This dataset contains species identifications of benthic worms collected during survey TAN0713 (R.V. Tangaroa, 7 Oct - 22 Nov 2007). Animals were collected from the Faust and Capel basins and Gifford Guyot with a boxcore, rock dredge, or epibenthic sled. Specimens were lodged at Museum of Victoria in June 2008. Species-level identifications were undertaken by Robin Wilson at the Museum of Victoria and were delivered to Geoscience Australia on 1 Aug 2008. See GA Record 2009/22 for further details on survey methods and specimen acquisition. Data is presented here exactly as delivered by the taxonomist, and Geoscience Australia is unable to verify the accuracy of the taxonomic identifications.

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.

A growing need to manage marine biodiversity at local, regional and global scales cannot be met by applying the limited existing biological data sets. Abiotic surrogacy is increasingly valuable in filling the gaps in our knowledge of biodiversity hotspots, habitats needed by endangered or commercially valuable species and systems or processes important to the sustained provision of ecosystem services. This review examines the utility of abiotic surrogates across spatial scales with particular regard to how abiotic variables are tied to processes which affect biodiversity and how easily those variables can be measured at scales relevant to resource management decisions.

This dataset contains species identifications of echinoderms collected during survey GA2476 (R.V. Solander, 12 August - 15 September 2008). Animals were collected from the Western Australian Margin with a BODO sediment grab or rock dredge. Specimens were lodged at Museum of Victoria on the 10 March 2009. Species-level identifications were undertaken by Tim O'Hara at the Museum of Victoria and were delivered to Geoscience Australia on the 24 April 2009. See GA Record 2009/02 for further details on survey methods and specimen acquisition. Data is presented here exactly as delivered by the taxonomist, and Geoscience Australia is unable to verify the accuracy of the taxonomic identifications.

This study presents new information on the regional geochemical characteristics of deep-sea floor sediments (1300 - 2423 m water depth) on the Lord Howe Rise (deep-sea plateau) and Gifford Guyot (seamount/tablemount), remote areas off eastern Australia. The aim was to provide a coherent synthesis for a suite of geochemical data that can be used to make habitat inferences and to develop surrogates of biodiversity. Sediment characteristics analysed were mineralogy, organic carbon and nitrogen concentrations and isotopic compositions, and concentrations of major and trace elements. We also measured parameters that convey information about the reactivity of organic matter and on the bio-availability of bioactive trace elements (e.g. chlorin indices and acid-extractable elements). Surface sediments from the region were calcareous oozes that were carbon-lean (0.26±0.1%) and had moderate to high chlorin indices (0.62 - 0.97)..

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 dataset contains species identifications of sponges collected during survey SOL4934 (R.V. Solander, 27 August - 24 September, 2009). Animals were collected from the Joseph Bonaparte Gulf with a benthic sled. Specimens were lodged at Northern Territory Museum on the 26 September 2009. Species-level identifications were undertaken by Belinda Glasby at the Northern Territory Museum and were delivered to Geoscience Australia on the 23 February 2011. See GA Record 2010/09 for further details on survey methods and specimen acquisition. Data is presented here exactly as delivered by the taxonomist, and Geoscience Australia is unable to verify the accuracy of the taxonomic identifications.

A number of terms used in this book are derived from the fields of biogeography and benthic ecology and these are defined in the glossary; the reader is also referred to the works cited at the end of this chapter for further information. Many of the case studies presented in this book refer to habitat classification schemes that have been developed based on principles of biogeography and ecology. For these reasons a brief overview is provided here to explain the concepts of biodiversity, biogeography and benthic ecology that are most relevant to habitat mapping and classification. Of particular relevance is that these concepts underpin classification schemes employed by GeoHab scientists in mapping habitats and other bioregions. A selection of published schemes, from both deep and shallow water environments, are reviewed and their similarities and differences are examined.

The World Summit on Sustainable Development implementation plan requires, by 2012, a representative system of marine protected areas (RSMPA) for the purposes of long-term conservation of marine biodiversity. A great challenge for meeting this goal, particularly in data-poor regions, is to avoid inadvertant failure while giving science the time and resources to provide better knowledge. A staged process is needed for identifying areas in data-poor regions that would enable the objectives to be achieved in the long term. We elaborate a procedure that would satisfy the first stage of identifying a RSMPA, including areas suitable as climate change refugia and as reference areas for monitoring change without direct interference of human activities. The procedure is based on the principles of systematic conservation planning. The first step involves the identification of ecologically-separated provinces along with the physical heterogeneity of habitats within those provinces. Ecological theory is then used to identify the scale and placement of MPAs, aiming to be the minimum spatial requirements that would satisfy the principles for a representative system: comprehensiveness, adequacy and representativeness (CAR). We apply the procedure to eastern Antarctica, a region with spatially-restricted sampling of most biota. We use widely available satellite and model data to identify a number of large areas that are likely to encompass important areas for inclusion in a RSMPA. Three large areas are identified for their pelagic and benthic values as well as their suitability as climate change refugia and reference areas. Four other areas are identified specifically for their benthic values. These areas would need to be managed to maintain these values but we would expect them to be refined over time as more knowledge becomes available on the specific location and spatial extent of those values.

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.