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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RC1: 'Comment on egusphere-2025-1730', Anonymous Referee #1, 22 Jul 2025
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?Citation: https://doi.org/10.5194/egusphere-2025-1730-RC1 -
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
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