the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 25 Aug 2026
Biogeochemical and microbial microseepage connectivity from a deeply buried salt diapir on the Scotian Slope of Atlantic Canada
Abstract. Cold seeps are seafloor environments where hydrocarbon-rich fluids, including methane and hydrogen sulfide, migrate through deep-seated faults and fractures to the seabed, supporting chemosynthetic communities. Although the biological activity within and immediately around these sites can be highly elevated compared to the surrounding deep-ocean ambient sediments, little is known about whether subtle changes extend to the larger periphery, where no visible signs of seepage exist. Here we examine how geological structures, such as subsurface faults, regulate seep formation and fluid migration, and assess the influence this has on microbial distributions by combining a 2.5×2.5×1 km three-dimensional seismic survey with a 1.6 km transect study that overlies a deeply buried salt diapir. The crest of the diapir rests ~1 km below the seafloor, where it has heavily disturbed the overlying bedrock with radial and crustal faults, half-graben block displacements, and salt-tectonic-influenced anticlinal mini-basins. Rocks draping the diapir also host a subsurface methanogenic deep biosphere that produces sufficient methane to sustain a biodiverse ocean floor cold seep. A portion of the produced hydrocarbons has become trapped within ~300 mbsf block-faulted strata where they are recognizable in seismic data as a direct hydrocarbon indicator (DHI). We analyzed 52 sediment samples extending 5–575 cm below seafloor (cmbsf) from five gravity cores and one push core collected at an active cold seep. Spatial heterogeneity in cored sediments along the transect was revealed by porewater geochemistry, stable isotopes, and lipidomics. Collectively, these data resolve distinct chemosynthetic zones that form tightly coupled functional networks mediated by interlinked redox-dependent cycling of nitrogen, carbon, iron, and manganese that are comprised of ammonia-oxidizing archaea (AOA), anaerobic methanotrophs (ANMEs), and sulfate-reducing bacteria (SRB). Evidence is provided that microbial assemblages and their metabolic interactions are shaped and sustained by diffuse and largely non-detectable microseepage ascending along more deeply buried fault systems associated with the salt diapir. The results, therefore, establish a spatially resolved model for offshore geochemical surveys that link subsurface fluid flow to redox gradients and microbial activity.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2026-5038', David Naafs, 16 Sep 2026
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AC2: 'Reply on RC1', Gamra Oueslati, 21 Oct 2026
We thank Dr. David Naaf for his thoughtful review and are working to make the needed corrections. Within Dr. Naaf’s review two major points were addressed. The first is that the paper’s discussion needs to tighten-up linkages between lipidomics and ANME activity (or lack of) using more traditional biomarker approaches (i.e. the methane index and archaeol/OH-archaeol ratios) and provide a more nuanced explanation of how biomarkers are used to infer the site’s microbial dynamics. We have included had OH-AR/AR and PA-OH-AR/PA-AR ratios in our analyses (section 4.2.2). While methane index (MI) values were evaluated, these data were not included in the manuscript, as they produced values signaling little to no methane influence. We agree that for the completeness of the analysis these data should be included in the revised paper. We are also working to improve the writing in the discussion of the paper to better tie the microbial systems together.
The second point was to question the independence of our study from that of Redshaw et al., 2026 (Frontiers of Microbiology; doi.org/10.3389/fmicb.2026.1709097). Both studies indeed examine the area known as Seep Site 2A-1 using lipid biomarkers and porewater geochemistry. Redshaw et al. (2026) resolved the localized biogeochemical stratification arising at the actively venting carbonate seep structure as a 500 m long push core (~40 cmbsf) transect that reproduces a cross-section of the seep structure. These push cores were then used to reconstruct the geochemical architecture of the bioherm and to compare the shallow sediment inputs from that of ambient sediments fringing the seep platform. This study marks a very different focus from our current study.
For our present study, we address the question of whether reduced fluids are also seeping out of the deeply buried radial and crustal fault systems surrounding the carbonate cold seep platform as a form of diffuse microseepage in what otherwise appears to be normal marine sediments. In doing so, we further analyzed how such microseepage locally affects the microbial communities of such impacted sediments. The investigated fault network is produced by a deeply buried salt diapir (sitting ~1 km below the ocean floor). At its most shallow extent, the faults reach to ~100 mbsf and propagate outward ~2 km from the central carbonate seep platform. Our study therefore uses gravity coring (up to 5.75 mbsf) collected up to 1.6 km off axis of the visible seep structure. A single push core (number 78 called the “The Hole”) from Redshaw et al. (2026) is used as a tie-point to compare active-seep conditions to that of ambient (pseudo-ambient) sediments. To resolve microseepage activity, the study contrasts its biomarker and porewater geochemical data with a sedimentological survey to constrain potential reservoir effects. In doing so, our study not only presents data supporting the presence of microseepage at these larger peripheral sites; it also shows microbial changes arise from the fluid interactions. By extension it further indicates salt tectonic influenced cold seeps are not point source features, but mark larger complex biotic networks that in some cases have no visual surface expression at the seafloor.
Citation: https://doi.org/10.5194/egusphere-2026-5038-AC2
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AC2: 'Reply on RC1', Gamra Oueslati, 21 Oct 2026
- AC1: 'Comment on egusphere-2026-5038 - Supplemental Information', Gamra Oueslati, 12 Oct 2026
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RC2: 'Comment on egusphere-2026-5038', Anonymous Referee #2, 23 Oct 2026
The manuscript by Oueslati et al., entitled „Biogeochemical and microbial microseepage connectivity from a deeply buried salt diapir on the Scotian Slope of Atlantic Canada“ presents data from six sediment cores taken off the Canadian Atlantic coast of Canada. The cores come from a relatively small area, overlying a salt diapir. One core (site 78) is directly in a cold seep site that is driven by fluids ascending along a North-South trending fault. The other coring sites are oriented along a more or less perpendicular running 1.6 km-long transect. Pore water geochemical data, bulk sediment geochemistry and lipid biomarker data are presented.
The main point of this manuscript was to observe how far beyond the actual cold seep seepage affects sediment biogeochemistry and thus the indigenous microbial communities.
I found the underlying idea and very appealing but I do have some major concerns about the experimental design and therefore about the interpretation of the data as well.
While I agree that biomarkers are a valuable tool in assessing microbial life or life in general sedimentary environments, particularly in ancient environments. Yet, they will never have the same explanatory power as genomics. In a study about active processes with absolutely no intention to look at ancient microbial communities I am wondering why the authors have focused exclusively on biomarkers, when the samples had to be preserved at -80°C anyways, which makes them perfect for DNA extraction and genomic analyses.
With some minor caveats that I will discuss later, the data presented in this manuscrpt appear to be of high quality.However, I don’t think that some of the conclusions are really supported by the data. Overall the manuscript contains some valuable data, but it needs a major revision before publication.
Major comments:
Line 177: During freezing the salt content of the pore water is concentrated, leading to precipitation of carbonates and other minerals that will not dissolve again upon freezing, changing the pore water concentration of ions, especially those in the carbonate system (Ca, Mg, DIC). Therefore, any pore water concentration data from previously frozen samples have to be considered minimal estimates. As this study uses DIC instead of methane concentration profiles to assume AOM activity, which I found awkward to start with, I would be very cautious with any interpretation based on these data.
Line 239ff: Just by looking at the TOC data would say there is no significant statistical difference in these profiles other than the peak and downward decrease at site 78.
Line 247: This is not what Fig. 2 shows. In fig. 2. the C/N ratio for Site 78 is a straight line at almost zero, definitely not 5.4.
Line 259, Figure 3: I think you are overinterpreting the data here. Thevery low R2 in Panel a in fact show that there is no correlation. Anything less than 0.5 I would not consider a correlation but rather as proof that these parameters are independent from each other.
Panel b: If you remove the red dots (site 78), your correlation will drop to much lower values. This pseudocorrelation is misleading.
Panels c and d only show that there is basically zero correlation because d13Corg does not vary at all.
Please remove all these pseudo-correlations or use the figures only to show that these parameters do not correlate.Line 292: What kind of SO4-DIC interaction was observed? There might be wiggles in the concentration profiles, but given the dubious quality of the DIC profile I would be extremely cautious to draw any conclusions based on those. Also, if you think there is an interaction, what kind?
Line 445: How do you know that AOA are more active in these samples? I find this statement problematic in two ways: First you don’t really know that MK-6:0 and 6:1 are truly from Thaumarcheota, there are no pure culture experiments, only correlations between genomic data and biomarkers from environmental samples. This is a strong indicator, but still no proof. Second, abundance does not translate to activity. You have a detailed pore water dataset, but as long as this dataset does not show any indication of AOA activity, then I don’t think that you can make such a statement.
Line 481: I agree that GDGT-1-3 is a very strong indicator for sulfate driven AOM, but I still find it awkward to speculate about this process when you don't have any methane data.
Line 519f: What could these mysterious electron acceptors be? Given the extensive porewater data that cover basically all potential electron acceptors with a higher energy yield than sulfate (NO3, Mn4+, Fe3+), one should be able to rule out any other electron acceptors.
Line 589: Given your geochemical data I do not see any evidence for this. Could you back up this claim or is this just an assumption? If the latter, please state this more clearly.
Minor comments:
Line 66: These are not the original publications that showed these processes for the first time. Credit should be given to those that led the way. For example, Haroon et al., (2013) "only" showed that Nitrate-dependent AOM in a novel group of organisms. The original study that proved that this process actually exists would be Raghoebarsing et al. (2006) https://doi.org/10.1038/nature04617. Please check also the other references.
Line 120: Sites 15,17,19 appear to be much closer together in panel B than in panel C. Part of this is caused by the different scale, but still, they don't seem to match.
Line 141: How were the gravity cores subsampled and how were the subsamples stored? There is some info at the bottom of the paragraph but it is not clear whether this relates to all cores or just the push cores. I would find it rather laborious to subsample a >5 m long core at 2-4 cm intervals.
Line 151ff, Table 2:That table is a bit poor. The information that the Hole has a seep HC signature and the other samples have an ambient (whatever that means) signature is not really worth reporting. If you already went to such great lengths to take samples for headspace gas analysis, why not report methane concentrations, even if it's just for the deepest sample from each core.
Line 298: What do you mean by biogeochemical zonation, what zone?
Figure 5: Writing the site number and depth together in tiny font does not help reading this fugure. I would suggest putting the site number in larger font once to the left for the entire dataset, and then just leave the depth next to the bars. Also, please label every axis, there is nothing at the bottom.
Citation: https://doi.org/10.5194/egusphere-2026-5038-RC2
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Summary
In this manuscript Oueslati and co-authors present biogeochemical and biomarker data from a range of short gravity/push cores that were taken along a transect across a deeply buried salt diapir in the Atlantic Ocean. The data demonstrate that the different cores along the transect have heterogenous geochemical and/or biomarker signatures and this is used to argue for different microbial assemblages across the transect, shaped by the presence of the salt diapir.
Main assessment
The data presented in this manuscript is of good quality and interesting. Especially the biomarker data as shown in figures 5&6 is extensive. The geochemical and/or biomarker data changes along the transect with core 78, from the methane seepage site, standing out. As such, the fundamental conclusion that the biogeochemistry/lipidomics, maybe related to the microbial assemblages, differ among the transect is supported by the data. It is likely that the salt diapir and associated methane seepages drives this. The presentation quality is good with clear language and figures.
However, in the current version of the manuscript the link between lipidomics and microbial assemblages is made to easy and with too much certainty. For example, the manuscript states that the lipid biomarkers indicate distinct ANME clades as shown by higher abundance of isoGDGT-1 to -3 in some cores. However, this is hard to see and normally indices such as the Methane Index would be used to explore the impact of ANME archaea in marine sediments (Zhang et al., 2011). The presence of isoGDGT-1 to -3 is not sufficient by itself as these lipids are also made by many other types of archaea. See recent review on GDGTs in marine sediments (Elling et al., 2026).
A much more nuanced discussion is needed on how biomarkers are used to infer microbial dynamics. This doesn’t mean that the differences between cores is not there, but the conclusions of what is driving this in terms of microbiology needs more nuance and expanded discussion as genomic data is lacking for these cores.
Secondly, it is not clear to me how the data presented in this submitted manuscript differs from that shown in a recent publication from this group (Redshaw et al., 2026). That published paper also appears to report biogeochemical and biomarker data from push cores across the same seep site. And the conclusion of this published paper “Spatial changes in the stratified system highlight the complex interplay of micro- and macro-seepage and provide insights into the seep’s evolution and impact on microbial dynamics across the carbonate structure” appears similar to the conclusion from this submitted manuscript. As such I can not determine whether the submitted manuscript represents a substantial contribution to scientific progress.
I encourage the authors to revise this manuscript and 1) provide a much more nuanced discussion about what the biomarker data represent in terms of microbial assemblages and 2) make it very clear what the novelty of this study is compared to published work.
David Naafs, 16th of September 2026.
Comments (in order of appearance)
Lines 103-118: An introduction into the (biomarker) methods is needed here, especially the wide range of biomarkers used in this manuscript. This includes iso and brGDGTs, chlorophyl, menaquinones, etc etc.
Lines 207-216: more details are needed here for the qTOF-MS methods. For example, what mobiles phases and gradients were used, what scan parameters (e.g. m/z range), etc etc.
Line 215-16: as only one internal standard was used for all different compounds, without response factors, the quantifications given here are semi-quantitative at best. Although this doesn’t undermine the results, this caveat needs to be clearly acknowledged.
Line 232: maybe I missed something, but I could not find methane concentrations in any of the figures. Methane data is key as this is proposed as main driver. So this data needs to be shown. Maybe in figure 2?
Lines 238-254 (and elsewhere): statistical proof needs to be given to support statements about parameters being different between cores. For example, is the TOC data in cores 15, 19, and 17 statistically different from that in cores 14 and 13 as stated? If it is, adding statistical data to support these statements will strengthen the manuscript. If not, then such passages need to be removed or altered. This applies to the whole manuscript.
Line 259: but for some the correlation (R2) is weak with values < 0.2. Is this still significant?
Line 262: See previous comment. Need to provide proof that these correlations are significant.
Figure 4: I wonder why no CH4 nor O2 data is presented here. Especially as CH4 is considered a key driver of some of the biomarker data. And are all cores anaerobic?
Line 307 (and throughout): crenarchaeol should not be called isoGDGT-5. Revise throughout the manuscript. IsoGDGT-5 has give cyclopentane rings and is normally not found in marine sediments.
Line 328: change “0-5 rings” to “0-4 cyclopentane rings as well as crenarchaeol”.
Line 338: no IPL versions of brGDGTs are found? As the authors argue that the brGDGTs are produced in the sediments and not transported from the terrestrial realm, wouldn’t IPL brGDGTs be expected?
Line 388-391: provide statistical evidence that the data from core 78 (the hole) is different from the other cores.
Lines 391-395: This sentence is not clear to me. If the methane has a d13C signature of – 71 ‰, I would expect the methanotrophic biomass to be even more depleted than that, but across all data, only 2 samples (2 and 8 cm from core 78) have d13Corg < -30 ‰. And even in those samples, d13Corg is around – 40 ‰. If methanotrophs are a major source of the carbon, wouldn’t d13Corg need to be even more depleted?
Line 404: if bioturbation is found, does that mean the core is not anaerobic?
Line 411: not clear why increased preservation can not be the main driver.
Line 436-437: why is degradation the reason and not reduced phytodetrital input? This requires more explanation
Line 446: thaumarchaeota have been renamed to Nitrososphaeria. Change throughout the manuscript.
Line 448: what core goes down to 800 cmbsf? All data is plotted down to 600 cmbsf, right?
Line 511-512: reference for these ANME thresholds are needed
Line 522-523: not clear why brGDGTs are assumed to be produced in the sediments and not transported from the terrestrial realm. Needs more discussion to rule out terrestrial production and transfer to marine realm. For example, use methods as proposed in (Sinninghe Damsté, 2016), maybe in combination with the BIT index (Hopmans et al., 2004). See also recent review on GDGTs in marine sediments (Elling et al., 2026).
Lines 529-532: not clear whether anybody has ever claimed brGDGTs to be derived from sulphate reducing bacteria, or is that not what this sentence means? So far the few known sources are aerobic (heterotrophic) acidobacteria (Sinninghe Damsté et al., 2018; Chen et al., 2022; Halamka et al., 2023).
References
Chen, Y., F. Zheng, H. Yang, W. Yang, R. Wu, X. Liu, H. Liang, H. Chen, H. Pei, C. Zhang, R.D. Pancost, and Z. Zeng, 2022. The production of diverse brGDGTs by an Acidobacterium providing a physiological basis for paleoclimate proxies. Geochimica et Cosmochimica Acta 337, 155-165. doi: 10.1016/j.gca.2022.08.033
Elling, F.J., G.N. Inglis, N. Davtian, S.J. Hurley, B.D.A. Naafs, L.K. O'Connor, R.D. Pancost, F. Peterse, R. Rattanasriampaipong, A. Rice, F. Schubotz, J.S. Sinninghe Damsté, L. Wörmer, A. Auderset, K.W. Becker, M.A. Berke, P.K. Bijl, C. De Jonge, L. Dong, B.J. Duncan, T.D. Jones, P. Fenies, S. Fietz, S.L. Ho, A. Huguet, C. Huguet, J. Kaiser, X.-L. Liu, G. Mollenhauer, S. Naeher, A. Pearson, K.K. Śliwińska, A. Sluijs, C. Sosa-Montes de Oca, Q. Tian, J.E. Tierney, D. Varma, W. Xiao, Y.G. Zhang, and X. Zhao, 2026. Archaeal Tetraether Lipids as Tracers for Past Marine Environmental Change. Paleoceanography and Paleoclimatology 41, e2025PA005373. doi: 10.1029/2025PA005373
Halamka, T.A., J.H. Raberg, J.M. McFarlin, A.D. Younkin, C. Mulligan, X.-L. Liu, and S.H. Kopf, 2023. Production of diverse brGDGTs by Acidobacterium Solibacter usitatus in response to temperature, pH, and O2 provides a culturing perspective on brGDGT proxies and biosynthesis. Geobiology 21, 102-118. doi: 10.1111/gbi.12525
Hopmans, E.C., J.W.H. Weijers, E. Schefuß, L. Herfort, J.S. Sinninghe Damsté, and S. Schouten, 2004. A novel proxy for terrestrial organic matter in sediments based on branched and isoprenoid tetraether lipids. Earth and Planetary Science Letters 224, 107-116. doi: 10.1016/j.epsl.2004.05.012
Redshaw, E., G. Oueslati, U.U. Umoh, N. MacAdam, P. Granados, J.N. Bentley, N. Ahangarian, R. Bennett, V. Baghalabadi, M.G. Fowler, A. MacDonald, C.R.J. Hubert, and G.T. Ventura, 2026. Microbial and geochemical architecture of an active Scotian Slope cold seep. Frontiers in Microbiology Volume 17 - 2026. doi: 10.3389/fmicb.2026.1709097
Sinninghe Damsté, J.S., 2016. Spatial heterogeneity of sources of branched tetraethers in shelf systems: The geochemistry of tetraethers in the Berau River delta (Kalimantan, Indonesia). Geochimica et Cosmochimica Acta 186, 13-31. doi: 10.1016/j.gca.2016.04.033
Sinninghe Damsté, J.S., W.I.C. Rijpstra, B.U. Foesel, K.J. Huber, J. Overmann, S. Nakagawa, J.J. Kim, P.F. Dunfield, S.N. Dedysh, and L. Villanueva, 2018. An overview of the occurrence of ether- and ester-linked iso-diabolic acid membrane lipids in microbial cultures of the Acidobacteria: Implications for brGDGT paleoproxies for temperature and pH. Organic Geochemistry 124, 63-76. doi: 10.1016/j.orggeochem.2018.07.006
Zhang, Y.G., C.L. Zhang, X.-L. Liu, L. Li, K.-U. Hinrichs, and J.E. Noakes, 2011. Methane Index: A tetraether archaeal lipid biomarker indicator for detecting the instability of marine gas hydrates. Earth and Planetary Science Letters 307, 525-534. doi: 10.1016/j.epsl.2011.05.031