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.

Marine physical and geochemical data can be valuable in predicting the potential distributions and assemblages of marine species, acting as surrogate measures of biodiversity. The results of surrogacy analysis can also be useful for identifying ecological processes that link physical environmental attributes to the distribution of seabed biota. This paper reports the results of a surrogacy study in Jervis Bay, a shallow-water, sandy marine embayment in south-eastern Australia. A wide range of high-resolution co-located physical and biological data were employed, including multibeam bathymetry and backscatter data and their derivatives, parameters that describe seabed sediment and water column physical characteristics, seabed exposure, and infauna species. The study applied three decision tree models and a robust model selection process. The results show that the model performance for three diversity indices and seven out of eight infauna species range from acceptable to good. Important surrogates for infauna diversity and species distributions within the mapped area are broad-scale habitat type, seabed exposure, sediment nutrient status, and seabed rugosity and heterogeneity. The results demonstrate that abiotic environmental parameters of a sandy embayment can be used to effectively predict infauna species distributions and biodiversity patterns. International Journal of Geographical Information Science

Geoscience Australia carried out a marine survey on Carnarvon shelf (WA) in 2008 (SOL4769) to map seabed bathymetry and characterise benthic environments through co-located sampling of surface sediments 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 Australian Institute of Marine Science (AIMS) Research Vessel Solander. Bathymetric mapping, sampling and video transects were completed in three survey areas that extended seaward from Ningaloo Reef to the shelf edge, including: Mandu Creek (80 sq km); Point Cloates (281 sq km), and; Gnaraloo (321 sq km). Additional bathymetric mapping (but no sampling or video) was completed between Mandu creek and Point Cloates, covering 277 sq km and north of Mandu Creek, covering 79 sq km. Two oceanographic moorings were deployed in the Point Cloates survey area. The survey also mapped and sampled an area to the northeast of the Muiron Islands covering 52 sq km. This is a folder of the images derived from benthic samples taken on cruise Sol4769 aboard RV Solander. Subfolders house images of Echinodermata, Mollusca, Polychaete, images taken of fresh material during cruise, and various categories of Crustacea, denoted by a C_ prefix in the folder name. Images of fresh material were made using a Canon EOS 40D camera on a rostrum in the wet lab of the ship. Images of preserved material were made using a Nikon Coolpix camera mounted on a Macroscope in the benthic lab at GA. 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.

Understanding marine biodiversity has received much attention from an ecological and conservation management perspectives. The Australian Government's Department of the Environment, Water, Heritage and the Arts has initiated the Commonwealth Environment Research Facilities (CERF) initiative to enhance the understanding of Australia's natural environment for policy making. One part of the CERF initiative through the marine biodiversity hub was to predict biodivesity from expansive physical variables. This talk presents some of the work arising from this area.

Physical sedimentological processes such as the mobilisation and transport of shelf sediments during extreme storm events give rise to disturbances that characterise many shelf ecosystems. The intermediate disturbance hypothesis predicts that biodiversity is controlled by the frequency of disturbance events, their spatial extent and the amount of time required for ecological succession. A review of available literature suggests that periods of ecological succession in shelf environments range from 1 to over 10 years. Physical sedimentological processes operating on continental shelves having this same return frequency include synoptic storms, eddies shed from intruding ocean currents and extreme storm events (cyclones, typhoons and hurricanes). Modelling studies that characterise the Australian continental shelf in terms of bed stress due to tides, waves and ocean currents were used here to create a map of ecological disturbance, defined as occurring when the Shield's parameter exceeds a threshold of 0.25. We also define a dimensionless ecological disturbance ratio (ED) as the rate of ecological succession divided by the recurrence interval of disturbance events. The results illustrate that on the outer part of Australia's southern, wave-dominated shelf the mean number of days between threshold events that the Shield's parameter exceeds 0.25 is several hundred days.

Field and supplementary environmental data for the Marine Biodiversity Hub Description: The directory contains the following datasets. 1. Multibeam acoustic data (both backscatter and bathymetry) for three field areas: Jervis Bay, Carnarvon Shelf, and Southern Tasmanian Shelf. 2. Marine environmental data at the Australian continental scale. 3. Side scan data for three regions: Fitzroy, Jervis Bay and Keppel Bay. 4. CARS and Ocean Color datasets obtained from CSIRO. 5. AUV data for the Tasmanian survey (October 2008). These datasets were collected from various field surveys and project partners for the research of Marine Biodiversity Hub. Please contact the CERF project team for further information.

This study tested the performance of 16 species models in predicting the distribution of sponges on the Australian continental shelf using a common set of environmental variables. The models included traditional regression and more recently developed machine learning models. The results demonstrate that the spatial distributions of sponge as a species group can be successfully predicted. A new method of deriving pseudo-absence data (weighted pseudo-absence) was compared with random pseudo-absence data - the new data were able to improve modelling performance for all the models both in terms of statistics (~10%) and in the predicted spatial distributions. Overall, machine learning models achieved the best prediction performance. The direct variable of bottom water temperature and the resource variables that describe bottom water nutrient status were found to be useful surrogates for sponge distribution at the broad regional scale. This study demonstrates that predictive modelling techniques can enhance our understanding of processes that influence spatial patterns of benthic marine biodiversity. Ecological Informatics

Anthropogenic global ocean warming is predicted to cause bleaching of many near-sea-surface (NSS) coral reefs and could make deep-water, mesophotic coral ecosystems (MCEs) into coral reef 'life boats', for many coral species. The question arises: how common are MCE's in comparison to NSS reefs? We used a dataset from the Great Barrier Reef (GBR) to show that only about 37% of available bank surface area is colonised by NSS coral reefs (16,110 km2); the other 63% of submerged bank area (25,599 km2) represents potential MCE habitat and it is spatially distributed along the GBR continental shelf in direct proportion to NSS coral reefs. Out of 25,599 km2 of submerged bank area, predictive habitat modelling indicates that about 52% (13,000 km2) is MCE habitat.

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 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.