This study was conducted in order to provide preliminary information on carbon cycling on the North West Shelf, extending from Exmouth shelf to Exmouth Plateau. The research aimed to understand the spatial scale of petroleum biomarkers in the water column, and to estimate the speed of synthesis and degradation of organic matter and hydrocarbons in the water column and surface sediments Six replicated sediment traps arrays were attached to wire moorings, fitted with S4 current meters below each trap. The arrays were deployed at stations throughout the region. Surface sediment samples were collected with a Smith-McIntyre grab sampler and core samples were collected using a Kasten Corer. Using molecular lipid biomarkers to indicate the sources of biogenic organic carbon and petroleum, sediment traps were used to collect fluxes of lipids from settling particles. This composition was compared with water volume samples and surface sediments.

This record describes the AIMS component of the eReefs phase 4 research program that ran from 2018 - 2020. The primary focus of eReefs phase 4 was to transition from research focused projects to operational services. The eReefs work was extended in the eReefs 2020-2024 project. eReefs is a collaboration between the Great Barrier Reef Foundation, CSIRO, the Australian Institute of Marine Science, Bureau of Meteorology, and Queensland Government. It aims to develop a platform that provides a picture of current and historical environmental conditions on the Great Barrier Reef. eReefs has many components developed and maintained by each of the organisations in the collaboration, including catchment modelling (Queensland Government), remote sensing (BOM and CSIRO), hydrodynamic modelling (BOM and CSIRO) and biogeochemical modelling (CSIRO). AIMS's contribution was providing data agregation and visualisation services and well as analysis of the biogeochemical model for inclusion in the Reef Plan report card. A major goal of the AIMS eReefs phase 4 project was to re-engineer the AIMS eReefs platform to use distributed cloud service components to make a platform that can scale its computing resources based on demand, to allow more visualisation and aggregation products to be supported in the future. The eReefs model data is very large (>15 TB) resulting high computation and storage costs associated with its processing. The new re-engineered architecture improve the computational cost efficiency by ~10x and the storage cost efficiency by 1.5x allowing a more complete set of visualisation and aggregation products to be made available. Key goals of this project were: Generating updated water quality scores based on eReefs BGC data for the Reef Plan report card based on methods developed in NESP TWQ 3.2.5. Re-engineering the AIMS eReefs platform for improved scaling. Developing a data extraction tool to allow easy access to time series data from eReefs data. The data for AIMS eReefs platform is stored on the Amazon cloud in S3 storage, managed by the AIMS Knowledge Systems team. All the data is derived from the original eReefs model data. The software was deployed on the Amazon Cloud, using AWS Batch to dynamically adjust the number of executing servers performing aggregation and animation tasks based on load. Coordination tasks are performed using AWS Lambda functions, which communicate using SNS messaging. The system coordinates the activities of all the executing tasks using a central MongoDB database. The setup of the AWS infrastructure is deployed using CloudFormation, which is a language for describing cloud computing infrastructure as code. The configuration of all the generated products (aggregation and animation) along with the infrastructure code is stored in the ereefs-definitions Git code repository. This repository has restricted access for security reasons. All other code will be made publicly available under an open source license by June 2021 as part of the eReefs 2020-2024 project. All the software for the platform is contained in 37 Git code repositories stored on GitHub. These repositories are linked to from https://github.com/open-AIMS/ereefs-documentation. This platform produces aggregation and animations of the CSIRO Hydrodynamic (GBR4 and GBR1) and BioGeoChemical eReefs models. The platform downloads model data from the National Computing Infrastructure (NCI) THREDDS data service. This data is then preprocessed to remove unused variables and half the depths, retaining only depth data from < 145m. This subsetting reduces the total storage needed by the system. This subsetted mirror is then produced to produce a range of temporal aggregations (daily, monthly, annual) and exposure products. The derived products are regridded from the original curvilinear grid used in the modelling to a regular rectangular grid. This regridding is performed to allow the data to be compatible with GIS software such as ArcMap and QGIS. All model data and derived model data is stored in NetCDF file format.

This dataset aggregates and summarises the water quality data collected by researchers from the Australian Institute of Marine Science from 1974 until the present. AIMS' biological oceanographers have studied the physical, chemical, and biological properties of seawater around northern Australia using a variety of methods including in situ sampling, moored sensors, and vertical profiles. This dataset contains in situ water quality information (list of analytes shown below) from northern Australia, with a large volume of data from the Great Barrier Reef, Queensland. It also contains an historical dataset transcribed from the reports of the Low Islands Expedition 1928-29 led by C.M. Yonge. This dataset contains biogeochemical data from many research expeditions (the majority led by Dr. Miles Furnas) as well as records from water quality monitoring programmes. Some data in this record were collected as part of the Great Barrier Reef Marine Monitoring Program for Inshore Water Quality (MMP WQ), which has collected in situ water quality data, along with time-series of temperature, salinity, fluorescence, and turbidity since 2005. More information about the MMP WQ can be found on its metadata record (see link below in Related Information). Each water sample occurs at a unique combination of geographic location, time, and date. In the AIMS database, samples are assigned a unique alphanumeric identifier (called a ‘station’), which is comprised of a 3-letter area code and a 3-digit station number (e.g. WQM324). Using this code, water chemistry information can be linked to other associated data, such as vertical profiles of the water column (i.e., CTD casts), which can be retrieved from AIMS’ CTD database (link below). Variables in this database include: depth, silicate (Si), ammonium (NH4), nitrite (NO2), nitrate (NO3), dissolved inorganic phosphorus (DIP), dissolved organic carbon (DOC), temperature (Temp), salinity (Sal), particulate nitrogen (PN), particulate phosphorus (PP), particulate organic carbon (POC), total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), Chlorophyll-a (Chl), phaeophytin (Phaeo), suspended solids (SS), Secchi depth, and coloured dissolved organic matter (CDOM). All analytes may not be available at every station. Brief description of collection, storage and analysis method for parameters: SAL: 250 mL unfiltered sample, stored refrigerated at 4ºC in screw-top plastic bottle, analysed on Guildline Portasal Salinometer (temperature-compensated and calibrated using OSIL standard seawater as reference) TEMP: Electronic reversing thermometer attached to Niskin SECCHI_DEPTH: The average of the vertical disappearance and reappearance depths of a Secchi disc SS: Filtered onto pre-weighed 47 mm 0.4 µm polycarbonate membrane filter, rinsed with deionised water, dried at 60ºC for 12 hours, gravimetric analysis CDOM: 50 mL filtered sample (0.2 µm acrodisc), CDOM absorption coefficient at 443 nm calculated from absorbance measured by UV-visible absorption spectroscopy NH4, NO3, NO2, and DIP: 10 mL filtered sample (0.45 µm minisart), stored frozen at -25°C, filtrate analysed on segmented flow analyser NH4_INSITU: Unfiltered 20 mL sample, processed immediately, OPA fluorescence method (post 2005) SI: 10 mL filtered sample (0.45 µm minisart), stored refrigerated at 4ºC, filtrate analysed on segmented flow analyser (reported as Si) PN_SHIM and POC: 500 mL filtered onto 25 mm GF/F, stored frozen at -25ºC, analysed by high temperature combustion (Shimadzu TOC-L) PP: 250 mL filtered onto 25 mm GF/F (0.7 µm), stored frozen at -25ºC, persulphate digestion of filter, colorific (molybdate blue) analysis on UV-Vis spectrophotometer TDN_PER and TDP_PER: 10 mL filtered sample (0.45 µm minisart), stored frozen at -25ºC, persulphate oxidation/digestion with mixture of NaOH, boric acid and K2S2O8 in autoclave, analysed on segmented flow analyser DOC: 10 mL filtered sample (0.45 µm minisart), acidified with 100 µL HCl, stored refrigerated at 4ºC, analysed by high temperature combustion (Shimadzu TOC-L) CHL and PHAEO: 100 mL filtered onto 25 mm GF/F (0.7 µm), stored frozen at -25ºC, extraction into 10 mL of acetone, read on Turner Fluorometer using acidification method Data can be downloaded from AIMS' main water quality database (see link below in Data Downloads). Data are presented as depth-weighted means calculated using surface, bottom, and any intermediate samples.