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geoscientificInformation

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    <p>Soil is a huge carbon (C) reservoir, but where and how much extra C can be stored is unknown. Here, using 5089 observations, we estimated that the uppermost 30&nbsp;cm of Australian soil holds 13&nbsp;Gt (10–18&nbsp;Gt) of mineral-associated organic carbon (MAOC). Using a frontier line analyses, described in Viscarra Rossel et al. (2023), we estimated the maximum amounts of MAOC that Australian soils could store in their current environments, and calculated the MAOC deficit, or C sequestration potential. We propagated the uncertainties from the frontier fitting and mapped the estimates of these values over Australia using machine learning and kriging with external drift (KED). The maps show regions where the soil is more in MAOC deficit and has greater sequestration potential. The modelling shows that the variation over the whole continent is determined mainly by climate, linked to vegetation, and soil mineralogy. We find that the MAOC deficit in Australian soil is 40&nbsp;Gt (25–60&nbsp;Gt). The deficit in the vast rangelands is 20.84&nbsp;Gt (13.97–29.70&nbsp;Gt) and the deficit in cropping soil is 1.63&nbsp;Gt (1.12–2.32&nbsp;Gt). Our findings suggest that the C sequestration potential of Australian soil is limited by climate.

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    These datasets consist of soil maps generated to assess baselines, drivers and trends for soil health and stability within the NSW Regional Forest Agreement (RFA) regions. <br> The maps are organised into empirical soil maps, digital soil maps, and data cube maps. <br> Empirical soil maps consists of four products. Maps include topsoil pH, carbon, Emerson Aggregate Stability and Soil Profile Quality Confidence. Each map consists of 2,162 units. Maps were generated using the most representative soil profile for each unit available within the Soil and Land Information System (SALIS). The 2008 woody vegetation coverage was used as baseline. Maps reflect values when the sampling occurred with temporal changes not being accounted for. Locations with missing or of poor quality data are identified, providing a confidence rating map as part of the evaluation process.<br> Digital soil maps include map products of key soil condition indicators covering the Regional Forest Agreement regions of eastern NSW. Raster maps of key soil indicators, such as soil carbon, pH, bulk density, hillslope erosion and others, were created at 100 m resolution. For each key soil indicator, maps include baseline (approximately 2008) levels as well as trends of change resulting from different human and natural disturbances such as forest harvesting, uncontrolled stock grazing, climate change and bush fire. <br> Data cube maps include time series of soil organic carbon (SOC) between January 1990 and December 2020 for the Regional Forest Agreement regions of eastern NSW. Products provide estimates of SOC concentrations and associated trends through time. Modelling was carried out using a data cube platform incorporating machine learning space-time framework and geospatial technologies. Important covariates required to drive this spatio-temporal modelling were identified using the Recursive Feature Elimination algorithm (RFE). <br> A web mapping application on the NSW Spatial Collaboration Portal depicts these datasets. Access the webapp through the link below:<br> https://portal.spatial.nsw.gov.au/portal/home/item.html?id=af9c71935f024f4a8f64cb39f5eba007

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    This dataset consists of bare earth covariates designed to indicate the presence of iron oxides, ferrous minerals, quartz/carbonate and hydroxyl minerals, to support soil and lithological modelling across Australia. <br> Bare earth layers (bands) represent the weighted geometric median of pixel values derived from a 30 year time-series of Landsat 5, 7 and 8 imagery converted to at-surface-reflectance, using the latest techniques to reduce the influence of vegetation (see Publications: Roberts, Wilford & Ghattas 2019). Bare earth layers are (BLUE (0.452 - 0.512), GREEN (0.533 - 0.590), RED, (0.636 - 0.673) NIR (0.851 - 0.879), SWIR1 (1.566 - 1.651) and SWIR2 (2.107 - 2.294) wavelength regions. <br> Covariates are then derived from principal components analysis and ratios of specific bare earth layers to target identification of elements of surface geochemistry. Layers are available as mosaics or tiles in 30 or 90 metre resolution.<br>

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    This dataset contains predictions of the aboveground biomass density (AGBD) for Australia for 2020. Data were generated by the Global Ecosystem Dynamics Investigation (GEDI) NASA mission, which used a full-waveform LIDAR attached to the International Space Station to provide the first global, high-resolution observations of forest vertical structure. Data include both Level 4A (~25&nbsp;m footprints) and Gridded Level 4B (1&nbsp;km x 1&nbsp;km) Version 2. The Australian portion of the data was extracted from the original global datasets <a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2056">GEDI L4A Footprint Level Aboveground Biomass Density</a> and <a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2299">GEDI L4B Gridded Aboveground Biomass Density</a>.

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    <p>This database contains occurrence data for vertebrates across the Australian Wet Tropics. Species occurrence point data has been collected during field intensive surveys using a variety of sampling methods as well as from the literature and institutional databases. The records are divided into two tables: Misc_records and STD_records. The first contains records collated opportunistically, as well as records collected from literature. The latter is a collection of standardized surveys conducted by Steve E. Williams (JCU). </p> <p> All occurrences were vetted for positional and taxonomic accuracy, and for sensitivity at the state and national levels. Sensitive species records are withheld or have their location generalised following sensitive species rules for processing these records. </p>

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    We used Digital Soil Mapping (DSM) technologies combined with the real-time collations of soil attribute data from TERN's recently developed Soil Data Federation System, to produce a map of Australian Soil Classification Soil Order classes with quantified estimates of mapping reliability at a 90m resolution.

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    The spatial layers in this dataset detail forest cover extent over NSW. They have been created for the NSW Natural Resources Commission to detail historic baseline and trends of forest cover extent coverage for NSW for all land tenures, including all RFAs and IFOAs. <br> These have been based off the National Greenhouse Gas Inventory (NGGI) National Carbon Accounting System (NCAS) National Forest and Sparse Woody Vegetation Data grids (ABARES, 2021). These base grids are Landsat in origin and have a resolution of 25m. <br> These base grids have been processed through a series of land use and vegetation type exclusion masking and a through a fuzzy-logic based certainty analysis to reflect a forest cover extent coverage for NSW that is reflective of past and current coverage. <br> These grids cover the years from 1995 to 2020. The year gaps are triennial or biennial data layers from 1995 to 2004. 1996,1997,1999,2001,2003 years missing as these were not assessed in original applied database. From 2004 to 2020 data layers become annualised.<br> Read more about the project on the Natural Resources Commission website:<br> https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1<br> This dataset supersedes "NSW Forest Monitoring and Improvement Program RFA Historic Forest Cover Extent – 1995 to 2019". https://portal.tern.org.au/metadata/23696.

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    This is Version 2 of the Australian Available Volumetric Water Capacity (AWC) product of the Soil and Landscape Grid of Australia.<br></br> The map gives a modelled estimate of the spatial distribution of AWC soil hydraulic property in soils across Australia.<br></br> <p>The Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5&nbsp;cm, 5-15&nbsp;cm, 15-30&nbsp;cm, 30-60&nbsp;cm, 60-100&nbsp;cm and 100-200&nbsp;cm. These depths are consistent with the specifications of the GlobalSoilMap.net project - <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf">GlobalSoilMaps</a>. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90&nbsp;m pixels).<br> Detailed information about the Soil and Landscape Grid of Australia can be found at - <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html">SLGA</a><br /><br /> <ul style="list-style-type: disc;"><li>Attribute Definition: Available Volumetric Water Capacity (Units: percent);</li> <li>Period (temporal coverage; approximately): 1950-2021;</li> <li>Spatial resolution: 3 arc seconds (approx. 90m);</li> <li>Total number of gridded maps for this attribute: 18;</li> <li>Number of pixels with coverage per layer: 2007M (49200 * 40800);</li> <li>Target data standard: GlobalSoilMap specifications;</li> <li>Format: Cloud Optimised GeoTIFF</li></ul>

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    This is Version 1 of the Australian Soil Cation Exchange Capacity product of the Soil and Landscape Grid of Australia.<br></br> The map gives a modelled estimate of the spatial distribution of cation exchange capacity in soils across Australia.<br></br> <p>The Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5&nbsp;cm, 5-15&nbsp;cm, 15-30&nbsp;cm, 30-60&nbsp;cm, 60-100&nbsp;cm and 100-200&nbsp;cm. These depths are consistent with the specifications of the GlobalSoilMap.net project - <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf">GlobalSoilMaps</a>. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90&nbsp;m pixels).</p> Detailed information about the Soil and Landscape Grid of Australia can be found at - <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html">SLGA</a><br /><br /> <ul style="list-style-type: disc;"><li>Attribute Definition: Cation Exchange Capacity (Units: meq/100g);</li> <li>Period (temporal coverage; approximately): 1970-2022;</li> <li>Spatial resolution: 3 arc seconds (approx 90&nbsp;m);</li> <li>Total number of gridded maps for this attribute: 18;</li> <li>Number of pixels with coverage per layer: 2007M (49200 * 40800);</li> <li>Target data standard: GlobalSoilMap specifications;</li> <li>Format: Cloud Optimised GeoTIFF.</li>

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    The soil in terrestrial and blue carbon ecosystems (BCE; mangroves, tidal marshes, seagrasses) is a significant carbon (C) sink. National assessments of C inventories are needed to protect them and aid nature-based strategies to sequester atmospheric carbon dioxide. We harmonised measurements from Australia's terrestrial and BCE and, using consistent multi-scale spatial machine learning, unravelled the drivers of soil organic carbon (SOC) variation and digitally mapped their stocks. The modelling shows that climate and vegetation are continentally the primary drivers of SOC variation. But the underlying regional drivers are ecosystem type, terrain, clay content, mineralogy, and nutrients. The digital soil maps indicate that in the 0-30&nbsp;cm soil layer, terrestrial ecosystems hold 27.6&nbsp;Gt (19.6-39.0&nbsp;Gt), and BCE 0.35&nbsp;Gt (0.20-0.62&nbsp;Gt). Tall open eucalypt and mangrove forests have the largest mean SOC per unit area. Eucalypt woodlands and hummock grassland, which occupy vast areas, store the largest total SOC stock. These ecosystems constitute important regions for conservation, emissions avoidance, and preservation because they also provide additional co-benefits.