the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 29 Jan 2024
Drought counteracts soil warming more strongly in the subsoil than in the topsoil according to a vertical microbial SOC model
Abstract. Soil organic carbon (SOC) is the largest terrestrial carbon pool, but it is still uncertain how it will respond to climate change. Especially the fate of SOC due to concurrent changes in soil temperature and moisture is uncertain. It is generally accepted that microbially driven SOC decomposition will increase with warming, provided that sufficient soil moisture, and hence enough C substrate, is available for microbial decomposition. We use a mechanistic, microbially explicit SOC decomposition model, the Jena Soil Model (JSM), and focus on the depolymerisation of litter and microbial residues by microbes at different soil depths, and its sensitivities to soil warming and different drought intensities. In a series of model experiments we test the effects of soil warming and droughts on SOC stocks, in combination with different temperature sensitivities (Q10 values) for the half-saturation constant Km (Q10,Km) associated with the breakdown of litter or microbial residues. Microbial depolymerisation rates of litter and residues are proportional to microbial biomass (reverse kinetics), so that at low microbial biomass, the temperature sensitivity of Km plays a more prominent role. We find that soil warming leads to long-term SOC losses, but depending on SOC composition and its associated Q10,Km values, these losses can be either reduced or further accelerated, especially in the subsoil where microbial biomass is low. Droughts can alleviate the effects of soil warming and reduce SOC losses, and even lead to SOC gains, provided unchanged litter inputs. Furthermore, a combination of drought and different Q10,Km values associated with the breakdown of litter or microbial residues can have counteracting effects on the overall decomposition rates. In this study, we show that while absolute SOC changes driven by soil warming and drought are highest in the topsoil, SOC in the subsoil is more sensitive to the (sometimes counteracting) interplay between Km, temperature and soil moisture changes, and mineral-associated SOC.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-186', Anonymous Referee #1, 25 Feb 2024
Review of Drought counteracts soil warming more strongly in the subsoil than in the topsoil according to a vertical microbial SOC model by Pallant et al.
The study by Pallant et al. aims to investigate the interactions between microbial depolymerization and climate change, specifically the influence of temperature and moisture on SOC decomposition and the differential response of soil layers to warming and drought, using the JSM model. Despite the study's promising title and significant potential contributions to future SOC research, it falls short in several key areas, preventing it from being a comprehensive study. In its present state, it seems incomplete, suitable at best for a sensitivity analysis within a broader, more thorough investigation. I recommend withholding publication until substantial improvements are made.
General comments:
The title's implication of a drought-focused study misaligns with the content, which predominantly consists of sensitivity tests devoid of any empirical assessment. The absence of observational data reduces the study to hypothetical model outputs, with an overemphasis on parameter sensitivity to temperature and moisture.
This study also overlooks other crucial dynamics in SOC, such as diffusion and advection, which could significantly influence SOC distribution within soil columns and thus its response to soil temperature and moisture changes. The omission of factors like soil texture and vegetation dynamics further limits the study's scope.
The introduction should be revised to avoid methodological details and instead provide a comprehensive overview of the factors controlling SOC dynamics. Additionally, the methodology does not adequately discuss SOC discretization or the interplay between the topsoil and subsoil layers.
I have confined my comments to the methodology section because the paper's foundation needs strengthening before the results and discussion can be meaningful.
Specific comments:
L20: Clarify the term "long-term" to provide proper context.
L20: Define "SOC-specific Q10" to elucidate its relevance to the study.
L21: Distinguish between "reduce" and "accelerated" processes to prevent ambiguity.
L23: Replace "SOC gain" with "SOC accumulation" to accurately reflect changes in SOC cycling during different environmental conditions.
L24: When using the term "decomposition rate," additional details should be provided for clarity. It might be preferable to use "SOC loss" for simplicity and better understanding.
L25-26: You need to be clearer. Maintain consistency in the comparison of temperature and moisture effects on both topsoil and subsoil.
L28-29: These assertions require supporting references for validation.
L34-35: The phrase "most important" is subjective and should be reworded to reflect that soil temperature and moisture are significant controlling factors. This section would benefit from an expanded discussion on the key factors that regulate soil dynamics.
L35: Clarify the term "de(stabilisation)" for better understanding.
L37-39: Reformulate these lines for enhanced clarity and readability.
L41: Specify the models referred to in this line.
L43-80: Shift the detailed methodological exposition to the methods section, using the introduction to provide a broader overview.
L83: A reference is missing and should be included.
L88: What about peatlands? Inclusion or exclusion of them would significantly change your findings. It is important to note that the moisture function, decomposition term, and vertical dynamics of SOC distinctly vary in wetland environments.
L95-99: Avoid repeating information from the methods section to streamline the text.
L113: Incorporate the previously mentioned introductory information here for coherence.
L115: Briefly explain each parameter, including those in Table 1, and cite the source of the formulations. Additionally, explain the rational for such formulation for DOC?
Eq1: For this and all subsequent equations, it is necessary to specify the units of the calculated flux. Additionally, clarify if any conversions were performed to derive these units from the parameters listed in Table 1.
L116: Although the layered structure of the soil has been mentioned and is depicted in Figure 2, there is a noticeable absence of any depth indicators in the equations or in the estimations provided.
Figure 2: The figure needs to be revised for clarity, including an explanation of the brown arrows and a clear differentiation between soil pools and depth indicators.
Table 1: Complete the table by labelling parameters that lack units as "unitless." Additionally, is there a reference for the parameter R that can be provided?
L145: The nutrient dynamics have a significant influence on uptake and other soil processes. While you state that the model accounts for nutrients, there's a missed opportunity to thoroughly explore and discuss this aspect within the current study.
L147: Consideration of root distribution across various soil depths is missing. An analysis of how roots are spread throughout the soil profile could offer valuable insights into soil dynamics.
L153: Include the sorption/desorption equation to complete the methodological description.
L184: What do you mean by first model run? Explain the rationale behind the first model run and the selection of a 100-year period.
L185: The decision to focus solely on the 0-50cm soil layer raises questions. Should processes like advection or diffusion be considered, the entire soil column to its maximum depth would likely experience changes during the spin-up period. Why then, is the analysis limited to this specific depth range?
L186: Detail the approach used to assess steady-state conditions.
L189: Clarification is needed on the term "all ambient soil temperature." Does this refer to temperatures at every soil depth? Moreover, to isolate the impact of temperature alone, it would be necessary to perform simulations with varying temperature and moisture, and then compare these to simulations with only temperature variation to accurately determine temperature sensitivity.
L194-196: Justify the chosen experimental values.
L201: What was the rational for 10% changes and why only between 0.9-0.7 values?
L210: Confirm whether equilibrium was reached after 100 spins and discuss mass balance and steady-state conditions for each run.
L216: The mention of R packages is less critical than a thorough analysis of the outputs. Consider focusing on the methods to output evaluation here.
Citation: https://doi.org/10.5194/egusphere-2024-186-RC1 - AC1: 'Reply on RC1', Marleen Pallandt, 10 May 2024
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RC2: 'Comment on egusphere-2024-186', Anonymous Referee #2, 27 Feb 2024
This paper conducts a series of model experiments using the JSM soil model to explore the response of modeled SOC to warming and drought, with specific focus to depolymerization terms and their temperature sensitivity.
To accomplish this, the authors impose several general warming and drought experiments. I think it would be useful to develop the model experiments following from a specific objective. For example, if the authors want to know how soils are likely to change with climate change in a given location, they may apply one or two warming scenarios using forcings derived from the Shared Socioeconomic Pathways (running the temperature and/or moisture changes over time rather than stepping up by a global average) at the site in Germany. While it is much more work to extract the appropriate forcing information, it gives a much more specific sense of what the model expects, and the potential to evaluate predictions.
There may be other objectives, such as to conduct a sensitivity analysis of JSM model parameters. With this objective, the authors could do a literature survey of possible parameter ranges and explore the SOC response space given systematic combinations of parameter values. Some attention needs to be given to the parameters chosen for analysis. Why were they chosen and not others? What physical or chemical significance do they have?
To understand how well JSM models the SOC response to temperature or soil moisture, authors could compare model output to data.
There are many options and I think this study could be quite interesting if expanded to fit into one of these frameworks, or a different one, as long as there is some clearer justification for the chosen experiments.
L46: I think there needs to be more description about what Km means in physical terms, and why it is important. As written, it seems a bit arbitrary to explore the temperature sensitive of a fairly abstract parameter in the kinetics equation and not the other sources of temperature sensitivity in the model.
L193: I found the choices of Q10 parameter experiment a little confusing. Q10=1 and Q10=literature values makes sense, but I didn’t quite understand the hypothesis underlying the choice to set both parameters to either litter or residue.
L223: Rather than visual inspection to determine steady state, you could set some quantitative measure such as <1% change in stock (or a moving average) over the last 100 years.
L230: Sulman et al. 2018 (https://link.springer.com/article/10.1007/s10533-018-0509-z) demonstrated that different soil C models had widely different assumed temperature sensitivities of mineral associated carbon. Can you make a compelling case that MAOM is less temperature sensitive than microbial processes?
L267: Define here which pools you consider to be in POC vs MAOC. I think this may be the first occurrence of the abbreviation so you should define the terms as well.
Figures 5 seems very similar to Figure 4, and not additive to the effect of temperature shown in Figure 3 – yellow line. Why is that? Does this imply that SOC in JSM is more sensitive to soil moisture than temperature?
L334: The temperature sensitivity of adsorption and desorption seems like potentially important parameters.
Citation: https://doi.org/10.5194/egusphere-2024-186-RC2 - AC2: 'Reply on RC2', Marleen Pallandt, 10 May 2024
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