The eAtlas delivers its mapping products via two Web Mapping Services, a legacy server (from 2008-2011) and a newer primary server (2011+) to which all new content it added. This record describes the legacy WMS.

This service delivers map layers associated with the eAtlas project (http://eatlas.org.au), which contains map layers of environmental research focusing on the Great Barrier Reef. The majority of the layers corresponding to Glenn De'ath's interpolated maps of the GBR developed under the MTSRF program (2008-2010).

This web map service is predominantly maintained for the legacy eAtlas map viewer (http://maps.eatlas.org.au/geoserver/www/map.html). All the these legacy map layers are available through the new eAtlas mapping portal (http://maps.eatlas.org.au), however the legends have not been ported across.

This WMS is implemented using GeoServer version 1.7 software hosted on a server at the Australian Institute of Marine Science.

For ArcMap use the following steps to add this service: 1. "Add Data" then choose GIS Servers from the "Look in" drop down. 2. Click "Add WMS Server" then set the URL to "http://maps.eatlas.org.au/geoserver/wms?"

Note: this service has around 460 layers of which approximately half the layers correspond to Standard Error maps, which are WRONG (please ignore all *Std_Error layers.

This services is operated by the Australian Institute of Marine Science and co-funded by the MTSRF program.

The eAtlas delivers its mapping products via two Web Mapping Services, a legacy server (from 2008-2011) and a newer primary server (2011+) to which all new content it added. This record describes the primary WMS.

This service delivers map layers associated with the eAtlas project (http://eatlas.org.au), which contains map layers of environmental research focusing on the Great Barrier Reef and its neighbouring coast, the Wet Tropics rainforests and Torres Strait. It also includes lots of reference datasets that provide context for the research data. These reference datasets are sourced mostly from state and federal agencies. In addition to this a number of reference basemaps and associated layers are developed as part of the eAtlas and these are made available through this service.

This services also delivers map layers associated with the Torres Strait eAtlas.

This web map service is predominantly set up and maintained for delivery of visualisations through the eAtlas mapping portal (http://maps.eatlas.org.au) and the Australian Ocean Data Network (AODN) portal (http://portal.aodn.org.au). Other portals are free to use this service with attribution, provided you inform us with an email so we can let you know of any changes to the service.

This WMS is implemented using GeoServer version 2.3 software hosted on a server at the Australian Institute of Marine Science. Associated with each WMS layer is a corresponding cached tiled service which is much faster then the WMS. Please use the cached version when possible.

The layers that are available can be discovered by inspecting the GetCapabilities document generated by the GeoServer. This XML document lists all the layers, their descriptions and available rendering styles. Most WMS clients should be able to read this document allowing easy access to all the layers from this service.

For ArcMap use the following steps to add this service: 1. "Add Data" then choose GIS Servers from the "Look in" drop down. 2. Click "Add WMS Server" then set the URL to "http://maps.eatlas.org.au/maps/wms?"

Note: this service has over 1000 layers and so retrieving the capabilities documents can take a while.

This services is operated by the Australian Institute of Marine Science and co-funded by the National Environmental Research Program Tropical Ecosystems hub.

This dataset contains Landsat 5 imagery for selected areas of Queensland, currently Torres Strait and around Lizard Island and Cape Tribulation. This collection was made as a result of the …Show full descriptionThis dataset contains Landsat 5 imagery for selected areas of Queensland, currently Torres Strait and around Lizard Island and Cape Tribulation. This collection was made as a result of the development of the Torres Strait Features dataset. It includes a number (typically 4 - 8) of selected Landsat images for each scene from the entire Landsat 5 archive. These images were selected for having low cloud cover and clear water. The aim of this collection was to allow investigation of the marine features. The complete catalogue of Landsat 5 for scenes 96_70, 96_71, 97_67, 97_68, 98_66, 98_67, 98_68_99_66, 99_67 and 99_68 were downloaded from the Google Earth Engine site ( https://console.developers.google.com/storage/earthengine-public/landsat/ ). The images were then processed into low resolution true colour using GDAL. They were then reviewed for picture clarity and the best ones were selected and processed at full resolution to be part of this collection. The true colour conversion was achieved by applying level adjustment to each channel to ensure that the tonal scaling of each channel was adjusted to give a good overall colour balance. This effectively set the black point of the channel and the gain. This adjustment was applied consistently to all images. Red: Channel B3, Black level 8, White level 58 Green: Channel B2, Black level 10, White level 55 Blue: Channel B1, Black level 32, White level 121 Note: A constant level adjustment was made to the images regardless of the time of the year that the images were taken. As a result images in the summer tend to be brighter than those in the winter. After level adjustment the three channels were merged into a single colour image using gdal_merge. The black surround on the image was then made transparent using the GDAL nearblack command. This collection consists of 59 images saved as 4 channel (Red, Green, Blue, Alpha) GeoTiff images with LZW compression (lossless) and internal overviews with a WGS 84 UTM 54N projection. Each of the individual images can be downloaded from the eAtlas map client (Overlay layers: eAtlas/Imagery Base Maps Earth Cover/Landsat 5) or as a collection of all images for each scene. Data Location: This dataset is filed in the eAtlas enduring data repository at: data\NERP-TE\13.1_eAtlas\QLD_NERP-TE-13-1_eAtlas_Landsat-5_1988-2011

The Bright Earth eAtlas Basemap dataset collection is a satellite-derived global map of the world at a 1:1M scale for most of the world and 1:200k scale for Australia. This map was inspired by Natural Earth II (NEII) and NASA's Blue Marble Next Generation (BMNG) imagery.

Its aim was to provide a basemap similar to NEII but with a higher resolution (~10x).

This basemap is derived from the following datasets: Blue Marble Next Generation 2004-04 (NASA), VMap0 coastline, Coast100k 2004 Australian coastline (GeoScience Australia), SRTM30 Plus v8.0 (UCSD) hillshading, Natural Earth Vector 10m bathymetry and coastline v2.0 (NE), gbr100 hillshading (JCU).

This dataset (World_Bright-Earth-e-Atlas-basemap) contains all the files required to setup the Bright Earth eAtlas basemap in a GeoServer. All the data files are stored in GeoTiffs or shapefiles and so can also be loaded into ArcMap, however no styling has been included for this purpose.

This basemap is small enough (~900 MB) that can be readily used locally or deployed to a GeoServer.

Base map aesthetics (added 28 Jan 2025)

The Bright Earth e-Atlas Basemap is a high-resolution representation of the Earth's surface, designed to depict global geography with clarity, natural aesthetics with bright and soft color tones that enhance data overlays without overwhelming the viewer. The land areas are based on NASA's Blue Marble imagery, with modifications to lighten the tone and apply noise reduction filtering to soften the overall coloring. The original Blue Marble imagery was based on composite satellite imagery resulting in a visually appealing and clean map that highlights natural features while maintaining clarity and readability. Hillshading has been applied across the landmasses to enhance detail and texture, bringing out the relief of mountainous regions, plateaus, and other landforms.

The oceans feature three distinct depth bands to illustrate shallow continental areas, deeper open ocean zones, and the very deep trenches and basins. The colors transition from light blue in shallow areas to darker shades in deeper regions, giving a clear sense of bathymetric variation. Hillshading has also been applied to the oceans to highlight finer structures on the seafloor, such as ridges, trenches, and other geological features, adding depth and dimensionality to the depiction of underwater topography.

At higher zoom levels prominent cities are shown and the large scale roads are shown for Australia.

Rendered Raster Version (added 28 Jan 2025)

A low resolution version of the dataset is available as a raster file (PNG, JPG and GeoTiff) at ~2 km and 4 km resolutions. These rasters are useful for applications where GeoServer is not available to render the data dynamically. While the rasters are large they represent a small fraction of the full detail of the dataset. The rastered version was produced using the layout manager in QGIS to render maps of the whole world, pulling the imagery from the eAtlas GeoServer. This imagery from converted to the various formats using GDAL. More detail is provided in 'Rendered-bright-earth-processing.txt' in the download and browse section.

Change Log 2025-01-28: Added two rendered raster versions of the dataset at 21600x10800 and 10400x5400 pixels in size in PNG, JPG and GeoTiff format. Added

The eAtlas delivers its NetCDF (Network Common Data Form) data file using a THREDDS Data Server (TDS), which provides metadata and data access using OPeNDAP, OGC WMS and WCS, HTTP, and other remote data access protocols.

The services delivers data, matadata and map layers associated with the eAtlas project (https://eatlas.org.au). The data focus on environmental research on the Great Barrier Reef and its neighbouring coast, the Wet Tropics rainforests and Torres Strait. The map layers served by the WMS service can be used to create environmental maps when combine with other dataset such as the layers provided by the eAtlas Web Mapping Service (https://eatlas.org.au/data/uuid/71127e4d-9f14-4c57-9845-1dce0b541d8d).

This web map service is predominantly set up and maintained for delivery of visualisations through the eAtlas mapping portal (https://maps.eatlas.org.au). Other portals are free to use this service with attribution, provided you inform us with an email so we can let you know of any changes to the service.

This THREDDS Data Server software is hosted on a Amazon Web Services (AWS) server. Associated with each NetCDF dataset, there is a list of corresponding WMS layers, one for each data variable, which can be discovered by inspecting the corresponding GetCapabilities document. This XML document lists all the layers, a short descriptions and available rendering styles. Most WMS clients should be able to read those documents allowing easy access to all the variables for a given NetCDF dataset.

This services is operated by the Australian Institute of Marine Science and co-funded by the National Environmental Science Program Tropical Water Quality (NESP TWQ) Hub.

This dataset is a combination of two projects monitoring long-term trends in coral reef communities of the Great Barrier Reef (GBR) - NERP TE Project 1.1 Monitoring status and trends of coral reefs of the GBR (AIMS) (see https://eatlas.org.au/data/uuid/1a46774e-a3ac-4982-b08b-94ce1ad8d45c) and NERP TE Project 8.1 Monitoring the ecological effects of the Great Barrier Reef Zoning Plan on mid- and outer-shelf reefs (AIMS) (see https://eatlas.org.au/data/uuid/2cf689a9-2f4e-4658-b838-9bdca45919ea) . Coral cover in percentage has been recorded at the family level. Data accessed 2020-03-20 from https://apps.aims.gov.au/metadata/view/5a8a4b00-4ade-11dc-8f56-00008a07204e using the two 'Subset of data...' links in the General Links section.

This dataset consists reprocessing and reformatting the SRTM30 PLUS v8.0 Digital Elevation Model (DEM) dataset developed by Scripps Institute Of Oceanography, University of California San Diego (UCSD) to produce a single raster covering the globe in GeoTiff format and create a full and low resolution hillshading from this DEM. The aim of this derived dataset is to reformat the data to allow easy use with GIS applications.

Full resolution hillshading:

The hillshading was produced by combining the 33 source DEMs using gdal_translate then processing using gdaldem with a z-factor of 0.0001. This output was then formatted as a JPEG compressed GeoTiff file with internal overviews (World_e-Atlas-UCSD_SRTM30-plus_v8_Hillshading.tif).

Low resolution smoothed hillshading:

A lower resolution of the hillshading (World_e-Atlas-UCSD_SRTM30-plus_v8_Hillshading-lr.tif) was also produced for for use when displaying zoomed out global maps. By making the hillshading smoother the bulk features (mountain ranges, etc) are easier to see.

This was generated by subsampling the DEM by two times (down to 21600x10800 pixels) then smoothing it with a pixel Gaussian filter. This was achieved using gdalwarp to subsample the data. Gdalbuildvrt was then used to create a virtual dataset that included a 4 pixel Gaussian filter kernel. The hillshading was then applied to this filtered data source using gdaldem with a z-factor of 0.0003, which 3 times stronger than the high resolution version of this dataset.

This dataset summarises 30 years of seagrass data collection (1984-2014) within the Great Barrier Reef World Heritage Area into a GIS shapefile which describes seagrass at 1,169 individual or composite meadows. The data includes information on species, meadow type and age and reliability of the data. The data described by this record is current as of 01/12/2016 for use in the The data described by this record is current as of 01/12/2016 for use in the Seamap Australia project. Newer versions of the data, additional 'point' site data, and alternative download formats are available from eAtlas. http://eatlas.org.au/geonetwork/srv/eng/metadata.show?u uid=77998615-bbab-4270-bcb1-96c46f56f85a

This dataset corresponds to a database of datasets that are relevant for the development of coastal development scenarios and impact assessments GBR. It corresponds to a list of all the datasets that were sourced as part of project 9.4. It contains basic information about each dataset along with the license that each dataset was obtained under and where the data can be sourced. This database is an excellent starting point for any others looking at obtaining data relevant for coastal management.

Methods:

Datasets were sourced from a large and various. They are presented in the database in their raw condition as downloaded or obtained. The database includes all metadata that was associated with them. The database is currently hosted on a server at the Centre of Excellence for Coral Reef Studies at James Cook University as is backed up weekly.

Format:

Coastal_zone_GIS_database.xlsx This is an excel file containing name and full description of all datasets. Each row corresponds to a different GIS file (either shapefile or raster). When dataset can be downloaded from a website with or without an open access licence, the link is included. For others, the best contact point is included.

70 selected reefs throughout the Great Barrier Reef (GBR) are sampled in the AIMS Long-term Monitoring Project (LTMP). Underwater visual census is used to survey reef fishes on fixed transects (3 sites per reef, 5 x 50 m transects per site). The abundance and length of all diurnally active, non-cryptic fishes are recorded. A full list of species observed each year can be obtained on request. The overarching goal of LTMP fish surveys are to detect changes in reef fish communities over time at a regional scale, but also to examine the effectiveness of Marine Protected Areas. All fish species counted are largely non-cryptic, easily identified underwater and include both commercial and non-commercial taxa. Because surveys span the annual recruitment season, 0+ individuals are excluded from counts: these are distinguished from adults by their small size and often distinctive colouration. Abundance data for each fish species is subsequently summed over the five transects at each site on each reef to provide reasonable sample sizes for analysis and interpretation. Updated results of surveys can be found at: https://apps.aims.gov.au/reef-monitoring/reefs A subset of the data has been provided to the Ocean Biogeographic Information System (OBIS, http://www.iobis.org/explore/#/dataset/3936). Data have been used for the e-Atlas: http://eatlas.org.au/data/uuid/05bde62a-70ec-407b-b999-30cf369498af

This dataset summarises 35 years of seagrass data collection (1984-2018) within the Great Barrier Reef World Heritage Area into one GIS shapefile containing seagrass presence and absence survey data for 81,387 sites. This dataset is dominated by 1,010,826 'absent' compared to 47,049 'present' records. Managing seagrass resources in the GBRWHA requires adequate baseline information on where seagrass is (presence/absence), what species are present, and date of collection. This baseline is particularly important as a reference point against which to compare seagrass loss or change through time. The scale of the GBRWHA (1000s of kilometres) and the remoteness of many seagrass meadows from human populations present a challenge for research and management agencies reporting on the state of seagrass ecological indicators. Broad-scale and repeated surveys/studies of areas this large are logistically and financially impracticable. However seagrass data is being collected through various projects which, although designed for specific reasons, are amenable to collating a picture of the extent and state of the seagrass resource. The data used here along with additional references and descriptions of the data is at https://eatlas.org.au/data/uuid/18386963-6960-4eb9-889b-d0964069ce13

70 selected reefs throughout the Great Barrier Reef (GBR) are sampled in the AIMS Long-term Monitoring Project (LTMP). Underwater visual census is used to survey reef fishes on fixed transects (3 sites per reef, 5 x 50 m transects per site). The abundance and length of all diurnally active, non-cryptic fishes are recorded. A full list of species observed each year can be obtained on request.


The overarching goal of LTMP fish surveys are to detect changes in reef fish communities over time at a regional scale, but also to examine the effectiveness of Marine Protected Areas.


All fish species counted are largely non-cryptic, easily identified underwater and include both commercial and non-commercial taxa. Because surveys span the annual recruitment season, 0+ individuals are excluded from counts: these are distinguished from adults by their small size and often distinctive colouration.


Abundance data for each fish species is subsequently summed over the five transects at each site on each reef to provide reasonable sample sizes for analysis and interpretation.


Updated results of surveys can be found at:


https://apps.aims.gov.au/reef-monitoring/reefs


A subset of the data has been provided to the Ocean Biogeographic Information System (OBIS, http://www.iobis.org/explore/#/dataset/3936).


Data have been used for the e-Atlas:


http://eatlas.org.au/data/uuid/05bde62a-70ec-407b-b999-30cf369498af

This dataset contains coastal features within and adjacent to the Great Barrier Reef World Heritage area. This dataset consists of two shapefiles GBR_FEATURES.shp and GBR_DRY_REEF.shp. The GBR_FEATURES shapefile contains the following features: * Queensland mainland coastline, * Major and other coral reef structures (as defined by the reef shoal edge), * Islands and rocks (exposed and submerged), * Major coral cay features. The GBR_DRY_REEFS contains major coral reef structures (as defined by the reef shoal edge) that are tidal, drying or emergent reef areas.

The reef features extend north above the GBRWHA to just within the Torres Strait region.

The features have not been statistically tested with precision survey techniques. Positional accuracy varies considerably and dataset should NOT be used for navigation purposes, however, for general use the coverage can be regarded as having a nominal scale of 1:250,000. Inshore areas are significantly worse in positional accuracy than offshore areas.

This dataset corresponds to the zoning within the Great Barrier Reef Marine Park effective 1st July 2004. It is derived from the Great Barrier Reef Marine Park Zoning Plan 2003.

The Great Barrier Reef Marine Park is a multiple-use area. Zoning helps to manage and protect the values of the Marine Park that users enjoy. Zoning Plans define what activities occur in which locations both to protect the marine environment and to separate potentially conflicting activities. Revised zoning of the Great Barrier Reef Marine Park was introduced in July 2004 as part of the Great Barrier Reef Marine Park Authority's Representative Areas Programme.

Between 1999 and 2004, the Great Barrier Reef Marine Park Authority undertook a systematic planning and consultative program to develop new zoning for the Marine Park. The primary aim of the program was to better protect the range of biodiversity in the Great Barrier Reef, by increasing the extent of no-take areas (or highly protected areas, locally known as ‘Green Zones’), ensuring they included 'representative' examples of all different habitat types - hence the name, the Representative Areas Program or RAP. Whilst increasing the protection of biodiversity, a further aim was to maximise the benefits and minimise the negative impacts of the rezoning on the existing users of the Marine Park. Both these aims were achieved by a comprehensive program of scientific input, community involvement and innovation [1].

In each zones there are a range of activities that are allowed, disallowed or require a permit. The following outlines a summary of activities that are disallowed in each zone. Please refer to [2] for a more detailed and authoritative description of all restrictions within each zone:

• General Use Zone: General use, some activities require a permit.

• Habitat Protection Zone: No trawling, some activities require permits.

• Conservation Park Zone: No trawling, limited crabbing and line fishing.

• Buffer Zone: No aquaculture, bait netting, crabbing, harvesting fishing, collecting, spearfishing, line fishing, netting and trawling. Trolling for pelagic fish is allowed.

• Scientific Research Zone: Research areas primarily around scientific research facilities. Same as Buffer zone but with no trolling.

• Marine National Park Zone (Green): 'no-take' area. The following are allowed: boating, diving, photography and limited impact research. Some other activities are allowed with permits.

• Preservation Zone (Pink): 'no go' area. No activities are allowed except research activities with a permit.

Official maps derived from this dataset can be downloaded from the GBRMPA Zoning Maps [3] page.

This dataset can now be downloaded directly from GBRMPA's Geohub.

Note: This metadata record was created for the eAtlas and is not authoritative. Please contact GBRMPA for more information.

GBR_FEATURES.shp:

Polygon Vector Shape file (5376 features) GBR_ID: A number that is made up of a two-digit number representing the latitude band the feature is in (LAT_ID) and a three or four-digit number representing the sequential number of a particular feature complex (GROUP_ID), e.g. an island with an adjacent reef/cay/rock etc should have the same GROUP_ID (19-051) SORT_GBR_I: A whole number for sorting (19051) GBR_NAME: Great Barrier Reef MP Name (Five Trees Cay (No 1)) QLD_NAME: Queensland Government Previous Name (Five Trees Cay (No 1)) FEATURE_C: a three-digit number representing the type of feature, e,g mainland, island, cay etc (102) FEAT_NAME: Name of feature (Cay, Island, Mainland, Reef, Rock, Sand) SUB_NO: Multiple Feature Identification Number: a two-digit number that is linked to the SUB_ID of a feature. The SUB_ID is a letter that identifies multiple features of the same type in a group, e.g. multiple reefs surrounding an island are labelled a, b, c, d etc - these will be numbered 101, 102, 103, 104 etc. If the SUB_ID is "s", it refers to a single feature and will be given the number 100 (101) LABEL_ID: GBR_ID plus SUB_ID if not an S (S is a singular feature and does not need a sub-id label) (19-051a) X_COORD: Centroid Longitude (DD) in GDA94 decimal degrees (150.221849) Y_COORD: Centroid Latitude (DD) in GDA94 decimal degrees (-22.227123) CODE: GBR_ID plus SUB_NO plus FEATURE_CODE with hyphens (19-051-101-102) UNIQUE_ID: GBR_ID plus SUB_NO plus FEATURE_CODE with no hyphens. This is to be used as the unique ID for the oracle database (19051102101)

GBR_DRY_REEFS.shp:

This shows areas of the reef that dry or the tops of the reefs. Polygon Vector Shape file (2318 features)

Errata: The following errors were determined from an analysis of this dataset undertaken by Eric Lawrey in April 2025 by comparison with Sentinel 2 composite imagery (Hammerton and Lawrey, 2024). Features with duplicate CODEs: 10-458-104-103, 12-140-100-106, 18-014-100-102, 16-028-102-102, 14-003-100-104, 20-033-100-104, 20-041-101-102, 20-227-100-104, 99-000-100-100, 23-059-100-102 Most of these duplicates correspond to what should be a multi-part polygon being split into multiple single parts with the same attributes. This can lead to the a false count in the number of reefs.

This analysis found over 120 false positive reef features, 58 reefs that are actually sand banks, and 36 reefs that are actually rocky reefs rather than coral reefs. There is also at least 360 missing reefs from the mapping, predominantly in the southern GBR. It should be noted that this analysis was not comprehensive

Reference: Hammerton, M., & Lawrey, E. (2024). North Australia Sentinel 2 Satellite Composite Imagery - 15th percentile true colour (NESP MaC 3.17, AIMS) (2nd Ed.) [Data set]. eAtlas. https://doi.org/10.26274/HD2Z-KM55

This dataset describes the predicted distribution of seagrass communities across the Great Barrier Reef World Heritage Area and adjacent estuaries, based on six multivariate regressions tree models for estuary intertidal, estuary subtidal, coastal intertidal, coastal subtidal, reef intertidal, and reef subtidal. The models are presented as six raster datasets with 30m resolution.


Managing seagrass resources in the GBRWHA requires adequate information on the spatial extent of seagrass communities. The enormous size of the GBRWHA (1000s of kilometres) and the remoteness of many seagrass meadows from human populations means that models are a useful tool to predict where different seagrass communities are likely to be in areas where data is lacking.

James Cook University’s Centre for Tropical Water & Aquatic Ecosystem Research (TropWATER) has been collecting spatial data on GBR seagrass since the early 1980s. This project used TropWATER’s synthesis of seagrass site data (NESP Project 3.1 and 5.4: https://eatlas.org.au/data/uuid/5011393e-0db7-46ce-a8ee-f331fcf83a88) to predict seagrass communities.

In making this data publically available for management, the authors from the TropWATER Seagrass Group request being contacted and involved in decision making processes that incorporate this data, to ensure its limitations are fully understood.



Methods:
Seagrass data
The sampling methods used to study, describe and monitors seagrass meadows were developed by the TropWATER Seagrass Group and tailored to the location and habitat surveyed; descriptions and references are available in the metadata for the GBRWHA data composite (https://eatlas.org.au/data/uuid/5011393e-0db7-46ce-a8ee-f331fcf83a88).

Environmental data
Environmental predictors used in the models were: depth below mean sea level (Beaman 2017), relative tidal exposure (Bishop-Taylor et al. 2019), water type (Marine Water Bodies definitions version 2_4, Data courtesy of the Great Barrier Reef Marine Park Authority; Dyall et al. 2004), proportion mud in the sediment (coast and reef models, https://research.csiro.au/ereefs/models/model-outputs/access-to-raw-model-output/) (see also Baird et al. 2020; Margvelashvili et al. 2018), dominant sediment (estuary models only; https://eatlas.org.au/data/uuid/5011393e-0db7-46ce-a8ee-f331fcf83a88), benthic geomorphology (Heap and Harris 2008), benthic light https://dapds00.nci.org.au/thredds/catalog/fx3/gbr1_bgc_924/catalog.html (see also Baird et al. 2016; Baird et al. 2020), water temperature, mean current speed and salinity https://thredds.ereefs.aims.gov.au/thredds/catalog/ereefs/gbr1_2.0/all-one/catalog.html (Steven et al. 2019), wind speed (https://thredds.ereefs.aims.gov.au/thredds/catalog/ereefs/gbr1_2.0/all-one/catalog.html ) and Australian Bureau of Meteorology’s ACCESS data products (Bureau of Meteorology 2020; Soldatenko et al. 2018; Steven et al. 2019), and latitude. Different models had different combinations of predictors after removing collinear variables and excluding variables that did not extend into an area. For example, estuary models only include depth, relative tidal exposure, dominant sediment, and latitude.

Models
We modelled seagrass communities in six areas: Estuary Intertidal, Estuary Subtidal, Coastal Intertidal, Coastal Subtidal, Reef Intertidal and Reef Subtidal. For each area we used multivariate regression trees to examine changes in seagrass community type within the GBRWHA and adjacent estuaries, using a matrix of seagrass presence/absence site data for 12 seagrass species in the data set. Multivariate regression trees (MRTs) were implemented using the R package mvpart (De’ath 2004) (available in archive form on CRAN at https://cran.r-project.org) in R version 4.0.2 (R Core Team 2020). The map in Figure 1 was created using ArcGIS 10.8.
A detailed description of the modelled communities can be found in the final report for the NESP TWQ Project 5.4 (currently in review).

Spatial limits
Seagrass community types were modelled within potential seagrass habitat. Potential seagrass habitat was modelled by Carter et al. 2020 and is available on eAtlas here: https://eatlas.org.au/data/uuid/108ee868-4fb1-4e5f-ae57-5d65198384cc . The models do not extend north and south of the GBRWHA. The models extend across the continental shelf but exclude waters deeper than ~100m east of the shelf that were not surveyed for seagrass. Data were included when sites extended west of the GBRWHA boundary into coastal and estuarine water immediately adjacent.

Data sets
The site data used in this model is available here: https://eatlas.org.au/data/uuid/5011393e-0db7-46ce-a8ee-f331fcf83a88)

Further information can be found in the upcoming publications of the final report for the NESP TWQ Project 5.4.


Limitations of the data:
The site data used in these models extends back to the mid-1980s. Large parts of the coast have not been mapped for seagrass presence since that time. The seagrass community rasters are at 30m grid resolution, however some environmental variables such as those from eReefs (wind speed, current speed, benthic light, water temperature) are from spatial data at 1km grid resolution, and are likely to vary at much smaller spatial scales that we could not include in these models.


Format:
This dataset consists of six raster datasets with a geographic coordinate system of WGS84. The rasters have been saved as layer packages with symbology representing seagrass communities. These are:

Estuary intertidal communities: GBR_seagrass_communities_estuary_intertidal.lpk
Estuary subtidal communities: GBR_seagrass_communities_estuary_subtidal.lpk
Coastal intertidal communities: GBR_seagrass_communities_coastal_intertidal.lpk
Coastal subtidal communities: GBR_seagrass_communities_coastal_subtidal.lpk
Reef intertidal communities: GBR_seagrass_communities_reef_intertidal.lpk
Reef subtidal communities: GBR_seagrass_communities_reef_subtidal.lpk


References:
TBC


Data Location:

This dataset is filed in the eAtlas enduring data repository at: data\custodian\2019-2022-NESP-TWQ-5\5.4_Seagrass-Burdekin-region


Additional licensing information:
TropWATER gives no warranty in relation to the data (including accuracy, reliability, completeness, currency or suitability) and accepts no liability (including without limitation, liability in negligence) for any loss, damage or costs (including consequential damage) relating to any use of the data. TropWATER reserves the right to update, modify or correct the data at any time. The limitations of some older data included need to be understood and recognised. The TropWATER Seagrass Group would appreciate the opportunity to review documents providing research, management, legislative or compliance advice based on this data.

The gbr100 dataset is a high-resolution bathymetry and Digital Elevation Model (DEM) covering the Great Barrier Reef, Coral Sea and neighbouring Queensland coastline. This DEM has a grid pixel size of 0.001-arc degrees (~100m) with a horizontal datum of WGS84 and a vertical datum of Mean Sea Level (MSL).

For the latest version of this dataset download the data from http://deepreef.org/bathymetry/65-3dgbr-bathy.html

This dataset was developed as part of the 3DGBR project.

This grid utilises the latest available multibeam, singlebeam, lidar and satellite bathymetry source datasets provided by Federal and State Government agencies, in addition to significant new multibeam data collected during research expeditions in the area.

The large increase in source bathymetry data added much detail to improving the resolution of the current Australian Bathymetry and Topography Grid (Whiteway, 2009). The gbr100 grid provides new insights into the detailed geomorphic shape and spatial relationships between adjacent seabed features.

The accompanying report contains an explanation of the various source datasets used in the development of the new grid, and how the data were treated in order to convert to a similar file format with common horizontal (WGS84) and vertical (mean sea level) datums. Descriptive statistics are presented to show the relative proportion of source data used in the new grid. The report continues with a detailed explanation of the pre-processing and gridding process methodology used to develop the grid. A description is also provided for additional spatial analysis on the new grid in order to derive associated grids and layers. The results section provides a short overview of the improvement of the new grid over the current Australian Bathymetry and Topography Grid (Whiteway, 2009). The report then presents the results of the new grid, called gbr100, and the associated derived map outputs as a series of figures. A table of metadata for the current source data accompanies this report as Appendix 1. The report is available at: http://www.deepreef.org/publications/reports/67-3dgbr-final.html

Data details and format:

gbr100 bathymetry grid: Height/Depth in metres (MSL) Formats: 19000x18000 pixel grid (32 bit float) in ESRI raster grid file, GMT/netCDF grid file, Fledermaus sd file, 100m contour ESRI shapefile, GeoTiff grid file.

Total Vertical Uncertainty: Total Vertical Uncertainty (TVU) in the bathymetry estimated from uncertainty classification of each source dataset. Formats: 19000x18000 pixel grid (32 bit float) in ESRI raster, GeoTiff.

Hillshading: Hillshading for full gbr100 and also ocean areas only. Derived from the gbr100 grid. Format: 19000x18000 pixel grid (8 bit) in GeoTiff.

Funding history:

This dataset was initially developed as part of project 2.5i.1 from the MTSRF program (2010).

Subsequent versions of the dataset were developed from other funding sources.

Version history:

• July 2010 - Version 1

• Dec 2014 - Version 3 This version incorporates dozens of new bathymetric surveys including many new navy LADS surveys and some satellite derived bathy to fill in some gaps left by LADS.

• Jan 2016 - Version 4 This version incorporates estimates of bathymetry from satellite imagery in shallow clear waters.

Data Location:

This dataset is filed in the eAtlas enduring data repository at: data\ongoing\GBR_JCU_Beaman_3DGBR-bathymetry-gbr100

This dataset describes the predicted probability of seagrass presence across the Great Barrier Reef World Heritage Area and adjacent estuaries, based on six Random Forest models. The models have been mosaicked together into one raster dataset with 30m resolution.

Managing seagrass resources in the GBRWHA requires adequate information on the spatial extent of seagrass habitat. The enormous size of the GBRWHA (1000s of kilometres) and the remoteness of many seagrass meadows from human populations means that models are a useful tool to predict the probability of seagrass for areas where data is lacking.

James Cook University’s Centre for Tropical Water & Aquatic Ecosystem Research (TropWATER) has been collecting spatial data on GBR seagrass since the early 1980s. This project used TropWATER’s synthesis of seagrass site data (NESP Project 3.1 and 5.4: https://eatlas.org.au/data/uuid/5011393e-0db7-46ce-a8ee-f331fcf83a88) to predict potential seagrass habitat.

In making this data publically available for management, the authors from the TropWATER Seagrass Group request being contacted and involved in decision making processes that incorporate this data, to ensure its limitations are fully understood.

Methods:

Seagrass data The sampling methods used to study, describe and monitors seagrass meadows were developed by the TropWATER Seagrass Group and tailored to the location and habitat surveyed; descriptions and references are available in the metadata for the GBRWHA data composite ( https://eatlas.org.au/data/uuid/5011393e-0db7-46ce-a8ee-f331fcf83a88 ).

Environmental data Environmental predictors used in the models were: depth below mean sea level (Beaman 2017), relative tidal exposure (Bishop-Taylor et al. 2019), water type (Marine Water Bodies definitions version 2_4, Data courtesy of the Great Barrier Reef Marine Park Authority; Dyall et al. 2004), proportion mud in the sediment (coast and reef models, https://research.csiro.au/ereefs/models/model-outputs/access-to-raw-model-output/ ) (see also Baird et al. 2020; Margvelashvili et al. 2018), dominant sediment (estuary models only; https://eatlas.org.au/data/uuid/5011393e-0db7-46ce-a8ee-f331fcf83a88 ), benthic geomorphology (Heap and Harris 2008), benthic light https://dapds00.nci.org.au/thredds/catalog/fx3/gbr1_bgc_924/catalog.html (see also Baird et al. 2016; Baird et al. 2020), water temperature, mean current speed and salinity https://thredds.ereefs.aims.gov.au/thredds/catalog/ereefs/gbr1_2.0/all-one/catalog.html (Steven et al. 2019), wind speed ( https://thredds.ereefs.aims.gov.au/thredds/catalog/ereefs/gbr1_2.0/all-one/catalog.html ) and Australian Bureau of Meteorology’s ACCESS data products (Bureau of Meteorology 2020; Soldatenko et al. 2018; Steven et al. 2019), and latitude. Different models had different combinations of predictors after removing collinear variables and excluding variables that did not extend into an area. For example, estuary models only include depth, relative tidal exposure, dominant sediment, and latitude.

Models We modelled seagrass probability in six areas: Estuary Intertidal, Estuary Subtidal, Coast Intertidal, Coast Subtidal, Reef Intertidal and Reef Subtidal. For each area we used the machine learning technique random forest to broadly examine whether there were habitats within the GBRWHA and adjacent estuaries where seagrass was never likely to grow, using the binary classification within the site data of seagrass present (1) or absent (0) irrespective of species. Random Forest models were implemented using the randomForest package (Liaw and Wiener 2002) in R version 4.0.2 (R Core Team 2020). We used ArcGIS 10.8 to mosaic the six rasters and create a single seagrass probability raster for the GBRWHA.

Spatial limits Seagrass data north and south of the GBRWHA were not included in the analysis. The model extends across the continental shelf but excludes waters deeper than ~100m east of the shelf that were not surveyed for seagrass. Data were included when sites extended west of the GBRWHA boundary into coastal and estuarine water immediately adjacent.

Data sets The site data used in this model is available here: https://eatlas.org.au/data/uuid/5011393e-0db7-46ce-a8ee-f331fcf83a88

Further information can be found in the upcoming publications of the final report for the NESP TWQ Project 5.4.

Limitation of the data:

The site data used in these models extends back to the mid-1980s. Large parts of the coast have not been mapped for seagrass presence since that time. The seagrass probability raster is at 30m grid resolution, however some environmental variables such as those from eReefs (wind speed, current speed, benthic light, water temperature) are from spatial data at 1km grid resolution, and are likely to vary at much smaller spatial scales that we could not include in these models.

Format:

This dataset consists of a raster dataset with a geographic coordinate system of WGS84. The raster has been saved as a layer package with symbology representing seagrass probability in 0.2 increments with a range of 0-1 (GBRWHA_seagrass_probability.lpk)

References: TBC

Data Location:

This dataset is filed in the eAtlas enduring data repository at: data\custodian\2019-2022-NESP-TWQ-5\5.4_Seagrass-Burdekin-region

Additional licensing information: TropWATER gives no warranty in relation to the data (including accuracy, reliability, completeness, currency or suitability) and accepts no liability (including without limitation, liability in negligence) for any loss, damage or costs (including consequential damage) relating to any use of the data. TropWATER reserves the right to update, modify or correct the data at any time. The limitations of some older data included need to be understood and recognised. The TropWATER Seagrass Group would appreciate the opportunity to review documents providing research, management, legislative or compliance advice based on this data.

This dataset shows the spatial distribution of the number of visitors to the Great Barrier Reef Marine Park based on visitation rates collected from the Environmental Management Charge (EMC) managed by GBRMPA. The spatial information has been quantised into a 0.1 degree grid size.

This data only represents visitors to the Great Barrier Reef who used commercial tourist operations. Data is collected and updated quarterly following receipt of Environmental Management Charge returns from tourism operators. This dataset is a set of annual snapshots of this monthly data.

The count of visitor days to the Marine Park is calculated where passengers undertake a visit as follows:

Full day visits: A day trip of more than three hours is recorded as a full day visit. Overnight trips are recorded as multiple full days, for example, a stay of two-days and one night is counted as two full day visits.

Part day visits: Where the trip is less than three hours. The first day of a trip entering the Marine Park after 5 pm. The last day of a trip leaving the Marine Park before 6 am.

Exempt visits are passengers who are not required to pay the Environmental Management Charge (EMC), for example: young children who are free-of-charge, trade familiarisation passengers who are free-of-charge, passengers for whom another operator has already paid EMC on that day and the fourth and subsequent days for passengers on extended charters.

This metadata is not authoritative and was developed for documenting layers on the eAtlas. This dataset was supplied by the SELTMP team (http://seltmp.eatlas.org.au). Please contact the SELTMP of GBRMPA for further information.

Format:

This dataset consists of two shapefiles, one for the 2010-2011 financial year and one for the 2011-2012 financial year.

This project conducted a biodiversity assessment of coral communities on Torres Strait reefs to establish a baseline of coral condition and start a longer-term monitoring program of selected coral reefs in the region. The monitoring looked for changes in the condition of coral reefs and documented factors that might contribute to changes including COTS, disease, bleaching, temperature anomalies etc. As part of this project, an early warning system was established for coral bleaching. This will give the Torres Strait Regional Authority (TSRA), Torres Strait communities, industry and other stakeholders, the ability to predict, prepare for and respond to coral bleaching.

Key outputs of this project included:

-biodiversity survey completed for a baseline monitoring survey (Feb 2013) and a repeat monitoring survey (Feb-March 2014). These surveys resulted in a total of 246 coral species recorded during biodiversity surveys in 2013 and 2014. Lists of scleractinian coral species were made in February 2013 at Poruma Island Reef, Aureed Island Reef, Masig Island Reef, Erub Island Reef and Mer Island Reef

• deployment of a real time observing station at Thursday Island and Masig (Yorke) Island from 2012 onwards

• temperature logger deployments at 15 sites throughout the Torres Strait region

• regular reports of environmental conditions including SST, coral bleaching rish, Chlorophyll-a and ocean currents from 2011-2014

Reports and project outputs are available on the eAtlas webpages linked below, and metadata for temperature logger deployments.

The purpose of this study is to detect and quantify spatial and temporal changes in reef fish assemblages of the Great Barrier Reef (GBR). Between 1993 and 2005, reef fish assemblages of 46 reefs were monitored annually along permanent transects within a standard habitat using visual census. The selected intensive survey reefs are distributed across three positions of the continental shelf and among six sectors each representing one band of latitude. These reefs continue to be surveyed in odd years as part of the Long Term Monitoring Program (LTMP). The survey pattern changed in 2006 in response to the implementation of a new zoning plan for the GBR Marine Park in 2004. In order to assess the effects of re-zoning on the biodiversity of reefs, a different selection of reefs are surveyed in even years as part of the Representative Areas Program (RAP). Surveys are carried out for 28 pairs of reefs, with each pair comprising one reef which was re-zoned as a no-take area in 2004 and another nearby reef which remained open to fishing. The RAP survey reef pairs are distributed among four of the same sectors in the original LTMP survey design and two different sectors. The cross-shelf distribution of reefs differs, though, as inshore reefs were not included in the RAP sampling design.

Fishes of 214 species are counted along the permanently marked transects. Larger mobile fishes (141 spp.) are counted in a 5m wide belt and damselfishes (73 spp.) are counted in a 1m wide belt. Total lengths of any coral trout species (Serranidae, Plectropomus spp.) recorded within transect belts have been estimated from 1996 onwards. Length estimates of other species within the Serranidae, Lethrinidae and Lutjanidae families have been recorded in RAP surveys since 2006.

To demonstrate spatial variation in fish community assemblages of the GBR, spatial distributions of a number of relevant variables were mapped in Google Earth using the long term average. Monitoring data collected up until and including the 2008 field season are included. Spatial variation in species richness and in total fish abundance are displayed. Fish species have also been divided into trophic groups and the spatial variation in abundance of each group is mapped accordingly.

As part of the Reef Atlas project (now the eAtlas) the fish observations were interpolated over the whole GBR by Glenn De'ath using Generalized Additive Models with a Quasipoisson fit. This produced a gridded version of the dataset and is available as a KML.

Data units:

Richness: number of species per transect Density: Number of fishes per transect

Resource Constraints:

Copyright remains with the data owner(s)

References:

• Cheal A, Wilson S, Emslie M, Dolman A, Sweatman H (2008) Responses of reef fish communities to coral declines on the Great Barrier Reef Marine Ecology - Progress Series 372:211-223
• Emslie M, Cheal A, Sweatman H, Delean S (2008) Recovery from disturbance of coral and reef fish communities on the Great Barrier Reef, Australia. Marine Ecology - Progress Series 371:177-190
• Sweatman H, Cheal A, Coleman N, Emslie M, Johns K, Jonker M, Miller I, Osborne K (2008) Long-term monitoring of the Great Barrier Reef. Australian Institute of Marine Science, Townsville 379

Each collection station is denoted by date, latitude and longitude. The data were sampled at several depths at each site: the number of samples was primarily, but not always, dependent on bottom-depth. A unique identifier has been assigned to each replicate.

Variables: depth, dissolved inorganic phosphate (DIP), silicate, ammonium, nitrite, nitrate, dissolved inorganic nitrogen (DIN), dissolved organic carbon (DOC), temperature, salinity, particulate nitrogen (PN), particulate phosphorus …Show full descriptionEach collection station is denoted by date, latitude and longitude. The data were sampled at several depths at each site: the number of samples was primarily, but not always, dependent on bottom-depth. A unique identifier has been assigned to each replicate.

Variables: depth, dissolved inorganic phosphate (DIP), silicate, ammonium, nitrite, nitrate, dissolved inorganic nitrogen (DIN), dissolved organic carbon (DOC), temperature, salinity, particulate nitrogen (PN), particulate phosphorus (PP), particulate organic carbon (POC), zooplankton, total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), Chlorophyll a, phaeophytin, Secchi disk. Weather information is recorded on swell and wind.

Information about the methods used are in the Data Quality section of this metadata record. To collect information about water quality on the Great Barrier Reef. To assist in better defining the range of conditions within which reefs normally exist and the extreme conditions likely to cause significant changes in biological reef communities. Chlorophyll a, PP, PN and Secchi data have been used for the e-Atlas: http://e-atlas.org.au

Data plot checks by year revealed seemingly abnormally high values of nitrogen-based parameters 1976-1987 with typical values >10 times those of later years. Since many other variables had no data for this period, the data for all parameters was restricted to the period 1988 to current.

Methods are summarised in the data quality section of this metadata record.