the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Revisiting overflow metabolism and its impact on soil carbon cycling
Abstract. A major challenge in biogeochemistry is to reduce the uncertainty of projections made by soil carbon models. In the last two decades, carbon-use efficiency, the proportion of consumed carbon incorporated into microbial biomass, has become a central parameter to represent microbial control on carbon fluxes. For models that integrate other elements, like nitrogen, the adjustment of carbon-use efficiency in response to substrate stoichiometry has gained popularity as a mechanism to balance these fluxes, mostly due to its mathematical convenience. The reasoning behind this, is that microbes release the excess carbon as CO2, a mechanism known as overflow respiration. This mechanism, however, causes a characteristic decrease of carbon-use efficiency when reaching nitrogen limitation. In this study we propose that the implementation of overflow respiration forces an unrealistic decrease of carbon-use efficiency for three reasons: 1) physiological mechanisms can minimize carbon excess, avoiding overflow; 2) carbon overflow has been reported in laboratory experiments mainly as dissolved organic carbon (organic acids), and not as CO2; 3) functionally diverse microbial communities can exhibit higher-level dynamics, improving the recycling of nutrients and avoiding overflow. We use an individual-based microbial litter decomposition model to test the impact of these mechanisms on carbon-use efficiency. We found that physiological mechanisms such as flexible biomass stoichiometry can eliminate overflow, but nutrient allocation does not. When carbon overflow occurs as dissolved organic carbon, carbon-use efficiency increases under nitrogen limitation. Finally, a functionally diverse community can avoid carbon overflow, although carbon-use efficiency declines due to higher maintenance respiration. We demonstrate that the representation of overflow respiration in soil carbon models is more relevant than currently acknowledged. Redirecting carbon overflow to a dissolved organic carbon pool can lead to opposite trends in carbon losses. The soil carbon modeling community should thoroughly assess current implementations and explore more mechanistically grounded alternatives. This includes dissolved organic carbon pathways, more realistic microbial community representations, or other processes that better capture the complexity of microbial carbon use.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-3590', Anonymous Referee #1, 27 Jul 2026
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RC2: 'Comment on egusphere-2026-3590', Anonymous Referee #2, 26 Aug 2026
General comment:
The scientific relevance of this manuscript is considered high and the approaches to model microbes differently are comprehensive and backed by literature. The general structure of paragraphs is mainly easy to follow, although confusions in the abstract, introduction and method sections can come up, which is addressed more in detail in ‘Minor revisions’. The conclusions are rational, although further computational and temporal analysis would support claims. For increasing the comparability to literature and clarifying the motivation some major revisions are necessary before publication.
Major revisions:
- In line 261 the CUE used in this study is defined. While this is common for most models, the innovative formulations in this study open the question what should be also subtracted in the numerator (e.g. overflow C or enzyme C). A comparison with what is actually measured in CUE lab or field experiments and what models represent as CUE would be very interesting. This is also necessary for the next major revision point.
- Compare to actual CUE-C:N data from field/lab studies. At least one plot reproducing real-world data for supporting the necessity of avoiding decreasing CUE at high C:N, as this motivation is repeated throughout the study.
Minor revisions
- L35: A large body of literature supports the opposite, i.e. no temporal predictive power exists.
- L63: Flexible biomass stoichiometry needs introduction. Also method section does not describe how that is handled in the model or to what range ‘flexible’ refers.
- L70-71: ‘sequential nature’ must be explained. I assume that overflow would only happen when the proposed mechanisms don’t resolve the imbalance.
- L88-90: three mechanisms are proposed here, but Table 2 lists four factors. Maybe put ‘(i.e. flexible stoichiometry, enzyme and uptake allocation)’ after the ‘physiological acclimation mechanisms’. Table 2 is a good overview, and the manuscript (including the abstract) would be easier to follow if each section presented the mechanisms in the same order and used consistent wording throughout.
- L127-128: Necromass decomposition being modulated by enzymes is not in the scheme.
- L131: The initialization of the enzymes, biomass, etc. pools is missing.
- L132-139: First stating what the study does and then mentioning what DEMENT would in theory provide (or is lacking) would improve readability. Same for 2.3 & 2.3.3.
- L175: Sigmoid function is described also in Eq. 1.
- L202-203: Why is constitutive production necessary at all?
- L213-214: I would find it valuable to see time-to-50% shown across the C:N range and model version.
- L214-215: In this case, the pulse actually has no duration.
- L228: The range would be interesting, as bacteria would have rather different values.
- L366: Some numbers on the duration of the experiment with the different versions would be interesting (in the supplement).
- L378-379: Assimilation efficiency would also be interesting to compare to different CUE formulations (see major revisions).
- L424-425: Could these data be used for comparison with the results of this study? (see major revisions).
- L439-440: Non-linearity in ESMs is also avoided for computational costs.
- L453-454: A predictive component, or at least a comparison with real-world data, would be needed to support this claim.
Technical problems:
- Figs. S7, S8: units are given in g, but total initial litter C is 344.56 mg cm⁻².
- 2.3.3 does not follow paragraph numbering correctly.
Citation: https://doi.org/10.5194/egusphere-2026-3590-RC2
Model code and software
Code scripts for running simulations and processing them José M. Murúa Royo, Brittni L. Bertolet, Luciana Chavez Rodriguez, Jeth Walkup, and Steven D. Allison https://doi.org/10.5281/zenodo.20752610
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Review for “Revisiting overflow metabolism and its impact on soil carbon cycling” by Royo et al.
General comments:
The authors propose three potential mechanisms to mitigate overflow respiration in soil C models that may force a decrease in microbial carbon-use efficiency. They design numerical experiments to test these three mechanisms using DEMENT. The manuscript is well structured and written. However, this is a purely numerical study with no comparisons to either observations or other numerical models. In addition, sensitivity analyses to critical numerical parameters are missing, which may affect the results presented. I recommend major revision before it can be considered for publication. See my detailed comments below.
Major comments:
1. This is a purely numerical study with no comparisons to either observations or other numerical models. I would suggest including these comparisons, as they would significantly strengthen the manuscript.
2. The proposed three mechanisms works well to mitigate overflow respiration in DEMENT, while it is uncertain for other soil carbon models. How do the authors comment on this uncertainty?
3. I would suggest conducting sensitivity analyses to critical numerical variables (e.g., Vmax and Km), so that we can know when to involve these three mechanisms to mitigate overflow respiration.
4. Lines 113-115.The authors conduct numerical experiments with constant environmental variables. However, it remains unclear whether the proposed three mechanisms work with changing environmental variables. The authors should also test their mechanisms in real cases. In addition, the authors focus on CUE responses to the three mechanisms. It is also important to look at other metrics (e.g., DOC), especially when redirecting C overflow to DOC.
Minor comments:
1. Line 13. “reasoning” to “reason”.
2. I suggest the authors shortening the abstract.
3. Line 36. “enabled” to “enable”.
4. Lines 40-41. References are needed to support this statement.
5. Line 86. “for C:N litter” is unclear.
6. Suggest combining Figures 1 and 2 into a single figure.
7. Line 175. Suggest moving Figure 3 to the supplementary material as it provides limited information.
8. Line 343. “decomposers feed” to “feeding decomposers”.
9. Line 351. “maintenance” to “maintenance respiration”.