Computation of total soil organic carbon stock and its standard deviation from layered soils

Abstract

To assess carbon sequestration in the agricultural and natural systems, it is usually required to report soil organic carbon (SOC) as mass per unit area (Mg ha-1) for a single soil layer (e.g., the 0-0.3 m ploughing layer). However, if the SOC data are reported as relative concentration (g kg-1 or %), it is required to compute the SOC stock and its standard deviation (SD) for a given layer as the product of SOC concentration and bulk density (BD). For a proper computation, it is required to consider that these two variables are correlated. Moreover, if the data are already reported as SOC stock for multiple sub-layers (e.g., 0-0.15 m, 0.15-0.3 m) it is necessary to compute the SOC stock and its SD for a single soil layer (e.g., 0-0.3 m). The correlation between stocks values from adjacent and non-adjacent soil sub-layers must be accounted to compute the SD of the single soil layer. The present work illustrates the methodology to compute SOC stock and its SD for a single soil layer based on SOC concentration and BD also from multiple sub-layers. An Excel workbook automatically computes the means of stocks and SD saving the results in a ready-to-use database.•Computation of a carbon (SOC) stock and its standard deviation (SD) from the product between SOC concentration and bulk density (BD), being correlated variables.•Computation of a SOC stock and its SD from the sum of SOC stocks of multiple correlated sub-layers.•An Excel workbook automatically computes the means of SOC stocks and SD and saves the results in a ready-to-use database.

Keywords: Bulk density; Correlation; Soil layer.

Graphical abstract

Fig. 1

Example of a single template for the setting of the data input. The user is allowed to fill the green cells with all the information related to the sample/study selected.

Fig. 2

Example of automatic setting of the correlation coefficients (product between OC and BD as Case 1, and sum of stocks as Case 2). In the Case 2, the correlation values are automatically retrieved separately for the control and treatment, and for the adjacent layers and non adjacent layers.

Fig. 3

Example of manual setting of the correlation coefficients (product between OC and BD as Case 1, and sum of stocks as Case 2). In the Case 2, the correlation values have to be defined by the user separately for the control and treatment, and for the adjacent layers and non adjacent layers.

Fig. 4

Database sheet. For each sample/study, SOC stock and SD in the total soil layer are saved in a single row separately for control and treatment. In the first row of the example, SOC stock and SD of a total soil layer (0-0.3 m) are displayed for control and treatment. Ancillary data, such as study and sample number, data source, date, and sample size are shown in the same row.