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environment

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  • This record provides an overview of the NESP Marine and Coastal Hub small-scale study - "Microplastics in South Eastern Australian coastal waters: synthesising current data and identifying key knowledge gaps for the management of plastic pollution". For specific data outputs from this project, please see child records associated with this metadata. -------------------- Plastic pollution is pervasive in coastal environments globally and in Australia. Due to their small size, microplastics (pieces <5mm) are readily ingested by marine organisms and potentially accumulate across food webs, raising concerns for biota, ecosystem services and human health. Yet, to define guidelines and support policy actions that curb microplastic pollution, managers and decision-makers lack clear, synthesised information on this multifaceted issue, including on occurrence, sources, and pathways of microplastics in coastal and marine environments. This project produces a synthesis of current data on microplastics in South Eastern Australian coastal waters (i.e. South Australia, Victoria and New South Wales) and identify key knowledge gaps for the management of plastic pollution. Outputs • List of compiled datasets relating to microplastics in SE Aus waters [spatial dataset] • Scoping document synthesising the information available on the presence of microplastics in coastal marine environments in South Eastern Australia, its potential sources and pathways [written]

  • This dataset summarises 40 years of seagrass data collection (1983-2022) within Torres Strait and the Gulf of Carpentaria. The full dataset is available through eAtlas at https://doi.org/10.26274/2CR2-JK51 and contains point and polygon packages. This record describes the meadow extent polygons at 641 individual or composite meadows. Managing seagrass resources in northern Australia requires adequate baseline information on where seagrass is (presence/absence), the mapped extent of meadows, what species are present, and date of collection. This baseline is particularly important as a reference point against which to compare seagrass loss or change through time. The scale of northern Australia and the remoteness of many seagrass meadows from human populations present a challenge for research and management agencies reporting on the state of seagrass ecological indicators. Broad-scale and repeated surveys/studies of areas are logistically and financially impractical. However seagrass data is being collected through various projects which, although designed for specific reasons, are amenable to collating a picture of the extent and state of the seagrass resource. In this project we compiled seagrass spatial data collected during surveys in Torres Strait and the Gulf of Carpentaria into a standardised form with point-specific and meadow-specific spatial and temporal information. We revisited, evaluated, simplified, standardised, and corrected individual records, including those collected several decades ago by drawing on the knowledge of one of our authors (RG Coles) who led the early seagrass data collection and mapping programs. We also incorporate new data, such as from photo records of an aerial assessment of mangroves in the Gulf of Carpentaria in 2017. This project was funded by the National Environmental Science Programme (NESP) Marine and Coastal Hub and Torres Strait Regional Authority (TSRA) in partnership with the Centre for Tropical Water and Aquatic Ecosystem Research (TropWATER), James Cook University. The project follows on from TropWATER’s previous work compiling 35 years of seagrass spatial point data and 30 years of seagrass meadow extent data for the Great Barrier Reef World Heritage Area (GBRWHA) and adjacent estuaries, funded through successive NESP Tropical Water Quality Hub Projects 3.1 (2015-2016) and 5.4 (2018-2020). These data sets are now publicly available through the eAtlas data portal: https://doi.org/10.25909/y1yk-9w85 . In making this data publicly available for management, the authors and data custodians request being contacted and involved in decision making processes that incorporate this data, to ensure its limitations are fully understood. Polygons in the meadow layer are drawn from extent data collected during some surveys. Not all surveys collected meadow extent data (e.g., Torres Strait lobster surveys). The seagrass meadow layer is a composite of all the spatial polygon data we could access where meadow boundaries were mapped as part of the survey. All spatial layers were compiled into a single spatial layer using the ArcToolbox ‘merge’ function in ArcMap. Where the same meadow was surveyed multiple times as part of a long-term monitoring program, the overlapping polygons were compiled into a single polygon using the ‘merge’ function in ArcMap. Because meadows surveyed more than once were merged, there were some cases where adjacent polygons overlap each other. Meadow Data Includes: 1. Temporal survey details – Survey month and year, or a list of survey dates for meadows repeatedly sampled; 2. Survey methods; 3. Meadow persistence – Classified into three categories: a. Unknown – Unknown persistence as the meadow was surveyed less than five times; b. Enduring – Seagrass is present in the meadow ≥90% of the surveys; c. Transitory – Seagrass is present in the meadow <90% of the surveys; 4. Meadow depth – Classified into three categories: a. Intertidal – Meadow was mapped on an exposed bank during low tide, e.g. Karumba monitoring meadow; b. Subtidal – Meadow remains completely submerged during spring low tides, e.g. Dugong Sanctuary meadow; c. Intertidal-Subtidal – Meadow includes sections that expose during low tide and sections that remain completely submerged, e.g. meadows adjacent to the Thursday Island shipping channel; 5. Dominant species of the meadow based on the most recent survey; 6. Presence or absence of individual seagrass species in a meadow; 7. Meadow density categories – Seagrass meadows were classified as light, moderate, dense, variable or unknown based on the consistency of mean above-ground biomass of the dominant species among all surveys, or percent cover of all species combined (see Table 2 in Carter et al. 2022). For example, a Halophila ovalis dominated meadow would be classed as “light” if the mean meadow biomass was always <1 gram dry weight m-2 (g DW m-2) among years, “variable” if mean meadow biomass ranged from <1 - >5 g DW m-2, and “dense” if mean meadow biomass was always >5 g DW m-2 among years. For meadows with density assessments based on both percent cover (generally from older surveys) and biomass, we assessed density categories based on the biomass data as this made the assessment comparable to a greater number of meadows, and comparable to the most recent data. Meadows with only one year of data were assigned a density category based on that year but no assessment of variability could be made and these are classified as “unknown”; 8. The minimum and maximum annual mean above-ground biomass measured in g DW m-2 (+ standard error if available) for each meadow is included for meadows with >1 year of biomass data. For meadows that were only surveyed once the mean meadow biomass (+ standard error if available) is presented as the minimum and maximum biomass of the meadow. “-9999” represents meadows where no above-ground biomass data was collected.; 9. The minimum and maximum annual mean percent cover is included for each meadow with >1 year of percent cover data. For meadows that were only surveyed once the mean meadow percent cover is presented as the minimum and maximum percent cover of the meadow. Older surveys (e.g., 1986 Gulf of Carpentaria surveys) used percent cover rather than biomass. For some surveys percent cover was estimated as discrete categories or ‘data binning’ (e.g., <10% - >50%). “-9999” represents meadows where no percent cover data was collected; 10. Meadow area survey details – The minimum, maximum and total area (hectares; ha) for each meadow: a. Total area - Total area of each meadow was estimated in the GDA 1994 Geoscience Australia Lambert projection using the ‘calculate geometry’ function in ArcMap. For meadows that were mapped multiple times, meadow area represents the merged maximum extent for all surveys. 11. Minimum and maximum area – For meadows surveyed more than once the minimum and maximum annual area of the meadow was reported. For meadows that were only surveyed once the meadow area is presented as the minimum and maximum area of the meadow. Where possible, we retained area data reported in the original shapefiles (and calculated using original projections). Where area data did not exist in original shapefiles (e.g., 1986 Gulf of Carpentaria surveys), we calculated area using the ‘calculate geometry’ function in ArcMap in the GDA 1994 Geoscience Australia Lambert projection; Data custodians. Spatial Limits: Data was limited to that collected in the Gulf of Carpentaria between Cape Arnhem (Northern Territory) and Cape York (Queensland). Torres Strait data was restricted to north of Queensland’s Great Barrier Reef World Heritage Area boundary, and includes data collected along the Papua New Guinea coastline. Taxonomy: Seagrass taxonomic revision over the last couple of decades has resulted in the revision and reclassification of some tropical species. For example, Zostera capricorni has been reclassified as Zostera muelleri subsp. capricorni, Halophila minor a synonym of Halophila ovalis, and Halodule pinifolia a synonym of Halodule uninervis. Field surveys have at times grouped species that are difficult to distinguish in the field. To address these issues, we amalgamated some species into complexes: Halophila minor and Halophila ovalis are included as Halophila ovalis complex. Zostera muelleri subsp. capricorni has been abbreviated to Zostera capricorni throughout for simplicity. Data Sets: Data was limited to that collected in the Gulf of Carpentaria between Cape Arnhem (Northern Territory) and Cape York (Queensland). Torres Strait data was restricted to north of Queensland’s Great Barrier Reef World Heritage Area boundary, and includes data collected along the Papua New Guinea coastline. Further information in the data sets included in this synthesis can be found in this report: Carter A, McKenna S, Rasheed M, Taylor H, van de Wetering C, Chartrand K, Reason C, Collier C, Shepherd L, Mellors J, McKenzie L, Roelofs A, Smit N, Groom R, Barrett D, Evans S, Pitcher R, Murphy N, Duke NC, Carlisle M, David M, Lui S, Torres Strait Indigenous Rangers (led by Pearson L, Laza T, Bon A), and Coles RG (2022). Four Decades of Seagrass Spatial Data from Torres Strait and Gulf of Carpentaria. Report to the National Environmental Science Program. Centre for Tropical Water and Aquatic Ecosystem Research (TropWATER), James Cook University. Limitations of the Data: Data included extends back to the mid-1980s. Large parts of the coast have not been mapped for seagrass presence since that time. Technology and methods for mapping and position fixing have improved dramatically in 40 years. This layer represents the most reliable interpretation of that early data. Not all surveys collected meadow data, including Torres Strait lobster and beche de mer surveys and Torres Strait intertidal transect monitoring collected only site data. Because of this, the meadow layer represents an underestimate of seagrass extent, particularly in deeper subtidal waters. The meadow layer should be used in conjunction with the site layer to determine where meadows have been mapped, and where seagrass surveys have occurred but no seagrass has been found. See Table 1 and Data age, Limitations and Variability section in Carter et al. (2022). Data Dictionary: Torres Strait and Gulf of Carpentaria seagrass meadows, 1984-2022 (polygon data) - ID (numeric) - Unique identifier representing a single meadow - SURVEY_NAME (text) – Name of survey location - SURVEY_DATE (text) – A list of survey date(s) for meadows repeatedly sampled; month and year - PERSISTENCE (text) – Meadow form on three categories: enduring, transitory, unknown - DEPTH (text) – Classified into three categories (intertidal, subtidal, intertidal-subtidal) - DENSITY (text) – Meadow density categories (light, moderate, dense, variable, unknown) - AREA (text) - Area of the composite meadow in a given location in hectares, represents merged maximum extent - SURVEY METHOD (text) – e.g., helicopter, walking, hovercraft, boat-based including camera, free diving, scuba diving, van Veen grab, sled net - COMMENTS (text) – Any comments for that site - CUSTODIAN (text) – Custodian/owner of the data set - NO_SURVEYS (numeric) – Number of times meadow has been surveyed - DOMINANT_SPP [DOM_SPP] (text) – The dominant species in the meadow - EA_PA (numeric) – Absence (0) or Presence (1) of Enhalus acoroides - TC_PA (numeric) – Absence (0) or Presence (1) of Thalassodendron ciliatum - TH_PA (numeric) – Absence (0) or Presence (1) of Thalassia hemprichii - CS_PA (numeric) – Absence (0) or Presence (1) of Cymodocea serrulata - CR_PA (numeric) – Absence (0) or Presence (1) of Cymodocea rotundata - ZC_PA (numeric) – Absence (0) or Presence (1) of Zostera muelleri subsp. capricorni - HU_PA (numeric) – Absence (0) or Presence (1) of Halodule uninervis - SI_PA (numeric) – Absence (0) or Presence (1) of Syringodium isoetifolium - HS_PA (numeric) – Absence (0) or Presence (1) of Halophila spinulosa - HT_PA (numeric) – Absence (0) or Presence (1) of Halophila tricostata - HO_PA (numeric) – Absence (0) or Presence (1) of Halophila ovalis - HC_PA (numeric) – Absence (0) or Presence (1) of Halophila capricorni - HD_PA (numeric) – Absence (0) or Presence (1) of Halophila decipiens - BIO_MIN (numeric) – The minimum mean meadow biomass measured in g DW m-2 for meadows sampled more than once, or -9999 where biomass data not recorded - BIO_MIN_SE (numeric) – Standard error of the minimum mean meadow biomass measured in g DW m-2, or -9999 where biomass data not recorded - BIO_MAX (numeric) – The maximum mean meadow biomass measured in g DW m-2 for meadows sampled more than once, or -9999 where biomass data not recorded - BIO_MAX_SE (numeric) – Standard error of the maximum mean meadow biomass measured in g DW m-2, or -9999 where biomass data not recorded - PER_CO_MIN (numeric) – The minimum mean meadow percent cover for meadows sampled more than once, or -9999 where percent cover data not recorded - PER_CO_MAX (numeric) – The maximum meadow percent cover for meadows sampled more than once, or -9999 where percent cover data not recorded - AREA_MIN (numeric) – The minimum area for meadows sampled more than once - AREA_MAX (numeric) – The maximum area for meadows sampled more than once

  • NESP Marine Biodiversity Hub Project C2 involved integration and analysis of three existing monitoring datasets: the Reef Life Survey (RLS), IMAS Long-term MPA (LTMPA), and AIMS Long-term (AIMS LTM) monitoring programs. These analyses involved generating new derived data on indicator values for survey sites in each of the datasets, which have been reported in the 2016 State of the Environment (SoE) report. Indicators included the biomass of large fishes, the community temperature index, the proportion of invasive species, crown-of-thorns seastar density and the proportion of threatened species. Details of calculation of these indicators and summary of trends in values across sites and times are provided in detail in a manuscript currently in the review process for an international journal [RSS to provide publication details once available], as well as in metadata supplied for the State of the Environment report. This metadata record provides links to each of the three datasets used in the synthesis, and links to access the derived biological indicator data reported in the 2016 SoE report. See "On-Line Resources" section.

  • The movement and behaviour of the Southern Rock Lobster (Jasus edwardsii) was monitored using a radio acoustic telemetry systems at two sites in eastern Tasmania.

  • <p>Flythrough movie of Bremer Commonwealth Marine Reserve, southwest Western Australia showing bathymetry of Bremer Canyon, Hood Canyon, Henry Canyon and Knob canyon. <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

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    Investigations of the impact of sewage and heavy metal inputs on inshore rocky reef communities have been limited to date because the scale of information on levels of pollutants has been much broader than the span of transects at sites investigated. As a consequence, analyses have been confounded by poor information on the variety of stressors operating at any site. Finer resolution data on pollutants are needed. To address this deficiency, the influence of sewage, heavy metals and other pollutants were assessed by collecting sediment samples at Reef Life Survey ecological monitoring sites and measuring a range of associated markers. This includes basic biogeochemical information (pH, turbidity, total phosphate, TKN, total organic carbon), stable isotopes (delta15N, delta13C), heavy metal concentrations, hydrocarbon concentrations.

  • Collected benthic community structure (species and abundance) and physical/chemical attributes (including sediment grain size, redox, sulphide and depth) for a large number of locations in the Huon and Derwent estuaries of south east Tasmania. Data was collected using van veen grab, divers where necessary or core samples. All locations include heavy metal data and site information. Most data was collected with spatial references (GPS).

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    Temperature loggers have been deployed at a range of sites statewide in waters ranging between 6 and 22m depth. From 2012, 27 sites around Tasmania are being monitored. This record shows data collected from 2004 up to December 2020. Data is still being collected (April 2023) and will be added to this collection as it becomes available.

  • This record provides an overview of the NESP Marine and Coastal Hub Research Plan 2023 project 3.7 – Identifying and overcoming barriers to coastal and marine habitat restoration and Nature based Solutions in Australia. No data outputs are planned for this project. -------------------- There is an increasing need for and investment in coastal and marine restoration around Australia to help manage habitat and biodiversity loss, water quality, coastal inundation and erosion, and blue carbon assets. These projects are undertaken by a range of Commonwealth, state and local government agencies, NGOs, and community groups, and range across different habitat types and scale. However, a number of barriers currently preclude widespread uptake and implementation of habitat restoration and nature-based solutions (NbS) in Australia, which centre on: 1) policy and legislative barriers; 2) engineering adoption of NbS; and 3) Aboriginal and Torres Strait Islander inclusion and co-design. Overcoming barriers to marine and coastal restoration, and Nature-based Solutions (NbS) adoption is critical to safeguarding Australia’s marine estate. We focus this research on three thematic areas that represent roadblocks and opportunities for more inclusion in implementing and scaling-up restoration and NbS: 1. Engaging policy &amp; permitting regulators to identify and breakdown barriers for marine and coastal habitat restoration; 2. Understanding and up-take of NbS by the engineering sector; and 3. Inclusion of Aboriginal and Torres Strait Islanders in restoration and NbS The research will be conducted through in person and/or virtual workshops, with the outcome being advancement of effective approaches to overcome these challenges. Planned Outputs • Final technical report with analysed data and a short summary of recommendations for policy makers of key findings [written]

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    Seagrass meadows within the Broadwater were mapped using high-resolution 2005 orthorectified color aerial photography obtained from the Gold Coast City Council at a scale of 1:10,000 and pixel size 0.15 m. Using desktop GIS mapping (MapInfo Professional 8.0), polygons were drawn over all potential seagrass meadows at a scale of 1:5000. Spatial accuracy was estimated to be approximately ± 1 m on well-defined boundaries (e.g. dense seagrass meadows) and ± 2 m along poorly defined boundaries (e.g. sparse seagrass meadows).