Global mapping of flux and microbial sources for oceanic N_2O

Domain: earth_science
Published: 2025-04-08
Editorial outcome: major_revision

Abstract
The ocean is the largest source of N2O emissions from global aquatic ecosystems. However, the N2O production–consumption mechanism and microbial spatial distribution are still unclear. Our study established a bottom-up model based on the source‒sink boundary and the microbial sources of N2O. A high-resolution (0.1°) global distribution of oceanic N2O was depicted, confirmed by approximately 150,000 surface measurements. The microbial N2O flux is 2.9 Tg/yr N-N2O, with the oxygen-deficient zones (ODZs) disproportionately accounting for more than half of the total emission. High primary productivity, sharp oxyclines, and shallow emission depths caused the ODZs to be N2O hotspots. Geographically, ammonia-oxidizing archaea (AOA, 1.0 Tg) are the most widely distributed contributors to N2O emissions in the ocean, completely overtaking ammonia-oxidizing bacteria (AOB). Heterotrophic denitrification, mainly occurring in ODZs, contributes the most (1.6 Tg) to N2O emissions. Overall, this study offers a bottom-up framework for understanding microbial source-sink mechanism in the ocean.

Introduction
Nitrous oxide (N2O), one of the most important greenhouse gases and the greatest human-related threat to the ozone layer, has increased substantially, by over 23%, since preindustrial times1. As a long-lived (116±9 years) greenhouse gas, nitrous oxide (N2O) is 265-298 times higher than CO2 in the global warming potential on a 100-year timescale2. Oceans are among Earth’s largest sources of N2O emissions, second only to natural soils and agriculture (IPCC). Although the amount of oceanic emissions has been well constrained3,4, current estimates are usually based on air‒sea flux (ΔpN2O)3,5 or simple semi-empirical equations6–8; thus, the N2O production‒consumption mechanism and spatial distribution of microbial N2O sources in oxygen-stratified oceans are still unclear9,10.

N2O emissions are microbially driven and highly oxygen sensitive in the ocean, leading to high heterogeneity in ΔpN2O. However, the coverage of ΔpN2O data is generally limited and in broad ranges, uncertainties inevitably widen when extrapolating ΔpN2O data to the global scale3. Moreover, sources and sinks coexist in the oxygen-stratified ocean11–13, and surface-based measurements cannot reflect the production and consumption of N2O in the deep layers. Therefore, how N2O is emitted from the ocean, how deep the source‒sink boundary is, and how it evolves cannot be explained, especially under the effects of increased stratification and deoxygenation expansion14. Most quantitative analyses of N2O microbial sources are conducted at the regional scale11,12 or on the basis of semi empirical equations of nitrification and denitrification6–8,10, which do not consider the niche separation of N2O-related microbial processes in different ecological niches6–8. For example, ammonia-oxidizing archaea (AOA) have greater affinity for substrates and compete for ammonia-oxidizing bacteria (AOB) in the NH4+-limited ocean15,16. Nevertheless, several studies have reported the contribution of AOB to marine N2O emissions via nitrifier denitrification (NDN)17. Under hypoxic or anoxic conditions, N2O is produced as an intermediate during heterotrophic denitrification (HDN), with organic matter as the electron donor10,18. However, the quantification and spatial distributions of these microbes with respect to N2O emissions have not been well depicted in the ocean9,10.

In this study, we established a bottom-up model based on the source‒sink boundary and the microbial sources of marine N2O. Extensive literature research has been conducted to obtain the geochemical profiles of DO and N2O concentrations and isotopic signatures (δ15NBulk, δ18O and δ15NSP) at in situ locations (approximately 1000 lines of data), along with the isotopic characteristic values for each N2O production pathway (i.e., AOA, AOB, HDN, and NDN). We identified the source‒sink boundary of N2O via global oxygen stratification (up to 5000 m) in the water column. FRAME model was then used to quantify the specific microbial contributions to N2O emissions and N2O reduction degree19. Finally, the ammoxidation (ammonia oxidation) flux, N2O yield during ammoxidation (NO-N/NH4+-N), and quantified N2O microbial sources and fraction of residual unreduced N2O (rN2O) were combined as constraints to accurately estimate global marine N2O emissions. The results have been confirmed by a large compilation of N2O in situ measurements (approximately 150,000)3. Overall, our results present a detailed spatial distribution of marine N2O emissions with a source‒sink mechanism and quantified microbial sources.

Results
N2O source‒sink boundary in the ocean
Due to the limit of light, the decomposition of organic matter or the poor mixing and ventilation, the ocean is oxygen-stratified. Earlier studies have revealed maximum N2O concentration in the oxygen minimum zones of the ocean11,20,21. N2O has a perfect mirror-image relationship with DO and reaches its highest concentration at the lowest amount of dissolved oxygen (Supplementary Figs. 2–11)11,22. Regardless of the upwelling, the source‒sink boundary of N2O, below which the water column does not contribute to N2O emissions, was identified by a comprehensive grid-by-grid (0.1°) traversal of DO up to 5000 m in the ocean (Fig. 1). In oxygen-deficient zones (ODZs), DO decreases to anaerobic levels (minimum O2 ≤10 μM) at shallower depths (387.9 m on average, Fig. 1b). In addition to the three major ODZs (Fig. 1c), namely, the Eastern Tropical North Pacific (ETNP), Eastern Tropical South Pacific (ETSP), and Arabian Sea, we also found some sporadic ODZs in the North Pacific Ocean, indicating the potential hotspots of N2O emissions. The upper oxycline (UO), with a N2O peak at the oxic‒anoxic interface (Supplementary Fig. 2–5), is the engine driving N2O diffusion to the mixed layer (ML). The sharp oxycline creates favorable conditions for incomplete denitrification and nitrification with high N2O yields, driving high supersaturation and fluxes of N2O at the surface11,23. Additionally, a stable proportionality of 0.45 and 2.58 for the plot of δ18O versus δ15NBulk (R2=0.52, Supplementary Fig. 12) was observed above and below the source‒sink boundary, respectively. In general, a strong correlation with slopes of 2.6 is evident when reduction process dominates, which contrasts from a slope of <1 commonly observed for mixing of N2O production and atmospheric N2O24–26. The slope of 0.45 proved the production, mixing and emission of N2O in the source part. In contrast, the slope of 2.58 confirmed the significant net N2O consumption in the ODZ core. Thereby the N2O concentrations simultaneously decreased to 0 at the middle of ODZ core (Fig. 1a). Furthermore, the isotopic composition of N2O in the ODZ core is significantly different from that in the source layer, further ruling out vertical exchange with the source layer. Therefore, the long-term and large-scale anaerobic areas ensure net N2O consumption in the ODZ core, which acts as the sink of N2O. In other oceans, the N2O peak was also observed at the lowest point of oxygen (Supplementary Fig. 6–11), although the boundary DO ranged from 10 μM to more than 300 μM (Fig. 1c). In the vast North Pacific Ocean and equatorial regions, the boundary DO is less than 50 μM, accompanied by a shallow boundary depth (less than 1000 m), favouring excessive N2O production and emission. A deeper source‒sink boundary has been found in the North Atlantic and Southern Oceans. The boundary DO increased to more than 300 μM with the boundary depth reaching 2000 m. Overall, the source‒sink boundary of N2O in the ocean was identified (Fig. 1), and the water column below the source‒sink boundary does not contribute to atmospheric emissions; therefore, it was excluded from the remainder of this study.

Microbial processes governing N2O production and consumption
To quantify the microbial sources of N2O and the fraction of residual unreduced N2O (rN2O) in the source part, the isotopic N2O values obtained from Keeling plot (Supplementary Figs. 13–22), the corrected isotope signatures of the microbial sources (Supplementary Table 1-2), and the isotopocule fractionation constants (i.e., εN: −15.4±4.7, εO: −7.1±2.1, and εSP: −5.9±1.4) for N2O reduction process were input to the model FRAME (Supplementary Fig. 23). In this study, four common microbial sources (HDN, NDN, AOB, AOA) and rN2O was quantified (Supplementary Fig. 24, Supplementary Table 3). The linear regression relationships between N2O microbial sources and boundary DO were uniformly adopted for extrapolation to global oceans (Supplementary Fig. 25, Fig. 2).

The primary productivity, substrate availability, boundary depth, and DO together determine the niche distribution of each N-cycling microorganism in the ocean. AOA dominate the nitrification pathway, contributing 34.1% of the N2O in the ocean (Table 1), which is the dominant N2O production pathway in the North Atlantic and Southern Oceans. Although both of them are chemoautotrophic processes, AOA have a greater affinity for NH4+ and oxygen20,22,27. Thereby, AOA exceeds AOB in NH4+-limited oceans with sharp oxyclines, while the contribution of AOB increases in high-latitude regions with high-oxygen (e.g., the Arctic Ocean and Antarctic Oceans). The isotopic signatures of N2O in the Arctic Ocean have proved the important role of both AOA and AOB to N2O productions12. In the ODZs, AOB are completely depleted (2.2%) because of phytoplankton competition, rapidly decreasing oxygen gradients, and surface light inhibition derived from shallow boundary depths. HDN, fueled by organic matter exported from the photic zone, is the dominant N2O production pathway in the North Pacific Ocean and equatorial regions. It further increases to 63.3% in ODZs because the abundant organic electron donors and sharp oxyclines create favorable conditions for incomplete denitrification. Notably, the contribution of denitrification is still considerable even if DO does not reach the anaerobic level in the open ocean. It is possibly associated with organic particles; the interior of sinking particles can afford a low-DO microenvironment20. On a global scale (Fig. 2), the contribution of denitrification (HDN+NDN) to N2O emissions is 61.1% (Table 1), nearly two-fold greater than that of nitrification (AOA+AOB). HDN is the first contributor to oceanic N2O emission, whereas AOA are the most widely distributed contributor in the ocean.

Global distribution of N2O flux in the ocean
To obtain the global N2O flux in a year scale (Tg N2O-N/yr), we first calculated the N2O emissions by AOA (N2OAOA) in each grid on the basis of the ammoxidation flux (ammonia oxidation amount in a year scale), N2O yield during ammoxidation (NO-N/NH4+-N), and the fraction of residual unreduced N2O (rN2O, Supplementary Fig. 25e). The total N2O flux was then obtained according to its proportion to total production in each grid (e.g., N2OAOA/fAOA; see Methods for details). It is worth noting that the fraction of residual unreduced N2O (rN2O) determines the net emission of N2O. We established the empirical formula between the rN2O and the boundary DO (Supplementary Fig. 25e). As the boundary DO rises, there is initially an increase in rN2O, followed by a subsequent decline. In ODZs with micro-oxic environment, the N2O production and reduction are both active. As the boundary DO increases, the N2O reduction is prior to be inhibited as nitrous oxide reductase (nos) is the most O2 sensitive denitrifying enzyme28, leading to the increase of rN2O. However, the data obtained in the shallow Arctic Ocean and off the coast of Antarctica gave rN2O values as low as 20% in spite of high boundary DO (Supplementary Fig. 25e)3,12,29. This implies that a significant portion of the N2O produced in situ or diffused from the atmosphere is reduced by denitrification in sediments12.

The annual N2O flux is 2.9 Tg/yr N-N2O (Fig. 3, Table 1), the distribution of which is in line with primary production pulses. On average, the turnover rate of phytoplankton (growth, death, and mineralization) is 45 times a year30, providing never-ending NH4+, NO3-, and organic matter for the continuous production of N2O via nitrification and denitrification. Furthermore, the decay of phytoplankton creates the anaerobic environment for the significant production of N2O. Therefore, the oceans around the equator contribute the most to marine N2O emissions, where ODZs disproportionately account for more than half of N2O emissions (1.6 Tg N-N2O) with only 0.1–0.2% of the ocean volume31. A higher flux of N2O has also been observed in other oceans with high primary productivity, e.g., the Gulf of Guinea, Bay of Bengal, Gulf of Mexico, and Indonesia. In contrast, slight supersaturation and occasional undersaturation are predicted in the open Arctic Ocean and Southern Ocean, with limits on light and temperature at high latitudes. With respect to microbial sources (Table 1), the contribution of denitrification is almost twofold greater than that of nitrification. Traditional HDN is the largest contributor (1.6 Tg) to N2O emissions in the ocean, which mainly occurs in ODZs (1.0 Tg). AOA are the most widely distributed contributors (1.0 Tg) in the NH4+-limited ocean and completely overcome AOB (0.1 Tg) to N2O emissions.

Methods

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript presents modelling of the N2O ocean flux based mostly on literature data of several ocean profiles including geochemical data and N2O isotopocules. The approach is innovative and tries to apply most up-to-date interpretation strategies to determine the special distribution of ocean N2O flux and to identify and quantify the microbial N2O production pathways. This is a very challenging task, the idea is very interesting but in my opinion the results evaluation and presentation is not acceptable. The calculation methods applied can not be verified due to lack of proper description, it is not clear how the authors came to most of their results.\nThere are many unclear point in the manuscript, I will mostly concentrate on my expertise – N2O modelling, which I cannot follow in many points, although I am working with such modelling and the applied approaches should be perfectly clear to me. And unfortunately they are not. It can be due to improper application of these methods or due to minimal description of the applied calculations. I understand it might have been forced by the requirements of this journal, but then I think it is not the proper journal to describe such a complex combination of approaches. I think you should chose a journal with unlimited length of articles, and where method can be described before results. In the current form your manuscript reads very difficult, because you use a few of advanced evaluation methods which are not introduced but discussed and the reader is quickly lost. I think it shouldn’t be published this way.\nWhen describing the evaluation method there are many important points missing, even if you have to keep it short you have to be precise, especially about methods you are using. You should always cite the original work presenting the method and shortly explain how it is working, eg. For your isotope map approach, mentioned in Scenario 1 you do not even cite the source paper of this. In Scenario 2 you try to make the multi-isotope mixing applying the SIMMR model, where you have to ignore or very much simplify the N2O reduction process. I have also been trying to work with this approach, unsuccessfully, because you cannot really compute fractionation process with this model. This is why we have developed another tool where you can simultaneously calculate mixing proportions and fractionation processes (Lewicki et al., 2022). This is an easy-to-use software, which even do not require any programming skills: https://malewick.github.io/frame/ . Applying this tool would save you a lot of inconsistencies in your descriptions, especially with the case of N2O reduction, which I really do not understand how you have determined, why you apply the mean value of 0.72, if you assume it is stable for all the data points you use.\nSome more questions to your evaluation scenarios:\nScenario 1 – lots of important information are missing on how the calculations were done – it is not possible to follow or check you calculations: which values you accepted as typical for nitrification and denitrification? Why these values? Citations needed! What is the map method? Where is this from – citation needed! How can you calculate r with map method? Why do you adopt 0.72? Do you expect that this reduction value will be quite stable across all the different sites you are recalculating?\nScenario 2 - It is not explained how you did the corrections of isotope values with the substrates. It is confusing if you have corrected N2O values or the characteristic signatures of the processes. How the O values were corrected, which assumption on O-exchange with water and incorporation of O2 were accepted – it is very complex and cannot be omitted. Did you ignore N2O reduction in scenario 2? I think your equation (11) and (12) are wrong, why suddenly rN2O appears there? It is not explained at all.\nMore specific comment provided by an early carrier scientist who contributed to this review. The person is experienced in N-cycle research, microbial processes, N2O isotopocule studies, but had numerous major problems in understanding the main methods applied in this manuscript:\nMain:\n- why N2O is particularly harmful compared to other greenhouse gases\n- why previous methods fail to capture deep ocean N2O dynamics\n- explanation of terms like δ15NBulk, δ18O, and δ15NSP and their role in distinguishing microbial processes.\nN2O Source‒Sink Boundary in the Ocean:\n- Explain terms like upper oxycline (UO), oxic-anoxic interface, supersaturation, and isotopic compositions\n- significance of (ODZs) and sporadic ODZs in the Northern Ocean.\n- Explaining δ18O vs. δ15NBulk isotopic relationship and how it tracks N2O processes\nMicrobial Processes Governing N2O Production and Consumption\n- difference between Scenario 1 and Scenario2 not clear\n- Explain nitrification, denitrification, and the cryptic sulfur cycle, and why it’s less studied\n- Why AOA and AOB dominate certain regions, how they contribute to N2O.\n- Would be nice to describe briefly what the referenced figures e.g., Figure S20, tables show.\nGlobal Distribution of N2O Flux in the Ocean\n- Define N2O flux, ammoxidation flux, and stoichiometric N2O yield & N2O flux calculation process\n- Relationship between primary production and N2O emissions.\n- What can be the Model limitations\nMaterials and methods\n- why δ15NBulk, δ18O, δ15NSP values matter\n- Why exclusion of lab simulations & why field data preferred\n- grid-by-grid traversal? Assumptions/ limitations\nKeeling plot analyses and the δ15NSP/δ18O mapping approach\n- What is Keeling plot? terms like mixing-reduction and reduction-mixing\n- Why Keeling plot doesn’t work in the ODZ core.\n- Why mixing-reduction model selected\nMicrobial source partitioning and N2O emission estimation\n- Explaining Terms like δ15NBulk, εminer, rN2O\n- How AOA, AOB, ADN, NDN, and HDN contribute to N2O production\n- why scenarios (1 and 2) were necessary? Why multi-isotope Bayesian model and stable isotope mixing models chosen.\n- It is tough for me to understand the equations.\nAmmoxidation-based isotopic model for global N2O estimation\n- Terms like ammoxidation, nitrate pool, and Redfield ratio\n- Complex equations\n- Why XGBoost algorithm?\n- purpose of ammonia oxidation model for N2O estimation\nAnd additionally my specific comments:\nL72 be precise with quantitative terms: N2O or N2O concentration, point of oxygen or amount of dissolved oxygen, it should be: highest N2O concentration at the lowest amount of dissolved oxygen\nL84 stable proportionality of 2.58? Do you mean the significant correlation with slope of 2.58? Why should this confirm N2O consumption? Could this relationship be a result of mixing between 2 sources? Rather the changes in SP value and its correlations prove the reduction progress (eg. Lewicka-Szczebak et al., 2014)\nL87 isotopic composition of what? N2O? How, when in the previous sentence you say that this zone ensures complete denitrification – if so, then we should find no N2O in the ODZ zone? So how you can know its isotopic composition? Or did you measure other compounds?\nL110 how the pathways contributions were determined, this is not trivial, you should shortly explained how it was done\nL112 what is scenario 1?\nL115 the contribution of denitrification (in what? Eg. Ocean N2O production?))\nL121 – So, the results provided in previous paragraph were not calculated with this model, so how? It is absolutely mysterious what you mean with the 2 scenarios\nL123 – I wonder why your model bases on SP values only, whereas other isotopes can also be applied for distinguishing processes. Ready models exist for performing calculations (based on Bayesian statistics) integrating all 3 N2O isotope values and also taking reduction into account – the FRAME model https://malewick.github.io/frame/ (Lewicka-Szczebak et al., 2020, Lewicki et al., 2022).\nL124 – not clear what are the “further distinguishing the N2O production pathways” – even when looking into your supplementary figures, it is not clear what has been done\nL124 and later – I really wonder how did you distinguish AOA and AOB, they do not significantly differ in isotope signature of N2O, do they? After reading methods and supplements – I still do not know how you have done this!\nL 277-279 – “the degree of N2O reduction in the source parts of oceans was quantified using δ15NSP/δ18O map method” – how does this method work? why there is no citation on the source or description of this method? Degree of N2O reduction – do you mean reduced or unreduced fraction of N2O?– we call this rather product ratio or progress of N2O reduction or reduced N2O fraction\nL 301 what is “original isotope source signatures of N2O (δi, original)”? From the previous paragraph I understand that you have corrected the isotope values of source processes with substrates?\nSupplement: Autotrophic denitrification enrichment and N2O source partitioning – here you present very interesting and important data for isotope characteristics of autotrophic denitrification. I think this dataset alone deserves a separate paper! It is important to publish separately that people can find these important data, why to hide this in the supplement, which few people will really discover.\nTo sum up, I think this could be a very valuable and important manuscript but not in this g=form, since it is impossible to follow. I suppose you were under pressure of shorten your message to the requirements of nature article, but in this form your really complex approaches lose their strength and significance. I would like to encourage you to write a long and extensive manuscript on this for another journal without length restriction.\n(Remarks on code availability)\nI looked at the code but I am not able to follow everything. There is no description of what the code does and how and it is impossible for me to check if the code is right.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "General comments\nThis paper reports detailed estimates of oceanic N2O flux and relative contributions of biological N2O production processes using published data of N2O isotope ratios, basic physical and chemical oceanic parameters, and a three-dimensional diffusion and reaction model. Because the ocean is one of the major sources of N2O, a potent greenhouse gas as well as a stratospheric ozone depleting gas, improving the estimates of N2O flux and understanding the key N2O production mechanisms would be beneficial in predicting future increases or decreases in N2O concentrations.\nThe strength of this paper is that the N2O flux was estimated with high spatial resolution using relatively basic parameters such as temperature, dissolved oxygen, particular organic nitrogen with the aid of N2O isotope ratios that provide a history of microbial production and consumption processes. The model-predicted N2O flux well reproduces spatial gradient found by observations.\nHowever, this paper has several shortcomings. First, the developed method for calculating the N2O flux depends on source partitioning based on isotopic measurements that cover only a few specific regions in the global ocean. For example, the authors used isotopic data from only eastern parts of the North and South Pacific. I think there have been several reports on other parts of the Pacific. Although the authors argue that relative contribution of nitrification and DO at the “source-sink” boundary has a linear relationship, it is not necessarily proven by the data presented in Figure S20. I think examination of more data from other regions are necessary.\nSecond, the authors’ assumption that N2O dissolved in the depths shallower than the “source-sink” boundary is a simple mixture of two components, N2O of atmospheric origin and that produced near the boundary, is a crude one that ignores detailed analysis of previous studies. For example, Kelly et al. (2021) identified two sources between the surface and the near-surface N2O maximum in their Keeling plot analysis of isotopic data obtained in the ETNP results. Toyoda et al. (2002) also noted that there are two different N2O sources between the surface and N2O maximum in the western North Pacific, although the latter work is not referred in the present manuscript. In addition to these points, I have a concern that previous efforts on observations and interpretation of oceanic N2O are not fully acknowledged in this manuscript.\nThird, it is not clear whether the authors assume the occurrence of N2O reduction even in the shallower seawater above the “source-sink” boundary. I was not able to understand why they uniformly used rN2O = 0.72 to estimate isotopic signature of N2O produced by microbial processes even though they seem to define the upper layer as source region.\nFourth, uncertainty of the estimated contributions from each microbial process is not shown, and explanation of the isotope-based source partitioning procedure is missing both in text and supporting materials. I cannot evaluate the accuracy of the estimation.\nIn summary, I do not recommend the publication of this paper in its present form. I encourage the authors to address the issue above and specific points below.\nSpecific comments\nL37 & 62. I cannot understand how “oxygen is stratified”, although seawater can be stratified because of its density.\nL41–45. It seems that the authors consider N2O in the deep waters below the mixed layer diffuses upward and is eventually emitted to the atmosphere. It is difficult to detect such a process within the typical time scale of the surface measurements. If ocean stratification is increased, vertical diffusion would be further suppressed. It would be better to clarify the time scale considered in this study.\nL47. I think refs #10 & #11 used N2O isotopes, not “semiempirical equations of nitrification and denitrification”.\nL52–54. The cited references reported the potential significance of autotrophic denitrification in the limited oceanic region such as coastal sea floor and the Black Sea, which are hardly considered in the present study.\nL58–62. This statement could be misleading as if the authors had made the field work and research. Cite appropriate studies, and briefly review the knowledge obtained by them. Also, as far as I know, no study reported isotopic signatures of N2O produced by ADN.\nL63. Did the authors use only d15NSP values out of the three isotope parameters? Describe the details of the model.\nL65. It seems that the authors use “ammoxidation” as a contradiction of ammonia oxidation. I think this term is not always in common use. Define it at the first use. Also, replace “stoichiometric” with other appropriate word. As described by the authors elsewhere, amount of microbially produced N2O is often variable and is difficult to predict using stoichiometry.\nL67 & 202. Citation is needed for the data set.\nL71–72. This has been pointed out repeatedly by the previous studies.\nL72–73. I think this statement is appropriate only when a certain time scale is considered. It is possible that N2O in the layer below the “source-sink” boundary could be ultimately released to the atmosphere by the global thermohaline circulation of deep water as speculated by Toyoda et al. (2019).\nL79. Where is “the Northern Ocean”?\nL80–82. Even above the oxycline, N2O can be produced by nitrification in the bottom of euphotic layer, and was suggested as a potential source to the atmosphere (Popp et al., 2002).\nL84–86. The quantitative relationship between d18O and d15N of N2O in the anaerobic seawater has been already reported by Yamagishi et al. (2007).\nL136–139. Without detailed information on the source-partitioning procedure and in situ reduced sulfur concentrations, I cannot believe the contribution of ADN as high as 13%. Did the authors test the calculation excluding ADN? I think a different solution can be obtained with mixing of four endmembers (AOA, AOB, HDN, and NDN).\nL162–164. Citation is needed.\nL201–202. Don’t the authors consider the seasonal variation in the N2O flux? I think most of the observational data were obtained at specific date/month/year. Seasonal variation has been suggested by studies based on data synthesis (Yang et al., 2020) and observation (Toyoda et al., 2023).\nL223–225. This has been pointed out repeatedly by the previous studies.\nL239. This holds under several assumptions as discussed by the previous studies.\nL244–247. Cite appropriate references.\nL277–279. Explain in detail. Did the authors use constant value for rN2O? Why?\nL290. Explain the abbreviation at its first appearance.\nL314. What do the authors mean by “concentration of the isotope”? Is it the isotope ratio?\nL333–334. Didn’t the authors account for assimilation of ammonia by primary producers?\nSupplement\nL99. Where were the water and sediment collected?\nTable S1. The epsilon and d15NSP values for ADN are different from those presented in L116. Explain the reason.\nTable S2. Show uncertainty of the contributions.\nL148. Is the “external input” of NH4 is included in the first term of the righthand side of the equation? If so, why it can be expressed by diffusion?\nL149, 150, & 151. The sign of the second terms in the righthand side of the equations should be “+” because these express production of NO2/NO3/N2.\nFigure S22. Cite the references used to create “observed” map. It is not clear what the “quantile” means. Was the distribution of the data with respect to their N2O concentration/flux divided into 10 groups?\nReferences (those already cited in the main text or supplement by the authors are omitted)\nToyoda, S., Yoshida, N., Miwa, T., Matsui, Y., Yamagishi, H., Tsunogai, U., et al. (2002). Production mechanism and global budget of N2O inferred from its isotopomers in the western North Pacific. Geophysical Research Letters, 29(3), 7–1–7–4. https://doi.org/10.1029/2001GL014311\nToyoda, S., Terajima, K., Yoshida, N., Yoshikawa, C., Makabe, A., Hashihama, F., et al. (2023). Extensive Accumulation of Nitrous Oxide in the Oxygen Minimum Zone in the Bay of Bengal. Global Biogeochemical Cycles, 37(9), e2022GB007689. https://doi.org/10.1029/2022gb007689\nPopp, B. N., Westley, M. B., Toyoda, S., Miwa, T., Dore, J. E., Yoshida, N., et al. (2002). Nitrogen and oxygen isotopomeric constraints on the origins and sea-to-air flux of N2O in the oligotrophic subtropical North Pacific gyre. Global Biogeochemical Cycles, 16(4), 1064. https://doi.org/10.1029/2001GB001806\n(Remarks on code availability)\nThe code does not provide a README file. I was not able to fully understand what's going on. In addition, as I pointed out in my report, the provided code includes the procedure for calculating ammonia oxidation rate, and not the one for calculating source contributions of N2O.", "reviewer_1_attached": "39 Reviewer 1\n2\n41 data of several ocean profiles including geochemical data and N O isotopocules. The\n2\n42 approach is innovative and tries to apply most up-to-date interpretation strategies to\n43 determine the special distribution of ocean N O flux and to identify and quantify the microbial\n2\n2\n45 my opinion the results evaluation and presentation is not acceptable. The calculation methods\n46 applied cannot be verified due to lack of proper description, it is not clear how the authors\n47 came to most of their results.\n49 expertise – N O modelling, which I cannot follow in many points, although I am working with\n2\n50 such modelling and the applied approaches should be perfectly clear to me. And unfortunately,\n51 they are not. It can be due to improper application of these methods or due to minimal\n52 description of the applied calculations. I understand it might have been forced by the\n53 requirements of this journal, but then I think it is not the proper journal to describe such a\n54 complex combination of approaches. I think you should choose a journal with unlimited\n55 length of articles, and where method can be described before results. In the current form your\n56 manuscript reads very difficult, because you use a few of advanced evaluation methods which\n57 are not introduced but discussed and the reader is quickly lost. I think it shouldn’t be\n58 published this way.\n60 if you have to keep it short you have to be precise, especially about methods you are using.\n62 working, eg. For your isotope map approach, mentioned in Scenario 1 you do not even cite\n63 the source paper of this. In Scenario 2 you try to make the multi-isotope mixing applying the\n2\n65 have also been trying to work with this approach, unsuccessfully, because you cannot really\n66 compute fractionation process with this model. This is why we have developed another tool\n67 where you can simultaneously calculate mixing proportions and fractionation processes\n68 (Lewicki et al., 2022). This is an easy-to-use software, which even do not require any\n69 programming skills: https://malewick.github.io/frame/. Applying this tool would save you a lot\n70 of inconsistencies in your descriptions, especially with the case of N O reduction, which I\n2\n71 really do not understand how you have determined, why you apply the mean value of 0.72, if\n72 you assume it is stable for all the data points you use."}, "author_response": "Answer: Thanks for your valuable comments. We are sorry for failing to provide a comprehensive description of the methods and calculation process. Now we have applied the software FRAME provided by your team to reconstruct our model with the objective of quantifying the microbial sources and reduction degree of N O. Furthermore, we have also established the empirical formula of the the fraction of residual unreduced N O (r ) and the boundary DO. We offered the detailed and step-by-step calculation processes in the Supplementary materials. Overall, we have revised the manuscript carefully to clarify the methods and calculation process of our manuscript. We provided detailed, point-by-point responses to the comments in the following pages, and we cordially invite you to delve into the revised manuscript and the detailed responses provided below.\n(1). Scenario 1 – lots of important information are missing on how the calculations were done – it is not possible to follow or check your calculations: which values you accepted as typical for nitrification and denitrification? Why these values? Citations needed! What is the map method? Where is this from – citation needed! How can you calculate r with map method? Why do you adopt 0.72? Do you expect that this reduction value will be quite stable across all the different sites you are recalculating?\nAnswer: Thanks for your comments. Sorry for the missing information and unclear calculations. We've revised Scenario1 as suggested by the third Reviewer, and no longer use the mapping approach. In scenario1, the contributions from the four major processes, ammonia-oxidizing by archaea (AOA), ammonia-oxidizing by bacteria (AOB), nitrifier denitrification (NDN) and heterotrophic denitrification (HDN) to N O production, and the degree of N O reduction were analyzed using the Monte Carlo modelling tool FRAME (Lewicki et al., 2022).\nTaking the samples MS1-MS9 as an example, the detailed and step-by-step calculations are as follows (Supplementary materials L163-L203):\n1. For the samples MS1-MS9 (Figure S2), the source‒sink boundary of N O was first confirmed at the lowest point of oxygen. Then the boundary DO for each sampling site was obtained (Table S3).\nFigure S2. Geochemical profiles of oxygen (μM), N O (nM), δ15NBulk (%), δ18O(%) and δ15NSP(%) of N O at MS1‒MS9 stations from the Eastern Tropical North Pacific (Kelly et al., 2021). The ODZs were divided into a mixed layer (ML, DO > 200 μM), upper oxycline (UO), ODZ core (OC) and lower oxycline (LO), in which ML and UO were identified as the source part.\n2. Keeling plot was applied to avoid bias derived from atmosphere-water exchange and obtain the microbial isotopic signatures of N O (Figure S12).\nFigure S12. Keeling plot analysis of N O sources from the source part was performed for the stations from the Eastern Tropical North Pacific (Kelly et al., 2021). Linear regressions of δ15Nbulk, δ18O, and δ15NSP vs. 1/[N O] are shown with solid lines.\n3. For source partitioning, the literature endmember values ε15NBulk, ε18O and δ15NSP are given in Table S1. Based on the actual isotopic signatures of the substrate (Table S2), the input source values are corrected with the actually measured precursor values, δ = ε + δ . The data and citations are as follows.\nN2O_endmember N2O/precursor actual precursor\nTable S1 Summary of mixing endmember isotopic signatures of particular pathways.\nLiterature endmember values δ\nactual precursor\nProcess ε15NBulk (‰) ε18O (‰) δ15NSP (‰) δ15N (‰) δ18O (‰)\nAOA(Santoro et al., 2011) 6.2 ± 1.5 32.1 ± 1.9 30.3 ± 1.2 δ15N-PON + ε\nminer.\nAOB(Sutka et al., 2006) -46.5 ± 0.4 23.5 ± 1.3 31.4 ± 4.2 δ15N-PON + ε\nminer.\nNDN(Frame and Casciotti, -56.9 ± 3.8 8.4 ± 1.4 -10.7 ± 2.9 δ15N-PON + ε δ18O-H O\n2010) miner. 2\nHDN(Lewicka-Szczebak et -15.7 ± 4.9 44.1 ± 6.1 -5.1 ± 1.8 δ15N-NO - δ18O-H O\nal., 2020; Toyoda et al., 2005) 3 2\nADN -14.8 ± 3.0 52.5 ± 2.0 7.2 ± 0.2 δ15N-NO - δ18O-H O\n3 2\nTable S2. The isotopic signatures of the substrate.\nRegions δ15N-PON (‰) δ15N-NO - (‰) δ18O-H O (‰)\n3 2\nEastern Tropical North 4(Buchanan et al., 9.6(Kelly et al., 2021) 0(LeGrande and Schmidt, 2006)\nPacific(Kelly et al., 2021) 2021)\nEastern Tropical North 2.5(Buchanan et al., 11.85(Monreal et al., 0.1(LeGrande and Schmidt,\nPacific(Monreal et al., 2022) 2021) 2022) 2006)\nEastern Tropical South 4.5(Buchanan et al., 12.44(Casciotti et al., 0.5(LeGrande and Schmidt,\nPacific(Casciotti et al., 2018) 2021) 2018) 2006)\nGulf of California (Yamagishi 2.5(Buchanan et al., 7.5(Yamagishi et al., 0(LeGrande and Schmidt, 2006)\net al., 2007) 2021) 2007)\nNamibian Upwelling 4(Buchanan et al., 0.7(LeGrande and Schmidt,\nZone(Frame et al., 2017) 2021) 13.99(Frame et al., 2017) 2006)\nEastern South Atlantic(Frame 3.5(Buchanan et al., 0.9(LeGrande and Schmidt,\net al., 2014) 2021) 8(Buchanan et al., 2021) 2006)\nCentral and Eastern South 5.5(Buchanan et al., 0.7(LeGrande and Schmidt,\nPacific Subtropical Gyre 7(Buchanan et al., 2021) 2021) 2006)\nSouthern Ocean(Boontanon et 1.5(Buchanan et al., -0.6(LeGrande and Schmidt,\nal., 2010) 2021) 4(Buchanan et al., 2021) 2006)\n4.5(Buchanan et al.,\nWestern Arctic Ocean 7(Buchanan et al., 2021) 1.4(Toyoda et al., 2021)\n2021)\nBay of Bengal(Toyoda et al., 2(Buchanan et al.,\n2023) 2021) 6.35(Toyoda et al., 2023) -0.05(Toyoda et al., 2023)\n4. The isotopic N O values obtained from Keeling plot, the corrected isotope signatures of the microbial sources (δ ), and the isotopocule fractionation constants (i.e., ε : -15.4±4.7, ε : -7.1±2.1, and ε : -5.9±1.4) was input into the model FRAME (Figure S22).\nFigure S22. The input values for the source partitioning of sampling points MS1-MS9.\n5. Run the model, get the quantified microbial sources and the fraction of residual unreduced N O (r ) for each sampling points (Figure S23, Table S3).\nFigure S23. The quantified microbial sources (HDN, NDN, AOB and AOA) and the fraction of residual unreduced N O (r ) for the sampling points MS1-MS9 in scenario1.\nThe remaining sampling points for scenario 1 and scenario 2 are calculated in the same way as above. The final results for the two scenarios in terms of the boundary DO, quantified microbial sources (f , n = HDN, NDN, AOB, AOA) and the fraction of residual unreduced N O (r ) are listed in Table S3. Based on the isotope results (Table S3), the correlations between f /r and boundary DO were obtained (Figure S24-S25). The empirical formula between the fraction of residual unreduced N O (r ) and the boundary DO was established and r is not stable across different sites.\nFigure S24. a-d, The correlation between the quantified microbial sources (AOA, AOB, HDN, NDN) and boundary DO; e, The correlation between the fraction of residual unreduced N O (r ) and boundary DO.\nFigure S25. Scenario2, a-e, The correlation between the quantified microbial sources (AOA, AOB, HDN, NDN, and ADN) and boundary DO; e, The correlation between the fraction of residual unreduced N O (r ) and boundary DO.\n(2). Scenario 2 - It is not explained how you did the corrections of isotope values with the substrates. It is confusing if you have corrected N O values or the characteristic signatures of the processes. How the O values were corrected, which assumption on O-exchange with water and incorporation of O were accepted – it is very complex and cannot be omitted. Did you ignore N O reduction in scenario 2? I think your equation (11) and (12) are wrong, why suddenly r appears there? It is not explained at all.\nAnswer: Thanks for your comments. As δ15NBulk and δ18O are dependent on the substrates, we adopted corrected isotopic values to avoid bias from precursor substances(Lewicka-Szczebak et al., 2020; Lewicki et al., 2022; Wu et al., 2019). The precursor isotopic signatures (δ15N-PON, δ15N-NO -, and δ18O-H O) were taken into account in FRAME (Liang et al., 2022; Wang et al., 2024b). Because it is rare to obtain the isotopic values of NH + due to its low concentrations in oceans, the nitrogen isotope of particulate organic nitrogen (PON) minus the isotope effect (ε , approximately -1‰) was used as the background isotope value of ammonia(Yoshikawa et al., 2016). The ε15NBulk, ε18O and δ15NSP values of N O for each process and substrates of N O (PON, NO − , or H O) were found in the literature (Table S1-S2). The literature endmember values are given as isotope effects (ε15NBulk, ε18O), ε = δ − δ . The input endmember values are corrected with the actually measured precursor values, δ = ε + δ . Specifically, the corrected δ15NBulk (‰) endmember values for AOA, AOB and NDN depend on the value of δ15N-PON + ε , whereas δ15NBulk (‰) for HDN, ADN depends on the value of δ15N-NO -. The δ18O endmember values for HDN, ADN and NDN depend on the δ18O-H O. The actual isotopic signatures of the substrate in each region are summarized in Table S2. (Line312-329)\nSimilar to previous literatures (Chen et al., 2023; Lewicka-Szczebak et al., 2020; Liang et al., 2022), oxygen isotope values of O 2 were not considered, thus we only consider the δ18O-H 2 O (‰) in this paper. As for the calculation process and fraction of residual unreduced N 2 O (r ) in scenario 2, they are the same with the above examples of MS1-MS9. The final results for extrapolation are illustrated in the Table S3 and Figure S25.\nAs for the equation (11) and (12): To obtain the global N 2 O flux at annual scale (Tg N 2 O-N/yr), we first calculated the N 2 O emissions by AOA (N 2 O AOA ) in each grid on the basis of the ammoxidation flux (ammonia oxidation amount in a year scale), N O yield during ammoxidation (N O-N/NH +-N), and the fraction of residual unreduced N O (r ). The total N O flux was then obtained according to its proportion to total production in each grid (e.g., N O /f ). (L178-182) By calculating the total production and consumption of N O in a year, the difference is the final emission. That why r appears here."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The manuscript has been vastly improved. As suggested, authors have now applied the most novel tool for N2O isotope modelling for calculating the N2O sources proportions and taking into account its reduction, which can be variable – this is definitely confirmed by the currently obtained results! I think now the data is evaluated in the proper way and the description of the applied methodology is very simplified, since it builds on the previously developed modelling tool FRAME.\nAuthors provided very extended responses to all the reviewers comments and included the suggestions, which made the manuscript much more clear and better organised.\nI think in the current form the manuscript deserves publication after minor corrections.\nI only have a few minor comments:\n304 – „it IS worth noting” or rather: Importantly, Noteworthy,\n312 – exchange of O-isotopes\n342 - „it IS worth noting” or rather: Importantly, Noteworthy,\nSupplementary materials Chapter 4 title - I would say “isotope effect associated with autotrophic denitrification” instead of “enrichment”\nThe nice feature of FRAME model is the determination of uncertainties of the obtained results - they can be seen on the graphs as you presented in Fig. S23, but you only show these for Scenario 1. I wonder how it looks like for Scenario 2 – because I suppose the assumption for the model with 5 sources and the fractionation process are really on the limit of model capabilities, so probably the distinction between particular processes may be rather poor and the uncertainties become large. Please provide also similar graphs for your scenario 2 in the supplementary materials. It would be also good to give information in the manuscript on the uncertainties of your modelled results – you may give general mean values – what is the SD of the provided contributions of the analysed processes, and indicate that the uncertainties are presented in the supplement.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "General comments\nThe authors have made substantial efforts to address criticisms raised by me and other reviewers. I admit that some of my concerns are now clarified, but still other points are not satisfactorily addressed. Also, I would like to add some extra comments below, after reading authors’ reply to other reviewers.\n(1) Although I suggested the authors to examine more published data, they only added the results from a single paper on the Bay of Bengal. They excuse that the raw data was not available, but it is not clear whether they made efforts such as asking the authors of other papers to provide them with the data set.\n(2) I am afraid that the first half of my major comment (2) was not well understood by the authors. Although it might be overlooked because only data from upper layer are plotted in Figure S12, for example, the data points marked with green broken circles (see attached file) suggest existence of another source (see Fig. 4 in Kelly et al. 2021). I think the authors should consider such multiple sources separately and which one mainly contribute to the emission to the atmosphere.\n(3) I strongly agree with the last two comments by the reviewer #2. As I noted below, ADN is not relevant to the present study. The novel experimental results on this process should be published elsewhere. Excluding this part, present work consists of compilation of literature data, application of existing isotope-analyzing model, and originally developed biogeochemical model of ammonia oxidation. This may fit to the publication in other journal.\nSpecific comments\nL127–131. To my eyes, linear relationship is significant only for AOA and AOB in Figures S24 and S25. Also, it is very strange that the r value is as low as 20% even in the well oxygenated water (DO >250uM, panel e/f in Figure S24/S25). This means 80% of the produced N2O is reduced to N2. I would like to know why the authors accepted this calculation results and fitted the relation between r and boundary DO with parabola function.\nL137–139. Do the authors consider AOA is not inhibited by the light? If so, please show reference or evidence.\nL153–155. I carefully read the cited papers (Canfield et al. 2010 and Dalsgaard et al., 2013) and confirmed that ADN has been detected only in anoxic water (O2 ~ 0 uM), which corresponds to ODZ core in the present study. Because the authors assume O2 minimum layer (upper edge of ODZ) is the boundary between source and sink and estimated the endmember value near the boundary, they should not include this processes as a potential source to the atmosphere.\nTable S1. Epsilon values are not “endmember values” but fractionation constants (or enrichment factor), although SP can be regarded as endmember value.\nL220–222. These equations are not consistent with the explanation in “Readme-for view in docx.pdf”."}, "author_response": "We thank all reviewers very much for their both positive or constructive comments. These professional and insightful comments are instrumental in disseminating our findings to a broader scientific community. We have made all suggested corrections according to reviewers’ comments. In the revised manuscript, Scenario 2 has been deleted according to the suggestions of the latter two reviewers. Additionally, we have addressed other minor points carefully and revised the manuscript accordingly. We provide detailed, point-by-point responses to the reviewers’ comments in the following pages.\nPlease note that the reviewers’ comments are presented in italics, and our responses are in Roman and blue font. All changes made to the manuscript accordingly are marked in red font in the revised manuscript. Please let me know if you have any further questions.\nThank you for your consideration."}, {"round": 3, "reviewer_comments": {"reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "General comments\nThe authors have made additional efforts to improve the manuscript. Now I am satisfied with the revision except following points. I respect their successive efforts and expect further progress of this research.\n(1) I understand that the authors would like to treat N2O production processes existing in the mixed layer and upper oxycline as a single end member, even if there are observational evidences that indicate multiple sources. Then, I strongly recommend them to revise the sentence in “Keeling plot analyses” section to reserve this issue, for example in L265–267: It assumes that the measured isotopic signature is a mixture of background atmosphere values and the microbial additions (Equations 1-3), if the N2O produced by the microbial processes have a constant signature throughout the water column of interest. Under this assumption of simple two-end member mixing, the isotopic composition of microbially produced N2O is represented as the y-intercept value in the source part (Figures S13–S22).\nAlso, I note the sentence following the above sentences must be corrected:\nIt is worth noting …\n(2) The authors explain that the data with low r values (~20%) at high DO (> 250 uM) in Figure S25 came from the Arctic Ocean and the Southern Ocean and argue that N2O can be reduced in these high-latitude marine areas. However, these data points correspond to shallow sea with depth of less than 100 m or coastal station instead of open ocean. As discussed in Toyoda et al., 2021, N2O reduction may occur in the sediments, not in the oxic water column, at these sites. Therefore, the sentences in L166–168 should be better revised as follows:\nHowever, the data obtained in the shallow Arctic Ocean and off the coast of Antarctica gave r values as low as 20% in N2O spite of high boundary DO (Fig. S25e). This implies that a significant portion of the N2O produced in situ or diffused from the atmosphere is reduced by denitrification in sediments (Toyoda et al., 2021)."}, "author_response": "We thank all reviewers very much for their positive comments. We have addressed these minor points carefully and provided detailed, point-by-point responses to the reviewers’ comments in the following pages. Please note that the reviewers’ comments are presented in italics, and our responses are in Roman and blue font. All changes made to the manuscript accordingly are marked in red font in the revised manuscript.\nPlease let me know if you have any further questions.\nThank you for your consideration."}]

Decision letter