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Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T
<h2><strong>Sub-dataset: WPCT mean, 2020–2022</strong></h2> <h2>Disclaimer</h2> <p>This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk.</p> <h2>Description</h2> <p>This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics.</p> <p>This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset.</p> <p>This data set includes:</p> <ul> <li><strong>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals):</strong><br> This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m<sup>3</sup> (scaled 10x). </li> <li><strong>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals):</strong><br> This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li><strong>SOCD mean:</strong><br> <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li><strong>SOCD p025:</strong><br> <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li><strong>SOCD p975:</strong><br> <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li><strong>WPCT mean:</strong><br> <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li><strong>WPCT p025:</strong><br> <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li><strong>WPCT p975:</strong><br> <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li><strong>Time period:</strong> 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li><strong>Type of data:</strong> Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li><strong>How the data was collected or derived:</strong> The data was derived using machine learning models.</li> <li><strong>Statistical methods used:</strong> Quantile Random Forest</li> <li><strong>Limitations or exclusions in the data:</strong> The dataset does not include data for Svalbard. </li> <li><strong>Coordinate reference system:</strong> EPSG:3035</li> <li><strong>Bounding box (Xmin, Ymin, Xmax, Ymax):</strong> (900,000, 899,000, 7,401,000, 5,501,000)</li> <li><strong>Spatial resolution:</strong> 30m</li> <li><strong>Image size:</strong> 216,700P x 153,400L</li> <li><strong>File format:</strong> Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> <p>If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc)</p> <h3>Name convention</h3> <p>To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are:</p> <ol> <li><strong>generic variable name:</strong> oc = organic carbon</li> <li><strong>variable procedure combination:</strong> iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm<sup>3</sup> for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li><strong>Position in the probability distribution/variable type:</strong> m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li><strong>Spatial support:</strong> 30m</li> <li><strong>Depth reference:</strong> b0cm..20cm = depth range from 0 to 20cm</li> <li><strong>Time reference begin time:</strong> 20000101 = 2000-01-01</li> <li><strong>Time reference end time:</strong> 20041231 = 2004-12-31</li> <li><strong>Bounding box:</strong> eu = pan-Europe</li> <li><strong>EPSG code:</strong> epsg.3035</li> <li><strong>Version code:</strong> v20240804 = version from 2024-08-04</li> </ol>
Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T
<h2><strong>Sub-dataset: WPCT mean, 2016–2020</strong></h2> <h2>Disclaimer</h2> <p>This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk.</p> <h2>Description</h2> <p>This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics.</p> <p>This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset.</p> <p>This data set includes:</p> <ul> <li><strong>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals):</strong><br> This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m<sup>3</sup> (scaled 10x). </li> <li><strong>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals):</strong><br> This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li><strong>SOCD mean:</strong><br> <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li><strong>SOCD p025:</strong><br> <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li><strong>SOCD p975:</strong><br> <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li><strong>WPCT mean:</strong><br> <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li><strong>WPCT p025:</strong><br> <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li><strong>WPCT p975:</strong><br> <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li><strong>Time period:</strong> 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li><strong>Type of data:</strong> Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li><strong>How the data was collected or derived:</strong> The data was derived using machine learning models.</li> <li><strong>Statistical methods used:</strong> Quantile Random Forest</li> <li><strong>Limitations or exclusions in the data:</strong> The dataset does not include data for Svalbard. </li> <li><strong>Coordinate reference system:</strong> EPSG:3035</li> <li><strong>Bounding box (Xmin, Ymin, Xmax, Ymax):</strong> (900,000, 899,000, 7,401,000, 5,501,000)</li> <li><strong>Spatial resolution:</strong> 30m</li> <li><strong>Image size:</strong> 216,700P x 153,400L</li> <li><strong>File format:</strong> Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> <p>If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc)</p> <h3>Name convention</h3> <p>To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are:</p> <ol> <li><strong>generic variable name:</strong> oc = organic carbon</li> <li><strong>variable procedure combination:</strong> iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm<sup>3</sup> for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li><strong>Position in the probability distribution/variable type:</strong> m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li><strong>Spatial support:</strong> 30m</li> <li><strong>Depth reference:</strong> b0cm..20cm = depth range from 0 to 20cm</li> <li><strong>Time reference begin time:</strong> 20000101 = 2000-01-01</li> <li><strong>Time reference end time:</strong> 20041231 = 2004-12-31</li> <li><strong>Bounding box:</strong> eu = pan-Europe</li> <li><strong>EPSG code:</strong> epsg.3035</li> <li><strong>Version code:</strong> v20240804 = version from 2024-08-04</li> </ol>
Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T
<h2><strong>Sub-dataset: WPCT mean, 2008–2012</strong></h2> <h2>Disclaimer</h2> <p>This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk.</p> <h2>Description</h2> <p>This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics.</p> <p>This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset.</p> <p>This data set includes:</p> <ul> <li><strong>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals):</strong><br> This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m<sup>3</sup> (scaled 10x). </li> <li><strong>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals):</strong><br> This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li><strong>SOCD mean:</strong><br> <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li><strong>SOCD p025:</strong><br> <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li><strong>SOCD p975:</strong><br> <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li><strong>WPCT mean:</strong><br> <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li><strong>WPCT p025:</strong><br> <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li><strong>WPCT p975:</strong><br> <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li><strong>Time period:</strong> 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li><strong>Type of data:</strong> Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li><strong>How the data was collected or derived:</strong> The data was derived using machine learning models.</li> <li><strong>Statistical methods used:</strong> Quantile Random Forest</li> <li><strong>Limitations or exclusions in the data:</strong> The dataset does not include data for Svalbard. </li> <li><strong>Coordinate reference system:</strong> EPSG:3035</li> <li><strong>Bounding box (Xmin, Ymin, Xmax, Ymax):</strong> (900,000, 899,000, 7,401,000, 5,501,000)</li> <li><strong>Spatial resolution:</strong> 30m</li> <li><strong>Image size:</strong> 216,700P x 153,400L</li> <li><strong>File format:</strong> Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> <p>If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc)</p> <h3>Name convention</h3> <p>To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are:</p> <ol> <li><strong>generic variable name:</strong> oc = organic carbon</li> <li><strong>variable procedure combination:</strong> iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm<sup>3</sup> for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li><strong>Position in the probability distribution/variable type:</strong> m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li><strong>Spatial support:</strong> 30m</li> <li><strong>Depth reference:</strong> b0cm..20cm = depth range from 0 to 20cm</li> <li><strong>Time reference begin time:</strong> 20000101 = 2000-01-01</li> <li><strong>Time reference end time:</strong> 20041231 = 2004-12-31</li> <li><strong>Bounding box:</strong> eu = pan-Europe</li> <li><strong>EPSG code:</strong> epsg.3035</li> <li><strong>Version code:</strong> v20240804 = version from 2024-08-04</li> </ol>
Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T
<h2><strong>Sub-dataset: WPCT mean, 2004–2008</strong></h2> <h2>Disclaimer</h2> <p>This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk.</p> <h2>Description</h2> <p>This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics.</p> <p>This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset.</p> <p>This data set includes:</p> <ul> <li><strong>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals):</strong><br> This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m<sup>3</sup> (scaled 10x). </li> <li><strong>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals):</strong><br> This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li><strong>SOCD mean:</strong><br> <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li><strong>SOCD p025:</strong><br> <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li><strong>SOCD p975:</strong><br> <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li><strong>WPCT mean:</strong><br> <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li><strong>WPCT p025:</strong><br> <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li><strong>WPCT p975:</strong><br> <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li><strong>Time period:</strong> 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li><strong>Type of data:</strong> Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li><strong>How the data was collected or derived:</strong> The data was derived using machine learning models.</li> <li><strong>Statistical methods used:</strong> Quantile Random Forest</li> <li><strong>Limitations or exclusions in the data:</strong> The dataset does not include data for Svalbard. </li> <li><strong>Coordinate reference system:</strong> EPSG:3035</li> <li><strong>Bounding box (Xmin, Ymin, Xmax, Ymax):</strong> (900,000, 899,000, 7,401,000, 5,501,000)</li> <li><strong>Spatial resolution:</strong> 30m</li> <li><strong>Image size:</strong> 216,700P x 153,400L</li> <li><strong>File format:</strong> Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> <p>If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc)</p> <h3>Name convention</h3> <p>To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are:</p> <ol> <li><strong>generic variable name:</strong> oc = organic carbon</li> <li><strong>variable procedure combination:</strong> iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm<sup>3</sup> for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li><strong>Position in the probability distribution/variable type:</strong> m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li><strong>Spatial support:</strong> 30m</li> <li><strong>Depth reference:</strong> b0cm..20cm = depth range from 0 to 20cm</li> <li><strong>Time reference begin time:</strong> 20000101 = 2000-01-01</li> <li><strong>Time reference end time:</strong> 20041231 = 2004-12-31</li> <li><strong>Bounding box:</strong> eu = pan-Europe</li> <li><strong>EPSG code:</strong> epsg.3035</li> <li><strong>Version code:</strong> v20240804 = version from 2024-08-04</li> </ol>
Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T
<h2><strong>Sub-dataset: WPCT mean, 2012–2016</strong></h2> <h2>Disclaimer</h2> <p>This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk.</p> <h2>Description</h2> <p>This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics.</p> <p>This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset.</p> <p>This data set includes:</p> <ul> <li><strong>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals):</strong><br> This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m<sup>3</sup> (scaled 10x). </li> <li><strong>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals):</strong><br> This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li><strong>SOCD mean:</strong><br> <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li><strong>SOCD p025:</strong><br> <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li><strong>SOCD p975:</strong><br> <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li><strong>WPCT mean:</strong><br> <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li><strong>WPCT p025:</strong><br> <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li><strong>WPCT p975:</strong><br> <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li><strong>Time period:</strong> 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li><strong>Type of data:</strong> Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li><strong>How the data was collected or derived:</strong> The data was derived using machine learning models.</li> <li><strong>Statistical methods used:</strong> Quantile Random Forest</li> <li><strong>Limitations or exclusions in the data:</strong> The dataset does not include data for Svalbard. </li> <li><strong>Coordinate reference system:</strong> EPSG:3035</li> <li><strong>Bounding box (Xmin, Ymin, Xmax, Ymax):</strong> (900,000, 899,000, 7,401,000, 5,501,000)</li> <li><strong>Spatial resolution:</strong> 30m</li> <li><strong>Image size:</strong> 216,700P x 153,400L</li> <li><strong>File format:</strong> Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> <p>If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc)</p> <h3>Name convention</h3> <p>To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are:</p> <ol> <li><strong>generic variable name:</strong> oc = organic carbon</li> <li><strong>variable procedure combination:</strong> iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm<sup>3</sup> for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li><strong>Position in the probability distribution/variable type:</strong> m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li><strong>Spatial support:</strong> 30m</li> <li><strong>Depth reference:</strong> b0cm..20cm = depth range from 0 to 20cm</li> <li><strong>Time reference begin time:</strong> 20000101 = 2000-01-01</li> <li><strong>Time reference end time:</strong> 20041231 = 2004-12-31</li> <li><strong>Bounding box:</strong> eu = pan-Europe</li> <li><strong>EPSG code:</strong> epsg.3035</li> <li><strong>Version code:</strong> v20240804 = version from 2024-08-04</li> </ol>
Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T
<h2><strong>Sub-dataset: WPCT mean, 2000–2004</strong></h2> <h2>Disclaimer</h2> <p>This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk.</p> <h2>Description</h2> <p>This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics.</p> <p>This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset.</p> <p>This data set includes:</p> <ul> <li><strong>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals):</strong><br> This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m<sup>3</sup> (scaled 10x). </li> <li><strong>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals):</strong><br> This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage. </li> </ul> <h3>Related identifiers</h3> <ul> <li><strong>SOCD mean:</strong><br> <a href="https://zenodo.org/records/13754343">2000-2004</a> <a href="https://zenodo.org/records/13771721">2004-2008</a> <a href="https://zenodo.org/records/13771841">2008-2012</a> <a href="https://zenodo.org/records/13771911">2012-2016</a> <a href="https://zenodo.org/records/13771967">2016-2020</a> <a href="https://zenodo.org/records/13772054">2020-2022</a> </li> <li><strong>SOCD p025:</strong><br> <a href="https://zenodo.org/records/13779539">2000-2004</a> <a href="https://zenodo.org/records/13774064">2004-2008</a> <a href="https://zenodo.org/records/13774089">2008-2012</a> <a href="https://zenodo.org/records/13774114">2012-2016</a> <a href="https://zenodo.org/records/13774167">2016-2020</a> <a href="https://zenodo.org/records/13774196">2020-2022</a> </li> <li><strong>SOCD p975:</strong><br> <a href="https://zenodo.org/records/13778472">2000-2004</a> <a href="https://zenodo.org/records/13773396">2004-2008</a> <a href="https://zenodo.org/records/13773765">2008-2012</a> <a href="https://zenodo.org/records/13773828">2012-2016</a> <a href="https://zenodo.org/records/13773953">2016-2020</a> <a href="https://zenodo.org/records/13774003">2020-2022</a> </li> <li><strong>WPCT mean:</strong><br> <a href="https://zenodo.org/records/13785010">2000-2004</a> <a href="https://zenodo.org/records/13785079">2004-2008</a> <a href="https://zenodo.org/records/13785170">2008-2012</a> <a href="https://zenodo.org/records/13785306">2012-2016</a> <a href="https://zenodo.org/records/13785419">2016-2020</a> <a href="https://zenodo.org/records/13785553">2020-2022</a> </li> <li><strong>WPCT p025:</strong><br> <a href="https://zenodo.org/records/13786250">2000-2004</a> <a href="https://zenodo.org/records/13786314">2004-2008</a> <a href="https://zenodo.org/records/13786449">2008-2012</a> <a href="https://zenodo.org/records/13786565">2012-2016</a> <a href="https://zenodo.org/records/13786594">2016-2020</a> <a href="https://zenodo.org/records/13786702">2020-2022</a> </li> <li><strong>WPCT p975:</strong><br> <a href="https://zenodo.org/records/13785722">2000-2004</a> <a href="https://zenodo.org/records/13785854">2004-2008</a> <a href="https://zenodo.org/records/13785917">2008-2012</a> <a href="https://zenodo.org/records/13786029">2012-2016</a> <a href="https://zenodo.org/records/13786119">2016-2020</a> <a href="https://zenodo.org/records/13786214">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li><strong>Time period:</strong> 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li><strong>Type of data:</strong> Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li><strong>How the data was collected or derived:</strong> The data was derived using machine learning models.</li> <li><strong>Statistical methods used:</strong> Quantile Random Forest</li> <li><strong>Limitations or exclusions in the data:</strong> The dataset does not include data for Svalbard. </li> <li><strong>Coordinate reference system:</strong> EPSG:3035</li> <li><strong>Bounding box (Xmin, Ymin, Xmax, Ymax):</strong> (900,000, 899,000, 7,401,000, 5,501,000)</li> <li><strong>Spatial resolution:</strong> 30m</li> <li><strong>Image size:</strong> 216,700P x 153,400L</li> <li><strong>File format:</strong> Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> <p>If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc)</p> <h3>Name convention</h3> <p>To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are:</p> <ol> <li><strong>generic variable name:</strong> oc = organic carbon</li> <li><strong>variable procedure combination:</strong> iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm<sup>3</sup> for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li><strong>Position in the probability distribution/variable type:</strong> m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li><strong>Spatial support:</strong> 30m</li> <li><strong>Depth reference:</strong> b0cm..20cm = depth range from 0 to 20cm</li> <li><strong>Time reference begin time:</strong> 20000101 = 2000-01-01</li> <li><strong>Time reference end time:</strong> 20041231 = 2004-12-31</li> <li><strong>Bounding box:</strong> eu = pan-Europe</li> <li><strong>EPSG code:</strong> epsg.3035</li> <li><strong>Version code:</strong> v20240804 = version from 2024-08-04</li> </ol>
ELABORATION OF THE ITALIAN PORTION OF THE GLOBAL SOIL ORGANIC CARBON MAP (GSOCMAP)
<p>The Global Soil Organic Carbon map (GSOCmap) published by the Food and Agriculture Organization<br> constitutes a baseline estimation of soil organic carbon stock (CS, ton ha–1) from 0 to 30 cm, on a grid at 30 arc-seconds<br> resolution (approximately 1 x 1 km). It has been produced for the Italian territory by the Italian Soil Partnership (ISP): a<br> national hub of institutions dealing with soils, either academic/research institutions, and regional soil services (RSS). The<br> RSS are the main soil data owners in Italy and play a central role in the elaboration of policies for soil management. The<br> RSS adhering to the ISP are: Calabria, Campania, Emilia Romagna, Friuli Venezia Giulia, Liguria, Lombardia, Marche,<br> Piemonte, Puglia, Sicilia, Toscana, and Veneto. A national soil database is maintained by the Consiglio per la Ricerca e<br> l'Analisi dell'Economia Agraria (CREA). The RSS contributed with soil data, with mean density of 1 point per 50 square<br> kilometres, selecting data analysed for soil organic carbon content (SOC, dag kg-1), which were representative and well<br> distributed for the following environmental covariates: land use, geomorphology, and climate. The data were selected inbetween<br> 1990 al 2013. This was necessary in order to exclude the effect of the new soil protection policies of the Rural<br> Development Programme 2014-2020. For the RSS not included in the ISP, the data were selected from the national soil<br> database. 6748 point data were finally selected. SOC values obtained with the Springer and Klee and flash combustion<br> elemental analyser methods were retained for elaborations, because the 2 methods, were found to give statistically<br> equivalent results. SOC values obtained with Walkey and Black method were, instead, corrected with an empirical factor<br> of 1.3. 2292 of the 6748 point data had also measured bulk density (BD, Mg m–3). Pedotransfer functions were calibrated<br> to estimate BD were measured BD were missing, with the following as auxiliary variables: land use, soil regions, texture,<br> and SOC. The carbon stock (CS, ton ha–1) was calculated by multiplying: 0.3 (m) * SOC (dag kg-1) * fine earth fraction (1 -<br> skeletal content expressed as daL m–3) * BD (Mg m–3). CS of the first 30 cm depth was calculated as depth-weighted<br> average. A spatial statistics method was used for the CS interpolation. The following auxiliary variables were used: soil<br> regions, soil subregions, Corine land cover 2006, lithology, soils affected by natural constrains (gleyic, histic, vertic,<br> coarse, shallow, arenic, sodic, and acid), sand content, silt content, 30-m aster-DEM, distance from coast, distance from<br> relieves, soil aridity index, annual mean precipitations, mean annual air temperature, soil inorganic carbon, and soil<br> depth. For the soil region of Po valley, the land units at 1:250,000 scale were also used. The interpolation method was a<br> general linear regression for the soil regions of Po valley, and a radial basis function for the remaining Italian territory.<br> The 6748 point data were divided, by spatial random sampling, into 10 subsets. Ten interpolations were produced, each<br> time leaving out 1/10 of the dataset. Average (fig. 1), standard deviation and confidence intervals of these 10<br> interpolations were calculated. Mean Absolute Errors (MAE) and Root Mean Squared Errors (RMSE) were respectively<br> 25.5 and 36.4 Mg/ha.</p> <p>A.85 Italy Map source: Country submission Point data Number of samples: 6748 Sampling period: 1990-2013 SOC analysis method: SOC values obtained with the Springer and Klee and ’flash combustion elemental analyser’ methods were retained for elaborations. Uncorrected values obtained by the Walkey and Black method were corrected with an empirical linear equation, based on previous studies and as recommended by the Italian official methods. BD analysis method: Undisturbed sampling, core method and pit method Mapping method Mapping method details: Neural Networks and GLM, according to soil region Validation statistics: Mean Error (ME) of the prediction is 1.688 Mg/ha, MAE 25.57 Mg/ha, Root Mean Squared Error (RMSE) is 36.24 Mg/ha. Contact Data Holder: Research centre for agriculture and environment Contact: CREA Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria edoardo.costantini@crea.gov.it</p>
Nevada Desert FACE Facility Soil Organic Carbon Data
This data set is the result of soils analysis from the Nevada Desert Free-Air CO2 Enrichment Facility (NDFF) experiment in the Mojave Desert and reports soil organic carbon (%C) and delta 13C stable isotope values. These soils were collected at the end of the NDFF experiment in 2007 and stored at Cornell University until analysis in 2018. Soils were harvested from 6 cover types (5 perennial vegetation covers and unvegetated interspace soils) from 0-100 cm in the soil profile in 20 cm increments. Soils were pretreated for inorganic carbon removal using an acid fumigation technique with HCl. Bulk density from NDFF plots is provided (kg soil* ha ^ -1) so that SOC stocks may be calculated. These data provide the basis for a publication challenging the prevailing idea that arid ecosystems will increase soil organic carbon stocks under long term elevated CO2.
Organic and inorganic carbon concentration and stable isotope composition in poorly drained agricultural soils in Iowa, USA
We measured soil organic carbon (SOC) and inorganic carbon (carbonate) in samples collected along topographic gradients in agricultural fields in Iowa, USA, in 2018. We also measured stable isotopes of SOC, soil nitrogen, and carbon in respired CO2 to provide additional context for organic matter dynamics. Additional physical, chemical, and hydrologic variables were measured on these samples and in the field sites to understand mechanisms underlying patterns in soil organic and inorganic carbon.
Effects of drying temperature on potential carbon mineralization and water-extractable organic carbon in Iowa cropland and riparian buffer soils
Measuring carbon dioxide (CO2) produced after re-wetting a previously dried soil is an increasingly popular soil health assay, but there is disagreement on the optimal soil drying temperature. We tested whether soil drying temperature impacts water-extractable organic carbon (WEOC) and soil CO2 emissions (potential carbon mineralization) following rewetting of dried soil. Samples were collected at four sites in north-central Iowa, US, and each site had soils planted to corn/soybean or perennial vegetation. The dataset includes measurements of WEOC prior to the incubation experiment, and measurements of CO2 flux and its stable carbon isotope ratio over the course of a 28-day incubation. The manuscript describing these data is under review in Geoderma.
Mechanisms influencing physically sequestered soil carbon in temperate restored grasslands in South Africa and North America
This dataset contains a measurement of physically protected carbon (microaggregate-within-macroaggregate C) and potential drivers of physically protected C accumulation during grassland restoration. The data were collected from three independent grassland restorations from agriculture in North America and South Africa. Northeast Kansas, USA data were collected in May 2013. Northeast Free State, RSA data were collected in September–November 2005. Southeast Nebraska, USA data were collected in October 2008–May 2008. Aggregate fractionations were performed by hierarchical wet sieving (Six et al 2000). Carbon and N quantification were done by flash combustion-gas chromatography. Microbial biomass C quantification was performed with chloroform fumigation-incubation (chloroform fumigation-extraction in the case of northeast Kansas). Phospholipid fatty acid biomass analysis was conducted using the methods of Bligh and Dyer (1959).
Respiration, isotope composition, and carbon source partitioning from incubations of soil amended with litter and isotope-labeled lignin
We incubated 10 forest soils (collected from sites across North America, including the Luquillo LTER/CZO) in the laboratory for over two years to quantify the decomposition of carbon derived from added litter and lignin, as well as from extant soil organic matter. Each soil was subjected to two substrate addition treatments: a) litter derived from a C4 grass precipitated with 13C-enriched lignin, or the same C4 grass litter was precipitated with natural-abundance lignin. The concentrations and delta13C composition of carbon dioxide produced from each soil were measured periodically over time and partitioned into sources (soil organic matter, litter, and added lignin) using isotope mixing models. The methods and results are described in detail by a manuscript in Ecology (Hall et al., 2020).
Data for: Soil Nutrients Increase Long-term Soil Carbon Gains Threefold on Retired Farmland
These data report soil C for almost four decades following intensive agricultural soil disturbance along an experimentally imposed gradient in nitrogen (N) added annually in combination with other macro- and micro-nutrients. Data were collected at the Cedar Creek Ecosystem Science Reserve (CCESR), a U.S. Long Term Ecological Research (USLTER) site located in central Minnesota, USA. Soil % C accumulated over the course of the study in unfertilized control plots leading to a gain of 6.1 Mg C ha-1 in the top 20 cm of soil. Nutrient addition increased soil % C accumulation leading to a gain of 17.8 Mg C ha-1 in fertilized plots, nearly a threefold increase over the control plots. These results demonstrate that substantial increases in soil C in successional grasslands following agricultural abandonment occurs over decadal timescales, and that C gain is increased by high supply rates of soil nutrients. In addition, soil % C continued to increase for decades under elevated nutrient supply, suggesting that short-term nutrient-addition experiments underestimate the effects of soil nutrients on soil C accumulation.
Seasonal relationships between soil respiration and water-extractable carbon as influenced by soil temperature and moisture in forest soils of the Andrews Experimental Forest, 1992-1993
The overall objective of this study is to model trace gas emissions from forest soils of the H. J. Andrews Experimental Forest. This is to be accomplished by studying trace gas emissions and related variable at a set of 20 permanent plots at the HJA.
Below ground soil carbon and nitrogen concentrations in quadrats harvested from the Anaktuvuk River Fire site in 2011
Summarized below ground soil carbon and nitrogen concentrations measured in quadrats at three sites at and around the Anaktuvuk River Burn: severely burned, moderately burned and unburned. This data corresponds with the aboveground biomass and root biomass data files: 2011ARF_AbvgroundBiomassCN, 2011ARF_RootBiomassCN_byDepth, 2011ARF_RootBiomassCN_byQuad, 2011ARF_SoilCN_byDepth.
Photo-oxidation and photomineralization apparent quantum yield dataset for dissolved organic carbon leached from permafrost soils collected from the North Slope of Alaska, July 2018.
Dissolved organic carbon (DOC) was leached from permafrost soils near the Toolik Field Station in the Alaskan Arctic and then characterized for its photochemical properties. Oxygen (O2) consumed from photo-oxidation of permafrost DOC was measured as a function of sunlight wavelength, defined as the apparent quantum yield spectrum of photo-oxidation (O2 consumed per mol photon absorbed by DOC). Carbon dioxide (CO2) produced from photomineralization of permafrost DOC was measured as a function of sunlight wavelength, defined as the apparent quantum yield spectrum of photomineralization (CO2 produced per mol photon absorbed by DOC).
Radiocarbon and stable carbon isotopes of CO2 produced from photomineralization of DOC leached from permafrost soils collected from the North Slope of Alaska in the summer of 2018
Dissolved organic carbon (DOC) was leached from permafrost soils near the Toolik Field Station in the Alaskan Arctic and then characterized for its photochemical properties. The radiocarbon (14C) and stable carbon (13C) isotopic compositions of carbon dioxide (CO2) photochemically produced from permafrost DOC were quantified.
Radiocarbon and stable carbon isotope dataset for DOC leached from permafrost soils collected from the North Slope of Alaska in the summer of 2018
Dissolved organic carbon (DOC) was leached from permafrost soils near the Toolik Field Station in the Alaskan Arctic. The radiocarbon (14C) and stable carbon (13C) isotopic compositions of permafrost DOC were quantified.
Soil temperature in Black Spruce Carbon cycling study along a temperature gradient in interior Alaska
Study conducted on black spruce C cycling study along a temperature gradient in interior Alaska from 1999 to 2002. The temperature gradient was established by locating sites in the Fairbanks area that varied in elevation and aspect. Measurements include:soil temperature, forest aboveground production, litterfall, decomposition of litter and cellulose proxies, soil carbon dioxide efflux, moss photosynthesis, soil moisture, foliar isotopes (15N and 13C).
Nitrogen cycling at treeline. II. Percent Soil Carbon and Nitrogen
We studied spatial and temporal patterns of nitrogen pools and fluxes in soils at treeline and forested sites within three mountain ranges across a 785 km transect in Alaska during 2001- 2002. We measured pools of soil mineral (ammonium and nitrate) and organic (amino acid and microbial biomass) nitrogen, in situ rates of net mineralization, net nitrification, net amino acid production, and decomposition, as well as soil carbon turnover in a laboratory incubation experiment. A complete characterization of the study can be found in Loomis et al. (2006).
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.