the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Dec 2024
A simple model of the turnover of organic carbon in a soil profile: model test, parameter identification and sensitivity
Abstract. Simulation models are potentially useful tools to test our understanding of the processes involved in the turnover of soil organic carbon (SOC) and to evaluate the role of management practices in maintaining stocks of SOC. We describe here a simple model of SOC turnover at the soil profile scale that accounts for two key processes determining SOC persistence (i.e. microbial energy limitation and physical protection due to soil aggregation). We tested the model and evaluated the identifiability of key parameters using topsoil SOC contents measured in three treatments with contrasting organic matter inputs (i.e. fallow, mineral fertilized and cropped, with and without straw addition) in a long-term field trial. The estimated total input of organic matter (OM) in the treatment with straw added was roughly three times that of the treatment without straw addition, but only 12 % of the additional OM input remained in the soil after 54 years. By taking microbial energy limitation and enhanced physical protection of root residues into account, the model could explain the differences in C persistence among the three treatments, whilst also accurately matching the time-courses of SOC contents using the same set of model parameters. Models that do not explicitly consider microbial energy limitation and physical protection would need to adjust their parameter values (either decomposition rate constants or the retention coefficient) to match this data.
We also performed a sensitivity analysis to identify the most influential parameters in the model determining soil profile stocks of OM at steady-state. Input distributions for soil and crop parameters in the model were defined for the agricultural production area of PO4 (east-central Sweden), which includes Uppsala. The resulting model predictions compared well with aggregated soil survey data for the PO4 region. This analysis showed that model parameters affecting SOC decomposition rates, including the rate constant for microbial-processed SOC and the parameters regulating physical protection and microbial energy limitation, are more sensitive than parameters determining OM inputs. Thus, the development of pedotransfer approaches to estimate SOC decomposition rates from soil properties would help to support predictive applications of the model at larger spatial scales.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(1759 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1759 KB) - Metadata XML
- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-3883', Anonymous Referee #1, 27 Feb 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3883/egusphere-2024-3883-RC1-supplement.pdfCitation: https://doi.org/
10.5194/egusphere-2024-3883-RC1 -
AC1: 'Reply on RC1', Elsa Coucheney, 03 Apr 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3883/egusphere-2024-3883-AC1-supplement.pdf
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AC1: 'Reply on RC1', Elsa Coucheney, 03 Apr 2025
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RC2: 'Comment on egusphere-2024-3883', Anonymous Referee #2, 11 Mar 2025
This study describes a simple model of soil organic carbon (SOC) turnover that represents the effects of soil physical protection and microbial energy limitation. The paper first describes the model in a soil profile, then tests it using SOC data from a long-term study on agricultural fields with varied C inputs to the soils. Finally, the model’s most influential parameters were identified in a sensitivity and uncertainty analysis. Overall, the paper is well written and presents a model of interest and relevance to soil carbon management. Below, please find specific comments intended to help improve the paper.
L83 – Define the abbreviation USSF.
L91-95 – I would suggest ending the introduction with a strong thesis statement of what the paper contributes to current knowledge of the subject.
L97-101 – I appreciate this overview of the methods, very helpful to have this framework.
L103 – In section 2.1.1 that starts on this line, it is unclear if the model as described in this section is the work of the authors or if this is describing previously published work. If it has been previously published, I suggest including most of the equations in this section in a supplement rather than in the main document. In the main manuscript, I suggest describing the model in writing and including important equations for the modifications to the model that are new in the current study. Additionally, I would encourage the authors to post their full model code online and cite it in the paper.
L107-109 – It would be helpful to specify the direction of the relationship between these effects (e.g., Do smaller pores get fewer root derived inputs? Do micropores have lower decomposition rates?).
L125 – Is the “(-)” after fr,mic supposed to indicate that it is unitless?
L218 – How does this straw addition rate compare to the maize biomass per hectare?
L219 - 220 – Include the scientific names/varieties of the crops.
L220 - What is the purpose of hand digging the plots after harvest?
L 231 – What measurements were used for the calibration? Only OM or additional measurements? Calibrating to additional variables could help reduce equifinality.
L238 – Specify the field bulk density values used for this validation.
Table 1 – Are there field measurements available for any of these parameters? If so, how similar are they to these fixed values?
Figure 1 needs a legend to identify what the different colors/patterns of shading indicates.
Table 1 – Are there data references for these parameter values? If not, how did you come to these values?
Tables – I recommend including captions for tables with relevant details.
L264- What determined if the data support was sufficient?
Table 3 – The source “SCB Statistics Sweden” needs to be more specific. Same comment for source listed as “site data” - where are site data accessible? Year, dataset name, authors etc.
L304 - 306 – Is this distinction of straw going into only mesopores and root OM going partially into micropores supported by empirical data?
L308 – What is meant by “export of residues?” Does that mean the removal of residues by land managers?
Figure 3 – This panel figure needs letters for each panel and a description of each panel and the definition of the X axes in the figure caption.
Figure 4 – This panel figure also needs to have the individual panels labeled/described and the axes defined in the caption.
L314 – In the introduction, large mechanistic models are criticized for having uncertainty and equifinality. That was provided as justification for a simpler parsimonious model. How does that criticism relate to your finding that the simple/parsimonious model presented here has the same issue of equifinality and parameter uncertainty as the more complex models? How does this affect the usefulness of the model or its applicability compared to the larger models? Or, should this model’s parameters be further simplified?
L317 – What is the evidence of strong correlation? This statement needs statistical support.
L341 – Temperate, not temperature.
Figure 5 – Can you provide a quantitative comparison of the means to support the conclusions?
Figure 6 – Why are only two depths shown in this figure? (there are 3 depths in the previous figure)
L357 – What are the cutoffs for NRC values to determine if they are strongly, moderately, or minimally sensitive in this analysis? I think that information should be included in the methods. In the discussion, it would be helpful to more quantitatively compare/describe the model sensitivity to these various parameters.
L359 – The fraction of aboveground residues incorporated is roughly as important as the clay content yet it is not mentioned here. I’m also unclear why the clay content is mentioned before the other more sensitive parameters in the table.
L367-370 – I would be interested to see this idea expanded upon – how does this USSF model result relate back to your model result of an 8% increase in SOM? And what are the larger implications of these increases for climate change mitigation as you mention? For example, how does a 1.4% increase over the course of 30 years compare to targeted goals for mitigation?
L379 – Here, the authors seem to consider a 4-5% reduction in SOM to be minor. But on lines 374 - 377 they seem to indicate that a 3-5% increase is significant. Some benchmarks for the relevance of these changes would be helpful for interpretation of the results.
L381 – Haddaway et al. found a difference by tillage intensity in the topsoil, as opposed to what is stated here. Intermediate intensity tillage resulted in greater SOC stocks than the high intensity tillage in that metanalysis.
L385 – It would be helpful to include empirical data supporting these model data on the figure for comparison with the model data. Or include the empirical data in a table caption.
Table 5 – It looks like this table was color coded according to the colors of the groups in table 3. That information and the meaning of the colors should be included in the caption.
Citation: https://doi.org/10.5194/egusphere-2024-3883-RC2 -
AC2: 'Reply on RC2', Elsa Coucheney, 03 Apr 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3883/egusphere-2024-3883-AC2-supplement.pdf
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AC2: 'Reply on RC2', Elsa Coucheney, 03 Apr 2025
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-3883', Anonymous Referee #1, 27 Feb 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3883/egusphere-2024-3883-RC1-supplement.pdf
-
AC1: 'Reply on RC1', Elsa Coucheney, 03 Apr 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3883/egusphere-2024-3883-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Elsa Coucheney, 03 Apr 2025
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RC2: 'Comment on egusphere-2024-3883', Anonymous Referee #2, 11 Mar 2025
This study describes a simple model of soil organic carbon (SOC) turnover that represents the effects of soil physical protection and microbial energy limitation. The paper first describes the model in a soil profile, then tests it using SOC data from a long-term study on agricultural fields with varied C inputs to the soils. Finally, the model’s most influential parameters were identified in a sensitivity and uncertainty analysis. Overall, the paper is well written and presents a model of interest and relevance to soil carbon management. Below, please find specific comments intended to help improve the paper.
L83 – Define the abbreviation USSF.
L91-95 – I would suggest ending the introduction with a strong thesis statement of what the paper contributes to current knowledge of the subject.
L97-101 – I appreciate this overview of the methods, very helpful to have this framework.
L103 – In section 2.1.1 that starts on this line, it is unclear if the model as described in this section is the work of the authors or if this is describing previously published work. If it has been previously published, I suggest including most of the equations in this section in a supplement rather than in the main document. In the main manuscript, I suggest describing the model in writing and including important equations for the modifications to the model that are new in the current study. Additionally, I would encourage the authors to post their full model code online and cite it in the paper.
L107-109 – It would be helpful to specify the direction of the relationship between these effects (e.g., Do smaller pores get fewer root derived inputs? Do micropores have lower decomposition rates?).
L125 – Is the “(-)” after fr,mic supposed to indicate that it is unitless?
L218 – How does this straw addition rate compare to the maize biomass per hectare?
L219 - 220 – Include the scientific names/varieties of the crops.
L220 - What is the purpose of hand digging the plots after harvest?
L 231 – What measurements were used for the calibration? Only OM or additional measurements? Calibrating to additional variables could help reduce equifinality.
L238 – Specify the field bulk density values used for this validation.
Table 1 – Are there field measurements available for any of these parameters? If so, how similar are they to these fixed values?
Figure 1 needs a legend to identify what the different colors/patterns of shading indicates.
Table 1 – Are there data references for these parameter values? If not, how did you come to these values?
Tables – I recommend including captions for tables with relevant details.
L264- What determined if the data support was sufficient?
Table 3 – The source “SCB Statistics Sweden” needs to be more specific. Same comment for source listed as “site data” - where are site data accessible? Year, dataset name, authors etc.
L304 - 306 – Is this distinction of straw going into only mesopores and root OM going partially into micropores supported by empirical data?
L308 – What is meant by “export of residues?” Does that mean the removal of residues by land managers?
Figure 3 – This panel figure needs letters for each panel and a description of each panel and the definition of the X axes in the figure caption.
Figure 4 – This panel figure also needs to have the individual panels labeled/described and the axes defined in the caption.
L314 – In the introduction, large mechanistic models are criticized for having uncertainty and equifinality. That was provided as justification for a simpler parsimonious model. How does that criticism relate to your finding that the simple/parsimonious model presented here has the same issue of equifinality and parameter uncertainty as the more complex models? How does this affect the usefulness of the model or its applicability compared to the larger models? Or, should this model’s parameters be further simplified?
L317 – What is the evidence of strong correlation? This statement needs statistical support.
L341 – Temperate, not temperature.
Figure 5 – Can you provide a quantitative comparison of the means to support the conclusions?
Figure 6 – Why are only two depths shown in this figure? (there are 3 depths in the previous figure)
L357 – What are the cutoffs for NRC values to determine if they are strongly, moderately, or minimally sensitive in this analysis? I think that information should be included in the methods. In the discussion, it would be helpful to more quantitatively compare/describe the model sensitivity to these various parameters.
L359 – The fraction of aboveground residues incorporated is roughly as important as the clay content yet it is not mentioned here. I’m also unclear why the clay content is mentioned before the other more sensitive parameters in the table.
L367-370 – I would be interested to see this idea expanded upon – how does this USSF model result relate back to your model result of an 8% increase in SOM? And what are the larger implications of these increases for climate change mitigation as you mention? For example, how does a 1.4% increase over the course of 30 years compare to targeted goals for mitigation?
L379 – Here, the authors seem to consider a 4-5% reduction in SOM to be minor. But on lines 374 - 377 they seem to indicate that a 3-5% increase is significant. Some benchmarks for the relevance of these changes would be helpful for interpretation of the results.
L381 – Haddaway et al. found a difference by tillage intensity in the topsoil, as opposed to what is stated here. Intermediate intensity tillage resulted in greater SOC stocks than the high intensity tillage in that metanalysis.
L385 – It would be helpful to include empirical data supporting these model data on the figure for comparison with the model data. Or include the empirical data in a table caption.
Table 5 – It looks like this table was color coded according to the colors of the groups in table 3. That information and the meaning of the colors should be included in the caption.
Citation: https://doi.org/10.5194/egusphere-2024-3883-RC2 -
AC2: 'Reply on RC2', Elsa Coucheney, 03 Apr 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3883/egusphere-2024-3883-AC2-supplement.pdf
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AC2: 'Reply on RC2', Elsa Coucheney, 03 Apr 2025
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Anke Marianne Herrmann
Nicholas Jarvis
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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