Three-Dimensional Modeling of Soil Organic Carbon Stocks in Forest Ecosystems of Northeastern China Under Future Climate Warming Scenarios

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

I made some of the observations, and the same are mentioned in the attached file.

1. The title of the MS needs more clarity, so the same can be modified.
2. There is a need to add the previous estimates of SOC stocks from China. Moreover, the global carbon budget can be added in the introduction section, so the section looks more attractive to the global readership. 
3. The approach used space for time substitution needs more literature in terms of reliability and uncertainties. 
4. The map showing sample points says that no samples were collected from the northern and western parts. pls explain why?
5. Also, if any studies have been done in that region on SOC estimation, pls add them also. It will provide an idea of the locals' estimates of the SOC. 
6. reference section needs to be updated with recent studies.

Comments for author File: Comments.pdf

Author Response

I made some of the observations, and the same are mentioned in the attached file.

Response: We appreciate your help and your patience. With this submission, we provided a version (marked) of the revised manuscript.

 

1. The title of the MS needs more clarity, so the same can be modified.

Response: We have modified the title to “Three-Dimensional Modeling of Soil Organic Carbon Stocks in Forest Ecosystems of Northeastern China under Future Climate Warming Scenarios”. Title

 

2. There is a need to add the previous estimates of SOC stocks from China. Moreover, the global carbon budget can be added in the introduction section, so the section looks more attractive to the global readership.

Response: Based on your comment, we have supplemented our global and Chinese SOC stocks estimates. L47-51

 

3. The approach used space for time substitution needs more literature in terms of reliability and uncertainties.

Response: Based on your comment, we have made additional revisions. L350-352, 783-792.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The work is of great interest, since the study of soil carbon is currently at the peak of popularity. This makes this study even more in demand, since it summarizes a significant amount of information and very good statistical analysis.
The article is of great interest, contains interesting scientific data. The material is processed using modern methods. A huge amount of information has been analyzed, which can further serve as a basis for research and monitoring. The authors also set new goals for themselves and leave a reserve for further research in this area.
Several suggestions:
1. Table 2 can be made smaller and not compare the correlations between all the parameters studied. It will be enough to correlate only carbon stocks with ELE, SG, SA, CA, PC, TWI, MAT, MAP, NDVI, Clay, Silt

2. Figures 3, 4 and 5 are very good, provide a lot of information, but it is difficult for a non-professional eye to see the differences between the polygons. Is it possible to focus only on the most contrasting cases of changes in SOC during warming?

3. In conclusion, it is worth repeating the hypothesis that you relied on when conducting the study and showing what happened, what might be worth improving.

In general, the work is very important for the scientific advancement of model experiments on studying global warming and changes in organic carbon in soils.

Author Response

Reviewer 2: 

 

The work is of great interest, since the study of soil carbon is currently at the peak of popularity. This makes this study even more in demand, since it summarizes a significant amount of information and very good statistical analysis.

The article is of great interest, contains interesting scientific data. The material is processed using modern methods. A huge amount of information has been analyzed, which can further serve as a basis for research and monitoring. The authors also set new goals for themselves and leave a reserve for further research in this area.

Response: We appreciate your help and your patience. With this submission, we provided a version (marked) of the revised manuscript.

 

Several suggestions:

1. Table 2 can be made smaller and not compare the correlations between all the parameters studied. It will be enough to correlate only carbon stocks with ELE, SG, SA, CA, PC, TWI, MAT, MAP, NDVI, Clay, Silt

Response: Based on your comments, we have made modifications to Table 2. Table 2

 

 

2. Figures 3, 4 and 5 are very good, provide a lot of information, but it is difficult for a non-professional eye to see the differences between the polygons. Is it possible to focus only on the most contrasting cases of changes in SOC during warming?

Response: Based on your comments, we have made modifications to Figures 3, 4, and 5. Figures 3, 4, and 5.

3. In conclusion, it is worth repeating the hypothesis that you relied on when conducting the study and showing what happened, what might be worth improving.

Response: Based on your comment, we have revised the conclusion. See the Conclusion

4. In general, the work is very important for the scientific advancement of model experiments on studying global warming and changes in organic carbon in soils.

Response: We appreciate your help and your patience.

 

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This study investigates the application of three-dimensional modeling to predict soil organic carbon (SOC) stocks in forest ecosystems. Pedological, topographical, climatic, and biological factors were used in a Random Forest (RF) model to predict SOC stocks at various soil depths. Although SOC stock modeling is a widely studied topic, many studies focus only on the surface soil horizons, neglecting deeper layers. In the present study, SOC stocks are also predicted at greater soil depths, taking into account the increase in temperature due to climate change. The manuscript is well-written and well-organized; however, some clarifications and modifications are necessary regarding the methodological approach and the presentation of the results.

Comments for author File: Comments.pdf

Author Response

Reviewer 3: 

This study investigates the application of three-dimensional modeling to predict soil organic carbon (SOC) stocks in forest ecosystems. Pedological, topographical, climatic, and biological factors were used in a Random Forest (RF) model to predict SOC stocks at various soil depths. Although SOC stock modeling is a widely studied topic, many studies focus only on the surface soil horizons, neglecting deeper layers. In the present study, SOC stocks are also predicted at greater soil depths, taking into account the increase in temperature due to climate change. The manuscript is well-written and well-organized; however, some clarifications and modifications are necessary regarding the methodological approach and the presentation of the results.

Response: We appreciate your help and your patience. With this submission, we provided a version (marked) of the revised manuscript.

 

 

1. Please continue the phrase on line 85. Do you mean support vector machine?

Response: Based on your comment, we have made modifications. L89-90

 

2. Table 1 reports the descriptive statistics of the SOC stock values and the parameters used in the RF model. I also suggest including the soil parameters (SOC concentration and BD) used for SOC stock calculation.

Response: Based on your comment, we have supplemented Table 1. Table 1

 

3. Table 3 reports the results of the RF model application across depth. Given the LCCC values, how can the model's predictive capability be described as strong or excellent at all depths when the highest R² value is 0.54?

Response: Based on your comments, we have made revisions to the manuscript. L408-419

 

1）Table 1 shows how SOC stock values increase with soil depth. However, Figure 3 shows a decrease in SOC stock with increasing depth for all temperature scenarios. How can this discrepancy between the measured and predicted SOC stock values and trends be explained?

Response: The observed forest soil SOC stocks in Table 1 with increasing depth may reflect the unique soil characteristics of the region, such as deep organic matter input, mineral protection, or historical disturbances. However, the warming simulation in Figure 3 predicts that SOC decreases with depth, following a general pattern of active surface carbon input and limited deep decomposition. This discrepancy could potentially arise from two main factors: (1) field observations capturing local-specific factors (e.g., deep root distribution or mineral-organic matter interactions), whereas the model relies on generalized assumptions; (2) the warming simulation highlights the temperature-driven acceleration of decomposition, while actual soil conditions may involve deep physical and chemical protective mechanisms that mitigate the effects of temperature. To reconcile these differences in the future, it will be essential to refine the model's parameterization by integrating site-specific soil processes. We have also made corresponding supplements in the manuscript. L570-583

2）It is probably not suitable to use the same RF model for all soil layers, as indicated by the R² values in Table 3. Have you tried including only the pedological, topographic, climatic and biological parameters that are significantly correlated with SOC stock values in the RF model? The correlation matrix may be able to guide you through this process.

Response:We attempted to include only pedological, topographic, climatic and biological parameters that were significantly correlated with SOC stock values in the RF model, but their accuracy did not improve significantly. On the contrary, the accuracy decreased, so we did not select significantly correlated variables for model construction. We have supplemented this section in the manuscript. L426-431

 

5. The soil profiles studied belong to different soil orders and the trend in SOC stocks at different depths is certainly due to factors correlated with soil types. Most of the studied soil profiles have been classified as Cambisols, which are characterised by an alteration horizon, but not a marked accumulation of materials; therefore, they can exhibit heterogeneous characteristics. Using a greater number of pedological parameters may make the RF model more robust, especially at greater depths. You partly explain this in the discussion section, but I think it is important to corroborate these findings.

Response: Based on your comments, we have supplemented the manuscript. L544-557

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

Thank you for your comprehensive and thoughtful responses to the initial round of review. In my assessment, the revisions you have made, particularly regarding the methodological aspects and the presentation of the results, are appropriate. That said, I encourage you to further refine the description of the experimental design for greater clarity and reproducibility. Additionally, improving the quality of the SOC stock prediction images would enhance the overall presentation of the results.

Author Response

 

Reviewer 3: 

1. Thank you for your comprehensive and thoughtful responses to the initial round of review. In my assessment, the revisions you have made, particularly regarding the methodological aspects and the presentation of the results, are appropriate. That said, I encourage you to further refine the description of the experimental design for greater clarity and reproducibility.

Response: We appreciate your help and your patience. Based on your comment, we have added a flowchart of the methodology. to enable other scholars to replicate. L362-364, Figure 2 

 

2. Additionally, improving the quality of the SOC stock prediction images would enhance the overall presentation of the results.

Response: Based on your comment, We have made modifications to Figures 5  Figures 5 and 6.

 

 

Author Response File: Author Response.docx