With their manuscript, the authors would like to share a full year of data on greenhouse gas fluxes from soil and ditch in a drained fen in Denmark. This is really kind of them, especially since the dataset appears to be of very good quality and obtaining it must have involved both financial and human effort. It is highly respectable, but surprising (for me at least) that they don't seek to promote it with a conventional article before sharing it with the rest of the community. I am not used to reviewing data papers and hope my comments will be helpful nonetheless.

I have only one major concern related to the discarded data. Discarding non-significant regressions as explained line 238 is a problem. If the flux is almost 0, the slope is also almost 0 and the regression, by nature, is non-significant. If a significant number of low fluxes were discarded, then means and cumulated fluxes used for annual budget in Table 3 for example are over estimated (in absolute value). Similarly, “wrong windows” (lines 251-259) can be repositioned. Of course, this takes time, but it is worth doing.

Minor comments

L25: replace by “flux was more dynamics”

L43: “changes” (plural)

L59: explain why night-time fluxes are expected to be overestimated

L166: provide the length of the long tube (important that the colleagues that will work with these data understand well how it was measured)

L166: “On the top” is duplicated. Remove one.

L173: clarify “thus” and the link between “net flux” and weed killing

L241: Use “annual cumulated fluxes” instead of “annual budget”

Fig 9,10: thicker green line will be appreciated

L345: was -> were

Fig 11, 18B, 18C: a horizontal line at intercept 0 will help

Section 3.6 seems oddly structured, starting with the annual cumulated fluxes, followed by  individual measures (5 per day) and then the monthly sum

I would like to thank the authors for compiling this extensive dataset and corresponding manuscript. 

I think the dataset could be very valuable to the research community. Before publication, I think both the dataset and the manuscript need revision.

General comments:

The structure and content of the manuscript reflect that of a classic research article, but the authors chose ESSD for publication. Given the focus on datasets in ESSD, I strongly recommend to revise the datasets to make them easy-to-use and comprehensive for potential users.

I find a bit concerning that the site experienced different levels of disturbance and wonder if that may affect the potential for modelers to use this data? Some discussion could be added in the manuscript, and possibly convincing arguments why this dataset would still be valuable for further use in models and experiments.

Generally, the impact of this study could be emphasized further and throughout the manuscript. Some more in-depth analysis would be nice regarding annual budgets of the site, and driving factors of GHG fluxes, for example, with correlation analyses or similar.

Dataset:

- I would recommend to use csv files rather than excel if the data is meant to be broadly used. 

- Were the measurements split up in different files because of varying temporal resolutions (I don’t see the need to separate them by figure)? If so, it might make sense to leave them in separate files. In that case, please use uniform column names, e.g. TIMESTAMP instead of Date, DateTime or Time and avoid several columns with the same name. Otherwise, it would also be nice to have all information in a single file, or at least have one file with flux measurements and accompanying WTD, etc.

- I would recommend to give latitude and longitude of the locations in each file. An indication whether the collar is soil or ditch might also be helpful as well as any other indicators that show differences among the collars (maybe elevation?).

- I don’t see the ebullition fluxes in the dataset. Please clarify how they are reflected in the CH4 column and ideally split up into diffusion and ebullition.

Specific comments:

Abstract: 

- Especially in the abstract and introduction, I suggest to clarify the directions of fluxes, e.g. “soil-atmosphere/ditch-atmosphere fluxes” and “emissions/source to the atmosphere”.

- note that the doi of the dataset should be given in the abstract for ESSD

- add numbers of average fluxes for CH4 and N2O as is done for CO2, and add standard deviations or similar

l. 26: replace “lead” with “led”    

l. 27: clarify what is meant by annual budget – N2O or GHG budget?

l. 30: remove “with expectations”

Introduction:

- since it is suggested to use this dataset for models, it might be worth to search the literature and include a paragraph about how/why this dataset is currently lacking and would be a valuable addition to the modelling realm

- the second paragraph only mentions a single measurement unit. It might be worth to mention a few others and make the advantages of the system used in this study a bit clearer.

- two paragraphs of the introduction focus on processing methods, although I don’t think that is part of the main points of this manuscript. Therefore, I would recommend to shift the focus a bit and make the impact of this manuscript a bit clearer.

- in the Methods you describe that the site went through a chain of disturbances/changes which likely affect GHG fluxes. Therefore, this should definitely be made clearer in the introduction as well.

l. 48: add “a”, i.e. allow for a standard number of…

l. 65: in Figure 3, the distance is 30 m, not 24 m – please revise.

Materials and Methods:

l. 73: add “in Denmark” and the latitude/longitude of the site

l. 79: replace “makes out” with “forms”

l. 86/Figure 1: The scale bar on the lower left is not visible.

l. 90/Figure 2: This figure could be shifted to the appendix or be removed.

l. 93/Figure 3: Lines and text not visible very well, please increase size and visibility, e.g. by adding white background to black text. “30 m” could be red for clarficiation.

l. 95-97: unclear what the JB numbers are without reference

l. 98: yet another transect length is given. Please stick to one throughout.

l. 99: specify analyser, e.g. “greenhouse gas analyser”?

l. 100-101: does the elevation refer to above sea level? Please specify. Remove repetition of “along the transect/across the transect”.

l. 102: replace “an N-S” with “a north-south”

l. 103: briefly mention what the SkyLine2D system is, add a reference or manufacturer

l. 104: clarify whether the the pallet tanks were simply used to stabilize the system

l. 109: replace “was” with “were” and remove repetition of “along the transect”

l. 110: replace “farmer’s field” with “agricultural field”

l. 118-119/Figure 4: The peat depth is not indicated in the figure, so I think the last sentence in the caption could be removed.

l. 120: I don’t find the section heading “Data variables” fitting here since the variables are not clearly presented, but it is rather described how they were measured as would be done in the Methods section of a classic research article.

l. 121: inconsistency with length of dataset – previously it was 12 months, now 13

l. 123: Please indicate whether there was any snow cover during the study period at some point in the manuscript.

l. 124: revise dates to include a comma between day and year and stick to the same date format throughout the manuscript (also in caption of Figure 12, for example)

l. 127/Table 1: The last column is missing a header – should it be “Data availability” or similar? The footnote 2 could be mistaken with exponent 2 – maybe consider choosing a different character such as asterisks instead.

l. 133-135: Worth mentioning here that these measurements were only conducted at specific collars.

l. 143: replace “collecting” with “measuring”

l. 154-160: While I don’t think section 2.5 is essential for the manuscript, it may be helpful for others in the research community. As a note, links should include the date of last access and abbreviations should be explained (such as SigFox).

l. 161: I think section 2.6 should come earlier in the manuscript since the SkyLine2D system has already been mentioned several times before without further explanation. Also, the distinction into subsections 2.6.1-2.6.3 does not seem overly helpful and they could be merged into one since they all describe the measurement setup. Note that at the beginning of a sentence, numbers should be spelled out. A little restructuring of section 2.6 might help to chronologically answer the questions: What was measured and why? How were things measured? I think some information is very detailed (e.g. some data processing steps in l. 219-226) and could be moved to the appendix to shorten this section a bit and focus on the most relevant information.

l. 169: replace “hit” with “sat on” – does this mean that if the water level was low, air could have entered through the holes?

l. 170-173: I think it would be worth to dedicate a subsection to summarize all the disturbances the site faced for clarification. Was the addition of Glyphosate done to reflect common agricultural practices? Or rather to get the true soil flux? Could this treatment have affected GHGs?

l. 185-189: I think this could be removed or are these variables relevant and given in the dataset?

l. 190/Figure 5: This is a nice figure – make sure all text and numbers are visible. I think it could be moved to the appendix since it shows details of the measurement setup.

l. 206: replace “hz” with “Hz”

l. 207: The precisions seem to be for 5-minute intervals? If so, please indicate.

l. 214: remove quotation marks

l. 215: sentence could be removed

l. 217: remove “the procedure outlined in”

l. 218: I think this sentence could be removed, or correct to “converted to micromole per mole” 

l. 228 and 233: Why “at time zero”? The slope would cover a range of timesteps.

l. 237: How were you able to detect mechanical malfunction?

l. 238: What do you mean by “non-significant”? Is this based on a p-value? Please indicate. If low fluxes were generally removed, does that mean that you overestimate fluxes?

l. 241-246: I am surprised that this simple approach to estimate annual budgets was chosen with this high-resolution dataset. Was there a reason why the daily values were not summed over the year instead of taking an average? At least a few different estimates using different simple methods to determine annual budgets could be presented. In my opinion, this point could be a strength of this manuscript and would make the data more comparable with other studies. 

l. 247/Figure 6: This figure should be moved to the appendix together with the following text in l. 253-261. As a modeler (which seems to be the main target group here), I might not be super interested in how exactly you processed the data, but want to see the clean data presented.

l. 263: Instead of “Ebullition, e.g. mass flow of CH4” I suggest “Methane ebullition flux”

l. 268 and 269: replace “enclosure-1” by “per enclosure” and clarify if you refer to a time or space component here – do you refer to 5 min? Please clarify.

l. 270: Equation 1 results in units nmol * 1e-6 * m-2, so I think 1e-6 should be removed?

l. 275: It is unclear how often ebullition was detected from the ditch, so the frequency remains unknown. Would it not be adequate to extrapolate ebullition fluxes throughout the day based on the measurements? Or is that what was done? Please clarify and elaborate.

l. 278-279: suggest to remove sentence

l. 279-284: I don’t understand this, please clarify. I’m also not sure whether upscaling is the right term here or if you refer to extrapolation? Does this mean that there were 2 actual out of 5 potentially measured ebullition events? And therefore, for 3 out of 5 measurements, the ebullition flux was zero? If so, those should be considered too. Were there any measurements where you were able to determine both diffusive and ebullition fluxes? Was the concentration burst only observed for CH4 or also CO2?

Figure 7: Again, I think this should be placed in the appendix.

Data presentation:

l. 300 and 312: I don’t think wind climate is a common term. Wind regime could be used for example.

l. 301: replace “max” with “maximum”

l. 301-303: A pattern is not super clear in Figure 8, so maybe best to remove this sentence? 

l. 307-308: Sentence does not seem very meaningful, so it could be removed.

l. 311/Figure 8: In panel A, how can the maximum speed be lower than the mean? Also, error bars for the mean should be inserted. In panel B, reconsider the legend of the color palette. Only blue colors are visible in the wind rose.

l. 323/Figures 9-12: Consider showing the times of GHG measurements with shaded areas spanning the y axis instead of lines on the x axis. Could the x axis ticks be improved to show each first of the month for example? Same comments apply to the following timeseries figures.

l. 327: Sentence is very vague. Seasonal variation in temperature is typical, not only in Denmark. One could either elaborate more on this, or remove the sentence.

l. 329-331: rephrase to “Monthly ranges of air temperatures (Tab. 2) show >20°C variation between minimum and maximum, except for February, pointing towards large diurnal variations.”

l. 333-335/Table 2: Usually, the mean alongside the standard deviation would be given or standard error, for example. Please add that.

l. 339/Figure 10: What is the message of this figure? The soil temperatures would be expected to be very similar along the transect, unless there are clear differences between the locations. It is a bit unclear whether any of the sensors could for example be below the groundwater level at any point. One could show one figure instead that shows the overall seasonal cycle of temperature for all collars combined. Also, the numbers of collars are not consistent with those given in Table 1 for soil temperature measurements, collars 1 and 18 are missing. Is there a reason for that? Add legends for the line colors in the plots. The different blue colors in panels A-E are difficult to distinguish, please choose others. 

l. 347-349: Is this information relevant for this study?

l. 356/Figure 11: If the overall water table depth for the site is to be presented, then the figure does not necessarily help much, since the elevation of each collar is different. Figure 4 does a better job. Maybe the authors could clarify the main message of this figure. Is it relevant or would it fit better in the appendix? Also, it would be worth to insert a horizontal line at depth 0. 

l. 394: Here and throughout the manuscript, mean fluxes should always be accompanied by an error estimate, such as standard deviation.

l. 396: I think there may be little spatial variation until the start of summer, but after that, most sites take up methane, while some emit. Can the moisture or water level be considered as drivers for methane at this site then?

l. 402: maybe microbes played a role here?

l. 404-406: is there any information available about nutrient content in soils?

l. 407/Figure 14: This figure is a very nice visualization of the study. Consider replacing Figure 4 with Figure 14 to avoid repetition.

l. 426-428 and 430-431: a bit awkwardly phrased sentences, consider to rephrase slightly for better understanding.

l.  436: This is the first time in this section that results were discussed and compared with those from other studies. I definitely miss a bit more discussion in this manuscript. Please add references and discussion for the other gases as well.

l. 439/Figure 16: Small text on right side of the figure to indicate months is barely visible. 

l. 443: Maybe better to state “we observed a clear diurnal cycle” or similar.

l. 444-446: Split up or rephrase sentence to avoid long chain of information.

l. 450/Figure 17: What is shown here? Are the fluxes averaged across collars and then summed? Is WTD also averaged across collars? If they are identical for subplots A-C, then there is no need to show it 3 times. Please revise and clarify in the caption.

l. 456: The relation could be shown explicitly in a correlation matrix or plot. In Figure 17, the relation is not clear.

l. 459 and following: Please make sure there is no repetition of this information. It might make sense to restructure or comprise section 3.6 a bit to avoid repetition.

l. 474/Figure 18: Is it possible to partition the diffusive and ebullition CH4 fluxes (considering your methodology) to see whether the higher CH4 fluxes result from ebullition? Please add horizontal lines at zero.

l. 480: Please be more precise about the frequency/occurrence of ebullition at the ditch. How often did it occur? What was the magnitude of the fluxes? And how does this compare to diffusion?

l. 502: Worth mentioning that ebullition fluxes are very sporadic and that there is no clear temporal pattern to be expected.

l. 511-512: The figure reference “(Fig. 19D)” should probably follow after “zero”, and reference to Figure 18C could be added at the end of the sentence.

l. 514/Figure 20: Please add horizontal line for zero or add shaded area or similar. 

l. 519: Is the proportionality based on visual inspection of Figure 20?

l. 546-547: I think a reference is needed here when referring to NO3- measurements which are not presented in this study.

l. 554-555: Might be worth to elaborate on this.

l. 559/Table 3: Footnote about GWP can be removed since the info is given in the table caption. Why is the 20-year GWP given only for the ditch? What are the numbers in parenthesis for the ditch GWP for CO2 and N2O? What are the numbers in squared brackets? It could be worth to add further estimates based on different approaches here, as indicated in earlier comments. Consider using <1 or similar for peat soil CH4 GWP since it is not equal to 0. Could the fluxes also be given as area-weighted (in addition to per-m2) fluxes if the area of peat soil and the ditch is known?

Conclusion:

Please list limitations of the study and answer the questions: Would the budgets in a different year likely be the same? What effects does the disturbance history of the site have on the measured parameters? I. e. is the data representative in time and among temperate fens?

Supplement:

It is unclear which plot belongs to which collar. Please indicate. Also, why was collar 10/the ditch excluded?

Review of

A full year of continuous net soil and ditch CO2, CH4, N2O fluxes, soil hydrology and meteorology for a drained fen in Denmark

Annelie Skov Nielsen, Klaus Steenberg Larsen, Poul Erik Lærke, Andres Felipe Rodriguez, Johannes W. M. Pullens, Rasmus Jes Petersen, and Jesper Riis Christiansen

This data paper is a useful contribution to the study of soil greenhouse gas fluxes in peatlands, because it presents data from a novel system of automatic chamber greenhouse gas measurements covering a transect with a large number of collars, a relatively high data frequency and a full year coverage. However, I have two serious objections to this paper that should be addressed properly before final publication. Therefore I recommend publication, but with major revisions. My main objections are:

1. A lack of ancillary soil and vegetation data. There is practically no data on soil and vegetation included, except for a short mentioning of peat soil. Neither it is clear which of the cited references gives adequate information on soil conditions of the transect. If these data are to be be used by other researchers on ecosystem greenhouse gas fluxes, one would at least expect a basic description of a soil profiles at the site, or a borehole transect, and some basic soil and water chemistry data.

2. The measurement procedure, that entails removal of vegetation. The procedure of removal of vegetation has been common in the past but is increasingly abolished because of the intense intertwining of vegetation, microbial community and soil processes that generate greenhouse gas fluxes. Removal of vegetation (including the application of herbicide in this case) is a large disturbance of this system, with questionable results. It introduces artefacts that are poorly quantified for CO₂ fluxes since labile carbon pools in the soil are affected.

In the case of CH₄ fluxes, the main supply of labile carbon for methanogens is reduced, and the main transport pathway of CH₄ from soil to atmosphere (by plant aerenchyma) is destroyed. Therefore it likely leads to much lower fluxes of CH₄ compared to those in an undisturbed system, resulting in data that cannot be compared to those of other sites – if not simply flawed. For details, see the comments below.

The authors should state clearly in the abstract that vegetation removal has been applied. Furthermore, they should discuss properly what effects this may have had on the fluxes that they have measured.

Even if this is a data paper only, reflection on the complexity of the system that you have measured, and on the effects of your measurements on that system, is necessary.

Minor comments concern mostly the quality of figures and their captions, and questions on the operation of the automatic chamber system.

Detailed comments on the paper.

Section 2.1 Site description: This is disappointingly incomplete. Not any information is given on the soil profile and it lateral variation along the transect, while this could have been checked with a few hand augerings. What is the peat stratigraphy, are there any sand or clay layers in between or on top of the peat? What is the peat type, its decomposition grade, loss on ignition? Any information about soil water chemistry, for instance the presence of anaerobic electron acceptors that influence the redox potential and methanogenesis? What is the variation of the vegetation along the transect? Juncus effussus and most grasses differ strongly in the characteristics of their root system and methane transport characteristics. All this is information that any user of your data would want to know.

Line 94 – 101, caption Fig. 3: What are the instruments in the lower right corner of the figure?

Figure 4: The figure is not very informative (except on the surface topography and placement of the collars) and the caption is confusing. The vertical profile has two colours, brown and dark grey, which suggests some sort of stratigraphy. However, the brown colour is marked as ‘transect surface’, but apparently it indicates the soil above the minimum water table depth. The lower depth of the peat is not indicated. Information on the peat properties and its variability (e.g. the presence of clay/sand layers) is lacking. This would be very useful information for users of the data.

Line 170 – 173:

This procedure of killing vegetation by harvesting, and application of a herbicide, attempts to reduce the effects of vegetation respiration and to measure the ‘true’ or ‘net’ soil GHG flux. However, it introduces other artefacts that are poorly quantified, in particular for the CH₄ fluxes. For measuring of CO₂ fluxes from the soil it often has been done with the purpose of reducing CO₂ respiration/uptake by plants. Because of the artefacts it introduces, alternative approaches have been developed that leave vegetation intact and separate soil and vegetation components of the flux by modelling (e.g. Boonman et al., 2024). For the CH₄ fluxes it may have resulted in serious underestimation of the fluxes.

The statement that the fluxes after removal of the vegetation represent the ‘net’ soil greenhouse gas flux is invalid without specification what is actually meant by ‘net flux’, in particular when it is not explained which soil carbon pools are assumed to contribute to to this net flux. It may at best approach the soil CO₂ flux (with an unknown error or bias) and likely severely underestimates the CH₄ flux. In general, CO₂ from the decomposition of recently produced labile carbon, and that from older soil carbon (e.g. the peat carbon pool) is difficult to separate in surface flux measurements. Vegetation removal does a poor job in that, because most the root mass often remains behind, will be active, and also affects the microbial population.

Besides these caveats, I also wonder if vegetation removal is a specific requirement of this automatic chamber system. Does vegetation hamper a leak-free placement of the chamber on the collars with this system?

A motivation why this procedure has been applied, and a discussion of the caveats listed below is necessary. I suggest to do this in a separate Discussion section. Also, the vegetation removal procedure itself should be mentioned clearly in the abstract, for potential users to judge wether the data are suitable for use.

Drawbacks of vegetation removal:

1. The soil greenhouse gas flux in an undisturbed ecosystem is the sum of all peat and other organic matter decomposition. The ‘other’ being various forms of recently produced, usually labile carbon, produced by the vegetation root system and litter decomposition. Removal or decrease of one carbon pool may strongly affect the measured fluxes, in particular when it is not known quantitatively what has been removed. Furthermore, labile carbon interacts also with stabile carbon decomposition via the priming effect. This may enhance stable carbon decomposition (e.g. peat decomposition) in the presence of labile carbon. Therefore, it should be specified which carbon pools are considered to be included in the flux measurements (peat, older humic matter, recently produced organic matter, labile or stable?), and what effects the measurement procedure has on CO₂ emission from these pools. If actual data collection, e.g. root mass, is not available, the authors could at least consult literature from other sites on that.

2. Glyfosate is known to affect soil faunal and soil microbial respiration (e.g. Nguyen et al., 2016). The application of this herbicide will have influenced the measured fluxes to an unknown extent.

3. As the need for very frequent removal of living vegetation during the experiment testifies, the root system in the soil remained active, producing labile carbon and adding a vegetation and labile carbon respiration component to the fluxes. Therefore, vegetation removal still does not remove vegetation effects.

4. Since detection of CH₄ emissions is included, you are removing one of the main transport mechanisms of CH₄ from soil to atmosphere: the transport via plant aerenchyma (e.g. Vroom et al., 2022). Moreover, the main source of carbon for methanogens is labile carbon compounds produced by plant roots. The low CH₄ emissions therefore may be flawed and not represent normal ecosystem or soil CH₄ fluxes. On peat soils with approximately similar water table variation and vegetation, significant positive CH₄ fluxes were measured with manual and automated chambers (Hendriks et al., 2007; Lippmann et al., 2023).

Furthermore, you say that you removed vegetation with a minimum of 7 days. What was the (probably higher) vegetation removal frequency in the spring and summer period? This is highly important given the rapid vegetation regrowth in that part of the year.

Line 179: How does wind speed affect the operation of the system? How reliable is it at higher wind speeds?

Line 180: How certain can you be that rapid vegetation growth near the collar does not affect the airtight connection of chamber and collar? For instance, leaks may result from high grass getting between the chamber and the gasket during windy conditions.

Line 182: If a fan was not installed in the chamber, what is the air flow provided by the main pump, and is it sufficient to flush the chamber?

Figure 5: Can the upper photos be made sharper or larger, providing more detail on the chamber construction? Eventually, provide them in a supplement.

Line 232: Check the sentence starting with “If the relative SE…”, the part “than 100%” appears to be misplaced.

Line 238: During the measurement time the temperature in the transparent chamber can rise in a matter of a minute in sunny weather. Is there no temperature sensor inside the chamber to detect this effect and correct for it?

Caption Fig. 7. Good point, but how sensitive is the system to bubble fluxes induced by the chamber lowering? Was the collar anchored somehow in the subsoil of the ditch to prevent disturbance?

Line 383: variability in soil water content. Again, it is disappointing that so few soil data is included. Could there be differences in water seepage from higher ground (which is to be expected given the topography) or does soil cracking in dry periods occur, influencing the SWC?

Line 398 – 402. Again, the large spatial variability should be no surprise. Unfortunately, any information on soil variability is missing. For instance, I would have expected information on the soil carbon content, which is an important predicting variable in CO₂ fluxes from soils. Although the above-ground vegetation is removed, there is still root mass present that produces labile carbon; root density also adds to the spatial variability. This kind of data would be very useful for other users of the data.

Line 424. Interesting to see these bursts. As mentioned above, this could also be an artefact of your methodology. It excludes plant emissions, which is usually a major CH₄ emission pathway (Vroom et al., 2002). By artificially removing the plant flux, a buildup of CH₄ concentration in the soil could induce a burst-like emission pattern.

Figure 16 and Figure 19. This figure is difficult to understand, information in the caption is ambiguous.

You have only 5 measurement points per day, but there are more observation points. The caption suggests that the points are based on a grouping of all soil collars together. Is this over one day, if so, which days? Or over an entire month, as the reference to the figure legend suggests? In that case I would have expected way more data points in the figure, unless it is a monthly average per collar. In short, be clear how your data have been grouped. This is also important for understanding sources of variation in the data. Grouping of all collars in one day introduces also spatial variation, next to temporal variation.

Next, the colour scale of the legend is not very distinctive by choosing only shades of blue and red. Better include other colours as well, which makes the data from different months more distinctive.

Line 443-444. The lack of diurnal variation for CH₄ may also have been caused by removing the vegetation. Plant fluxes of CH₄ tend to have diurnal variation, driven by solar radiation (Vroom et al., 2022).

Line 540. ‘it cannot be ruled out that living roots inhabited the soil below the chambers’. You can be quite sure about that if you have to clip the vegetation frequently!

Line 547-550. There could be other electron acceptors inhibiting methanogenesis, for instance Fe³⁺, sulfate. Here again, some information on basic soil and water chemistry could have been helpful for users of the data.

Table 3. Mention the source of the GWP factors used here.

Section 5 Conclusions: The causes for spatial variability of the GHG fluxes is unresolved – but that is not surprising given that any information on soil variability is lacking. Fig. 15 suggests that the spatial variability is larger than the temporal variability on these closely spaced collars, which would be an interesting conclusion.

Line 578-580: The low CH₄ emission is attributed to low water table and a cold wet winter. However, the huge elephant in the room here is the potential effect of vegetation removal on the CH₄ fluxes detailed above. At other peat sites with similar water table and vegetation that I have measured myself, persistent positive summer CH₄ fluxes occurred (Hendriks et al., 2007; Lippmann et al., 2023). Neither, alternative explanations for the low emissions are considered, such as the presence of other anaerobic electron acceptors (e.g. sulfate reduction) that maintain a too high redox potential for methanogenesis? This is mentioned elsewhere in the article for NO₃⁻, but not considered here.

Supplement.

Missing: collar numbers at each graph. What do the ticks on the horizontal axis represent? First day of each month, midpoint? Day numbers would be more informative on the horizontal axis!

Data.

The data representation is largely correct. However, for greenhouse gas fluxes it would be useful include the standard error of the flux calculation method that is applied. This would allow data users to apply additional quality checks.

References.

Boonman, J., et al. (2024):Transparent automated CO2 flux chambers reveal spatial and temporal patterns of net carbon fluxes from managed peatlands. Ecological Indicators, 164, 112121.

Hendriks et al., (2007): The full greenhouse gas balance of an abandoned peat meadow. Biogeosciences, 4(3), 411-424

Lippmann et al. (2023): Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH₄, and CO₂ emissions. Geoscientific Model Development, 16(22), 6773-6804.

Nguyen et al. (2016): Impact of glyphosate on soil microbial biomass and respiration: a meta-analysis. Soil Biology and Biochemistry, 92, 50-57.).

Vroom et al., (2022): Physiological processes affecting methane transport by wetland vegetation, Aquatic Botany 182:103547