Comment on bg-2021-353

Factors that affect and/or govern methane emission from wetlands are of great interest because better understanding of the influential factors would enhance the predictability of methane emission from wetlands when subjected to environmental changes. This paper aims to assess the functional potential impact of CH4 producing and consuming microbes on the magnitude of CH4 flux. The authors concluded that the functional potential [of the methane cycling community] plays a minor role in explaining the observed differences in methane flux categories (HFM, MFM, LFM).

The authors thank the reviewer for their comments. We have addressed the major issues in individual sections rather than writing a lengthy text at the bottom. Please find our responses below. In addition, each specific comment has been addressed individually.

Major issues:
The key weakness of this paper is the use of genetic information of the methane cycling community alone in an attempt to address the scientific question the author set out Authors response: We agree that the CH4 cycle is not simple and does not operate individual of other processes. However, to reduce the complexity of this system, we kept temperature and light levels the same among treatments while the water table was kept stable throughout the experiment (section 2.2). This minimizes the influence of these drivers on spatial variability, which should enhance differences arising from CH4 cycling functional genes and taxonomy. We believe that using our targeted approach is a strength, rather than a weakness as we can observe many functional genes used across multiple metabolic pathways, which cannot be achieved when using 16s studies. In addition, we were able to make conclusions not observed in more complex whole metagenomic studies.
Firstly, the text does not provide clearly the reasoning of why the authors hypothesized that the differences in the measured methane flux (categories) could be explained by shifts in the composition of the methane cycling taxa in the 9 mesocosms. It would be to lay out the logic.
can be observed in figure 1 and was the reason for establishing three flux categories (LFM, MFM and HFM), and the basis for the paper. The mention of gene expression on line 587 is merely a suggestion for future research used in our conclusion.
Secondly, only abundance data of these methane cycling taxa relative to each other (i.e. the methane cycling community) was stated (or available). It is uncertain to this reviewer that how the PCR steps in the "captured metagenomics" analysis might have altered such relative abundance. And the use of "captured metagenomics" has, to the disadvantage of the study, prevented one from knowing the abundance of the methane cycling community relative to the total microbial community, as such relative abundance would be helpful to hint the proportion of the whole methane cycling community. These may explain why this study does not find significant correlation between the so-called "functional gene abundance" with the observed CH4 flux categories, when compared to Zhang et al. (2019, cited in this manuscript) that showed a positive correlation of gene abundance (absolute mcrA gene copy number) and methane flux. The use of relative abundance to the specific functional group is less robust when compared to absolute gene copy numbers. Additionally, it was not obvious that the calculation of the "abundance data" was explained in details or with clarity. It will be helpful for the reads to understand how the sequencing data was process to obtain the abundance. Some of the above mentioned points could be addressed by writing, but sadly, this weakness is a fundamental flaw that transcends through this manuscript, and affects the robustness of the analysis and interpretation Authors response: The research has been conducted using the captured metagenomics approach. We used this approach as we wanted to narrow our research question and try not to overcomplicate our conclusions by including a broader whole metagenomic approach. As this approach uses custom designed probes to target sequences of interest, any off-target sequences (i.e. non methanogen/methanotroph) within our dataset must be ignored and we cannot trust those values to be correct. Therefore, we chose to exclude any other taxa other than methanogens and methanotrophs. During the PCR step, 7 cycles were used for libraries with a genomic DNA input of 150 ng, and 5 cycles where the input was 1 μg to minimise any risk of PCR biases (section 2.5.3). In addition, we did not see any correlation between the samples with low amount of DNA versus those with high. We use the term relative abundance throughout this paper as we cannot call it absolute abundance since that is not what we are measuring; Rather, when using next generation sequencing, we always get relative abundances. Authors response: We used a double root transformation on abundance of taxa and functional genes as a form of normalization. We clarified this in the text as follows: Original: Input data for the PERMANOVA was double root transformed to reduce the influence of highly abundant taxa and genes.
Authors revision: Taxonomic and gene abundances data for the PERMANOVA was double root transformed to reduce the influence of highly abundant taxa and genes.
L45 Missing "the" before "second most important", and please delete "has" in "has in the atmosphere" Authors response: This change has been made according to the reviewer's suggestion L89 Is mmoX a commonly targeted gene in CH4 research? mmoX gene codes for the soluble methane monooxygenase, which is known to use substrates other than CH4. Did the authors mean to say mmoX or particular methane monooxygenase (pmoA)?
Authors response: As stated in the text mmoX is often targeted in similar experiments, however as we particularly focus upon pmoA in this manuscript and believe the swap to pmoA to be more appropriate. This change has been made according to the reviewer's suggestion Original: In CH4 research, key genes such as methyl coenzyme M reductase (mcrA) and methane monooxygenase component A alpha chain (mmoX) are often targeted to determine community composition and functional potential Authors revision: In CH4 research, key genes such as methyl coenzyme M reductase (mcrA) and particulate methane monooxygenase subunit A (pmoA) are often targeted to determine community composition and functional potential L98 "are detected" should be "to be detected" Authors response: This change has been made according to the reviewer's suggestion L100 (there may be a better place to mention the following) mcrA gene is for detecting both methanogenic and methanotrophic archaea. Anaerobic methanotrophs (ANMEs) have been detected, albeit at very low abundance, in wetlands and permafrost-affected areas. Nonetheless, ANMEs have not been mentioned in this manuscript. In this study, Methanosarcinales were found among the methanogens, and Methanosarcinales contains ANMEs. Authors are suggested to investigate further whether ANMEs have contributed to the taxonomic and functional diversity in their data.
Authors response: we have added a shot passage of text within the discussion to reflect this. Members of the order Methanosarcinales were included in the calculation of diversity indexes, therefore this will not alter the diversity results.
Original L428: However, the presence of the genera acetoclastic Methanosaeta and Methanosarcina, which possess a more diverse genome allowing them to perform hydrogenotrophic, acetoclastic and methylotrophic methanogenesis, suggests that the community holds a metabolic potential to produce CH4 under altered environmental conditions. Authors revisions: However, the presence of the acetoclastic genera Methanosaeta and Methanosarcina, which possess a more diverse genome allowing them to perform hydrogenotrophic, acetoclastic and methylotrophic methanogenesis, suggests that the community holds a metabolic potential to produce CH4 under altered environmental conditions. Furthermore, members of order Methanosarcinales were also detected that hold the functional potential to perform anaerobic oxidation of CH4 and is carried out by anaerobic methaneoxidizing archaea, further increasing the functional potential of the methanogenic community.
L114-115 Please clarify whether the "beta-diversity" here refers to both of the CH4 producing and consuming microorganisms. And please explain why such increases is thought to increase with increasing CH4 emission.
For clarification, we have rewritten this sentence: Original: (2) determine whether the -diversity increases with increasing CH4 emission Authors revision: (2) determine whether the combined CH4 producing and consuming community -diversity increases with higher CH4 flux L142 Is the n=6 per mesocosm?
We have rewritten this sentence to clarify this: Original: During the experiment, weekly to bi-weekly (final 3 weeks, n = 6) measurements of CO2 and CH4 fluxes were conducted.
Authors revision: During the final three weeks of the experiment, bi-weekly measurements of CO2 and CH4 fluxes were conducted (n = 6 per mesocosm). L166 This reviewer was not able to comprehend the phrase "based of comparison with isotopic mass spectrometer". Please rewrite to clarify.
We understand that this phrase may be confusing. We have adjusted this section as follows: Original: The CH4 emission and its δ13C signature were determined using a cavity ring-down laser absorption spectrometer (CRDLAS) with the closed chamber technique described above (G2201i, Picarro, Santa Clara, USA). The surface of each peat mesocosm was covered with a transparent cylindrical chamber for 25-30 minutes while the CH4 mixing ratio and δ13C-CH4 was recorded with 1 second intervals. Data was averaged into one minute averages. CH4 emission were calculated using linear fitting, and the δ13C signature of emitted CH4 was determined with a Keeling plot intercept approach (Keeling, 1958;Thom et al., 1993). The resulting δ13C-CH4 values were corrected by adding a constant value of 3.4 ‰, based of comparison with isotopic mass spectrometer.
Authors revision: The CH4 emission and its δ13C signature were determined using a cavity ringdown laser absorption spectrometer (CRDLAS) with the closed chamber technique described above (G2201i, Picarro, Santa Clara, USA). The surface of each peat mesocosm was covered with a transparent cylindrical chamber for 25-30 minutes while the CH4 mixing ratio and δ13C-CH4 was recorded with 1 second intervals. Data was averaged over one minute and the δ13C signature of emitted CH4 was determined with a Keeling plot intercept approach (Keeling, 1958;Thom et al., 1993). We compared values from the CRDLAS instrument with an isotope ratio mass spectrometer (IRMS) by taking air samples from the flux chamber during measurements from the CDRLAS and analyzing these with the IRMS (Rinne et al., 2022). The values from the IRMS indicated a bias of -3.4 ‰ on the CRDLAS, thus we have corrected the values of the δ13C signature by adding 3.4 ‰.

L179-180 Please provide the access date and/or the version of KEGG database used in this study.
We have changed the text accordingly: Original: Genes encoding enzymes closely related to the CH4 production and oxidation in pathway map00680 were identified from the Kyoto Encyclopedia of Genes and Genomes (KEGG).
Authors revision: Genes encoding enzymes closely related to the CH4 production and oxidation in pathway map00680 were identified from the Kyoto Encyclopedia of Genes and Genomes (KEGG), database version 88.

L189-190 What is "low TE"? Please explain.
We have rewritten this sentence to better explain this: Original: Depending on the extracted DNA concentration, 150 ng or 1 μg of genomic DNA in a total volume of 100 μl low TE Authors revision: Depending on the extracted DNA concentration, 150 ng or 1 μg of genomic DNA in a total volume of 100 μl low Tris-Ethylenediaminetetraacetic acid buffer (TE buffer).

Section 2.7 It is not clearly stated that what data is being used to calculate the Bray-Curtis dissimilarity and the various statistical tests. This makes it a bit difficult to interpret the results.
We have rewritten this sentence to clarify the data used for these tests:

Original: Further statistical tests for use on genomic data, including the Permutational multivariate analysis of variance (PERMANOVA), α-diversity and β-diversity, and Nonmetric Multidimensional Scaling (NMDS)
Authors revision: absolute abundances for taxonomic and functional sequences from the KEGG ko:00680 metabolism pathway were used as input for the statistical tests including the Permutational multivariate analysis of variance (PERMANOVA), α-diversity and β-diversity, and Nonmetric Multidimensional Scaling (NMDS).

L252 Should it be "between" CH4 fluxes, instead of "within"?
Changed to "among" Original: After observing such large variability within CH4 fluxes Authors revision: After observing such large variability among CH4 fluxes L271 What does "the flux of CH4 held a positive relationship to Reco" actually mean?
We mean "correlated positively" and have changed the text to clarify this:

L272-273 Authors explained that GPP is calculated from NEE and Reco (GPP = NEE -Reco). What was the reason for the authors to examine such correlation relationship stated in L272-273?
We examined this due to the influence of GPP and Reco on available substrate. We have changed the text to make this point more clearly: Original: In an attempt to investigate the relationships between carbon fluxes we conducted a correlation test and found that the flux of CH4 held a positive relationship to Reco (R2 = 0.60, p ≤ 0.04), but not to GPP or NEE (fig 2). When analysing CO2 fluxes, GPP held a strong negative relationship to Reco (R2 = 0.70,p ≤ 0.002), while NEE held a strong positive relationship to GPP (R2 = 0.82, p ≤ 0.001) (fig 2). (Ström et al., 2005). In an attempt to investigate whether the relationships between carbon fluxes matched previous research, we conducted a correlation test and found that the flux of CH4 held a positive relationship to Reco (R2 = 0.60, p ≤ 0.04), but not to GPP or NEE (fig 2). When analysing CO2 fluxes, GPP held a strong negative relationship to Reco (R2 = 0.70,p ≤ 0.002), while NEE held a strong positive relationship to GPP (R2 = 0.82,p ≤ 0.001) (fig 2). L280 Please add "statistically" before "significant".

Authors revision: Previous research has shown that CH4 flux holds a strong correlation to both GPP and Reco, which can influence the availability of CH4 substrates
Authors response: This change has been made according to the reviewer's suggestion L288-289 Is it possible that the less negative value was contributed to higher CH4 oxidation rate in M2 and M4?
Authors response: This is of course possible, as the d13C of the emitted methane reflects both processes involved in methanogenesis and methanotrophy. However, combining the d13C value with the fact that this mesocosm had high methane emission makes it likely that the variation is caused by the methanogenesis, not methanotrophy (e.g. Hornibrook 2009;Rinne et al., 2022). We will include a paragraph on the interpretation of d13C in relation to methane emission in discussion section (see next response).
Original: L564-566: Furthermore, the positive correlation between δ13C-CH4 to CH4 emission rate indicates the CH4 emission to be mostly controlled by the trophic status for methanogenesis, rather than methanotrophy (Hornibrook, 2009).
Authors revision: Furthermore, the positive correlation between δ13C-CH4 to high CH4 emission rates, especially observed in HFM, indicates that the CH4 emission is mostly controlled by the trophic status for methanogenesis, rather than methanotrophy (Hornibrook, 2009).

L290-291 It is not intuitive as to why a relationship between CH4 flux and the Keeling intercept is investigated, and thus, what it meant if there is a significant relationship. To help readers to follow, please explain. Explain the keeling method more clearly, why we use keeling to investigate ch4 fluxes
We have revised the text to explain this further: Original: Distinct isotopic signatures of individual mesocosms are shown in fig 3. All mesocosms fell within the range of hydrogenotrophic methanogenesis (δ13C = −110‰ to −60‰) (Chanton, 2005;Whiticar, 1999). However, M2 (MFM) and M4 (HFM) indicated a slight tendency towards acetoclastic methanogenesis with less negative isotopic signature (δ13C = -60‰ to -50‰), both yielding mid -60‰ δ13C Keeling intercepts. A significant positive correlation (R2 = 0.5, p ≤ 0.001) and significant relationship also existed between CH4 flux and the Keeling intercept shown in fig 3. Authors revision: Distinct isotopic signatures of individual mesocosms are shown in fig 3. The relationship between d13C and CH4 fluxes can be indicative of the processes controlling the spatial variability of the CH4 emissions (Hornibrook 2009;Rinne et al., 2022). A positive correlation between d13C and CH4 fluxes indicates that the variation is due to the substrate availability for methanogenesis, while a negative correlation is indicative for methanotrophy to be the dominant cause for the variability of CH4 flux. All mesocosms fell within the range of hydrogenotrophic methanogenesis (δ13C = −110‰ to −60‰) (Chanton, 2005;Whiticar, 1999) and held a significant positive correlation (R2 = 0.5, p ≤ 0.001), indicating the dominant methanogenesis pathway to be hydrogenotrophic. However, M2 (MFM) and M4 (HFM) indicated a slight tendency towards acetoclastic methanogenesis with less negative isotopic signatures (δ13C = -60‰ to -50‰), both yielding mid -60‰ δ13C Keeling intercepts.  Figure 3 shows the individual measurements of methane emissions. At one time, the emission from LFM and MFM mesocosms was high, leading to the data point mentioned moving away from the other data points. As this study is focused on a replicated peak growing season, and not a temporal scale, we prefer not to remove the data point just because it is an outlier.

L298-299 What unit is it? phyla OR OTU OR genera as in L307? (Add and genus level)
We have changed this sentence to clarify this: Original: In total, 20 methanogenic Archaea and 5 methanotrophic Bacteria were detected.
Authors response: In total, 20 genera of methanogenic Archaea and 5 methanotrophic Bacteria were detected.
L308 It would be clearer to say "methanogenic community" (provided that ANMEs are not detected), instead of "proportion. We understand that this sentence may be misinterpreted, which is why we have rewritten it as follows: Original: we can expect CH4 production and consumption to still occur, but possibly using alternative metabolic pathways than currently observed Authors revision: our results indicate that we can expect CH4 production and consumption to still occur, as the community holds the functional potential to continue producing or reducing CH4, possibly using alternative metabolic pathways such as acetoclastic or methylotrophic methanogenesis.

L441-442
Please provide information about "the absence of acetogenesis and fermentation"...then it would be helpful for readers to relate the following statement "the less dominant functional...." at their study site.

Information added.
Original: In the absence of acetogenesis and fermentation, the less dominant functional groups (i.e. acetoclastic and methylotrophic methanogens) may still remain dormant, due to the absence of necessary substrates to metabolize.
Authors revision: In the absence of acetogenesis and fermentation, that produce the necessary products for acetoclastic and methylotrophic methanogenesis, the less dominant acetoclastic and methylotrophic methanogens may still remain dormant due to the absence of necessary substrates to metabolize.
L445 The "spatial" info of the highly variable CH4 flux is not given, and it would be good for readers to know the spatial variability represented by M1-M9.