AndreaBozzo/ceres-open-data-index huggingface dataset:
Final report of the joint investigation into SSD modelling and ssdtools implementation for the derivation of toxicant guidelines values in Australia and New Zealand

This report summarises the results of the final set of investigations, additional studies, and software fixes  prior  to  the  release  of  ssdtools  2.0  and  companion  on-line  implementation, shinyssdtools. It is intended that the release of ssdtools 2.0 will coincide with its adoption by Australian,  New  Zealand,  and  Canadian  jurisdictions  as  the  recommended  software  tool  for establishing default guideline values (DGVs) for concentrations of contaminants in natural aquatic systems.  This  signifies  the  achievement  the  collaborative  project&rsquo;s  over-riding  objective  of harmonising  the  statistical  and  computational  basis  of  guideline  value  derivation  across  all  three jurisdictions. In the context of SSD modelling, we believe this is the first time such collaboration and coordination among non-EU countries has occurred.

Organization: Australian Ocean Data Network
Wave energy and other environmental drivers as predictors of seeded-coral performance on the Great Barrier Reef

This dataset explores how wave energy affects the survival and growth of coral recruits on seeded devices. Data were collected to understand how environmental factors influence post-settlement coral survival, aiming to improve seeding device deployment strategies.

Broodstock colonies of three Acropora species (A. hyacinthus, A. millepora, and A. tenuis) were collected and spawned at the Australian Institute of Marine Science. The resulting larvae were reared, settled onto devices, and deployed between January and February 2022 across wave energy gradients at Moore, Davies, and Heron Reefs on the Great Barrier Reef. Devices were placed at 10 sites per reef (n = 25 devices per site), spanning five wave-energy levels, and censused over 1.5 to 2 years. Environmental data included wave energy estimates, bottom stress, flow velocity, sedimentation, and benthic community composition. Analyses used Bayesian models to assess survival and size in relation to environmental predictors. The dataset supports research on fine-scale spatial variability in coral restoration outcomes.

Organization: Australian Ocean Data Network
Distinct coral reef habitat communities characterized by environmental DNA metabarcoding

eDNA metabarcoding were applied using the rRNA 18S Universal eukaryote assay to explore differences in community profiles between samples collected from the lagoon and reef slope habitats across the Ningaloo Coast World Heritage Area in Western Australia

In May 2019, near-surface (1&ndash;2 m depth) 120 seawater samples were collected at 14 different localities along Ningaloo Reef, from the backreef lagoon and the exposed reef slope.

For shallow lagoon samples, five replicate 1 L samples were collected at five different sites across the reef using Nalgene bottles by snorkellers (site depth&thinsp;&lt;&thinsp;6 m). At each site, three different locations were used for the replicates, within a 5 m radius of each other (n&thinsp;=&thinsp;75 samples total, 15 samples per lagoon site).

On the reef slope, samples were collected using a livewire CTD Niskin rosette system, with five replicates repeated at nine sites approximately&thinsp;~&thinsp;20 km apart along the western edge of the outer reef at a site depth range of 11 to 22 m (n&thinsp;=&thinsp;45 samples total).

All samples were filtered, and DNA extraction occurred. 2061 amplicon sequence variants were recovered that comprised of 401 taxa spanning 14 different metazoan phyla such as cnidarians, poriferans, molluscs, algae, worms, and echinoderms. For full details, see Dugal et al., (2022)

Organization: Australian Ocean Data Network
Integrated Monitoring and Reporting Deep-Water Inter-Reef

The Reef Authority&#39;s 2050 plan and QLD fisheries identified a critical need for information on key fish species and communities in under-surveyed areas of the Great Barrier Reef Marine Park. Funding through the reef trust partnership was distributed by the Great Barrier Reef Foundation to AIMS to lead a 3-tiered, highly collaborative Integrated Monitoring and Reporting Program (IMR) with the goal of providing better data that can be used for stakeholders. One of these tiers focused on obtaining data on the deep-water inter-reef habitats of the GBR. Legacy data from AIMS, fisheries data and known habitat models of the GBR were used to select candidate sites for monitoring fish along all 3 major latitudinal regions of the GBR. These sites were surveyed using multibeam sonar to identify features, resulting in 36 target sites to develop baselines for future monitoring to be repeated over two years. Using the multibeam data, a spatially balanced sampling design was then developed to survey the selected areas using Baited Remote Underwater Video. 1545 stereo-BRUV drops were completed within the 36 sites over a two-year period. Multibeam derivatives, environmental covariates, and benthic habitat classification has been extracted and linked to the site metadata. Data will be analysed for key fish species (commercial, recreational, conservation and cultural importance) and fish community relative abundance, taking a focused look at how zoning and remoteness influences populations and size of individuals.

Organization: Australian Ocean Data Network
Adaptive monitoring of coral health at Scott Reef where data exhibit nonlinear and disturbed trends over time

Time series data are often observed in ecological monitoring. Frequently such data exhibit nonlinear trends over time potentially due to complex relationships between observed and auxiliary variables, and there may also be sudden declines over time due to major disturbances. This poses substantial challenges for modelling such data and also for model-based adaptive monitoring. We propose novel methods for finding adaptive designs for monitoring when historical data show such nonlinear patterns and sudden declines over time. This work is motivated by a coral reef monitoring program that has been established at Scott Reef; a coral reef off the Western coast of Australia. Data collected for monitoring the health of Scott Reef are considered, and semiparametric and interrupted time series modelling approaches are adopted to describe how these data vary over time. New methods are then proposed that enable adaptive monitoring designs to be found based on such modelling approaches. These methods are then applied to find future monitoring designs at Scott Reef and form a set of recommendations for future monitoring.

Through applying the proposed methods, it was found that future in formation gain is expected to be similar across a variety of different sites, suggesting that no particular location needed to be prioritised at Scott Reef for the next monitoring phase. In addition, it was found that omitting some sampling sites/reef locations was possible without substantial loss in expected information gain, depending upon the disturbances that were observed. The resulting adaptive designs are used to provide recommendations for future monitoring in this region, and for reefs where changes to the current monitoring practices are being sought. Furthermore, as the methods used and developed throughout this study are generic in nature, this research has the potential to improve ecological monitoring more broadly where complex 28 data are being collected over time.

Organization: Australian Ocean Data Network
Ningaloo in situ water temperatures 2010 - 2025, Western Australia

These in situ sea temperature data are based on submersible loggers stationed at various scales for several research projects spanning the period 2010 to 2025.

In the early years these data were focused on stations in the eastern, northern and southern sections of Ningaloo Marine Park for research projects on coral bleaching during the 2010/11 marine heatwave (e.g. Moore et al. 2012; Depczynski et al. 2013), seasonal canopy dynamics in tropical Sargassum forests (Fulton et al. 2014), and Marine Heatwave workshops led by DPIRD WA in 2011 and 2013.

More recently two main stations in the Ningaloo lagoon near Tantabiddi and Coral Bay that have been collecting hourly sea temperatures over 2013 to 2025 were used to explore the thermal characteristics of the 2024/25 marine heatwave in terms of Degree Heat Weeks for coral heat stress (Fulton et al.).

Organization: Australian Ocean Data Network
Cross-generational effects of climate change on a photosynthetic sponge

Unlike calcifying invertebrates, a number of sponges have demonstrated tolerance to climate scenarios predicted for the future; however, the mechanisms that enable them to cope with ocean warming and ocean acidification are limited. In this project, we examined whether microbiome-mediated cross-generational acclimatization could enable a photosynthetic sponge to survive under predicted climate scenarios. This associated dataset provides information on the mortality and bleaching observed in juvenile sponge recruits that were transplanted to climate scenarios predicted for 2050 and 2100. A visual bleaching assessment was conducted at the end of the 5-week experiment, with mortality captured throughout. Data was entered in excel and visualized using graphs in R.

Organization: Australian Ocean Data Network
Reef Flat surveys using the ReefScan survey system for the ecoRRAP project

Data from the ReefScan image survey system for reef flats along the Great Barrier Reef for the ecoRRAP project. 

The ReefScan survey system consists of a series of GoPro cameras mounted on an underwater boom either side of a small Tender which then undertakes surveys of reef flat areas of reefs. The surveys are typically 0.5Ha in area (100m x 50m) located over the top of the shallow ecoRRAP sites with the intent to include all of the area of the ecoRAPP DSRL camera surveys and to include the reef edge and reef flat.

The images are geo-located and so can be stitched using the Metashape software (www.agisoft.com) into Ortho-mosaics, the data is also processed into 2.5D DEM&#39;s and object clouds which can be used to get structural information. As the data is colelcted at the surface it has some depth information and so best represents 2.5D over true 3D.

The images can also be analysed using Machine Learning to give percent cover of the major benthic forms. One compoent of the work is to develop and validate a set of classificaiton labels suitable for the data collected.

Surveys were done over 2021 and 2022 as part of the Technology Development work with the techniques evolving as the work progressed. The first survey was incomplete and some of the ecoRAPP trips were not surveyed using this system.

The following trips have been completed:

<code>Orpheus / Pelorus Island and Davies Reef  I [Jan 2021] (partial survey)

Torres Strait (Dunganess / Masig / Aukane) [Feb 2021]

Moore Reef / Lizard Island [Oct 2021]

Orpheus / Pelorus Island / Davies Reef / Chicken Reef / Little Boardhurst Reef II [Jan 2022]

Davies post-bleaching and Southern Reefs (Heron, Lady Muscgrave) [March 2022]
</code>

The core data are sets of geo-located GoPro images of shallow reef areas with a high degree of overlap. The data products derived from these include:

<code>Orth-mosaic images either a GeoTIFFs or as GeoServer layers

Digital Elevation Models (DEM&amp;#39;s) showing elevation / bathymetry as GeoTIFFs

Point Clouds or 3D/2.5D models (as obj files)

Percent cover estimates from the images via Machine Learning models
</code>

Each survey will have a child metadata record to this parent record.

Organization: Australian Ocean Data Network
Cape Cleveland  Automated Marine Weather And Oceanographic Station

This dataset contains meteorological data from a land-based weather station, which was located on Cape Cleveland, near Townsville, from June 1993 to September 1996.
 These data are collected to support scientific research at AIMS. Data are made available on request to other researchers and to the public.
 The weather station was a Steedman EMS System.Data recorded: Barometric Pressure, Air Temperature, Wind Direction True (vector averaged), Wind Speed True (10 min average prior to every half hour).

Organization: Australian Ocean Data Network
Davies Reef Base Station

The Davies Reef Base Station performs two functions. The first is to act as a collection point for the sensor network platforms deployed within the reef and to in turn send the data back to the AIMS Data Centre. The second is as a platform for sensors with current sensors including two underwater PAR sensors and a still camera.

The base station is co-located with the AIMS Automatic Weather Station on the Davies Reef Tower in order to optimise the use of power and communications infrastructure.

The base station provides the link between the on-water platforms and the mainland systems, it polls each of the sensor floats and collects the data and then forwards this over a Telstra nextG link to the mainland and the AIMS Data Centre.

The base station also hosts its own sensors, currently these include underwater PAR and a still camera.

Wireless Sensor Networks Facility (formerly known as Facility for The Automated Intelligent Monitoring of Marine Systems (FAIMMS)), part of the Great Barrier Reef Ocean Observing System project (GBROOS) (IMOS)

Organization: Australian Ocean Data Network
Carnarvon Shelf Survey, Western Australia (CERF Marine Biodiversity Hub Survey)

The survey was a collaboration between the Australian Institute of Marine Science (AIMS) and Geoscience Australia (GA) aboard RV Solander, as part of the CERF Marine Biodiversity Hub&#39;s Surrogates Program.

The purpose of the survey was to collect high-quality, accurately co-located data test a range of physical parameters for relationships to the biodiversity and seabed patterns across the offshore Carnarvon shelf, adjacent to Ningaloo. Estimates of relative importance of latitude, distance offshore, water depth, physical setting, exposure and local habitat complexity were explored in relation to biodiversity patterns in the region. The region is highly variable in its geomorphology, where shelf width ranges from less than 6km (northern region at Mandu) to more than 30kms (southern region at Gnaraloo).

The surveys collected physical data:

<code>        - wave and current measurements


        - multibeam sonar bathymetry and backscatter


        - sediment grab samples


        - acoustic sediment profiles
</code>

And biological data:

<code>        - towed underwater video and stills photography


        - bottom sediment samples


        - near-bottom plankton samples
</code>

Data sources and results were compared to determine the influence of physical and biological seabed features. The study used existing AIMS underwater video survey data and seabed samples. 

Please note: as other parties were involved in the collection of the data, that additional permission may be required for its use and/or distribution.

Organization: Australian Ocean Data Network
IMOS - Ships of Opportunity - Air-Sea Flux : Meteorological and SST Observations collected on the Research Vessel Southern Surveyor

This dataset contains environmental observations as well as ship parameters (such as speed and direction).

As part of the Ships of Opportunity - Research Vessels Real-Time Air-Sea Flux (ASF) Sub-Facility, R.V. Southern Surveyor collects underway meteorological and oceanographic observations during scientific  voyages in the oceans adjacent to Australia. 

Data streams are fed into the existing ship data management system, and broadcast via satellite back to Australia 3-hourly. The observations are quality controlled at the Bureau of Meteorology and air-sea fluxes calculated using the COARE Bulk Flux algorithm. 

A daily file of 1-minute averages of the observations are generated shortly after 0000UTC and provided to eMII.

The data is contained in NetCDF format files and consists of environmental observations as well as ship parameters (such as speed and direction). Wind is observed with two different sensors, and the relative (observed) and true (relative to fixed earth) wind speed and direction provided. Air temperature and humidity is observed on the port and starboard of the main mast. Short-wave (sunlight) and long-wave (infra-red radiation or heat, from sky and clouds) is observed on the port and starboard side of the monkey island (above the bridge). Precipitation is observed with an optical rain-gauge and traditional siphon gauge from the foremast.  Instrument meta-data and QC flags are also contained in the files.

Tags: Atmosphere | Atmospheric Pressure | Atmospheric Pressure, Atmosphere | Atmospheric Temperature | Surface Air Temperature, Atmosphere | Atmospheric Water Vapor | Humidity, Atmosphere | Precipitation | Precipitation Rate, Atmosphere | Radiation Budget | Longwave Radiation, Atmosphere | Radiation Budget | Shortwave Radiation, Countries | Australia, Countries | Fiji, Countries | New Caledonia, Countries | New Zealand, Global / Oceans | Indian Ocean, Global / Oceans | Pacific Ocean, Global / Oceans | Southern Ocean, Oceans | Ocean Optics | Photosynthetically Active Radiation, Oceans | Ocean Temperature | Sea Surface Temperature, Oceans | Ocean Winds | Surface Winds, Regional Seas | Coral Sea, Regional Seas | Tasman Sea, air_pressure, air_temperature, rainfall_rate, relative_humidity, sea_water_temperature, surface_downwelling_longwave_flux_in_air, surface_downwelling_photosynthetic_radiative_flux_in_air, surface_downwelling_shortwave_flux_in_air, thickness_of_rainfall_amount, wind_from_direction, wind_speed
Organization: Australian Ocean Data Network
The No-Significant-Effect Concentration

An alternative toxicity estimate to the no-effect concentration (NEC) has been developed - the no-significant-effect concentration (NSEC). The no-effect concentration (NEC) is the preferred threshold metric for single-species toxicity tests applied to derive safe concentration thresholds for contaminants in the environment for use in species sensitivity distributions, but is only suitable when concentration&ndash;response (C-R) data exhibit a threshold response.

The no-significant-effect concentration (NSEC) is better suited to C-R data for which the response is a monotonically decreasing function of concentration and no threshold effects are evident. A flexible, three-parameter sigmoidal function is used to describe the C-R relationship and detail both Bayesian and frequentist approaches to estimation and inference for the NSEC.

Organization: Australian Ocean Data Network
Impacts of individual aromatics on larvae of the coral Acropora millepora

This collection consists of a series of data sets assessing the sensitivity of planula larvae of the coral Acropora millepora to dissolved, individual aromatic compounds under two light conditions: visible light in the absence of ultraviolet radiation and visible light in the presence of ultraviolet radiation. Data was collected on the sensitivity of larval survival, larval fragmentation and larval metamorphosis success through laboratory experiments performed at the Australian Institute of Marine Science Townsville site during the mass coral spawning events in November and December of 2016-2019. The data was analysed using Bayesian dose-response modelling using the package bayesnec in the software R.

Parameters in this study: Larval survival, Larval fragmentation, Larval metamorphosis success

For full methodological and analytical details please refer to the full research report: Nordborg et al. 2023, Effects of aromatic hydrocarbons and evaluation of oil toxicity modelling for larvae of a tropical coral (Marine Pollution Bulletin, Vol. 196, 115610, https://doi.org/10.1016/j.marpolbul.2023.115610) and its supplementary materials.

Organization: Australian Ocean Data Network
NSW Office of Environment and Heritage (OEH) Multi-beam Bathymetry Surveys

Data products from multi-beam bathymetry surveys carried out by the New South Wales Office of Environment and Heritage (OEH). Surveys were conducted in and around NSW Coastal and State Waters, using a mounted GeoAcoustics Geoswath 125KHZ Interferometric sidescan sonar system, by the HABMAP program. The HABMAP program, which was initiated to provide fine scale benthic habitat information for NSW State Waters, initiated surveys to provide a minimum of 5 x 5m bin scale bathymetric and backscatter layers for use in GIS applications. Products include fine-scale bathymetric and relative acoustic backscatter data in several formats. For each survey there is also a "scientific rigour" document describing the origin and processing of the data, and files showing the geographic coverage of the survey (ESRI shapefile and Google KMZ formats).

Tags: Countries | Australia, Field Surveys | Underwater Surveys, Global / Oceans | Pacific Ocean, Oceans | Bathymetry | Seafloor Topography, Oceans | Bathymetry | Water Depth, Oceans | Coastal Processes | Coral Reefs, Oceans | Marine Biology | Marine Habitat, Oceans | Ocean Acoustics | Acoustic Scattering, Physical Oceanography, Regional Seas | Tasman Sea, States, Territories (Australia) | New South Wales
Organization: Australian Ocean Data Network
EDNA data for Crown of Thorns Seastar (Acanthaster cf. solaris) - CCIP-D-03

AIMS developed an eDNA based methods to detect and quantify CoTS. The data included here include field data from initial method development as part of AIMS appropriation, and later testing through several CoTS Control Innovation Program (CCIP) projects. Data consist of filtered water samples, in most cases collected with 12 replicates at three sites per reef. 

Data Dictionary:

Field name: Explanation/units

Date: Julian Date

Year: Collection Year

Reef: GBR Reef Name

Site_name: Site name

Site_No: Site number

Lat: Latitude in decimal degrees

Long: Longitude in decimal degrees

Project: Project Code

Reef_rep: replicate number on a reef basis

Site_rep: replicate number on a site

PCR1_binary: First technical PCR replicate: positive or negative (1 or 0)

PCR2_binary: First technical PCR replicate: positive or negative (1 or 0)

LOD_sample_positive: Limit of Detection based: 1 if either of the technical replicates are positive

PCR1_conc: CoTS eDNA copy number per L water filtered, first technical replicate

PCR2_conc: CoTS eDNA copy number per L water filtered, second technical replicate

Conc_mean: CoTS eDNA copy number per L water filtered, averaged over both replicates

Organization: Australian Ocean Data Network
DNA-Based Detection and Patterns of Larval Settlement of the Corallivorous Crown-of-Thorns Sea Star (Acanthaster sp.)

219 larval settlement collectors were deployed on the Great Barrier Reef during 4 sampling periods between October 2016 and February 2020.

Deployments were approx. 2.5 months in duration, coinciding with the COTS summer reproduction and spawning season

All larval settlement collectors were deployed at three sampling locations in northern (near Lizard Island and Cairns) and central GBR (near Townsville), at three different depths (4-6m, 7-9m and 10-12m) and at three sites per reef.

Larval settlement collectors were constructed using 2 leaf baskets ¿lled with about 60&ndash;70 aquarium ¿lter Ovi-Flow bio balls. During deployment, each collector was secured to the substrate and allowed to float approx. 1m above the substrate.

All larval settlement collectors were deployed at sites with relatively steep reef slopes, de-¿ned by a high cover of coral rubble encrusted with coralline algae, which is where COTS juveniles are typically observed.

Following retrieval, each apparatus was processed to remove all sample material (see Doll et al. (2021) for more details). DNA extraction allowed for genetic analysis to explore spatial and temporal settlement patterns.

Organization: Australian Ocean Data Network