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.

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.

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.

Mapping of benthic habitats seldom considers biogeochemical variables or changes across time. We aimed to: (i) develop winter and summer benthic habitat maps for a sandy embayment; and (ii) compare the effectiveness of various maps for differentiating infauna. Patch-types (internally homogeneous areas of seafloor) were constructed using combinations of abiotic parameters, and are presented in sediment-based, biogeochemistry-based and combined sediment/biogeochemistry-based habitat maps. August and February surveys were undertaken in Jervis Bay, Australia, to collect samples for physical (%mud, sorting, %carbonate), biogeochemical (chlorophyll a, sulfur, sediment metabolism, bio-available elements) and infaunal analyses. Boosted Decision Tree and cokriging models generated spatially continuous data-layers. Habitat maps were made from classified layers using GIS overlays, and were interpreted from a biophysical-process perspective. Biogeochemistry and %mud varied spatially and temporally, even in visually homogeneous sediments. Species turnover across patch-types was important for diversity, and the utility of habitat maps for differentiating biological communities varied across months. Diversity patterns were broadly related to reactive carbon and redox which varied temporally. Inclusion of biogeochemical factors and time in habitat maps provides a better framework for differentiating species and interpreting biodiversity patterns than once-off studies based solely on sedimentology or video-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 Eden, NSW CRA. CD1 contains original and 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. CD2 contains the DEFUNCT directories, data that has been modified or replaced in the final version. CD3 contains the INTEGRTN directory, integration data used for evaluating options.

Community concern about changes in the earth's environment has intensified during the past decade. The Government's response is reflected in the Prime Minister's statement on the Environment, in the setting up of the Resource Assessment Commission to investigate the developmental and environmental use of resources, and in the ASTEC review of environmental research in Australia. There is increasing recognition that science provides the framework for the protection of the Australian environment and for the responsible use of its resources. The geosciences are vital for the understanding of the environment, the development of essential resources, and the simultaneous conservation of environmental quality and diversity. The Government's new charter for BMR, tabled in the Senate in June 1989, recognised the need for BMR to provide the knowledge base for the resolution of environmental issues. For BMR to respond to the increasing demand for geoscientific base line data and advice in the context of sustainable development for Australia, it needs to identify the areas of geoscience necessary to take on a new role in understanding and conserving Australian earth resources in parallel with its traditional role of guiding the development of those resources. It is proposed that new environmental projects should be managed under a new Unit of Environmental Geoscience. For 1989/90 the development of the program will require approximately 1% of BMR resources - in professional staff and funding. In 1990/91, expenditure should be close to 2%. For fully operational programs in 1991/92 we estimate costs will be around 5-6% of total BMR resources.

From February to March 2010, Geoscience Australia (GA) conducted an multibeam survey of the coastal waters of the Vestfold Hills in the Australian Antarctic Territory. The survey was conducted jointly with Australian Antarctic Division (AAD) and the Deployable Geospatial Survey Team (DGST) of the Royal Australian Navy. The survey was aimed primarily at understanding the the character of the sea floora round Davis to better inform studies of the benthic biota and the possible impacts of the Davis Station sewage outfall. DGST were involved so the data could be used to update and extend the nautical charts of the Davis area.

This chapter presents a broad synthesis and overview based on the 57 case studies included in Part 2 of this book, and on questionnaires completed by the authors. The case studies covered areas of seafloor ranging from 0.15 to over 1,000,000 km2 (average of 26,600 km2) and a broad range of geomorphic feature types. The mean depths of the study areas ranged from 8 to 2,375 m, with about half of the studies on the shelf (depth <120 m) and half on the slope and at greater depths. Mapping resolution ranged from 0.1 to 170 m (mean of 13 m). There is a relatively equal distribution of studies among the four naturalness categories: near-pristine (n=17), largely unmodified (n = 16), modified (n=13) and extensively modified (n=10). In terms of threats to habitats, most authors identified fishing (n=46) as the most significant threat, followed by pollution (n=12), oil and gas development (n=7) and aggregate mining (n=7). Anthropogenic climate change was viewed as an immediate threat to benthic habitats by only three authors (n=3). Water depth was found to be the most useful surrogate for benthic communities in the most studies (n=17), followed by substrate/sediment type (n=14), acoustic backscatter (n=12), wave-current exposure (n=10), grain size (n=10), seabed rugosity (n=9) and BPI/TPI (n=8). Water properties (temperature, salinity) and seabed slope are less useful surrogates. A range of analytical methods were used to identify surrogates, with ARC GIS being by far the most popular method (23 out of 44 studies that specified a methodology).

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.

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.