Dense coral-sponge communities on the upper continental slope (570 - 950 m) off George V Land, east Antarctica have been identified as Vulnerable Marine Ecosystems. We propose three main factors governing their distribution on this margin: 1) their depth in relation to iceberg scouring; 2) the flow of organic-rich bottom waters; and 3) their location at the head of shelf cutting canyons. Icebergs scour to 500 m in this region and the lack of such disturbance is a likely factor allowing the growth of rich benthic ecosystems. In addition, the richest communities are found in the heads of canyons which receive descending plumes of Antarctic Bottom Water formed on the George V shelf, which could entrain abundant food for the benthos. The canyons harbouring rich benthos are also those that cut the shelf break. Such canyons are known sites of high productivity in other areas due to strong current flow and increased mixing with shelf waters, and the abrupt, complex topography.

In 2007-08 scientists from Australia, Japan and France set out to survey the marine life and habitats in the region adjacent to Terre Adelie and George V Land in East Antarctica (Australian Antarctic Magazine 14: 2-13, 2008). The Collaborative East Antarctic Marine Census (CEAMARC) - part of Australia's contribution to the International Polar Year - aimed to understand the processes that have lead to the evolution and survival of marine life existing in the region today, so that scientists can predict how these organisms may respond to future climate-related changes in their environment. Scientists involved in the census are now finalising the collation and analysis of data and the following pages (13-18) provide an insight into some of the results. The team aims to publish its findings as a series of papers in a special volume of a scientific journal in late 2010.

This study investigated bio-environment relationships in Jervis Bay, a sandy partially enclosed embayment in NSW. Three decision tree models and a robust model selection process were applied to a wide-range of physical data (multibeam bathymetry and backscatter grids and derivatives, parameters that describe seabed sediment and water column physical/geochemical characteristics, seabed exposure) and co-located biological data. The models for selected infaunal species and three diversity indices explained 32-79% of data variance. Patterns of abundance and diversity were statistically related to a wide range of environmental variables, including sediment physical (e.g. mud, CaCO3, gravel) and geochemical properties (e.g. chlorophyll a, total sediment metabolism, total sulphur), seabed morphometric characteristics (e.g. local Moran's I of bathymetry, rugosity), seabed exposure regime and water column light attenuation. The modelled response curves together with results from an earlier habitat mapping study informed the development of a conceptual model that provides a process-based framework for the interpretation of biodiversity patterns in the southern part of the Bay. The conceptual model had three zones which were noted for: (i) fine-sediment resuspension and macroalgae accumulation (leading to anoxia; extreme); (ii) bioturbation (in-between); and (iii) exposure of the seabed to waves (extreme in places). Most bio-environment relationships pointed to complex relationships between multiple biological and physical factors occurring in the different process domains/zones. The combined use of co-located samples and bio-environment and conceptual models enabled a mechanistic understanding of benthic biodiversity patterns in Jervis Bay.

The term 'surrogacy' is used in habitat mapping with reference to the biophysical variables that can be mapped with a quantifiable correspondence to the occurrence of benthic species and communities. Surrogacy research can be defined as an empirical method of determining which easily measured characteristics best describe the species assemblage in a particular space and at a particular time. These characteristics act as predictors (with some known probability and uncertainty) for the occurrence of species assemblages in unexplored areas. Abiotic variables are, in general, more easily and less expensively obtained than biological observations, which is a key driver for surrogacy research. However, the suite of abiotic factors that exert control over the occurrence of species (its niche) is also a scientifically interesting aspect of ecology that provides important insights into a species evolution and biogeography. This chapter provides a review of surrogates used by case study authors and of the methods used to quantify relationships between variables.

Geoscience Australia carried out a marine survey on Lord Howe Island shelf (NSW) in 2008 (SS062008) 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 wavegenerated 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. lh_4m is an ArcInfo grid of the Lord Howe survey area produced from the processed EM300 bathymetry data of the survey area using the CARIS HIPS and SIPS software.

Cold seeps and hydrothermal vents can be detected by a number of oceanographic and geophysical techniques as well as the recovery of characteristic organisms. While the definitive identification of a seep or vent and its accompanying fauna is seldom unequivocal without significant effort. We suggest an approach to identifying associated VMEs in the CCAMLR region that uses the results of scientific surveys to identify confirmed features while documenting a series of criteria that can be used by fishing vessels to reduce the accidental disturbance of seep communities.

In ecology, a common form of statistical analysis relates a biological variable to variables that delineate the physical environment, typically by fitting a regression model or one of its extensions. Unfortunately, the biological data and the physical data are frequently obtained from eparate sources of data. In such cases there is no guarantee that the biological and physical data are co-located and the regression model cannot be used. A common and pragmatic solution is to predict the physical variables at the locations of the biological variables and then to use the predictions as if they were observations.We show that this procedure can cause potentially misleading inferences and we use generalized linear models as an example. We propose a Berkson error model which overcomes the limitations. The differences between using predicted covariates and the Berkson error model are illustrated by using data from the marine environment, and a simulation study based on these data.

The East Antarctic continental shelf has had very few studies examining the macrobenthos structure or relating biological communities to the abiotic environment. In this study, we apply a hierarchical method of benthic habitat mapping to Geomorphic Unit and Biotope levels at the local (10s of kilometers) scale across the George V Shelf between longitudes 1421E and 1461E. We conducted a multi-disciplinary analysis of seismic profiles, multibeam sonar, oceanographic data and the results of sediment sampling to define geomorphology, surficial sediment and near-seabed water mass boundaries.

Mapping of benthic habitats seldom considers biogeochemical variables or changes across time. We aimed to: (i) develop winter and summer benthic habitat maps for a sandy embayment; and (ii) compare the effectiveness of various maps for differentiating infauna. Patch-types (internally homogeneous areas of seafloor) were constructed using combinations of abiotic parameters, and are presented in sediment-based, biogeochemistry-based and combined sediment/biogeochemistry-based habitat maps. August and February surveys were undertaken in Jervis Bay, Australia, to collect samples for physical (%mud, sorting, %carbonate), biogeochemical (chlorophyll a, sulfur, sediment metabolism, bio-available elements) and infaunal analyses. Boosted Decision Tree and cokriging models generated spatially continuous data-layers. Habitat maps were made from classified layers using GIS overlays, and were interpreted from a biophysical-process perspective. Biogeochemistry and %mud varied spatially and temporally, even in visually homogeneous sediments. Species turnover across patch-types was important for diversity, and the utility of habitat maps for differentiating biological communities varied across months. Diversity patterns were broadly related to reactive carbon and redox which varied temporally. Inclusion of biogeochemical factors and time in habitat maps provides a better framework for differentiating species and interpreting biodiversity patterns than once-off studies based solely on sedimentology or video-analysis.

The ArcINFO grid is one of the outputs of a finescale hydrodynamic model, the Simulating WAves Nearshore (SWAN) model (Booij et al., 1999; Ris et al., 1999).The grid describes the modelled maximum orbital velocity (m/s) which can be used as estimation of seabed exposure on the Carnarvon Shelf.