Recent datasets

This dataset summarises intertidal benthic surveys of Masig Island, Torres Strait in September 2020 into 3 GIS shapefiles. (1) The site shapefile describes (a) seagrass presence/absence, (b) species composition, (c) algae cover and (d) benthic macro-invertebrate cover at 128 sites. (2) The meadow shapefile describes seagrass communities for the intertidal meadow. (3) The interpolation shapefile describes variation in seagrass biomass within the meadow.

This dataset summarises intertidal benthic surveys of Dungeness Reef, Torres Strait, in September 2023 into 3 GIS shapefiles. (1) The point (site) shapefile describes (a) seagrass presence/absence and (b) species composition across 104 sites. (2) The meadow shapefile describes the seagrass community for the intertidal meadow. (3) The interpolation shapefile describes variation in seagrass biomass across sites for the intertidal meadows. The full report is: Carter A, Proctor M, David M, Scott A, Rasheed M and Torres Strait Regional Authority Land and Sea Rangers (2024).

This dataset summarises intertidal benthic surveys of Dungeness Reef, Torres Strait, in February 2023 into 3 GIS shapefiles. (1) The point (site) shapefile describes (a) seagrass presence/absence and (b) species composition across 113 sites. (2) The meadow shapefile describes the seagrass community for the intertidal meadow. (3) The interpolation shapefile describes variation in seagrass biomass across sites for the intertidal meadows. The full report is: Carter AB, Allan SJ, Scott A, Rasheed M and Torres Strait Regional Authority Land and Sea Rangers (2023).

This dataset provides modelled hourly, 0.01° (~1 km) resolution NetCDF grids of surface flow rates (water flowing over land and in rivers) from 1 Jan 2007 through to 31 Dec 2023 in the catchments of the Great Barrier Reef. This dataset was generated with the Grid‑to‑Grid (G2G) distributed hydrological model configured jointly by the Bureau of Meteorology (BOM) and the UK Centre for Ecology & Hydrology (UKCEH). Flows were produced based on blended gridded rainfall and potential evapotranspiration with mapped landscape data (terrain, soils, land cover, derived river channel dimensions).

This dataset consists of two years of relative coral recruitment from within and among reefs in the Cairns-Port Douglas region from 2023 to 2025. The dataset includes one csv of the site gps coordinates where recruitment tiles were deployed during annual mass spawning periods in 2023/2024 and 2024/2025. A second csv file provides a summary of recruits recorded per tile at each site in total and, where possible, total recruits for three Scleractinia family groups or ‘Other’ where not identifiable.

This dataset records Scooter Assisted Large Area Diver-based (SALAD) surveys of Crown of Thorns Starfish (CoTS) in the northern Great Barrier Reef from 2019 - 2025. Using scooters allows large coral reef areas to be surveyed, while allowing divers to slow down and spend more time to locate cryptic CoTS where scars on coral are visible. This dataset records the density of CoTS over the survey tracks and size measurements of individual CoTS. This dataset comprises of two inter-related tables.

This dugong (Dugong dugon) aerial survey database compiles observations collected by James Cook University (JCU) from systematic aerial surveys conducted along the Australian coast since 1984. Each survey is represented by a unique survey identifier (eventID), with multiple occurrence records derived from individual sightings made during that survey.

This record provides an overview of the NESP Marine and Coastal Hub Project 'Water quality trends analysis at key GBR basins (sediment and DIN)'. For specific data outputs from this project, please see child records associated with this metadata. Despite considerable government investment in Great Barrier Reef catchment area (GBRCA) water quality programs (>$2B) including on-ground works and regulation, this is the first comprehensive analysis of long-term trends in empirical water quality monitoring data to test and quantify any detectable changes.

The vessel tracking data in this product originates from the Australian Maritime Safety Authority’s (AMSA) Craft Tracking System (CTS) and Mariweb databases. These systems collect Automatic Identification System (AIS) signals from ships using both terrestrial and satellite receivers. AIS data from these sources, covering the period from September 2012 to the most recently completed month, provides vessel position reports across the entire Australian Search and Rescue Region.

This collection contains supporting datasets created to assist in estimating the number of reefs in the Coral Sea and northern Australia. The 'Analysis-regions' shapefile provides standardised spatial boundaries defining reporting regions across northern Australia and adjacent waters (Great Barrier Reef, Torres Strait, Coral Sea, and northern/northwestern coastal areas) used to aggregate and compare reef count statistics.

This dataset corresponds to high resolution (10 m) raster shallow benthic and geomorphic habitat maps for Northern and Western Australia estimated from Sentinel 2 composite imagery from 2018 – 2023. Benthic classes include sand, rubble, rock, seagrass, coral/algae, microalgal mats and light seagrass. Geomorphic classes include deep, sediment slope, shallow lagoon, deep lagoon, inner reef flat, outer reef flat, reef crest, terrestrial reef flat, sheltered reef slope, plateau, back reef slope, small reef and rocky reef.

This dataset documents the evaluation and selection of crown-of-thorns starfish (CoTS) larval connectivity matrices for use in ReefMod-GBR, along with the subsequent calibration of CoTS population parameters. The project evaluated which pre-existing connectivity matrix set produces the most accurate CoTS density predictions when integrated into the model, and determined the optimal parameter values for that matrix set. Note: This metadata record is published for discovery purposes only; the dataset files are not directly available for download.

This record describes the visualisations made available through the AIMS eReefs visualisation platform (https://ereefs.aims.gov.au/). It is a collection of 88,000 pre-rendered animations and static maps of selected combinations of model variables from the eReefs hydrodynamic and biogeochemical models. Each visualisation product shows multiple related variables together to assist in understanding the dynamics that drive the marine environmental conditions on the Great Barrier Reef and Coral Sea.

This dataset contains a shapefile of the boundaries of more than 23,000 tropical coral reefs, rocky reefs and sand banks of tropical Australia, covering Indian Ocean, Timor Sea, Gulf of Carpentaria, Torres Strait, Great Barrier Reef and the Coral Sea. This dataset provides the first comprehensive mapping of the reefs of tropical Australia, covering intertidal rocky reefs through to offshore oceanic coral reefs. It includes all reefs shallower than approximately 10 - 30 m on the continental shelf and up to 60 m depth in oceanic waters.

This dataset provides mapping of over 11,800 shallow coral reef, rocky reef, and sand bank feature boundaries in the north and west of tropical Australia. This dataset is intended to assist with environmental accounting, marine management, marine research planning and environmental impact assessments. All features were digitised manually from satellite imagery that was optimised for image clarity of marine habitats (Hammerton & Lawrey, 2024a; Hammerton & Lawrey, 2024b).

Highly pathogenic avian influenza (HPAI) is endemic in many countries along the East Asian-Australasian Flyway (EAAF). Shorebirds are noted carriers of avian influenza [1], making them likely candidates to not only fall victim to the increasingly alarming HPAI panzootic [2, 3], but also cause incursions of the virus into Australia [4]. Understanding the current and future migratory connectivity of different Australian shorebird populations within sites along their flyway is required to better predict and mitigate disease incursion risks.

This dataset is a collection of spatial climatologies derived from the eReefs hydrodynamic and biogeochemical models for the Great Barrier Reef (GBR) region. It contains GeoTiff raster files representing long-term average conditions for numerous environmental variables across different depths (3m, 9m, 18m, and 39m below surface) and models (GBR4 BGC v3.1 2011 - 2018, GBR4 Hydro v2.0 2011 - 2023, and GBR1 Hydro v2.0 2015 - 2023). Each GeoTiff represents the average conditions over the set of whole years in the model time series.

This dataset consists of drone footage (DJI Mini 2) taken at the fringing reef off Pretty Beach, south of Port Douglas in Queensland at low tide (0.5 - 0.6 m LAT) on 2022-10-06. It contains 16 videos showing the reef from a broad range of angles including footage from 90 m and low footage from 6 m elevation. It also includes the raw photos to create two orthomosaics. The first corresponds to 310 photos that cover the whole reef from 90 m and the second consists of 176 photos covering a central strip of the of the reef taken from 6 m elevation.

This dataset represents a comprehensive mapping of shallow marine areas across Northern Australia and the Great Barrier Reef, encompassing intertidal zones, shallow subtidal habitats (down to approximately 5 meters depth in turbid waters), and offshore reef features visible at depths of up to 40 meters in clear waters. Derived from Sentinel-2 composite imagery, it identifies benthic areas where seafloor features are visible in the satellite imagery, providing a mask for mapping of marine habitats from Sentinel 2 imagery.

The 2020 Independent Review of the EPBC Act (the Samuel Review) states that “Decision-makers, proponents and the community do not have access to the best available data, information and science. This results in sub-optimal decision-making, inefficiency and additional cost for business, and poor transparency for the community. Immediate investment in the information supply chain is needed to support reform. We can't wait until perfect data is available.