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

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 colocated 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. Sample diversity indices calculated in PRIMER (version 6) using the species level data from JBinfauna_species (25Oct10).xls.

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.

Geoscience Australia carried out a marine survey on Lord Howe Island shelf (NSW) in 2008 (SS06-2008) to map seabed bathymetry and characterise benthic environments through co-located sampling of surface sediments and infauna, rock coring, observation of benthic habitats using underwater towed video, and measurement of ocean tides and wave-generated currents. Sub-bottom 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 pre-existing 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. This folder contains the images derived from benthic samples taken on cruise SS06_2008 aboard Southern Surveyor. The main folder houses all images taken while processing samples at the microscope. 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. Three additonal folders exist within the main folder. Amphipoda contains repeats of the amphipod taxa, SS062008Biota contains images of live organisms taken as soon as the sample was recovered to the ship and Tanaidacea contains repeats of the tanaid taxa.

This dataset contains species identifications of crinoids 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 Museum of Victoria on the 19 April 2010. Species-level identifications were undertaken by Kate Naughton at the Museum of Victoria and were delivered to Geoscience Australia in December 2010. 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.

High-precision measurements of N2 in benthic chamber waters indicated that denitrification occurs within the major sedimentary facies in Port Phillip Bay. The integrated fluxes of biogenic N2 , ammonia, nitrate and nitrite showed that the stoichiometric relationship between organic C and N in the muddy sediments, occupying about 70% of the seafloor, was 5.7, this being similar to the Redfield ratio of 6.6. High denitrifying efficiencies (75-85%; denitrification rates ~1.3 mmol N2 m-2 day-1) at organic carbon loadings of ~15-25 mmol m-2 day-1 indicate that most N processed through the sediments was returned to the overlying waters as biologically (generally) unavailable N2. At sites of high organic carbon loadings to the sediments (>100 mmol m-2 day-1) denitrification rates and denitrifying efficiencies were near zero and most N is returned to the Bay waters as biologically available ammonium. In chambers 'spiked' with 15NO3 , denitrifyers used nitrate produced in the sediments in situ, rather than the exogenous nitrate in overlying waters. The sedimentary microbial processes of ammonification, nitrification and denitrification are therefore tightly coupled.

Conservation planning requires spatial information on biodiversity within a region of interest and its patterns of association with physical environmental features. Such information, however, is often unavailable, and spatial planning is reliant upon proxies based on assumed relationships between species and environmental features have been used as the basis of spatial planning. Here we evaluate the effectiveness of a set of key ecological features (KEF) used in the design of Australia's network of Commonwealth Marine Reserves for representing key marine macrobenthos in a large and biodiverse but data-sparse region in the Oceanic Shoals Commonwealth Marine Reserve (CMR), Timor Sea. Predictive spatial models of the distributions of four key habitat-forming macrobenthic taxa including hard corals, soft corals, gorgonians and sponges, were built using 10 geophysical variables and Boosted Regression Trees. We identified the extent to which KEFs captured the distributions of each taxon, and whether models derived from the western region of the CMR could predict well the distribution of the same taxon in the eastern CMR. All four taxa showed similar habitat preferences, occurring on the tops of raised geomorphic features with hard substrata and while absent from deeper habitats with soft substrata. However, high variability in the biodiversity observed among similar features indicated that factors other than geomorphology alone influence spatial patterns in the distribution of macrobenthos in the region. Overall, models derived from the western region performed reasonably well predicting distribution patterns in eastern region. Transferability of models among sites increased with greater model precision accuracy (higher deviance explained), and all models predicted taxon absence better than presence.

Submarine canyons have been recognised as areas of significant ecological and conservation value for their enhanced primary productivity, benthic biomass and biodiversity. In Australia, 753 submarine canyons were mapped on all margins of the continent by the Marine Biodiversity Hub through the Australian Government's National Environmental Research Program. An analysis of canyon geomorphic metrics provided the basis to objectively classify these canyons across a hierarchy of physical characteristics (e.g. volume, depth range, rugosity) separately for shelf-incising and slope-confined canyons (Huang et al., 2014). Here we extend this analysis to include oceanographic variables in presenting a first pass assessment of habitat quality for all canyons on the Australian margin, with a focus on their upper reaches. This study is based on the premise that habitat heterogeneity, productivity and disturbance are the three factors that potentially determine the quality of a canyon habitat. For each factor we derived a range of variables to inform the assessment of habitat quality (see Table). Habitat heterogeneity was measured using a selection of eight geomorphic metrics including canyon volume and rugosity that are considered likely to have a positive relationship with habitat heterogeneity. Canyon productivity was assessed from five variables including: distance to the shelf break as a proxy of nutrient inputs from land and the continental shelf; bottom current speed as an indicator of nutrient supply to benthic epifauna (derived from time-series re-analysis of the BLUElink oceanographic model and in-situ data), and; measures of the probability, frequency and intensity of upwelling (also from BLUElink data). The BLUElink variables have positive relationships with productivity whereas the relationship between distance to shelf and productivity is negative. Benthic disturbance was assessed from the maximum and range of bottom current speeds, and the frequency and intensity of tropical cyclones. According to these relationships, individual canyons were assigned habitat quality scores, first separately for each variable and then aggregated for the three habitat factors. The final scores were obtained by averaging the scores of the three habitat factors. The results show that many submarine canyons on the eastern Australian margin have high habitat quality scores (see Figure). This is interpreted to be mainly due to the influence of the upwelling-favourable East Australian Current which generates high productivity throughout the year. The Albany canyons on the south-western margin also offer high habitat quality for marine species due to complex geometrical and geophysical structures. They also benefit from the upwelling-favourable Flinders Current. In contrast, canyons on the northern and western margins have lower habitat quality. Many of these canyons receive little input from land and continental shelf. In addition, the downwelling- favourable Leeuwin Current, which flows along the western margin of the continent, hampers the supply of deep water nutrients from reaching the upper reaches of canyons, particularly canyon heads that intersect the euphotic zone. Overall, these results provide a framework for targeted studies of canyons aimed at testing and verifying the habitat potential identified here and for establishing monitoring priorities for the ongoing management of canyon ecosystems.

This dataset contains species identifications of macro-benthic worms 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 Robin Wilson at the Museum of Victoria and were delivered to Geoscience Australia on the 7 May 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 dataset contains species identifications of molluscs 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 3 May 2010. Species-level identifications were undertaken by Richard Willan at the Northern Territory Museum and were delivered to Geoscience Australia on the 5 May 2010 (leg 1 only). 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.