the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Jan 2026
Plant-soil interactions drive GHG dynamics in organic soils under variable water tables: a case study with poplar
Abstract. Organic soils provide a substantial capacity for carbon storage both in below- and above-ground biomass, but they are also a significant contributor to natural terrestrial Greenhouse gas (GHG) emissions. Organic soil melioration, carried out to increase the primary productivity, often leads to increased CO2 emissions. By monitoring a controlled environment, it is possible to determine how organic soil management practices influence the carbon cycle, including plant vitality and productivity, and consequently shape future carbon sequestration potential.
The aim of this study was to develop a system under semi-controlled conditions to assess the impact of different groundwater levels on GHG emissions, accumulated biomass, and tree vitality. We conducted experiments in semi-controlled conditions to determine the effects of different groundwater levels (-2 cm; -15 cm; -25 cm; -35 cm) on CH4 and CO2 emission, soil chemical analyses, and plant morphological (biomass, root and leaf area, shoot length) and physiological (leaf chlorophyll a and b content) parameters. Temporal and diurnal variation strongly impacted GHG fluxes due to the changes in temperature, moisture, and plant growth activity. During soil temperature extremes, extremely high CH4 emissions occurred at a -2 cm groundwater level. Higher plant productivity had a greater influence on GHG fluxes: it decreased both CH4 and CO2 emissions during the day compared to bare soil. Therefore, the autotrophic respiration rate increased with increased productivity, but the primary determinant was heterotrophic respiration.
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RC1: 'Comment on egusphere-2025-4493', Anonymous Referee #1, 01 Mar 2026
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AC1: 'Reply on RC1', Austra Zuševica, 12 Apr 2026
The manuscript is well-structured and addresses the important topic of CO2 and CH4 emissions from managed organic soils, with clear implications for climate-smart forestry. Strengths include the semi-controlled setup to isolate water table effects and the integration of plant physiology with GHG fluxes.
However, clarification on the replication structure is needed (n=1 box per water level, split into veg/bare sections?) and extrapolation to annual fluxes (t C ha⁻¹ year⁻¹) from ~2.5 months of data is bold, especially with seasonal spikes like June CH₄ extremes. It would be good to present GHG fluxes as short-term rates per day or hour to avoid overgeneralization, and/or please provide details on the scaling method used, including your assumptions about non-measured periods.
Answer: Yes, this study does not include replicates for the different sections. We acknowledge this limitation, however, as this was a pilot study, we faced technical constraints. To partly address this, we introduced replication at other levels, for example by planting multiple (n = 5) poplars within the vegetated section, carrying out multiple rounds of GHG emission monitoring. We also agree that this limitation was not sufficiently acknowledged in the text. Therefore, we have added a statement at the end of the Discussion highlighting these constraints (Lines 468–472).
The presentation of GHG fluxes as short-term rates was also suggested by another reviewer. Accordingly, we revised the calculations and now present fluxes rate per day. We agree that the previous approach could lead to overgeneralization and overestimation of annual fluxes. Initially, we used that approach because it is widely applied in the literature and we aimed to ensure comparability with other studies. However, the revised approach is more appropriate for our data.
Specific comments:
Line 7: No need to capitalize “g” in “greenhouse”
Answer: Done (Line 8).
Line 11-15: Some of the info here is repeated, like no need to tell me twice that the experiment is in semi-controlled conditions
Answer: Corrected (Line 14).
Abstract: Some info on the effect of organic soil melioration on GHGs would be nice as this is the initial framing. Or, if the study doesn’t provide answers to this question, focus on groundwater table as that seems to be the main study factor. Maybe also inform the reader in the abstract that they are going to learn about autotrophic vs heterotrophic respiration.
Answer: We included statement with a main take home message at the end of the abstract, summarizing that the results showed, that groundwater together with plant productivity and environmental condition influence GHG emissions (Lines 22-23). We also indicated in the middle of abstract that both autotrophic and heterotrophic respiration were determined (Line 16).
Line 76: I am convinced that the light intensity in the greenhouse was consistent with the region, but the argument about shading is less convincing. Shading was consistent with which conditions exactly? Field conditions? In young poplar forest, old poplar forest, peat area? Shrub zones, the treeline?
Answer: We agree that this lacks evidence and excluded shading from the text (Line 86)
Line 63: But no data on diurnal variability is presented in this study. Only arithmetic means per day, or day/night splits. This effectively erases any insights to diurnal variability, like duration of sunrise/sunset, how long during the day temperatures are at the optimum for given plant species, how quick temperature rises/falls etc. Maybe some diurnal plots could be added?
Answer. As in this research we also address the correlations with soil temperature, which is known to be a driver for soil emissions, we now included analyses depending on different air temperature intervals in both bare and plots with poplar. We chose these intervals according to the optimal temperature for poplar in our region (20–25°C) DOI:10.3390/plants12051152), and we have also have observed in other studies that during daytime, with increasing temperatures, the photosynthetic activity slows down for poplar. In other studies, we conducted photosynthetic activity measurements in the morning, before temperature reaches too high levels (DOI:10.1101/438069).
We chose air temperature intervals during daytime, the active photosynthetic period, below optimum(<20°C), optimum (20-25°C), and above optimum (>25°C). We did, however, observe a tendency of increasing emissions depending on temperature, although the statistical analysis did not show any significant results. The main effect on poplar was seen in the later observation period for groups -25 and -35 cm (highest plant biomass), when the biomass exceeds its maximum, and at the highest temperatures, where it can be seen that sections with poplar emit more CO₂. This could be due to increased respiration processes in plants and soil and decreased photosynthesis. However, these data had high variability and also different sample sizes in each temperature interval, therefore the results should be interpreted with caution.
We included this section under 3.2 subsection in the results (Lines 317-330). We also included additional information in method section (Lines 223-225), and also talked more about this in discussion section (412-417).
Line 69: Does this mean ALL studied soils were organic soils? In that case, the study does not test the effect of organic content in soil, as no control exists for this factor. So please remove from the abstract.
Answer: Thank you for your question. Yes, all soils included in this study is organic, but we did not tested different organic contents in this study. Only mineral soil tested, was the control in the highest water table level, we now indicated this in method section (Lines 88-96, 108-109). We did not mention it earlier, because the scope of this study was not to see the differences between mineral and organic, we installed this control, just to be sure our system works properly and can distinguished the differences in GHG emissions form mineral and peat soils. We carried out soil chemical analyses only to see how they corelate with other our observed parameters, not to compare organic content in soil. We will remove plural form of ‘Soils’ in the title, as this manuscript includes only 1 soil (Line 1). Sorry if we are mistaken if this was the issue place, but we did not find a place in abstract where we mentioned soil organic content.
Line 86/117: Please clarify the replication structure: How many independent replicates for each soil organic matter content x water table x plant level?
Answer: Thank you for your suggestion, we now clarify that all water table levels except -2 cm was installed only in one repetition, the -2 cm was installed in two repetitions, because we create the control of two soils: mineral and peat, which we used to create the substrate used in this study (Lines 97-99). We did not include earlier this in to the study, because it was just to make sure that our created study design is able to detect the differences of the substate. It was effective, and now we also include this aspect in the methos section. We also added addition figure in appendix, however, we still do not think this should be added to result section main text, as it was not so much part of the experiment, as the more the way to calibrate study design usage (Lines 488-495).
Line 100: So, this study uses a single mixed substrate (peat + mineral soil from two depths, layered consistently across all boxes) to meet the >20% organic matter threshold for "organic soil."? It's thence not testing varying soil organic matter content as a factor, everything is presented by groundwater level only, and no significant differences in OM are analyzed or graphed. Please rewrite abstract and intro accordingly.
Answer: We have now included in the text a clarification that there are no differences in soil organic matter (OM) between the sections at the beginning of the study (Line 117). We agree that this study does not test varying soil organic matter, but rather focuses on how groundwater level and vegetation influence the carbon cycle, which includes soil OM and emissions.
If the abstract was written in a way that could mislead the reader into thinking that our aim was to investigate differences in emissions related to varying OM, then we acknowledge that we may not have clearly communicated the main idea of the research. However, we are currently unable to identify a specific place in the abstract where such an interpretation might arise, and we would greatly appreciate it if you could indicate which part may be problematic.
At this stage, we have revised the abstract to reduce emphasis on organic soil as a varying factor and instead focus more clearly on high emissions from soils with high organic carbon content, which are primarily regulated by groundwater level (Lines 7-23).
Line 126: I do not know how often OPUS is updated, but it seems a bit strange to me to provide the date and time stamp of the version.
Answer: We excluded this (Line 144)
Line 133/134: Why express GHG as yearly fluxes when measurements cover much shorter periods? It would be more meaningful to present data per hour or per day if it must be.
Answer: We acknowledge this drawback and recalculated these values per day (Line 162).
137: every 5 mins. What happened between these periods?
Answer: We selected this period because the system used detects soil temperature with a precision no higher than 0.5 °C, therefore, it is unable to capture small changes occurring within this period. We also verified that one of the fastest detectable changes of 0.5 °C occurred over approximately 40 minutes. We also included accuracy in method section (Line 164).
Line 138-142: At what time of day/light intensity was chlorophyll fluorescence measured? Were the measurements standardized for time of day/light intensity?
Answer: We did not measure chlorophyll fluorescence, for observation of chlorophyll a and chlorophyll b we used nondestructive method using spectrophotometer (Lines 147-149). We acknowledge that this may be misleading, as in some pats we referred to Chl a and Chl b content, when it is really Chl content index, we will edit this throughout the manuscript.
We carried out samples with a near-infrared ‘The SpectraVue’ leaf spectrometer in the morning hours to avoid heat stress (Lines 173-174)
Line 214/15: Please rephrase
Answer: Edited (Line 254-255)
Line 222-25: Why is non-normality an “issue”?
Answer: We rephrased this part, we agree that this is not an issue, but just data distribution (Lines 264-265)
Line 233:34: what does the R2 tell us here?
Answer: R² indicates how much variability is explained by the model. Although the higher R² value (R² = 0.37) is still not particularly high, the main focus was to demonstrate moderate (for −2 cm and −15 cm) variation in comparison to low (for −25 cm and −35 cm) variation. We also included this limitation aspect in the Results section (Lines 295-297).
Line 241: No need to capitalize “d” in “day”
Answer: Edited (Line 286)
Figure 5: After reading the abstract I was really expecting a figure showing GHG-emissions as a function of soil organic C content. Since this is not possible from the experimental design, maybe rephrase abstract/intro focusing on water table instead of OM content.
Answer: We revised our abstract to be focus more on groundwater rather than organic matter of soil (Lines 7-23). We also made some changes in introduction highlighting the focus on water table regulation (Lines 37-38, 40, 78)
Figure 4+6: I am not entirely convinced that we can assume linearity across the spare measurements.
Answer: Given the relatively sparse measurements, strict linearity cannot be assumed. The regression lines are used to illustrate general temporal trends rather than to define a predictive relationship. Due to the high variability typical for physiological data under semi-controlled conditions, linear regression is applied here as a descriptive tool to highlight differences in temporal dynamics between treatments, which are not as clearly visible from summary statistics alone.
Although the R² values are moderate, the regression analysis indicates that responses at higher groundwater levels (−2 cm) are more structured compared to deeper drained conditions, where variability is higher and trends are less consistent. This supports the interpretation that temperature sensitivity is stronger under shallow groundwater conditions, even if the overall explanatory power of the model remains limited.
As in the previous comment, we have already included a statement in the Results section explaining the meaning of R² values in Figure 6; we will also add a short comment about Figure 4 in the paragraph where these results are explained (Lines 276–277).
Line 285: … can decrease productivity at the young seedling growth stages investigated here. Would it be the same for more mature trees?
We agree, that the treshholds for this may differ depending on different stages of tree maturation, therefore we included this in discussion (Lines 352-354)
Line 292: Leaf? Leaves?
Answer: Edited (Line 360)
Line 312: initial?
Answer: Edited (Line 382)
Line 339: The proportion was not really measured but only inferred from parallel measurement of unplanted soil (where the microbial community may be entirely different). Therefore, I’d be in favor of a more careful interpretation. Do you have measurements to show that microbial biomass/community composition were not significantly different between planted and unplanted soils?
Answer: Thank you for your comment. We do not have measurements of microbial biomass and communities; the only reference is that we used identical substrates for both bare soil and poplar sections. Therefore, we know that at the beginning of the experiment the microbial communities in both sections were similar. We now include a part in the Discussion section (Lines 421–426) stating that changes in microbial communities during and at the end of the experiment were not controlled and may have occurred. However, we also highlight that, although this is clearly heterotrophic respiration, it is indirectly driven by plants and can be attributed to a plant effect. We also mention that this may lead to an overestimation of autotrophic respiration.
Line 376: Diurnal variability was not really presented in this manuscript?
Answer: We will now exclude the word “strongly” from this conclusion, as the results indicate that temporal variation (between periods) influenced this effect strongly, while the results from the diurnal analysis indicated only possible trends without significant values. Therefore, it cannot be described as a strong influence (Line 476).
Citation: https://doi.org/10.5194/egusphere-2025-4493-RC1
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AC1: 'Reply on RC1', Austra Zuševica, 12 Apr 2026
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RC2: 'Comment on egusphere-2025-4493', Anonymous Referee #2, 15 Mar 2026
General comments
This paper presents the effect of different groundwater levels on GHG emissions in the case of bare soils vs cultivated soils (poplar + F. ovina). The experimental design is smart, and the semi-controlled conditions allow for precise adjustment of the groundwater levels which of course wouldn’t be possible in an open environment.
The results show that even for tree species that benefit from high water content, water-saturated soils (groundwater level at -2 cm especially) prevent efficient growth of the vegetation. Also, high groundwater levels reduce CO2 emissions but enhance CH4 emissions through anaerobic processes.
Although I acknowledge the difficulty of conducting long term experiments and managing the material aspect (need for space, etc.), the lack of replicates may be an issue, as well as the short duration of the experiment (less than 3 months), especially to derive long term trends.
However, while not perfect, the experiment and manuscript still give a great insight in the way the plants and environmental conditions interact and generate GHG, especially in the context of worldwide peatlands degradation.
Specific comments
L84: 'Water regulation system was installed inside each of the five hydroisolated boxes at four different levels depending on the depth from the soil surface: -2 cm, -15 cm, -25 cm, and -35 cm' → so, out of the five boxes, there was one at -2 cm, one at -15 cm, one at -25 cm and one at -35 cm? Was the fifth one a control box? If so, please write it. Sorry if I’m misunderstanding something here.
L137: why not monitor temperature all along the experiment? Same for chlorophyll.
L177: why '1/Date' (and not just 'Date')?
L205: the -2 cm trees did not show any root development? Also, did you correct the below-ground biomass with the mass of the stems you planted at t=0? If not, did you make sure all stems were initially around the same width and mass?
L207: the sentence seems unclear to me, as I would interpret 'shallow' as -2 cm. However, given your statement, I suppose it rather refers to -35 cm. Please clarify this, at least once, so that you can then use shallow without risking misinterpretation. Also, accumulation does not only depend on biomass production but also on biomass degradation…which might be lower in -2 cm (water-saturated environment) than in -35 cm conditions.
L223: To me, 'high weekly variability' means that there is a weekly pattern with high variability along the week. I suppose you rather mean it varies greatly along the weeks, from one measurement to the other. If so, this sentence may need rephrasing. You should also rephrase the caption of Figure 4 the same way.
L231: what do you mean by 'the most important' and 'the most significant'? The days with the highest chlorophyll concentrations? If so, this may not be the most adequate wording.
L238: 'on soil respiration depth'? I don’t think 'depth' belongs here, does it?
L327: is 'per year' a good unit as you are specifically talking about huge differences in GHG emissions from one month to the other? While the overall conclusion will be the same, wouldn’t 'per month' or 'per day' make more sense?
L353: diurnal or daily?
The whole discussion section might benefit from slight changes, such as adding subsections with clear titles, to help structure the reflection and guide the reader along.
Technical corrections
All along: please be careful with overall English, punctuation and wording: some sentences are unclear, and many would be improved with (adequate) use of commas. The sentences tend to be long. Also, the way you introduce statistical results and p-values along the text may benefit from a change. It lacks punctuation between the different groundwater levels, and globally lowers the readability of the text where it is introduced.
L31: 'decreasing CH4' I guess.
L33: 'Although these are the main threats after peat drainage, recent studies show that whether the ecosystem on organic soil acts as a carbon source or sink is significantly determined by local environmental conditions, vegetation, land use, chemical and physical properties […]' → to me it feels a bit strange to put 'land use' in this list, as you are precisely explaining before that peat drainage is a problem, and I interpret peat drainage as a land use change in itself.
L83–84: typo (×3): 'from', not 'form'. Same L140 (×1) and 141 (×1).
L101: 'kg' not needed (it is a ratio).
L109: '-1' in superscript (×2).
L140–142: the sentence is unclear, please rephrase. Also, what does CCI stand for?
L194–197: This is already visible on the figure as you indicated significant differences with different letters. I suppose you want to emphasize that it is even smaller than 0.05, but I don’t think it’s needed. If you want to keep it, I would advise to find another way to present these statistical results (a table?).
L206: in Figure 2, '-2 cm' suddenly turned into -5 cm on the figure. Please correct all the occurrences.
L227–230: I would advise to find another way to present these statistical results (a table?).
L247: 'Nevertheless, the regression analyses showed […]' → Unclear, probably lacks punctuation.
L249: '10000 kg c' → '10000 kg C'.
L289: 'with for' → please correct.
L321: remove 'are', or make two different sentences.
L333: grammar → 'the vegetation negatively influences', or 'the vegetation negative influence on'
L345: 'in advance'? I don’t understand.
Citation: https://doi.org/10.5194/egusphere-2025-4493-RC2 -
AC2: 'Reply on RC2', Austra Zuševica, 12 Apr 2026
General comments
This paper presents the effect of different groundwater levels on GHG emissions in the case of bare soils vs cultivated soils (poplar + F. ovina). The experimental design is smart, and the semi-controlled conditions allow for precise adjustment of the groundwater levels which of course wouldn’t be possible in an open environment.
The results show that even for tree species that benefit from high water content, water-saturated soils (groundwater level at -2 cm especially) prevent efficient growth of the vegetation. Also, high groundwater levels reduce CO2 emissions but enhance CH4 emissions through anaerobic processes.
Although I acknowledge the difficulty of conducting long term experiments and managing the material aspect (need for space, etc.), the lack of replicates may be an issue, as well as the short duration of the experiment (less than 3 months), especially to derive long term trends.
However, while not perfect, the experiment and manuscript still give a great insight in the way the plants and environmental conditions interact and generate GHG, especially in the context of worldwide peatlands degradation.
Specific comments
L84: 'Water regulation system was installed inside each of the five hydroisolated boxes at four different levels depending on the depth from the soil surface: -2 cm, -15 cm, -25 cm, and -35 cm' → so, out of the five boxes, there was one at -2 cm, one at -15 cm, one at -25 cm and one at -35 cm? Was the fifth one a control box? If so, please write it. Sorry if I’m misunderstanding something here.
Answer: In this study, only four boxes were included in the analysis, corresponding to predefined water table depths (−2 cm, −15 cm, −25 cm, and −35 cm from the soil surface). Additionally, one control box at −2 cm was established, containing both mineral soil and peat, which were the substrates used in the other experimental boxes. This information has now been included in the Methods section, and emission values from the control box have also been added (Lines 98-99, 102-103, 117-119, 485-492).
L137: why not monitor temperature all along the experiment? Same for chlorophyll.
Answer: We did monitor air temperature and moisture throughout the experiment. We did not have the possibility to monitor soil temperature continuously, as our chosen method was removable temperature plugs, which needed to be removed from the soil in the greenhouse and read in the laboratory. Therefore, we decided to monitor soil temperature only during the periods when we had the opportunity to carry out GHG analysis. This was also limited by the project finances as well as the delivery of nitrogen gas needed for GHG measurements. Our primary reason for gathering soil temperature data was to use it in GHG calculations. The same applied to chlorophyll, we carried out as many repetitions as possible with these measurements.
L177: why '1/Date' (and not just 'Date')?
Answer: The model includes Date as a random effect, however, the brackets were excluded in the text by mistake. The notation has been corrected to (1 | Date) (Lines 210-218).
L205: the -2 cm trees did not show any root development? Also, did you correct the below-ground biomass with the mass of the stems you planted at t=0? If not, did you make sure all stems were initially around the same width and mass?
Answer: We planted bareroot stem cuttings with only initiation of root nods (one week in water). We did select the around same size cuttings for experiment. However, there was some error, as it was hard to collect them identically, we now will acknowledge this in method section (Line 129).
L207: the sentence seems unclear to me, as I would interpret 'shallow' as -2 cm. However, given your statement, I suppose it rather refers to -35 cm. Please clarify this, at least once, so that you can then use shallow without risking misinterpretation. Also, accumulation does not only depend on biomass production but also on biomass degradation…which might be lower in -2 cm (water-saturated environment) than in -35 cm conditions.
Answer: Thank you for your comment, we see, that we need to indicate more precisely in the method section. Our drainage graduation was based mainly on methane emissions. Previous studies show that they increase drastically when water table exceeds 25-20 cm belowground, therefore, we used this to determine the depth of the drainage – deep drainage – Very low CH4 emissions expected (-35 cm), shallow drainage – increase of CH4 emission expected (-15 and -25 cm), no drainage – very high CH4 emission expected (-2 cm). In this sentence it was actually meant -35 cm, as the average trend was more productive in all parameters, but did not show significant differences. We corrected this in the text (Line Line 241). We also include now our gradation in the method sections (Lines 97-98).
L223: To me, 'high weekly variability' means that there is a weekly pattern with high variability along the week. I suppose you rather mean it varies greatly along the weeks, from one measurement to the other. If so, this sentence may need rephrasing. You should also rephrase the caption of Figure 4 the same way.
Answer: Thank you for comment, we did indeed mean that it varies between different weeks, we rephrase this sentence (Lines 263, 280)
L231: what do you mean by 'the most important' and 'the most significant'? The days with the highest chlorophyll concentrations? If so, this may not be the most adequate wording.
Answer: We agree, that this is not adequate wording, we rephrase sentences, as this was meant, when the peak concentrations of Chl A and Chl B were observed (Lines 271-274).
L238: 'on soil respiration depth'? I don’t think 'depth' belongs here, does it?
Answer: We excluded ‘depth’ form subtitle (Line 283)
L327: is 'per year' a good unit as you are specifically talking about huge differences in GHG emissions from one month to the other? While the overall conclusion will be the same, wouldn’t 'per month' or 'per day' make more sense?
Answer: Thank you for your comment. We agree that your suggestion would be logical from the perspective of this manuscript. We firstly chose to express emissions on a per-year basis despite measurements being conducted only over a two-month period, because this is the standard unit used in greenhouse gas studies. Using this convention facilitates comparison with other published results. However, we also were aware that this could be useless comparison taking in mind that this may be a large overestimation due to the measurements only during active vegetation period. We decided to calculate and redraw our figures to per day calculations (Lines 298-305, 326-329). We also wrote addition paragraph in discussion section acknowledging this issue (Lines 453-458)
L353: diurnal or daily?
Answer: Thank you for your questions. For the listed factors, variability occurs at both daily and diurnal scales. Here, we emphasized diurnal variability as a reference for the differences we found, shown in Figure 5, between daytime and nighttime hours.
The whole discussion section might benefit from slight changes, such as adding subsections with clear titles, to help structure the reflection and guide the reader along.
Answer: Thank you for your comment, we now included similar subsections as for result section, adding additions in the end of the discussion section where we talked about experimental design, greenhouse conditions, and implications for future climate scenarios (Lines 348, 390, 435)
Technical corrections
All along: please be careful with overall English, punctuation and wording: some sentences are unclear, and many would be improved with (adequate) use of commas. The sentences tend to be long. Also, the way you introduce statistical results and p-values along the text may benefit from a change. It lacks punctuation between the different groundwater levels, and globally lowers the readability of the text where it is introduced.
Answer: We went throughout the text and carefully edited vocabulary and grammar. Also, we change the way of introducing statistics, moving them to the tables of Appendix section.
L31: 'decreasing CH4' I guess.
Answer: Edited (Line 35)
L33: 'Although these are the main threats after peat drainage, recent studies show that whether the ecosystem on organic soil acts as a carbon source or sink is significantly determined by local environmental conditions, vegetation, land use, chemical and physical properties […]' → to me it feels a bit strange to put 'land use' in this list, as you are precisely explaining before that peat drainage is a problem, and I interpret peat drainage as a land use change in itself.
Answer: We agree on this, by this we meant current and/or previous ecosystem on peat soil (etc. peatland, peatland forest, agriculture), but this can also attribute to already listed factors as vegetation and the history of peat accumulation, therefore we decided to exclude land use (Line 40).
L83–84: typo (×3): 'from', not 'form'. Same L140 (×1) and 141 (×1).
Answer: Edited (Lines 93-94, 171)
L101: 'kg' not needed (it is a ratio).
Answer: Excluded (Line 115)
L109: '-1' in superscript (×2).
Answer: Edited (Line 126)
L140–142: the sentence is unclear, please rephrase. Also, what does CCI stand for?
Answer: Thank you for suggestion. We agree that this sentence may be hard to understand, maybe also because of its length. Therefore, we separated it in three distinct sentences, which we also rephrased (169-173). We now indicated in the text when first mentioned, that CCI refers to Chlorophyll Content Index (Line 169).
L194–197: This is already visible on the figure as you indicated significant differences with different letters. I suppose you want to emphasize that it is even smaller than 0.05, but I don’t think it’s needed. If you want to keep it, I would advise to find another way to present these statistical results (a table?).
Answer: We agree that this is a lengthy way to show statistics, and its not needed, when we already showed same results in figure. We excluded them here and also in similar situations throughout the paper. We have now created tables for statistically significance results (527-545).
L206: in Figure 2, '-2 cm' suddenly turned into -5 cm on the figure. Please correct all the occurrences.
Answer: We edited Figure 2 and Figure 4, where older version was left. We were firstly planned to regulate water table in height of -5 cm, but later after establishing experiment, it was seen that water table for this group was higher, respectively, -2 cm, therefore, we corrected this group (Lines 245, 280).
L227–230: I would advise to find another way to present these statistical results (a table?).
Answer: Thank you for suggestion, we added 5 tables in Appendix section, at the end of paragraph, with statistically significant differences, that previously were displayed in brackets (527-545). In the main text we now only reference these tables (Lines 235, 239, 251, 253, 268, 290, 291)
L247: 'Nevertheless, the regression analyses showed […]' → Unclear, probably lacks punctuation.
Answer: Thank you for your comment, we separated this sentence in two to increase readability (Line 293-294).
L249: '10000 kg c' → '10000 kg C'.
Answer: Edited (Line 294)
L289: 'with for' → please correct.
Answer: ‘for’ excluded (Line 358)
L321: remove 'are', or make two different sentences.
Answer: Removed (Line 393)
L333: grammar → 'the vegetation negatively influences', or 'the vegetation negative influence on'
Answer: included ‘on’ (Line 407)
L345: 'in advance'? I don’t understand.
Answer: Edited to “In addition”
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AC2: 'Reply on RC2', Austra Zuševica, 12 Apr 2026
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The manuscript is well-structured and addresses the important topic of CO2 and CH4 emissions from managed organic soils, with clear implications for climate-smart forestry. Strengths include the semi-controlled setup to isolate water table effects and the integration of plant physiology with GHG fluxes.
However, clarification on the replication structure is needed (n=1 box per water level, split into veg/bare sections?) and extrapolation to annual fluxes (t C ha⁻¹ year⁻¹) from ~2.5 months of data is bold, especially with seasonal spikes like June CH₄ extremes. It would be good to present GHG fluxes as short-term rates per day or hour to avoid overgeneralization, and/or please provide details on the scaling method used, including your assumptions about non-measured periods.
Specific comments:
Line 7: No need to capitalize “g” in “greenhouse”
Line 11-15: Some of the info here is repeated, like no need to tell me twice that the experiment is in semi-controlled conditions
Abstract: Some info on the effect of organic soil melioration on GHGs would be nice as this is the initial framing. Or, if the study doesn’t provide answers to this question, focus on groundwater table as that seems to be the main study factor. Maybe also inform the reader in the abstract that they are going to learn about autotrophic vs heterotrophic respiration.
Line 76: I am convinced that the light intensity in the greenhouse was consistent with the region, but the argument about shading is less convincing. Shading was consistent with which conditions exactly? Field conditions? In young poplar forest, old poplar forest, peat area? Shrub zones, the treeline?
Line 63: But no data on diurnal variability is presented in this study. Only arithmetic means per day, or day/night splits. This effectively erases any insights to diurnal variability, like duration of sunrise/sunset, how long during the day temperatures are at the optimum for given plant species, how quick temperature rises/falls etc. Maybe some diurnal plots could be added?
Line 69: Does this mean ALL studied soils were organic soils? In that case, the study does not test the effect of organic content in soil, as no control exists for this factor. So please remove from the abstract.
Line 86/117: Please clarify the replication structure: How many independent replicates for each soil organic matter content x water table x plant level?
Line 100: So, this study uses a single mixed substrate (peat + mineral soil from two depths, layered consistently across all boxes) to meet the >20% organic matter threshold for "organic soil."? It's thence not testing varying soil organic matter content as a factor, everything is presented by groundwater level only, and no significant differences in OM are analyzed or graphed. Please rewrite abstract and intro accordingly.
Line 126: I do not know how often OPUS is updated, but it seems a bit strange to me to provide the date and time stamp of the version.
Line 133/134: Why express GHG as yearly fluxes when measurements cover much shorter periods? It would be more meaningful to present data per hour or per day if it must be.
137: every 5 mins. What happened between these periods?
Line 138-142: At what time of day/light intensity was chlorophyll fluorescence measured? Were the measurements standardized for time of day/light intensity?
Line 214/15: Please rephrase
Line 222-25: Why is non-normality an “issue”?
Line 233:34: what does the R2 tell us here?
Line 241: No need to capitalize “d” in “day”
Figure 5: After reading the abstract I was really expecting a figure showing GHG-emissions as a function of soil organic C content. Since this is not possible from the experimental design, maybe rephrase abstract/intro focusing on water table instead of OM content.
Figure 4+6: I am not entirely convinced that we can assume linearity across the spare measurements.
Line 285: … can decrease productivity at the young seedling growth stages investigated here. Would it be the same for more mature trees?
Line 292: Leaf? Leaves?
Line 312: initial?
Line 339: The proportion was not really measured but only inferred from parallel measurement of unplanted soil (where the microbial community may be entirely different). Therefore, I’d be in favor of a more careful interpretation. Do you have measurements to show that microbial biomass/community composition were not significantly different between planted and unplanted soils?
Line 376: Diurnal variability was not really presented in this manuscript?