This study investigated the surrogacy relationships between marine physical variables and the distribution of marine infauna species and measures of benthic biodiversity across the continental shelf offshore from Ningaloo Reef, Western Australia. The three study areas are located at Mandu Creek, Point Cloates and Gnaraloo covering a combined area of 1038 km2. The physical variables include morphometric variables derived from multibeam bathymetry data, texture measures derived from acoustic backscatter data, sediment variables from 265 samples, seabed exposure estimates and geomorphic feature types. Together, these data were used to model total abundance and species richness, and 10 individual infauna species using a Random Forest Decision Tree. The key findings are: - Generally, the surrogacy relationships are stronger at Gnaraloo than at Mandu and Point Cloates. This is likely due to the fact that Gnaraloo is dominated by soft sediment and Point Cloates and Mandu have larger areas of hard substrates which preclude infauna. - At Gnaraloo, the most important physical surrogates were the sediment variables. - At Point Cloates, the most important physical surrogates were the bathymetry-derived parameters including seabed heterogeneity, morphological position, and slope. - At Mandu, the most important physical surrogates were the mixture of the bathymetry- derived parameters including morphological position and geomorphic features, and the sediment variables including gravel content, and backscatter derived texture measures. - Seabed exposure was not a useful physical surrogate for the infauna distribution in this study. The likely reasons are not clear, but could be a function of the grid resolution (150 m) of the hydrodynamic model used to generate the exposure variable relative to infaunal patterns; or that the infauna species are protected by the sediment from seabed disturbance.

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.

This introductory chapter provides an overview of the book's contents and definitions of key concepts including benthic habitat, potential habitat and seafloor geomorphology. The chapter concludes with a summary of commonly used habitat mapping technologies. Benthic (seafloor) habitats are physically distinct areas of seabed that are associated with particular species, communities or assemblages that consistently occur together. Benthic habitat maps are spatial representations of physically distinct areas of seabed that are associated with particular groups of plants and animals. Habitat maps can illustrate the nature, distribution and extent of distinct physical environments present and importantly they can predict the distribution of the associated species and communities.

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.

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.

Seabed sediment textural parameters such as mud, sand and gravel content can be useful surrogates for predicting patterns of benthic biodiversity. Multibeam swath mapping can provide near-complete spatial coverage of high-resolution bathymetry and backscatter data that are useful in predicting sediment parameters. The multibeam acoustic data at a ~1000 km2 area of the Carnarvon Shelf, Western Australia was used in a predictive modeling approach to map eight seabed sediment parameters. The modeling results indicates overall satisfactory statistical performance, especially for %Mud, %Sand, Sorting, Skewness, and Mean Grain Size. The study demonstrated that predictive modelling using the combination of machine learning models has several advantages over the interpolation of Cokriging. Combing multiple machine learning models can not only improve the prediction performance but also provides the ability to generate useful prediction uncertainty maps. Another important finding is that choosing an appropriate set of explanatory variables, through a manual feature selection process, is a critical step for optimizing model performance. In addition, machine learning models are able to identify important explanatory variables, which is useful in explaining underlying environmental process and checking prediction against existing knowledge of the study area. The sediment prediction maps obtained in this study provide reliable coverage of key physical variables that will be incorporated into the analysis of co-variance of physical and biological data for this area. International Journal of Geographical Information Science

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.

Williams et al. (2009) report on new multibeam sonar bathymetry and underwater video data collected from submarine canyons and seamounts on Australia's southeast continental margin to 'investigate the degree to which geomorphic features act as surrogates for benthic megafaunal biodiversity' (p. 214). The authors describe what they view as deficiencies in the design of the Marine Protected Areas (MPAs) in the southeast region of Australia, in which geomorphology information was employed as a surrogate to infer regional-scale patterns of benthic biodiversity. This comment is designed to support and underscore the importance of evaluating MPA designs and the validity of using abiotic surrogates such as geomorphology to infer biodiversity patterns, and seeks to clarify some of the discrepancies in geomorphic terminologies and approaches used between the original study and the Williams et al. (2009) evaluation. It is our opinion that the MPA design criteria used by the Australian Government are incorrectly reported by Williams et al. (2009). In particular, we emphasise the necessity for consistent terminology and approaches when undertaking comparative analyses of geomorphic features. We show that the MPA selection criteria used by the Australian Government addressed the issues of false homogeneity described by Williams et al. (2009), but that final placement of MPAs was based on additional stakeholder considerations. Finally, we argue that although the Williams et al. (2009) study provides valuable information on biological distributions within seamounts and canyons, the hypothesis that geomorphic features (particularly seamounts and submarine canyons) are surrogates for benthic biodiversity is not tested explicitly by their study.

Multibeam sonars provide co-located high-resolution bathymetry and acoustic backscatter data over a swath of the seafloor. Not only does backscatter response vary with incidence angles but it also changes with different seabed habitat types as well. The resulting imagery depicts spatial changes in the morphological and physical characteristics of the seabed that many use to relate to other dataset such as biology and sediment data for seabed habitat classification purposes. As a co-custodian of national bathymetry data, Geoscience Australia holds massive volumes of multibeam data from various systems including comprehensive collection from its own SIMRAD EM3002D multibeam sonar system. Consequently, Geoscience Australia is researching the application of acoustic backscatter data for seabed habitat mapping to assist with deriving an inventory of seabed habitats for Australia's marine jurisdiction. We present a procedure and a technique developed for our SIMRAD EM3002D multibeam sonar system to derive meaningful angular backscatter response curves. The ultimate goal of this excersie is to try to make use of the angular backscatter response curve that many believe is unique and is an intrinsic property of the seafloor for seabed habitat classification purposes. Adopting the technique intially developed by the Centre for Marine Science and Technology at Curtin University of Technology, Geoscience Australia has further improved these techniques to suits its own sonar system. Issues surrounding the production of the angular backscatter response curves and their solutions will be discussed. We also present results derived from multibeam data acquired in the Joseph Bonaparte Gulf, NT and from the Carnarvorn Shelf (Point Cloates), WA from aboard AIMS Research Vessel Solander. This includes potential use of the angular backscatter response curves for seabed classification and results from a simple analysis using the Kolmogrov-Smirnov goodness of fit.

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. This folder contains the images derived from benthic samples taken on the surveys GA0312, GA0315 and GA0309 aboard HMS Kimbla. 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. Four phylum folders exist within the main folder: Annelida, Crustacea, Echinodermata and Mollusca. The crustacea folder contains further folders, breaking the images into finer groupings. Images of taxa that do not fit in the four phylum folders are loose in the main folder.