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  • 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). Q25, or the 0.25 Quartile of the Geomacs output, represents the values for which 25% of the observations fall below (Hughes & Harris 2008).

  • 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.

  • This dataset contains identifications of arthropods collected during survey SOL4934 (R.V. Solander, 27 August - 24 September, 2009) and SOL5117 (R.V. Solander 30 July - 27 August, 2010). Animals were collected from the Joseph Bonaparte Gulf with a Smith McIntyre grab and identified to operational taxonomic units by an ecologist (Rachel Przeslawski). Specimens were lodged at the Australian Museum on the 27 August 2011. See GA Records 2010/09 2011/08 for further details on survey methods and specimen acquisition. The data files is organised into 3 spreadsheets: - 'arthropod list' presents identifications as they were entered in the laboratory during the identification process. 'Voucher' column refers to those specimens kept at Geoscience Australia as voucher specimens. 'Completion' refers to the order in which specimens and their operational taxonomic units were identified. - 'arthropod matrix' is the species composition matrix to be used for data analysis. Stations are listed as columns; species are listed as rows. - 'stations' includes the location and depth of each station from which grabs were deployed Arthropods were identified only to operational taxonomic unit by a non-taxonomist and so the accuracy of identifications is uncertain. See geocat no 72919 for all taxa identified from grabs from SOL4934 and geocat no 72926 (molluscs) and geocat (worms) from SOL5117.

  • This dataset contains species-level identifications of polychaetes collected during survey SOL5117 (R.V. Solander 30 July - 27 August, 2010). Animals were collected from the Joseph Bonaparte Gulf with a Smith McIntyre grab, with a few specimens from a benthic sled. Species-level identifications were undertaken by Chris Glasby and Charlotte Watson at the Museum and Art Gallery of the Northern Territory (MAGNT) and were delivered to Geoscience Australia on the 6 June 2013. See GA Record 2011/08 for further details on survey methods and specimen acquisition. Data is presented here as delivered by the taxonomist, and Geoscience Australia is unable to verify the accuracy of the taxonomic identifications. The data file contains two spreadsheets: - 'species list' includes all polychaete species as identified at the MAGNT, including family, abundance, and comments from the taxonomists. It also contains phyla-level identifications for non-polychaete specimens that were mistakenly sent to the MAGNT with the polychaete samples. CG = Chris Glasby; CW = Charlotte Watson - 'Stations' includes location and depth for each station at which grabs and sleds were deployed.

  • Submerged relict reef systems and modern coral communities discovered around the Balls Pyramid shelf are presented as new evidence of extensive carbonate production at the boundary of reef-forming seas. Balls Pyramid is the southernmost island in a chain of island-reefs in the southwest Pacific Ocean, 24 km south of the southernmost known coral reef in the Pacific Ocean at Lord Howe Island. This paper explores the detailed geomorphic structure of the shelf through the production of a high resolution bathymetric model from multibeam echosounder data and depth estimates from satellite imagery. Key seafloor features identified include a large, mid shelf reef dominating the shelf landscape in 20 - 60 m water depth, mid shelf basins and channels, and shelf margin terrace sequences in 50 - 100 m depth. Sub-bottom profiles, backscatter, drill core and vibro-core data are used to investigate the seafloor composition. Drill cores extracted from the submerged reef surface confirm coral, coralline algae and cemented sands composition, and vibro-core material extracted from unconsolidated areas demonstrate substantial accumulation of carbonates shed from the reef surface. Underwater video imagery reveals abundant modern mesophotic reef communities, including hard corals, colonising the relict reef surface. This paper reveals prolific past reef growth and abundant modern coral growth on what was previously considered to be a planated volcanic shelf outside of reef-forming seas, thus extending understanding of reef evolution at, and beyond, the limits of growth.

  • 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.

  • This study aims to quantify sponge biodiversity of the Van Diemen Rise and eastern Joseph Bonaparte Gulf in northern Australia and to examine spatial and environmental patterns associated with differences in community structure of sponges.

  • 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. Apart from surface cooling and advection, the Leeuwin Current's sizable cross-shelf movement may be another contributing factor to the seasonal and inter-annual variations of its chlorophyll a concentrations.

  • Benthic marine invertebrates and their planktonic life stages live in a multistressor world where stressor levels are, and will continue to be, exacerbated by global change. Global warming and increased atmospheric CO2 are causing the oceans to warm, decrease in pH and become hypercapnic. These concurrent stressors have strong impacts on biological processes, but little is known about their combined effects on marine invertebrate development. Increasing temperature has a pervasive stimulatory effect on metabolism until lethal levels are reached, whereas hypercapnia can depress metabolism. Ocean acidification is a major threat to calcifying life stages because it decreases carbonate mineral saturation and also exerts a direct pH effect on physiology. Ocean pH, pCO2 and CaCO3 covary and will change simultaneously with temperature, challenging our ability to predict future outcomes for marine biota. The need to consider both ocean warming and acidification is reflected in the recent increase in multifactorial studies of these stressors on development of marine invertebrates. The outcomes and trends in these studies are synthesized here. Different sensitivities of life history stages and species have implications for persistence and community function in a changing ocean. Some species are more resilient than others and may be potential 'winners' in the climate change stakes. For echinoderms where multistressor studies span across life stages, the impacts of pH/pCO2 and warming on benthic-pelagic life cycle phases are assessed. As the ocean will change more gradually over coming decades than in 'future shock' experiments, it is likely that some species may be able to tolerate near future ocean change through acclimatization or adaption.

  • The accuracy of spatially continuous environmental data, usually generated from point samples using spatial prediction methods (SPMs), is crucial for evidence-informed environmental management and conservation. Improving the accuracy by identifying the most accurate methods is essential, but also challenging since the accuracy is often data specific and affected by multiple factors. Because of the high predictive accuracy of machine learning methods, especially random forest (RF), they were introduced into spatial statistics by combining them with existing SPMs, which resulted in new hybrid methods with improved accuracy. This development opened an alternative source of methods for spatial prediction. In this study, we introduced these hybrid methods, along with the modelling procedure adopted to develop the final predictive models. These methods were compared with the commonly used SPMs in R using cross-validation techniques based on both marine and terrestrial environmental data. We also addressed the following questions: 1) whether they are data-specific for marine environmental data, 2) whether input predictors affect their performance, and 3) whether they are equally applicable to terrestrial environmental data? This study provides suggestions and guidelines for the application of these hybrid methods to spatial predictive modelling not only in environmental sciences, but also in other relevant disciplines.