This dataset contains the sea surface temperature data derived from the MODIS Terra sensor, the chlorophyll data derived from the SeaWIFS satellite, and the K490 data derived from the SeaWIFS satellite. Ocean temperature is a useful indicator of the type of marine life that could be found at a particular location. Many marine plants and organisms have a relatively narrow range of tolerance for temperature, and will either perish or be out-competed where temperatures are outside their comfort zone. Chlorophyll a is a plant pigment which provides a measurement of the biomass (or quantity) of plants. In the water column, it is a measure of the suspended (or planktonic) biomass of single-celled microscopic plants. Chlorophyll is a commonly used measure of water quality. K490 indicates the turbidity of the water column; the depth to which the visible light in the blue-green region of the spectrum penetrates the water column. It is directly related to the presence of particles in the water column. Turbidity has consequences for benthic marine life, ranging from the availability of light to the quantity of nutrients in the water column. The datasets contain 6 grids. Two for each variable: mean and standard deviation. Please see the metadata for detailed information.

No abstract available

Geoscience Australia has been updating its collection of navigation for marine surveys in Australia. These include original navigation files, the 2003 SNIP navigation files and survey track maps along with survey acquisition reports. The result will be an updated cleansed navigation collection. The collection is based on the standard P190 extended header navigation file which follows the UKOOA standard. Industry standard metadata associated with a seismic survey is preserved. To assist industry, Geoscience Australia is making available its updated version of cleansed navigation. Although the process of updating the navigation data is ongoing and there is still legacy data to check, the navigation data is at point where a significant improvement has been achieved and it is now usable. Users should be aware that this navigation is not final and there may be errors. The KML file can be viewed using a range of applications including Google Earth, NASA WorldWind, ESRI ArcGIS Explorer, Adobe PhotoShop, AutoCAD3D or any other earth browser (geobrowser) that accepts KML formatted data. Alternatively the Shapefiles can be downloaded and viewed using any application that supports shape files.

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In early 2014 the RVIB Nathaniel B. Palmer conducted the first ever multidisciplinary study of the Sabrina Coast continental shelf. This area is remote and generally inaccessible, but biological significance is recognised by its initial inclusion within the proposed East Antarctic representative system of Marine Protected Areas. The datasets collected during this voyage allow analysis of the physical habitat parameters and benthic biota through interpretation of bottom camera images, high resolution multibeam bathymetry, sediment properties and oceanographic measurements, with satellite observations of sea ice also providing important environmental context. The suite of environmental and biological datasets provides evidence for a diverse, relatively high biomass continental shelf community that is strongly structured by the physical environment. The distribution of benthic taxa is most closely related ( = 0.592) to seafloor bathymetry, substrate type, latitude and the occurrence of phytodetritus. Phytodetritus accumulation is associated with muddy/sandy substrates, indicating long term sediment focussing in these areas, consistent with evidence of bottom recirculation features. These softer substrates contain relatively high abundances of mobile holothurians and amphipods. Scattered occurrence of dropstones creates habitat heterogeneity at fine-scales. Harder substrates have high abundances of brachiopods, bryozoans, polychaete tubeworms, a range of massive and encrusting sponges and sea whips. Several taxa are found only on areas of hard substrate, yet have a broad distribution across the sites, indicating that the density of dropstones is sufficient for most sessile invertebrates to disperse across the region. The occurrence of dropstones is associated with significant increases in taxa diversity, abundance and percent biological cover, enhancing the overall diversity and biomass of this ecosystem. This study illustrates how multidisciplinary studies can inform understanding of the drivers of benthic ecosystems, providing important constraints for generating realistic ecosystem models and contributing to our understanding of the sensitivity of this community to environmental change.

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. This is a folder of the images derived from benthic samples taken on cruise Sol4769 aboard RV Solander. Subfolders house images of Echinodermata, Mollusca, Polychaete, images taken of fresh material during cruise, and various categories of Crustacea, denoted by a C_ prefix in the folder name. Images of fresh material were made using a Canon EOS 40D camera on a rostrum in the wet lab of the ship. Images of preserved material were made using a Nikon Coolpix camera mounted on a Macroscope in the benthic lab at GA. These images formed the first point of reference in identifying subsequent specimens to save wear and tear on the specimens put aside as reference material.

No abstract available

This dataset contains species identifications of all taxa collected from grabs during survey SOL4934 (R.V. Solander, 27 August - 24 September, 2009). Animals were collected from the Joseph Bonaparte Gulf with a Smith-MacIntyre grab. Echinoderms, molluscs, and worms were identified by taxonomists Tim O'Hara, Richard Willan, and Belinda Glasby, respectively, and lodged at museums. All other taxa were identified to operational taxonomic units by Rachel Przeslawski and lodged at the Australian Museum on the 27 August 2011. See GA Record 2010/09 for further details on survey methods and specimen acquisition.

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

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