This resource is relates to recreational use patterns from surveys with recreational boaters at 12 locations around Australia across 2019-2020. The collected recreational use patterns are intended to be indicative of use levels for various marine areas. Use patterns were recorded during face-to-face surveys at boat ramps using gridded maps upon which boaters indicated areas they had visited in the last 12 months along with approximate percentages, indicating the relative time spent at each location. Data is supplied modelled frequency of recreational boating trips (per grid cell per year), based on aggregated boat ramp survey data. Data Source: https://metadata.imas.utas.edu.au/geonetwork/srv/eng/catalog.search#/metadata/9f40ac0c-e0b1-436b-abc7-b19bc7159d86 Report: https://www.nespmarine.edu.au/document/social-and-economic-benchmarks-australian-marine-parks Site as: Navarro, M, Langlois, TJ, Burton, M, Hegarty, A, Aston, C, Kragt, ME, Rogers, A (2021) Social and economic benchmarks of the Australian Marine Parks; https://www.nespmarine.edu.au/node/4682

At night, satellite images of Earth capture a uniquely human signal--artificial lighting. Remotely-sensed lights at night provide a new data source for improving our understanding of interactions between human systems and the environment. NASA has developed the Black Marble, a daily calibrated, corrected, and validated product suite, so nightlight data can be used effectively for scientific observations. Black Marble is playing a vital role in research on light pollution, illegal fishing, fires, disaster impacts and recovery, and human settlements and associated energy infrastructures. https://blackmarble.gsfc.nasa.gov/ Romn, M.O. et al. (2018) NASAs Black Marble nighttime lights product suite. Remote Sensing of Environment. 210, 113143.

The datasets contain summaries of Queensland aquaculture locations in state marine and estuarine waters. The data has been recorded and submitted to Queensland DPI.

This resource is the 2022 offshore petroleum acreage release. The 2022 Petroleum Acreage Release comprises 10 areas located across four sedimentary basins: the Bonaparte Basin, the Browse Basin, the Gippsland Basin and the Northern Carnarvon Basin. Work program bidding for the 2022 release areas will remain open until 2 March 2023. For more information on investing in offshore petroleum exploration, including the acreage release map booklet and diagrams, refer to the Department of Industry, Science and Resources. For information on the 2022 acreage release areas visit the Department of Industry, Science and Resources website. The release areas can also be viewed interactively via the Acreage Release persona on Geoscience Australia's Data Discovery Portal.

Verification of fisheries sustainability credentials is essential to increase consumer confidence, market access and community benefit. Sector performance currently centres on monitoring fish stocks and economic performance. However, markets and stakeholder organisations increasingly require traceable evidence of Environmental, Social and Governance (ESG) indicators such as provenance, safety, diversity, animal welfare, carbon, biodiversity to inform decisions. To meet this need, this project activates CSIROs Healthcheck ESG Fisheries data system by engaging industry and Indigenous leaders, management agencies and researchers to identify targeted indicators, collect data, prioritise data gaps to enable more comprehensive ESG reporting. The reporting system is designed to collect and report data which is ready for ingestion into existing catalogues and exchanges (e.g., Ag Food data Exchange). Data is compatible and interoperable for publishing to recognised sustainability framework reporting (e.g. Status of Australian Fish Stocks, Marine Stewardship Certification, National Fisheries Plan, UN SDGs, Taskforce for Nature-related Financial Disclosure, Australian Agricultural Sustainability Framework, Agricultural Innovation Australia (AIA) Environmental Accounting Platform), and ready for supplying relevant indicators and data for Australia’s Fisheries and Aquaculture Sustainability Framework development. We demonstrate the capability of this sustainability data reporting system with selected fisheries. New indicators address climate impacts and adaptation responses, food safety systems, modern slavery protections, sector-led initiatives to improve ESG outcomes, Indigenous sector participation and economic development, among others. Using and building new digital and LLM (large language model) technologies to identify, screen and verify data sources, the sustainability reporting data system reflects global standards in traceability of data itself. Data provenance pipelines provide a pathway for repeatable, routine data extraction and reporting, and increase data accessibility for the Australian fisheries sector. Construction of these pipelines has highlighted critical gaps to address and what actions to take to overcome remaining limitations on data accessibility and shareability for key ESG reporting areas.

This resource is a map of Bottom Aragonite Saturation State and comes from from a simulation that uses the multi-model mean forcings from RCP8.5 projection to drive an ocean eddy-resolving model (OFAM3). Insights for Warming and Acidification Increased frequency and duration of marine heatwaves increase the likelihood of more frequent and severe coral bleaching events. Tasman Sea approaches a permanent marine heatwave state by GWL3. Great Barrier Reef and Ningaloo Reef will experience annual conditions for extreme bleaching by GWL3. Acidity at GWL3: Southern Ocean surface waters south of 60S will drop below an annual mean aragonite saturation state of 1. Values above 1.0 are required to produce calcareous shells or skeletons optimally. Values below 1 are considered corrosive, and skeletons and shells may be subject to dissolution. The ocean environment will become more stressful for marine organisms and ecosystems. The references for the simulations are: Feng, M., Zhang, X., Oke, P., Monselesan, D., Chamberlain, M. A., Matear, R. J., & Schiller, A. (2016). Invigorating ocean boundary current systems around Australia during 19792014: As simulated in a near-global eddy-resolving ocean model. Journal Of Geophysical Research-Oceans. Hayashida, H., Matear, R. J., & Strutton, P. G. (2020). Background nutrient concentration determines phytoplankton bloom response to marine heatwaves. Global Change Biology, 26(9), 48004811. https://doi.org/10.1111/gcb.15255 Hayashida, H., Matear, R. J., Strutton, P. G., & Zhang, X. (2020). Insights into projected changes in marine heatwaves from a high-resolution ocean circulation model. Nature Communications, 11(1), 19. https://doi.org/10.1038/s41467-020-18241-x Matear, R. J., Chamberlain, M. A., Sun, C., & Feng, M. (2015). Climate change projection for the western tropical Pacific Ocean using a high-resolution ocean model: Implications for tuna fisheries. Deep Sea Research Part II: Topical Studies in Oceanography, 113(0), 2246. Matear, R. J., Chamberlain, M. A., Sun, C., & Feng, M. (2013). Climate change projection of the Tasman Sea from an Eddy-resolving Ocean Model. Journal Of Geophysical Research-Oceans, 118(6), 29612976. Zhang, X., Oke, P. R., Feng, M., Chamberlain, M. A., Church, J. A., Monselesan, D., et al. (2016). A near-global eddy-resolving OGCM for climate studies. Geoscientific Model Development Discussions. Diagnostics The key ocean diagnostics are displayed according to Global Warming Levels (GWLs) using the 20 year period that define a given GWL. The key ocean diagnostics are: 1. Sea Surface Temperature monthly climatology 2. Surface Aragonite Saturation State monthly climatology 3. Surface pH monthly climatology 4. Intensity of Marine Heat Wave 5. Duration of Marine Heat Wave 6. NPP monthly climatology (N mol/m^2/s) 7. Degree Heating Weeks (average of the annual maximum value dhw_amax, maximum (dhw_max) and minimum (dhw_max) annual value over GWL period 8. Bottom Temperature 9. Full ocean depth temperature (note simulation used restoring to T and S below 2000m)10. Magnitude of Bottom Stress (bmf) 10. Bottom aragonite saturation state Data/confidence Confidence: high confidence in the direction of change, medium confidence in the magnitude of change and low confidence in the ecological consequence of the changes. (consistent with IPCC AR6) Limitation: ocean simulations that are not well suited for representing the high-resolution dynamics and features of the Australian coastal areas. https://github.com/AusClimateService/hazard_ocean/blob/main/README.md

This resource is Cylcone tracks for the periods 2003-2007, 2008-2012, 2013-2017 and 2018-2023 The International Best Track Archive for Climate Stewardship (IBTrACS) provides location and intensity for global tropical cyclones. The data span from the 1840s to present, generally providing data at 3-hour intervals. While the best track data is focused on position and intensity (maximum sustained wind speed or minimum central pressure), other parameters are provided by some agencies (e.g., radius of maximum winds, environmental pressure, radius of hurricane force winds, etc.) and are likewise provided in IBTrACS. Files are available subset by Basin or time period, where basins include: East Pacific, North Atlantic, North Indian, South Atlantic, South Indian, South Pacific, and the West Pacific. Time periods include: All data, since 1980, and the last 3 years. https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C01552