The Leeuwin Current has significant ecological impact on the coastal and marine ecosystem of south-western Australia. This study investigated the spatial and temporal dynamics of the Leeuwin Current using monthly MODIS SST dataset between July 2002 and December 2012. Topographic Position Index layers were derived from the SST data for the mapping of the spatial structure of the Leeuwin Current. The semi-automatic classification process involves segmentation, 'seeds' growing and manual editing. The mapping results enabled us to quantitatively examine the current's spatial and temporal dynamics in structure, strength, cross-shelf movement and chlorophyll a characteristic. It was found that the Leeuwin Current exhibits complex spatial structure, with a number of meanders, offshoots and eddies developed from the current core along its flowing path. The Leeuwin Current has a clear seasonal cycle. During austral winter, the current locates closer to the coast (near shelf break), becomes stronger in strength and has higher chlorophyll a concentrations. While, during austral summer, the current moves offshore, reduces its strength and chlorophyll a concentrations. The Leeuwin Current also has notable inter-annual variation due to ENSO events. In El Niño years the current is likely to reduce strength, move further inshore and increase its chlorophyll a concentrations. The opposite occurs during the La Niña years. In addition, this study also demonstrated that the Leeuwin Current has a significantly positive influence over the regional nutrient characteristics during the winter and autumn seasons.

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

A biophysical dispersal model was used to simulate hydrodynamic connectivity among canyons located within Australia's South-west marine region. The results show that exchange among canyons in this area is greatly influenced by the Leeuwin current, transporting larvae in a unidirectional manner around Cape Leeuwin, and continuing eastwards along the Great Australian Bight. Larvae within canyons tend to remain within them, however if they are transported above the canyon walls, they then have the opportunity to be transported significant distances (thousands of kilometres). Analysis of the variability in connectivity patterns reveals concentrated flow near the shelf break, with increasing levels of variability leading offshore from the canyons. While the average potential flow distance and duration between canyons were approximately 550 kilometres and 33 days respectively, the average realized flow distance and duration were approximately 30 kilometres and 6 days respectively. This study provides the first consideration of connectivity among submarine canyons and will help improve management of these features by providing a better understanding of larval movement, transboundary exchange and the potential spread of invasive species.

Bathymetric flythrough of the Southeast Margin of Australia for a Powerpoint presentation on the Marine Geoscience capabilities of the RV Investigator. The presentation will be given at the Welcome to Port Ceremony for the ship.

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.

This dataset contains sediment and geochemistry information for the Oceanic Shoals Commonwealth Marine Reserve (CMR) in the Timor Sea collected by Geoscience Australia during September and October 2012 on RV Solander (survey GA0339/SOL5650). Further information on the survey is available in the post-survey report published as Geoscience Australia Record 2013/38: Nichol, S.L., Howard, F.J.F., Kool, J., Stowar, M., Bouchet, P., Radke, L., Siwabessy, J., Przeslawski, R., Picard, K., Alvarez de Glasby, B., Colquhoun, J., Letessier, T. & Heyward, A. 2013. Oceanic Shoals Commonwealth Marine Reserve (Timor Sea) Biodiversity Survey: GA0339/SOL5650 - Post Survey Report. Record 2013/38. Geoscience Australia: Canberra. (GEOCAT #76658).

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.

Acoustic remote sensing is the only effective technique to investigate deep sea bottom. Modern high-frequency multibeam echosounders transmit and receive backscatter signals from hundreds of narrow-angle beams which enlighten small footprints on the seabed. They can produce bathymetry and backscatter data with a spatial resolution around 2% of water depth, which enables us to map the seabed with great detail and accuracy. After calibration, the backscatter intensity is largely controlled by three seabed physical properties: the acoustic impedance contrast (often called hardness), apparent interface roughness (relative to acoustic frequency) and volume inhomogeneity [3, 4, 7]. These seabed physical properties are directly related to sediment grain size characteristics at the sedimentary areas. Studies showed that backscatter intensity had a moderate and positive correlation with sediment mean grain size [1, 3, 6]. Also, backscatter intensity was found to be positively correlated with coarse fractions and inversely correlated with finer fractions [2, 5, 6]. Other sediment grain size properties, especially sorting may also play important roles in the backscatter-sediment relationship [3, 5, 6]. The backscatter-sediment relationship, however, is complex in nature. Research is needed to better understand how acoustic sound interacts with sediment. This study aims to explore this relationship using a set of high quality sediment and multibeam backscatter data, and a robust spatial modelling technique. The co-located sediment and multibeam data were collected from four different areas of Australian margin which represent different sedimentary environments. Five hundred sixty-four sediment grab samples were taken from these survey areas. They were analysed in laboratory using the same procedure to generate grain size properties of %gravel, %sand, %mud, mean grain size, sorting, skewness and kurtosis. The multibeam data were collected using Kongsberg's 300 kHz EM3002 system. The raw multibeam backscatter was processed using the CMST-GA MB Process v8.11.02.1 software developed by Geoscience Australia and the Centre for Marine Science and Technology at Curtin University of Technology. As a result, the backscatter mosaics from incidence angles of 1o to 60o, at an interval of 1o, were generated. The backscatter intensity values from these 60 incidence angles were extracted for all of the sediment samples. The machine learning model Random Forest Decision Tree (RFDT) was used to investigate the backscatter-sediment relationship. The seven sediment grain size properties were the explanatory variables. The response variable was the backscatter intensity from each incidence angle. The model performance was evaluated using 10-fold cross-validation. For incidence angles between 1o and 42o, the RFDT models achieved fairly good performance, with a percentage of variance explained around 70% (Figure 1). The model performance gradually decreased for the outer beam range (incidence angle > 42o). Mud content was consistently identified as the most important explanatory variable to the backscatter strength. The second most important explanatory was usually sediment mean grain size. The RFDT models were also able to generate predicted response curves to quantitatively investigate the relationships between the important explanatory variables and individual response variables. The predicted relationship between %mud and the acoustic backscatter intensity is shown in Figure 2. This indicates a negative but non-linear relationship, with the increase of mud content in the sediment, the backscatter intensity decreases. This finding is consistent with that of previous studies [2, 5, 6]. Fine sediment with high mud content not only is soft (e.g., low impedence contrast) but also has high acoustic penetration (e.g., high attenudation in sediment), which naturally incurs low backcatter return

Geoscience Australia completed an underwater towed video survey (GA survey 0338) of the Shelf Rocky Reefs Key Ecological Feature (KEF) in the vicinity of the Solitary Islands in collaboration with the New South Wales Office of Environment and Heritage on the R.V. Bombora between 7 - 16 August 2012. The aim of the survey was to characterize benthic habitat in areas of the KEF, and to compare and contrast the effectiveness of different methods for capturing visual representations of biological communities. The survey collected forward-facing mono video, forward-facing stereo video, and downward facing stills along 12 transects, each of 2 km length. The geographic position of the vessel was determined using a GPS system, and the location of the towed camera body was recorded using a USBL system. The KEF survey was part of the National Marine Biodiversity Hub's National Monitoring Evaluation and Reporting Theme. The aim of this theme is to develop a blueprint for the sustained monitoring of the Commonwealth Marine Reserve Network, specifically; 1) to contribute to an inventory of demersal and epibenthic conservation values in the KEF and; 2) to test methodologies and deployment strategies in order to inform future survey design efforts. Embargo statement: Resource embargoed pending completion of NERP research. Release date 31 December 2014 Attribution statement: Users of NERP Marine Biodiversity Hub data are required to clearly acknowledge the source of the material in the format: "Data was sourced from the NERP Marine Biodiversity Hub" the Marine Biodiversity Hub is supported through funding from the Australian Government's National Environmental Research Program (NERP), administered by the Department of Sustainability, Environment, Water, Population and Communities (DSEWPaC)." Dataset name: National Environmental Research Program (NERP) Marine Biodiversity Hub, 2012, Flinders Commonwealth Marine Reserve Shelf Backscatter