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 colocated 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 wavegenerated 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. entrance_3m is an ArcINFO grid of entrance of Jervis Bay survey area produced from the processed EM3002 bathymetry data using the CARIS HIPS and SIPS software

Understanding the distribution and abundance of sponges and their associated benthic habitats is of paramount importance for the establishment and monitoring of marine reserves. Benthic sleds or trawls can collect specimens for taxonomic and genetic research, but these sampling methods can be too qualititative for many ecological analyses and too destructive for monitoring purposes. Advances in the use of underwater videography and still imagery for biodiversity habitat mapping and modelling have been used within Geoscience Australia to extract data related to sponge biodiversity patterns across three regions. In the new Oceanic Shoals Commonwealth Marine Reserve, sponge morphologies were characterized from still images to locate areas in which biodiversity may be high due to habitat-forming taxa. In the Carnarvon Shelf abundance of a target sponge (Cinachyrella sp.) was quantified from video to investigate relationships between biology and sediment characteristics. Around Lord Howe Island, benthic habitats are being analysed to the national standard of classification using both video and still images. Importantly specialists within ecology, geophysics and spatial statistics work together to integrate biological and physical data to provide unique and meaningful maps of predicted distributions and habitat suitability for key ecological benthic habitats.

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 colocated 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 wavegenerated 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. jb_s4 is an ArcINFO grid of southern part of Jervis Bay survey area (south4 is part of Darling RD grid) produced from the processed EM3002 bathymetry data using the CARIS HIPS and SIPS software

Marine benthic biodiversity can be quantified using a range of sampling methods, including benthic sleds or trawls, grabs, and imaging systems, each of which targets a particular community or habitat. Research studies often incorporate only one of these sampling methods in published results, and the generality of marine biodiversity patterns identified among different sampling methods remains unknown. In this study we use three biological collections obtained during a collaborative survey between Geoscience Australian and the Australian Institute of Marine Science to the Van Diemen Rise in northern Australia: 1) Infauna sampled from a Smith-McIntyre grab, 2) Epifauna sampled from a benthic sled, and 3) Biological communities identified from video. For each dataset, we investigated potential patterns of species richness and community structure in relation to depth, geomorphology, and study area, as well as the relationships between datasets. No gear type yielded data that was strongly correlated with depth, but different patterns were evident among gear types based on study area and geomorphology. Comparisons among datasets indicate that species richness from sleds and grabs are more strongly correlated with each other than with richness from video. Further research is planned to incorporate datasets from other regions and habitats in order to provide a general assessment of sampling methods used in the quantification of benthic marine biodiversity in Australasia.

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 colocated 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 wavegenerated 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. jb_s3 is an ArcINFO grid of southern part of Jervis Bay survey area (south3 is part of Darling RD grid) produced from the processed EM3002 bathymetry data using the CARIS HIPS and SIPS software

Discerning how marine ecosystems are linked through larval dispersal is essential for understanding demographic flow, investigating the development of population genetic structure, and for evaluating the potential responses of communities to climate change. This information is of critical importance when designing reserve networks, identifying key locations for restoration, controlling invasive species, and administering transboundary resources. As part of Geoscience Australia's commitment to the National Environmental Research Programme's Marine Biodiversity Hub, we have developed a fully four-dimensional (3D space x time) individual-based model that embeds artificially intelligent particles within real-world ocean flow fields, making it possible to examine expected dispersal patterns of marine larvae under a variety of conditions. The model fuses strategic biological behaviour with physical equations in a flexible manner through the use of object-oriented programming. We will discuss aspects of model development and testing, as well as practical issues relating to computing on the National Computing Infrastructure, and addressing large-scale data storage. We will also identify potential avenues for data analysis that can be used to inform environmental decision-making.

Geoscience Australia's GEOMACS model was utilised to produce hindcast hourly time series of continental shelf (~20 - 300 m depth) bed shear stress (unit of measure: Pascal, Pa) on a 0.1 degree grid covering the period March 1997 to February 2008 (inclusive). The hindcast data represents the combined contribution to the bed shear stress by waves, tides, wind and densitydriven circulation. Ecological data collected from Torres Strait suggests that bed shear stresses exceeding 0.4 Pa are important in determining the species present (Long, Bode, & Pitcher 1997). Although this data may not be representative of other regions or benthic communities, it has been utilised to calculate two parameters for determining the relationship between shear bed stress and the benthic community. One of the parameters, which is denoted by , and is calculated using; represents the stress in excess of 0.4 Pa integrated over time as a proportion of the total stress integrated over time, and is intended to represent the proportion of the total integrated stress that has some control on the benthic community (Hughes & Harris 2008).

This study demonstrates that seabed topography and geodiversity play key roles in controlling the spatial dynamics of large fish predators over macro-ecological scales. We compiled ten years of commercial fishing records from the Sea Around Us Project and developed continental-scale catch models for an assemblage of large open-water fish (e.g. tuna, marlins, mackerels) for Western Australia. We standardised catch rates to account for the confounding effects of year, gear type and species body mass using generalised linear models, from which relative indices of abundance were extracted. We combined these with an extensive array of geophysical, oceanographic, biological, and anthropogenic data to (1) map the location of pelagic hotspots and (2) determine their most likely mechanistic drivers. We tested whether submarine canyons promote the aggregation of pelagic fish, and whether geomorphometrics (measures of seafloor complexity) represent useful surrogate indicators of their numbers. We also compared predicted fish distributions with the Australian network of Commonwealth Marine Reserves to assess its potential to provide conservation benefits for highly mobile predators. Both static and dynamic habitat features explained the observed patterns in relative abundance of pelagic fish. Geomorphometrics alone captured more than 50% of the variance, and submarine canyon presence ranked as the most influential variable in the North bioregion. Seafloor rugosity and fractal dimension, salinity, ocean energy, current strength, and human use were also identified as important predictors. The spatial overlap between fish hotspots and marine reserves was very limited in most parts of the EEZ, with high-abundance areas being primarily found in multiple use zones where human activities are subject to few restrictions.

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 colocated 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 wavegenerated 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. jb_s2 is an ArcINFO grid of southern part of Jervis Bay survey area (south2 is part of Darling RD grid) produced from the processed EM3002 bathymetry data using the CARIS HIPS and SIPS software

Geoscience Australia's GEOMACS model was utilised to produce hindcast hourly time series of continental shelf (~20 - 300 m depth) bed shear stress (unit of measure: Pascal, Pa) on a 0.1 degree grid covering the period March 1997 to February 2008 (inclusive). The hindcast data represents the combined contribution to the bed shear stress by waves, tides, wind and densitydriven circulation. Included in the parameters that represent the magnitude of the bulk of the data are the quartiles of the distribution; Q25, Q50 and Q75 (i.e. the values for which 25, 50 and 75 percent of the observations fall below). Q50, or the 0.50 Quartile of the Geomacs output, represents the values for which 50% of the observations fall below (Hughes & Harris 2008).