This study utilizes lipid biomarker signatures from surface sediment samples to obtain a time-integrated signal of methane release events in the Laptev Sea. The results suggest that methane oxidation occurs across the Laptev Sea shelf, including the mid-shelf region that was previously known as a region of low methane emissions. This study is relevant for the community, and for better understanding methane cycling in the Arctic. Overall, it is very well-written and very thorough. I have several minor comments and suggestions regarding the manuscript.

Comments:

Lines 23-24, 76, and 81: The authors interpret the d13C values of the hopanoids as a proxy for “methane release”. In principle, yes, there does appear to be a correlation between methane concentrations and d13C values, however, this has not been thoroughly tested in diverse environmental settings and with different methanotroph communities. It would be more accurate to say that this proxy reflects aerobic methane oxidation, and therefore enhanced methane cycling. I would recommend rephrasing this in both the abstract and the manuscript by replacing “methane release” with “enhanced methane cycling” or “methane oxidation”.

Lines 86-87: Based on previous studies, does methane-oxidation predominantly occur in the sediment or the water column? Or does this vary based on the site?

Lines 268-275: Based on these measurements the methane concentrations are highly variable between sites as you mentioned. Is most of the methane being emitted from the Laptev Sea from a diffusive or ebullitive flux? Previous studies have shown that aerobic methanotrophs are usually less efficient with oxidizing methane when the methane flux is mostly ebullitive. If the flux is mostly ebullitive rather than diffusive, do you expect this to influence the proxy signatures and your interpretations? Coming back to my previous comment, is the water fully oxygenated at all these sites? If so, do you expect most of the methane-oxidation to occur in the water column and sediment, and how would this influence the proxy signatures you obtain?

Lines 335-336: Not all members of the family Methyloligellaceae are considered methanotrophs. The majority of the classified strains appear to be methylotrophs, including Methyloligella and certain strains of Methyloceanibacter. You can still mention these as potential candidates for Type II methanotrophs, but you should add a sentence somewhere indicating that these are not all necessarily methanotrophs. Further, do you know whether Methyloligella and Methyloceanibacter have the capacity to produce hopanoids? It would be good to confirm this as this can influence some of your interpretations. You can check this by searching for the sqhc gene (accession no. WP_038942977.1) on the NCBI database, and then checking to see if either of these species contain the gene (see Richter et al. 2023 Biogeosciences for more details).

Lines 344-354: The title of this subsection and the content seem unrelated. This section also sounds like it belongs more in the conclusions rather than at the start of the discussion.

Line 381-383: Are there hydrothermal vents in the ILS region?

Lines 382-383: The reference that you site here (Takeuchi et al. 2014) says the strain of Methyloceanibacter is a methylotroph and not a methanotroph. Going back to my previous comment, maybe check to see if they produce hopanoids.

Lines 383-387: Since it is unclear whether some of the MOB you have classified as Type II MOB are methanotrophs, I would say it is difficult to fully exclude terrestrial inputs in the ILS region. Do you have any other independent biomarkers that can give an indication of how much of your signal here is derived from terrestrial sources? In your next paragraph, you seem to indicate that terrestrial inputs are relatively high, so you might still have a terrestrial signal from your methanotrophs.

Line 392: Check your reference for the “10% bacteria”. Belin et al (2018) was not the first paper to report this, this was already shown in previous studies.

Line 401: Could the high methane concentrations in the ILS region also be derived from the Lena River rather than in situ production in the ILS, or a combination of both? Based on your figure 3, it seems like the methane in this region should be very depleted. Could this tell us a bit more about the source of the methane in this region?

Line 417: change to “here we show”

Line 429: Change “Our display” to “Our biomarkers”

Comments on figures:

Figure 1: The numbers for the stations are hard to read in the figure and against the subsea permafrost shading. Consider making the numbers black to make them easier to read. It would also be helpful if you could indicate the outer, mid-, and inner Laptev Sea regions in this figure.

Figure 3: In the caption you say the shaded “gray zone” but in the figure it looks “green” to me. Consider changing this. All of these figures are showing the same things but the varying scales are a bit confusing. Consider making this into one large figure that contains all of the same information to make it easier to read. 

Figures 4 & 5: It would be helpful if you could indicate the ILS, MLS, and OLS regions on these figures. It would make the figures easier to interpret and to know which station numbers and data points belong to which region.

1. Summary of manuscript

Elevated methane concentrations in seawater have been widely reported in the Eastern Siberian Arctic seas underlying subsea permafrost. These methane concentrations show strong spatial and temporal variability.

In this study, the authors combine hopanoid-specific carbon isotope measurements (δ13C- C30) with 16S rRNA gene analyses of surface sediments to trace aerobic methane oxidation (AeMO) as a proxy for methane release in the Laptev Sea. Depleted δ13C- C30 values, ranging from −57 to −37‰, are interpreted as diagnostic of AeMO. The results suggest that methane release is most intense in the outer shelf region (OLS), consistent with previously reported seawater methane concentrations. Notably, depleted δ13C- C30 values were also observed in the mid-shelf region (MLS), an area traditionally considered to exhibit low methane emissions, alongside methane concentrations that have not been reported previously. In contrast, high methane concentrations were measured near the Lena River delta in the inner shelf region (ILS), yet hopanoids there display comparatively heavier δ13C- C30 values, indicating that different processes may be influencing the isotopic signal. The authors acknowledge the additional complexity this introduces for interpretation but argue that δ13C- C30 values remain lower than bulk organic carbon δ13C, supporting the presence of AeMO.

Main findings:

1. The mid-shelf region (MLS) exhibits higher methane concentrations than previously reported for this area.
2. The outer shelf region (OLS) is characterised by elevated methane concentrations and the most depleted δ13C- C30 values, consistent with intense aerobic methane oxidation.
3. The inner shelf region (ILS) shows high methane concentrations, but comparatively heavier δ13C- C30 values than the other regions, suggesting that additional processes influence the isotopic signal in this area.

This study presents interesting results on methane cycling in the Laptev Sea across the outer, mid-, and inner-shelf regions with very interesting trends and variations. The manuscript is generally well written and structured and the results show interesting findings. I have a small number of minor to major comments which, once addressed, it can help strengthen the interpretation.

1. Major comments

• Hopanoids are not unique to methanotrophic bacteria. Although this study includes measurements of bulk δ13C-OC and presents a stable carbon isotope mixing model with defined end members, the interpretation would be strengthened by more explicitly contextualising the δ13C- C30 values within the existing AeOM literature. In particular, it would be helpful to include reported δ13C- C30 ranges from other methane seep studies where hopanoids have been used as proxies for methane release. This information could be included in both the Introduction and then in the discussion, comparing results with existing literature values. In addition, providing δ13C- C30 ranges from related environments, such as peatlands and lacustrine systems which are mentioned in the Introduction, would offer useful broader context. By providing this broader context it will make it easier to assess the AeOM results and improve the clarity and interpretability of the results throughout the manuscript.
• In relation, the introduction would benefit from more clearly outlining previous studies that have applied the δ13C- C30 proxy to infer methane release, including a brief summary of their main findings. At present, it is not entirely clear whether this proxy is well established or in early stages, only one study is mentioned (van Winden et al., 2020. This ambiguity comes from the third paragraph of the introduction, which is a key section for framing the proxy and one of the most important paragraphs in the manuscript. It would benefit from being rewritten.
• Anaerobic methane-oxidising archaea (ANME), which are often key components of methane seep ecosystems, were not investigated in this study. While ANME do not produce hopanoids, they commonly dominate methane oxidation in anoxic sediments and are therefore critical for understanding methane cycling in methane seep environments. Their absence may have important implications for the interpretation of the results, particularly in the inner shelf region (ILS), where high methane concentrations coincide with comparatively heavier δ13C- C30 values. Without information on sediment redox conditions or the presence and activity of ANME, it is difficult to determine whether reduced AeOM signals in this area reflect lower methane release, a shift toward anaerobic methane oxidation, or differences in carbon source mixing. Expanding the discussion to acknowledge this limitation would strengthen the overall interpretation of methane seep dynamics. In particular to consider how ANME-related processes (potentially constrained by biomarkers such as archaeol or crocetane, or by microbial community data) might influence the observed patterns,.
• In line of the points raised above, the sections discussing the inner shelf region (ILS) would benefit from reconsideration and restructuring. Based on the δ13C- C30 values reported for ILS, the AeOM signal appears relatively weak. Values that are only moderately depleted (e.g., not more negative than ~−40‰) quite likely reflect mixing between multiple bacterial carbon sources rather than a distinct methanotrophic signature, making it difficult to draw firm conclusions. Strengthening this discussion would likely require clearer consideration of (i) the relative roles of aerobic versus anaerobic methane oxidation, (ii) potential mixing with terrestrially derived organic matter delivered by the Lena River, and (iii) the limitations of the δ13C- C30 proxy in this specific setting where you have a large river. In addition, the interpretation in terms of MOB I versus MOB II would be more convincing if it was explicitly contextualised using the δ13C- C30 literature ranges as well as typical values for non-methanotrophic bacteria. Providing these comparative ranges would make it much easier for readers to assess whether the ILS signal is consistent with methanotrophy or more likely reflects mixed sources.
• The results appear to show a consistent geographic trend from the inner shelf region (ILS) to the outer shelf region (OLS), with organic carbon concentrations decreasing, δ13C- OC values becoming less negative (from approximately −26‰ to −23‰), and δ13C- C30 values becoming more depleted (from ~−39‰ to ~−52‰). The manuscript would benefit from a more integrated discussion of these spatial trends and the processes that may control their origin, as this could help unify the Results and Discussion sections and strengthen the overall interpretation.

1. Line by line comments

Introduction

Line 71- 73: This sentence is quite long and could be rephrased for clarity, as it is currently difficult to follow the main point. More generally, this paragraph would benefit from including a reported range of δ13C- C30 values for AeOM from the literature, which would help clarify how AeOM is being diagnosed in this study.

Line 75: This sentence illustrates the point above. When stating that “a larger presence of methane has been linked to decreasing δ¹³C values of hopanoids,” you need to specify the δ¹³C–C₃₀ range associated with high methane presence, based on published studies.

Line 76: The text mentions that this approach is “generally used,” but only one relatively recent reference (Van Winden et al., 2020) is cited. Including additional references would help support the idea that this is a well-established and widely applied method.

Line 76: The phrase “intensity of time-integrated” could benefit from a brief clarification. A short explanation or example would help readers better understand what is meant here.

Line 79: Introduce with few words or a short sentence the concept of contemporary system calibrations for hopanoids and why are they important for interpreting geological records.   

Line 96: Since time-integrated proxies appear to be a central concept in this study (and are also linked to the point raised in line 76), it would be very helpful to introduce and explain this concept more explicitly earlier in the manuscript.

Line 97: OLS and ILS are mentioned here, but their locations are not clear from the map. It would be helpful to indicate both OLS and ILS in Figure 1.

Line 99: When referring to “high concentrations,” specify what is being measured (e.g. methane concentrations) for clarity.

Line 99:  The term “low δ¹³C values” is used here and throughout the manuscript, but it remains somewhat ambiguous. It may be clearer to indicate how low is low, or to refer directly to typical δ13C- C30 values for AeOM. Including a short description of the δ¹³C–C₃₀ range for AeOM earlier in the introduction, based on literature values, would be very helpful.

Line 100: It is not immediately clear where the mid-shelf is located relative to OLS and ILS. Referring explicitly to Figure 1 would help orient the reader.

Line 101: The second hypothesis is somewhat unclear. When referring to “lower concentrations of higher hopanoids,” it is not clear whether this refers to lower δ¹³C–C₃₁ values. Since the manuscript focuses primarily on δ¹³C–C₃₀, this section may benefit from clarification and consistency in terminology.

Methods

Line 113: As mentioned earlier, OLS and ILS should be clearly indicated on the map.

Line 158: While the sampled interval (1–2 cm slice) is provided, it would be helpful to also report the mass of material used for δ13C- OC analyses.

Line 160: Please clarify what is meant by “Ag capsules.” If “Ag” is an abbreviation, it should be defined at first use.

Line 218: Indicate how much sample material was used for 16s rRNA analyses

Line 235: The absence of analyses targeting anaerobic methane-oxidising archaea (ANME) may need further discussion. While ANME does not produce hopanoids, they are commonly present in anoxic methane seep environments and can be useful for identifying oxic–anoxic transitions in sediments. As oxygen data is not available for the sediment cores, it is possible that areas with lower AeOM signals reflect more anoxic conditions dominated by ANME rather than lower methane release. Considering ANME (and associated biomarkers such as archaeol and crocetane) alongside hopanoid-based proxies would strengthen the interpretation of methane seepage intensity.

Line 245 to 265: For the statistical analyses, it would be helpful to clearly outline throughout the manuscript (results, discussion, conclusions) that these estimates are semi-quantitative, not only here.

Results

Line 283: The results suggest that OC concentrations decrease from ILS to MLS to OLS. If this reflects the geographic order, presenting the results consistently in that sequence will improve clarity of the manuscript.

Line 285: Same for δ13C.

Line 290 to 294: There is a relatively large uncertainty associated with OLS values, can you provide an explanation? Perhaps in the methodology. Additionally, the statement that OLS and ILS have similar concentrations, while MLS and ILS show no significant difference, is somewhat confusing and could be rephrased for clarity.

Line 303: If −57‰ represents the most depleted δ13C value observed at OLS stations, state more explicitly. You might also consider only reporting mean values with standard deviations, or instead providing ranges for OLS, MLS, and ILS, rather than listing individual station values. Whichever approach is chosen, stay consistent across the results section.

Discussion

4.2.2. ILS paragraph: This section would benefit from substantial revision. When discussing more or less depleted values, it is necessary to include specific δ13C- C30 values for ILS results. It would also be helpful to compare them with published literature values for AeOM signal diagnosis. The ILS appears to be the area where the δ13C- C30 proxy for methane release is least straightforward. Although methane concentrations are high, δ13C- C30 values do not seem to clearly indicate AeOM. Given the proximity of the ILS to the Lena River—one of the largest rivers globally—terrestrial carbon inputs may influence the δ13C- C30 signal. The link between δ13C- C30 values and methane release in this area should therefore be treated with caution.

Line 379: How can it be ruled out that lower AeOM activity in the ILS is not driven by more anoxic sediment conditions and a higher contribution from ANME, rather than reduced methane release? If there is data available from the literature for sediment oxygen levels or ANME presence/absence, this section would benefit of a small discussion here in order to rule this out (or not).

Line 390: Including literature values for typical δ13C- C30 values of hopanoids produced by non-methanotrophic bacteria would help clarify how mixing between sources may influence the observed signal.

Conclusion

The conclusions might benefit from more cautious wording, emphasising that the δ13C- C30 –methane release proxy appears robust for MLS and OLS, but that in areas influenced by large terrestrial inputs (such as the Lena River), this proxy likely needs to be complemented by additional lines of evidence.

1. Minor comments:

• Several sentences throughout the manuscript are quite long (three lines or more). Breaking these into shorter sentences would improve readability.
• I suggest being coherent when describing ILS/MLS/OLS. For clarity it would be helpful if you follow the geographical progression
• Line 301: “Strikingly” may sound somewhat strong; “remarkably” could be a suitable alternative.
• The discussion section header titles are confusing, re-name to clearly indicate you are discussing: 1. OLS, 2. ILS, and 3. IMS. Similarly to above, I would suggest to do in geographical order.
• It would be helpful to clearly define key terminology early in the Introduction (e.g. δ¹³C –OC, δ¹³C –C₃₀, δ¹³C–CH₄).
• All maps should include scales, and OLS/MLS/ILS areas should be clearly indicated.

1. Figures:

Figure 1: Indicate ILS, MLS, and OLS areas in the map. The coordinate labels are very large, they can be reduced in size, and then the rectangular map enlarged. Label the Lena River and add a scale for the map. The land–sea boundary is currently difficult to interpret, maybe changing the map/permafrost overlay could help.

Figure 2: A scale bar should be included, reduce panel labels (a, b, c, d) size. The methane concentrations colour scale makes it difficult to distinguish values between ~50 and 300 nM; adjusting the colour scheme may help. Indicating OLS, MLS, and ILS on the map and summarising key spatial trends in the caption would improve interpretability.

Figure 3: Panel labels (a, b, c) should be included directly in the figure, not only in the caption. The shaded area referred to as “grey” in the caption appears green in the figure and should be made consistent. Please also indicate the literature sources of the hopanoid end-member values in the caption and clarify that the shaded areas are based on semi-quantitative estimations.