From 1 - 10 / 215
  • In the past two decades, multibeam sonar systems have become the preferred seabed mapping tool. Many users have assumed that multibeam bathymetry data is highly accurate in spatial position. In reality, both vertical and horizontal uncertainties exist in every data point. These uncertainties are often represented as one single measure of Total Propagated Uncertainty (TPU). TPU is important to understand because it affects the quality of products generated from multibeam bathymetry data. To account for the magnitude and spatial distribution of this influence, an objective uncertainty analysis is required. Randomisation is the key process in such an uncertainty analysis. This study compared two randomisation methods, restricted spatial randomness (RSR) and complete spatial randomness (CSR), in an uncertainty analysis of a slope gradient dataset derived from multibeam bathymetry data. CSR regards data error in every grid cell as independent and assumes that the data error varies within a known statistical distribution without any neighbourhood effect. RSR assumes spatial structure and thus spatial auto-correlation in the data. We present a case study from a survey of the Oceanic Shoals Commonwealth Marine Reserve in the Timor Sea, conducted in 2012 by the Marine Biodiversity Hub through the Australian Government National Environmental Research Program. The survey area is characterised by steep-sided carbonate banks and terraces with abrupt breaks in slope of limited spatial extent. As habitats, the carbonate banks and terraces are important because they provide hardground for diverse epibenthic assemblages of sponges and corals, with their steep sides marking the environmental transition to deeper water, soft sediment habitats. In this analysis, the data errors in the multibeam bathymetry data were assumed to follow a Gaussian distribution with a mean of zero and a standard deviation represented by the TPU. The CSR and RSR methods were each implemented using a Monte Carlo procedure with 500 iterations. After about 300 iterations, the Monte Carlo procedure converged for both methods. Results for the study area are compared against pre-processed slope data (Figure 1a). The averaged slope gradient from the CSR method is 4.5 degree greater than the original slope layer, whereas for the RSR method this value is 0.03 degree. Moreover, the slope layer from the CSR method resolves noticeably less detail than the original slope layer and is an over-simplification of the true bathymetry (Figure 1b). In contrast, the RSR method maintained the spatial pattern and detail observed in the original slope layer (Figure 1c). This study demonstrates that although the uncertainty in multibeam bathymetry data should not be ignored, its impact on the subsequent derivative analysis may be limited. The selection of appropriate randomisation method is important for the uncertainty analysis. When the data errors exhibit spatial structure, we recommend using the RSR method.

  • A fully four-dimensional (3D x time) open source (BSD-3), object-oriented biophysical dispersal model was developed to simulate the movement of marine larvae over semi-continuous surfaces. The model is capable of handling massive numbers of simulated larvae, can accommodate diverse life history patterns and distributions of characteristics, and saves point-level information to a relational database management system. The model was used to study Australia's northwest marine region, with attention given to connectivity patterns among Australia's north-western Commonwealth Marine Reserves (CMRs). This work was supported by the Marine Biodiversity Hub through the Australian Government's National Environmental Research Program (NERP).

  • In September and October of 2011 Geoscience Australia surveyed part of the offshore northern Perth Basin in order to map potential sites of natural hydrocarbon seepage. The primary objectives of the survey were to map the spatial distribution of seepage sites and characterise the nature of the seepage at these sites (gas vs oil, macroseepage vs microseepage; palaeo vs modern day seepage) on the basis of: acoustic signatures in the water column, shallow subsurface and on the seabed; geochemical signatures in rock and sediment samples and the water column; and biological signatures on the seabed. Areas of potential natural hydrocarbon seepage that were surveyed included proven (drilled) oil and gas accumulations, a breached structure, undrilled hydrocarbon prospects, and areas with potential signatures of fluid seepage identified in seismic, satellite remote sensing and multibeam bathymetry data. Within each of these areas the survey acquired: water column measurements with the CTD; acoustic data with single- and multi-beam echosounders, sidescan sonar and sub-bottom profiler (sidescan not acquired in Area F as it was too deep in places); and sediment and biological samples with the Smith-McIntyre Grab. In addition, data were collected with a remotely operated vehicle (ROV), integrated hydrocarbon sensor array, and CO2 sensor in selected areas. Sampling with the gravity corer had limited success in many of the more shallow areas (A-E) due to the coarse sandy nature of the seabed sediments. This dataset comprises major and trace element concentrations in marine sediments.

  • The Australian Government, through Geoscience Australia, is tailoring its national seabed mapping program to support the implementation of policies aimed at delivering improved clean energy options for the nation. The current focus is upon the assessment of offshore sedimentary basins as potential sites for the geological storage of carbon dioxide (CO2). These assessments include targeted seabed research that aims to reduce uncertainty around the risks of CO2 storage by developing an integrated understanding of the physical connectivity between the deeper basin structures, the shallow (<100 m) sub-surface and seabed environments. This paper presents an overview of the science strategy developed to undertake this work in the Australian context, with reference to case studies.

  • 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).

  • The seascape of the vast Australian continental margin is characterised by numerous submarine canyons that represent an equally vast array of geomorphic and oceanographic heterogeneity. Theoretically, this heterogeneity translates into habitats that may vary equally widely in their ecological characteristics. Here we describe the methodology to develop a framework to broadly derive estimates of potential habitat condition (¿suitability¿ sensu lato) for pelagic and epibenthic megafauna (including demersal fishes), and benthic infauna in all of Australia¿s known submarine canyons. We find that the high geomorphic and oceanographic diversity of submarine canyons creates a multitude of potential habitat types. In general, it appears that canyons may be particularly high-quality for benthic species. Canyons that incise the shelf tend to score higher in habitat potential than those confined to the slope. Canyons with particularly high habitat potential are located mainly off the Great Barrier Reef, the NSW coast, the eastern margin of Tasmania and Bass Strait, and on the southern margin. Many of these canyons have complex bottom topography, are likely to be productive, and have less intense sediment disturbance regimes. The framework presented here can be relevant ¿ once refined and comprehensively validated with ecological data - in a management and conservation context to identify canyons (or groups of canyons) that are likely to represent high-value habitat along a vast continental margin where marine planning decisions may require spatial prioritization decisions. <b>Citation:</b> Zhi Huang, Thomas A. Schlacher, Scott Nichol, Alan Williams, Franziska Althaus, Rudy Kloser, A conceptual surrogacy framework to evaluate the habitat potential of submarine canyons, <i>Progress in Oceanography</i>, Volume 169, 2018, Pages 199-213, ISSN 0079-6611, https://doi.org/10.1016/j.pocean.2017.11.007

  • Population connectivity science involves investigating how populations are related to one another through biological dispersal. Here, we review tools, techniques and analyses used by connectivity researchers, and place them in the context of how they can be used by marine managers and policy-makers to enhance their decision-making capabilities. Specific examples of developing technologies include: advances in mark and recapture techniques, underwater imaging systems, population genetic analyses, as well as four-dimensional dispersal simulations (3D space x time). These data can then be analysed using a wide array of analyses, including matrix analysis, graph theory, and various GIS-based routines. The results can be used to identify key source and sink areas, critical linkages (keystones), natural clusters and groups, levels of accuracy, precision and variability, as well as areas of asymmetric exchange. In turn, this information can be used to help identify natural management units, to target critical conservation areas, to develop efficient sampling strategies through power analysis, and to negotiate equitable allocation of resources to upstream management in cases where downstream benefits are significant. Through a better understanding of how connectivity science can assist decision-making, we hope to encourage increased uptake of these kinds of information into institutional planning processes.

  • Submarine canyons have been recognised as areas of significant ecological and conservation value for their enhanced primary productivity, benthic biomass and biodiversity. In Australia, 753 submarine canyons were mapped on all margins of the continent by the Marine Biodiversity Hub through the Australian Government's National Environmental Research Program. An analysis of canyon geomorphic metrics provided the basis to objectively classify these canyons across a hierarchy of physical characteristics (e.g. volume, depth range, rugosity) separately for shelf-incising and slope-confined canyons (Huang et al., 2014). Here we extend this analysis to include oceanographic variables in presenting a first pass assessment of habitat quality for all canyons on the Australian margin, with a focus on their upper reaches. This study is based on the premise that habitat heterogeneity, productivity and disturbance are the three factors that potentially determine the quality of a canyon habitat. For each factor we derived a range of variables to inform the assessment of habitat quality (see Table). Habitat heterogeneity was measured using a selection of eight geomorphic metrics including canyon volume and rugosity that are considered likely to have a positive relationship with habitat heterogeneity. Canyon productivity was assessed from five variables including: distance to the shelf break as a proxy of nutrient inputs from land and the continental shelf; bottom current speed as an indicator of nutrient supply to benthic epifauna (derived from time-series re-analysis of the BLUElink oceanographic model and in-situ data), and; measures of the probability, frequency and intensity of upwelling (also from BLUElink data). The BLUElink variables have positive relationships with productivity whereas the relationship between distance to shelf and productivity is negative. Benthic disturbance was assessed from the maximum and range of bottom current speeds, and the frequency and intensity of tropical cyclones. According to these relationships, individual canyons were assigned habitat quality scores, first separately for each variable and then aggregated for the three habitat factors. The final scores were obtained by averaging the scores of the three habitat factors. The results show that many submarine canyons on the eastern Australian margin have high habitat quality scores (see Figure). This is interpreted to be mainly due to the influence of the upwelling-favourable East Australian Current which generates high productivity throughout the year. The Albany canyons on the south-western margin also offer high habitat quality for marine species due to complex geometrical and geophysical structures. They also benefit from the upwelling-favourable Flinders Current. In contrast, canyons on the northern and western margins have lower habitat quality. Many of these canyons receive little input from land and continental shelf. In addition, the downwelling- favourable Leeuwin Current, which flows along the western margin of the continent, hampers the supply of deep water nutrients from reaching the upper reaches of canyons, particularly canyon heads that intersect the euphotic zone. Overall, these results provide a framework for targeted studies of canyons aimed at testing and verifying the habitat potential identified here and for establishing monitoring priorities for the ongoing management of canyon ecosystems.

  • Geoscience Australia marine reconnaissance survey GA2476 to the west Australian continental margin was undertaken as part of the Australian Government's Offshore Energy Program between 25 October 2008 and 19 January 2009 using the German research vessel RV Sonne. The survey acquired geological, geophysical, oceanographic and biological data over poorly known areas of Australia's western continental margin in order to improve knowledge of frontier sedimentary basins and marginal plateaus, and allow assessment of their petroleum prospectivity and environmental significance. Four key areas were targeted: the Zeewyck and Houtman sub-basins (Perth Basin), the Cuvier margin (northwest of the Southern Carnarvon Basin), and the Cuvier Plateau (a sub-feature of the Wallaby Plateau). These areas were mapped using multi-beam sonar, shallow seismic, magnetics and gravity. Over the duration of the survey a total of 229,000 km2 (26,500 line-km) of seabed was mapped with the multibeam sonar, 25,000 line-km of digital shallow seismic reflection data and 25,000 line-km of gravity and magnetic data. Sampling sites covering a range of seabed features were identified from the preliminary analysis of the multi-beam bathymetry grids and pre-existing geophysical data (seismic and gravity). A variety of sampling equipment was deployed over the duration of the survey, including ocean floor observation systems (OFOS), deep-sea TV controlled grab (BODO), boxcores, rock dredges, conductivity-temperature depth profilers (CTD), and epibenthic sleds. Different combinations of equipment were used at each station depending on the morphology of the seabed and objectives of each site. A total of 62 stations were examined throughout the survey, including 16 over the Houtman Sub-basin, 16 over the Zeewyck Subbasin, 13 in the Cuvier margin, 12 over the Cuvier Plateau and four in the Indian Ocean. This dataset comprises total chlorin concentrations and chlorin indices measured on the upper 2 cm of seabed sediments. For more information: Daniell, J., Jorgensen, D.C., Anderson, T., Borissova, I., Burq, S., Heap, A.D., Hughes, M., Mantle, D., Nelson, G., Nichol, S., Nicholson, C., Payne, D., Przeslawski, R., Radke, L., Siwabessy, J., Smith, C., and Shipboard Party, (2010). Frontier Basins of the West Australian Continental Margin: Post-survey Report of Marine Reconnaissance and Geological Sampling Survey GA2476. Geoscience Australia, Record 2009/38, 229pp

  • 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 co-located 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 wave-generated currents. Data and samples were acquired using the Defence Science & 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. This 42 sample data set comprises the mineraology of surface seabed sediment (~0-2 cm) in Jervis Bay. More information: Radke, L.C., Huang, Z., Przeslawski, R., Webster, I.T., McArthur, M.A., Anderson, T.J., P.J. Siwabessy, Brooke, B. 2011. Including biogeochemical factors and a temporal component in benthic habitat maps: influences on infaunal diversity in a temperate embayment. Marine and Freshwater Research 62 (12): 1432 - 1448. Huang, Z., McArthur, M., Radke, L., Anderson, T., Nichol, S., Siwabessy, J. and Brooke, B. 2012. Developing physical surrogates for benthic biodiversity using co-located samples and regression tree models: a conceptual synthesis for a sandy temperature embayment. International Journal of Geographical Information Science DOI:10.1080/13658816.2012.658808.