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.

Anthropogenic threats to benthic habitats do not pose an equal risk, nor are they uniformly distributed over the broad depth range of marine habitats. Deep sea benthic environments have, by and large, not been heavily exploited and most are in relatively good condition. In contrast, shelf and coastal habitats, and deep ocean pelagic fisheries, have been exploited extensively and human impacts here are locally severe. A critical point is that anthropogenic threats do not act in isolation; rather, they are cumulative and the impacts are compounded for every affected habitat. In general, the impacts of humans on benthic habitats is poorly understood. Habitat mapping provides condition assessments and establishes baselines against which changes can be measured. GeoHab scientists ranked the impacts on benthic habitats from fishing as the greatest threat, followed by pollution and litter, aggregate mining, oil and gas, coastal development, tourism, cables, shipping, invasive species, climate change and construction of wind farms. The majority of authors (84%) reported that monitoring changes in habitat condition over time was a planned or likely outcome of the work carried out. In this chapter the main anthropogenic threats to benthic habitats are reviewed in relation to their potential impacts on benthic environments.

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.

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

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.

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.

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.

Understanding and predicting the bio-physical relationships between seabed habitats, biological assemblages, and marine biodiversity is critical to managing marine systems. Species distributions and assemblage structure of infauna were examined on the oceanic shelf surrounding Lord Howe Island (LHI) relative to seabed complexity within and adjacent to a newly discovered relict coral reef. High resolution multibeam sonar was used to map the shelf, and identified an extensive relict reef in the middle of the shelf, which separated an inner drowned lagoon from the outer shelf. Shelf sediments and infauna were sampled using a Smith McIntyre grab. The three geomorphic zones (drowned lagoon, relict reef and outer shelf) were strong predictors or surrogates of the physical structure and sediment composition of the LHI shelf and its infaunal assemblage. Infaunal assemblages were highly diverse with many new and endemic species recorded. Each zone supported characteristic assemblages and feeding guilds, with higher abundance and diversity offshore.

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.