Monitoring changes in the spatial distribution and health of biotic habitats requires spatially extensive surveys repeated through time. Although a number of habitat distribution mapping methods have been successful in clear, shallow-water coastal environments (e.g. aerial photography and Landsat imagery) and deeper (e.g. multibeam and sidescan sonar) marine environments, these methods fail in highly turbid and shallow environments such as many estuarine ecosystems. To map, model and predict key biotic habitats (seagrasses, green and red macroalgae, polychaete mounds [Ficopamatus enigmaticus] and mussel clumps [Mytilus edulis]) across a range of open and closed estuarine systems on the south-west coast of Western Australia, we integrated post-processed underwater video data with interpolated physical and spatial variables using Random Forest models. Predictive models and associated standard deviation maps were developed from fine-scale habitat cover data. Models performed well for spatial predictions of benthic habitats, with 79-90% of variation explained by depth, latitude, longitude and water quality parameters. The results of this study refine existing baseline maps of estuarine habitats and highlight the importance of biophysical processes driving plant and invertebrate species distribution within estuarine ecosystems. This study also shows that machine-learning techniques, now commonly used in terrestrial systems, also have important applications in coastal marine ecosystems. When applied to video data, these techniques provide a valuable approach to mapping and managing ecosystems that are too turbid for optical methods or too shallow for acoustic methods.

Coral reefs occur in shallow water with sea surface temperatures (SST) greater than 18ºC, extending beyond the tropics where warm currents enable their establishment [Hopley et al., 2007]. The southernmost reef in the Pacific Ocean occurs at Lord Howe Island (31° 30°S), fringing 6 km of the western margin of the island, with isolated reef patches on the north, west and eastern sides. The island is a Miocene volcanic remnant on the western flank of the Lord Howe Rise (foundered continental crust) formed of basaltic cliffs rising to 875 m, flanked by Quaternary eolianites [McDougall et al., 1981]. The reefs support 50-60 species of scleractinian corals, whose rates of growth are only slightly slower than in more tropical locations [Harriott and Banks, 2002]. However, carbonate sediments on the surrounding shelf are dominated by temperate biota, such as foraminifera and algal rhodoliths [Kennedy et al., 2002]. Prominent in mid shelf is a broad ridge-like feature that rises from water depths of 30-50 m, which we considered to be a relict coral reef that formerly encircled the island [Woodroffe et al., 2005, 2006]. This paper describes results of sonar swath mapping to determine the extent of the reef, and coring and dating that establishes its age and demise.

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.

OzCoasts is a web-based database and information system managed by Geoscience Australia that draws together a diverse range of data and information on Australia's coasts and estuaries. Maps, images, reports and data can be downloaded and there are tools to assist with coastal science, monitoring, management and policy. A Tropical Rivers module is the newest major feature of the website and was developed in partnership with the Griffith University node of the Tropical Rivers and Coastal Knowledge (TRaCK) consortium and Boab Interactive. The module contains the Australian Riverine Landscape Classifier (AURICL) and provides links to the TRaCK Digital Atlas. AURICL will assist researchers and policy makers make better decisions about riverine landscapes. It is a dynamic and flexible system (i.e. can be updated as new data layers become available) for classifying and comparing tropical catchments and their rivers based on the similarity, or dissimilarity, of a wide range of parameters. Importantly, AURICL provides researchers with: (i) data-sets to link stream segments from the National Catchment Boundaries database to estuary point locations for north Australia; (ii) a collection of riverine attribute data that sum their upstream contributions to an estuary; and (iii) an amalgamation of inputs for estuaries with multiple contributing streams. To date, researchers have only had access to very general data on the catchments that feed estuaries (e.g. catchment areas). The Mangroves and Coastal Saltmarsh of Victoria: Distribution, Condition, Threats and Management report is new to the Habitat Mapping module, and constitutes the first State-wide assessment of Victoria's coastal wetlands. The 514 page report, led by Prof. Paul Boon (Victoria University), examines the diversity of wetland types and plant communities along the Victorian coast and provides analysis of the ecological condition and major threats to coastal wetlands in Victoria. OzCoasts will also soon deliver the Coastal Eutrophication Risk Assessment Tool (CERAT) for the NSW Office of Environment and Heritage. CERAT will help identify and prioritise land use planning decisions to protect and preserve the health of NSW estuaries. A partnership between OzCoasts and the coastal facility of the TERN (Terrestrial Ecosystem Research Network) is also currently under negotiation.

Legacy product - no abstract available

Note that this Record has now been published as Record 2014/050, GeoCat number 78802

The variability in the inherent optical properties along an estuary-coast-ocean continuum in tropical Australia has been studied. The study area, the Fitzroy Estuary and Keppel Bay system, is a shallow coastal environment (depth < 30 m) with highly turbid waters in the estuary and blue oceanic waters in the bay and subject to macrotides. Biogeochemical and inherent optical properties (IOPs) were sampled in the near-surface layer spatially and across the tidal phase during the dry season. These determinations included continuous measurements of spectral absorption, scattering and backscattering coefficients, together with discrete measurements of spectral absorption coefficients of phytoplankton, nonalgal particles and colored dissolved organic matter, and concentrations of phytoplankton pigments and suspended matter. Because of a large variability in the characteristics of the water components on short spatial and temporal scales, we observe a large variability in the associated optical properties. From the estuary to the bay, particle scattering and dissolved absorption decreased by 2 orders of magnitude, and nonalgal particle absorption decreased by 3 orders of magnitude. We also observed a strong variability in particle single scattering albedo and backscattering efficiency (by a factor of 6) and in specific IOPs (IOPs normalized by the relevant constituent concentration) such as suspended matter-specific particle scattering and chlorophyll-specific phytoplankton absorption. Superimposed on this strong spatial variability is the effect of the semidiurnal tide, which affects the spatial distribution of all measured properties. These results emphasize the need for spatially and temporally adjusted algorithms for remote sensing in complex coastal systems.

This dataset maps the geomorphic habitat environments (facies) for 36 South Australian coastal waterways. The classification system contains 12 easily identifiable and representative environments: Barrier/back-barrier, Bedrock, Central Basin, Channel, Coral, Flood- and Ebb-tide Delta, Fluvial (bay-head) Delta, Intertidal Flats, Mangrove, Rocky Reef, Saltmarsh/Saltflat, Tidal Sand Banks (and Unassigned). These types represent habitats found across all coastal systems in Australia. Most of the 36 coastal waterways have a "Modified" environmental condition (as opposed to "Near Pristine"), according to the National Land and Water Resources Audit definition.

This dataset maps the geomorphic habitat environments (facies) for 88 Tasmanian coastal waterways. The classification system contains 11 easily identifiable and representative environments: Barrier/back-barrier, Bedrock, Central Basin, Channel, Coral, Flood- and Ebb-tide Delta, Fluvial (bay-head) Delta, Intertidal Flats, Rocky Reef, Saltmarsh/Saltflat, Tidal Sand Banks (and Unassigned). These types represent habitats found across all coastal systems in Australia. The majority of near pristine estuaries in Tasmania are located in the south and west of the State and on Cape Barren Island, according to the Department of Primary Industries, Water and Environment.

Diatom assemblages in sandy deposits of the 2004 tsunami at Phra Thong Island, Thailand may provide clues to flow conditions during the tsunami. The tsunami deposits contain one or more beds that fine upward, commonly from medium sand to silty very fine sand. Diatom assemblages of the lowermost portion of the deposit predominantly comprise of unbroken beach and subtidal species that live attached to sand grains. The dominant taxa shift to marine plankton species in the middle of the bed and to a mix of freshwater, brackish, and marine species near the top. These trends are consistent with expected changes in current velocities of tsunami through time. During high current velocities, medium sand is deposited; only beach and subtidal benthic diatoms attached to sediment can be incorporated into the tsunami deposit. High shear velocity keeps finer material, including planktonic diatoms in suspension. With decreasing current velocities, finer material including marine plankton can be deposited. Finally, during the lull between tsunami waves, the entrained freshwater, brackish, and marine species settle out with mud and plant trash. Low numbers of broken diatoms in the lower medium sand implies rapid entrainment and deposition, whilst selective breakage of marine plankton (Thalassionema nitzschioides, and Thalassiosira and Coscinodiscus spp.) in the middle portion of the deposit probably results from abrasion in the turbulent current before deposition.