<p>The dataset indicates the seasonal primary productivity hotspots of ocean surface waters. They are derived from MODIS (aqua) images using NASA's SeaDAS image processing software. The monthly chlorophyll a images between July 2002 and August 2014 are used to identify the primary productivity hotspots 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 value (between 0 and 1.0) of the dataset represents the likelihood of the location being a primary productivity hotspot. <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

In 2017, the NESP Marine Biodiversity Hub committed to developing field manuals for selected marine sampling platforms to ensure that data collected at different times and places across Australia are directly comparable. Ultimately, 136 individuals from 53 organisations contributed to the Field Manuals for Marine Sampling in Australian Waters released in 2018 (Version 1) and 2020 (Version 2). These field manuals are underpinned by a highly collaborative and iterative process, involving extensive community consultation and review and can thus be considered best practices. In this report, we aim to compile the outcomes of these marine sampling best practices. These outcomes are then integrated into an impact assessment based on the CSIRO Impact Framework. Due to the short period in which the best practices have existed, impact cannot yet be fully assessed, but we lay the foundations to facilitate such an assessment in the future. Overall, the marine sampling best practices are spreading nationally and internationally, as evidenced by uptake and adoption, including by industry (e.g. Woodside) and developing countries (e.g. St Lucia). Australia and the Unites States represent countries with the most downloads, and highest uptake seems to be for the survey design, benthic BRUV, pelagic BRUV, and multibeam manuals. In addition, the best practices have received community endorsement, with recommendations from key national and international organisations (e.g. Parks Australia, Global Ocean Observing System (for the BRUV manual), National Offshore Petroleum Safety and Environmental Management Authority). We anticipate several social, economic, and environmental impacts of the best practices to be measurable in 5-10 years after the release of the best practices (i.e. after 2025). For any single survey, the impact of these best practices may be small, but there is much stronger impact when considering a national perspective, as combined multiple datasets from multiple surveys allow us to see the bigger spatial and temporal picture. In this case, standardised datasets can be combined without the fear of confounding between method-of-observation and ecological signal. Thus, a series of compatible surveys are needed before they can be usefully combined, and the true impact of these best practices will not be felt for years, or maybe even decades. Ultimately, the measures of outcome and impact described in this report will help strengthen the links between marine observing communities and policymaking communities by ensuring that timely and fit-for-purpose information is generated for evidence-based decisions. <b>Citation:</b> Przeslawski R, Foster S, Gibbons B, Langlois T, Monk J (2021). Impact and Outcomes of Marine Sampling Best Practices. Report to the National Environmental Science Program, Marine Biodiversity Hub. Geoscience Australia.

<p>This dataset provides the spatially continuous data of seabed gravel (sediment fraction >2000 µm), mud (sediment fraction < 63 µm) and sand content (sediment fraction 63-2000 µm) expressed as a weight percentage ranging from 0 to 100%, presented in 10 m resolution raster grids format and ascii text file.</p> <p>The dataset covers the eight areas in the Timor Sea region in the Australian continental EEZ.</p> <p>This dataset supersedes previous predictions of sediment gravel, mud and sand content for the basin with demonstrated improvements in accuracy. Accuracy of predictions varies with sediment types, with a VEcv = 71% for mud, VEcv = 72% sand and VEcv = 42% for gravel. Artefacts occur in this dataset as a result of noises associated predictive variables (e.g., horizontal and vertical lines resulted from predictive variables derived from backscatter data are the most apparent ones). To obtain the most accurate interpretation of sediment distribution in these areas, it is recommended that noises with backscatter data should be reduced and predictions updated.</p> <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

<p>This dataset contains identifications of polychaetes collected during surveys on the RV Solander in northern Australia: SOL4934 (27 August-24 September, 2009) , SOL5117 (30 July-27 August, 2010), SOL5463 (3-31 May 2012), and SOL5650 (12 September-6 October 2012). Sediment was collected with a Smith McIntyre grab or boxcore and elutriated over a 500um sieve. Elutriated material was then sorted back at Geoscience Australia, and all polychaetes were removed and sent to the Museum and Art Gallery of the Northern Territory (MAGNT). Chris Glasby and Charlotte Watson taxonomically identified each animal to the lowest possible level, differentiating species using established names and operational taxonomic units (OTUs). Specimens are lodged at the MAGNT. See relevant post-survey reports (GA Records 2010/09, 2011/08, 2012/66 and 2013/38) for further details on survey methods and specimen acquisition. This dataset is published with the permission of the CEO, Geoscience Australia. <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

<p>The dataset measures the long-term seasonal means 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 means 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. <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

<p>Australia has established a network of 58 marine parks within Commonwealth waters covering a total of 3.3 million square kilometres, or 40 per cent of our exclusive economic zone (excluding Australian Antarctic Territory). These parks span a range of settings, from near coastal and shelf habitats to abyssal plains. Parks Australia manages the park network through management plans that came into effect for all parks on 1 July 2018. Geoscience Australia is contributing to their management by collating and interpreting existing environmental data, and through the collection of new marine data. “Eco-narrative” documents are being developed for those parks, where sufficient information is available, delivering collations and interpretations of seafloor geomorphology, oceanography and ecology. Many of these interpretations rely on bathymetric grids and their derived products, including those in this data release. <p>Bathymetry grids: <p>The bathymetry of the marine parks was created by compiling and processing Geoscience Australia’s bathymetry data holding gridded at the optimum resolution depending of the vessel’s sonar system. <p>The bathymetry of the park is illustrated by a panchromatic geotiff image, developed by combining the bathymetric data with a hillshade image. <p> Morphological Surfaces: <p>Geoscience Australia has developed a new marine seafloor classification scheme, which uses the two-part seafloor mapping morphology approach of Dove et al (2016). This new scheme is semi-hierarchical and the first step divides the slope of the seafloor into three Morphological Surface categories (Plain, <2°; Slope, 2-10°; Escarpment, >10°). <p>Dove, D., Bradwell, T., Carter, G., Cotterill, C., Gafeira, J., Green, S., Krabbendam, M., Mellet, C., Stevenson, A., Stewart, H., Westhead, K., Scott, G., Guinan, J., Judge, M. Monteys, X., Elvenes, S., Baeten, N., Dolan, M., Thorsnes, T., Bjarnadóttir, L., Ottesen, D. (2016). Seabed geomorphology: a twopart classification system. British Geological Survey, Open Report OR/16/001. 13 pages. <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.<p><p>This dataset is not to be used for navigational purposes.

Australia has established a network of 58 marine parks within Commonwealth waters covering a total of 3.3 million square kilometres, or 40 per cent of our exclusive economic zone (excluding Australian Antarctic Territory). These parks span a range of settings, from near coastal and shelf habitats to abyssal plains. Parks Australia manages the park network through management plans that came into effect for all parks on 1 July 2018. Geoscience Australia is contributing to their management by collating and interpreting existing environmental data, and through the collection of new data. This includes compiling existing bathymetry datasets for select marine parks. This dataset includes a compilation of multibeam sonar bathymetry (gridded to 100 m spatial resolution) for Bremer Marine Park, in the South-west Marine Park Network. The park incorporates Bremer Canyon and adjacent smaller canyons that incise the continental slope and outer shelf. This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.<p><p>This dataset is not to be used for navigational purposes.

<p>The dataset indicates the long-term overall primary productivity hotspots of ocean surface waters. They are derived from MODIS (aqua) images using NASA's SeaDAS image processing software. The monthly chlorophyll a images between July 2002 and August 2014 are used to identify the overall primary productivity hotspots. The extent of the dataset covers the entire Australian EEZ and surrounding waters (including the southern ocean). The value (between 0 and 1.0) of the dataset represents the likelihood of the location being a primary productivity hotspot. <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

<p>This dataset measures the mean decadal warming rates of the sea surface temperature (SST) in 58 Australian Marine Parks (with the exception of the Heard Island and McDonald Islands Marine Park) over the past 25 years (1992 to 2016). They are derived from the Sea Surface Temperature Atlas of the Australian Regional Seas (SSTAARS). The field of “trend_d” represents the linear SST trend for March 1992 to December 2016. The unit of the warming rates is Celsius degree/per decade. <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

<p>Australia has established a network of 58 marine parks within Commonwealth waters covering a total of 3.3 million square kilometres, or 40 per cent of our exclusive economic zone (excluding Australian Antarctic Territory). These parks span a range of settings, from near coastal and shelf habitats to abyssal plains. Parks Australia manages the park network through management plans that came into effect for all parks on 1 July 2018. Geoscience Australia is contributing to their management by collating and interpreting existing environmental data, and through the collection of new marine data. “Eco-narrative” documents are being developed for those parks, where sufficient information is available, delivering collations and interpretations of seafloor geomorphology, oceanography and ecology. Many of these interpretations rely on bathymetric grids and their derived products, including those in this data release. <p>Bathymetry grids <p>The bathymetry of the marine parks was created by compiling and processing Geoscience Australia’s bathymetry data holding gridded at the optimum resolution depending of the vessel’s sonar system. <p>The bathymetry of the park is illustrated by a panchromatic geotiff image, developed by combining the bathymetric data with a hillshade image. <p> Morphological Surfaces <p>Geoscience Australia has developed a new marine seafloor classification scheme, which uses the two-part seafloor mapping morphology approach of Dove et al (2016). This new scheme is semi-hierarchical and the first step divides the slope of the seafloor into three Morphological Surface categories (Plain, <2°; Slope, 2-10°; Escarpment, >10°). <p>Dove, D., Bradwell, T., Carter, G., Cotterill, C., Gafeira, J., Green, S., Krabbendam, M., Mellet, C., Stevenson, A., Stewart, H., Westhead, K., Scott, G., Guinan, J., Judge, M. Monteys, X., Elvenes, S., Baeten, N., Dolan, M., Thorsnes, T., Bjarnadóttir, L., Ottesen, D. (2016). Seabed geomorphology: a twopart classification system. British Geological Survey, Open Report OR/16/001. 13 pages. <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.<p><p>This dataset is not to be used for navigational purposes.