Explaining spatial variation and habitat complexity of benthic habitats from underwater video through the use of maps. Different methodologies currently used to process and analyse percent cover of benthic organisms from underwater video will be addressed and reviewed.

This record is a review and synthesis of geological research undertaken along the northern margin of Australia. The record has been written in support of regional marine planning and provides fundamental baseline scientific information for the Northern Planning Area.

The Petrel Sub-basin Marine Survey GA-0335 (SOL5463) was acquired by the RV Solander during May 2012 as part of the Commonwealth Government's National Low Emission Coal Initiative (NLECI). The survey was undertaken as a collaboration between the Australian Institute of Marine Science (AIMS) and GA. The purpose was to acquire geophysical and biophysical data on shallow (less then 100m water depth) seabed environments within two targeted areas in the Petrel Sub-basin to support investigation for CO2 storage potential in these areas. The survey mapped two targeted areas of the Petrel-Sub-basin located within the Ptrl-01 2009 Greenhouse Gas acreage release area (now closed). Data acquired onboard the AIMS research vessel, Solander included multibeam sonar bathymetry (471.2 km2 in Area 1 and 181.1 km2 in Area 2) to enable geomorphic mapping, and multi-channel sub-bottom profiles (558 line-kilometres in Area 1 and 97 line-kilometres in Area 2) to investigate possible fluid pathways in the shallow subsurface geology. Sampling sites covering a range of seabed features were identified from the preliminary analysis of multibeam bathymetry and shallow seismic reflection data. Sampling equipment deployed during the survey included surface sediment grabs, vibrocores, towed underwater video, conductivity-temperature-depth (CTD) profilers and ocean moorings. A total of 14 stations were examined in Area 1 (the priority study area) and one station in Area 2. This report provides a comprehensive overview of the survey activities and preliminary results from survey SOL5463. Detailed analyses and interpretation of the data acquired during the survey will be integrated with new and existing seismic data. This new information will support the regional assessment of CO2 storage prospectivity in the Petrel Sub-basin and contribute to the nation's knowledge of its marine environmental assets.

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 dataset contains species identifications of macro-benthic worms collected during survey SOL4934 (R.V. Solander, 27 August - 24 September, 2009). Animals were collected from the Joseph Bonaparte Gulf with a benthic sled or a Smith-McIntyre grab. Specimens were lodged at Northern Territory Museum on the 24 September 2009. Species-level identifications were undertaken by Chris Glasby at the Northern Territory Museum and were delivered to Geoscience Australia on the 26 October 2009 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.

The world's first satellite-derived mineral maps of a continent, namely Australia, are now publicly available as digital, web-accessible products. The value of this spatially comprehensive mineral information is readily being captured by explorers at terrane to prospect scales. However, potentially even greater benefits can ensue for environmental applications, especially for the Earth's extensive drylands which generate nearly 50% of the world's agricultural production but are most at risk to climate change and poor land management. Here we show how these satellite mineral maps can be used to: characterise soil types; define the extent of deserts; fingerprint sources of dust; measure the REDOX of iron minerals as a potential marine input; and monitor the process of desertification. We propose a 'Mineral Desertification Index' that can be applied to all Earth's drylands where the agriculturally productive clay mineral component is being lost by erosion. Mineral information is fundamental to understanding geology and is important for resource applications1. Minerals are also a fundamental component of soils2 as well as dust eroded from the land surface, which can potentially impact on human health3, the marine environment4 and climate5. Importantly, minerals are well exposed in the world's 'drylands', which account for nearly 50% of Earth's land area6. Here, vegetation cover is sparse to non-existent as a result of low rainfall (P) and high evaporation (E) rates (P/E<0.65). However, drylands support 50% of the world's livestock production and almost half of all cultivated systems6. In Australia, drylands cover 85% of the continent and account for 50% of its beef, 80% of its sheep and 93% of its grain production7. Like other parts of the world, Australia is facing serious desertification of its drylands6. Wind, overgrazing and overstocking are major factors in the desertification process8. That is, the agriculturally productive clay-size fraction of soils (often includes organic carbon) is lost largely through wind erosion, which is acerbated by the loss of any vegetative groundcover (typically dry plant materials). Once clay (and carbon) loss begins, then the related break down of the soil structure and loss of its water holding capacity increases the rate of the degeneration process with the final end products being either exposed rock or quartz sands that often concentrate in deserts.

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.

Identifying the spatial distribution and extent of biotic habitats in estuaries is important in managing our natural resources. Although a number of remote-sensing habitat distribution mapping methods have been successful in clear, shallow-water coastal environments and deeper marine environments, these methods fail in highly turbid and shallow estuarine environments. In this study, we used underwater video to record percent cover of biotic habitats of seagrasses, green and red macroalgae, polychaete mounds and mussel clumps in five estuaries on the south-west coast of Western Australia. Random Forest (RF) was used to model, predict and map their habitats across the estuaries based on the video data and spatially continuous environmental variables. RF is an ensemble, machine-learning method that is robust and able to handle non-linear relationships frequently encountered with ecological data. RF is often used within terrestrial ecosystems but less so in marine ecosystems (e.g. predicting seabed sediment and hardness for marine habitats). The results of this study show that RF models performed well for predictions of biotic habitats, with 79-90% of variation explained by depth, latitude, longitude and water quality variables. This study confirms that RF also has important applications in estuaries, with results refining existing baseline maps and highlighting the importance of biophysical processes driving plant and invertebrate species distribution. Underwater video and RF modelling offer a valuable approach to mapping the spatial distribution of highly turbid biotic habitats.

Between March 2008 and August 2009, 65,445 tonnes of ~75 mol% CO2 gas were injected in a depleted natural gas reservoir approximately 2000 m below surface at the Otway project site in Victoria, Australia. Groundwater flow and composition were monitored biannually in 2 near-surface aquifers between June 2006 and March 2011, spanning the pre-, syn- and post-injection periods. The shallow (~0-100 m), unconfined, porous and karstic aquifer of the Port Campbell Limestone and the deeper (~600-900 m), confined and porous aquifer of the Dilwyn Formation contain valuable fresh water resources. Groundwater levels in either aquifer have not been affected by the drilling, pumping and injection activities that were taking place, or by the rainfall increase observed during the project. In terms of groundwater composition, the Port Campbell Limestone groundwater is fresh (electrical conductivity = 801-3900 ?S/cm), cool (temperature = 12.9-22.5 C), and near-neutral (pH 6.62-7.45), whilst the Dilwyn Formation groundwater is fresher (electrical conductivity 505-1473 ?S/cm), warmer (temperature = 42.5-48.5 C), and more alkaline (pH 7.43-9.35). Evapotranspiration and carbonate dissolution control the composition of the groundwaters. Comparing the chemical and isotopic composition of the groundwaters collected before, during and after injection shows either no sign of statistically significant changes or, where they are statistically significant, changes that are generally opposite those expected if CO2 addition had taken place. The monitoring program demonstrates that the physical and chemical properties of the groundwaters at the sampled bores have not been affected by CO2 sequestration.

Geoscience Australia is supporting the exploration and development of offshore oil and gas resources and establishment of Australia's national representative system of marine protected areas through provision of spatial information about the physical and biological character of the seabed. Central to this approach is prediction of Australia's seabed biodiversity from spatially continuous data of physical seabed properties. However, information for these properties is usually collected at sparsely-distributed discrete locations, particularly in the deep ocean. Thus, methods for generating spatially continuous information from point samples become essential tools. Such methods are, however, often data- or even variable- specific and it is difficult to select an appropriate method for any given dataset. Improving the accuracy of these physical data for biodiversity prediction, by searching for the most robust spatial interpolation methods to predict physical seabed properties, is essential to better inform resource management practises. In this regard, we conducted a simulation experiment to compare the performance of statistical and mathematical methods for spatial interpolation using samples of seabed mud content across the Australian margin. Five factors that affect the accuracy of spatial interpolation were considered: 1) region; 2) statistical method; 3) sample density; 4) searching neighbourhood; and 5) sample stratification by geomorphic provinces. Bathymetry, distance-to-coast and slope were used as secondary variables. In this study, we only report the results of the comparison of 14 methods (37 sub-methods) using samples of seabed mud content with five levels of sample density across the southwest Australian margin. The results of the simulation experiment can be applied to spatial data modelling of various physical parameters in different disciplines and have application to a variety of resource management applications for Australia's marine region.