Reliable marine benthic habitat maps at regional and national scales are needed to enable the move towards the sustainable management of marine environmental resources. The most effective means of developing broad-scale benthic habitat maps is to use commonly available marine physical data due to the paucity of adequate biological data and the prohibitive cost of directly sampling benthic biota over large areas. A new robust method of mapping marine benthic habitats at this scale was developed based on a stratified approach to habitat classification. This approach explicitly uses knowledge of marine benthic ecology to determine an appropriate number of stratification levels, to choose the most suitable environmental variables for each level, and to select ecologically significant boundary conditions (i.e. threshold values) for each variable. Three stratification levels, with nine environmental variables, were created using a spatial segmentation approach. Each level represents major environmental processes and characteristics of the Australian marine benthic environment. The finest scale of benthic habitat is represented by seafloor physical properties of topography, sediment grain size and seabed shear stress. Water-column nutrient parameters and bottom water temperature depicted the intermediate scale, while the broadest scale was defined by seabed insolation parameters derived from depth data. The classifications of the three stratified levels were implemented using an object-based fuzzy classification technique that recognises that habitats are largely homogenous spatial regions, and transitions between habitats are often gradual. Classification reliability was indicated in confidence maps. Physical habitat diversity was evaluated for the final benthic habitat map that combines the three classifications. The final benthic habitat map identifies the structurally complex continental shelf break as an area of relatively high habitat diversity. Continental Shelf Research

Geoscience Australia carried out a marine survey on Lord Howe Island shelf (NSW) in 2008 (SS06-2008) to map seabed bathymetry and characterise benthic environments through co-located sampling of surface sediments and infauna, rock coring, observation of benthic habitats using underwater towed video, and measurement of ocean tides and wave-generated currents. Sub-bottom profile data was also collected to map sediment thickness and shelf stratigraphy. Data and samples were acquired using the National Facility Research Vessel Southern Surveyor. Bathymetric data from this survey was merged with other pre-existing bathymetric data (including LADS) to generate a grid covering 1034 sq km. As part of a separate Geoscience Australia survey in 2007 (TAN0713), an oceanographic mooring was deployed on the northern edge of Lord Howe Island shelf. The mooring was recovered during the 2008 survey following a 6 month deployment. This folder contains the images derived from benthic samples taken on cruise SS06_2008 aboard Southern Surveyor. The main folder houses all images taken while processing samples at the microscope. 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. Three additonal folders exist within the main folder. Amphipoda contains repeats of the amphipod taxa, SS062008Biota contains images of live organisms taken as soon as the sample was recovered to the ship and Tanaidacea contains repeats of the tanaid taxa.

Autonomous Underwater Vehicles (AUVs) have only recently become available as a tool to investigate the biological and physical composition of the seabed utilizing a suite of image capture and high-resolution geophysical tools. In this study we trialled the application of an AUV, integrating AUV image capture with ship-based high resolution multibeam bathymetry, to map benthic habitats and biodiversity in coastal and offshore waters of SE Tasmania. The AUV successfully surveyed a plethora of marine habitats and organisms, including high-relief kelp-dominated rocky reefs to deep mid-shelf reef and sediments that are otherwise difficult to access. To determine the spatial extent of these habitats within a broader-scale context, the AUV surveys were integrated with larger scale multibeam mapping surveys. The data collected using the AUV significantly improved our understanding of the distribution of benthic habitats and marine organisms in this region, with direct application to the management and conservation of these environments. Integrating the AUV data with the largescale mapping data provided the opportunity to quantify the relationships between the biological and physical variables, and to use thise data to develop predictive models of biodiversity across the region.

The Marine Biodiversity Hub was funded by the Australian Government Commonwealth Environmental Research Facilities (CERF) between 2007 and 2010. The Hub was developed to improve the scientific knowledge available to support marine bioregional planning and addressed two fundamental questions: 1. How can we predict the distribution of marine biodiversity; and 2. How can we use this improved capability to conserve and manage biodiversity in a multiple-use environment? This talk focuses on the Surrogates Program, one of four research programs in the Hub. The Surrogates Program addressed the above questions by testing and developing physical variables as surrogates of marine biodiversity, with a focus on seabed environments. In the program, we employed a range of marine survey technologies to collect high-quality and co-located benthic physical and biological data at four selected areas in temperate and tropical waters. We also developed advanced spatial and statistical approaches to test the degree of covariance between the physical and biological data, identify ecological processes, and generate prediction maps. During a number of field campaigns, we deployed a range of instruments to collect data including multibeam sonar, sediment grabs, benthic sleds, towed-video/still images and Autonomous Underwater Vehicles. GIS, machine-learning models and the SWAN hydrodynamic model were used to derive and predict a large number of physical variables as potential surrogates. The effectiveness of the surrogacy approaches were examined using multivariate analyses and spatial modelling techniques. In general, we found that using physical surrogates to predict marine biodiversity is a cost-effective approach. The new knowledge of surrogates and seabed ecological processes directly supports the management of the Australian marine estate. Other major outputs of the Surrogates Program include: - Thirty-seven new and updated national-scale marine physical environmental datasets; - High resolution bathymetry of targeted areas, covering almost 2000 km2, plus 171 km of underwater video transects, 402 sediment grab samples and 232 epifauna samples; - New seabed exposure and fetch models/datasets; and - Peer-reviewed reports and papers in scientific journals. The success of the Marine Biodiversity Hub has enabled the Hub to be refunded for a further four years through the new National Environmental Research Program. In this, Geoscience Australia (GA) is collaborating with the University of Tasmania, CSIRO Marine & Atmospheric Research, Australian Institute of Marine Science, Museum of Victoria, University of Western Australia and Charles Darwin University; GA is also leading Theme 3 Project 1 which focuses on identifying the functions and processes of shelf and canyon ecosystems. The project is expected to further advance marine biodiversity research in Australia by investigating the role of large-scale physical features on the shelf in influencing patterns of marine biodiversity.

This report provides a description of the research activities completed during the CERF Marine Biodiversity Hub survey of southeast Tasmanian temperate reefs, aboard RV Challenger, as part of the Hub's Surrogates Program. The survey was undertaken as a collaborative exercise between the Tasmania Aquaculture and Fisheries Institute (TAFI, University of Tasmania) and Geoscience Australia (GA), and was completed in two stages during 2008 and 2009. This report describes the methods employed in the mapping and video characterisation of shallow-shelf temperate reef habitats across seven survey sites in southeast Tasmania. Preliminary results are provided of the analysis of multibeam sonar and underwater video data. Examples of the types of biota encountered in the towed video and stills photography, and initial interpretations of the benthic communities are also provided. In addition, initial results are presented from the deployment of an Autonomous Underwater Vehicle (AUV) to collect high resolution photographs of reefs and associated biota.

A series of short field surveys in Jervis Bay, New South Wales, were undertaken by Geoscience Australia staff as part of the Surrogates Program in the Commonwealth Environmental Research Facilities (CERF) Marine Biodiversity Hub. The aim of the Jervis Bay field work was to collect accurately co-located physical and biological data to enable research into the utility of physical parameters as surrogates for patterns of benthic biodiversity in shallow soft-sediment habitats. In this report the survey design and sampling methods are described; selected field datasets are mapped and discussed; initial results of the laboratory analysis of seabed samples are presented; and there is a brief description of the upcoming analysis of covariance of the physical and biological datasets. The major outputs of the survey work to date are: 1. High-resolution multibeam acoustic datasets for priority areas along the open coast of Jervis Bay (Beecroft Head to Drum and Drumsticks), within the Jervis Bay National Park; and within the southern bay around Darling Road, and in the bay entrance. 2. High quality underwater video footage of benthic habitats in the Darling Road study area acquired with Geoscience Australia's shallow-water towed-video system. The video was used to characterise benthic habitat types, relief/bedform types, and biota occurrence. Characterisations were collected in real-time along bi-directional (six offshore and four alongshore) towed video transects, and were subsequently processed and mapped into three ArcGIS map layers. 3. A set of broad-scale (bay-wide) widely-spaced, co-located sediment and biotic (infauna) seabed samples from the bay's soft-sediment habitats (polychaete mounds, drift algal beds, sand flats, and sand ripple and wave habitats); 4. Sediment samples for geochemical, biogeochemical and sedimentological analyses. 5. A new acoustic doppler current profiler was successfully trialed, and is now being used to collect seabed current data in the Darling Road study area. 6. A progress report on the survey work was presented at the annual CERF Marine Biodiversity Hub's Annual Science Workshop in October 2008.

This chapter presents a broad synthesis and overview based on the 57 case studies included in Part 2 of this book, and on questionnaires completed by the authors. The case studies covered areas of seafloor ranging from 0.15 to over 1,000,000 km2 (average of 26,600 km2) and a broad range of geomorphic feature types. The mean depths of the study areas ranged from 8 to 2,375 m, with about half of the studies on the shelf (depth <120 m) and half on the slope and at greater depths. Mapping resolution ranged from 0.1 to 170 m (mean of 13 m). There is a relatively equal distribution of studies among the four naturalness categories: near-pristine (n=17), largely unmodified (n = 16), modified (n=13) and extensively modified (n=10). In terms of threats to habitats, most authors identified fishing (n=46) as the most significant threat, followed by pollution (n=12), oil and gas development (n=7) and aggregate mining (n=7). Anthropogenic climate change was viewed as an immediate threat to benthic habitats by only three authors (n=3). Water depth was found to be the most useful surrogate for benthic communities in the most studies (n=17), followed by substrate/sediment type (n=14), acoustic backscatter (n=12), wave-current exposure (n=10), grain size (n=10), seabed rugosity (n=9) and BPI/TPI (n=8). Water properties (temperature, salinity) and seabed slope are less useful surrogates. A range of analytical methods were used to identify surrogates, with ARC GIS being by far the most popular method (23 out of 44 studies that specified a methodology).

The aim of the study was to explore different approaches of feature selection, extraction and reduction from backscatter angular response curves for a relatively complex seabed. The study area is located at Point Cloates along the coast of central Western Australia where water depths range from 6 to 200 m and is characterised by extensive sandy bedforms, flat sandy seabed and numerous reefs. A Simrad EM3002 300 kHz sonar system was used to collect multibeam data across an area of 281 km2 in 2008. A series of radiometric and geometric corrections were applied to the backscatter data. The angular response curves were derived separately for port and starboard by averaging 100 pings along the ship track. Seabed sediment texture was characterised from 90 samples that were analysed for grain size properties (gravel, sand, mud%) and classified into six sediment classes. Co-located towed-video transects from the survey were used to identify areas of rocky seabed. Four approaches of processing the angular response curves have been explored. The first approach used all effective beam angles (4o to 51o) with a manual feature selection method in the modelling process. The second approach used principal component analysis to condense the 48 variables into four (explained 99% data variance). The third approach extracted nine parameters from two domains of the angular response curves including slope, intercept, orthogonal distance and mean. The fourth approach derived continuum-removed angular response curves. Probability Neural Network was used as the classifier. The classification results show that the continuum removal approach performed the best with an overall accuracy of 73% when classifying the seven seabed classes (Figure 1).When merging the six sediment classes into four, which results in five seabed classes, the performance was improved for all approaches.

Geoscience Australia carried out a marine survey on Lord Howe Island shelf (NSW) in 2008 (SS06_2008) to map seabed bathymetry and characterise benthic environments through colocated sampling of surface sediments and infauna, rock coring, observation of benthic habitats using underwater towed video, and measurement of ocean tides and wave generated currents. Subbottom profile data was also collected to map sediment thickness and shelf stratigraphy. Data and samples were acquired using the National Facility Research Vessel Southern Surveyor. Bathymetric data from this survey was merged with other preexisting bathymetric data (including LADS) to generate a grid covering 1034 sq km. As part of a separate Geoscience Australia survey in 2007 (TAN0713), an oceanographic mooring was deployed on the northern edge of Lord Howe Island shelf. The mooring was recovered during the 2008 survey following a 6 month deployment. Sample diversity indices calculated in PRIMER (version 6) using the species level data from LHI_Infauna_species (27Oct10).csv

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 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. The GA0309_0312_JervisBay2008 folder contains video footage; the GA0326_JervisBay2009 folder contains still images; and the files are the video characterisation datasets. Underwater towed-video footage and still images represent the raw data. Video characterisation datasets include substrata types and the presence/absence of benthic taxa.