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.
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Citation
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 (2024) High resolution datasets of soil organic carbon and nitrogen stocks in Canadian lowland tundra. Dataset version 1. Bolin Centre Database. https://doi.org/10.17043/wagner-2024-soc-1
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.