the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Oct 2025
Modelling root exudation and plant-microbe interactions under CO2 fertilization in a mature forest
Abstract. Root exudation, defined as labile carbon (C) allocation into soils through fine roots, is a substantial yet often overlooked pathway of the terrestrial carbon cycle. Root exudation is likely to increase under rising levels of atmospheric CO2, but the implications of the increase in this flux are poorly understood. Increased labile C availability in soils may stimulate microbial growth and increase soil carbon storage but at the same time microbial nutrient acquisition could offset this accumulation by enhanced decomposition of soil organic matter
Here, we implement a dynamic representation of root exudation based on plant surplus carbon and nutrient limitation in the microbial explicit terrestrial biosphere model QUINCY-JSM (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system). We evaluate the effect of elevated CO2 on root exudation and its consequences for microbial C, nitrogen (N) and phosphorus (P) cycling using observations from the Eucalyptus Free Air CO2 Enrichment (EucFACE) experiment in a soil phosphorus impoverished forest. In the experiment, more than half of additional gross primary productivity (GPP) under elevated CO2 (eCO2) could not be assigned to a measured vegetation flux.
With the explicit implementation of root exudation, our model predicted that elevated CO2 caused an increase in belowground carbon flux and an increase in microbial growth, but a limited effect on soil carbon storage. Root exudation was increased to 30 %, but more than half of this additional input was directly respired by microbes. As a result, root exudation gives a possible explanation for the not measured vegetation flux and the enhanced heterotrophic respiration under eCO2 observed in the experiment. Increased C input through root exudation also enhanced microbial growth, but in order to support this growth, microbes mostly gained nutrients from decomposition and mineralization of organic matter. As a consequence, increased decomposition negated build-up of microbial necromass. Our study emphasizes the role of root exudation and microbial activity for soil carbon sequestration under elevated CO2 and guides further research regarding plant-microbe interactions.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Biogeosciences.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-4286', Anonymous Referee #1, 22 Nov 2025
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AC1: 'Reply on RC1', Kristian Schufft, 04 Feb 2026
The reviewer comments are in bold, and the replies in regular font.
This manuscript presents an interesting and timely study that contributes to the overall understanding of carbon allocation and transfer via root exudates, and how these processes interact with nutrient cycling under elevated CO₂. The work highlights the importance of root exudation from a modelling perspective and provides valuable recommendations for improving the representation of root exudation, microbial dynamics, and plant-microbe interactions in global ecosystem models.
The authors implemented a dynamic root exudation module within the QUINCY-JSM model and applied it to the EucFACE experiment, a P-limited mature eucalypt forest. The goal of quantifying competing soil mechanisms that regulate carbon storage under changing root exudation fluxes at elevated CO₂ is both relevant and timely, particularly given the current uncertainties surrounding belowground carbon dynamics and their coupling to nutrient availability under future conditions. The model appears to be a meaningful advancement in simulating carbon and nutrient dynamics by explicitly incorporating exudation fluxes. Although the exudation flux is not validated, I appreciate that the authors transparently discuss model limitations and outline thoughtful directions for future development.
We thank referee 1 for taking the time to read our manuscript and acknowledge the advancements of our manuscript. We appreciate the detailed feedback, which will help us to improve the manuscript.
Major Comments
- Focus and structure of results: The results section is very detailed, and at times it is difficult to see how each subsection directly contributes to addressing the central research aim. To improve readability and narrative coherence, I recommend focusing the main text on the findings that directly support the study’s objectives and relocating more descriptive or tangential results to the supplementary information.
We thank the reviewer for this observation. We will revise the figure items and readability of the results section to ensure that we focus on the research questions. Additional information that is useful for understanding but less relevant for the narrative will be moved towards the supplement.
Clarity of terminology: Several key terms are used inconsistently or remain insufficiently defined. For example, “C sequestration” is not clearly specified—does this refer to plant biomass, soil carbon, or both? Please clarify terminology throughout.
We thank the reviewer for this observation. While revising our manuscript we will ensure that we clearly define carbon sequestration throughout the manuscript.
Introduction, structure, and research gap: The introduction would benefit from clearer structuring. Some sections are heavily process-oriented without sufficiently linking these processes to the specific research gaps the study aims to address. In particular, a clearer explanation of how belowground carbon allocation fits into the forest carbon cycle – and how it connects to NPP or GPP under elevated CO₂ - would strengthen the rationale for the study.
We thank the reviewer for this helpful suggestion. We will pay attention to this when rewriting the manuscript and ensure that the sections are balanced and provide a clear link to our research focus on forest productivity under elevated CO2.
Mechanisms for soil carbon sequestration: The paragraph outlining mechanisms contributing to soil carbon sequestration requires revision, as several points are unclear or insufficiently explained (see specific line comments).We thank the referee for pointing out inconsistencies within this specific paragraph. When revising the manuscript we will improve the clarity and provide more explanations. See also our answers on specific line comments below.
Grammar and style: Please ensure the manuscript is carefully revised for grammar, typos, and general language clarity.We thank the reviewer for this observation. We will ensure that the revised manuscript will be thoroughly checked for grammar, typos, and language clarity.
Overall, this is a valuable and timely contribution that substantially advances modeling efforts related to root exudation and belowground carbon–nutrient interactions. With improved focus, clearer terminology, and a more structured introduction, the manuscript will be significantly strengthened.
We thank the reviewer for this positive feedback and the helpful comments.
Specific line comments:
We will implement below suggestions as far as the comments have not been resolved by a restructuring of the respective sentence/paragraph. We provide comments where further explanation is needed.
L28: If the study anticipated that root exudation would play a key role here, please state this explicitly, as it would help clarify the motivation behind the work.
- Agreed. We will revise this.
L35–36: This conclusion appears too weak, given the strength of the results. One key outcome seems to be that incorporating exudate C fluxes into forest C budgets under elevated CO₂ improves the precision of GPP estimates—shouldn’t this be highlighted?
- Agreed. We will add this to the abstract.
L57: This sentence is incomplete and needs revision.
- Agreed. We will revise this.
L70: Does this statement imply a shift in carbon use efficiency? Please clarify.
- Yes, this refers to shifts in microbial carbon use efficiency based on nutrient availability. We will revise the text for clarification.
L72–77: This passage is highly speculative. As phrased, it describes a natural process; larger microbial biomass will, of course, generate more necromass. This could be more clearly integrated into point (i): exudates regulate microbial biomass, which in turn influences necromass production.
- We thank the reviewer for this observation. We tried to convey that respiration of root exudation (based on microbial CUE) and necromass build up are two different processes. We agree that both processes depend on microbial growth and will revise the text to make this clearer.
L84–88: Is this describing a specific scenario? Please clarify how this relates to mechanisms promoting soil C sequestration.
- We describe the process of biochemical mineralization, by which microbes (and plants) are able to acquire P without depolymerisation of microbial necromass. This is especially relevant in the scenario of microbial P limitation and represents a pathway which does not exist under microbial N limitation. We will ensure that this linkage is clarified in the revised manuscript.
L92: Why are FACE sites considered “low-disturbance”? Please justify or clarify this statement.
- We referred to FACE experiments as low-disturbance since after establishment, vegetation is not removed from the experiment and soil conditions are kept as close to the original conditions as possible. However, the experiment is still subject to natural disturbances by climate, and the infrastructure and its construction itself is some form of disturbance, in particular at the start of the experiment. We thank the reviewer for questioning the terminology here, and will remove the term:”low-disturbance” in the revised manuscript as it may be unnecessarily misleading at this point.
L97: Please repeat or clarify the explanation here; the meaning is currently unclear.
- We will revise this.
L111–117: This seems to be methodological information and may fit better in the Methods section.
- We thank the reviewer for this observation. However, we believe that the description of our methodological approach and the study site is necessary here to to understand the research questions.. In the revised manuscript, we will shorten this part and move parts of it into the method section to improve readability.
L120–122: This information requires appropriate references.
- We will revise this and add the reference Jiang et al (2020).
L122–123: Please explain “surplus” and “vegetation flux” more clearly. How do these terms connect to exudation processes and soil C sequestration?
- Agreed. We will revise this. We will rephrase “surplus” into “additional” and clarify “vegetation flux”
L138: Please define what is meant by “dynamic root exudation.”
- Agreed. We refer to root exudation based on plant nutrient and labile C surplus status. We use the term “dynamic” to differentiate from approaches that use a fixed percentage of GPP/NPP. We will revise the sentence to clarify this.
L141: The phrasing is awkward; a model cannot “decompose” something. Please rephrase.
- Agreed. We will revise this.
L144-157: This section reads like a procedural description, yet this is where one would expect the research aim, plus research questions or hypotheses. Please revise accordingly.
- Agreed. We will revise this.
L154: Is it possible to describe in this section how the model was used for this study, not how the model functions in general?
- We thank the reviewer for this observation. We think that a general model description is necessary and an important part of the methodology. We explain in section 2.4. model application in more detail how we used the model for this particular study. To improve readability, and to account for this concern, we will move section 2.4 before the model description in the revised manuscript.
L172: How do the soil layers in the model correspond to actual soil horizons, especially given the podsolic profile with strong vertical heterogeneity?
- The model does not explicitly model soil horizons and cannot reproduce the strong vertical heterogeneity. However our model simulates vertical heterogeneity by explicitly calculating C,N and P dynamics on different soil layers. There are 15 soil layers reflecting to 9.5 m depth, from which 6 layers represent the top 50 cm (in manuscript defined as topsoil). In our simulations we adjusted the model by using sand, silt and clay fractions measured at the experiment. Additionally we reduced P content in lower soil layers and reduced maximum sorption capacity of organic matter to fine soil particles to adjust for the weathered soils. Furthermore even between the rings of the experiment there is strong variation.
L225: Please justify how well supported the assumption is that exudate C: N reflects the C: N of the labile soil pool.
- We thank the reviewer for this observation. This was in fact a typo and we meant to say that the exudate C:N ratio reflects the C:N ratio of the current plant labile pool. We will revise the sentence.
L310–313: I cannot evaluate the technical accuracy, but as written, the logic is unclear. Please check and revise for coherence.
- Agreed. We will revise this.
L225: The assumption that exudates contain no P is incorrect. Several known exudates contain phosphorus. This should be reconsidered.
- We thank the reviewer for this observation. We agree and will revise the sentence. We assume that the majority of root exudates are sugars, amino-acids and carboxylates, and therefore focus on modelling C and N exudation. Nonetheless, there are root exudates which contain P and we will add this topic as a model uncertainty in the discussion and for potential future refinement.
L233: Does this imply that a lower amount of root branches exude less simply because they exhibit less growth? How well does this assumption reflect empirical field observations?
- In QUINCY-JSM we do not model root branching. To a specific range less root growth might reflect an increase in plant labile C pools and may therefore result in higher exudation rates. However, ultimately, root exudation is bound to root biomass distribution across the soil profile (more precise root N content). We currently lack observations to model specific exudation rates based on different soil depth. We are aware that this is a debatable assumption and contributes to the uncertainty of the model results. Please see our response to reviewer 2 on this point.
L255: Please clarify what “saturation” refers to in this context.
- Agreed. We will revise this.
L316: Again, how accurately does this separation represent actual soil horizons?
- See top comment.
L390: This figure and also the other figures in the manuscript would benefit from improved clarity, for example, by reducing the number of abbreviations and making the x-axis description clearer.
- Agreed. We will revise this.
L410: It may be worthwhile to discuss whether implementing microbial non-growth anabolism in the model would be appropriate.
- We thank the reviewer for this observation. We have explicitly decided not to implement non-growth anabolism as it is not suitable for our model. The model assumes a quasi-steady-state approximation of enzyme dynamics, to reduce complexity. This has been discussed in detail in Wutzler et al. (2022).
L646: Would using in-situ root exudates to extract plant-available P yield more realistic results than the Hedley extraction?
- We agree that artificial root systems may be more suited to evaluate the plant P availability and the direct interaction between root exudation and plant-available PO4. However it remains to be discussed if this method can actually reproduce root zone activity. We mention Hedley fractions here as they are commonly used and available.
additional references
Jiang, M., Medlyn, B. E., Drake, J. E., Duursma, R. A., Anderson, I. C., Barton, C. V. M., Boer, M. M., Carrillo, Y., Castañeda-Gómez, L., Collins, L., Crous, K. Y., De Kauwe, M. G., dos Santos, B. M., Emmerson, K. M., Facey, S. L., Gherlenda, A. N., Gimeno, T. E., Hasegawa, S., Johnson, S. N., Kännaste, A., Macdonald, C. A., Mahmud, K., Moore, B. D., Nazaries, L., Neilson, E. H. J., Nielsen, U. N., Niinemets, Ü., Noh, N. J., Ochoa-Hueso, R., Pathare, V. S., Pendall, E., Pihlblad, J., Piñeiro, J., Powell, J. R., Power, S. A., Reich, P. B., Renchon, A. A., Riegler, M., Rinnan, R., Rymer, P. D., Salomón, R. L., Singh, B. K., Smith, B., Tjoelker, M. G., Walker, J. K. M., Wujeska-Klause, A., Yang, J., Zaehle, S., and Ellsworth, D. S.: The fate of carbon in a mature forest under carbon dioxide enrichment, Nature, 580, 227–231, https://doi.org/10.1038/s41586-020-2128-9, 2020.
Wutzler, T., Yu, L., Schrumpf, M., and Zaehle, S.: Simulating long-term responses of soil organic matter turnover to substrate stoichiometry by abstracting fast and small-scale microbial processes: the Soil Enzyme Steady Allocation Model (SESAM; v3.0), Geoscientific Model Development, 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022, 2022.
Citation: https://doi.org/10.5194/egusphere-2025-4286-AC1 - Focus and structure of results: The results section is very detailed, and at times it is difficult to see how each subsection directly contributes to addressing the central research aim. To improve readability and narrative coherence, I recommend focusing the main text on the findings that directly support the study’s objectives and relocating more descriptive or tangential results to the supplementary information.
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AC1: 'Reply on RC1', Kristian Schufft, 04 Feb 2026
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RC2: 'Comment on egusphere-2025-4286', Anonymous Referee #2, 14 Jan 2026
The authors integrated root exudation into the QUINCY-JSM model to ascertain whether it would provide a plausible mechanism for the empirical inability to measure a vegetation flux that could account for the increase in GPP under elevated CO2 as well as explain why there was an increase in heterotrophic respiration without a concurrent increase in soil C at EUCFACE site. The core motivating idea behind this model-data synthesis paper is intriguing and the inclusion of root exudation in QUINCY-JSM is a significant model development. The model formulation of root exudation that depends upon the nutrient status of the plant presented in Figure 2 is also a simple but novel way to predict exudation fluxes in a dynamic manner. Overall, the manuscript presents a good idea, executes it in the model, and uses it to generate new hypotheses to explore to understand how elevated CO2 impacts ecosystem carbon cycling in P limited systems. However, the manuscript needs better structure, some cleaning up of grammar and sentence structure, a culling down of the presented results to give the reader the main points in a way that is easy to follow, and some clear discussion of the limitations and assumptions of the modeling effort and how they impact the conclusions. Below I provide the major concerns followed by more detailed line by line comments.
- Structure of introduction: The introduction could use some streamlining and focus. Some examples: The authors present four mechanisms to explain the fate of root exudates early in the introduction (one note here a conceptual pictorial model of this would be a great addition). Then there are three loose objectives that are presented at the end. However, these loose objectives are not tied to the four mechanisms that start off the introduction and would benefit from being clearly stated formal objectives or hypotheses. Another example is the paragraph that starts on line 120. I would split this into a simple clear description of the empirical results and then another paragraph that speaks to where models have failed in capturing these results.
- Results and figures: The results section is very hard to comprehend and follow. This seems to result from the authors presenting almost all the model data in the text and figures. My recommendation is to go through and pull out the relevant model results that meet the objectives and provide evidence for which of the four proposed mechanisms is operating at the site. As a reader of the results section, I found that there were too many fluxes, too many percentage changes, and many presented that didn’t inform the conclusions or the loose objectives in the introduction.
- Discussion of the model parametrization and assumptions: First, in Section 2.6, the authors provide a very brief overview of the model parameterization. One of the clear assumptions in the parameterization is that root exudation was parameterized to get the other fluxes right. What are the implications of this and can you provide more detail on how this was done.
Second, the model assumes that if you have roots they exude carbon. One big impact of this assumption is that there are exudate fluxes deep in the soil profile that lead to enhanced carbon storage at depth. At some level these deep roots are probably more important in water uptake than priming decomposition where nutrients and organic matter are scarce and more than likely are not exuding substantial amounts of carbon. Another big impact of this assumption is that with the model predicting a 33% increase in belowground production that is not matched in the empirical data that you have more roots exuding more carbon.
Finally, there also appear to be mechanistic assumptions in how microbial necromass is cycled in the model. The necromass appears to simply just get recycled as the microbes are using it to mine nutrients. Does the model assume that all necromass is readily available for microbial attack? What is the nature of the competition for necromass fate between sorption to mineral surfaces vs. microbial attack? It seems like the model assumes that necromass is always available for microbial attack which doesn’t parallel empirical mechanisms where microbes are living and dying in intimate contact with soil minerals so that they are preferentially stabilized on mineral surfaces.
All models have issues and the comments above are not meant to say that the model is wrong. Instead, there just needs to be a thoughtful discussion of how the model assumptions/issues impact the main conclusions.
- What about mycorrhizal fungi? Assuming that all the surplus C goes into root exudation ignores the fact that the eucalyptus is ectomycorrhizal and more than likely has high levels of colonization and biomass that could account for the missing vegetation pool as well. You should include this in your discussion of your results.
Line by line:
line 24: Need period
line 33: “not measured vegetation flux” is awkward and unclear.
line 57: change affect to determine or control
line 64-65: last clause in this sentence hangs. Could just switch comma for and
line 65: insert may between mechanism and regulate
line 70: maybe call this waste respiration like in Schimel and Weintraub 2003
line 75: maybe include something about sorptive capacity
line 88: I would make it obvious that this sentence pertains to all 4 mechanisms
line 96: remove where
line 98: it may be interesting to discuss Terrer 2021 Nature here
line 108: change for to in
line 116: remove P between widespread and globally and add a comma after globally
line 126: change did only invoke to only invoked
line 128: remove that between synthesis and done and remove :
line 133: What do you mean by trade mechanisms?
line 136: I would be specific here and speak to root exudation
line 141: decompose really isn’t the best word here
line 144-153: maintain active voice first person here and be consistent
Figure 1: What are the pools that start with as like asDOM and asRES?
Table 2: How did you validate these parameters? The description in section 2.6 is very brief.
line 303: Does this downward trend impact your interpretation?
Table B1: There are clear errors in NPP and soil C.
Table B2: These wider stoichiometric constraints would have a direct impact on the exudation flux. You should discuss this as well.
Table B3: You have more carbon coming into the system and more going to belowground production that is then exacerbated by the root exudation flux. How does this impact what you see in your results and what you state in your conclusions? Roots are a nutrient rich pool which would enhance microbial limitation.
Line 350: These numbers are fairly high compared to the Chari paper which you cite later and may want to cite here. Your flux may be high because you assume all roots exude, you have more roots, more GPP, and don’t account for mycorrhizae. You should acknowledge how this impact your conclusions.
Figure 3: You show soil C sequestration int his figure that is not observed at the site that is due to I think mostly the deep roots sending out carbon and the greater root production.
line 410: what assumption?
Line 416: are these deep roots really doing this or is this a model artifact?
Line 435: I think this is clearly wrong and you mean a high C:N ratio. In the same vein, it seems like the exudate C:N is a big driver of your microbial limitation. Basically you are pumping a bunch of C into the soil and it drives nutrient limitation. What if you varied the C:N ratio like JE Drake 2013 Biogeosciences.
Line 450: Why is this fixed and how does it impact the necromass results?
Line 520: Is this true? You have a lot of things that aren’t quite right. I would soften this language and again talk about the big conclusion but also the things that aren’t quite right in the model. I think there is a compelling case that this is important to explain the EUCFACE results but what is presented here is a first pass and it generates important hypotheses and questions. It doesn’t really solve the case of the missing carbon for good.
Line 535: I disagree with this statement as you don’t account for mycorrhizae which could take up a big chunk of this carbon and the deep root issue.
Line 568: This contradicts what I think is wrong in 435 and also raises an important question. What if the C:N was different?
Line 608: Why did it enhance necromass desorption?
Line 696: Your results and model efforts do not support a grand global statement like this. As stated above, there are issues with this model exercise and as such you are raising cool hypotheses and potential mechanisms but there is not nearly enough evidence for statements like this.
Citation: https://doi.org/10.5194/egusphere-2025-4286-RC2 -
AC2: 'Reply on RC2', Kristian Schufft, 04 Feb 2026
The reviewer comments are in bold, and the replies in regular font.
The authors integrated root exudation into the QUINCY-JSM model to ascertain whether it would provide a plausible mechanism for the empirical inability to measure a vegetation flux that could account for the increase in GPP under elevated CO2 as well as explain why there was an increase in heterotrophic respiration without a concurrent increase in soil C at EUCFACE site. The core motivating idea behind this model-data synthesis paper is intriguing and the inclusion of root exudation in QUINCY-JSM is a significant model development. The model formulation of root exudation that depends upon the nutrient status of the plant presented in Figure 2 is also a simple but novel way to predict exudation fluxes in a dynamic manner. Overall, the manuscript presents a good idea, executes it in the model, and uses it to generate new hypotheses to explore to understand how elevated CO2 impacts ecosystem carbon cycling in P limited systems. However, the manuscript needs better structure, some cleaning up of grammar and sentence structure, a culling down of the presented results to give the reader the main points in a way that is easy to follow, and some clear discussion of the limitations and assumptions of the modeling effort and how they impact the conclusions. Below I provide the major concerns followed by more detailed line by line comments.
We thank the anonymous referee for taking the time to read our manuscript, for appreciating the novelty of this work and for their detailed feedback.
- Structure of introduction: The introduction could use some streamlining and focus. Some examples: The authors present four mechanisms to explain the fate of root exudates early in the introduction (one note here a conceptual pictorial model of this would be a great addition). Then there are three loose objectives that are presented at the end. However, these loose objectives are not tied to the four mechanisms that start off the introduction and would benefit from being clearly stated formal objectives or hypotheses. Another example is the paragraph that starts on line 120. I would split this into a simple clear description of the empirical results and then another paragraph that speaks to where models have failed in capturing these results.
- We thank the referee for the recommendations and will revise the structure of the introduction. We agree with the idea of bringing described processes and research goals closer together and will take the idea of a pictorial model into consideration.
- Results and figures: The results section is very hard to comprehend and follow. This seems to result from the authors presenting almost all the model data in the text and figures. My recommendation is to go through and pull out the relevant model results that meet the objectives and provide evidence for which of the four proposed mechanisms is operating at the site. As a reader of the results section, I found that there were too many fluxes, too many percentage changes, and many presented that didn’t inform the conclusions or the loose objectives in the introduction.
- We thank the reviewer for this observation. We agree that the results section is too elaborate and will reduce the presented data and text to link it closer to the mechanisms and research goals described in the introduction.
- Discussion of the model parametrization and assumptions: First, in Section 2.6, the authors provide a very brief overview of the model parameterization. One of the clear assumptions in the parameterization is that root exudation was parameterized to get the other fluxes right. What are the implications of this and can you provide more detail on how this was done.
- We thank the reviewer for this comment. We will clarify how the parametrization was conducted in the revised manuscript. We calibrated our parameters to reproduce GPP and biomass of ambient observations, which limited the size of the root exudation flux. While doing so, we ensured that the modelled exudation flux still responded to variations in the size and stoichiometry of the labile plant pool (i.e. that the flux was not controlled by empirical bounds of maximum exudation etc.), implying that it is sensitive to changes in plant carbon and nutrient status induced by elevated CO2.
Second, the model assumes that if you have roots they exude carbon. One big impact of this assumption is that there are exudate fluxes deep in the soil profile that lead to enhanced carbon storage at depth. At some level these deep roots are probably more important in water uptake than priming decomposition where nutrients and organic matter are scarce and more than likely are not exuding substantial amounts of carbon. Another big impact of this assumption is that with the model predicting a 33% increase in belowground production that is not matched in the empirical data that you have more roots exuding more carbon.
We thank the reviewer for this observation. We agree that the allocation of C in lower soil levels, based on the model assumption that root exudates follows root distribution, is a major uncertainty. This reflects a common model simplification that does not separate functionality of water and nutrient acquiring roots, given a lack of data to parameterise these functions and the relative contributions across soil depth. As a result of this assumption, we prescribe an exponential declining distribution of the exudation response to eCO2, which may lead to an overestimate of the carbon input via exudation in deep soil layers. Nonetheless, we agree that this is an important point for future improvement and will add this as a point in the discussion to further elaborate on how it impacted the model results and interpretation thereof.
To clarify further, our model simulated a 33% increase in biomass production under eCO2, which translated into a 13.6 % increase in annual fine root production only. This did cause an increase in total root exudation. However, our model also showed an increase in annual specific root exudation (up to 30%, mean increase over whole treatment period: 18%), such that increased root exudation is not solely attributable to increased fine root production. The revised manuscript will clarify this in the discussion. For the impact of additional litter input see the response below.
Finally, there also appear to be mechanistic assumptions in how microbial necromass is cycled in the model. The necromass appears to simply just get recycled as the microbes are using it to mine nutrients. Does the model assume that all necromass is readily available for microbial attack? What is the nature of the competition for necromass fate between sorption to mineral surfaces vs. microbial attack? It seems like the model assumes that necromass is always available for microbial attack which doesn’t parallel empirical mechanisms where microbes are living and dying in intimate contact with soil minerals so that they are preferentially stabilized on mineral surfaces.
We thank the reviewer for this comment. The model does separate between necromass that is freely accessible to microbial decay and necromass that is adsorbed to the soil mineral surface. The latter one is not available for enzymatic depolymerization, but for biochemical mineralization (P-only). Sorption and desorption are represented by Langmuir equilibrium. Therefore, only a fraction of the necromass is readily available for microbial attack. Uncertainty in the fraction emerges from the sorption capacity of the soil, which is challenging to parameterise with readily available data. We did mention this already in section 2.3, but we will further clarify this in the revised manuscript.
All models have issues and the comments above are not meant to say that the model is wrong. Instead, there just needs to be a thoughtful discussion of how the model assumptions/issues impact the main conclusions.
We thank the reviewer for this thoughtful and encouraging comment. We will use those comments to prepare a revised version with more clarifications of critical points and an improved thoughtful discussion.
- What about mycorrhizal fungi? Assuming that all the surplus C goes into root exudation ignores the fact that the eucalyptus is ectomycorrhizal and more than likely has high levels of colonization and biomass that could account for the missing vegetation pool as well. You should include this in your discussion of your results.
- We agree that the topic of mycorrhiza needs to be further elaborated in the discussion. An explicit parametrization of mycorrhiza fungi requires additional parameters even though we would not be able to capture all benefits of mycorrhiza colonization (Thurner et al., 2023). We here only assumed a general flux from plants to (all) microbes in soils. Clearly this interpretation has its limits. We will revise our discussion to address the role of mycorrhiza in the interpretation of the here used data and its implications for model uncertainty.
Line by line:
We will implement below suggestions as far as the comments have not been resolved by a restructuring of the respective sentence/paragraph. We provide comments where further explanation is needed.
line 24: Need period
- Agreed. We will revise this.
line 33: “not measured vegetation flux” is awkward and unclear.
- Agreed. We will revise this.
line 57: change affect to determine or control
- Agreed. We will revise this.
line 64-65: last clause in this sentence hangs. Could just switch comma for and
- Agreed. We will revise this.
line 65: insert may between mechanism and regulate
- Revised the sentence
line 70: maybe call this waste respiration like in Schimel and Weintraub 2003
- Agreed. We will revise this.
line 75: maybe include something about sorptive capacity
- Agreed. We will revise this.
line 88: I would make it obvious that this sentence pertains to all 4 mechanisms
- Agreed. We will revise this.
line 96: remove where
- Agreed. We will revise this.
line 98: it may be interesting to discuss Terrer 2021 Nature here
- Agreed. We will think about discussing this paper.
line 108: change for to in
- Agreed. We will revise this.
line 116: remove P between widespread and globally and add a comma after globally
- Agreed. We will revise this.
line 126: change did only invoke to only invoked
- Agreed. We will revise this.
line 128: remove that between synthesis and done and remove :
- Agreed. We will revise this.
line 133: What do you mean by trade mechanisms?
- We refer to root exudation and mycorrhiza representation, and its role in plant nutrient acquisition. The will clarify terminology in the revised manuscript.
line 136: I would be specific here and speak to root exudation
- Agreed. We will revise this.
line 141: decompose really isn’t the best word here
- Agreed. We will revise this.
line 144-153: maintain active voice first person here and be consistent#
- Agreed. We will revise this.
Figure 1: What are the pools that start with as like asDOM and asRES?
- We thank the reviewer for this observation. AsDOM and asRES refer to DOM and RES (microbial necromass) sorbed to the soil mineral surface. We will clarify this in the revised manuscript.
Table 2: How did you validate these parameters? The description in section 2.6 is very brief.
- See our answer to major comments above. Model parameters cannot be validated.
line 303: Does this downward trend impact your interpretation?
- We thank the reviewer for this observation. The downward trend does not result in major bursts in nutrient input. Therefore it is unlikely that it reflects on interpretation results. Nonetheless the revised manuscript will pick up this topic in the discussion section.
Table B1: There are clear errors in NPP and soil C.
- In the revised manuscript we will mention the error in NPP in the evaluation of model performance under ambient conditions and further pick up on this in the discussion. We note that soil C is highly variable between rings and underlies uncertainties in observations. Our overestimation of the mean estimate by 13 % is well within the observational range.
Table B2: These wider stoichiometric constraints would have a direct impact on the exudation flux. You should discuss this as well.
- A wider fine-root C:N ratio would have resulted in a 16 % lower baseline root exudation flux, because the baseline is tied to the fine root N concentration. However the actual exudation flux is also determined by labile pool dynamics. Additionally the root exudation was calibrated via ambient GPP and biomass pools. Nonetheless the deviation from simulated fine root C:N to observed fine root C:N leads to parameter uncertainty.
Table B3: You have more carbon coming into the system and more going to belowground production that is then exacerbated by the root exudation flux. How does this impact what you see in your results and what you state in your conclusions? Roots are a nutrient rich pool which would enhance microbial limitation.
- We thank the reviewer for this comment. Even though under eCO2 biomass production increased by 33 %, annual litterfall did only increase by 11 %. Annual fine root litterfall increased by 11 % and annual coarse root litterfall increased by 13 %. This additional input contributed to increased heterotrophic respiration (original manuscript figure 4), but did not result in a strong nutrient input. Litter input contributed to additional microbial growth under eCO2. However the contribution of litter to microbial growth under eCO2 in N and P (elevated CO2; N: 5%, P: 1%) was substantially lower than for microbial recycling (elevated CO2; N: 32%, P: 39%), depolymerised necromass (elevated CO2; N: 36%, P: 14%) and biochemical mineralization (original manuscript figure 5). We remain with the conclusion that in our model changes in root exudation and the imposed microbial nutrient demands are a key driver for increased cycling of organic matter and heterotrophic respiration at this site. However we cannot exclude that in our simulations litter input influenced microbial limitations and its consequences on necromass cycling. Therefore we will keep this in mind when revising the paper to ensure that this is clarified.
Line 350: These numbers are fairly high compared to the Chari paper which you cite later and may want to cite here. Your flux may be high because you assume all roots exude, you have more roots, more GPP, and don’t account for mycorrhizae. You should acknowledge how this impact your conclusions.
- Agreed. We will revise the discussion to take CO2 fertilization effects and mycorrhizae into consideration. As discussed above.
Figure 3: You show soil C sequestration in this figure that is not observed at the site that is due to I think mostly the deep roots sending out carbon and the greater root production.
- Agreed. Especially as the sequestration happens in deeper soil layers. We will discuss this as a possible result from model assumptions.
line 410: what assumption?
- We assume that microbial carbon use efficiency is constrained between 0.3 and 0.5, which impacts the amount of possible respiration of overflow respiration. We will revise this sentence.
Line 416: are these deep roots really doing this or is this a model artifact?
- This refers to simulated results. Clarified
Line 435: I think this is clearly wrong and you mean a high C:N ratio. In the same vein, it seems like the exudate C:N is a big driver of your microbial limitation. Basically you are pumping a bunch of C into the soil and it drives nutrient limitation. What if you varied the C:N ratio like JE Drake 2013 Biogeosciences.
- Correct, we meant high C:N ratio. Yes, our model assumes very high root exudation C:N ratios. We briefly discussed the consequences of high C:N ratio in the original manuscript at section 4.3 and 4.4. We will discuss this in more detail in the revised manuscript.
- A low C:N ratio, like in Drake 2013, would mostly relate to loss of plant N. Root exudation would be, under considerations of use-efficiencies, closer to microbial C:N ratio. As a consequence increased root exudation under eCO2 would result in less N demand, potentially reducing priming, and resulting in positive net mineralization effect (Thurner et al., 2023). A majority of this N would be stored in SOM or lost. Microbes would depend more on root exudation nutrient input, slowing down the cycling of microbial necromass and possibly increasing the decomposition of litter.
- There is the possibility that high N exudation is part of a mechanism in which plants allocate C and N to soil microorganisms (including mycorrhiza) to obtain higher P mineralisation and uptake. Testing this in the current model would require extending the microbial enzyme allocation algorithm to account for this N dependency. Such an extension is interesting, but challenging to parameterise and we consider this beyond the scope of the existing study.
Line 450: Why is this fixed and how does it impact the necromass results?
- It is fixed, based on the assumption of microbial homeostasis in terms of stoichiometry, given a fixed composition of cytoplasma and cell walls/membrane. This is a clear limitation of the model, however, data availability limits the ability to adequately constrain a model formulation in which the stoichiometry and the carbon-use efficiency vary dynamically A higher recycling value (flux toward DOM) would accelerate the nutrient cycling by microbes and reduce necromass C : N : P ratio. As a result necromass would be less attractive for microbial attack.
Line 520: Is this true? You have a lot of things that aren’t quite right. I would soften this language and again talk about the big conclusion but also the things that aren’t quite right in the model. I think there is a compelling case that this is important to explain the EUCFACE results but what is presented here is a first pass and it generates important hypotheses and questions. It doesn’t really solve the case of the missing carbon for good.
- We will revise the manuscript to reflect the reviewer’s comment.
Line 535: I disagree with this statement as you don’t account for mycorrhizae which could take up a big chunk of this carbon and the deep root issue.
- Agreed. We will revise this.
Line 568: This contradicts what I think is wrong in 435 and also raises an important question. What if the C:N was different?
- Agreed. We will revise this. Also see comment on Line 435
Line 608: Why did it enhance necromass desorption?
- In our simulation increased microbial biomass and DOM, but also increased litter input, decreased soil sorption capacity, by altering the volumetric content of mineral soil in soil layers. We will add this to the discussion.
Line 696: Your results and model efforts do not support a grand global statement like this. As stated above, there are issues with this model exercise and as such you are raising cool hypotheses and potential mechanisms but there is not nearly enough evidence for statements like this.
- Agreed. We will revise this.
additional references
Thurner, M. A., Caldararu, S., Engel, J., Rammig, A., and Zaehle, S.: Modelled forest ecosystem carbon-nitrogen dynamics with integrated mycorrhizal processes under elevated CO2, Biogeosciences Discussions, 1–30, https://doi.org/10.5194/bg-2023-109, 2023.
Citation: https://doi.org/10.5194/egusphere-2025-4286-AC2
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This manuscript presents an interesting and timely study that contributes to the overall understanding of carbon allocation and transfer via root exudates, and how these processes interact with nutrient cycling under elevated CO₂. The work highlights the importance of root exudation from a modelling perspective and provides valuable recommendations for improving the representation of root exudation, microbial dynamics, and plant-microbe interactions in global ecosystem models.
The authors implemented a dynamic root exudation module within the QUINCY-JSM model and applied it to the EucFACE experiment, a P-limited mature eucalypt forest. The goal of quantifying competing soil mechanisms that regulate carbon storage under changing root exudation fluxes at elevated CO₂ is both relevant and timely, particularly given the current uncertainties surrounding belowground carbon dynamics and their coupling to nutrient availability under future conditions. The model appears to be a meaningful advancement in simulating carbon and nutrient dynamics by explicitly incorporating exudation fluxes. Although the exudation flux is not validated, I appreciate that the authors transparently discuss model limitations and outline thoughtful directions for future development.
Major Comments
Overall, this is a valuable and timely contribution that substantially advances modelling efforts related to root exudation and belowground carbon–nutrient interactions. With improved focus, clearer terminology, and a more structured introduction, the manuscript will be significantly strengthened.
Specific line comments: