IMAS Metadata Catalogue
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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
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This project undertook a rapid exploration of information on a priority subset of species identified by the Department of Climate Change, Energy, the Environment and Water (DCCEEW) and the National Offshore Petroleum Safety and Environment Authority (NOPSEMA) that are listed as critically endangered or endangered under the Environment Protection and Biodiversity Conservation Act 1999. It specifically focused on these species in relation to the Gippsland declaration area, and the adjacent areas to the declaration area in Bass Strait. This rapid exploration of information was conducted as follows: 1) identify datasets and information sources relevant to priority species identified by DCCEEW and NOPSEMA for the Gippsland declaration area; 2) identify the source of these datasets and information and their level of accessibility; 3) evaluate the utility of datasets and information identified in 2) for assessments/regulatory processes required to be undertaken by DCCEEW and NOPSEMA; and 4) identify what activities would need to be undertaken to improve the accessibility and utility of datasets and information sources identified in 3) that are not currently accessible in useable formats. Fifteen priorities species (12 birds, 3 cetaceans) were identified for which publicly-available occurrence data could be located. This record and the attached download describes the data inventory for Shy Albatross (Thalassarche cauta). To download the data inventory for all fifteen priority species, see https://doi.org/10.25959/GB51-RW44.
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This record provides an overview of the scope and research output of NESP Marine Biodiversity Hub Project A9 - "Grey Nurse Shark CK-MR Population Estimate – East Coast". For specific data outputs from this project, please see child records associated with this metadata. -------------------- A review of the 2002 National Recovery Plan for Grey Nurse Shark (DEWHA 2009) concluded it was not possible to determine if the east coast population had shown any signs of recovery (DoE 2014); recommending a new recovery plan be developed for this species. A primary objective of the new recovery plan (DoE 2014) is to improve knowledge of GNS population status. This will require a robust estimate of population size and trend – something that has not been provided to date. This project will use genetic SNP data to inform close kin-mark recapture analysis to estimate population size and trend, and provide guidance on future monitoring strategies for the east coast population of grey nurse shark. Planned Outputs • Tools to refine and integrate CK-MR and species demographic data for population assessments of a key threatened species at a national scale (combining knowledge developed under this project combined with similar techniques being applied under NESP to euryhaline sharks and white sharks). • A national estimate of (census) population size and trend for the eastern Australian population of grey nurse shark will be developed to fulfil the highest priority actions of the National Recovery Plan. • Identify national strategies to guide future monitoring of grey nurse shark populations. • The project will provide peer-reviewed additions to the scientific literature that will add to the science-support for the development and implementation of policies to support the ecologically sustainable management of Australia’s marine environment.
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A comparison was made of sediments and associated macrobenthos at sites sampled within 42 fish farm leases distributed across Tasmania. Several key biotic and abiotic metrics recommended in previous studies for assessing environmental impacts of fish farm waste were investigated.
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These data were collected on the RV L'Astrolabe (platform code: FHZI) from 19/10/2004 to 24/10/2004 on a trip from Hobart to Dumont D'Urville. Maximum photochemical efficiency of photosystem II (PSII), also called maximum quantum yield of PSII (Fv/Fm), has become one of the most widely utilized fluorescence parameters in phytoplankton research. It represents the potential photochemical efficiency, which is the probability that the light energy captured by the photosynthetic apparatus is being utilized as photochemistry. Fv/Fm has been shown to have an instant response to variations in physical and chemical properties and is interpreted as a diagnostic of the overall health or competence of phytoplankton. Together with the absorption cross section area of PSII and chlorophyll concentration, it can be used to measure primary production (Cheah et al. 2011, Deep Sea Research). Seawater from 3 m depth was supplied continuously from the ship’s clean seawater line. FRR fluorescence yields were measured continuously at 1 minute intervals in dark-adapted state (! 15 minutes dark-adaptation) using a flash sequence consisting of a series of 100 subsaturation flashlets (1.1 μs flash duration and 2.8 μs interflash period) and a series of 20 relaxation flashlets (1.1 μs flash duration and 51.6 μs interflash period).
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This record describes a gridded map of ocean wind noise for Australian EEZ for a typical April-September period.
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The Marine Futures Project was designed to benchmark the current status of key Western Australian marine ecosystems, based on an improved understanding of the relationship between marine habitats, biodiversity and our use of these values. Approximately 1,500 km2 of seafloor were mapped using hydroacoustics (Reson 8101 Multibeam), and expected benthic habitats "ground-truthed" using towed video transects and baited remote underwater video systems. Both sources of information were then combined in a spatial predictive modelling framework to produce fine-scale habitat maps showing the extent of substrate types, biotic formations, etc. Surveys took place across 9 study areas, including Geographe Bay in the southwest Capes region. The marine environment at this location varies from extensive seagrass meadows in protected waters, to kelp-dominated granite and limestone reefs in areas of high wave energy. A small number of corals are also found throughout the region, reflecting the influence of the southward flow of the Leeuwin Current. The fish fauna is also diverse, with a high proportion of endemic species.
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This resource is a map of Intensity of Marine Heatwaves 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 Heatwave 5. Duration of Marine Heatwave 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
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These data were collected on the RV L'Astrolabe (platform code: FHZI) from 22/01/2005 to 27/01/2005 on a trip from Dumont D'Urville to Hobart. Maximum photochemical efficiency of photosystem II (PSII), also called maximum quantum yield of PSII (Fv/Fm), has become one of the most widely utilized fluorescence parameters in phytoplankton research. It represents the potential photochemical efficiency, which is the probability that the light energy captured by the photosynthetic apparatus is being utilized as photochemistry. Fv/Fm has been shown to have an instant response to variations in physical and chemical properties and is interpreted as a diagnostic of the overall health or competence of phytoplankton. Together with the absorption cross section area of PSII and chlorophyll concentration, it can be used to measure primary production (Cheah et al. 2011, Deep Sea Research). Seawater from 3 m depth was supplied continuously from the ship’s clean seawater line. FRR fluorescence yields were measured continuously at 1 minute intervals in dark-adapted state (! 15 minutes dark-adaptation) using a flash sequence consisting of a series of 100 subsaturation flashlets (1.1 μs flash duration and 2.8 μs interflash period) and a series of 20 relaxation flashlets (1.1 μs flash duration and 51.6 μs interflash period).