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oceans

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  • This record provides an overview of the scope and research output of NESP Marine Biodiversity Hub Emerging Priorities project - "Assessing the effectiveness of waste management in reducing the levels of plastics entering Australia’s marine environment". For specific data outputs from this project, please see child records associated with this metadata. -------------------- This project will contribute to better understanding where to target investment in abatement measures by providing information on the extent of the leakage of plastic materials into the marine environment, where the greatest leakages are and in what quantity, and what form they take (e.g. plastic bags, packaging, takeaway containers). It will also identify what type of facilities, policies and outreach strategies governments (state and local) have in place and undertake an assessment of their effectiveness. The objectives of this project are to: 1. Investigate the relationship between plastic debris in the marine environment and litter data from nearby sites; 2. Determine whether there are identifiable pathways through which plastic debris moves into the marine environment; 3. Investigate whether particular investments in facilities, policies or outreach are effective in reducing plastic debris on coasts and in oceans and where investment should be directed in the future; and 4. Initiate an internal department workshop to socialise the outcomes of the research across the relevant arms of the department, including staff involved in approvals, waste, protected species, and parks, and explore the utility of existing data to address the Department’s needs, including those arising from the TAP and the Senate Inquiry. Planned Outputs • A written report and plain English summary for use by state, territory and local governments, which: - Synthesises existing knowledge on the relationship between debris in the marine environment and litter data from nearby sites, the types of litter and the pathways through which litter moves into the marine environment. - Summarises existing coastal debris/litter survey methodologies with discussion of applications of each. • A list of the activities and programs associated with plastic waste reduction (including facilities, policies and outreach), • A publically accessible analysis and summary of different survey methods aiming to reduce debris inputs to the marine environment. - The cost of the activities and programs - Ranking of activities and programs regarding their effectiveness in reducing plastic waste in the marine environment. • Conclusions on where marine debris hot spots are in Australia’s marine environment and effective mitigation strategies. • Recommendations on where more information (scientific, policy, infrastructure, community engagement) is required to obtain a better understanding of the problem and possible solutions. This may include identifying knowledge gaps and needs for further analysis

  • The Aqua and Orbview satellites carry a MODIS and SeaWIFS sensors (respectively) 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 and aggregating the data over time. This data set is a reprocessed copy of 9km monthly and 8-day versions produced globally by NASA, adjusted for the Southern Ocean south of latitude 30S. The full methodology is described in Johnson, R., Strutton, P.G., Wright, S.W., McMinn, A., Meiners, K.M., 2013. Three improved satellite chlorophyll algorithms for the Southern Ocean. Journal of Geophysical Research: Oceans. doi: 10.1002/jgrc.20270. It is expected that the data set will be periodically updated with contemporary data as it becomes available. There are four sub-streams within this data set. A monthly and an 8-day series for MODIS/Aqua and similarly for SeaWIFS. Note that SeaWIFS ceased operation in late 2010 so there will be no further SeaWIFS data. The data represented by this record is weekly data for MODIS/Aqua.

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    The AUStralian Tidal Energy (AUSTEn) project was a three year project (2018 - 2020) funded by the Australian Renewable Energy National Agency (agreement number G00902) led by the Australian Maritime College (University of Tasmania), in partnership with CSIRO and University of Queensland. The project had a strong industry support (Atlantis Resources Limited, MAKO Tidal Turbines Ltd, Spiral Energy Corporation Ltd). The aim of the project was to assess the technical and economic feasibility of tidal energy in Australia, based on the best understanding of resource achievable. For further information and output of the project, please visit the AUSTEn project website www.austen.org.au.

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    At the inception of our project, no study had examined particle fluxes in the Subantarctic Zone (SAZ) of the Southern Ocean, despite the fact that the SAZ represents a large portion of the total area of the Southern Ocean, serve as a strong sink for atmospheric (~1G t C yr-1 [Metzl et al., 1999]), and is central to hypotheses linking particle fluxes and climate change [Francois et al., 1997; Kumar et al., 1995; Sigman et al., 1999]. The SAZ serves as an interface between the cold nutrient-rich waters to its south and the nutrient-depleted subtropical gyres to its north. SAZ upper layers are marked by a thick layer of relatively homogenous Subantarctic Mode Water (SAMW), which overlies Antarctic Intermediate Water (AAIW). Both water masses are subducted northward beneath the subtropical gyres. Thus particles leaving the surface in these regions contribute to carbon redistribution via both the fraction that reaches the deep sea by settling and the fraction that is remineralized within SAMW or AAIW and subsequently subducted. The SAZ exhibits surface water carbon dioxide partial pressures well below atmospheric equilibrium, but PFZ waters are closer to atmospheric equilibrium in this sector [Metal et al., 1999; Poppet al., 1999]. The relative physical and biological contributions to these carbon dioxide partial pressure variations are unclear, but it is important to determine them because physical and biological carbon dioxide transfers are expected to show different responses to climate change [ Matear et al., 1999; Sarmiento and LeQuere, 1996]. For these reasons we focused on the SAZ and, for comparative purposes, on the PFZ to its south. We measured particle fluxes using moored sinking particle traps at three sites in the SAZ, in the PFZ, and beneath the Subantarctic Front (SAF), which separates them. This record describes particle flux data collected between 2000 and 2001. The NetCDF data contains the following variables. Please note not all variables are supplied in all files, specifically there are not uncertainty estimates and no quality control flags for this data. -----DATA DICTIONARY----- Name, description, units, standard name TIME, time, YYYY-MM-DD, time of sample midpoint TIME_START, time sample open, YYYY-MM-DD, time sample open NOMINAL_DEPTH, depth, m, nominal depth LATITUDE, latitude, degrees_north, latitude of anchor LONGITUDE, longitude, degrees_east, longitude of anchor pressure_actual, actual, dbar, actual pressure sample, sample number, 1, sample number sample_quality_control, quality flag for sample number, unitless, quality flag for sample number mass_flux, <1mm, mg m-2 d-1, particulate total mass flux mass_flux_uncertainty, uncertainty for particulate total mass flux, mg m-2 d-1,), uncertainty for particulate total mass flux mass_flux_quality_control, quality flag for particulate total mass flux, unitless, quality flag for particulate total mass flux SAL_BRINE, supernatant, 1, sample supernatant practical salinity SAL_BRINE_uncertainty, uncertainty for sample supernatant practical salinity, 1, uncertainty for sample supernatant practical salinity SAL_BRINE_quality_control, quality flag for sample supernatant practical salinity, unitless, quality flag for sample supernatant practical salinity pH_BRINE, supernatant, 1, sample supernatant pH NBS scale pH_BRINE_uncertainty, uncertainty for sample supernatant pH NBS scale, 1, uncertainty for sample supernatant pH NBS scale pH_BRINE_quality_control, quality flag for sample supernatant pH NBS scale, unitless, quality flag for sample supernatant pH NBS scale PC_mass_flux, <1mm, mg m-2 d-1, particulate total carbon mass flux PC_mass_flux_uncertainty, uncertainty for particulate total carbon mass flux, mg m-2 d-1, uncertainty for particulate total carbon mass flux PC_mass_flux_quality_control, quality flag for particulate total carbon mass flux, unitless, quality flag for particulate total carbon mass flux PN_mass_flux, <1mm, mg m-2 d-1, particulate total nitrogen mass flux PN_mass_flux_uncertainty, uncertainty for particulate total nitrogen mass flux, mg m-2 d-1, uncertainty for particulate total nitrogen mass flux PN_mass_flux_quality_control, quality flag for particulate total nitrogen mass flux, unitless, quality flag for particulate total nitrogen mass flux POC_mass_flux, <1mm, mg m-2 d-1, particulate organic carbon mass flux POC_mass_flux_uncertainty, uncertainty for particulate organic carbon mass flux, mg m-2 d-1, uncertainty for particulate organic carbon mass flux POC_mass_flux_quality_control, quality flag for particulate organic carbon mass flux, unitless, quality flag for particulate organic carbon mass flux PIC_mass_flux, <1mm, mg m-2 d-1, particulate inorganic carbon mass flux PIC_mass_flux_uncertainty, uncertainty for particulate inorganic carbon mass flux, mg m-2 d-1, uncertainty for particulate inorganic carbon mass flux PIC_mass_flux_quality_control, quality flag for particulate inorganic carbon mass flux, unitless, quality flag for particulate inorganic carbon mass flux BSi_mass_flux, <1mm, mg m-2 d-1, particulate biogenic silicon mass flux BSi_mass_flux_uncertainty, uncertainty for particulate biogenic silicon mass flux, mg m-2 d-1, uncertainty for particulate biogenic silicon mass flux BSi_mass_flux_quality_control, quality flag for particulate biogenic silicon mass flux, unitless, quality flag for particulate biogenic silicon mass flux TIME_END, time sample closed, YYYY-MM-DD, time sample closed Reference, citable reference DOI, DOI

  • Redmap is a primarily a website that invites the community to spot, log and map marine species that are uncommon in their region, or along particular parts of their coast. The information collected is mapped and displayed on the site, demonstrating, in time, how species distributions may be changing. Sightings are divided into two categories – those with a photo that can be ‘verified’ by a marine biologist, and sightings without photos that we call community sightings (anecdotal). All the information collected, with and without photos, is mapped and will be used in the following years to map out a ‘story’ of changes occurring in our marine environment. The main data collected includes the species sighted (normally selected from a list comprising preselected species of interest), the location, date/time and activity being undertaken. Other optional information gathered include biological data such as sex, size and weight and environmental data such as water depth and temperature and habitat. This record is associated with live data (and will subsequently change over time) and spatial elements have reduced accuracy. It is also subject to a three year embargo (ie. does not contain data less than three years old). If you wish to discuss obtaining a citable, static dataset, that is current and/or contains accurate spatial elements, please see Point of Contact.

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    This dataset consist of dissolved oxygen (DO) and temperature data collected using HOBO Dissolved Oxygen loggers (U26-001) under FRDC project 2016-067. Loggers are deployed on strings in two locations in Macquarie Harbour, Tasmania.

  • The ETAS (Eastern TASmania) model is a high-resolution (~2 km in the horizontal) ocean model for eastern Tasmania, providing three-dimensional estimates of daily temperature, salinity, and circulation over the 1993-2014 period. This dataset consists of eastward (u) and northward (v) currents organised into yearly files.

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    Model output from a circumpolar realisation of the Regional Ocean Modelling System (ROMS). Model was run at a horizontal resolution of 1/4 degree and 31 vertical levels. Spatial domain was circumpolar out to 30 degrees South. Forcing comes from prescribed salt and heat fluxes based on a derived climatology from Tamura et al (2008). For open water regions the Tamura data is blended with open-water heat, salt and surface stress fluxes from a monthly NCEP2 climatology.

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    This record presents data collected from tagged and recaptured Short-tailed shearwaters (Puffinus tenuirostris), with data presented throughout the Southern Ocean. The study was initially conducted on Wedge Island (43 km2), southern Tasmania (43o 07' S, 147o 40' E). Fifty geolocation archival (GLS) tag deployments were made on 34 adult birds in the pre-laying exodus (n = 18), incubation (n = 12) and early chick-rearing (ECR) phases (n = 20). In 2012, 12 birds were tracked during the pre-laying exodus. GLS tags were deployed between the 10th and the 18th of October. Ten birds were tracked from Wedge Island (as in 2010) and 2 were tracked from Whalebone Point, Bruny Island (43.44 South, 147.23 East; birds 22 and 80).

  • The dataset measures the long-term seasonal variations of the sea surface temperature (SST) of ocean surface waters. They are derived from MODIS (aqua) images using NASA's SeaDAS image processing software. The monthly SST images between July 2002 and December 2017 are used to calculate the standard deviations of the four austral seasons: winter (June, July, and August), spring (September, October and November), summer (December, January and February) and autumn (March, April and May). The extent of the dataset covers the entire Australian EEZ and surrounding waters (including the southern ocean). The unit of the dataset is Celsius degree. This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.