shows a general decrease from south to north. Given its lower bioavailability in acid soils, Mo is likely to be deficient in the south of the region, despite higher total concentrations here. Farmers report the necessity to use Mo-enriched fertilisers in this area. Conclusions Low-density geochemical surveys can be conducted in Australia using common regolith sampling media. They provide a cost-effective, internally consistent dataset that can be used by to support a variety of critical economic, environmental and societal decisions.

This dataset contains species identifications of crinoids 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 Museum of Victoria on the 19 April 2010. Species-level identifications were undertaken by Kate Naughton at the Museum of Victoria and were delivered to Geoscience Australia in December 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.