In November 2012, the Australian Government finalised a national network of Commonwealth Marine Reserves (CMR) covering 3.1 million km2 and representing the full range of large scale benthic habitats known to exist around mainland Australia. This network was designed using the best available regional-scale information, including maps of seabed geomorphic features and associated Key Ecological Features. To support the management objectives of the marine reserves, new site-specific information is required to improve our understanding of biodiversity patterns and ecosystem processes across a range of spatial scales. In this context, the Marine Biodiversity Hub (funded through the National Environmental Research Program) recently completed a collaborative 'voyage of discovery' to the Oceanic Shoals CMR in the Timor Sea. This area was chosen because it hosts globally significant levels of biodiversity (including endemic sponge and coral taxa), faces rapidly increasing pressures from human activities (offshore energy industry, fishing) yet is recognised as one of the most poorly known regions of Northern Australia. Undertaken in September 2012 on board RV Solander, the survey acquired biophysical data on the shallow seabed environments for targeted areas within the Oceanic Shoals CMR, with a focus on the carbonate banks that characterise this tropical shelf and are recognised as a Key Ecological Feature. Data collected included 500 km2 of high resolution (300 kHz) multibeam sonar bathymetry and acoustic backscatter across four grids, plus seabed sediment samples, underwater tow-video transects (~1 km length), pelagic and demersal baited underwater video, epifaunal and infaunal samples and water column profiles at pre-determined stations. Station locations were designed to provide a random but spatially balanced distribution of sample sites, with weighting toward the banks. This design also facilitated observations of patterns of benthic biodiversity at local to feature-scale and transitions associated with depth-gradients and exposure to tidal currents. Results reveal the banks are broadly circular to elliptical with steep sides, mantled by muddy sand and gravel with areas of hard ground. Rising to water depths of 50-70 m, the banks support benthic assemblages of sponges and corals (including hard corals at shallower sites) which in turn support other marine invertebrates. In strong contrast, the surrounding seabed is characterised by barren, mud-dominated sediments in 70-100 m water depth, although infaunal samples reveal diverse biological communities beneath the seafloor. While the bank assemblages are locally isolated, the potential exists for connectivity between shoals via tide-driven larval dispersal. Ongoing work is aimed at identifying species to determine overlap between bank communities, as well as modelling the sources, pathways and sinks for larvae as a proxy for understanding the physical processes controlling the patterns of biodiversity across the Oceanic Shoals CMR at multiple scales.

Seabed hardness is an important character of seabed substrate as it may influence the nature of attachment of an organism to the seabed. Hence spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia's marine jurisdiction. Seabed hardness is usually inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage or directly measured at limited locations. It can also be predicted based on two-class hardness data using environmental predictors, but no study has been undertaken for predicting multiple-class hardness data. In this study, we classified the seabed hardness into four classes based on underwater video images that were extracted from the underwater video footage. We developed an optimal predictive model to predict the spatial distribution of seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam bathymetry, backscatter and other derived predictors. A novel model selection method that is the averaged variable importance (AVI) was used based on predictive accuracy that was acquired from averaging the results of 100 times replication of 10-fold cross validation. Finally, the spatial predictions generated using the most accurate model was visually examined and analyzed in comparison with previously published predictions based on two-class hardness data. This study confirmed that: 1) seabed hardness of four classes can be predicted into a spatially continuous layer with a high degree of accuracy; 2) model selection for RF is essential for identifying an optimal predictive model in environmental sciences and AVI select the most accurate predictive model(s) instead of the most parsimonious ones, and is recommended for future studies; 3) the typical approach used in pre-selecting predictors by excluding correlated variables (i.e. r 0.95 or the inflation factor 20) needs to be re-examined for identifying predictive models using machine learning methods, at least for the application of random forest in marine environmental sciences; 4) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to `small p and large n problems in the environmental sciences; and 5) the spatial predictions for four-class hardness data were similar with the predictions based on two hardness classes, with a high match rates. RF and AVI are recommended for generating spatially continuous predictions of categorical variables in future studies. In summary, AVI shows its effectiveness in searching for the most accurate predictive models and are recommended for future studies. This study further confirms the superior performance of RF in marine environmental sciences. RF is an effective modelling method with high predictive accuracy not only for presence/absence data and but also for multi-level categorical data. RF and AVI are recommended for generating spatially continuous predictions of categorical variables in future studies.

This resource contains geochemistry data 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). This dataset comprises inorganic element data from the fine fraction (Mud: <63um) of the upper ~2cm of seabed sediment. The Oceanic Shoals Commonwealth Marine Reserve survey was undertaken as an activity within the Australian Government's National Environmental Research Program Marine Biodiversity Hub and was the key component of Research Theme 4 - Regional Biodiversity Discovery to Support Marine Bioregional Plans. Hub partners involved in the survey included the Australian Institute of Marine Science, Geoscience Australia, the University of Western Australia, Museum Victoria and the Museum and Art Gallery of the Northern Territory. Data acquired during the survey included: multibeam sonar bathymetry and acoustic backscatter; sub-bottom acoustic profiles; physical samples of seabed sediments, infauna and epibenthic biota; towed underwater video and still camera observations of seabed habitats; baited video observations of demersal and pelagic fish, and; oceanographic measurements of the water column from CTD (conductivity, temperature, depth) casts and from deployment of sea surface drifters. Further information on the survey is available in the post-survey report published as Geoscience Australia Record 2013/38 (Nichol et al. 2013).

Marine benthic biodiversity can be measured using a range of sampling methods, including benthic sleds or trawls, grabs, and imaging systems, each of which targets a particular community or habitat. Due to the high cost and logistics of benthic sampling, particularly in the deep sea, studies are often limited to only one or two biological sampling methods. Results of biodiversity studies are used for a range of purposes, including species inventories, environmental impact assessments, and predictive modelling, all of which underpin appropriate marine resource management. However, the generality of marine biodiversity patterns identified among different sampling methods is unknown, as are the associated impacts on management decisions. This report reviews studies that have used two or more sampling methods in order to determine the consistency of their results among gear types, as well as the optimum combination of gear types. In addition, we directly analyse data that were acquired using multiple gear types to examine the consistency of biodiversity patterns among different gear types. These data represent two regions: 1) Joseph Bonaparte Gulf (JBG) in northern Australia, and 2) Icelandic waters as part of the Benthic Invertebrates of Icelandic Waters (BIOICE) program. For each dataset, we investigate potential patterns of biodiversity (measured by species richness, diversity indices, abundance, and community structure) in relation to environmental variables such as depth, geomorphology, and substrate. The availability of worldwide data from benthic marine biodiversity surveys reporting the results of two or more gear types is generally poor. Surveys were concentrated in the coastal regions of UK, Norway and Australia, with limited or no studies elsewhere and only 13% including the slope or deep sea. Between different gear groups, our review and analysis of datasets from two regions (northern Australia and Iceland) demonstrates there is little consistency in marine biodiversity trends, with only one study yielding consistent ecological patterns between sampling gear groups (imagery and epifaunal). This indicates that ideal gear combinations are not easily able to be generalised among studies and regions. In addition, the lack of consistency between sampling gear groups highlights the need to analyse gear-specific data and avoid amalgamation. Even among gear that yielded relatively consistent ecological relationships, results varied across biological or environmental factors. Within a gear group, there are more consistencies in ecological relationships, with only two out of the eight studies compiled showing inconsistent ecological relationships A lack of gear-specific studies precluded the determination of the optimal combination of gear types for a particular regions or environments. Nevertheless, based on our findings, we provide preliminary recommendations and inform further research: 1) If general biodiversity patterns are to be investigated, sampling for marine benthic surveys should be carried out using multiple gear types that are concurrently deployed; 2) Target measures of biodiversity need to be decided a priori and appropriate gear used; 3) Preliminary data will help determine the optimal combination of gear types used to sample that region and address a given hypothesis; and 4) If only two gear types are able to be deployed, a grab or corer should be one of them, as this sampling gear type samples a different habitat than other gear groups.

This resource contains multibeam sonar backscatter data for the continental shelf area of Flinders Commonwealth Marine Reserve, northeast Tasmania. Multibeam data were collected by Geoscience Australia and University of Tasmania in May 2011 (survey GA0331) and June-July 2012 (survey GA0337) on RV Challenger. The survey used a Kongsberg EM3002 300 kHz multibeam sonar system mounted in single head configuration to broadly classify the seabed into hard (bedrock reef), soft (sedimentary) and mixed substrate types at select locations across the shelf. The 2011 survey involved reconnaissance mapping along a series of cross-shelf transects, covering a total of 767 line km. For the 2012 survey, multibeam data (bathymetry and backscatter) were collected at 40 pre-determined stations, each covering an area approximately 200 x 200 m. The location of stations was selected using a Generalised Random Tessellation Stratified (GRTS) sampling design that ensured an even spatial distribution of sites. Multibeam data was also collected along transits between GRTS stations (410 line km) and across a 30 km2 area of the outer shelf, incorporating areas of low profile reef, sandy shelf and three shelf-incising canyon heads. Backscatter data are gridded to 2 m spatial resolution. The 2012 survey also included seabed observations at the 40 GRTS stations using a drop camera and collection of sediment samples at 31 stations using a Shipek grab. The Flinders CMR survey was a pilot study undertaken in 2012 as 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 South-east Commonwealth Marine Reserve Network, specifically; 1) to contribute to an inventory of demersal and epibenthic conservation values in the reserve and 2) to test methodologies and deployment strategies in order to inform future survey design efforts. Several gear types were deployed; including multibeam sonar, shallow-water (less than 150m) Baited Remote Underwater Video Systems (BRUVS), deep- water BRUVS (to 600 m), towed video and digital stereo stills. Embargo statement: Resource embargoed pending completion of NERP research. Release date 31 December 2014. Attribution statement: 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

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 colocated 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 wavegenerated currents. Data and samples were acquired using the Defence Science and 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. jb_s2 is an ArcINFO grid of southern part of Jervis Bay survey area (south2 is part of Darling RD grid) produced from the processed EM3002 bathymetry data using the CARIS HIPS and SIPS software

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). Q50, or the 0.50 Quartile of the Geomacs output, represents the values for which 50% of the observations fall below (Hughes & Harris 2008).

Although marine reserves are becoming increasingly important as anthropogenic impacts on the marine environment continue to increase, we have little baseline information for most marine environments. In this study, we focus on the Oceanic Shoals Commonwealth Marine Reserve (CMR) in northern Australia, particularly the carbonate banks and terraces of the Sahul Shelf and Van Diemen Rise which have been designated a Key Ecological Feature (KEF). We use a species-level inventory compiled from three marine surveys to the CMR to address several questions relevant to marine management: 1) Are carbonate banks and other raised geomorphic features associated with biodiversity hotspots? 2) Are there environmental or biogeographic variables that can help explain local and regional differences in community structure? 3) How do sponge communities differ between individual raised geomorphic features? Approximately 750 sponge specimens were collected in the Oceanic Shoals CMR and assigned to 348 species, of which only 18% included taxonomically described species. Between the eastern and western CMR, there was no difference between sponge species richness or assemblages on raised geomorphic features. Within individual raised geomorphic features, sponge assemblages were significantly different (ANOSIM: Global R = 0.328, p < 0.001), but species richness was not. There were no environmental factors related to sponge species richness, although sponge assemblages were weakly but significantly related to several environmental variables (mean depth, mean backscatter, mean slope). These patterns of sponge diversity are considered in the context of marine reserve management in order to explore how such information may help support the future management of this region.

Australia is increasingly recognised as a global hotspot for sponge biodiversity, with sponges playing key roles in habitat provision, water quality, bioerosion, and biodiscovery. Despite the intense focus on marine resource management in northern Australia, there is a large knowledge gap about sponge communities in this region. This study focuses on shelf environments of the Timor Sea, in particular the Van Diemen Rise and Londonderry Rise which are characterised by extensive carbonate terraces, banks and reefs, separated by soft sediment plains and deeply incised valleys. These carbonate terraces and banks are recognised as a Key Ecological Feature (KEF) in the marine region plans for northern Australia (North and Northwest Marine Regions) and are in part incorporated into the Oceanic Shoals Commonwealth Marine Reserve. To support the management of this marine reserve and its associated KEF, we use new datasets to investigate regional patterns in sponge assemblages and their relationships to seabed geomorphology. To do this, we use sponge assemblage data and multibeam-derived variables (depth, backscatter, slope, geomorphic feature) from seven survey areas located on the Van Diemen Rise (four sites) and Londonderry Rise (three sites), spanning approximately 320 km in an east-west direction. The dataset was collected during three collaborative surveys undertaken in 2009, 2010 and 2012 by Geoscience Australia, the Australian Institute of Marine Science and the Museum and Art Gallery of the Northern Territory as part of the Australian Government's Offshore Energy Security Initiative and the National Environmental Research Program Marine Biodiversity Hub. All surveys returned geophysical, biological, geochemical, and sedimentological data. Benthic biota were collected with a benthic sled across a range of geomorphic features (bank, terrace, ridge, plain, valley) identified from high-resolution multibeam sonar. Sponges were then taxonomically identified to 350 species, with the species accumulation curve indicating there may be over 900 sponge species in the region. Sponge assemblages were different between the Van Diemen Rise and Londonderry Rise, as well as between individual banks in the same area, indicating that different suites of species occurred at regional (east-west) and local (between banks) scales. Relationships between sponges and other multibeam-derived variables are more complex and warrant further research. The current study will help: i) facilitate integrated marine management by providing a baseline species inventory; ii) support the listing of carbonate banks of the Timor Sea shelf as a Key Ecological Feature, and; iii) inform future monitoring of marine protected area performance, particularly for areas of complex seabed geomorphology.

This report provides detailed descriptions (metadata) of 45 Australian marine environmental datasets that have been generated and collated by the Marine Biodiversity Hub as part of Theme 3 - National Ecosystems Knowledge, Project 1 - Shelf and Canyon Ecosystems Functions and Processes. The report also includes a map for each dataset to illustrate coverage and general spatial structure. The datasets contain both marine environmental and biological variables from diverse data sources and include both new and updated information. Among them, the national bathymetry grid and derived products, seabed sediment grids, seabed exposure (GEOMACS) parameters, water quality data, the national canyon dataset and connectivity layers were produced by Geoscience Australia. Other environmental and biological datasets are the outputs of oceanographic models and collections of various governmental and research organisations. These datasets are important for the success of marine biodiversity research in Theme 3 Project 1 in that they describe key aspects of Australian marine physical, geochemical and biological environments. The physical and geochemical datasets not only characterise the static seabed features but also capture the temporal variation and three-dimensional interactions within marine ecosystems. The biological datasets represent a unique collection of fish and megafauna data available at the national scale. Together, these marine environmental datasets enhance our understanding of large-scale ecological processes driving marine biodiversity patterns. However, we should be aware of the uncertainties and potential errors exist in these datasets due to limitations of data collection and processing methods. Data quality issues of individual datasets have been documented in this report where possible.