This is a compilation of Seabed and Habitat Mapping Publications 2008 - 2010: GA Record 2008_20.pdf Vlaming Sub-Basin and Mentelle Basin: Environmental Summary GA Record 2008_23.pdf A Review of Spatial Interpolation Methods for Environmental Scientists GA Record 2009_02.pdf Carnarvon Shelf Survey Post-Survey Report GA Record 2009_09.pdf Ceduna Sub-basin: Environmental Summary GA Record 2009_10.pdf Mapping and characterising soft sediment habitats, and evaluating physical variables as surrogates of biodiversity in Jervis Bay, NSW GA Record 2009_12.pdf Temporal and fine-scale variation in the biogeochemistry of Jervis Bay GA Record 2009_13.pdf Review of Ten Key Ecological Features (KEFs) in the Northwest Marine Region GA Record 2009_22.pdf Seabed Environments and Subsurface Geology of the Capel and Faust basins and Gifford Guyot,Eastern Australia GA Record 2009_26.pdf Deep Sea Lebensspuren: Biological Features on the Seafloor of the Eastern and Western Australian Margin GA Record 2009_38.pdf Frontier basins of the west Australian continental margin: post-survey report of marine reconnaissance and geological sampling survey GA2476 GA Record 2009_42.pdf A Review of Surrogates for Marine Benthic Biodiversity GA Record 2009_43.pdf Southeast Tasmania Temperate Reef Survey Post-Survey Report GA Record 2010_09.pdf Seabed Environments of the Eastern Joseph Bonaparte Gulf, Northern Australia

The benthic (sea floor) component of the National Marine Bioregionalisation covers the 80% of Australia's Exclusive Economic Zone that lies beyond the continental shelf break. It provides a description of patterns of biological distributions and physical habitats on the seafloor. The Benthic Bioregionalisation Report is a technical document describing how the benthic bioregions were created. It includes descriptions of all the datasets used, details of each bioregion, and examples of how the physical data may be used to sub-divide the marine bioregions for management. An evaluation of the benthic bioregionalisation including strengths, weaknesses and future work is also contained in the report.

A growing need to manage marine biodiversity at local, regional and global scales cannot be met by applying the limited existing biological data sets. Abiotic surrogacy is increasingly valuable in filling the gaps in our knowledge of biodiversity hotspots, habitats needed by endangered or commercially valuable species and systems or processes important to the sustained provision of ecosystem services. This review examines the utility of abiotic surrogates across spatial scales with particular regard to how abiotic variables are tied to processes which affect biodiversity and how easily those variables can be measured at scales relevant to resource management decisions.

The dataset provides the spatially continuous data of the seabed gravel content (sediment fraction >2000 µm) expressed as a weight percentage ranging from 0 to 100%, presented in 0.01 decimal degree resolution raster format. The dataset covers the Australian continental EEZ, including seabed surrounding Tasmania. It does not include areas surrounding Macquarie Island, and the Australian Territories of Norfolk Island, Christmas Island, and Cocos (Keeling) Islands or Australia's marine jurisdiction off of the Territory of Heard and McDonald Islands and the Australian Antarctic Territory. This dataset supersedes previous predictions of sediment gravel content for the Australian Margin with demonstrated improvements in accuracy. Accuracy of predictions varies based on density of underlying data and level of seabed complexity. Artefacts occur in this dataset as a result of insufficient samples in relevant regions. This dataset is intended for use at national and regional scales. The dataset may not be appropriate for use at local scales in areas where sample density is insufficient to detect local variation in sediment properties. To obtain the most accurate interpretation of sediment distribution in these areas, it is recommended that additional samples be collected and interpolations updated.

A nationally-consistent wave resource assessment is presented for Australian shelf (<300 m) waters. Wave energy and power were derived from significant wave height and period, and wave direction hindcast using the AusWAM model for the period 1 March 1997 to 29 February 2008 inclusive. The spatial distribution of wave energy and power is available on a 0.1° grid covering 110'156° longitude and 7'46° latitude. Total instantaneous wave energy on the entire Australian shelf is on average 3.47 PJ. Wave power is greatest on the 3,000 km-long southern Australian shelf (Tasmania/Victoria, southern Western Australia and South Australia), where it widely attains a time-average value of 25-35 kW m-1 (90th percentile of 60-78 kW m-1), delivering 800-1100 GJ m-1 of energy in an average year. New South Wales and southern Queensland shelves, with moderate levels of wave power (time-average: 10-20 kW m-1; 90th percentile: 20-30 kW m-1), are also potential sites for electricity generation due to them having a similar reliability in resource delivery to the southern margin. Time-average wave power for most of the northern Australian shelf is <10 kW m-1. Seasonal variations in wave power are consistent with regional weather patterns, which are characterised by winter SE trade winds/summer monsoon in the north and winter temperate storms/summer sea breezes in the south. The nationally-consistent wave resource assessment for Australian shelf waters can be used to inform policy development and site-selection decisions by industry.

Australia's near-pristine estuaries are some of our most valuable natural assets, with many natural and cultural heritage values. They are important as undisturbed habitat for native plants and animals, for biodiversity conservation, as Indigenous lands and for tourism. They also support near-shore fisheries. In addition, by studying near-pristine estuaries, scientists can learn more about the way humans have changed natural systems. This information then feeds into natural resource management because it constitutes benchmark or baseline information against which similar information from more modified estuaries can be compared.

Map showing all of Australia's Maritime Jurisdiction north of approx 25°S . This includes areas around Cocos (Keeling) Islands and areas west of Christmas Island as well as those contiguous to the continent in the north. Included as one of the now 28 constituent maps of the "Australia's Maritime Jurisdiction Map Series" (GeoCat 71789). Depicting Australia's extended continental shelf approved by the Commission on the Limits of the Continental Shelf in April 2008, treaties and various maritime zones. Background bathymetry image is derived from a combination of the 2009 9 arc second bathymetry and topographic grid by Geoscience Australia and a grid by W.H.F. Smith and D.T. Sandwell, 1997. Background land imagery derived from Blue Marble, NASA's Earth Observatory. 3277mm x 1050mm (for 42" plotter) sized .pdf downloadable from the web.

Map showing all of Australia's Maritime Jurisdiction north of approx 25°S. Updated in June 2014 from "Australia's Maritime Jurisdiction North of 25°S" (GeoCat 71985) to conform with "Australian Maritime Boundaries 2014" data by Geoscience Australia. This includes areas around Cocos (Keeling) Islands and areas around Christmas Island as well as those contiguous to the continent in the north. Included as one of the now 28 constituent maps of the "Australia's Maritime Jurisdiction Map Series" (GeoCat 71789). Depicting Australia's continental shelf as proclaimed in the "Seas and Submerged Lands (Limits of Continental Shelf) Proclamation 2012" established under the "Seas and Submerged Lands Act 1973". Background bathymetry image is derived from a combination of the 2009 9 arc second bathymetry and topographic grid by Geoscience Australia and a grid by W.H.F. Smith and D.T. Sandwell, 1997. Background land imagery derived from Blue Marble, NASA's Earth Observatory. 3277mm x 1050mm (for 42" plotter) sized .pdf downloadable from the web.

In 2008, the performance of 14 statistical and mathematical methods for spatial interpolation was compared using samples of seabed mud content across the Australian Exclusive Economic Zone (AEEZ), which indicated that machine learning methods are generally among the most accurate methods. In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK) and inverse distance squared (IDS). We aim to identify the most accurate methods for spatial interpolation of seabed mud content in three regions (i.e., N, NE and SW) in AEEZ using samples extracted from Geoscience Australia's Marine Samples Database (MARS). The performance of 18 methods (machine learning methods and their combinations with OK or IDS) is compared using a simulation experiment. The prediction accuracy changes with the methods, inclusion and exclusion of slope, search window size, model averaging and the study region. The combination of RF and OK (RFOK) and the combination of RF and IDS (RFIDS) are, on average, more accurate than the other methods based on the prediction accuracy and visual examination of prediction maps in all three regions when slope is included and when their searching widow size is 12 and 7, respectively. Averaging the predictions of these two most accurate methods could be an alternative for spatial interpolation. The methods identified in this study reduce the prediction error by up to 19% and their predictions depict the transitional zones between geomorphic features in comparison with the control. This study confirmed the effectiveness of combining machine learning methods with OK or IDS and produced an alternative source of methods for spatial interpolation. Procedures employed in this study for selecting the most accurate prediction methods provide guidance for future studies.

A statistical assessment of wave, tide, and river power was carried out using a database of 721 Australian clastic coastal depositional environments to test whether their geomorphology could be predicted from numerical values. The geomorphic classification of each environment (wave- and tide-dominated deltas, wave- and tide-dominated estuaries, lagoons, strand plains, and tidal flats) was established independently from remotely sensed imagery. To our knowledge, such a systematic numerical analysis has not been previously attempted for any region on earth.