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  • Geoscience Australia marine reconnaissance survey TAN0713 to the Lord Howe Rise offshore eastern Australia was completed as part of the Federal Government¿s Offshore Energy Security Program between 7 October and 22 November 2007 using the New Zealand Government¿s research vessel Tangaroa. The survey was designed to sample key, deep-sea environments on the east Australian margin (a relatively poorly-studied shelf region in terms of sedimentology and benthic habitats) to better define the Capel and Faust basins, which are two major sedimentary basins beneath the Lord Howe Rise. Samples recovered on the survey contribute to a better understanding of the geology of the basins and assist with an appraisal of their petroleum potential. They also add to the inventory of baseline data on deep-sea sediments in Australia. The principal scientific objectives of the survey were to: (1) characterise the physical properties of the seabed associated with the Capel and Faust basins and Gifford Guyot; (2) investigate the geological history of the Capel and Faust basins from a geophysical and geological perspective; and (3) characterise the abiotic and biotic relationships on an offshore submerged plateau, a seamount, and locations where fluid escape features were evident. This dataset comprises total oxygen uptake and total carbon fluxes from core incubation experiments. Some relevant publications which pertain to these datasets include: 1. Heap, A.D., Hughes, M., Anderson, T., Nichol, S., Hashimoto, T., Daniell, J., Przeslawski, R., Payne, D., Radke, L., and Shipboard Party, (2009). Seabed Environments and Subsurface Geology of the Capel and Faust basins and Gifford Guyot, Eastern Australia ¿ post survey report. Geoscience Australia, Record 2009/22, 166pp. 2. Radke, L.C. Heap, A.D., Douglas, G., Nichol, S., Trafford, J., Li, J., and Przeslawski, R. 2011. A geochemical characterization of deep-sea floor sediments of the northern Lord Howe Rise. Deep Sea Research II 58: 909-921

  • ESRI Grids of available bathymetry within the bounds of proposed Marine Protected Areas in the Antarctic. Interpolated datasets are also included.

  • Submarine canyons are recognised as having an influence on oceanographic processes, sediment transport, productivity and benthic biodiversity from the shelf to the slope. However, not all canyons are the same and the relative importance of an individual canyon will, in part, be determined by its form, shape and position on the continental margin. Here we present an analysis of these parameters using an updated national dataset of 713 submarine canyons for the margin of mainland Australia. Attribute data for each canyon is used to classify them into canyon types across a hierarchy of canyon physical characteristics for shelf-incised and slope-confined (blind) canyons. At each level on the hierarchy, large groupings of canyons are identified that represent common sets of characteristics. The spatial distribution of canyons on the Australian margin is not regular, with clusters located in the east, southeast, west and southwest. The northern margin has the lowest concentration of canyons. We also assess the potential productivity associated with the various canyon types using chlorophyll-a data derived from satellite (MODIS) images. Shelf-incised canyons are associated with significantly higher and more temporally variable chlorophyll-a concentrations, consistent with their function as conduits for upwelling. Australian submarine canyons are well represented in the national network of marine protected areas, with 36 percent of the mapped canyon population intersecting (whole or in part) a Commonwealth Marine Reserve. This information is relevant to setting priorities for the management of these reserves. Results from this study provide a framework for further analysis of the relative importance of canyons on the Australian margin.

  • As part of Geoscience Australia's commitment towards the National Environmental Programme's Marine Biodiversity Hub, we have developed a fully four-dimensional (3D x time) Lagrangian biophysical dispersal model to simulate the movement of marine larvae over large, topographically complex areas. The model operates by fusing the results of data-assimilative oceanographic models (e.g. BLUELink, HYCOM, ROMS) with individual-based particle behaviour. The model uses parallel processing on Australia's national supercomputer to handle large numbers of simulated larvae (on the order of several billion), and saves positional information as points within a relational database management system (RDBMS). The model was used to study Australia's northwest marine region, with specific attention given to connectivity patterns among Australia's north-western Commonwealth Marine Reserves and Key Ecological Features (KEFs). These KEFs include carbonate terraces, banks and reefs on the shelf that support diverse benthic assemblages of sponges and corals, and canyons that extend from the shelf edge to the continental slope and are potential biodiversity hotspots. We will show animations of larval movement near canyons within the Gascoyne CMR; larval dispersal probability clouds partitioned by depth and time; as well as matrices of connectivity values among features of interest. We demonstrate how the data can be used to identify connectivity corridors in marine environments, and how the matrices can be analysed to identify key connections within the network. Information from the model can be used to inform priorities for monitoring the performance of reserves through examining net contributions of different reserves (i.e. are they sources or sinks), and studying changes in connectivity structure through adding and removing reserve areas.

  • 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.

  • Fisheries groups worldwide are concerned that seismic operations negatively affect catch rates within a given area, although there is a lack of field-based scientific evidence. In southeast Australia, marine seismic surveys have been blamed for mass mortalities of benthic invertebrates including the commercial scallop Pecten fumatus. Geoscience Australia conducted a 2-D seismic survey in this region in April 2015, thereby presenting an opportunity to conduct field-based experiments investigating the potential impacts on marine organisms. Moored hydrophones recorded noise before and during the seismic survey. An Autonomous Underwater Vehicle (AUV) was used to evaluate the effectiveness of seafloor images to support scallop monitoring. In addition, more traditional sampling was undertaken using a commercial scallop dredge from which a variety of biological and biochemical variables were analysed. The AUVs and dredge were deployed at three time periods (before the seismic survey, 2 months after seismic operations ceased, 10 months after seismic operations ceased), although poor-quality AUV images acquired before the survey precluded the analysis of these data. The highest sound exposure level recorded by the hydrophones was 146 dB re 1 µPa2s at 51 m water depth, at a distance of 1.4 km from the airguns. Commercial scallops were not abundant in the study area, and analysis of AUV images revealed no differences in commercial scallop types (live, clapper, dead shell, other) between experimental and control zones. Similarly, analysis of dredged scallops shows no detectable impact due to seismic activity on shell size, meat size and condition, gonad size and condition, and biochemical indices. Both AUV and dredging data showed strong spatial patterns, with significant differences between sites. Our study confirms previous work showing no evidence of immediate mortality on scallops in the field, and it expands this to include no evidence of long-term or sub-lethal effects. Negative impacts are currently confined to laboratory settings with unrealistic sound exposures. If short-term effects are investigated, we recommend a focus on the underlying mechanisms of potential impacts (i.e. physiological responses), rather than gross metrics such as mortality or size. Physiological responses to airgun sound may not be as immediately obvious as mortality or behavioural responses, but they are equally important to provide early indications of negative effects, as well as to explain the underlying mechanisms behind mortality events and reduced catch.

  • Submarine canyons are highly energetic and dynamic environment. Owing to their abrupt and complex topographies that are contrast to the adjacent shelf and slope, they can generate intense mixing, both horizontally through internal tides and waves and vertically through upwelling and downwelling. Complex hydrodynamic processes and increased food supply in sediment and water column result in elevated primary and secondary production which would favour the development of a highly productive and temporally dynamic food web over the canyons. Consequently, many submarine canyons, especially those incise into continental shelf, are considered as biodiversity hotspots. To better understand the ecosystem functions and ecological processes of marine environment, identification and classification of submarine canyons are needed. This study developed a national-scale submarine canyon classification system for Australian ocean based on canyon's physical characteristics. A hierarchical classification scheme was proposed. At the top level, the submarine canyons were classified into shelf-incising canyons and confined-to-slope canyons. At the lower levels, the canyons were classified on their morphometry, shape and location characteristics separately. Accurate identification of submarine canyons was the critical first step for the success of the proposed canyon classification system. A national bathymetry data at a spatial resolution of 250 metres and a completed set of multibeam bathymetry data at a spatial resolution of 50 metres from all previous multibeam surveys, both published by Geoscience Australia, were used. Hill-shaded layers were generated from which most submarine canyons could be easily identified. The extents of individual canyons, from wall to wall, were manually digitised as a GIS polygon layer. The initial number of canyons was then filtered using the following criteria: - Depth of the canyon head is less than 4000 m, - Depth range between the canyon's head and foot is greater than 600 m, and - Incision of the canyon head is greater than 100 m. At the lower levels, the following metrics were calculated as the inputs to the canyon classifications: - Morphometry metrics: incision depth of the canyon head, standard deviation of the slope gradient (within all cells in a canyon), slope gradient between the canyon head and the canyon foot, and canyon overall rugosity. - Shape metrics: canyon area, number of branches, length/width ratio of the smallest bounding rectangle, border index, compactness and canyon volume. - Location metrics: depth of the canyon head, depth range between the canyon's head and foot, canyon density, distance to coast, distance to the shelf break, incision depth (shelf-incising canyons only), and incision area (shelf-incising canyons only). The hierarchal agglomerative clustering technique was used for the unsupervised classifications. After the filtering, a total of 708 submarine canyons were identified for the entire Australian EEZ. Among these 708 canyons, 134 of them incise into continental shelf; the rest are confined in continental slope. For the shelf-incising canyons, the morphometry, shape and location based classifications all resulted in three classes. Combining the three lower level classifications yielded 15 classes. For the slope-confined canyons, the morphometry, shape and location based classifications resulted in three, four and four classes, respectively. Combining the three lower level classifications yielded 37 classes. GeoHab 2013

  • Flythrough movie showing the bathymetry, seabed habitats and biota of the outer continental shelf within the Flinders Commonwealth Marine Reserve (CMR), offshore from Flinders Island northeast Tasmania. The bathymetric image is derived from multibeam sonar collected by Geoscience Australia in 2012 using a 30 kHz Simrad EM3002 system on RV Challenger. Videos and seabed images were collected by the University of Tasmania and CSIRO as part of the same field program. Key features on the shelf bathymetry include low profile reefs, flat sandy seabed and the heads of two submarine canyons. The reefs provide hard substrate for sponge gardens whereas the sand flats are mostly barren. The two submarine canyons are sites of local upwelling, and attract large schools of Tasmanian Striped Trumpeter. The Flinders CMR is a study site for the Marine Biodiversity Research Hub, funded through the National Environmental Research Program (NERP). ..

  • As part of Geoscience Australia's commitment towards the National Environmental Programme's Marine Biodiversity Hub, we have developed a fully four-dimensional (3D x time) biophysical dispersal model to simulate the movement of marine larvae over large, topographically complex areas. The model uses parallel processing on Australia's national supercomputer to handle large numbers of simulated larvae (on the order of several billion), and saves positional information as points within a relational database management system RDBMS). The model was used to study Australia's northwest marine region, with specific attention given to connectivity patterns among Australia's north-western Commonwealth Marine Reserves and Key Ecological Features (KEFs). These KEFs include carbonate terraces, banks and reefs on the shelf that support diverse benthic assemblages of sponges and corals, and canyons that extend from the shelf edge to the continental slope and are potential biodiversity hotspots. We will show animations of larval movement near canyons within the Gascoyne CMR; larval dispersal probability clouds partitioned by depth and time; as well as matrices of connectivity values among features of interest. We demonstrate how the data can be used to identify connectivity corridors in marine environments, and how the matrices can be analysed to identify key connections within the network. Information from the model can be used to inform priorities for monitoring the performance of reserves through examining net contributions of different reserves (i.e. are they sources or sinks), and studying changes in connectivity structure through adding and removing reserve areas.

  • The local Moran I grid calculates local autocorrelation of the bathymetry grid. It indicates local heterogeneity. The large and positive values represent positive autocorrelation or clumped pattern; the large negative values represent negative autocorrelation or checkerboard pattern; the values close to zero represent random local pattern. The grid was created from the bathymetry grid of Darwin Harbour. Please see the metadata of the bathymetry grid for details (GeoCat no: 74915).