Data

Soil and Landscape Grid National Soil Attribute Maps - Soil Organic Carbon Fractions (3" resolution) - Release 1

Terrestrial Ecosystem Research Network
Dobarco, Mercedes ; Wadoux, Alexandre ; Malone, Brendan ; Minasny, Budiman ; McBratney, Alex ; Searle, Ross
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/nf8v-p205&rft.title=Soil and Landscape Grid National Soil Attribute Maps - Soil Organic Carbon Fractions (3 resolution) - Release 1&rft.identifier=10.25919/nf8v-p205&rft.publisher=Terrestrial Ecosystem Research Network&rft.description=This is Version 1 of the Soil Organic Carbon Fractions product of the Soil and Landscape Grid of Australia. The Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. This product contains six digital soil attribute maps for each of three depth intervals, 0-5 cm, 5-15 cm, 15-30 cm. These depths are consistent with the specifications of the GlobalSoilMap.net project - GlobalSoilMaps. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). These maps are generated using Digital Soil Mapping methods. Attribute Definition: Soil Organic Carbon Fractions : mineral-associated organic carbon (MAOC), particulate organic carbon (POC) and pyrogenic organic carbon (PyOC) (Units: Various); Period (temporal coverage; approximately): 1950-2022; Spatial resolution: 3 arc seconds (approximately 90 m); Total number of gridded maps for this attribute: 18; Number of pixels with coverage per layer: 2007M (49200 * 40800); Total size before compression: about 8GB; Total size after compression: about 4GB; Format: Cloud Optimised GeoTIFF.Soil organic carbon (SOC) is the largest terrestrial carbon pool. SOC is composed of a continuum set of compounds with different chemical composition, origin and susceptibilities to decomposition, that are commonly separated into pools characterised by different responses to anthropogenic and environmental disturbance. Here we map the contribution of three SOC fractions to the total SOC content of Australia’s soils. The three SOC fractions: mineral-associated organic carbon (MAOC), particulate organic carbon (POC) and pyrogenic organic carbon (PyOC) represent SOC composition with distinct turnover rates, chemistry, and pathway formation. Data for MAOC, POC, and PyOC were obtained with near- and mid-infrared spectral models calibrated with measured SOC fractions. We transformed the data using an isometric log-ratio transformation (ilr) to account for the closed compositional nature of SOC fractions. The resulting, back-transformed ilr components were mapped across Australia. SOC fraction stocks for the 0-30 cm were derived with maps of total organic carbon concentration, bulk density, coarse fragments and soil thickness. Mapping was done by quantile regression forest fitted with the ilr transformed data and a large set of environmental variables as predictors. The resulting maps along with the quantified uncertainty show the unique spatial pattern of SOC fractions in Australia. MAOC dominated the total SOC with an average of 59% ±17.5%, whereas 28% ± 17.5% was PyOC and 13% ± 11.1% was POC. The allocation of TOC into the MAOC fractions increased with depth. SOC vulnerability (i.e., POC/[MAOC + PyOC]) was greater in areas with Mediterranean and temperate climate. TOC and the distribution among fractions were the most influential variables on SOC fraction uncertainty. Further, the diversity of climatic and pedological conditions suggests that different mechanisms will control SOC stabilisation and dynamics across the continent, as shown by the model covariates importance metric. We estimated the total SOC stocks (0-30 cm) to be 12.7 Pg MAOC, 2 Pg POC and 5.1 Pg PyOC, which is consistent with previous estimates. The maps of SOC fractions and their stocks can be used for modelling SOC dynamics and forecasting changes in SOC stocks as response to land use change, management, and climate change. Code - https://github.com/AusSoilsDSM/SLGA Observation data - https://esoil.io/TERNLandscapes/Public/Pages/SoilDataFederator/SoilDataFederator.html> Covariate rasters - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/GetData-COGSDataStore.htmlProgress Code: completedMaintenance and Update Frequency: notPlanned&rft.creator=Dobarco, Mercedes &rft.creator=Wadoux, Alexandre &rft.creator=Malone, Brendan &rft.creator=Minasny, Budiman &rft.creator=McBratney, Alex &rft.creator=Searle, Ross &rft.date=2023&rft.edition=1.0&rft.relation=https://doi.org/10.1016/j.geoderma.2020.114579&rft.coverage=northlimit=-10.000416666; southlimit=-44.000416667; westlimit=112.999583333; eastLimit=153.999583334; projection=EPSG:4326&rft_rights=Creative Commons Attribution 4.0 International Licence http://creativecommons.org/licenses/by/4.0&rft_rights=&rft_rights=TERN services are provided on an “as-is” and “as available” basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure.<br /><br />Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN.<br /><br />Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting<br /><br />Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.&rft_subject=environment&rft_subject=geoscientificInformation&rft_subject=SOILS&rft_subject=AGRICULTURE&rft_subject=EARTH SCIENCE&rft_subject=LAND SURFACE&rft_subject=Agricultural Land Management&rft_subject=AGRICULTURAL AND VETERINARY SCIENCES&rft_subject=AGRICULTURE, LAND AND FARM MANAGEMENT&rft_subject=Agricultural Spatial Analysis and Modelling&rft_subject=SOIL SCIENCES&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=Soil Sciences not elsewhere classified&rft_subject=soil carbon content (Percent)&rft_subject=Percent&rft_subject=30 meters - < 100 meters&rft_subject=Decadal&rft_subject=TERN_Soils&rft_subject=TERN_Soils_DSM&rft_subject=Soil&rft_subject=Raster&rft_subject=Attributes&rft_subject=Continental&rft_subject=Australia&rft_subject=DSM&rft_subject=Global Soil Map&rft_subject=spatial modelling&rft_subject=3-dimensional soil mapping&rft_subject=spatial uncertainty&rft_subject=Soil Maps&rft_subject=Digital Soil Mapping&rft_subject=SLGA&rft_subject=Soil Organic Carbon Fractions&rft.type=dataset&rft.language=English Access the data

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Creative Commons Attribution 4.0 International Licence
http://creativecommons.org/licenses/by/4.0

TERN services are provided on an “as-is” and “as available” basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure.

Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN.

Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting

Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.

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Terrestrial Ecosystem Research Network
Building 1019, 80 Meiers Rd
QLD 4068
Australia
Ph: +61 7 3365 9097

esupport@tern.org.au

Brief description

This is Version 1 of the Soil Organic Carbon Fractions product of the Soil and Landscape Grid of Australia.

The Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. This product contains six digital soil attribute maps for each of three depth intervals, 0-5 cm, 5-15 cm, 15-30 cm. These depths are consistent with the specifications of the GlobalSoilMap.net project - GlobalSoilMaps. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).

These maps are generated using Digital Soil Mapping methods.

  • Attribute Definition: Soil Organic Carbon Fractions : mineral-associated organic carbon (MAOC), particulate organic carbon (POC) and pyrogenic organic carbon (PyOC) (Units: Various);
  • Period (temporal coverage; approximately): 1950-2022;
  • Spatial resolution: 3 arc seconds (approximately 90 m);
  • Total number of gridded maps for this attribute: 18;
  • Number of pixels with coverage per layer: 2007M (49200 * 40800);
  • Total size before compression: about 8GB;
  • Total size after compression: about 4GB;
  • Format: Cloud Optimised GeoTIFF.

Lineage

Soil organic carbon (SOC) is the largest terrestrial carbon pool. SOC is composed of a continuum set of compounds with different chemical composition, origin and susceptibilities to decomposition, that are commonly separated into pools characterised by different responses to anthropogenic and environmental disturbance. Here we map the contribution of three SOC fractions to the total SOC content of Australia’s soils.

The three SOC fractions: mineral-associated organic carbon (MAOC), particulate organic carbon (POC) and pyrogenic organic carbon (PyOC) represent SOC composition with distinct turnover rates, chemistry, and pathway formation. Data for MAOC, POC, and PyOC were obtained with near- and mid-infrared spectral models calibrated with measured SOC fractions. We transformed the data using an isometric log-ratio transformation (ilr) to account for the closed compositional nature of SOC fractions. The resulting, back-transformed ilr components were mapped across Australia.

SOC fraction stocks for the 0-30 cm were derived with maps of total organic carbon concentration, bulk density, coarse fragments and soil thickness. Mapping was done by quantile regression forest fitted with the ilr transformed data and a large set of environmental variables as predictors.

The resulting maps along with the quantified uncertainty show the unique spatial pattern of SOC fractions in Australia. MAOC dominated the total SOC with an average of 59% ±17.5%, whereas 28% ± 17.5% was PyOC and 13% ± 11.1% was POC. The allocation of TOC into the MAOC fractions increased with depth. SOC vulnerability (i.e., POC/[MAOC + PyOC]) was greater in areas with Mediterranean and temperate climate. TOC and the distribution among fractions were the most influential variables on SOC fraction uncertainty. Further, the diversity of climatic and pedological conditions suggests that different mechanisms will control SOC stabilisation and dynamics across the continent, as shown by the model covariates importance metric. We estimated the total SOC stocks (0-30 cm) to be 12.7 Pg MAOC, 2 Pg POC and 5.1 Pg PyOC, which is consistent with previous estimates. The maps of SOC fractions and their stocks can be used for modelling SOC dynamics and forecasting changes in SOC stocks as response to land use change, management, and climate change.

Progress Code: completed
Maintenance and Update Frequency: notPlanned

Notes

Credit
We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.


The observed data used to produce this map was obtained from state and federal soil survey agencies. The work was supported by TERN. CSIRO maintains and makes the data available through the Australian Soil Resource Information System.
Purpose
The aim is to operate an open national capability that provides access to verified, science-quality land surface dynamics data and soils information layers, plus high-end data analytics tools that integrated with other TERN observations can meet the needs of ecosystem researchers and actionable information for policy makers and natural resource managers.

Created: 2022-10-06

Issued: 2023-11-23

Modified: 2024-09-23

Data time period: 1950-01-01 to 2022-10-06

This dataset is part of a larger collection

153.99958,-10.00042 153.99958,-44.00042 112.99958,-44.00042 112.99958,-10.00042 153.99958,-10.00042

133.4995833335,-27.0004166665