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.

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 will be calculated to 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). The interquartile range, , of the GEOMACS output takes the observations from between Q25 and Q75 to provide an accurate representation of the spread of observations. The interquartile range was shown to provide a more robust representation of the observations than the standard deviation, which produced highly skewed observations (Hughes & Harris 2008).

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

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.

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.

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.

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 were calculated to 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). Q75, or the 0.75 Quartile of the Geomacs output, represents the values for which 75% of the observations fall below (Hughes & Harris 2008).

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).

Multibeam sonar data incorporates a wide range of metrics of physical seabed properties that can be utilised to generate substrate maps for marine habitat mapping. In particular, statistical descriptors of seabed form and texture can be derived to maximise the information provided by multibeam data. This study investigates the full potential of multibeam data for mapping seabed properties for an area of geomorphically complex seabed on the continental shelf offshore from Point Cloates, Western Australia. In 2008, as part of a collaborative survey within the Commonwealth Environmental Research Facilities (CERF) Marine Biodiversity Hub, Geoscience Australia acquired high resolution multibeam data and sediment samples across a 280 km2 area of the shelf, using a Kongsberg EM 3002 (300 kHz) system. Using this data, a two stage analysis was developed to: (i) separate 'hard seabed (e.g., reefs, ridges and mounds) from 'soft' sediments, and; (ii) predict textural properties for seabed sediments, including %Gravel, %Sand, %Mud, mean grain size and sorting. For a mapping tool, we chose the Random Forest Decision Tree technique. This entailed using ten combinations of input datasets as explanatory variables, including morphometric variables derived from bathymetry, and angular response curves and related statistics derived from backscatter mosaics. The training dataset was derived by combining sediment data from grab samples with locations of hard substrate inferred from bathymetry data. The predictive mapping of 'hard' and 'soft' seabed types resulted in predictions with very strong confidence levels, especially when bathymetry information was combined with backscatter data (i.e., cross-validated Area Under Curve = 0.99). The five sediment properties were predicted with moderate to good cross-validation accuracies (Figure 1). The highest accuracies were achieved for %Mud and Sorting, (R2s equal 0.73 and 0.68, respectively).

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