Computing C Stock for the BE-Lcr site in 2017
http://www.icos-etc.eu/icos/
info@icos-etc.eu
Possible issues
Rock fragments
Warning: The name of the attribute in the database has changed in 2020. The \(`sosmW30s`\) variable is now \(`sosmW105s`\). Therefore, we have 2 ways for computing the RF.
Before 2020, the RF was computed in the following way:
\[RF_{30} = \frac{sosmW30s_{sp2}} {sosmW30s_{sp2}+sosmW30e_{sp2} }\]
After 2020, RF is computed using the weight of the coarse elements dried at 105°C:
\[RF_{105} = \frac{sosmW105s_{sp2}} {sosmW105s_{sp2}+sosmW30e_{sp2} }\]
Load and curate the data
This file is gathering the results for the site \(BE-Lcr\)
Extract the soil data
As a first step, we load and prepare the data. They are extracted from the ICOS soil database located in the French soil information system (DONESOL), which contains all the data from all sites. These files came from a SQL query.
Then, I extract the data and the sampling year for the selected site.
Extract coordinates and site stratification details
To compute design-based estimates of soil properties, we rely on spatial stratification parameters derived from the ETC’s pre-sampling analysis.
Using the spcosa package and KMZ files (which contain
spatial layers), we extract:
\(idstratum\): Stratum identifier (ranging from 1 to 10).
\(H\): Total number of strata.
\(n_h\): Sample size (number of SP-I plots) per stratum.
\(nSites\): Total sample size (sum of all SP-I plots across strata).
\(stratumArea\): Area of each stratum (in pixels).
\(a_h\): Relative area per stratum.
Note: For KML files, extraction from the KMZ archive is required—this can be done using Windows.
Extract the soil depth limits
Accurate soil depth limits are essential for BADM quality control by ETC-Soil. While some errors may evade automated checks during C portal submission, uncorrected depth values directly impact derived calculations (e.g., soil stock estimates).
Impact on Downstream Calculations
Soil Stock Errors: Uncorrected thickness values bias carbon stock estimates.
ETC Feedback: Proactive corrections reduce revision requests post-submission.
Protocol Definitions
Standard Layer Depths
| Layer type | Description | Order |
|---|---|---|
| O (undifferentiated) | WRB 2022 classification | -4 |
| Oi (initial decomposition) | WRB 2022 classification | -3 |
| Oe (intermediate) | WRB 2022 classification | -2 |
| Oa (advanced) | WRB 2022 classification | -1 |
| 0 - 5 cm | ICOS standard depth | 1 |
| 5 - 15 cm | ICOS standard depth | 2 |
| 15 - 30 cm | ICOS standard depth | 3 |
| 30 - 60 cm | ICOS standard depth | 4 |
| 60 - 100 cm | ICOS standard depth | 5 |
Exceptions
Peatlands and wetlands: May have not standard depths due to hydromorphic conditions.
Rocky Soils: Often exhibit shallow profiles with non-standard final layers.
Key Rules
To compute the mean and uncertainties accurately, we need to harmonize the soil layers as follow:
If the depth of the last layer is incomplete and varies across observations (e.g., extends only to 80 cm instead of the full 100 cm), we apply a frequency-weighted mean to harmonize this layer.
For non-standard layer intervals, we apply a spline model to interpolate the variables at the standard ICOS depth.
The correct organic layer ordering is (Oa → Oe → Oi). If stratification is unclear, we aggregate the O layers into a single one (O layer).
Within a single SP-I plot, all associated SP-II units should share the same classification for the O layer.
The thickness (cm) of the O layer within an SP-I plot is assumed to be the average of the corresponding SP-II measurements.
Note: If you notice any inconsistencies in your depth limits, please contact ETC-Soil to update your BADM accordingly.
In this site, the PI implemented the following depths:
| Layer group | Soil Layers | Layer order | Number of samples |
|---|---|---|---|
| Mineral | 0-5 cm | 1 | 100 |
| Mineral | 5-15 cm | 2 | 100 |
| Mineral | 15-30 cm | 3 | 100 |
| Mineral | 30-60 cm | 4 | 100 |
| Mineral | 60-100 cm | 5 | 100 |
The soil depth limits were:
| Layer group | Layer order | SOSM_UD | SOSM_LD |
|---|---|---|---|
| Mineral | 1 | 0 | 5 |
| Mineral | 2 | 5 | 15 |
| Mineral | 3 | 15 | 30 |
| Mineral | 4 | 30 | 60 |
| Mineral | 5 | 60 | 100 |
Soil properties and Quality Control
In this section, we outline the procedures used to compute the key soil properties necessary for calculating carbon and nitrogen stocks. Variables such as bulk density and fine soil stock are derived from standardized field measurements and imputed where missing values are detected.
Data quality control focuses on identifying and addressing missing and negative values. With the exception of SIC content, negative values are not expected in the dataset. Negative values are replaced with \(NA\), which are followed by imputation using the layer-specific average.
Checking the soil organic carbon (SOC) content
Checking for negative and missing values in SOC content. If the table is not empty, it means that SOC content is negative or missing.
| MinOrg | depth_horizon | sp1 | sp2 | no_profil_sp2 | carbone |
|---|
Negative and missing values of SOC content are imputed using the
layer-specific averages.
The following graph shows the organic carbon content frequency \(SOC_{layer}\) distribution across soil layers, following imputation of missing values using the layer-specific averages.
Checking the total nitrogen (NT) content
Checking for negative and missing values in NT content.
| MinOrg | depth_horizon | sp1 | sp2 | no_profil_sp2 | Nitrogen |
|---|
Negative values are replaced with \(NA\) and the missing values of NT are imputed using the layer-specific averages.
The following graph shows the NT content frequency \(NT_{layer}\) distribution across soil layers, following imputation of missing values using the layer-specific averages.
Compute the soil inorganic carbon (SIC) content
Soil inorganic carbon (SIC; g.kg-1) was calculated as the product of the result of the calcimetry analysis (CaCO3; g.kg-1 equivalent) multiplied by 0.12.
Checking for missing values in inorganic carbon content.
| MinOrg | depth_horizon | sp1 | sp2 | no_profil_sp2 | Carbonates |
|---|
Note: Negative values of carbonates are not replaced with the mean because they represent the detection threshold of the laboratory analysis.
The following graph shows the \(SIC_{layer}\) content frequency distribution across soil layers
Compute residual water content using the wet-basis approach
We compute the residual water content (\(RW^l_{ik}\)) using the wet based approach as follow :
For mineral layers at SP-I level:
\[ RW^l_{ik} = \frac{SOSM\_WX30\_E^l_{ik} - SOSM\_WX105\_E^l_{ik}}{SOSM\_WX30\_E^l_{ik}} \]
For organic layers at SP-I level:
SOSM_W30_E is considered as a dry mass because residual
water content is assumed to be negligible.
In order to check the data quality, missing and negative values of soil water mass at 30 and 105°C are listed in the two tables below:
If the table below is not empty, it means that either or both
SOSM_WX30_E or SOSM_WX105_E are missing:
| sp1 | sp2 | no_profil_sp2 | sosm_wx30e_sp1 | sosm_wx105e_sp1 |
|---|
If the table below is not empty, it means that the residual water is
negative, that is, SOSM_WX30_E <
SOSM_WX105_E.
| MinOrg | depth_horizon | sp1 | sp2 | no_profil_sp2 | Residual water (g/g) |
|---|---|---|---|---|---|
| Mineral | 15-30 cm | SP-I_03 | SP-II_03-01 | BE-Lcr/SP-II_03-01 | -0.0215870 |
| Mineral | 15-30 cm | SP-I_03 | SP-II_03-02 | BE-Lcr/SP-II_03-02 | -0.0215870 |
| Mineral | 15-30 cm | SP-I_03 | SP-II_03-03 | BE-Lcr/SP-II_03-03 | -0.0215870 |
| Mineral | 15-30 cm | SP-I_03 | SP-II_03-04 | BE-Lcr/SP-II_03-04 | -0.0215870 |
| Mineral | 15-30 cm | SP-I_03 | SP-II_03-05 | BE-Lcr/SP-II_03-05 | -0.0215870 |
| Mineral | 5-15 cm | SP-I_13 | SP-II_13-01 | BE-Lcr/SP-II_13-01 | -0.0229796 |
| Mineral | 5-15 cm | SP-I_13 | SP-II_13-02 | BE-Lcr/SP-II_13-02 | -0.0229796 |
| Mineral | 5-15 cm | SP-I_13 | SP-II_13-03 | BE-Lcr/SP-II_13-03 | -0.0229796 |
| Mineral | 5-15 cm | SP-I_13 | SP-II_13-04 | BE-Lcr/SP-II_13-04 | -0.0229796 |
| Mineral | 5-15 cm | SP-I_13 | SP-II_13-05 | BE-Lcr/SP-II_13-05 | -0.0229796 |
The negative values are replaced with \(NA\).
Negative values are replaced with \(NA\) and the missing values of \(RW^l_{ik}\) are imputed using the layer-specific averages.
The following graph shows the \(RW^l_{ik}\) frequency distribution across soil layers, following imputation of missing values using the layer-specific averages.
Compute the density and mass of soil fractions for SP-II plots
Bulk density
\[ BD^l_{ik} = \frac{ \left( SOSM\_W30\_E^{l}_{ik}\times (1 - RW^{l}_{ik}) \right) + SOSM\_W105\_S^{l}_{ik} + SOSM\_W70\_R^{l}_{ik} }{SOSM\_VOLUME^{l}_{ik}} \]
In order to check the data quality of bulk density, missing values are tracked in the following table.
If the following table is not empty, it means that one of the
following variables contain missing values: SOSM_W30_E,
SOSM_W105_S (or SOSM_W30_S in previous
versions), SOSM_W70_R, or SOSM_VOLUME.
| no_profil_sp1 | depth_horizon | residWater | sosm_w30e_sp2 | sosm_w30s_sp2 | sosm_w70r_sp2 | sosm_volume_sp2 |
|---|---|---|---|---|---|---|
| BE-Lcr/SP-I_01 | 5-15 cm | 0.0110039 | NA | 0 | 0 | 458.9366 |
| BE-Lcr/SP-I_18 | 15-30 cm | 0.0104464 | NA | 0 | 0 | 688.4049 |
The missing values of \(BD^l_{ik}\) are imputed using the layer-specific averages.
The following graph shows the \(BD^l_{ik}\) frequency distribution across soil layers, following imputation of missing values using the layer-specific averages.
Coarse organic fragments
As coarse organic fragments is mostly composed by root fragments, this variable is named \(RD^l_{ik}\), that denotes root density.
\[ RD^l_{ik} = \frac{SOSM\_W70\_R^{l}_{ik}}{SOSM\_VOLUME^{l}_{ik}} \]
In order to check the data quality of \(RD^l_{ik}\), missing values are tracked in the following table.
If the table is not empty, it means that one of the following
properties contains missing values: SOSM_W30_E,
SOSM_W105S (or SOSM_W30_S in previous
versions), SOSM_W70_R, or SOSM_VOLUME.
| no_profil_sp1 | depth_horizon | residWater | sosm_w30e_sp2 | sosm_w30s_sp2 | sosm_w70r_sp2 | sosm_volume_sp2 |
|---|
The missing values of \(RD^l_{ik}\) are imputed using the layer-specific averages.
The following graph shows the \(RD^l_{ik}\) frequency distribution across soil layers, following imputation of missing values using the layer-specific averages.
Fine soil stock for mineral layers
Fine soil stock (FSS) is equivalent to mass of fine earth (FE), as commonly defined in scientific literature.
\[ FSS^l_{ik} = \frac{ (SOSM\_LD^{l}_{ik} -SOSM\_UD^{l}_{ik}) \times (SOSM\_W30\_E^l_{ik}) \times (1 - RW ^l_ik)}{SOSM\_VOLUME^{l}_{ik}} \]
In order to check the \(FSS^l_{ik}\) quality, missing data are tracked in the following table.
If the table is not empty, it means that either or both
SOSM_W30_E or SOSM_VOLUME are missing:
| no_profil_sp1 | depth_horizon | sosm_w30e_sp2 | residWater | sosm_volume_sp2 |
|---|---|---|---|---|
| BE-Lcr/SP-I_01 | 5-15 cm | NA | 0.0110039 | 458.9366 |
| BE-Lcr/SP-I_18 | 15-30 cm | NA | 0.0104464 | 688.4049 |
Missing values of \(FSS^l_{ik}\) are imputed using the layer-specific averages.
The following graph shows the fine soil stock frequency \(FSS^l_{ik}\) distribution across soil layers, following imputation of missing values using the layer-specific averages.
Organic material (OM) mass in O layers
This fraction represents the organic material in the O horizon after removing stones and living material.
\[ OM^l_{ik} = \frac{ SOSM\_W30^l_{ik} \times (1 - residWater^l_{ik})}{SOSM\_AREA^l_{ik}} \]
Coarse mineral elements (rock fragments)
\[ RF^l_{ik} = \frac { SOSM\_W105\_S^l_{ik}}{ SOSM\_W105\_S^l_{ik} + SOSM\_W30\_E^l_{ik}} \]
Warning: In the version 20200319 of
the “Instruction for SOIL SAMPLING AND PREPARATION”, the drying
temperature of coarse elements was set to 105°C instead of 30 °C.
Therefore, the variable name of rock fragments changed from
SOSM_W30_S to SOSM_W105_Sin the BADM.
In order to check the \(RF^l_{ik}\) quality, missing data are tracked in the following table.
| MinOrg | depth_horizon | no_profil_sp1 | no_profil_sp2 | sosm_w30e_sp2 | sosm_w30s_sp2 | RF |
|---|---|---|---|---|---|---|
| Mineral | 5-15 cm | BE-Lcr/SP-I_01 | BE-Lcr/SP-II_01-04 | NA | 0 | NA |
| Mineral | 15-30 cm | BE-Lcr/SP-I_18 | BE-Lcr/SP-II_18-01 | NA | 0 | NA |
The following graph shows the \(RF^l_{ik}\) distribution across soil layers, following imputation of missing values using the layer-specific averages.
Compute the SP-I data
Here we compute the stock \(z_{i}^l\) for the monitored properties using the formula described in the protocol. The data are aggregated at SP-I level.
We now check if all the observations and layers are present.
Specifically, we compute:
- The number of SP-I plots in \(BE-Lcr\) is \(20\).
- The number of available SP-I plots should total 20.
| Stratum ID | nb. of SP-I |
|---|---|
| 1 | 2 |
| 2 | 2 |
| 3 | 2 |
| 4 | 2 |
| 5 | 2 |
| 6 | 2 |
| 7 | 2 |
| 8 | 2 |
| 9 | 2 |
| 10 | 2 |
- The number of SP-I plots per stratum should total 2.
| sp1 | nb. of soil layer |
|---|---|
| SP-I_01 | 5 |
| SP-I_02 | 5 |
| SP-I_03 | 5 |
| SP-I_04 | 5 |
| SP-I_05 | 5 |
| SP-I_06 | 5 |
| SP-I_07 | 5 |
| SP-I_08 | 5 |
| SP-I_09 | 5 |
| SP-I_10 | 5 |
| SP-I_11 | 5 |
| SP-I_12 | 5 |
| SP-I_13 | 5 |
| SP-I_14 | 5 |
| SP-I_15 | 5 |
| SP-I_16 | 5 |
| SP-I_17 | 5 |
| SP-I_18 | 5 |
| SP-I_19 | 5 |
| SP-I_20 | 5 |
The number of layers per SP-I plot, which should total between 5 (only mineral) or 7 (mineral + organic)
The number of observations is \(100\).
Profile plot of the data
Using the package aqp, it is possible to plot the
collection of profiles.
Horizon-level attributes can be symbolized with color.
Note to PI: If the profile plot present some anomaly (e.g; incomplete depth limits), please contact ETC-Soil for verification.
We plot here the bulk density
We plot here the fine soil stock
We plot here the organic carbon content
We plot here the soil inorganic carbon content
We plot here the total nitrogen content
We plot here the organic carbon stocks
We plot here the soil inorganic carbon stocks
And finally we plot here the total nitrogen stocks
Plot of the relation C/N
Some Maps to visualize the raw data at SP-I site
In this section, we provide a set of maps per soil layer for the different monitored parameters.
The dots represent the value measured on the SP-I plots.
Bulk density
The map shows the bulk density per layer.
Rock fragments
The map shows the rock fragments per layer.