This resource is a map of Aboriginal, Torres Strait Islander body (RATSIB) is a body recognised by the Commonwealth under s 203AD of the NTA to represent native title holders and persons who may hold native title and to consult with Aboriginal and Torres Strait Islander persons within a specified area. The statutory functions of RATSIBs are detailed in Part 11 Division 3 of the NTA and include: a) facilitation and assistance to prepare and progress native title applications and negotiation of future act processes; b) certification of native title applications and applications for registration of an ILUA; c) resolution of disputes between constituents; d) notification to persons who hold or may hold native title in the area of notices that relate to land and water in the RATSIB area; and e) agreement making to be a party to ILUAs as appropriate in its specified area. Provides a spatial representation of native title matters, related to custodial statutory functions associated with Registers in support of the Native Title Act 1993.

This resource is a map of Surface pH 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 a map of Custodial geospatial data held by the National Native Title Tribunal (NNTT) consists of those datasets necessary to contribute to the statutory functions associated with Registers and other information, in support of the Native Title Act 1993 (Cth). Provides a spatial representation of native title matters, related to custodial statutory functions associated with Registers in support of the Native Title Act 1993.

The datasets contain summaries of Queensland logbook data on catch and effort distribution for commercial fisheries in state marine and estuarine waters. The logbook data has been recorded and submitted to QLD Department of Primary Industries by commercial fishers. The data are aggregated to produce summaries of total catch and effort by fishery at a 6 nm resolution where 5 boats or more operate. For areas where less than 5 boats operate the data is shown as confidential. The data was mapped using 5 year - financial year periods; 2003/04 to 2007/08, 2008/09 to 2012/13, 2018/19 to 2022/23, and 1 year; 2022/23.

This resource is daily means of Chla measured by the Aqua satelite which represents phytoplanton in the water for the periods 2018-2023 and 2022-2023. The Aqua satellite platform carries a MODIS sensor that observes sunlight reflected from within the ocean surface layer at multiple wavelengths. These multi-spectral measurements are used to infer the concentration of chlorophyll-a (Chl-a), most typically due to phytoplankton, present in the water. There are multiple retrieval algorithms for estimating Chl-a. These data use the OCI method (Hu et al 2012, doi: 10.1029/2011jc007395) recommended by the NASA Ocean Biology Processing Group and implemented in the SeaDAS processing software l2gen. The OCI algorithm is described at https://oceancolor.gsfc.nasa.gov/atbd/chlor_a/ (and links therein).

This resource is a map of Surface 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 a map of Sea Surface Temperature 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 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