<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.

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 90&nbsp;m resolution.

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.

Vadose zone soil moisture was collected at the Avon River Critical Zone Observatory (CZO). The measurements were taken at four different depths: 0.6, 1.2, 1.8, 2.4 metres.

This dataset contains soil microbial and genomic analysis files of 9 soil samples from each of three plots at Fletcherview, Northern Queensland (NQ) processed by the <a href='https://agrf.org/'>Australian Genome Research Facility Ltd (AGRF) </a>. The files are available as compressed FastQ formatted sequence files.<br> For the nine Far North Queensland (FNQ) new plots (3 plots in Fletcherview and six plots at Wambiana), soil sampling additional to that done as component of plot installation by TERN have been undertaken. This is aligned with potential future exploratory work on soil eDNA proposed for WA. The protocol is a modified version of the <a href="https://doi.org/10.1186/s13742-016-0126-5">BASE sampling protocol</a>, combined with soil sampling as per <a href="https://www.tern.org.au/wp-content/uploads/TERN-Rangelands-Survey-Protocols-Manual_web.pdf">White et al. (2012)</a>. <br> DNA extracted from the soil samples and Metagenomics 10Gbp (giga base pairs) bundle as per AGRF protocol.

This is Version 1 of the Australian 15 Bar Lower Limit Volumetric Water Content (L15) product of the Soil and Landscape Grid of Australia.<br><br> The map gives a modelled estimate of the spatial distribution of 15 Bar Lower Limit Volumetric Water Content in soils across Australia.<br><br> 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 <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf">GlobalSoilMap.net project</a>. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90&nbsp;m pixels).<br><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: 15 Bar Lower Limit Volumetric Water Content;</li> <li>Units: percent;</li> <li>Period (temporal coverage; approximately): 1950-2021;</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>Data license : Creative Commons Attribution 4.0 (CC BY);</li> <li>Target data standard: GlobalSoilMap specifications;</li> <li>Format: Cloud Optimised GeoTIFF;</li></ul>

This map gives a modelled estimate of the spatial distribution of Pedogenon soil classes across Australia.<br><br> Pedogenon mapping is a method for stratifying the landscape (similar to soil-landscape units), which can be used to assess past soil change with a space-for-time substitution approach.<br><br> Pedogenon classes are a conceptual taxa that aim to define groups of homogeneous environmental variables. These groups are created applying unsupervised classification to a set of state variables, proxies of the soil-forming factors for a given reference time. The assumption is that the soil-forming processes within these classes (i.e., pedogenons) have been relatively similar over pedogenetic time and thus have developed soils with similar properties. Pedogenon classes can afterwards be divided into subclasses along a gradient from less (i.e., remnant pedogenons) to more anthropogenic pressure on soils (i.e., pedophenons), in an analogous way to the concept of genoform and phenoform (Rossiter and Bouma, 2018). The assessment of changes in soil condition can be done with a space for time substitution within and across pedogenon classes. The conceptualization and methodology for pedogenon mapping and using the classes as basis to assess changes in soil condition are explained with more detail in two publications (Román Dobarco et al., 2021a; Román Dobarco et al., 2021b).<br><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>Period (temporal coverage; approximately): 1950-2022;</li> <li>Spatial resolution: 3 arc seconds (approx 90&nbsp;m);</li> <li>Number of pixels with coverage per layer: 2007M (49200 * 40800);</li> <li>Data license : Creative Commons Attribution 4.0 (CC BY);</li> <li>Target data standard: GlobalSoilMap specifications;</li> <li>Format: Cloud Optimised GeoTIFF;</li></ul>

This is Version 2 of the Australian Soil Clay Content product of the Soil and Landscape Grid of Australia.<br><br> It supersedes the Release 1 product that can be found at <a href="https://doi.org/10.4225/08/546EEE35164BF">https://doi.org/10.4225/08/546EEE35164BF</a>.<br></br> The map gives a modelled estimate of the spatial distribution of clay 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: 2&nbsp;μm mass fraction of the less than 2&nbsp;mm soil material determined using the pipette method;</li> <li>Units: %;</li> <li>Period (temporal coverage; approximately): 1950-2021;</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>Data license : Creative Commons Attribution 4.0 (CC BY);</li> <li>Target data standard: GlobalSoilMap specifications;</li> <li>Format: Cloud Optimised GeoTIFF.</li></ul>

The map gives a modelled estimate (probability) of the spatial distribution of rock outcroppings across Australia.<br></br> This product was produced in the development of the updated soil thickness map of Australia, details of which are published in Malone and Searle (2020; https://doi.org/10.1016/j.geoderma.2020.114579). This product is the output from Model 1 of aforementioned paper and uses the Rock Properties database provided by Geoscience Australia which gives the locations of sampled rock outcrops across Australia (http://www.ga.gov.au/scientific-topics/disciplines/geophysics/rock-properties). Filtering this dataset resulted in 14616 rock outcrop locations within areas where relief >300 m. A machine learning model was used to find relationships between observed data and associated environmental covariate data to inform the mapping of rock outcrop occurrence across Australia.<br></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: Probability of rock outcrops;</li> <li>Units: 0-1;</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: 1;</li> <li>Number of pixels with coverage per layer: 2007M (49200 * 40800);</li> <li>Data license : Creative Commons Attribution 4.0 (CC BY);</li> <li>Target data standard: GlobalSoilMap specifications;</li> <li>Format: Cloud Optimised GeoTIFF;</li></ul>

This is Version 1 of the Soil Bacteria and Fungi Beta Diversity product of the Soil and Landscape Grid of Australia.<br></br> The Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. These products provide estimates of the Beta Diversity of soil fungi and bacteria. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90&nbsp;m pixels).<br></br> These maps are generated using Digital Soil Mapping (DSM) methods. Detailed information about the Australian DSM an be found at <a href="https://aussoilsdsm.esoil.io/home">AusSoilsDSM</a><br /><br /> <ul style="list-style-type: disc;"><li>Attribute Definition: Soil Bacteria and Fungi Beta Diversity (Units: NA);</li> <li>Period (temporal coverage; approximately): 1950-2022;</li> <li>Spatial resolution: 3 arc seconds (approximately 90&nbsp;m);</li> <li>Total number of gridded maps for this attribute: 6;</li> </li>Number of pixels with coverage per layer: 2007M (49200 * 40800);</li> <li>Total size before compression: about 8GB;</li> <li>Total size after compression: about 4GB;</li> <li>Format: Cloud Optimised GeoTIFF.</li></ul>