Geoscience Australia carried out marine surveys in Jervis Bay (NSW) in 2007, 2008 and 2009 (GA303, GA305, GA309, GA312) to map seabed bathymetry and characterise benthic environments through co-located sampling of surface sediments (for textural and biogeochemical analysis) and infauna, observation of benthic habitats using underwater towed video and stills photography, and measurement of ocean tides and wave-generated currents. Data and samples were acquired using the Defence Science and Technology Organisation (DSTO) Research Vessel Kimbla. Bathymetric mapping, sampling and tide/wave measurement were concentrated in a 3x5 km survey grid (named Darling Road Grid, DRG) within the southern part of the Jervis Bay, incorporating the bay entrance. Additional sampling and stills photography plus bathymetric mapping along transits was undertaken at representative habitat types outside the DRG. This 128 sample data set comprises major, minor and trace elements derived from x-ray fluorescence analysis of surface seabed sediments (~0-2 cm). Sediment surface area data are also presented.

Geoscience Australia carried out marine surveys in south-east Tasmania in 2008 and 2009 (GA0315) to map seabed bathymetry and characterise benthic environments through observation of habitats using underwater towed video. Data was acquired using the Tasmania Aquaculture and Fisheries Institute (TAFI) Research Vessel Challenger. Bathymetric mapping was undertaken in seven survey areas, including: Freycinet Pensinula (83 sq km, east coast and shelf); Tasman Peninsula (117 sq km, east coast and shelf); Port Arthur and adjacent open coast (17 sq km); The Friars (41 sq km, south of Bruny Island); lower Huon River estuary (39 sq km); D Entrecastreaux Channel (7 sq km, at Tinderbox north of Bruny Island), and; Maria Island (3 sq km, western side). Video characterisations of the seabed concentrated on areas of bedrock reef and adjacent seabed in all mapped areas, except for D Entrecastreaux Channel and Maria Island. Seabed sediment samples were collected by TAFI in August 2010 in a targeted area to the east of Tasman Peninsula. Samples were collected at 25 stations using a Van Veen grab, from which a 50 - 100 g sub-sample was taken and submitted to Geoscience Australia for analysis.

The overarching theme of this book (and for the GeoHab organisation in general) is that mapping seafloor geomorphic features is useful for understanding benthic habitats. Many of the case studies in this volume demonstrate that geomorphic feature type is a powerful surrogate for associated benthic communities. Here we provide a brief overview of the major geomorphic features that are described in the detailed case studies (which follow in Part II of this book). Starting from the coast we will consider sandy temperate coasts, rocky temperate coasts, estuaries and fjords, barrier islands and glaciated coasts. Moving offshore onto the continental shelf we will consider sandbanks, sandwaves, rocky ridges, shallow banks, coral reefs, shelf valleys and other shelf habitats. Finally, on the continental slope and deep ocean environments we will review the general geomorphology and associated habitats of escarpments, submarine canyons, seamounts, plateaus and deep sea vent communities.

Geoscience Australia carried out a marine survey on Carnarvon shelf (WA) in 2008 (SOL4769) to map seabed bathymetry and characterise benthic environments through colocated sampling of surface sediments and infauna, observation of benthic habitats using underwater towed video and stills photography, and measurement of ocean tides and wave generated currents. Data and samples were acquired using the Australian Institute of Marine Science (AIMS) Research Vessel Solander. Bathymetric mapping, sampling and video transects were completed in three survey areas that extended seaward from Ningaloo Reef to the shelf edge, including: Mandu Creek (80 sq km); Point Cloates (281 sq km), and; Gnaraloo (321 sq km). Additional bathymetric mapping (but no sampling or video) was completed between Mandu creek and Point Cloates, covering 277 sq km and north of Mandu Creek, covering 79 sq km. Two oceanographic moorings were deployed in the Point Cloates survey area. The survey also mapped and sampled an area to the northeast of the Muiron Islands covering 52 sq km. Sample diversity indices calculated in PRIMER (version 6) using the species level data from Carnarvon_infauna(26_Oct_2010).xls

The Lord Howe Island survey SS06-2008 in April 2008 aboard the RV Southern Surveyor was a collaboration between the University of Wollongong and Geoscience Australia. The survey was also an activity of the Commonwealth Environment Research Facilities' (CERF) Marine Biodiversity Hub, of which Geoscience Australia is a partner, and will contribute to the revised Plan of Management for the Lord Howe Marine Parks. The objectives of the survey were to map the morphology and benthic environments of the shallow shelf that surrounds Lord Howe Island as well as the deeper flanks of this largely submarine volcano. Of particular interest was the apparent drowned reef structure on the shelf and the spatial distribution of seabed habitats and infauna. The data collected are required to better understand the history of reef growth at Lord Howe Island, which sits at the southernmost limit of reef formation, and links between the physical environment and ecological processes that control the spatial distribution of biodiversity on the shelf. The morphology of the flanks of the submarine volcano was also examined to reveal whether they provide evidence of major erosional and depositional processes acting on the volcano. This report provides a description of the survey activities and the results of the processing and initial analysis of the data and samples collected.

The Carnarvon Shelf Survey (SOL4769, GA survey #0308) was conducted on the R.V. Solander in collaboration with the Australian Institute of Marine Science between 12 August and 15 September 2008. The survey was operated as part of the Surrogates Program of the CERF Marine Biodiversity Hub. The survey was completed under a Memorandum of Understanding between GA and the AIMS and represents the first of three surveys planned under this agreement. The objective was to collect high-quality, accurately co-located data to enable the robust testing of a range of physical parameters as surrogates of patterns of benthic biodiversity. Underwater video footage and still images were collected from 122 stations from water depths of 13-125 m, although video quality varies among transects and some still images were not of suitable quality for analysis. Images from the still camera can be found in 'Image Library', and images from towed video screen captures can be found in 'Tow Video Stills'. Image files from screen captures are named according to area (1 = Mandu, 2 = Point Cloates, 3 = Gnarloo) followed by the station number and video identifier (TVA1). For example, 2_032TVA1 would represent a towed video transect from Station 32 at Point Cloates. See GA Record 2009/02 (Geocat #68525) for further details. Video footage was recorded to mini DV tapes, and copied to digital format. The original mini DV tapes are archived at AIMS-WA.

The identification of marine habitats based on physical parameters is increasingly important for marine reserve design, allowing characterisation of habitat types over much wider areas than is possible from often patchy biological data. Marine management zones often contain a wide array of physical environments, which may not be captured in the biological sampling effort. The mismatch between biological and physical information leads to uncertainty in the application of bio-physical relationships at the broader management scale. In this study, a case study from northern Australia is used to demonstrate a methodology for defining uncertainties which result from the extrapolation of bio-physical associations across areas where detailed biological data is absent. In addition, uncertainties relating to the interpolation of physical data sets and that resulting from the cluster analysis applied to the physical data are calculated and mapped, providing marine managers with greater robustness in their analysis of habitat distributions.

Geoscience Australia carried out a marine survey on Carnarvon shelf (WA) in 2008 (SOL4769) to map seabed bathymetry and characterise benthic environments through co-located sampling of surface sediments and infauna, observation of benthic habitats using underwater towed video and stills photography, and measurement of ocean tides and wave-generated currents. Data and samples were acquired using the Australian Institute of Marine Science (AIMS) Research Vessel Solander. Bathymetric mapping, sampling and video transects were completed in three survey areas that extended seaward from Ningaloo Reef to the shelf edge, including: Mandu Creek (80 sq km); Point Cloates (281 sq km), and; Gnaraloo (321 sq km). Additional bathymetric mapping (but no sampling or video) was completed between Mandu creek and Point Cloates, covering 277 sq km and north of Mandu Creek, covering 79 sq km. Two oceanographic moorings were deployed in the Point Cloates survey area. The survey also mapped and sampled an area to the northeast of the Muiron Islands covering 52 sq km.. 0308_carnarvon_shelf contains processed multibeam backscatter data of the Carnarvorn Shelf. The SIMRAD EM3002 multibeam backscatter data were processed using the CMST-GA MB Process, a multibeam processing toolbox co-developed by Geoscience Australia and Curtin University of Technology.

Seabed sediment textural parameters such as mud, sand and gravel content can be useful surrogates for predicting patterns of benthic biodiversity. Multibeam swath mapping can provide near-complete spatial coverage of high-resolution bathymetry and backscatter data that are useful in predicting sediment parameters. The multibeam acoustic data at a ~1000 km2 area of the Carnarvon Shelf, Western Australia was used in a predictive modeling approach to map eight seabed sediment parameters. The modeling results indicates overall satisfactory statistical performance, especially for %Mud, %Sand, Sorting, Skewness, and Mean Grain Size. The study demonstrated that predictive modelling using the combination of machine learning models has several advantages over the interpolation of Cokriging. Combing multiple machine learning models can not only improve the prediction performance but also provides the ability to generate useful prediction uncertainty maps. Another important finding is that choosing an appropriate set of explanatory variables, through a manual feature selection process, is a critical step for optimizing model performance. In addition, machine learning models are able to identify important explanatory variables, which is useful in explaining underlying environmental process and checking prediction against existing knowledge of the study area. The sediment prediction maps obtained in this study provide reliable coverage of key physical variables that will be incorporated into the analysis of co-variance of physical and biological data for this area. International Journal of Geographical Information Science

The dataset contains three grids. Each of the ArcINFO grids is an output of a finescale hydrodynamic model, the Simulating WAves Nearshore (SWAN) model (Booij et al., 1999; Ris et al., 1999).The grids describe the modelled maximum orbital velocity (m/s) which can be used as estimation of seabed exposure in Jervis Bay.