the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Jun 2025
Characterizing soil organic carbon spatial and seasonal variability using Rock-Eval and CO2/O2 fluxes measurements
Abstract. Soil organic matter (SOM) stores most of the terrestrial carbon, and changes in this storage can have a significant effect on the global carbon cycle. Various approaches have been used to understand the SOM transformations and stability. Here we tested the combination of two complementary approaches: 1) We estimated the long-term SOM stability, and the effect of decomposition on the stability and composition of the remaining fraction, by Rock-Eval pyrolysis. 2) We measured the respiratory CO2 and O2 fluxes, and their ratio (the Apparent Respiratory Quotient – ARQ) in soil incubations at different temperatures, to learn about the short-term processes. To study in detail the spatial and temporal variability, we examine soil samples from two sample sets: a regional set, and a local set that was used to study the seasonality and environmental variability within a site. The Rock-Eval analysis showed an effect of the slope aspect on SOM. The south-facing slope organic matter was more mature and stable. For the particulate organic matter fraction, we found an increase in O2 uptake rate with an increase in Hydrogen Index (HI), indicating that the respiration rates are higher when the reduced and easily degradable fraction is larger. The soil incubation experiments showed an increase in the ARQ values with temperature. This can be explained by higher respiration rates at high temperatures and the formation of anoxic microsites where electron acceptors alternative to O2 are used. This suggestion was supported by incubation of soil clods that at 23°C resulted in ARQ values >1, implying anerobic conditions, while the addition of O2 to the headspace lowered the ARQ. Based on additional experiments, we further suggest that incubations at low temperatures can reflect the history of the soil and indicate past anaerobic conditions that resulted in soil rich in reduced chemical species, resulting in a lower ARQ. This line of reasoning can explain the lower ARQ measured for soil sampled in winter, since high moisture content limits oxygen diffusion and creates anaerobic microsites. Combining the measurements of ARQ with Rock Eval pyrolysis can provide a more complete understanding of the state of the organic matter in the soil.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-2774', Anonymous Referee #1, 25 Jul 2025
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AC1: 'Reply on RC1', Tal Weiner, 20 Aug 2025
We thank the reviewer for the critical and detailed comments, which will significantly guide us in improving the manuscript. We have detailed below what action we plan to take in response to each comment.
RC1 comments, and suggested revision :
This manuscript explores the combination of CO2 and O2 flux measurements during incubations of soil samples from the Golan region with Rock-Eval analysis results to gain insight into the state of organic matter in the soil both spatially and on a seasonal variation scale. The idea is interesting, and so far, few articles have combined these two approaches. However, the manuscript is currently based on only two datasets that are difficult to link.
We agree that these two data sets describe different properties of the SOM. The flux measurements are closely linked to short-term response, while the Rock-Eval is linked to longer time scales. In our revised version, we will aim to make this distinction clearer.
The discussion of the results is highly speculative, with hypotheses that cannot really be debated in the absence of other data to link the Rock-Eval analyses and the incubation results.
The more speculative discussion parts will be removed.
It's a pity that the study doesn't include in situ gas exchange measurements to find out whether those made in vitro can really be transposed to the field. In terms of form, the manuscript is also open to criticism, at least because the uncertainties of the Rock-Eval parameters are neither given nor discussed. For instance, the accuracy of HI values is generally ± 10 mg HC/g TOC and ± 20 mg CO2/g TOC for OI. A difference of 0.02 in the RC/TOC ratio between north and south exposure (Table 6) is not significant, contrary to what is stated in the manuscript.
The significance level was reported based on the statistics of replicates. We will correct this to ”a small but statistically significant difference”.
As it stands, I suggest rejecting this manuscript, which requires additional data and a more detailed and argued discussion to deserve publication by Biogeosciences. The main weaknesses of this manuscript are listed below.
Some basic data are missing, including:
- The texture of the soils studied (proportion of clay, silt and sand fractions) and quantification of iron oxyhydroxides (which can contribute to oxygen consumption) should definitely be included in the site descriptions.
This data will be added to the revised manuscript.
- The authors examine the stability of organic matter according to a slope gradient. How steep is the slope gradient? The discussion assumes –in one sentence– that organic matter may be transferred to the slope (lines 417-418). Do field data support this hypothesis? Finally, in the summary, this hypothesis is presented as a result. As nothing has been demonstrated, this shift from an hypothesis to an assertion is not correct.
This data will be added. A previous paper about this site, which we will now cite and discuss, reported the rates of down-slope transfer:
Ben‐Asher, M., Haviv, I., Roering, J. J., & Crouvi, O. (2017). The influence of climate and microclimate (aspect) on soil creep efficiency: Cinder cone morphology and evolution along the eastern Mediterranean Golan Heights. Earth Surface Processes and Landforms, 42(15), 2649-2662.
- Were the 2 mm sieved soil samples dried before being wetened for ARQ analysis?
No. This data will be now added.
- For the Rock-Eval method, the start and end temperatures of the pyrolysis and oxidation phases must be given, as well as the heating ramp gradients.
This data will be added.
There is too much supplementary data, and not all are useful or well exploited in the manuscript. For example, a correlation between TOC and HI is shown (Fig. S3), which is expected since TOC is used to calculate HI. The same applies to the inverse correlation between the I- and R-index (Fig. S1), which is so by construction, if we refer to the definition of these indices by Sebag et al. (2016).
We will shorten the supplementary data to include only essential results.
Regarding the stability of organic matter, a paragraph on the state of the art would be welcome. There are numerous references on this subject, especially in the last two or three years. In fact, POM and MAOM fractions are not directly equivalent to the proportion of labile and stable fractions. Depending on the nature of the POM, some of it is stable, particularly if there are charcoal fragments. Regarding, the Rock-Eval method, the I- and R-index are useful for characterizing the lability and thermal stability of organic matter but do not allow for quantification. Other stability indices may be useful, such as the oven temperature when 50% of the effluents have been emitted during pyrolysis or oxidation (T50_HC or T50_CO2_ox from Soucémarianadin et al. 2018). A model (Cécillon et al., 2018, 2021 https://doi.org/10.5194/gmd-14-3879-2021) allows the proportion of stable carbon and active/labile carbon to be estimated.
We will add such paragraph, and discuss other indices.
On the results. Seasonal variations in TOC exceed 1%, i.e. more than 10gC/kg of soil or nearly 25% of the carbon stock, which seems a lot. Was density measured for each sample? This would confirm that the data comes from the same soil mass. Otherwise, there may have been variations in density leading to variations in sampling depth. In this case, the variation in TOC would result more from a depth effect than a seasonal effect. After each sample collection, did you weigh the initial soil mass and the mass after drying and sieving? With this data and the soil moisture content, it would be possible to recalculate a kind of ‘bulk density’ (dry mass/auger volume).
Indeed, the soil in this site is very shallow, and the top mineral soil layer (below the litter layer) can include varying amounts of fresh litter inputs. We will discuss this further in our revision. Sampling this stony, hard, and shallow soil caused disturbance of its structure. As a result, we do not have direct measurements of volume and hence bulk density.
On the seasonal variation, TOC values are lowest in February, and it is assumed in the discussion (lines 493-494) that this is due to increased precipitation. Although February is the coldest month in the Golan region (line 85), this does contradict ARQ data, which shows greater degradation at 23°C than at 5°C. Isn't water availability the most important factor?
In summer months, which lack precipitation, moisture is indeed the limiting factor. When the soil is wet, temperature plays an important role. We will include a discussion of this in the revised version.
If we extrapolate the in vitro mineralization flux over a period of five months (between October and February), what flux do we obtain, and is it in the same order of magnitude as the decrease in carbon stocks?
Yes, we did now such a calculation and it is indeed on the same order. This is an important point, and we will include this calculation and a discussion of it in the revised version.
Furthermore, we must question the ecological significance of these calculations and comparisons. The incubated soil is sieved, and therefore aerated and disturbed, and is therefore not at all realistic in terms of what happens in situ. Furthermore, only heterotrophic respiration is measured here, which tells us very little about the in situ balance resulting from inputs and other outputs (autotrophic respiration and leaching/lixiviation). Finally, the incubation experiments presented here are only meaningful for studying the sensitivity of microbial communities to temperature and humidity and for suggesting that there are seasonal shifts in the taxonomic (and/or functional) compositions of microbial communities.
We will add a discussion regarding this.
Discussion of the effect of anoxic microsites in ARQ experiments is highly speculative. As the soil conditions in the experiments are very different from those in situ, it's difficult to extrapolate what happens in vitro.
In the revised version, we will make sure to deal head-on with this issue.
Is it possible to acquire microtomographic images of these soils to calculate pore space descriptors?
No, unfortunately, this is not possible. See the comment above on the disturbance during sampling.
Some of the litter disappeared between October and February. It would have been useful to distinguish between these two pools and to carry out degradation experiments on the litter alone and on the soil without litter.
We did such experiments, and could run some more and include this data in the revised text.
As the authors point out, it is curious that the POMs do not exceed 7.1% TOC (Table 9), whereas POMs under forest cover usually have TOCs ranging from 10 to 40%. Have the POMs been scrutinized to identify the origin of the particles?
Indeed, this is not POM but mineral soil aggregates. We will include this data in the revision.
Citation: https://doi.org/10.5194/egusphere-2025-2774-AC1
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AC1: 'Reply on RC1', Tal Weiner, 20 Aug 2025
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RC2: 'Comment on egusphere-2025-2774', Anonymous Referee #2, 29 Jul 2025
Based on a series of soil incubation experiments the authors study multiple aspects influencing the apparent respiratory quotient (ARQ; calculated as the ratio of CO2 efflux to O2 uptake) including warming, moisture changes, aggregation (anoxia) and seasonality. The paper also includes a comparison of ARQ to results from Rock-Eval thermal analysis. Moreover, the authors study the relationship between soil organic matter composition (using POM-MAOM fractionation), Rock-Eval and ARQ. This topic could be of interest to BG readers, as it is a new contribution to an already existing discussion regarding the usefulness of this emerging tool (ARQ) for better understanding respiration. As similarly done by others before, (e.g., Hicks Pries et al., 2020, Vaziourakis et al., 2025) using ARQ in multi-method studies is key towards deciphering its drivers since it is a parameter influenced simultaneously by many biotic and abiotic factors. In my view, the main strength of this study is the amount of experimental work, that is very rich in results. Unfortunately, I found that the paper currently lacks structure, causing multiple problems. First, following the details of each experiment and the relevant arguments throughout the paper is challenging but second and more important, I found that there are problems in assessing the validity of the scientific approach due to both confusing parts and in some cases missing information. A clearer structure and explicit presentation of the aims, hypotheses, expectations, assumptions and limitations of each experiment could help resolve these issues. This study does not and probably will not resolve the question of co-occurring seasonal, temperature, substrate, etc., variability in ARQ but it could be a step towards understanding its response to changes in these parameters. However, in my view, it would first need to be majorly revised or even re-written.
Specific comments:
As stated above, one of the problems created by the lack of structure is that the validity of the scientific approach is unclear. Some points that are in urgent need of clarification in my opinion include:
- The description of elevation and slope aspect sampling is inadequate (line 105), and I couldn’t follow the results and their interpretation. What were the elevations, what were the distances between the sampled locations, were they identical between the two slopes? What is the number of true replicates? What does the statement in line 106 mean “on the southern slope, there were fewer samples under the tree canopy”? Is the comparison of vegetation type and slope even valid if the samples come from different land covers? Is that why in the results section, line 247 the comparison of R- and I-index between the two slopes is specific to the vegetation?
- The temperature effect on ARQ (Fig. 5) is obtained from incubations of drastically different durations, varying from 5 hours to 15 days. With the rate of respiration expected to vary during the incubation period, is the comparison of rates averaged over different periods valid? Isn’t there a correction needed according to the total amount of labile C consumed? In any case, a discussion of the assumptions would be again very helpful for the reader.
- Comparing Rock-Eval results to ARQ is the main novelty of this work as suggested by the title. Yet, although the two methods are fundamentally different and describe different fractions of SOM, the assumptions, expectations and limitations of this comparison are not discussed. The lack of attention to the time-scales of stability assessed by the methods becomes even more evident in the next section where ARQ obtained on the whole soil is compared to Rock-Eval results obtained on POM without assessing the size of this pool.
- Studying the effect of spatial variability and soil properties on ARQ is stated as a goal of this work in the abstract and introduction (line 75) and as a reason for the use of the regional set. Yet, this is not further discussed neither in the results nor in the discussion section. Was the initial objective was forgotten or changed? Instead in line 229 the regional set results are used to explain an increase in ARQ with temperature (I assume monthly?). It is hard to follow the argument here, seen how statistics are lacking, that in 3-5 out of 11 locations means are quite close to each other and in 2 locations (Dallawe and Hushania SE) it even looks like there was a decrease in October compared to January? It is unclear where these differences are coming from and why they are not discussed.
- What could be a strong point of this work is the use of Rock-Eval to assess influence of slope aspect and seasonal changes, since as far as I know this is the first study to attempt that. However, the strong seasonal variability in Rock-Eval parameters, especially TOC is quite alarming. Is there any other indication that SOC should fluctuate this much in the year? Could any other (management?) events be influencing this or could there be inconsistencies in soil sampling depth in February? At least in part, the lower TOC as well as higher HI and lower OI reported here could be very well explained by non-equivalent (deeper) soil sampling for example and dilution of (labile) C-rich topsoil with (more stabilized) C-poor subsoil.
- Moreover, there is a general lack of information about the use of the Rock-Eval technique. Without the name of the apparatus and the heating routine applied the experiment is not reproducible, and it is not clear how the results can be compared to other studies.
- Finally, regarding the use of the Rock-Eval method, another point that needs clarification in my opinion, is the choice of the used parameters and the fact that the focus is heavily on the HC signal in this study. Even though there is a general trend relating thermal and biogeochemical stability, different parameters correlate better or less well with different SOC pools. I think it would be important to define the scale of SOC stability that the chosen Rock-Eval parameters reflect (particularly the I and R-index, considering they are poorly correlated to centennially stable SOC; Cécillon et al., 2021).
- The introduction is missing clear objectives and hypotheses and how they were addressed by the conducted experiments. An easy solution would be to list them in the last introduction paragraph (and preferably keep the same order in the rest of the manuscript sections).
- Moreover, it would be useful to introduce the POM-MAOM fractionation and how it is related to this work, as well as the expected influence of the slope aspect, vegetation, elevation, and season on SOM quality, since these are in the focus of the conducted experiments.
- Table 1 is a good idea, as an effort to present a summary of the conducted experiments and used samples in each case. I would suggest adding more details to it and maybe splitting the last column to clearly titled ones such as aim, origin and number of samples (and expected outcome?). Alternatively, a schematic summary figure could also serve this purpose and could offer an even easier way to gain an overview of the work presented in the draft.
Technical corrections:
- In line 40 ARQ values of different substrates are given and the work of Masiello et al. (2008) is cited. In that paper however there is no mention of ARQ. I assume the authors calculated it from the oxidation state of organic carbon (COX) found in the referenced paper. As done in Hilman et al. (2022), I think it would be important to distinguish between theoretical and apparent RQ and then also explain why different numbers are given for the same substrates in the later and the current study.
- Equations for ARQ and Q10 are missing.
- In lines 43-49 of the introduction section references are needed.
- Line 60: Yes, not many studies combine Rock-Eval with CO2 measurements but there are a few more than cited here, that may be interesting also for the interpretation of the findings of this work; namely, Gregorich et al. (2015), Henneron et al. (2022) and Malou et al. (2023).
- 11 sites are mentioned in the regional set but excluding Mt Baron, only 7 locations are given on Fig.1 and 8 sets of coordinates in Table 2. Are there 11 sites or less? Would an additional term be useful to differentiate between sites and maybe “locations”?
- Figure 1: I think it is conventional to present maps with a north arrow and a scale.
- Section 2.3 ARQ: An estimate of the expected precision associated with the measurement of the two gases in this setup is missing.
- The units for HI and OI are missing as well as the definitions of Tmax and TpkS2.
- Lines 158-159: The provided formula for the calculation of I-index (temperature cuts for A peak areas) does not match the provided reference. In Sebag et al. (2006) I-index areas have different cuts than in Sebag et al. (2016). Which ones were used here?
- Generally, I think it would be useful to always mention on or under each figure, what the error bars represent, what is the n in each case and if they are currently missing, what are the units?
- Methods section 2.3 on the ARQ measurement could be improved in terms of language. I had to read this multiple times and go through results section to understand exactly what was done in the end.
- The supplementary material is very long, and the tables provided there (Tables S1-3) are not used. Similar for Fig. S2 but probably due to a typo in line 300?
- Supplementary material figures appear in a different order in the draft and in the supplementary material file. Figs. S5-7 appear in the text before Fig. S2 and S4, similar for Figs. S11-18.
- Starting at section 4.3., the final paragraphs of discussion are lacking references and results should be compared better to previous studies.
References:
Cécillon, L., Baudin, F., Chenu, C., Christensen, B. T., Franko, U., Houot, S., Kanari, E., Kätterer, T., Merbach, I., Van Oort, F., Poeplau, C., Quezada, J. C., Savignac, F., Soucémarianadin, L. N., & Barré, P. (2021). Partitioning soil organic carbon into its centennially stable and active fractions with machine-learning models based on Rock-Eval® thermal analysis (PARTYSOCv2.0 and PARTYSOCv2.0EU). Geoscientific Model Development, 14(6), 3879–3898. https://doi.org/10.5194/gmd-14-3879-2021
Gregorich, E. G., Gillespie, A. W., Beare, M. H., Curtin, D., Sanei, H., & Yanni, S. F. (2015). Evaluating biodegradability of soil organic matter by its thermal stability and chemical composition. Soil Biology and Biochemistry, 91, 182–191. https://doi.org/10.1016/j.soilbio.2015.08.032
Henneron, L., Balesdent, J., Alvarez, G., Barré, P., Baudin, F., Basile-Doelsch, I., Cécillon, L., Fernandez-Martinez, A., Hatté, C., & Fontaine, S. (2022). Bioenergetic control of soil carbon dynamics across depth. Nature Communications, 13(1), 7676. https://doi.org/10.1038/s41467-022-34951-w
Malou, O. P., Sebag, D., Moulin, P., Chevallier, T., Badiane-Ndour, N. Y., Thiam, A., & Chapuis-Lardy, L. (2020). The Rock-Eval® signature of soil organic carbon in arenosols of the Senegalese groundnut basin. How do agricultural practices matter? Agriculture, Ecosystems and Environment, 301(February), 107030. https://doi.org/10.1016/j.agee.2020.107030
Vaziourakis, K.-M., Heffernan, L., Jakobsson, E., Grasset, C., Kothawala, D., & Tranvik, L. (2025). Controls on the respiratory quotient of organic matter decomposition across ecosystems. Biogeochemistry, 168(2), 24. https://doi.org/10.1007/s10533-025-01217-8
Citation: https://doi.org/10.5194/egusphere-2025-2774-RC2 -
AC2: 'Reply on RC2', Tal Weiner, 20 Aug 2025
We thank the reviewer for the critical and detailed comments, which will significantly guide us in improving the manuscript. We have detailed below what action we plan to take in response to each comment.
RC2 comments, and suggested revision :
Based on a series of soil incubation experiments the authors study multiple aspects influencing the apparent respiratory quotient (ARQ; calculated as the ratio of CO2 efflux to O2 uptake) including warming, moisture changes, aggregation (anoxia) and seasonality. The paper also includes a comparison of ARQ to results from Rock-Eval thermal analysis. Moreover, the authors study the relationship between soil organic matter composition (using POM-MAOM fractionation), Rock-Eval and ARQ. This topic could be of interest to BG readers, as it is a new contribution to an already existing discussion regarding the usefulness of this emerging tool (ARQ) for better understanding respiration. As similarly done by others before, (e.g., Hicks Pries et al., 2020, Vaziourakis et al., 2025) using ARQ in multi-method studies is key towards deciphering its drivers since it is a parameter influenced simultaneously by many biotic and abiotic factors. In my view, the main strength of this study is the amount of experimental work, that is very rich in results. Unfortunately, I found that the paper currently lacks structure, causing multiple problems. First, following the details of each experiment and the relevant arguments throughout the paper is challenging but second and more important, I found that there are problems in assessing the validity of the scientific approach due to both confusing parts and in some cases missing information. A clearer structure and explicit presentation of the aims, hypotheses, expectations, assumptions and limitations of each experiment could help resolve these issues. This study does not and probably will not resolve the question of co-occurring seasonal, temperature, substrate, etc., variability in ARQ but it could be a step towards understanding its response to changes in these parameters. However, in my view, it would first need to be majorly revised or even re-written.
We will follow the authors suggestion for an overhaul revision.
Specific comments:
As stated above, one of the problems created by the lack of structure is that the validity of the scientific approach is unclear. Some points that are in urgent need of clarification in my opinion include:
- The description of elevation and slope aspect sampling is inadequate (line 105), and I couldn’t follow the results and their interpretation. What were the elevations, what were the distances between the sampled locations, were they identical between the two slopes? What is the number of true replicates? What does the statement in line 106 mean “on the southern slope, there were fewer samples under the tree canopy”? Is the comparison of vegetation type and slope even valid if the samples come from different land covers? Is that why in the results section, line 247 the comparison of R- and I-index between the two slopes is specific to the vegetation?
We will add this information.
- The temperature effect on ARQ (Fig. 5) is obtained from incubations of drastically different durations, varying from 5 hours to 15 days. With the rate of respiration expected to vary during the incubation period, is the comparison of rates averaged over different periods valid? Isn’t there a correction needed according to the total amount of labile C consumed? In any case, a discussion of the assumptions would be again very helpful for the reader.
Since the respiration rates are temperature dependent, the different durations are aimed to make the total amount of labile C consumed, and CO2 emitted, similar. We will add an explanation for this in the text.
- Comparing Rock-Eval results to ARQ is the main novelty of this work as suggested by the title. Yet, although the two methods are fundamentally different and describe different fractions of SOM, the assumptions, expectations and limitations of this comparison are not discussed. The lack of attention to the time-scales of stability assessed by the methods becomes even more evident in the next section where ARQ obtained on the whole soil is compared to Rock-Eval results obtained on POM without assessing the size of this pool.
We will add a discussion for this important point.
- Studying the effect of spatial variability and soil properties on ARQ is stated as a goal of this work in the abstract and introduction (line 75) and as a reason for the use of the regional set. Yet, this is not further discussed neither in the results nor in the discussion section. Was the initial objective was forgotten or changed?
Indeed, that was the original aim, but our analysis did not find spatial variability related to site parameters like. We will add this discussion to the revised manuscript.
Instead in line 229 the regional set results are used to explain an increase in ARQ with temperature (I assume monthly?). It is hard to follow the argument here, seen how statistics are lacking, that in 3-5 out of 11 locations means are quite close to each other and in 2 locations (Dallawe and Hushania SE) it even looks like there was a decrease in October compared to January? It is unclear where these differences are coming from and why they are not discussed.
We will discuss and make this clearer in the revised version.
- What could be a strong point of this work is the use of Rock-Eval to assess influence of slope aspect and seasonal changes, since as far as I know this is the first study to attempt that. However, the strong seasonal variability in Rock-Eval parameters, especially TOC is quite alarming. Is there any other indication that SOC should fluctuate this much in the year? Could any other (management?) events be influencing this or could there be inconsistencies in soil sampling depth in February? At least in part, the lower TOC as well as higher HI and lower OI reported here could be very well explained by non-equivalent (deeper) soil sampling for example and dilution of (labile) C-rich topsoil with (more stabilized) C-poor subsoil.
This is a very important point. We discussed this above in the answer to RC1 about the possibility of fresh litter addition to this shallow soil, and in our new calculation, which showed that respiration-based carbon loss is in the same order of magnitude as RockEval-based seasonal change. This calculation will be detailed and discussed in the next manuscript version.
- Moreover, there is a general lack of information about the use of the Rock-Eval technique. Without the name of the apparatus and the heating routine applied the experiment is not reproducible, and it is not clear how the results can be compared to other studies.
This data will be added in the revised manuscript
- Finally, regarding the use of the Rock-Eval method, another point that needs clarification in my opinion, is the choice of the used parameters and the fact that the focus is heavily on the HC signal in this study. Even though there is a general trend relating thermal and biogeochemical stability, different parameters correlate better or less well with different SOC pools. I think it would be important to define the scale of SOC stability that the chosen Rock-Eval parameters reflect (particularly the I and R-index, considering they are poorly correlated to centennially stable SOC; Cécillon et al., 2021).
We will discuss the limitations of these indices and include other ones in the revised version.
- The introduction is missing clear objectives and hypotheses and how they were addressed by the conducted experiments. An easy solution would be to list them in the last introduction paragraph (and preferably keep the same order in the rest of the manuscript sections).
This will be corrected and added in the revision.
- Moreover, it would be useful to introduce the POM-MAOM fractionation and how it is related to this work, as well as the expected influence of the slope aspect, vegetation, elevation, and season on SOM quality, since these are in the focus of the conducted experiments.
We will add this in the revision.
- Table 1 is a good idea, as an effort to present a summary of the conducted experiments and used samples in each case. I would suggest adding more details to it and maybe splitting the last column to clearly titled ones such as aim, origin and number of samples (and expected outcome?). Alternatively, a schematic summary figure could also serve this purpose and could offer an even easier way to gain an overview of the work presented in the draft.
We will add this in the revision.
Technical corrections:
All the technical corrections will be addressed in the revised version.
- In line 40 ARQ values of different substrates are given and the work of Masiello et al. (2008) is cited. In that paper however there is no mention of ARQ. I assume the authors calculated it from the oxidation state of organic carbon (COX) found in the referenced paper. As done in Hilman et al. (2022), I think it would be important to distinguish between theoretical and apparent RQ and then also explain why different numbers are given for the same substrates in the later and the current study.
- Equations for ARQ and Q10 are missing.
- In lines 43-49 of the introduction section references are needed.
- Line 60: Yes, not many studies combine Rock-Eval with CO2measurements but there are a few more than cited here, that may be interesting also for the interpretation of the findings of this work; namely, Gregorich et al. (2015), Henneron et al. (2022) and Malou et al. (2023).
- 11 sites are mentioned in the regional set but excluding Mt Baron, only 7 locations are given on Fig.1 and 8 sets of coordinates in Table 2. Are there 11 sites or less? Would an additional term be useful to differentiate between sites and maybe “locations”?
- Figure 1: I think it is conventional to present maps with a north arrow and a scale.
- Section 2.3 ARQ: An estimate of the expected precision associated with the measurement of the two gases in this setup is missing.
- The units for HI and OI are missing as well as the definitions of Tmax and TpkS2.
- Lines 158-159: The provided formula for the calculation of I-index (temperature cuts for A peak areas) does not match the provided reference. In Sebag et al. (2006) I-index areas have different cuts than in Sebag et al. (2016). Which ones were used here?
- Generally, I think it would be useful to always mention on or under each figure, what the error bars represent, what is the n in each case and if they are currently missing, what are the units?
- Methods section 2.3 on the ARQ measurement could be improved in terms of language. I had to read this multiple times and go through results section to understand exactly what was done in the end.
- The supplementary material is very long, and the tables provided there (Tables S1-3) are not used. Similar for Fig. S2 but probably due to a typo in line 300?
- Supplementary material figures appear in a different order in the draft and in the supplementary material file. Figs. S5-7 appear in the text before Fig. S2 and S4, similar for Figs. S11-18.
- Starting at section 4.3., the final paragraphs of discussion are lacking references and results should be compared better to previous studies.
References:
Cécillon, L., Baudin, F., Chenu, C., Christensen, B. T., Franko, U., Houot, S., Kanari, E., Kätterer, T., Merbach, I., Van Oort, F., Poeplau, C., Quezada, J. C., Savignac, F., Soucémarianadin, L. N., & Barré, P. (2021). Partitioning soil organic carbon into its centennially stable and active fractions with machine-learning models based on Rock-Eval® thermal analysis (PARTYSOCv2.0 and PARTYSOCv2.0EU). Geoscientific Model Development, 14(6), 3879–3898. https://doi.org/10.5194/gmd-14-3879-2021
Gregorich, E. G., Gillespie, A. W., Beare, M. H., Curtin, D., Sanei, H., & Yanni, S. F. (2015). Evaluating biodegradability of soil organic matter by its thermal stability and chemical composition. Soil Biology and Biochemistry, 91, 182–191. https://doi.org/10.1016/j.soilbio.2015.08.032
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Citation: https://doi.org/10.5194/egusphere-2025-2774-RC2
Citation: https://doi.org/10.5194/egusphere-2025-2774-AC2
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- 1
This manuscript explores the combination of CO2 and O2 flux measurements during incubations of soil samples from the Golan region with Rock-Eval analysis results to gain insight into the state of organic matter in the soil both spatially and on a seasonal variation scale. The idea is interesting, and so far, few articles have combined these two approaches. However, the manuscript is currently based on only two datasets that are difficult to link. The discussion of the results is highly speculative, with hypotheses that cannot really be debated in the absence of other data to link the Rock-Eval analyses and the incubation results. It's a pity that the study doesn't include in situ gas exchange measurements to find out whether those made in vitro can really be transposed to the field. In terms of form, the manuscript is also open to criticism, at least because the uncertainties of the Rock-Eval parameters are neither given nor discussed. For instance, the accuracy of HI values is generally ± 10 mg HC/g TOC and ± 20 mg CO2/g TOC for OI. A difference of 0.02 in the RC/TOC ratio between north and south exposure (Table 6) is not significant, contrary to what is stated in the manuscript. As it stands, I suggest rejecting this manuscript, which requires additional data and a more detailed and argued discussion to deserve publication by Biogeosciences. The main weaknesses of this manuscript are listed below.
Some basic data are missing, including:
There is too much supplementary data, and not all are useful or well exploited in the manuscript. For example, a correlation between TOC and HI is shown (Fig. S3), which is expected since TOC is used to calculate HI. The same applies to the inverse correlation between the I- and R-index (Fig. S1), which is so by construction, if we refer to the definition of these indices by Sebag et al. (2016).
Regarding the stability of organic matter, a paragraph on the state of the art would be welcome. There are numerous references on this subject, especially in the last two or three years. In fact, POM and MAOM fractions are not directly equivalent to the proportion of labile and stable fractions. Depending on the nature of the POM, some of it is stable, particularly if there are charcoal fragments. Regarding, the Rock-Eval method, the I- and R-index are useful for characterizing the lability and thermal stability of organic matter but do not allow for quantification. Other stability indices may be useful, such as the oven temperature when 50% of the effluents have been emitted during pyrolysis or oxidation (T50_HC or T50_CO2_ox from Soucémarianadin et al. 2018). A model (Cécillon et al., 2018, 2021 https://doi.org/10.5194/gmd-14-3879-2021) allows the proportion of stable carbon and active/labile carbon to be estimated.
On the results. Seasonal variations in TOC exceed 1%, i.e. more than 10gC/kg of soil or nearly 25% of the carbon stock, which seems a lot. Was density measured for each sample? This would confirm that the data comes from the same soil mass. Otherwise, there may have been variations in density leading to variations in sampling depth. In this case, the variation in TOC would result more from a depth effect than a seasonal effect. After each sample collection, did you weigh the initial soil mass and the mass after drying and sieving? With this data and the soil moisture content, it would be possible to recalculate a kind of ‘bulk density’ (dry mass/auger volume).
On the seasonal variation, TOC values are lowest in February, and it is assumed in the discussion (lines 493-494) that this is due to increased precipitation. Although February is the coldest month in the Golan region (line 85), this does contradict ARQ data, which shows greater degradation at 23°C than at 5°C. Isn't water availability the most important factor?
If we extrapolate the in vitro mineralization flux over a period of five months (between October and February), what flux do we obtain, and is it in the same order of magnitude as the decrease in carbon stocks? Furthermore, we must question the ecological significance of these calculations and comparisons. The incubated soil is sieved, and therefore aerated and disturbed, and is therefore not at all realistic in terms of what happens in situ. Furthermore, only heterotrophic respiration is measured here, which tells us very little about the in situ balance resulting from inputs and other outputs (autotrophic respiration and leaching/lixiviation). Finally, the incubation experiments presented here are only meaningful for studying the sensitivity of microbial communities to temperature and humidity and for suggesting that there are seasonal shifts in the taxonomic (and/or functional) compositions of microbial communities.
Discussion of the effect of anoxic microsites in ARQ experiments is highly speculative. As the soil conditions in the experiments are very different from those in situ, it's difficult to extrapolate what happens in vitro. Is it possible to acquire microtomographic images of these soils to calculate pore space descriptors?
Some of the litter disappeared between October and February. It would have been useful to distinguish between these two pools and to carry out degradation experiments on the litter alone and on the soil without litter.
As the authors point out, it is curious that the POMs do not exceed 7.1% TOC (Table 9), whereas POMs under forest cover usually have TOCs ranging from 10 to 40%. Have the POMs been scrutinized to identify the origin of the particles?