Publicly available baseline ecology data are compiled to provide a common information base for environmental, resource development and regulatory decisions in the Adavale Basin region. This web service summarises the existing knowledge of the ecosystems and environmental assets in the Adavale Basin region.

Publicly available baseline ecology data are compiled to provide a common information base for environmental, resource development and regulatory decisions in the Adavale Basin region. This data guide captures existing knowledge of the ecosystems and environmental assets overlying the Adavale Basin. The land overlying the Adavale Basin is dominated by Mulga and Mitchell Grass Downs Interim Biogeographic Regionalisation for Australia (IBRA) bioregions, with small areas of Brigalow Belt South and Desert Uplands bioregions. The data on the ecosystems and environmental assets overlying the Adavale Basin have been summarised in July 2021 to inform decisions on resource development activities. Key data sources are broad vegetation groups - pre-clearing and 2019 remnant - Queensland series (Queensland Government), Field Environmental Data, Australian Wetlands Database and Heritage places and lists (Department of Climate Change, Energy, the Environment and Water), and the Atlas of Living Australia.

Publicly available baseline ecology data are compiled to provide a common information base for environment, resource development and regulatory decisions in the Galilee Basin region. This data guide captures existing knowledge of the ecosystems and environmental assets overlying the Galilee Basin. The land overlying the Galilee Basin is dominated by the Mitchell Grass Downs Interim Biogeographic Regionalisation for Australia (IBRA) bioregion and contains nearly the entire Desert Uplands bioregion. There are also smaller areas of Mulga, Brigalow Belt bioregions, Channel Country, Gulf Plains and Einasleigh Uplands bioregions. The data on the ecosystems and environmental assets overlying the Galilee Basin have been summarised in July 2021 to inform decisions on resource development activities. Key data sources are broad vegetation groups - pre-clearing and 2019 remnant - Queensland series (Queensland Government), Field Environmental Data, Australian Wetlands Database and Heritage places and lists (Department of Climate Change, Energy, the Environment and Water), and the Atlas of Living Australia.

Spatially explicit predictive models of species distributions integrating fine quality habitat descriptors and species information have the potential to provide new insights into species-habitat associations and their range shifts. This study describes the distributions and interactions of two commercial marine macro-invertebrates blacklip abalone Haliotis rubra and black urchin Centrostephanus rodgersii along the coast of Victoria, Australia. A generalized linear modelling (GLM) was used to model current and future (IPCC scenario for the year 2100) occurrence and abundance of these benthic species by analyzing associations between observations from fisheries independent diver surveys and environmental variables from bathymetric light detection and ranging (LiDAR) derivatives and oceanographic parameters. Species spatial patterns were also evaluated in relation to observed macro-algae biota. The predictive GLM was suitable to predict species responses to environmental gradients with reef complexity , sea surface temperature (SST) and chlorophyll a (Chl a) influential predictors strongly associated with species distributions. H. rubra abundance showed a negative association with summer SST, conversely, the distribution of C. rodgersii showed positive responses to increasing winter SST. Furthermore, high abundance of H. rubra was associated with dense brown macro-algae whereas areas in high C. rodgersii densities were relatively devoid of algal assemblages and were low in abalone abundance. The modelling for the year 2100 predict a south-westward range extensions of urchin C. rodgersii, in response to increased ocean temperatures and the potential conflict with existing abalone commercial fishing grounds is discussed.

Australia has one of the world’s largest marine estates and has recently established the largest network of marine protected areas in the world. As such, Australia is now uniquely placed to develop standardised national approaches to monitor the marine environment. We have therefore developed a suite of field manuals for the acquisition of marine data from a variety of frequently-used sampling platforms so that data is directly comparable in time and through space. This will then facilitate a national monitoring program in Australian waters, with a particular focus on Australian Marine Parks (AMPs). Due to the large geographic area, diverse flora and fauna, and range of environmental conditions represented by the Australian marine estate, a single method of sampling is neither practical nor desirable. For this reason, we present a standard operating procedure (SOP) for each of six key marine benthic (i.e. seafloor) sampling platforms that were identified based on their frequency of use in previous sampling and monitoring programs: • Multibeam sonar (MBES) provides bathymetry and backscatter data that are used to map the seafloor. • Autonomous Underwater Vehicles (AUVs) acquire high-resolution continuous imagery of the seafloor and its associated habitats and organisms. • Benthic Baited Remote Underwater Video (BRUV) systems acquire video of demersal fish attracted to a baited camera system dropped to the seafloor. • Pelagic BRUVs acquire video of pelagic fish and other fauna that are attracted to a baited camera system suspended in the water column. This platform is included as an emergent sampling method for pelagic ecosystems. • Towed cameras acquire video or still imagery of the seafloor and its associated habitats and organisms. • Grabs and box corers collect sediment samples that can be analysed for biological, geochemical, or sedimentological variables. • Sleds and trawls collect benthic or demersal fauna near the seafloor. The main challenge in the development of these manuals was to find a balance between being overly prescriptive (such that everyone follows their existing protocols and ignores the manuals) and overly flexible (such that data is not consistent and therefore not comparable). A collaborative approach was paramount to addressing this concern. Ultimately, over 60 individuals from 28 organisations contributed to the field manual package. By engaging researchers, managers, and technicians from multiple agencies with a variety of experience, sea time, and subject matter expertise, we strove to ensure the field manuals represented the broader marine science community of Australia. This not only improved the content but also increased the potential for adoption across multiple agencies and monitoring programs. Future work is based on the understanding that SOPs should be periodically checked and revised, lest they become superseded or obsolete. Resources are available to develop a Version 2 of this field manual package, due for completion in late 2018. As part of this version, a long-term plan for managing the field manuals will be developed, including maintenance and version control.

Publicly available baseline ecology data are compiled to provide a common information base for environmental, resource development and regulatory decisions in the Cooper Basin region. This data guide captures existing knowledge of the ecosystems and environmental assets overlying the Cooper Basin. The land overlying the Cooper Basin is dominated by the Channel Country, Simpson Strzelecki Dunefields and Mulga Lands Interim Biogeographic Regionalisation for Australia (IBRA) bioregions with small areas of Mitchell Grass Downs and Stony Plains bioregions. The data on the ecosystems and environmental assets overlying the Cooper Basin have been summarised in July 2021 to inform decisions on resource development activities. Key data sources are broad vegetation groups - pre-clearing and 2019 remnant - Queensland series (Queensland Government), Field Environmental Data, Australian Wetlands Database and Heritage places and lists (Department of Climate Change, Energy, the Environment and Water), and the Atlas of Living Australia.

Publicly available baseline ecology data are compiled to provide a common information base for environmental, resource development and regulatory decisions in the Adavale Basin region. This web service summarises the existing knowledge of the ecosystems and environmental assets in the Adavale Basin region.

Relatively little is known about what the seafloor of Australia's continental shelf looks like or has living on it. Geoscience Australia (GA), together with other partners, undertakes a range of marine surveys to improve our understanding and management of Australia's marine environments. One component of the research involves the collection of underwater imagery to directly observe and characterise coastal and deep sea habitats. In some regions these surveys build on existing baseline knowledge, but in many areas, particularly deep offshore locations, these surveys provide the first images of the seafloor. The imagery collection includes both still and video imagery collected using various systems, including towed platforms, remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs). Post-survey reports and metadata files are included as part of the collection, which describe further details of the surveys and respective imagery collections. The seafloor imagery provides a wealth of information about the geological features, habitats and life forms occurring throughout Australia's marine jurisdiction. <b>Value: </b>Improve the understanding and management of Australia's marine environments. <b>Scope: </b>GA surveys from 2007 onwards in waters around Australia and Australia's Antarctic Territory.

Publicly available baseline ecology data are compiled to provide a common information base for environment, resource development and regulatory decisions in the Galilee Basin region. This web service summarises existing knowledge of the ecosystems and environmental assets in the Galilee Basin region.

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.