Site-specific water column profiles and underway pCO 2 data

A standard conductivity–temperature–depth rosette (24 Niskin (20 litres) and full Sea-Bird 24 electronics (salinity, density, O 2 , temperature and so on) was used to collect and characterize the water at each site between 5 and 4,000 m. The distribution of N 2 O, CO 2 and NO 2 − was measured as described previously4, except that the GC also had a hot-nickel catalyst and flame-ionization detector to quantify CO 2 after rapid equilibration and reduction to CH 4 (ref. 39). High temporal resolution measurements of pCO 2 in surface seawater and atmosphere were also made every 5 min using an underway instrument (see below).

Production of N 2 O as a function of oxygen and gene abundance

We measured the production of 15N-N 2 O at two depths, both within and beneath the oxycline, at each of the six sites (Supplementary Table 1). Seawater was drained from a Niskin into 4 litre Nalgene bottles and sparged for 20 min to generate six oxygen treatments (Table 1). Seawater was then dispensed under pressure into 4 × 1 litre clear glass moulded infusion vials (Laboratory Precision Limited), except for the Ambient treatments, which went directly into the 1 litre vials. Oxygen (50 μm calibrated electrode, Unisense) and temperature were measured and, following up on studies in the Arabian Sea4, the vials spiked with 15N-NO 2 − ([10 μM], 98 atom%, Sigma, see Supplementary Table 1 for 15N atom % in each of the 12 sets of experiments). It is important to appreciate that all published work to date that uses 15N to trace the production of either N 2 O or N 2 applies a ‘tracer’ at concentrations in excess of apparent K m values for these processes, that is, typically 5–10 μmol NO 2 − l−1 spike, compared with 1–2 μmol NO 2 − l−1 k m and, as such, should be considered as potentials6,34,40. The vials were then sealed and incubated in the dark, at 12 °C, for 72 h as previously4. Later, bacterial activity was stopped in three of the vials by the addition of 6 ml formaldehyde (36% v/v), while the fourth vial was used to measure oxygen and the water then filtered (Supor, ø=47 mm, 0.2 μm pore size filters). The filters were immediately frozen in 2 ml cryovials, in liquid nitrogen, and stored at −80 °C for later extraction of nucleic acids (see below). Production of 15N 2 O and 15N 2 was measured in the three remaining vials against reference samples for each of the treatments, or natural abundance, by mass spectrometry (see below and Nicholls et al.4). The data for each triplicate were then averaged and the mean value compared with its corresponding, single measure of functional gene abundances. Genes targeted with a potential role in N 2 O production were: β- and γ-proteobacterial amoA; bacterial nirS, bacterial nirK, archaeal nirK, archaeal amoA (here AamoA) and, in addition, general bacterial and archaeal Marine Group I 16S rRNA genes (see Supplementary Table 4 for primer sets). A combination of the large 1 litre glass vials and multiple oxygen treatments precluded a full time series incubation in each of the 12 N 2 O experiments (1,400 bottles versus 280). We did, however, measure N 2 O production at 2, 4, 9, 18, 36 and 72 h at two sites, for two oxygen treatments during a subsequent cruise to check that our single time point incubation was not overestimating production.

Mass spectrometry for 15N 2 O and 15N 2 and rate calculations

All the samples were transferred under constant temperature back to the home laboratory in London and were brought to 22 °C before processing. Two subsamples of the 1 litre vials were forced out under helium and transferred to either a helium-filled 12 ml gas-tight vial (Exetainer, Labco), for 15N 2 analysis, or a helium-filled 20 ml gas-tight vial (Gerstel and 20 mm butyl rubber stoppers and aluminium seals, Grace—Alltech) for 15N 2 O analysis. The 20 ml vials ended up with 10 ml of seawater and 10 ml of helium headspace to which we added a carrier of 3 nmol N 2 O, as sparging with the compressed air, N 2 and O 2 treatments effectively removed all of the natural N 2 O from the samples. These were then analysed for enrichment of both single- and dual-labelled 45N 2 O and 46N 2 O, respectively, against seawater samples (collected on the cruise) sparged with the five treatment gases, or, in the case of the ambient treatment, reference samples of seawater, using a trace gas pre-concentrator unit (PreCon, Thermo-Finnigan)4. Calibration was performed against known amounts of N 2 O (98 p.p.m.; BOC), and it was linear (r2=0.998) over the range 0 to 20.72 nmol N 2 O absolute (∑44N 2 O, 45N 2 O and 46N 2 O).

After bringing the remaining 12 ml gas-tight vials to 22 °C, a helium headspace (1 ml) was added and the vials shaken by hand and left overnight on rollers (Spiramix) to allow N 2 gas to equilibrate between the water phase and headspace. Samples of the headspace (100 μl) were then analysed for enrichment in 15N 2 by injection (Multipurpose Sampler MSP2, Gerstel) into an elemental analyzer (Flash EA 1112, Thermo-Finnigan), interfaced with the continuous flow isotope ratio mass spectrometer (CF-IRMS)4. Calibration was performed at the beginning of each run with known amounts of oxygen free nitrogen gas (BOC) in seawater collected on the cruise, in the range of 0 to 12.6 μmol N 2 absolute (∑28N 2 , 29N 2 and 30N 2 ). Values for the production of 29N 2 and/or 30N 2 were calculated as excess over the production in the time zero ‘reference’ samples41.

We used 15NO 2 − to trace the production of N 2 O as per our previous work in the Arabian Sea4 and present two principle methods for calculating the total production of N 2 O in response to oxygen. In the first method, given that the archaea appear to lack Nor, we assume that they cannot make N 2 O purely from exogenous NO 2 − and that any measured production of p46N 2 O (that is, 2 × 15NO 2 −) must be due to canonical denitrification reducing NO 2 − as far as N 2 O. Then, any production of N 2 O that we cannot account for by canonical denitrification with exogenous NO 2 − we assign to hybrid N 2 O formation, as in the most recent models for Thaumarchaeotal ammonia oxidation22. In the second method, we assume that all of the measured production of N 2 O is due to a classic bacterial-type mode of nitrifier–denitrification, with random isotope pairing of 14NO and 15NO upstream of the production of N 2 O.

We calculate the overall production of N 2 O that we assume to be owing to canonical denitrification of exogenous NO 2 − according to:

where FN NO2− is the fraction of 15N in the NO 2 − pool (Supplementary Table 1) in each set of incubations, determined by difference34, and we ignore any turnover by either ammonium or nitrite oxidation, which is shown to be negligible relative to the size of the NO 2 − pool (See the ‘Discussion’ section and Supplementary Table 2). We then used the measured amount of dual-labelled p46N 2 O to predict the expected amount of single-labelled p45N 2 O exp for canonical denitrification according to40:

We would then argue that any production of p45N 2 O above p45N 2 O exp cannot be solely due to reduction of external NO 2 −, and must be due to 15N pairing with an alternative source of 14N (for example, 15NO from 15NO 2 −, pairing with 14NH 2 OH in archaeal hybrid N 2 O formation22) which, for simplicity, we refer to as endogenous N 2 O:

The first estimate of total production of N 2 O in our incubations with 15NO 2 − is then the sum of the two former products:

Hence, the calculation of pN 2 O total , pN 2 O endogenous and pN 2 O exogenous with 15NO 2 − is synonymous to that for total N 2 , anammox and denitrification, respectively, in all other work measuring the production of N 2 ; though the biological context is not40. The alternative formulation assumes that all of our measured production of N 2 O was dominated by a classic bacterial-type mode of nitrifier–denitrification, with random isotope pairing of 14NO and 15NO upstream of the production of N 2 O (ref. 22) and we can calculate an alternative pN 2 O total ′ according to42:

Molecular analysis

In the home laboratory, each Supor filter was cut in half and one half was placed into a 2 ml sterile screw-cap tube, containing ø=0.1 mm glass beads. The following solutions were then added to each tube: 700 μl of 120 mmol l−1 sodium phosphate (pH 8.0) plus 1% (w/v) acid-washed polyvinylpolypyrrolidone, 500 μl of Tris-equilibrated phenol (pH 8.0), and 50 μl of 20% (w/v) sodium dodecyl sulfate. The extraction process involved bead beating and passing the samples through hydroxyapatite and Sephadex G-75 spin columns, to separate nucleic acids from proteins and salts43. Nucleic acids were resuspended in 50 μl of TE (10 mmol l−1 Tris, 1 mM EDTA [pH 8.0]) and stored at −80 °C.

The extracted DNA was used for quantification of functional genes (primer details are shown in Supplementary Table 4). Quantitative real-time PCR was performed in a Bio-Rad CFX96 Real-Time System. The reaction was performed in duplicate in a final volume of 15 μl, which contained 7.5 μl of SensiFAST SYBR No-ROX mix (2 × ) (Bioline), 200 nmol l−1 of each primer and 1 μl of 10 times diluted DNA. The conditions for all reactions were as follows: 95 °C for 3 min; 40 cycles of 95 °C for 0.05 min and 60 °C for 0.30 min; 95 °C for 0.05 min; 65 °C for 0.05 min and a final step of 95 °C for 0.5 min. Absolute quantification of the targeted genes was performed with a series of 10-fold standard dilutions, using the CFX Manager version 2.0 software (Bio-Rad). Standards for bacterial 16S rRNA, nirS and nosZ genes were derived from Pseudomonas brenneri DSM15294; environmental PCR products were used for bacterial amoA, AamoA, nirK, AnirK and MG1 16S. Samples with Cq values that were the same or greater than those of the no template controls were assumed to be below the limit of detection (LOD). In each of these cases, the calculated LOD for the particular qPCR plate was used as the value for that sample (maximum LOD=171 copies ml−1). Specificity of the AnirK PCR was assessed by sequencing product from a number of sites. All showed that the PCR assay was specific for its target gene (data not shown).

Nitrification

To account for any possible turnover of the 15NO 2 − pool in our 72 h 15N 2 O incubations, we incubated additional water under ambient oxygen (1 to 23 μmol O 2 l−1) from the second depth at each site (Supplementary Table 1). Water was sampled into 1 litre vials, allowed to overflow three times, sealed, brought to 12 °C and then, without any sparging, pushed out (2 mm Teflon tubing) under helium into the bottom of 12 ml, gas-tight vials (Exetainer, Labco), overflowed three times and sealed. The vials were then enriched from concentrated stocks (Sigma, sparged with OFN) to [10 μmol l−1], in quadruplets, with either 15NO 2 − or 15NH 4 +. Ammonia oxidation was estimated from the net accumulation of 15NO 2 − after the addition of 15NH 4 +, single time point incubations (96 h); nitrite oxidation from net accumulation of 15NO 3 − over 3, 6, 12, 24, 48 or 96 h from 15NO 2 − and overall net nitrification from the accumulation of total 15NO x − after 96 h from 15NH 4 +. The samples were fixed (50 μl 50% (w/v) ZnCl 2 ) and production of 15NO x −, 15NO 2 − or 15NO x − measured with a sulphamic acid assay at the University of Southern Denmark.

Modelling N 2 O production

We formulated a simple 1D model of N 2 O (1 m depth resolution), coded in R. The model is largely based on the parameterizations given by Babbin et al.5 encompassing physical processes (upwelling, vertical diffusion and implicit gas exchange of N 2 O) as well as biological production of N 2 O. Vertical transport was parameterized according to Fickian diffusion with a diffusivity K z of 4 × 10−4 m2 s−1 at the surface, decreasing linearly to 4 × 10−5 m2 s−1 at 10 m and remained constant thereafter apart from the pycnocline (20–48 m depth) where K z was 1 × 10−5 m2 s−1. This K z profile effectively simulated near surface turbulence while the remaining water column was dominated by diffusive processes. An upwelling velocity (w up ) of 8 × 10−7 m s−1 and a particle sinking velocity (of 1.2 × 10−4 m s−1 (ref. 5) were used.

The model resolved the upper 400 m of the water column at 1 m depth resolution and 1 min time intervals. Boundary conditions at the surface and at 400 m were fixed and prescribed by the respective averages from our profiles. This average profile also described initial conditions for NO 3 −, PO 4 3−, N 2 O and O 2 . Particulate Organic Carbon (POC) values for the ETNP were taken from the literature44,45, with a surface concentration of 3 μmol l−1, a sub-surface maximum of 5 μmol l−1 at 32 m and decreasing thereafter to 1.3 μmol l−1 at 400 m. Model POC remineralization (POC rem ) was parameterized as a first-order process with a rate constant of 5 × 10−7 s−1. POC production at the surface was implicit via the fixed boundary concentration as in Babbin et al.5 In addition, we parameterized POC production ( p POC Z ) at depth (Z) as a function of the upwelling NO 3 − flux and light attenuation:

where F is the ratio of upwelled NO 3 − used by primary producers (0.2), [NO 3 −] is the concentration of NO 3 − at depth Z, K d is the light attenuation coefficient (0.09 m−1) and r N:Cremin is the N:C ratio production/remineralization (r N:Cremin =16/106). The value of K d was chosen as it gave a subsurface p POC Z maximum which was consistent with the positions of the subsurface POC- and chlorophyll-concentration maxima at the base of the mixed layer as observed during our cruise. NO 3 −, PO 4 3− and O 2 were linked to POC production/remineralization according to Redfield stoichiometry, as in Babbin et al.5 O 2 consumption followed a respiratory ratio of ∼1.4 (r O:Crem =150:106).

Production to consumption of N 2 O was parameterized for two separate variants of the model: (i) according to Babbin et al.5 and (ii) as a function of O 2 concentration as described here. All processes except those producing N 2 O were identical in both the models. In our second variant, we parameterized model N 2 O production (pN 2 O in nmol m−3 d−1) using the estimates for a and b from our nonlinear mixed-effects models (M2 and M5, Table 2 and equation 12):

Note that the original Babbin formulation included an [O 2 ]-dependent Heaviside function which terminated N 2 O production when [O 2 ]<0.4 μmol L−1. Here, as oxygen was always above 0.4 μmol O 2 L−1 it was redundant and not included in our variant of the model.

Estimating N 2 O exchange using high-resolution pCO 2 data

High temporal resolution measurements of pCO 2 in surface seawater and atmosphere were made every 5 min using an underway instrument (PML Dartcom Live pCO 2 . UK.46,47) with the ‘vented’ equilibrator modification46. The equilibrator was fitted with two platinum resistance thermometers (Pico Technology, model PT100) and a water-jacket supplied with seawater from the ship’s underway seawater system. A seawater flow of 1.6 litres min−1 was maintained through the main equilibrator. The average warming between the ship’s underway seawater intake and the equilibrator was 0.2±0.1 °C. Atmospheric measurements of CO 2 were taken from an intake located on the foremast. Both gas streams from the equilibrator headspace and the air inlet were dried in a Peltier cooler (−20 °C). Mixing ratios of CO 2 and water in the marine air and equilibrator headspace were determined by non-dispersive infrared dection (LI-840, LI-COR). Measurements were referenced against secondary calibration gases (BOC Gases, UK) with known CO 2 mixing ratios (257.6, 373.4 and 463.5 μmol CO 2 per mole) in synthetic air mixtures (21% oxygen and 79% nitrogen). All calibration gases were calibrated against certified primary standards from the National Oceanic and Atmospheric Administration (244.9 and 444.4 μmol CO 2 per mole). The pCO 2 system described here showed high consistency with a similar pCO 2 system and pCO 2 calculated from independent TA, DIC and pH during ‘at sea’ inter-comparison48. Sampling was carried out continuously (every 5 min), with the exception of periods for maintenance. See Supplementary Fig. 7 for a summary of the pCO 2 and wind data and resultant efflux estimates.

Then, for the samples for which high-resolution seawater pCO 2 (pCO 2 sw) data were available but in which N 2 O was not directly quantified, we predicted molar seawater N 2 O concentrations (N 2 Osw) using the linear relationship between N 2 Osw and the molar seawater concentration of CO 2 (CO 2 sw; Supplementary Fig. 1). To do this, we first estimated the CO 2 and N 2 O solubility for each sample (mol kg−1 atm−1; refs 49, 50). CO 2 sw for each sample was next calculated as the product of its pCO 2 sw and corresponding molar solubility. Each resulting molar N 2 Osw concentration was then converted to pN 2 Osw by dividing it by the calculated, corresponding N 2 O molar solubility. Atmospheric pN 2 Oatm was taken as the average for samples collected from the bow of the ship throughout the ∼6 week cruise (348±6 natm s.e., n=35) and the corresponding N 2 O flux estimated from the high-resolution CO 2 fluxes calculated using the average 12 h wind speed:

Statistical analyses

All the analyses were conducted in R (ref. 32) following procedures largely described in ref. 51. We began with linear mixed-effects models treating oxygen as a categorical variable and modelling N 2 O production as an additive, linear function of the six oxygen treatments (Table 1). With the linear mixed-effects models, we fitted the oxygen treatment as a fixed effect and included random intercepts for each of the 12 experiments, comparing models with and without ‘oxygen’ with likelihood ratio testing. Given that there was clear spread within the oxygen data, we then used nonlinear mixed-effects models to model 15N 2 O production as a continual, exponential function of oxygen:

Where pN 2 O total comes from equations (1, 2, 3, 4, 5) and O 2 exp is the measured concentration of oxygen (μmol l−1) in each incubation bottle and total production of N 2 O is that measured in each bottle at the end of its incubation. For the 12 sets of experiments analysed using nonlinear mixed-effects models, we either fitted both the intercept (a, that is, maximum N 2 O production) and sensitivity (b, that is, response to oxygen) as random effects, or, a and b, each individually, and compared model fit in each case with the Akaike Information Criterion (AIC). Relationships between these ‘random’ elements, that is, variance not explained by experimental oxygen and other possible explanatory variables (for example, gene abundance) were explored visually (at the 12-experiment, group level, n=12) and then more rigorously using multiple regression and the entire, linearized and centred (x c ) data set (natural log, x c =x−x mean , n=70). Here, we judge the simplest model (that is, just oxygen) against more complex models (oxygen plus single or multiple functional gene abundance) also using likelihood ratio testing.

Data availability

The data that support the findings of this study are available from the authors on reasonable request, see author contributions for specific data sets.