Marine benthic biodiversity can be measured using a range of sampling methods, including benthic sleds or trawls, grabs, and imaging systems, each of which targets a particular community or habitat. Due to the high cost and logistics of benthic sampling, particularly in the deep sea, studies are often limited to only one or two biological sampling methods. Results of biodiversity studies are used for a range of purposes, including species inventories, environmental impact assessments, and predictive modelling, all of which underpin appropriate marine resource management. However, the generality of marine biodiversity patterns identified among different sampling methods is unknown, as are the associated impacts on management decisions. This report reviews studies that have used two or more sampling methods in order to determine the consistency of their results among gear types, as well as the optimum combination of gear types. In addition, we directly analyse data that were acquired using multiple gear types to examine the consistency of biodiversity patterns among different gear types. These data represent two regions: 1) Joseph Bonaparte Gulf (JBG) in northern Australia, and 2) Icelandic waters as part of the Benthic Invertebrates of Icelandic Waters (BIOICE) program. For each dataset, we investigate potential patterns of biodiversity (measured by species richness, diversity indices, abundance, and community structure) in relation to environmental variables such as depth, geomorphology, and substrate. The availability of worldwide data from benthic marine biodiversity surveys reporting the results of two or more gear types is generally poor. Surveys were concentrated in the coastal regions of UK, Norway and Australia, with limited or no studies elsewhere and only 13% including the slope or deep sea. Between different gear groups, our review and analysis of datasets from two regions (northern Australia and Iceland) demonstrates there is little consistency in marine biodiversity trends, with only one study yielding consistent ecological patterns between sampling gear groups (imagery and epifaunal). This indicates that ideal gear combinations are not easily able to be generalised among studies and regions. In addition, the lack of consistency between sampling gear groups highlights the need to analyse gear-specific data and avoid amalgamation. Even among gear that yielded relatively consistent ecological relationships, results varied across biological or environmental factors. Within a gear group, there are more consistencies in ecological relationships, with only two out of the eight studies compiled showing inconsistent ecological relationships A lack of gear-specific studies precluded the determination of the optimal combination of gear types for a particular regions or environments. Nevertheless, based on our findings, we provide preliminary recommendations and inform further research: 1) If general biodiversity patterns are to be investigated, sampling for marine benthic surveys should be carried out using multiple gear types that are concurrently deployed; 2) Target measures of biodiversity need to be decided a priori and appropriate gear used; 3) Preliminary data will help determine the optimal combination of gear types used to sample that region and address a given hypothesis; and 4) If only two gear types are able to be deployed, a grab or corer should be one of them, as this sampling gear type samples a different habitat than other gear groups.

This resource contains geochemistry data for the Oceanic Shoals Commonwealth Marine Reserve (CMR) in the Timor Sea collected by Geoscience Australia during September and October 2012 on RV Solander (survey GA0339/SOL5650). This dataset comprises inorganic element data from the fine fraction (Mud: <63um) of the upper ~2cm of seabed sediment. The Oceanic Shoals Commonwealth Marine Reserve survey was undertaken as an activity within the Australian Government's National Environmental Research Program Marine Biodiversity Hub and was the key component of Research Theme 4 - Regional Biodiversity Discovery to Support Marine Bioregional Plans. Hub partners involved in the survey included the Australian Institute of Marine Science, Geoscience Australia, the University of Western Australia, Museum Victoria and the Museum and Art Gallery of the Northern Territory. Data acquired during the survey included: multibeam sonar bathymetry and acoustic backscatter; sub-bottom acoustic profiles; physical samples of seabed sediments, infauna and epibenthic biota; towed underwater video and still camera observations of seabed habitats; baited video observations of demersal and pelagic fish, and; oceanographic measurements of the water column from CTD (conductivity, temperature, depth) casts and from deployment of sea surface drifters. Further information on the survey is available in the post-survey report published as Geoscience Australia Record 2013/38 (Nichol et al. 2013).

Marine visual imaging has become a major assessment tool in the science, policy and public understanding of our seas and oceans. The technology to acquire and process this imagery has significantly evolved in recent years through the development of new camera platforms, camera types, lighting systems and analytical software. These advances have led to new challenges in imaging, including storage and management of `big data, manipulation of digital photos, and the extraction of biological and ecological data. The need to address these challenges, within and beyond the scientific community, is set to substantially increase in the near future, as imaging is increasingly used in the designation and evaluation of marine conservation areas, and for the assessment of environmental baselines and impact monitoring for maritime industry. We review the state of the theory, techniques and technologies associated with each of the steps of marine imaging for observation and research, and to provide an outlook on the future from this active scientific and engineering community that develops and uses it.

At the Australian Marine Sciences Association conference held in Canberra in July 2014, a group of scientists and managers engaged in a roundtable discussion to identify areas where linkages could be improved between researchers working on marine population connectivity and managers of marine areas. Population connectivity is the degree of demographic connectedness between populations, indicating the degree to which populations are linked through dispersal and recruitment of organisms, or through gene flow. Connectivity allows organisms and genes to move among different habitats, helping to ensure survival of species by providing increased habitat and reproduction options, and helping to maintain genetic variability. Although connectivity science was used as the focal point of the discussion, the issues discussed are applicable to other topics at the interface of science and management. Here we summarise the key themes and outcomes/recommendations from the discussion.

The Jervis Bay Multibeam 2 survey, was acquired by Geoscience Australia after the purchase of the new shallow bathymetry acquisition systems Kongsberg EM3002D. This system is a mobile and compact system that can be installed on different vessels. This survey was acquired by the DSTO vessel, RV Kimbla during the 31st of May to the 5 of June 2008. The survey location was in Jervis Bay. The aim of the survey was to test the new bathymetry acquisition system and to acquire geophysical data on the shallow water (less than 100m water depth) seabed environment. The bathymetry grids are of 1m resolution projected in Easting and Northing WGS84 UTM 56S

A fully four-dimensional (3D x time) object-oriented biophysical dispersal model was developed to simulate the movement of marine larvae over semi-continuous surfaces. The model is capable of handling massive numbers of simulated larvae, can accommodate diverse life history patterns and distributions of characteristics, and saves point-level information to a relational database management system.

Seafloor bathymetric data and its derivatives fulfil a range of applications that are relevant to supporting the management of marine ecosystems and can provide a potentially powerful physical surrogate for benthic biodiversity. Similarly, morphological and seafloor terrain variables such as slope, curvature and rugosity derived from bathymetry data through GIS analysis not only describe seabed morphology but can also act as proxies for oceanographic processes The distributions of benthic marine fauna and flora most commonly respond to local changes in the topography of the seafloor. When seafloor topography is coupled with biological surveys it can help managers understand which environments contribute most to the growth, reproduction and survival of marine species. These models of habitat suitability provide natural resource managers with a tool with which to visualise the potential habitats of particular species. The accuracy of the habitat suitability models however, is critically reliant on the accuracy of underlying bathymetric data. The uncertainty in the bathymetric data is often ignored and often there is little recognition that the input bathymetric data and the derived spatial data products of the bathymetric data are merely modelled representations of one reality. These models can contain significant levels of uncertainty that are dependent upon the original depth measurements. This research paper explores a method to represent the uncertainty in bathymetric data. We discover that multibeam bathymetry data uncertainties are stochastic at individual soundings but exhibit a distinct spatial distribution with increasing magnitude from nadir to outer beams. We find that the restricted spatial randomness method is able to realistically simulate both the stochastic and spatial characteristics of the data uncertainty. This research concludes that the Monte Carlo method is appropriate for the uncertainty analysis of GIS operations and although the multibeam bathymetry data have notable overall uncertainty level, its impact on subsequent derivative analysis is likely to be minor in this dataset at the 2 m scale. Monitoring and change detection of the seafloor requires detailed baseline data with uncertainty estimates to ensure that features that display change are reliably detected. The accuracy of marine habitat maps and their associated levels of uncertainty are extremely hard to convey visually or to quantify with existing methodologies. The new techniques developed in this research integrate existing statistical techniques in a novel way to improve insights into classification and related uncertainty for seabed habitat maps which will progress and improve resource management for regional and national ocean policy.

Promotional magnetic panel produced for the conference booth to be used at seabed mapping conferences. The panel highlights research conducted by Geoscience Australia in mapping and modelling processes that occur in Australian submarine canyons under the National Enrvironmental Research Program.

Flythrough movie showing the bathymetry, seabed habitats and biota of the outer continental shelf within the Flinders Commonwealth Marine Reserve (CMR), offshore from Flinders Island northeast Tasmania. The bathymetric image is derived from multibeam sonar collected by Geoscience Australia in 2012 using a 30 kHz Simrad EM3002 system on RV Challenger. Videos and seabed images were collected by the University of Tasmania and CSIRO as part of the same field program. Key features on the shelf bathymetry include low profile reefs, flat sandy seabed and the heads of two submarine canyons. The reefs provide hard substrate for sponge gardens whereas the sand flats are mostly barren. The two submarine canyons are sites of local upwelling, and attract large schools of Tasmanian Striped Trumpeter. The Flinders CMR is a study site for the Marine Biodiversity Research Hub, funded through the National Environmental Research Program (NERP). ..

New mapping by Geoscience Australia has identified 713 submarine canyons on the Australian margin and an additional 40 within external territorial seas. Ninety-five canyons are classified as shelf-incising and the remainders are located on the continental slope and classed as blind canyons. A range of metrics were derived to describe canyon form and distribution and used to identify morphologically unique canyons. This poster illustrates this dataset in the context of the national network of Commonwealth Marine Reserves.