This introductory chapter provides an overview of the book's contents and definitions of key concepts including benthic habitat, potential habitat and seafloor geomorphology. The chapter concludes with a summary of commonly used habitat mapping technologies. Benthic (seafloor) habitats are physically distinct areas of seabed that are associated with particular species, communities or assemblages that consistently occur together. Benthic habitat maps are spatial representations of physically distinct areas of seabed that are associated with particular groups of plants and animals. Habitat maps can illustrate the nature, distribution and extent of distinct physical environments present and importantly they can predict the distribution of the associated species and communities.

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.

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.

This dataset contains species identifications of all taxa collected from grabs during survey SOL4934 (R.V. Solander, 27 August - 24 September, 2009). Animals were collected from the Joseph Bonaparte Gulf with a Smith-MacIntyre grab. Echinoderms, molluscs, and worms were identified by taxonomists Tim O'Hara, Richard Willan, and Belinda Glasby, respectively, and lodged at museums. All other taxa were identified to operational taxonomic units by Rachel Przeslawski and lodged at the Australian Museum on the 27 August 2011. See GA Record 2010/09 for further details on survey methods and specimen acquisition.

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® element contents. Results to date indicate a common spatial coincidence of elevated commodity element concentrations near areas of known mineralisation, for instance of U, Au and REEs. The survey data also identifies areas with elevated concentrations of energy and ore-related elements away from known deposits or occurrences, information which may be useful to the exploration industry. Comparison with airborne radiometric data indicates reasonable correlations between ground and airborne concentrations of K, U and Th. The phenomenon of disequilibrium in the radioactive decay chain of U does lead to some insights about leaching and accumulation of the more mobile daughter products (e.g., Rn, Ra). A continental-scale correction factor for airborne gamma-ray U surveys applicable to depositional areas is being developed.

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.

The Coorong, a shallow coastal lagoon at the mouth of the Murray River, has had a significant decline in water quality over the last 15 years because of reduced freshwater inflows. Salinity has increased throughout the lagoon and currently ranges between 60 and 190 psu depending on the proximity to the Murray Mouth and the season. Although nutrient inflow has been negligible in recent years, the lagoon is considered euthrophic. This study aimed to identify the source of nutrients and the biogeochemical processes that transform them. The key findings were: 1. Groundwater discharge is likely to be an important nutrient source 2. Nitrogen appears to be the nutrient limiting primary production 3. Decomposition of organic matter in the sediments is highly seasonal with much higher rates in the summer.

This atlas volume summarises historic geographical knowledge about Australia's soil resources and land use and complements the other environmental and resource topics in the Atlas of Australia Resource Series. The following volumes in this series are also available: <ul><li><a href="https://www.ga.gov.au/products/servlet/controller?event=GEOCAT_DETAILS&amp;catno=60922">Volume 3: Atlas of Australian Resources Third Series - Agriculture (1982 (edition)</a></li> <li><a href="https://www.ga.gov.au/products/servlet/controller?event=GEOCAT_DETAILS&amp;catno=60924">Volume 5: Atlas of Australian Resources Third Series - Geology and Minerals (1988 edition)</a> </li> <li><a href="https://www.ga.gov.au/products/servlet/controller?event=GEOCAT_DETAILS&amp;catno=60925">Volume 6: Atlas of Australian Resources Third Series - Vegetation (1990 edition)</a></li> </ul> <strong>The following PDFs have been reproduced in A3 format, for best results please print on A3 paper (297mm x 420mm).</strong>

The upper Swan River estuary located in the eastern suburban area of Perth in Western Australia experiences periods of poor water quality in the form high nutrient levels, anoxic bottom water conditions and occasional nuisance algae blooms. It has long been suspected that oxygen uptake and nutrient release from estuarine sediments are major drivers for these poor water quality conditions. Geoscience Australia in conjunction with the Department of Water in Western Australia investigated water quality in the upper Swan River estuary through water and sediment quality studies in October 2006, September 2007 and May 2008. The objectives of these studies were (1) to characterise the distribution of sediments, in particular to identify areas of high nutrient release, (2) to better understand conditions leading to high oxygen consumption and nutrient release, and (3) to determine the influence of the bottom water oxygen status on nutrient release from sediments.