This dataset contains species identifications of molluscs collected during survey SOL5117 (R.V. Solander, 30 July - 27 August, 2010). Animals were collected from the Joseph Bonaparte Gulf with a benthic sled (SL) and Smith McIntyre grab (GR). Specimens were lodged at Northern Territory Museum on the 27 August 2010. Species-level identifications were undertaken by Richard Willan at the Northern Territory Museum and were delivered to Geoscience Australia on the December 2010 (for large samples) and 26 June 2012 (for smaller molluscs from grabs). See GA Record 2011/08 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. Comments: The following comments relate to live-taken specimens only: 1. The SOL5117 molluscan samples contain at least one new species (Talabrica sp.), one new record for Australia (Oliva rufofulgurata), and five new records for Commonwealth waters north of the Northern Territory (Strombus hickeyi, Trigonostoma textilis, Dentalium formosum, Phyllidiopsis shireeenae, Ceratosoma trilobatum). 2. Many of the molluscan species in the SOL5117 grab samples, both live individuals and dead shells, are represented only by tiny juveniles, so identification to species level is not possible because the shell characters change considerably as the species reaches maturity. 3. Clearly the majority of molluscs in the SOL5117 samples are represented by dead shells only. 4. Species richness is far higher than suggested by these samples. Judging from the range of species present in the SOL4934 and SOL5117 samples plus the accumulation of species through the samples, the molluscan biodiversity in this area would be between 400 and 500 species, the great majority micromolluscs (i.e., < 5 mm in greatest dimension). 5. The SOL5117 molluscan samples are not as comprehensive as the earlier SOL4934 samples taken in the same areas(s). 6. The SOL5117 molluscan samples provide us with hardly any picture of the composition or abundance of molluscs within or between the sites. 7. The SOL5117 molluscan samples should not be used to assess the conservation status of the submarine communities in the area(s) sampled. 8. More targeted and intensive sampling is required to appropriately measure molluscan diversity, abundance and communities in this region. ~ R Willan

The Vlaming Sub-basin Marine Survey GA-0334 was undertaken in March and April 2012 as part of the Commonwealth Government's National CO2 Infrastructure Plan (NCIP). The purpose was to acquire geophysical and biophysical data to help identify sites suitable for the long term storage of CO2 within reasonable distances of major sources of CO2 emissions. This dataset contains identifications of animals collected from 32 Van Veen grabs deployed during GA-0334. Sediment was elutriated for ~ 5 minutes over a 500um sieve. Retained sediments and animals were then preserved in 70% ethanol for later laboratory sorting and identification (see `lineage'). During sorting, all worms were separated and sent to Infaunal Data Pty Ltd (Lynda Avery) for identification to species or operational taxonomic unit (OTU). Lynda Avery completed identifications on 17 April 2013, and specimens were lodged at the Museum of Victoria. All other taxa were identified to morphospecies at GA by an ecologist. Gray shading indicates taxa identified to species level by Lynda Avery (Refer to GeoCat # 76463 for raw data of species identifications by taxonomist); all other taxa were identified to morphospecies. Data is presented here exactly as delivered by the taxonomist/ecologist, and Geoscience Australia is unable to verify the accuracy of the taxonomic identifications. Stations are named XXGRYY where XX indicates the station number, GR indicates Van Veen grabs, and YY indicates the sequence of grabs deployed (i.e. the YYth grab on the entire survey). H indicates heavy fraction animals and HS indicates animals found on a sponge. The dataset is current as of November 2014, but will be updated as taxonomic experts contribute. See GA Record 2013/09 for further details on survey methods and specimen acquisition.

The term 'surrogacy' is used in habitat mapping with reference to the biophysical variables that can be mapped with a quantifiable correspondence to the occurrence of benthic species and communities. Surrogacy research can be defined as an empirical method of determining which easily measured characteristics best describe the species assemblage in a particular space and at a particular time. These characteristics act as predictors (with some known probability and uncertainty) for the occurrence of species assemblages in unexplored areas. Abiotic variables are, in general, more easily and less expensively obtained than biological observations, which is a key driver for surrogacy research. However, the suite of abiotic factors that exert control over the occurrence of species (its niche) is also a scientifically interesting aspect of ecology that provides important insights into a species evolution and biogeography. This chapter provides a review of surrogates used by case study authors and of the methods used to quantify relationships between variables.

Permeable, sandy sediments cover most of the continental shelf. The important role of pore-water advective flow on biogeochemical processes in these sediments has been highlighted in recent studies. Such flow can be driven by wave-action, water-density and interactions between topography and bottom currents, in addition to biological activity, and can create spatially complex and highly dynamic benthic environments in which processes vary on timescales ranging from minutes to months. It is well known that the patchiness of soft sediment (organic matter/bacteria, particle diversity, redox) is likely to be a major determinant of species diversity, but previous studies have not specifically defined patches based on a range of biologically-relevant physico-chemical variables, nor observed how patches change across time. This study, as part of the Surrogates Program in the Commonwealth Environmental Research Facilities Marine Biodiversity Hub, investigated temporal changes in the geochemistry, physical sediments and infauna of sandy sediments in Jervis Bay at two times.

In a recent paper, Dye (2006) analyzed the distribution of species of macrobenthos and meiobenthos within two geomorphic facies of four small intermittently closed and open estuaries in New South Wales, Australia (colloquially known as ICOLLs). We believe that Dye's (2006) study is not an appropriate test of the Roy et al. (2001) habitat classification, and consequently several of the hypotheses posed by Dye do not follow logically from their model.

The Primary Coastal Sediment Compartment data set represents a regional-scale (1:250 000 - 1:100 000) compartmentalisation of the Australian coastal zone into spatial units within (and between) which sediment movement processes are considered to be significant at scales relevant to coastal management. The Primary and accompanying Secondary Coastal Sediment Compartment data sets were created by a panel of coastal science experts who developed a series of broader scale data sets (Coastal Realms, Regions and Divisions) in order to hierarchically subdivide the coastal zone on the basis of key environmental attributes. Once the regional (1:250 000) scale was reached expert knowledge of coastal geomorphology and processes was used to further refine the sub-division and create both the Primary and Secondary Sediment Compartment data sets. Environmental factors determining the occurrence and extents of these compartments include major geological structures, major geomorphic process boundaries, orientation of the coastline and recurring patterns of landform and geology - these attributes are given in priority order below. 1 - Gross lithological/geological changes (e.g. transition from sedimentary to igneous rocks). 2 - Geomorphic (topographic) features characterising a compartment boundary (often bedrock-controlled) (e.g. peninsulas, headlands, cliffs). 3 - Dominant landform types (e.g. large cuspate foreland, tombolos and extensive sandy beaches versus headland-bound pocket beaches). 4 - Changes in the orientation (aspect) of the shoreline.

Bathymetry is the study and mapping of the sea floor. It involves obtaining measurements of the depth of the ocean and is the equivalent to mapping topography on land. Bathymetric data is collected in multiple ways: 1. Satellite data can be used to produce maps showing general features over a large area at low resolution. Satellite altimetry measures the height of the ocean surface. If there are hills/mountains on the sea floor, the gravitational pull around that area will be greater and hence the sea surface will bulge. This measurement can be used to show where the seafloor is higher, and this can be used to produce maps showing general features over a large area at low resolution. 2. Single beam echosounders produce a single line of depth points directly under the equipment. These measurements are usually made while a vessel is moving to identify general sea floor patterns and/or schools of fish. 3. Equipment that captures swathes of data by acquiring multiple depth points in each area, such as multibeam echosounders (or swath echosounders) and airborne laser measurements (LADS). These datasets are very high resolution, with data down to better than one metre accuracy. This bathymetry dataset is a collection of singlebeam data sourced from seismic navigation lines, multibeam data, satellite and LADS data acquired by GA and by other government and non-government agencies.

The Divisions data set was created as one of three broad-scale data layers to facilitate the definition of Primary and Secondary compartments. The Divisions data is provided so that the logic of the compartment creation can be understood. With regards to spatial scale, the Divisions data set represents one of the mid-scale products, as shown in the hierarchical listing for all of the polygon data sets shown below: - Coastal Realms (1:5 000 000) - Coastal Regions (1:1 000 000) - Coastal Divisions (1:250 000) - Primary Compartments (1:250 000 - 1:100 000) - Secondary Compartments (1:100 000 - 1:25 000)

Geoscience Australia and CO2CRC have constructed a greenhouse gas controlled release reference facility to simulate surface emissions of CO2 (and other GHG gases) from an underground slotted horizontal well into the atmosphere under controlled conditions. The facility is located in a paddock maintained by CSIRO Plant and Industry at Ginninderra, ACT. The design of the facility is modelled on the ZERT controlled release facility in Montana, which conducts experiments to develop capabilities and test techniques for detecting and monitoring CO2 leakage. The first phase of the installation is complete and has supported an above ground, point source, release experiment, utilising a liquid CO2 storage vessel (2.5 tonnes) with a vaporiser, mass flow controller unit with a capacity for 6 individual metered gas outlet streams, equipment shed and a gas cylinder cage. Phase 2 involved the installation of a shallow (2m depth) underground 120m horizontally drilled slotted well, in June 2011, intended to model a line source of CO2 leakage from a storage site. This presentation will detail the various activities involved in designing and installing the horizontal well, and designing a packer system to partition the well into six CO2 injection chambers. A trenchless drilling technique used for installing the slotted HDPE pipe into the bore hole will be described. The choice of well orientation based upon the effects of various factors such as topography, wind direction and ground water depth, will be discussed. It is envisaged that the facility will be ready for conducting sub-surface controlled release experiments during spring 2011.

Data gathered in the field during the sample collection phase of the National Geochemical Survey of Australia (NGSA) has been used to compile the Preliminary Soil pH map of Australia. The map, which was completed in late 2009, offers a first-order estimate of where acid or alkaline soil conditions are likely to be expected. It provides fundamental datasets that can be used for mineral exploration and resource potential evaluation, environmental monitoring, landuse policy development, and geomedical studies into the health of humans, animals and plants.