High resolution datasets of soil organic carbon and nitrogen stocks in Canadian lowland tundra

Julia Wagner, Victoria Martin, Niek J. Speetjens, Willeke A’Campo, Luca Durstewitz, Rachele Lodi, Michael Fritz, George Tanski, Jorien E. Vonk, Andreas Richter, Annett Bartsch, Hugues Lantuit, Gustaf Hugelius

This dataset is a quantification soil organic carbon (SOC) and nitrogen (N) stocks for two study sites in Canadian lowland tundra at a spatial resolution of 2 m. The sampling was carried out during field campaigns in 2018 at Ptarmigan Bay and in 2019 at Komakuk Beach.

The field data was collected within the Nunataryuk project (EU Horizon 2020 project, 2017 – 2023) to investigate soil properties, in particular SOC and N stocks, between two sites one of which was glaciated and one not during the last glacial maximum.

This dataset includes field sample data and predicted soil organic carbon and nitrogen stocks in tiff format for the two study areas in the following depth increments: 0 – 5 cm, 5 – 15 cm, 15 – 30 cm, 30 – 60 cm and 60 – 100 cm. Further we provide tiff files estimating the uncertainty for each predicted depth increment.

TerrestrialSoilRandom forestMachine learningSoil organic carbonTundraPermafrost

Name

Version

Citation

References

Wagner, J., Martin, V., Speetjens, N. J., A’Campo, W., Durstewitz, L., Lodi, R., Fritz, M., Tanski, G., Vonk, J. E., Richter, A., Bartsch, A., Lantuit, H., & Hugelius, G. (2023). High resolution mapping shows differences in soil carbon and nitrogen stocks in areas of varying landscape history in Canadian lowland tundra. Geoderma, 438 (116652), 116652. https://doi.org/10.1016/j.geoderma.2023.116652

Yigini, Y., Olmedo, G.F., Reiter, S., Baritz, R., Viatkin, K., Vargas, R., (2018). Soil Organic Carbon Mapping Cookbook 2nd edition. FAO.

Kuhn, M., 2022. caret: Classification and Regression Training. R package version 6.0-92

Data description

Zip-file containing four directories.

Sample data

Sample data is provided in form of the wagner-2024-soc-1.xlsx spreadsheet for the sampling locations from the field campaigns in 2018 at Ptarmigan Bay and 2019 at Komakuk Beach. The data covers the full depth up to 1 m. Depth increments without sample data available were estimated.

• Spreadsheets_soil_data/PB_KB_soil_data.xlsx
  • ID site ID
  • sample_ID sample ID
  • AL_1_PF_2 sample from the Active Layer = 1, sample from the Permafrost = 2
  • OL_3yes_0no sample from the organic layer = 3, not organic = 0
  • sample_estimated values basted on sample = 1, values estimated = 3 (interpolated/ estimated), only values for bulk density (BD) estimated = 3
  • sample_CN_1yes2no sample for carbon : nitrogen ratio (CN) measurements was available
  • sample_BD1yes2no sample for bulk density was available
  • comment_sample_material_CN comment on the sample material
  • comment_CN commenton the value for CN when no sample was available
  • comment_BD commenton the value for BD when no sample was avaiable
  • BD dry bulk density at 65 °C
  • diff_bottom_top thickness of the sampling depth in centimetre
  • top_cm top depth of the sampling depth in centimetre
  • bottom_cm bottom depth of the sampling depth in centimetre
  • N_content nitrogen content [%]
  • C_content carbon content [%]
  • CN_ratio C:N ratio
  • SOC_stocks soil organic carbon stocks [Kg / m²]
  • N_stocks nitrogen stocks [Kg / m²]
  • d_13C_12C ratio of 13C and 12C
  • d_15N_14N ratio of 15C and 14N
  • water_content water content/ ice content for permafrost samples, simple ratio between weight of dry and fresh material (PB_2018_soil_data: water content given as fraction of %, KB_2019_soil_data water content given in %)

Sampling sites

The sampling locations are provided as shapefiles for the two study sites Komakuk Beach (KB) and Ptarmigan Bay (PB): a total of 46 sampling locations at KB and 40 at PB.

• sampling_locations
  • KB_sampling_locations
  • PB_sampling_locations
  • KB_sampling_locations_additional.shp for samples that were taken in the field, but were not used in the study Wagner et al. 2023.

The attribute table contains the sampling Date in the format YYYY-MM-DD

Models

Random Forest models for each depth increment were created in R based on environmental variables and the target variables SOC and N (for more information see Wagner et al. 2023). The final models for each depth increment were saved as rds-files.

models contains the random forest models created in R to be used within the package randomForest that is implemented in the package caret (Kuhn 2022) for the two study areas

• area_Ptarmigan_Bay Ptarmigan Bay (PB)
• N-stocks Nitrogen stocks
  • SOC-content soil organic carbon content (SOC content)
  • SOC-stocks soil organic carbon stocks
  • SOC-stocks_SOC-stocks_above_as_variable contains the models for SOC stock maps where predicted SOC stocks (all layers accumulated)
• area_Komakuk_Beach Komakuk Beach (KB)
  • N-stocks Nitrogen stocks
  • SOC-content soil organic carbon content (SOC content)
  • SOC-stocks soil organic carbon stocks
  • SOC-stocks_SOC-stocks_above_as_variable contains the models for SOC stock maps where predicted SOC stocks (all layers accumulated)

for the depth intervals 0-5, 5-15, 15-30, 30-60 and 60-100 cm.

Structure of the files e.g.:

PB_model_0_05_N_stocks.rds with area-code (PB, KB), model depth interval and soil property (N_stocks, SOC_stocks, SOC_content)

Predictions

Predictions were made using random forest models based on the target variable and environmental variables (for more information see Wagner et al. 2023). The predictions are 2 m raster resolution saved in tiff format and in WGS 84 / UTM zone 7N (EPSG: 32607).

outputs/Predictions contains the random forest maps created in R with the package randomForest implemented in the caret package for the two study areas

• area_Ptarmigan_Bay Ptarmigan Bay (PB)
  • N-stocks Nitrogen stocks in kg / m²
    • cubicm Nitrogen stocks in kg / m³
  • SOC-content soil organic carbon content (SOC content) in %
  • SOC-stocks soil organic carbon stocks in kg / m²
    • cubicm soil organic carbon stocks in kg / m³
  • SOC-stocks_SOC-stocks_above_as_variable contains the models for SOC stock maps where predicted SOC stocks in % (all layers accumulated)
• area_Komakuk_Beach Komakuk Beach (KB)
  • N-stocks Nitrogen stocks in kg / m²
    • cubicm Nitrogen stocks in kg / m³
  • SOC-content soil organic carbon content (SOC content) in %
  • SOC-stocks soil organic carbon stocks in kg / m²
    • cubicm soil organic carbon stocks in kg / m³
  • SOC-stocks_SOC-stocks_above_as_variable contains the models for SOC stock maps where predicted SOC stocks in % (all layers accumulated)

at depth intervals 0 – 5, 5 – 15, 15 – 30, 30 – 60 and 60 – 100 cm.

Structure of the files e.g.:

KB_prediction_model_N_stocks_1_0_05.tif with the area-code (PB, KB), model soil property (N_stocks, SOC_stocks, SOC_content) and deph interval (e.g. 0 – 05,5 – 15, etc.).

The folders containing the SOC stocks contain a subfolder called "cubicm" where kg / m² were converted into kg / m³ for better comparison (as in Wagner et al. 2023) .

Uncertainty assessment

Uncertainty estimations were created based on quantile regression forest (Yigini et al. 2018). The files are 2 m raster resolution saved in tiff format and in WGS 84 / UTM zone 7N (EPSG: 32607).

outputs/Uncertainty_maps contains the uncertainty maps created in R using quantile regression forest (workflow of Yigini et al 2018, "Soil Organic Carbon Mapping Cookbook") for the two study areas

• area_Ptarmigan_Bay Ptarmigan Bay (PB)
  • N-stocks Nitrogen stocks
  • SOC-content soil organic carbon content
  • SOC-stocks soil organic carbon stocks
• area_Komakuk_Beach Komakuk Beach (KB)
  • N-stocks Nitrogen stocks
  • SOC-content soil organic carbon content
  • SOC-stocks soil organic carbon stocks

at depth intervals 0 – 5, 5 – 15, 15 – 30, 30 – 60 and 60 – 100 cm.

Structure of the files e.g.:

KB_uncertainty_N_stocks_1_0_05.tif for the area-code (PB, KB), model uncertainty (N_stocks, SOC_stocks, SOC_content) and deph interval (e.g. 0 – 05,5 – 15, etc.)

All tif-files are in a WGS 84 UTM Zone 7N projection.

Comments

This study is part of the Nunataryuk project. The collected soil data contributes towards a better understanding of the sparsely sampled permafrost region in general, may contribute to global databases of soil properties and may enhance future digital soil mapping efforts. Maps of predicted SOC and N stocks contribute to a better understanding of small scale distribution of SOC and nitrogen stocks and may be used for further studies that estimate potential release of SOC and N from permafrost affected soils. The sites were sampled by horizon from soil pits of the active layer. The permafrost was cored in 10 cm depth increments by using a steel pipe.

Project

This study is part of the Nunataryuk project, which received funding under the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no. 773421. It was further funded by the Swedish Research Council (grant 2018–04516) and the ESA DUE GlobPermafrost project (contract number 4000116196/15/I–NB).

Publisher

Bolin Centre Database

License

First name

Julia

Last name or organisation

Wagner

Email address

julia.wagner@natgeo.su.se

Address

Department of Physical Geography; Stockholm University

Postal code

SE-106 91

City

Stockholm

Country

Sweden

GCMD science keyword

Earth science > Land surface > Soils > Carbon

GCMD location

Continent > North America > Canada

Dataset language

English

DOI

Time