the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Jun 2025
Electrical conductivity measurements as a proxy for diffusion-limited microbial activity in soils
Abstract. Soils play a highly dynamic role in the carbon cycle, by acting as either a carbon source or sink. Despite their importance in the global carbon cycle, uncertainties surrounding soil-atmosphere interactions remain, due to the many mechanisms that underlie soil carbon dynamics. One of the main mechanisms determining the decomposition of organic C in soil is the access microbial decomposers have to substrates. While not yet formally tested, there is evidence to support the idea that microbial decomposer access to substrates is diffusion-limited. This is underlined by soil respiration rates being strongly dependent on water availability. In recent years, non-destructive geophysical tools, including electrical conductivity measurements, have been used to determine the water content of soils and connectedness of the water phase in the soil pore network. As both respiration and electrical conductivity may depend on water availability and connectivity, our study aimed to determine whether electrical conductivity measurements could be used as a proxy of diffusion-limited microbial activity in soils. This was done by measuring electrical conductivity and respiration rates at different matric potentials. Sieved and undisturbed top and subsoil samples taken from conventional tillage and conservation agriculture management plots were used. Our results revealed an initial increase and consecutive drop in soil respiration associated with a decrease in the matric potential. The electrical conductivity followed a similar decrease throughout the experimental range and these showed a significant non-linear relationship. These results thus suggest that both measured variables depend on the connectedness of the aqueous phase and suggest that they could be used as groundwork for further investigations into soil respiration and electrical conductivity dynamics.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-1730', Anonymous Referee #1, 22 Jul 2025
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AC1: 'Reply on RC1', Orsolya Fülöp, 24 Nov 2025
We thank both the reviewers for their very thorough and constructive reading of the manuscript. We have added a sentence to the manuscript to acknowledge their contribution.
General comments
The authors present a study where electrical conductivity measurements were related to soil CO2 emission from intact and sieved cores.
The mansucript is well-structured and in written in a consice style. I am not a native speaker, but I think the written English is OK. I made some suggestions for edits.Response: We thank the reviewer for this very positive assessment of our manuscript. We provide a point-by-point responses to the different comments in the text.
Soil heterotrophic respiration is known to vary with soil water status. Electrical conductivity measurements are used over a wide range of spatial scales as a proxy for water content. This study directly relates soil heterotrophic respiration to electrical conductivity measurements. In this respect I have two general comments:
1) Apart from the basic research aspect of this study, what is the potential use of this respiration/electrical conductivity relation? Is the idea to generate e.g. a field-scale map of soil heterotrophic respiration from spatially-distributed electrical conductivity measurements? This should be pointed out in the conclusions section. In the Introduction, I am also missing the motivation for this study.Response: We thank the reviewer for this comment and we will provide a revised version of the introduction and conclusion in order to reflect our motivations for this study more clearly. Given the complexity of biological processes in soils in situ, we believe that more work has to be conducted to validate our approach before applying it to field conditions. In this study we aim at testing our working hypothesis and prepare the ground for future field scale studies.
We would like to point out that, to the best of the authors knowledge, that this is the time that this hypothesis is tested and that this approach is proposed. Which means that we have to move step by step, first proving the working hypothesis in controlled conditions, then moving toward more quantitative approaches or larger scales and complexities.
In the revised version of our introduction, we added the following sentence to lines 77 and 78:
“Our working hypothesis was tested to validate a novel methodology for rapidly characterizing soil biological processes.”In the conclusion, the purpose of our study is re-emphasized in line 349-351 to the following:
“This study investigated whether electrical conductivity measurements can serve as a proxy for soil respiration, given the hypothesis that both variables are affected by the availability of a connected water phase. The objective was to validate a novel methodology for characterizing soil biological processes through the use of electrical conductivity and its uniquely fast way to quantify water connectivity in partially saturated soils.”And in line 349 to end of article:
“This study demonstrates the potential of electrical conductivity as a proxy for diffusion processes governed by water connectedness and tortuosity in soils. By addressing the inherent complexity of biological soil systems, our findings lay the groundwork for a field-ready methodology capable of capturing these dynamics in situ. Future work will refine the quantitative framework linking soil respiration to electrical conductivity, with the more long-term goal of advancing the development of a deployable system for field-scale applications. By establishing electrical conductivity as a quantitative indicator of soil biological dynamics, this study lays the foundation for future field-scale applications.”
2) Why is respiration related to pressure head? Pressure head can clearly be used to describe the soil water status, but it is probably the variable with the worst indication of diffusivity in the soil pore water. From a soil-physics point of view, volumteric water content or water-filled pore space will be a much better indicator of the volume (!) available for diffusion. If the soil water retention function is known, this can of course easily be converted ...Response: We understand the reviewer’s concern regarding the use of moisture content as an alternative to matric potential. However, due to the specifics of our experimental set-up, we were unable to monitor weight changes throughout the measurements. We did measure the water retention curves of our samples and, based on this comment, we will include them in the supplementary material of the revised manuscript.
Nevertheless, we wanted to avoid potential biases associated with transforming our known applied matric potentials into water contents via the retention curves. As our main objective is to test the relationship between soil respiration and electrical conductivity under identical experimental conditions, we chose to present the results directly in terms of the applied matric potentials. To clarify this decision, we added the following sentence to the revised Materials and Methods section (Lines 122-124):
“The decision to work in matric potential throughout this experiment was taken to avoid biases stemming from the transformation of our known applied pressure values into water content based on measured water retention curves.”
Other methodological aspects:
I would be interested to see a more physically-based interpretation of the data. Now, we have something like an empirical black box model (ECa in - Rh out). What about using e.g. the Topp et al. 1980 (or something more recent and advanced) approach to estimate water content from ECa. Then estimate relative diffusivity in dependence of porosity and the estimated water content. The Millington-Quirk approach is well-established, but I could imagine that more recently-developed approaches (e.g. from Peer Moldrup and his group) even perform better. Subsequently, relate relative diffusivity to heterotrophic respiration.Response:We thank the reviewer for this valuable methodological suggestion. We fully recognise the usefulness of applying quantitative petrophysical models to transform electrical conductivity into water content (e.g., Topp et al., 1980) or to infer relative diffusivity. One of the authors has worked extensively on petrophysical relationships for variably saturated porous media, and we agree that such models provide powerful tools for mechanistic interpretation. However, these relationships remain simplifications of the true pore-scale processes, and applying one model to derive water content and a second to infer diffusion would introduce additional layers of model-driven assumptions and potential bias.
Because our aim in this first study was to establish a non-biased proof of concept for using electrical conductivity as a proxy for microbial respiration, we chose to base our analysis directly on the experimentally controlled matric potentials rather than on model-derived water contents. We therefore present all measurements in terms of applied matric potential, avoiding uncertainties associated with transforming pressure head through water retention curves.
To strengthen the mechanistic interpretation, and in line with the reviewer’s suggestion, we have now included estimates of tortuosity/connectivity derived from standard petrophysical relationships in the revised manuscript. These estimates help illustrate how changes in pore connectivity accompany changes in respiration with moisture content. The corresponding curves and examples are provided in the revised Supplementary Information.
We fully agree that a more comprehensive physically based modelling framework is a promising future direction, and we are currently developing such an approach. However, given the complexity of biological processes in soils, several parameters still need to be constrained before this can be implemented quantitatively.
Specific comments
19 replace 'surrounding' with 'in'?Response: This correction has been made in a revised version of our manuscript.
46 replace 'believed' with 'supposed'?
Response: This correction has been made in a revised version of our manuscript.
62 I disagree. The single most important factor affecting microbial processes is temperature. At least under field conditions, soil temperature is much more relevant than soil water status. There is a number of studies on that topic, e.g Bauer et al. 2008 (Geoderma) or Fang & Moncrieff, 1999 (Agric. For. Meteorol.)
Response: We understand this point and we were thinking about adiabatic conditions, however, we modified our sentence to be more precise, in the revised version of our manuscript, it now reads (line 62): “to one of the most important factors”
75 I guess 'the quantification of soil' must be removed here
Response: We corrected this point in the revised version of our manuscript.
77 Why matric potential and not water-filled pore space or water content? With a perspective on the transfer of results of this study, water content is much easier to measure that matric head. Further, a sandy soil will have a very different water content than a silty soil at the same pressure head. And in the end, the water volume available for diffusion is what drives nutrient accessibility, just as summarized nicely in the first part of this introduction.
Response We chose to use an applied pressure head to allow our samples to be comparable, independent of depth and agricultural treatment, as well as sieved and undisturbed treatments. Note that we have now attached the water retention curves to the supplementary materials. However, we prefer to use the known applied matric potential in the article to avoid biases (i.e., model simplification) that would arise from the use of water retention function models. As mentioned in response to the second comment, we also added the following line to our material and methods section to make our decision transparent in the paper:
“The decision to work in matric potential throughout this experiment was taken to avoid biases stemming from the transformation of our known applied pressure values into water content based on measured water retention curves.” (L122-124)
140 a bulk density of 1.73 g/cm3 is relatively high, particularly for a frequently tilled topsoil. The conventional till soil would be expected to have a consistently lower bulk density than the conservation tilled (no-till) topsoil.Response: We agree that bulk density values of 1.71-1.80 g cm⁻³ are high for a frequently tilled topsoil and exceed typical values reported for the La Cage experimental site (~1.3-1.4 g cm⁻³). These elevated values did not reflect the true in-situ soil structure. Rather, they resulted from the difficulty of collecting “undisturbed” cores under very wet field conditions. The soil was plastic and highly resistant to core insertion, which likely caused compaction of material inside the rings and consequent overestimation of bulk density.
Because the study focused on treatment comparisons rather than characterizing field bulk density, we used the measured values solely to standardize soil packing in the laboratory microcosms. After sieving, soils were repacked to this density to ensure identical soil mass and pore volume across treatments, thereby eliminating differences due to inherited structure. While the resulting density was higher than field conditions, it establishes a conservative, low-porosity scenario. All treatments experienced the same packing conditions, so the relative differences observed remain valid. We now clarify this rationale in the Methods and note that these values should not be interpreted as representative field bulk densities, in Line 143-145:
“Because undisturbed cores were collected under very wet field conditions that caused resistance during insertion, the measured bulk density likely overestimates field values and was used solely to standardize soil mass and pore volume among treatments, not to reproduce in-situ structure.”
183 I think 'compared to' should be replaced with 'and'
Response: This change has been made to the revised version of our manuscript.
Fig. 3 I wonder how much water is in the soil at those pressure heads. A soil water retention curve would be helpful. I guess this could easily be obtined by fitting a function to the measured water content/pressure head pairs. I assume water content can be computed from the measured weight?!Response: We did conduct water retention measurements as part of the study. We initially did not include them as we have been working with pressures instead of water content, but we have now included them in the supplementary materials.
266 Macropores in the undisturbed samples?
Response: We thank the reviewer for this helpful comment. As the largest pores drain first with increasing matric potential (Jurin-Laplace relationship), sieving the soil likely altered the pore-size distribution substantially. Undisturbed samples retain their natural structure, including macropores that empty rapidly and intra-aggregate micropores that remain water-filled until lower matric potentials (around -250 hPa). This means that oxygen can enter the macropores early, while the interiors of aggregates remain saturated and potentially anoxic. In contrast, the sieved samples exhibit a more homogeneous and unimodal pore-size distribution, allowing oxygen to diffuse more uniformly throughout the sample. This structural difference provides a plausible explanation for the higher optimal respiration observed at lower matric potentials in the sieved samples. We have added this point to the revised Discussion.
Citation: https://doi.org/10.5194/egusphere-2025-1730-AC1
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AC1: 'Reply on RC1', Orsolya Fülöp, 24 Nov 2025
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RC2: 'Comment on egusphere-2025-1730', Benjamin Mary, 20 Aug 2025
# Electrical conductivity measurements as a proxy for diffusion-limited microbial activity in soils
I was very curious to read this paper, as the title reflects something innovative and trendy at the frontier between agrogeophysics and biogeophysics research. I really appreciate that the research explores this new line of inquiry. Indeed, the authors investigate the relationship between soil water conductivity and soil respiration measured in a laboratory setup, assuming a diffusion-limited environment. I have to say that the concept behind this assumption was not entirely clear to me on first reading, and I had to consult additional literature to understand it. This probably indicates that new references are needed.
The setup and data collection are very impressive. The chain from field to lab is well executed, with a precise protocol for each step, which is greatly appreciated.
My main concern is that, although the work is very innovative with an in-depth discussion, the paper provides only a shallow interpretation of the correlation between EC and respiration rate. Since samples were weighed, the authors could have attempted to distinguish, for instance, the contributions of water connectivity, water conductivity, and moisture content to total respiration (via pedophysical relationships or simply normalizing by soil moisture). This would allow assessing whether variations in EC provide additional insight beyond the effect of simple moisture changes. Without this step, in my opinion, an analysis based solely on sample moisture changes (from weight measurements) would likely yield correlations similar to those obtained from EC, suggesting that the study does not fully demonstrate the added value of using EC values.
Overall, the manuscript is well written, but I still have minor comments:
- The authors frequently refer to “geophysical methods” in the manuscript. At this stage, I do not think the method can be qualified as such. All measurements were conducted in the laboratory on a sample holder with a simple quadrupole ABMN setup. In my view, geophysical methods usually refer to field applications, such as tomography, which is obviously a perspective this work could lead to. Such approaches are often associated with electrical impedance measurements. It might be worth including “laboratory” in the title.
- Review the manuscript again for typos, missing punctuation, and minor language issues.
- The use of acronyms could simplify reading. I suggest defining them early (e.g., Electrical Conductivity = EC), but the authors are free to make adjustments as they see fit.
- Consider shortening or simplifying figure legends to avoid redundancy with the text.
- The diffusion-limited concept, which is the main hypothesis, is not sufficiently addressed and should be clarified.I thank the editor for the opportunity to review the manuscript and the authors for their work. I recommend that the editor accept the manuscript for publication after revision.
# Abstract
L.21 I understand that this is the authors hypothesis. i would rephrase "While not yet formally tested, there is evidence to support the idea that microbial
decomposer access to substrates is diffusion-limited. This is underlined by soil respiration rates being strongly dependent on water availability." to make it more evident
# IntroductionL.65: Those are very generic references, which do not reflect the idea of the sentence.
L.65: Rephrase "measurement of soil moisture contents" (e.g., "sensitive to soil moisture variations").
L.77: Explain the importance of different soil matric potentials. What is the influence of increasing soil potential? Add references.
Being a bit provocative: would it be possible to reach the same conclusions using soil water content sensors? Why was ERT chosen here? Is future research planned to extend this approach to SIP?
For instance, could Figure 2 be replotted using relative soil moisture content instead of conductivity?
As you mentioned that there is no flow; this would be equivalent to measuring with FDR sensors.# 2 Materials and methods
The author took advantage of an interesting field site! To me, the material and method are quite well executed with replicated etc .. and explained. Good point for reproducible research!
## 2.2. Study approach and incubation set-up
L.120 "Samples were placed in airtight microcosms fitted with a ceramic plate, allowing for adjustments of the pressure head, and a septum for headspace sampling (Poll et al., 2010; Fig.1)": I don't understand why the authors refer to Poll fig 1. In Poll's study, there is no pressure head adjustment nor a septum for headspace sampling. Maybe rephrase and call you figure S1?## 2.3 Sample preparation for incubation
I would have put this section before 2.2. Does it make more sense in terms of experiment chronology?## 2.4 Analytical data collection
L 145: CO2 flux measurements - this is a bit short. Particularly the description of the instruments (model, manufacturer, etc..). Please add a reference to figure S1.
Does the Agilent measure the "increase in CO2 concentration" or the actual C02 concentration? Rephrase accordingly.
### 2.4.2 Electrical Conductivity Measurements
L149: a word about injection parameters would be interesting here(number of repetition, voltage required, Vab etc ...)L.157: rephrase (currently it reads that there is only injection electrodes to me): [...] with three pairs of potential electrodes inserted ...
L158: distribution of electrical lines --> distribution of current lines or equipotential? rephrase
Unit of EC? (missing in the whole manuscript)
### 2.4.3. Organic matter and water content data collection
L.162: “After the measurements had been concluded…” is in past perfect, which is often too heavy for a methods section. suggestion: After the measurements, the samples were dried at 105 °C for 24 hours…### 2.4.4. Statistical analysis and data visualisation
I would suggest to detail the maths and use acronyms such as:The soil respiration flux (FCO2) was obtained as the slope of the regression of CO2 concentration (C, unit?) against time (t, h):
FCO2 = dC/dt
The flux per gram of organic matter (FOM) was then calculated as (then use the acronyms in the figures):
FOM = FCO2 / OMFinally, the relative flux (Frel) was calculated as the ratio of the flux at the given condition to the flux at –70 hPa:
Frel = FOM / FOM(-70 hPa)
Also I recommend substituting electrical conductivity with EC everywhere (except first occurrence)
L178: A word about data quality, how uncertainty evaluation based on repeated samples is assessed, filtering, and outliers would be very welcome.
# Results
## 3.1. Soil respiration rates across soil matric potential and organic matter quantificationL.180: What does "Welch" stand for? I assume this refers to Welch’s test for Satterthwaite’s method, but please clarify this in the previous paragraph.
L.180: The first sentence is difficult to understand and very specific. I suggest starting with a more contextual sentence (for example, stating the range of organic matter, from 0.7 to 4 g per sample), and then explaining the test (degrees of freedom, etc.).
Please also recall the treatment types, i.e., CA and CT.
L.185: Replace "The relative respiration rate, normalised to the measured values at -70 hPa" with **Frel**.
L.186: The sentence "showed a near-consistent decrease across the tested matric potentials (Fig. 1)" is confusing. A clearer suggestion would be: "showed an increase from 0.01 to 10 as matric potential rose from –996 to –70 hPa (Fig. 1)".
- Ensure consistency with the figure, which shows that Frel increases with increasing matric potential.
- Be consistent in terminology: in Fig. 1, you call it *applied suction*, while in the text you use *matric potential*.L.186: The sentence "For the sieved samples, this decrease was maintained across all matric potentials, while for the undisturbed samples there was a respiration peak at -250 hPa" does not reflect the data accurately. I observe peaks for all samples, with the peak shifting according to the sampling strategy.
## 3.2 Soil electrical conductivity
I don't really understand the idea of comparing the different pairs of electrodes. Do you suspect that the sample is not homogeneous? If so, what is the interest of showing this heterogeneity? (Only CT Topsoil seems to have issues of replicability between pairs.) To me, it would make more sense to take the mean and variance between each pair of measurements (and not between repeated measurements for a single pair) and plot a single line with error bars. This would clearly simplify the interpretation of the figure.
L.210: Relative to what? The mean EC of all samples? The sentence "To allow an easier comparison between samples given these differences, we chose to use the relative conductivity of each sampling depth and field trial to improve the comparability between samples" should clarify this.
L.215: Add a period at the end of the sentence.
Authors could have conducted the same analysis as in the previous figure to test for significant differences between treatments and sample types from an EC perspective. Demonstrating this could have had a major impact and would have avoided the need to rely on relationships and regression analysis.
## 3.3 Relationship between relative respiration rate and relative electrical conductivity
For clarity, in Figure 3, I suggest adding a legend within each subplot showing the R² and p-values, or include a table with R² scores in the manuscript. Otherwise, this paragraph is difficult to read.
L.222–227: "Because respiration rates in the undisturbed samples decreased between -250 and -70 hPa (Fig. 1). This increase has been recorded in past studies and is caused by limitations in oxygen availability rather than substrate access (Moyano et al., 2013)."
- Be consistent: the first sentence calls it a decrease, the second calls it an increase. This issue appears multiple times in the manuscript; please check for consistency.
- I am not convinced by the explanation provided to remove data between -250 and -70 hPa. Saying "caused by limitations in oxygen availability rather than substrate access" is not sufficient justification for removing it.
## DiscussionThe discussion is very extensive, which is much appreciated!
### 4.1
Figure 4
- I like the conceptual figure. However, for the diffusion-limited respiration range, your results show a non-linear relationship between EC and CO₂ fluxes, which is not represented in Fig. 4.
- Could you discuss what it means that the relationship is non-linear? Why fit an exponential model—due to water connectivity, change in respiration regime, or other reasons?L.255: "Showing a decrease in both measured parameters": I understand you are referring to hydraulic and electrical tortuosity. If so, your results don’t clearly show this (or only indirectly, which is not explained). Consider rephrasing.
L.285–L.291: The idea that the conductivity of the microenvironment surrounding fungal hyphae increases is cited twice (Ameen et al., 2019; Sun et al., 2022), which is redundant. Consider combining the references into a single statement for conciseness.
## Conclusion
L.352
- You state "revealed a strong relationship," but this is a simplification. The relationship is non-linear and ranges from 0.07 to 0.84 (Table S9).
- Avoid generic terms like "parameters" or "variables." Refer specifically to EC and CO₂ fluxes to prevent confusion.Suggested rephrasing:
"The analysis of the relationship between EC and CO₂ fluxes revealed a strong correlation across the tested soil matric potentials, confirming that both EC and CO₂ fluxes respond similarly to the loss of water availability."### Figures
Figure 1:
- Rephrase the figure legend to make it shorter. For example, remove: "The different suctions represent different soil matric potentials analysed over the course of the study."
- Use the same color for the same soil treatment, changing only the marker type. Example: CT Topsoil / CT Topsoil sieved — same color, different marker type.
- Add units to the y-axis.Figure 3: missing unit for "applied pressure" in the legend panel
Citation: https://doi.org/10.5194/egusphere-2025-1730-RC2 -
AC2: 'Reply on RC2', Orsolya Fülöp, 24 Nov 2025
We thank both reviewers for their very thorough and constructive reading of the manuscript. We have added a sentence to the manuscript to acknowledge their contribution.
# Electrical conductivity measurements as a proxy for diffusion-limited microbial activity in soils
I was very curious to read this paper, as the title reflects something innovative and trendy at the frontier between agrogeophysics and biogeophysics research. I really appreciate that the research explores this new line of inquiry. Indeed, the authors investigate the relationship between soil water conductivity and soil respiration measured in a laboratory setup, assuming a diffusion-limited environment. I have to say that the concept behind this assumption was not entirely clear to me on first reading, and I had to consult additional literature to understand it. This probably indicates that new references are needed.
Response: Thank you for your thoughtful comment and for highlighting that the diffusion-limited framework would benefit from additional background. To address this, we added several references in the Introduction to further support the underlying mechanisms. Specifically, new citations were incorporated in the paragraph discussing the mechanisms linking soil moisture to microbial respiration (Lines 55-58), including additional sources on microbial movement and water-dependent growth (Schwartz, 2007; Spohn et al., 2016). We also reinforced the discussion of moisture-related constraints by expanding the references associated with oxygen limitation, osmotic stress, and diffusion-controlled processes (Moyano et al., 2012, 2013). These additions provide a clearer context for the diffusion-limited assumptions used in our study.
The setup and data collection are very impressive. The chain from field to lab is well executed, with a precise protocol for each step, which is greatly appreciated.
Response: Thank you.
My main concern is that, although the work is very innovative with an in-depth discussion, the paper provides only a shallow interpretation of the correlation between EC and respiration rate. Since samples were weighed, the authors could have attempted to distinguish, for instance, the contributions of water connectivity, water conductivity, and moisture content to total respiration (via pedophysical relationships or simply normalizing by soil moisture). This would allow assessing whether variations in EC provide additional insight beyond the effect of simple moisture changes. Without this step, in my opinion, an analysis based solely on sample moisture changes (from weight measurements) would likely yield correlations similar to those obtained from EC, suggesting that the study does not fully demonstrate the added value of using EC values.
Response: We would like to thank the reviewer for this very positive assessment of our article and the detailed suggestions of improvement given. Based on your suggestion, we have extended our analysis to explicitly evaluate whether electrical conductivity provides information beyond simple moisture changes. To do this, we fitted the bulk electrical conductivity to the measurements using the following pedophysical relationship:
σ_b = (S_w^n / F) * σ_w + (σ_s / S_w)
and we determined the water phase tortuosity from Archie’s parameter (the formation factor F and saturation exponent n) following the proposition of Jougnot et al. (2018):
τ_w = Φ * F * (S_w)^(1 − n).
To explicitly evaluate whether EC provides information beyond moisture content. We include below an example of the fitted curves for two representative samples. This analysis will be incorporated into the revised Results section to strengthen the interpretation of the added value of electrical conductivity. In this, one can clearly see that the water-phase tortuosity increases as water saturation decreases, thereby quantitatively validating our working hypothesis.
Figure 1: Example of fitted bulk electrical conductivity (top) and the resulting inferred tortuosity (bottom) as a function of water saturation for one undisturbed CA topsoil and one sieved CT topsoil sample. Points are the measured EC data, while lines are the models predictions. These fits illustrate the additional information EC provides on pore connectivity beyond moisture content alone.
Overall, the manuscript is well written, but I still have minor comments:
- The authors frequently refer to “geophysical methods” in the manuscript. At this stage, I do not think the method can be qualified as such. All measurements were conducted in the laboratory on a sample holder with a simple quadrupole ABMN setup. In my view, geophysical methods usually refer to field applications, such as tomography, which is obviously a perspective this work could lead to. Such approaches are often associated with electrical impedance measurements. It might be worth including “laboratory” in the title.
Response: Thank you for this helpful comment. We agree that our measurements are more accurately described as laboratory electrical conductivity measurements rather than geophysical methods. We have therefore updated the terminology throughout the manuscript to reflect this.
We also clarified that this study is a laboratory-based validation of a concept that could later be applied in geophysical field settings. Following your suggestion, we have revised the title to:
“Electrical conductivity measurements as proxies for diffusion-limited microbial activity in soils under controlled laboratory conditions.”
- Review the manuscript again for typos, missing punctuation, and minor language issues.
We appreciate this remark. The manuscript has been carefully re-read and edited for grammar, punctuation, and clarity.
- The use of acronyms could simplify reading. I suggest defining them early (e.g., Electrical Conductivity = EC), but the authors are free to make adjustments as they see fit.Response: Thank you for this suggestion. We now define all acronyms at first use (e.g., Electrical Conductivity, EC), and ensured consistent usage throughout the manuscript.
- Consider shortening or simplifying figure legends to avoid redundancy with the text.Response: We agree and have revised the figure captions to remove redundancy and improve readability.
- The diffusion-limited concept, which is the main hypothesis, is not sufficiently addressed and should be clarified.Response: We thank the reviewer for this critical point. We have added additional explanation and references to clarify the theoretical basis of diffusion-limited respiration and why EC provides complementary information to gravimetric water content by reflecting aqueous-phase connectivity and tortuosity. This improves the conceptual grounding and strengthens the link between our hypothesis and results.
We added the following section for line 73-78:
“In partially saturated soils, diffusion-limitation arises not only from reduced water content but from loss of continuity in the water-filled pore network, which increases tortuosity and constrains the movement of substrates and gases (Ebrahimi & Or, 2015; Ghezzehei et al., 2019). Electrical conductivity therefore provides complementary information to gravimetric water content by reflecting the connectivity of the aqueous phase and the effective pore-scale pathways available for diffusive transport (Jougnot et al., 2009; Revil & Jougnot, 2008).This diffusion-limited framework applies only when advective water flow is negligible, i.e., not during or immediately after rainfall events.”
And in the discussion at Lines 294-298:
“Below this optimal range, respiration becomes increasingly diffusion-limited, as reduced water continuity and increased tortuosity constrain substrate and gas transport even when some moisture remains available (Ebrahimi & Or, 2015; Ghezzehei et al., 2019). In this regime, electrical conductivity provides complementary information to water content by indicating the loss of connected aqueous pathways required for diffusive exchange (Revil & Jougnot, 2008; Jougnot et al., 2009).”
I thank the editor for the opportunity to review the manuscript and the authors for their work. I recommend that the editor accept the manuscript for publication after revision.
Response: Thank you.
# Abstract
L.21 I understand that this is the authors hypothesis. I would rephrase "While not yet formally tested, there is evidence to support the idea that microbial decomposer access to substrates is diffusion-limited. This is underlined by soil respiration rates being strongly dependent on water availability." to make it more evident
Response: Thank you for the suggestion, we have rephrased this accordingly.
# IntroductionL.65: Those are very generic references, which do not reflect the idea of the sentence.
Response: Thank you for this comment. We agree that the previous references were too general. Following the suggestion, we have replaced them with more specific citations that directly support the role of connectivity and tortuosity. The revised sentence now cites Ghanbarian et al. (2013) and Jougnot et al. (2018), which better reflect the processes described.
The revised sentence in L71-73 corresponds to:Geophysical tools are increasingly applied as fast, non-destructive approaches to monitor soil moisture dynamics (Garre et al., 2021; Hermans et al., 2023; Loiseau et al., 2023) and to infer water-phase connectivity in porous media (Ghanbarian et al., 2013; Li et al., 2015; Jougnot et al., 2018; Wilson et al., 2024).
L.65: Rephrase "measurement of soil moisture contents" (e.g., "sensitive to soil moisture variations").Response: Thank you, we rephrased that line based on this suggestion.
L.77: Explain the importance of different soil matric potentials. What is the influence of increasing soil potential? Add references.
Response: Thank you for this helpful suggestion. We have expanded the text at Line 77 to clarify why soil matric potential is relevant in this context. The revised sentence now explains that different soil matric potentials correspond to different water contents, which directly influence water-phase connectivity and tortuosity, and therefore affect diffusion-controlled processes. We have also added the recommended references to support this explanation.These changes have been applied to L88-90:
“Different soil matric potentials correspond to different water contents, which alter pore connectivity and tortuosity and therefore influence diffusion-controlled transport processes (Ghanbarian et al., 2013; Jougnot et al., 2018).”
Being a bit provocative: would it be possible to reach the same conclusions using soil water content sensors? Why was ERT chosen here? Is future research planned to extend this approach to SIP?
Response: Thank you for this interesting question. Soil water content sensors, which rely on dielectric permittivity, measure the bulk volume of water but do not provide information on pore-scale connectivity or tortuosity. For this reason, they cannot be used to investigate the connectivity-dependent diffusion processes that are central to our study. We also clarify that our measurements were performed using laboratory electrical conductivity (EC) measurements rather than electrical resistivity tomography (ERT).
Regarding future directions, spectral induced polarization (SIP) would indeed be a promising approach to explore pore-scale connectivity in more detail. We agree with the reviewer that this represents a valuable next step, and we now mention this in the perspectives section.
To reflect this idea L400-L403 now include:
“In addition, future studies could extend this approach to spectral induced polarization (SIP) to further investigate pore-scale connectivity with greater sensitivity.”
For instance, could Figure 2 be replotted using relative soil moisture content instead of conductivity?
Response: Thank you for this suggestion. We are currently replotting Figure 2 using relative soil moisture content to examine how it compares with the conductivity-based relationship. However, it is important to note that relative water content reflects only the bulk amount of water and does not capture water-phase connectivity or tortuosity, which are the key variables governing diffusion-limited respiration in our study. Once this replotting is completed, we will include it in the revised manuscript if it provides additional insight.
As you mentioned that there is no flow; this would be equivalent to measuring with FDR sensors.
Response: Thank you for this comment. Even under no-flow conditions, FDR sensors are not equivalent to our electrical conductivity measurements. FDR quantifies dielectric permittivity and therefore only the bulk volumetric water content. In contrast, electrical conductivity is sensitive to water-phase connectivity and tortuosity, which are central to diffusion-limited transport and cannot be inferred from bulk water content alone. For this reason, FDR measurements would not capture the processes investigated in our study.
# 2 Materials and methods
The author took advantage of an interesting field site! To me, the material and method are quite well executed with replicated etc .. and explained. Good point for reproducible research!Response: Thank you!
## 2.2. Study approach and incubation set-up
L.120 "Samples were placed in airtight microcosms fitted with a ceramic plate, allowing for adjustments of the pressure head, and a septum for headspace sampling (Poll et al., 2010; Fig.1)": I don't understand why the authors refer to Poll fig 1. In Poll's study, there is no pressure head adjustment nor a septum for headspace sampling. Maybe rephrase and call you figure S1?Response: The microcosm design was adapted from Poll et al. (2010, Fig.1). The microcosm was equipped with a septum for gas sampling and the base was fitted with a ceramic plate connected to a suction system, enabling precise pressure-head control. An opening in the lid was used to route electrical cables for conductivity measurements. A schematic of the modified setup is provided in Fig. S1.
We have updated the manuscript accordingly in L137-140:
“Samples were placed in microcosms adapted from Poll et al. (2010, Fig. 1). The microcosms were equipped with a septum for gas sampling and the base was fitted with a ceramic plate connected to a suction system, enabling precise pressure-head control. An opening in the lid was used to route electrical cables for conductivity measurements. A schematic of the modified setup is provided in Fig. S1. “
## 2.3 Sample preparation for incubation
I would have put this section before 2.2. Does it make more sense in terms of experiment chronology?Response: We have inverted sections 2.2 and 2.3.
## 2.4 Analytical data collection
L 145: CO2 flux measurements - this is a bit short. Particularly the description of the instruments (model, manufacturer, etc..). Please add a reference to figure S1.
Response: Thank you for this helpful comment. We have expanded the description of the CO₂ flux measurements to clarify the sampling procedure and the functioning of the instrument. We now specify that CO₂ concentrations were measured at multiple time points using a micro-GC (Agilent 3000), from which the increase in CO₂ concentration over time was used to calculate respiration rates. We have added details on the instrument model, manufacturer, column type, carrier gas, and detection principle, as suggested. A reference to Fig. S1 has also been included for completeness and consistency with the description of the microcosm setup. The manuscript has been updated accordingly in L168-170:“Soil respiration rates were measured by taking four gas samples (20 mL each) from the microcosm headspace at each applied matric potential. CO₂ concentrations were analysed using a micro gas chromatograph (micro-GC, Agilent 3000). The instrument was equipped with a PLOT Q column (Poropak Q) to separate CO₂ from other gases, and helium was used as the carrier gas. Detection was performed with a thermal conductivity detector (TCD). Respiration rates were calculated from the increase in CO₂ concentration over time. Additional details of the microcosm and gas sampling setup are shown in Fig. S1.”
Does the Agilent measure the "increase in CO2 concentration" or the actual C02 concentration? Rephrase accordingly.
Response: The concentration was measured at different times and the increase was calculated. It has been rephrased.
### 2.4.2 Electrical Conductivity Measurements
L149: a word about injection parameters would be interesting here(number of repetition, voltage required, Vab etc ...)Response: Thank you for this comment. We have added the injection parameters used in our electrical measurements, including the applied voltage, the number of repetitions, and the measurement settings. The manuscript has been updated accordingly in L173-177:
“Sample electrical conductivity was monitored using a PSIP unit (Portable Spectral Induced Polarisation, Ontash and Ermac; ontash.com) in parallel with soil respiration measurements. The PSIP unit was fitted to a custom-made electrode configuration on each sample. A voltage of 5 V was imposed between the current injection electrodes, and the real part of the complex conductivity at 1 Hz was recorded and averaged over five periods. A frequency of 1 Hz was used, aligning with the most commonly employed frequency for electrical conductivity measurements in field studies (e.g., Blanchy et al., 2025).”
L.157: rephrase (currently it reads that there is only injection electrodes to me): [...] with three pairs of potential electrodes inserted ...
Response: Thank you we made this clarification in the manuscript.
L158: distribution of electrical lines --> distribution of current lines or equipotential? Rephrase
Response: Thank you we made this correction in the manuscript to current lines instead of electrical lines.
Unit of EC? (missing in the whole manuscript)
Response: This was added in the Material and Methods and Results section.
### 2.4.3. Organic matter and water content data collection
L.162: “After the measurements had been concluded…” is in past perfect, which is often too heavy for a methods section. suggestion: After the measurements, the samples were dried at 105 °C for 24 hours…Response: Thank you for this observation. We have simplified the sentence by replacing the past perfect with the simple past, as suggested in L187:
“After the measurements, the samples were dried at 105 °C for 24 hours to obtain the final water content of each sample.”
In addition, we reviewed the Methods section more broadly and reformulated several verb tenses to ensure clearer and more consistent readability throughout. The manuscript has been updated accordingly.
### 2.4.4. Statistical analysis and data visualisation
I would suggest to detail the maths and use acronyms such as:The soil respiration flux (FCO2) was obtained as the slope of the regression of CO2 concentration (C, unit?) against time (t, h):
FCO2 = dC/dt
The flux per gram of organic matter (FOM) was then calculated as (then use the acronyms in the figures):
FOM = FCO2 / OMFinally, the relative flux (Frel) was calculated as the ratio of the flux at the given condition to the flux at –70 hPa:
Frel = FOM / FOM(-70 hPa)
Also I recommend substituting electrical conductivity with EC everywhere (except first occurrence)
Response: Thank you for this helpful suggestion. We agree that defining the mathematical expressions and consistently using the proposed acronyms will improve clarity. We will revise this section accordingly by detailing the equations for FCO₂, FOM, and Frel, and by applying the EC acronym throughout the text (after the first occurrence). The manuscript will be updated to reflect these changes.
L178: A word about data quality, how uncertainty evaluation based on repeated samples is assessed, filtering, and outliers would be very welcome.
# Results
## 3.1. Soil respiration rates across soil matric potential and organic matter quantificationL.180: What does "Welch" stand for? I assume this refers to Welch’s test for Satterthwaite’s method, but please clarify this in the previous paragraph.
Response: Thank you for this comment. We have clarified that “Welch” refers to Welch’s test using Satterthwaite’s method for estimating degrees of freedom. This clarification has been added in the Statistical Analysis subsection (L203), where the method is first introduced:
“Variance across matric potentials was assessed using Type III ANOVA with Welch’s test and Satterthwaite’s method for degrees of freedom (appropriate for unbalanced data), implemented via the ‘ggstatsplot’ package.”L.180: The first sentence is difficult to understand and very specific. I suggest starting with a more contextual sentence (for example, stating the range of organic matter, from 0.7 to 4 g per sample), and then explaining the test (degrees of freedom, etc.).
Please also recall the treatment types, i.e., CA and CT.
Response: Thank you for this comment. We have rewritten the opening of this paragraph to provide clearer context by first introducing the variation in organic matter content across samples and then presenting the statistical results. We have also added a reminder of the treatment types (CT = conventional tillage, CA = conservation agriculture) as requested. The manuscript has been updated accordingly in L211-214:
“The organic matter (OM) content varied across samples (Fig. S3), ranging from 3.6% to 14.1%. The lowest OM content was observed in the sieved conventional tillage (CT) topsoil, and the highest in the sieved conventional tillage subsoil. A Welch’s ANOVA indicated no significant differences in OM between treatments (CT = conventional tillage; CA = conservation agriculture), with a small-to-moderate effect size (ω² = 0.27, 95% CI [0.00, 1.00]). ”
L.185: Replace "The relative respiration rate, normalised to the measured values at -70 hPa" with **Frel**.
Response: Thank you this change has been applied.
L.186: The sentence "showed a near-consistent decrease across the tested matric potentials (Fig. 1)" is confusing. A clearer suggestion would be: "showed an increase from 0.01 to 10 as matric potential rose from –996 to –70 hPa (Fig. 1)".
Response: Thank you for this correction suggestion, we have made the replacement accordingly.
- Ensure consistency with the figure, which shows that Frel increases with increasing matric potential.
Response: We have changed the text to ensure consistency.
- Be consistent in terminology: in Fig. 1, you call it *applied suction*, while in the text you use *matric potential*.Response: Thank you for this comment. To ensure consistency throughout the manuscript, we have replaced the term applied suction with matric potential in all relevant sections, including the figure captions. The terminology is now used consistently across the entire article.
L.186: The sentence "For the sieved samples, this decrease was maintained across all matric potentials, while for the undisturbed samples there was a respiration peak at -250 hPa" does not reflect the data accurately. I observe peaks for all samples, with the peak shifting according to the sampling strategy.
Response: This sentence was corrected to: “For the sieved samples, this decrease was maintained across all matric potentials with a small respiration peak being observed at -100 hPa, while for the undisturbed samples there was a respiration peak at -250 hPa.”
## 3.2 Soil electrical conductivity
I don't really understand the idea of comparing the different pairs of electrodes. Do you suspect that the sample is not homogeneous? If so, what is the interest of showing this heterogeneity? (Only CT Topsoil seems to have issues of replicability between pairs.) To me, it would make more sense to take the mean and variance between each pair of measurements (and not between repeated measurements for a single pair) and plot a single line with error bars. This would clearly simplify the interpretation of the figure.
Response: Thank you for this comment. In our setup, each sample was equipped with several electrode pairs, which allowed us to assess the reproducibility of the electrical measurements within a single sample. We presented the results for the different electrode pairs to show that the EC response was consistent across the measurement configuration and not influenced by a single pair. This reproducibility check was an important part of validating the methodology.
We agree that an alternative presentation, such as plotting the mean EC with its associated variance, could also be used. This approach will be considered in future applications where simplifying the visual comparison is the priority. For the present study, we chose to retain the individual pair responses because they directly document measurement repeatability across the electrode configuration. To address the reviewer’s second point, we have clarified that “relative EC” refers to the conductivity of each sample normalized to its value at -70 hPa. This has been added to the manuscript to make the definition explicit in L244-245:
“To improve comparability between samples, we expressed electrical conductivity as the value of each sample normalised to its conductivity at -70 hPa, which corresponded to the highest saturation used in this study.”
L.210: Relative to what? The mean EC of all samples? The sentence "To allow an easier comparison between samples given these differences, we chose to use the relative conductivity of each sampling depth and field trial to improve the comparability between samples" should clarify this.
Response: We adjusted this sentence to: “To allow an easier comparison between samples given these differences, we chose to use the relative conductivity in relation to the value observed at the highest saturation of each sampling depth and field trial.”
L.215: Add a period at the end of the sentence.
Response: The period has been added.
Authors could have conducted the same analysis as in the previous figure to test for significant differences between treatments and sample types from an EC perspective. Demonstrating this could have had a major impact and would have avoided the need to rely on relationships and regression analysis.
Response: Thank you for this suggestion. We agree that comparing electrical conductivity values directly between treatments can be informative under fully saturated conditions or when samples can be brought to an identical saturation state. In our experiment, however, saturation was not imposed; instead, matric potential was controlled for each sample. Because different samples have different water retention properties, the same matric potential does not correspond to the same degree of saturation across treatments or depths. As a result, absolute EC values are not directly comparable between samples at a given matric potential.
For this reason, we focused on the relationship between relative EC and relative respiration rate, which allows us to evaluate the effect of water-phase connectivity independent of differences in intrinsic saturation behaviour. This approach is therefore more appropriate for the objectives of the study.
## 3.3 Relationship between relative respiration rate and relative electrical conductivity
For clarity, in Figure 3, I suggest adding a legend within each subplot showing the R² and p-values, or include a table with R² scores in the manuscript. Otherwise, this paragraph is difficult to read.
Response: Thank you for this helpful suggestion. We will add the R² values and corresponding p-values within each panel of Figure 3 in the revised version to improve readability.
L.222–227: "Because respiration rates in the undisturbed samples decreased between -250 and -70 hPa (Fig. 1). This increase has been recorded in past studies and is caused by limitations in oxygen availability rather than substrate access (Moyano et al., 2013)."
- Be consistent: the first sentence calls it a decrease, the second calls it an increase. This issue appears multiple times in the manuscript; please check for consistency.
Response: thank you for pointing this error out. We have checked the manuscript to ensure that everything is consistent.
- I am not convinced by the explanation provided to remove data between -250 and -70 hPa. Saying "caused by limitations in oxygen availability rather than substrate access" is not sufficient justification for removing it.Response: Thank you for this comment. We agree that the original wording did not fully justify the exclusion of the near-saturation data. Our intention was not to remove points arbitrarily, but to separate two well-established physiological regimes. At very high soil water content, respiration is known to become controlled by oxygen limitation due to low air-filled porosity, rather than by diffusion constraints on substrate transport. Since the purpose of the study was to evaluate electrical conductivity as a proxy specifically under diffusion-limited conditions, we focused our analysis on the matric potential range where diffusion limitation is expected to dominate.
To clarify this, we have rewritten the manuscript's relevant section and added a brief sensitivity comparison in the Supplementary Information showing the relationship both with and without the near-saturation measurements. The overall conclusions remain unchanged, and the comparison demonstrates that the diffusion-limited range shows a clearer and more consistent relationship between electrical conductivity and respiration.
The start of section 3.3. of the results are changed to:
“The relationships between respiration rates and electrical conductivity were established within the matric potential range corresponding to substrate diffusion-limited conditions. At near-saturated conditions (above approximately -250 hPa), respiration was limited by oxygen availability rather than substrate diffusion, consistent with the behaviour shown in Figure 1 and previously reported in the literature (Moyano et al., 2013). Because our objective was to evaluate electrical conductivity specifically under substrate diffusion-limited conditions, only matric potentials drier than the observed respiration peak were included in the analysis of the relationship between respiration and electrical conductivity. For transparency, the full dataset and the corresponding relationships are shown in the Supplementary Information (Fig. S5). For clarity of presentation, we selected to present only electrode pairs 1 and 2. However, the entire data range is presented in the supplementary material (Supplementary, Fig. S5).”
## DiscussionThe discussion is very extensive, which is much appreciated!
### 4.1
Figure 4
- I like the conceptual figure. However, for the diffusion-limited respiration range, your results show a non-linear relationship between EC and CO₂ fluxes, which is not represented in Fig. 4.Response: Thank you for this comment. The conceptual figure illustrates only the general expected trend under diffusion-limited conditions. In our experiment we did not obtain measurements at full saturation, so the empirical data do not include the near-saturated region where a more linear relationship would be expected. As a result, only the diffusion-limited range is represented in our measured data, and within this range the relationship between EC and respiration becomes non-linear due to the rapid loss of water connectivity as matric potential decreases. We have clarified this point in the Results section.
- Could you discuss what it means that the relationship is non-linear? Why fit an exponential model—due to water connectivity, change in respiration regime, or other reasons?Response: Thank you for this comment. The non-linear relationship between electrical conductivity and respiration reflects a threshold-type change in water connectivity as soils dry. At higher water contents, both electrical conductivity and respiration decrease gradually because larger pores drain first while many conductive pathways remain connected. As matric potential becomes more negative, smaller pores empty and tortuosity increases sharply, which causes a more rapid decline in both ion transport and substrate diffusion. This behaviour is consistent with established descriptions of connectivity-driven transitions in diffusion-limited conditions.
To represent this non-linear behaviour without imposing an inappropriate linear form, we fitted a log-log power-law (exponential-type) model. This approach is commonly used for processes controlled by pore connectivity and tortuosity and provides a better representation of the observed pattern than a linear model.
We have added this explanation to the Discussion section for clarity in L299-305:
“The relationship between electrical conductivity and soil respiration in our data was non-linear within the diffusion-limited range. At higher water contents, both parameters decreased only gradually because larger pores drained first while many conductive pathways remained connected. As matric potential became more negative, smaller pores emptied and tortuosity increased sharply, producing a faster decline in both EC and respiration. This threshold-like transition in pore connectivity has been widely reported in diffusion-limited systems and explains why the empirical relationship departs from the simplified linear trend represented in the conceptual figure. For this reason, we described the relationship using a log-log power-law model rather than a linear fit.”
L.255: "Showing a decrease in both measured parameters": I understand you are referring to hydraulic and electrical tortuosity. If so, your results don’t clearly show this (or only indirectly, which is not explained). Consider rephrasing.
Response: That sentence was changed to: “Our results tend to confirm this hypothesis, showing a decrease in both EC and soil respiration as the soils dry, associated with a lower matric potential”
L.285–L.291: The idea that the conductivity of the microenvironment surrounding fungal hyphae increases is cited twice (Ameen et al., 2019; Sun et al., 2022), which is redundant. Consider combining the references into a single statement for conciseness.
Response: Based on this comment we adjusted Line 312-316 as:
“Previous studies have shown that fungal hyphae can alter the electrical properties of their surrounding microenvironment through both chemical and physical mechanisms, including the mobilisation of phosphate ions and the formation of micro-aggregates (Ameen et al., 2019; Hartmann & Six, 2022; Sun et al., 2022). Such effects may explain the isolated increase in electrical conductivity observed in the conventional-tillage subsoil at -630 hPa, although this pattern was not present in other depths or treatments.”
## Conclusion
L.352
- You state "revealed a strong relationship," but this is a simplification. The relationship is non-linear and ranges from 0.07 to 0.84 (Table S9).
- Avoid generic terms like "parameters" or "variables." Refer specifically to EC and CO₂ fluxes to prevent confusion.Response: Thank you for pointing this out. We have replaced the term “strong relationship” with a more accurate description and now acknowledge that the strength of the EC-CO₂ relationship varies across samples. We also explicitly report the R² range (0.07-0.84) and refer directly to electrical conductivity and CO₂ fluxes instead of using generic terms. The sentence has been revised accordingly in the manuscript.
Suggested rephrasing:
"The analysis of the relationship between EC and CO₂ fluxes revealed a strong correlation across the tested soil matric potentials, confirming that both EC and CO₂ fluxes respond similarly to the loss of water availability."Response: Thank you for the rephrasing suggestion, we implemented it in the conclusion.
### Figures
Figure 1:
- Rephrase the figure legend to make it shorter. For example, remove: "The different suctions represent different soil matric potentials analysed over the course of the study."Response: The caption of Figure 1 has been rephrased to read as:
“Mean relative soil respiration fluxes measured across the applied matric potentials (hPa) for each treatment. CA refers to conservation agriculture and CT to conventional tillage. Solid lines represent undisturbed cores and dashed lines represent sieved samples. Respiration rates are normalised to the value at -70 hPa (highest tested saturation) and plotted on a logarithmic scale. Error bars show the standard deviation from triplicate measurements. Further numerical details are provided in Table S3.”
- Use the same color for the same soil treatment, changing only the marker type. Example: CT Topsoil / CT Topsoil sieved — same color, different marker type.
- Add units to the y-axis.Figure 3: missing unit for "applied pressure" in the legend panel
Response: Thank you for these helpful suggestions. We will adjust the figures accordingly. Specifically, we will:
- Use a consistent colour scheme for each soil treatment, varying only the marker type to distinguish sieved and undisturbed samples.
- Add the appropriate units to all y-axes.
- Add the missing unit for “applied pressure” in the legend of Figure 3.
These corrections will be implemented in the revised figures.
-
AC2: 'Reply on RC2', Orsolya Fülöp, 24 Nov 2025
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General comments
The authors present a study where electrical conductivity measurements were related to soil CO2 emission from intact and sieved cores.
The mansucript is well-structured and in written in a consice style. I am not a native speaker, but I think the written English is OK. I made some suggestions for edits.
Soil heterotrophic respiration is known to vary with soil water status. Electrical conductivity measurements are used over a wide range of spatial scales as a proxy for water content. This study directly relates soil heterotrophic respiration to electrical conductivity measurements. In this respect I have two general comments:
1) Apart from the basic research aspect of this study, what is the potential use of this respiration/electrical conductivity relation? Is the idea to generate e.g. a field-scale map of soil heterotrophic respiration from spatially-distributed electrical conductivity measurements? This should be pointed out in the conclusions section. In the Introduction, I am also missing the motivation for this study.
2) Why is respiration related to pressure head? Pressure head can clearly be used to describe the soil water status, but it is probably the variable with the worst indication of diffusivity in the soil pore water. From a soil-physics point of view, volumteric water content or water-filled pore space will be a much better indicator of the volume (!) available for diffusion. If the soil water retention function is known, this can of course easily be converted ...
Other methodological aspects:
I would be interested to see a more physically-based interpretation of the data. Now, we have something like an empirical black box model (ECa in - Rh out). What about using e.g. the Topp et al. 1980 (or something more recent and advanced) approach to estimate water content from ECa. Then estimate relative diffusivity in dependence of porosity and the estimated water content. The Millington-Quirk approach is well-established, but I could imagine that more recently-developed approaches (e.g. from Peer Moldrup and his group) even perform better. Subsequently, relate relative diffusivity to heterotrophic respiration.
Specific comments
19 replace 'surrounding' with 'in'?
46 replace 'believed' with 'supposed'?
62 I disagree. The single most important factor affecting microbial processes is temperature. At least under field conditions, soil temperature is much more relevant than soil water status. There is a number of studies on that topic, e.g Bauer et al. 2008 (Geoderma) or Fang & Moncrieff, 1999 (Agric. For. Meteorol.)
75 I guess 'the quantification of soil' must be removed here
77 Why matric potential and not water-filled pore space or water content? With a perspective on the transfer of results of this study, water content is much easier to measure that matric head. Further, a sandy soil will have a very different water content than a silty soil at the same pressure head. And in the end, the water volume available for diffusion is what drives nutrient accessibility, just as summarized nicely in the first part of this introduction.
140 a bulk density of 1.73 g/cm3 is relatively high, particularly for a frequently tilled topsoil. The conventional till soil would be expected to have a consistently lower bulk density than the conservation tilled (no-till) topsoil.
183 I think 'compared to' should be replaced with 'and'
Fig. 3 I wonder how much water is in the soil at those pressure heads. A soil water retention curve would be helpful. I guess this could easily be obtined by fitting a function to the measured water content/pressure head pairs. I assume water content can be computed from the measured weight?!
266 Macropores in the undisturbed samples?