Data

Australian Terrestrial and Coastal Marine (Blue) Carbon Stocks

Terrestrial Ecosystem Research Network
Viscarra Rossel, Raphael A. ; Walden, Lewis
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:doi10.25901/6kn5-1020&rft.title=Australian Terrestrial and Coastal Marine (Blue) Carbon Stocks&rft.identifier=10.25901/6kn5-1020&rft.publisher=Terrestrial Ecosystem Research Network&rft.description=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 cm soil layer, terrestrial ecosystems hold 27.6 Gt (19.6-39.0 Gt), and BCE 0.35 Gt (0.20-0.62 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.The data was produced using a compilation of various regional datasets. They were analysed and harmonised using statistical methods that are described in the publication that describes the research - Walden et al. (2023) in Communications Earth & Environment.Progress Code: completedMaintenance and Update Frequency: notPlanned&rft.creator=Viscarra Rossel, Raphael A. &rft.creator=Walden, Lewis &rft.date=2024&rft.edition=0.01&rft.coverage=All of Australia, including terrestrial and coastal marine (mangroves, tidal marshes, seagrasses) ecosystems.&rft.coverage=northlimit=-7.648005; southlimit=-45.52084; westlimit=105.6359; eastLimit=161.6151; projection=EPSG:3577&rft_rights=Creative Commons Attribution 4.0 International Licence http://creativecommons.org/licenses/by/4.0&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 />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&rft_rights=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=SOIL ORGANIC CARBON (SOC)&rft_subject=SOILS&rft_subject=CARBON&rft_subject=Soil chemistry and soil carbon sequestration (excl. carbon sequestration science)&rft_subject=Carbon Sequestration Science&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=SOIL SCIENCES&rft_subject=Machine learning&rft_subject=Spatial data and applications&rft_subject=Spatial statistics&rft_subject=Agricultural Spatial Analysis and Modelling&rft_subject=AGRICULTURAL AND VETERINARY SCIENCES&rft_subject=AGRICULTURE, LAND AND FARM MANAGEMENT&rft_subject=soil carbon content (metric tonne per hectare)&rft_subject=metric tonne per hectare&rft_subject=30 meters - < 100 meters&rft_subject=< 1 meter&rft_subject=one off&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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unclassified

Contact Information

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

esupport@tern.org.au

Brief description

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 cm soil layer, terrestrial ecosystems hold 27.6 Gt (19.6-39.0 Gt), and BCE 0.35 Gt (0.20-0.62 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.

Lineage

The data was produced using a compilation of various regional datasets. They were analysed and harmonised using statistical methods that are described in the publication that describes the research - Walden et al. (2023) in Communications Earth & Environment.

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.
Authors thank the Australian Government for funding this research via grant ACSRIV000077. We thank all co-authors and their contributions, and the many colleagues who contributed to the collection of soil samples and data used in this research. This work is also supported by the use of (i) Terrestrial Ecosystem Research Network (TERN) infrastructure, which is enabled by the Australian Government’s National Collaborative Research Infrastructure Strategy (NCRIS), and (ii) computational resources in the Pawsey Supercomputing Centre, which is funded by the Australian Government and the Government of Western Australia.
Purpose
A fine spatial resolution, spatially explicit dataset on the soil organic carbon stocks (t/ha) in Australia's terrestrial and coastal marine (or blue carbon: mangroves, tidal marshes, seagrasses) ecosystems. The data provides a consistently-derived and up-to-date baseline of Australia's 0-30 cm soil carbon stocks. Can be used by land managers, researchers, and policy-makers.
Data Quality Information

Data Quality Assessment Result
local : Quality Result
Multi-scale spatial machine learning. <br>The modelling and validation accuracies are as follows.</br> <br>Model training:<ul style="list-style-type: disc;"> <li>Root mean squared error (RMSE) = 0.20 (min, max: 0.18 - 0.22) - log<sub>10</sub> t/ha</li> <li>Lin's concordance correlation = 0.76 (0.72-0.8).</li></ul> </br><br> Model validation:<ul style="list-style-type: disc;"> <li>RMSE = 0.20 (0.19-0.21) - log<sub>10</sub> t/ha</li> <li>Mean error (ME) = -0.01 (-0.03 - -0.004) </li> <li>Standard deviation of error (SDE) = 0.20*(0.19-0.21)</li> <li>Lin's concordance correlation = 0.76 (0.72-0.8).</li></ul>

Created: 2022-12-01

Issued: 2024-09-24

Modified: 2024-09-24

Data time period: 2005-01-01 to 2015-01-01

This dataset is part of a larger collection

Click to explore relationships graph

161.6151,-7.64801 161.6151,-45.52084 105.6359,-45.52084 105.6359,-7.64801 161.6151,-7.64801

133.6255,-26.5844225

text: All of Australia, including terrestrial and coastal marine (mangroves, tidal marshes, seagrasses) ecosystems.