SUPPLEMENTARY INFORMATIONDOI: 10.1038/NGEO1832

NATURE GEOSCIENCE | www.nature.com/naturegeoscience 1

Supplementary Information for

“The acceleration of oceanic denitrification during deglacial warming”

Galbraith, Kienast and the NICOPP Working Group.

Nitrogen isotopic fractionation in the oceanThere are two stable isotopes of N, 14N (which constitutes 99.63 % of N in the environment) and the rare isotope 15N (see ref. 1 for a review of nitrogen isotope systematics). Measurements of the stable isotope ratio are reported relative to atmospheric N2 using the notation δ15N = (( 15N/14Nsample / 15N/14Nair ) – 1 ) * 1000 ‰.

Field observations and laboratory experiments have shown that the δ15N of sinking organic matter differs from the δ15N of mean ocean nitrate (~5 ‰) due to two classes of fractionating processes 2. When included in the global ocean circulation model, each of the fractionating processes produces zones of high δ15N and zones of low δ15N, which can be referred to as ‘dipoles’.

The first dipole arises from the internal cycling of nitrogen within the ocean, due to fractionation during the growth of phytoplankton and redistribution of dissolved nitrogen by the large-scale ocean circulation. The light isotope is preferentially incorporated in phytoplankton biomass, leading to a 15N enrichment in the residual nitrate (with a typical fractionation factor, ε, of ~ 6 ‰ Refs. 3,4). This residual nitrate is then advected and mixed into neighbouring regions, according to the ocean circulation. Thus, plankton growing on nitrate directly upwelled from the deep ocean will tend to have low δ15N, while plankton growing downstream on residual nitrate have high δ15N.

The second dipole arises from inventory-altering processes, including the addition of Nbio to the ocean by N2 fixation and the removal of Nbio by denitrification. N2 fixation adds new nitrogen with a low isotopic signature (-1 ‰), while pelagic (i.e. water column) denitrification strongly fractionates during the production of N2, leaving residual nitrate that is greatly enriched in 15N. The enzyme-level isotope effect has generally been thought to be ~ 25 ‰, but recent culture work suggests that the expressed value εpelagic may be smaller than this5. Also, because pelagic denitrification occurs in small volumes of the ocean, a significant fraction of the enriched nitrate is consumed, further reducing the expressed isotope effect6,7. εpelagic may, in fact, vary significantly, if it depends on the role of the anammox pathway, or the degree of consumption within oxygen minimum zones6. However, for the analysis below, we assume that temporal variability of εpelagic over the deglaciation was negligible.

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Pelagic denitrification occurs in only three regions of the modern ocean: the Eastern Tropical North Pacific, Eastern Tropical South Pacific, and the Arabian Sea. Meanwhile, N2 fixation appears to occur throughout a broad swath of the low-latitude ocean 8.

Biogeochemical-circulation model simulationsWe used two different coupled ocean-biogeochemical models in order to examine some fundamental aspects of nitrogen isotope cycling in the ocean.

The first is the UVic model9, which is a 3-degree ocean model coupled to a 2-dimensional energy balance atmosphere. The Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD) ecosystem component contains a nitrogen cycle, simulating both internal cycling fractionation and inventory-altering processes. The standard simulation was integrated under pre-industrial conditions to a steady-state. The mean oceanic δ15N in the model is determined by the balance of pelagic vs. benthic denitrification, as discussed above, and was tuned to produce a value of ~5 ‰ by adjusting the amount of sediment denitrification10. It should be noted that, although the intrinsic fractionation factor for pelagic denitrification in the baseline version of the model is 25 ‰, it produced a relatively small effective fractionation (εpelagic, as defined in Figure 1) due to an erroneously large degree of nitrate consumption within the oxygen minimum zones. Modeled NO3 concentrations were as low as 5 mmol m-3, whereas observations do not show concentrations below 15 mmol m-3. The result of this small expressed εpelagic is that little benthic denitrification is required to satisfy the isotopic mass balance. As a result, the absolute magnitude of the pelagic denitrification signal may be underestimated, although the spatial distribution of it is likely to be reasonable.

The internal-cycling impact on δ15N (Figure 2c) was estimated by setting N2 fixation and denitrification to zero, and integrating the model to steady state with the same inventory of nitrogen. The inventory-altering impact on δ15N (Figure 2d) was estimated by setting the fractionation factors for N assimilation and excretion to zero, so that only N2 fixation and denitrification altered the N isotope ratios. Note that the model places the Indian Ocean denitrification zone in the Bay of Bengal, rather than the Arabian Sea, due to a common ocean model circulation bias; it is this bias that causes the δ15N to be too low in the Arabian Sea and too high in the Bay of Bengal. Note also that the model mean ocean δ15N-NO3 of 5.25 ‰ is predicted by the global balance of pelagic:benthic denitrification, and is the same for Figures 2b, c and d.

The second model is CM2Mc, a fully coupled ~3-degree ocean-atmosphere model with a simple biogeochemical module, ibgc11. The biogeochemistry module does not simulate N2 fixation or denitrification. However it does simulate the internal cycling of 14NO3 and 15NO3, with an uptake

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fractionation of 5 ‰, the same value as the UVic model. The simulated distribution of sinking δ15N is very similar to that simulated by the UVic model (Figure 2c), as shown in Figure S1.

Diagenetic enrichment of 15N in deep sea sedimentsIt has long been recognized that deep sea sediments are enriched in 15N relative to the expected supply of organic matter, whether estimated from local sinking particles or δ15NO3 (Refs. 3,12). Consistent with this expectation, the observed seafloor δ15N is generally higher than that predicted by the UVic ocean-biogeochemistry model (Fig. S2).

Furthermore, the model-data comparison is consistent with an enrichment of 15N that is correlated with water depth, as proposed by Ref. 12, as follows. The ocean-biogeochemistry model of Ref. 10 simulates approximately the correct global δ15NO3 (5.3 ‰). When the observed δ15N of seafloor sediments are interpolated onto the model grid and compared to the model output, there is a difference between the average model δ15N and the co-located observations of -2.0 ‰ (see Table S1). Increasing the model values as a function of local water depth reduces this model-obs. difference, while the correlation coefficient increases and the Root Mean Squared Error (RMSE) decreases. Together, these three metrics suggest an optimal correction of 0.75 ±0.25 ‰ (km water depth)-1. It is important to emphasize that this empirical relationship

3

Figure S1. Sinking δ15N as estimated by CM2Mc-ibgc, an independent ocean and biogeochemical model that simulates only internal cycling fractionation. As apparent from comparison with Figure 2c, the results are very similar to the UVic model.

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with water depth is indirectly accounting for mechanistic factors such as oxygen-exposure time or sediment characteristics, for which we have no direct information. In future, it would be preferable to obtain more direct means with which to quantify site-specific diagenetic alteration.

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Figure S2. Frequency distribution of sedimentary δ15N values at the seafloor and in the model. The overall higher seafloor values are consistent with isotopic alteration during the sinking and sedimentation of organic matter. Other discrepancies could be due to any combination of errors in the physical, biogeochemical, or isotopic components of the model.

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Average model-obs. r2 RMSE

no correction -2.0 ‰ 0.52 1.4 ‰

0.25 ‰ km-1 -1.3 ‰ 0.55 1.3 ‰

0.5 ‰ km-1 -0.6 ‰ 0.57 1.2 ‰

0.75 ‰ km-1 0.1 ‰ 0.58 1.2 ‰

1.0 ‰ km-1 0.8 ‰ 0.59 1.3 ‰

1.25 ‰ km-1 1.5 ‰ 0.59 1.5 ‰

Nitrogen isotopic provincesThe nitrogen isotopic provinces were created by generating masks of the ocean surface from thresholds of export flux and surface nitrate concentrations. These were combined as required, or subdivided where sufficient data density allowed, according to a) fronts observed in seafloor δ15N or b) where pelagic denitrification occurs today (Figure S3). High data density allowed

Table S1. Comparison between the observed seafloor δ15N and the co-located model estimate of sinking δ15N. The model-observation agreement is most improved when the model values are increased by ~0.75 ‰ km-1 water depth.

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0 50 100 150 200 250 300 350

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78 9

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Figure S3. δ15N provinces. Coloured circles indicate seafloor δ15N measurements in ‰. The numbered shaded regions correspond to the provinces in Table S2.

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smaller provinces to be defined in some areas (e.g. Arabian Sea) than others (e.g. North Atlantic). Further subdivision of the larger provinces will likely be desirable in future, when more data are available. The export flux field was calculated from SeaWiFS chlorophyll data, using the algorithms described in Ref. 13. The provinces are listed in table S2.

Province fraction of global export

seafloor mean δ15N

seafloor s.d. downcore n

1 0.062 5.0 1.3 3

2 0.026 6.2 1.7 3

3 0.056 8.0 1.3 9

4 0.011 7.3 1.7 4

5 0.055 3.9 0.8 8

6 0.031 6.5 2.8 3

7 0.021 5.9 0.8 1

8 0.146 4.8 1.0 6

9 0.027 7.8 1.8 10

10 0.015 6.6 1.1 3

11 0.049 5.0 1.6 13

12 0.033 8.7 2.2 4

13 0.032 3.9 0.9 4

14 0.129 4.3 1.7 1

15 0.198 4.9 1.9 2

16 0.109 2.8 1.1 2

Table S2. δ15N provinces. Fraction of global export production within each province, as estimated from satellite data; the mean and standard deviation of all coretop δ15N measurements within each province; and the number of downcore records in each province. The pelagic denitrification provinces shown in Figure 4b are indicated in boldface.

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50 100 150 200 250 300 350

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!60

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0

20

40

60

80

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2

3

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Time (ka)

b15N

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Figure S4. δ15N provinces over time. Top panel: provinces, colour-coded with numbers and curves in lower panel, showing the locations of downcore records with complete data coverage over the interval 5-30 ka. Lower panel: The average time history for each of the 16 regions.

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The deglacial history of pelagic denitrification provinces In addition to the mean δ15N of the pelagic denitrification provinces discussed in the main text, we also calculated the timeseries of the standard deviation among tropical records. Given that pelagic denitrification is expected to produce strong local maxima in the tropics, we would expect the standard deviation of tropical δ15N provinces to be larger when pelagic denitrification is more active. Some caution must be exercised with this interpretation, as the standard deviation will also reflect changes in nitrate utilization and N2 fixation. Nonetheless, the standard deviation of all tropical provinces increases in concert with the rise of the mean δ15N of the pelagic denitrification provinces (Figure 4c). It should be emphasized that both the standard deviation and the mean are subject to dilution of the denitrification signal by ocean circulation6 and by N2 fixation above the anoxic zones, such that they cannot be taken as direct measures of pelagic denitrification rates14. Nonetheless, the most straightforward interpretation of both is that pelagic denitrification in the Pacific accelerated during HS1.

8

age

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Figure S5. Hoffmueller plot of δ15N provinces. All downcore records are plotted horizontally (vs. age), with colour representing δ15N. The records are grouped vertically according to the provinces, as indicated by the numbers on the left axis and separated by heavy black lines. The records in the bottom category are not associated with a province (from the Arctic and western tropical Atlantic oceans).

Time (ka)

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Sinking flux and the global mean δ15N-NO3

The sources of error in our estimate of δ15Nmean can be summarized as follows, with the calculation steps on the left, the sources of error related to each step on the right, and in parentheses on the right, the approach used to quantify (or correct for) the error:

province δ15N timeseries

weighted export δ15N

mean ocean δ15N

heterogeneity within province (+/- 1 s.d. of the coretop δ15N within the province; also, random deletion of half of the records)

individual δ15N records

variability in provincial export fluxes (+/- 20%)

mean-ocean approximation (box model estimate)

measurement (+/-0.2 ‰); diagenesis (partially corrected using the empirical water-depth relationship); age model (not considered here)

sediment

As shown, the final step in calculating δ15Nmean is to determine its relationship with the export-flux-weighted δ15Nexport. We are not aware of prior attempts to quantify this relationship, and therefore estimated it in two ways.

First, we constructed a box model in order to explore potential biases that might arise from using the δ15Nglobal_export as a monitor of δ15Nmean. The model includes a deep and a shallow layer, and essentially provides a test of the range over which the δ15Nmean - δ15Nglobal_export offset might vary under a broad range of environmental conditions while still satisfying the constraint of mass balance.

All nitrate uptake and N2 fixation occur within the shallow layer, which we give a nominal depth limit of 500 m. The remainder of the ocean, below 500 m, contains most of the NO3-. Denitrification, both pelagic and benthic, occurs in both layers. Given the observation that there is no significant alteration of the sinking flux of organic N in the water column12, the δ15N at 500 m should equal the integrated export from the surface layer where photosynthesis occurs.

At steady state, mass balance requires that the sinking flux of organic N across the surface/deep-boundary be equal to the upward flux of NO3- due to advection and turbulent mixing, plus the net addition of terrigenous N and N2 fixation less denitrification in the surface box (note that the net addition in the surface box is equal to the net loss by denitrification in the deep box).

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The equations that describe the behavior of the nitrogen isotopes in this model are:Vs

· [14NO�

3 ]sdt

= � ·�[14NO�

3 ]d � [14NO�3 ]s

��14 �exp +14 �terr +14 �fix �14 �wc

s

�14 �sed

s

Vs

· [15NO�

3 ]sdt

= � ·�[15NO�

3 ]d � [15NO�3 ]s

��15 �exp +15 �terr +15 �fix �15 �wc

s

�15 �sed

s

Vd

· [14NO�

3 ]ddt

= � ·�[14NO�

3 ]s � [14NO�3 ]d

�+14 �exp �14 �wc

d

�14 �sed

d

Vd

· [15NO�

3 ]ddt

= � ·�[15NO�

3 ]s � [15NO�3 ]d

�+15 �exp �15 �wc

d

�15 �sed

d

14�exp =Vs

� bio·�[NO�

3 ]s � [NO�3 ]

restore

s

�

15�exp =

✓�15N

s

� offset

1000+ 1

◆·14 �exp

15�terr =14 �terr

15�fix =14 �fix

15�wc = ↵wc · 14�wc

15�sed =14 �sed

where ν is vertical exchange, Φ indicates a flux of export (exp), input from N2 fixation (fix) and terrestrial sources (terr), pelagic denitrification (wc) or benthic denitrification (sed), and the subscripts s and d refer to the surface and deep oceans, respectively. The terms are the same for both 15NO3- and 14NO3-, as modified by the isotope effects as described above.

Because of the spatial and temporal complexity of uptake fractionation, it cannot be resolved in our single shallow box. Therefore, we do not model uptake fractionation as a Rayleigh distillation, but rather represent the net result as an average offset between the δ15N of the surface box and δ15Nglobal_export. We use the internal-cycling only version of the UVic model as well as the ibgc model, described above, in order to estimate the magnitude of this net fractionation (see Table S3).

Newly-fixed nitrogen can be either exported directly to the deep sea, or nitrified and recirculated within the ocean. To account for this, a portion of N2 fixed was transferred directly to export (not shown in the equations above) in the fraction of 0.08 ± 0.05, centered on the global mean value for the export fraction and spanning most of the modern open ocean range as summarized by Ref. 8. Because this parameter could potentially lie outside of this range, depending on where N2 fixation occurs and how it is recycled, we also demonstrate how it varies with a sensitivity test (Figure S6).

A Monte Carlo simulation was conducted with the box model in order to determine the degree to which δ15Nmean - δ15Nglobal_export would be expected to vary. The parameters were simultaneously varied across the range shown in Table S4 to provide 100,000 random combinations of values,

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distributed normally according to the specified mean and standard deviation (using a gamma distribution in order to prevent negative values as required). The +/- values indicated on the right side of the flow chart above correspond to 1 s.d. of the range across which the values were

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Fraction of fixation exported

Nut

rient

util

izat

ion

offs

et (p

erm

il)

b15N(permil) offset (Global − Export)

0.6

0.8

1

1

1.2

1.2

1.4

1.4

1.4

1.6

1.6

1.6

1.8

1.8

1.8

1.8

2

2

2

2

2.2

2.2

2.2

2.2

2.4

2.4

2.4

2.6

2.6

2.6

2.8

2.8

3

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.50

0.5

1

1.5

2

2.5

3

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

2.8

3

Figure S6. The sensitivity of δ15Nmean - δ15Nglobal_export to the nutrient utilization offset and the fraction of N2 fixation that is directly exported. Note that the average values for other parameters do not correspond to the modern ocean, so that the magnitudes of these values cannot be directly compared with Table S4.

UVic Uvic - internal only ibgc

δ15Nmean 5.25 5.25 5.21

δ15NO3-surface 6.22 5.84 6.87

δ15NO3-deep 5.19 5.23 4.98

NO3-surface 14.3 14.8 20.4

NO3-deep 29.4 29.5 36.6

δ15Nglobal_export 4.52 4.72 4.95

δ15Nmean - δ15Nglobal_export 0.73 0.53 0.26

δ15Nmean - δ15Nsurface 1.70 1.12 1.92

Table S3. Ocean-biogeochemistry model estimates of δ15Nmean, δ15Nglobal_export and related parameters.

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varied. Note that N2 fixation is always equal to total denitrification minus terrigenous inputs, fulfilling the steady-state requirement.

The results suggest that δ15Nmean - δ15Nglobal_export = 1.0 ± 0.6 ‰ (1 s.d.). We add the 1 s.d. variation to the error in the province estimate, assuming the errors are uncorrelated.

Two processes explain most of the offset. First, the vertical gradient of δ15N causes vertical mixing to transfer relatively more 14N to the surface ocean, since it is relatively depleted there. As a result, the δ15N of export is depleted relative to the source, even at steady state. Second, the input of new N from N2 fixation contributes significantly to export; although it makes up a small fraction of total export, it is very depleted in 15N relative to the NO3-based export, and therefore has a significant impact on the δ15Nglobal_export.

Given these dominant controls, one would expect that a world with more complete utilization would have a smaller δ15Nmean - δ15Nglobal_export offset, while a world with more N2 fixation would have a larger δ15Nmean - δ15Nglobal_export offset.

The second approach to estimating the offset was to calculate δ15Nmean, δ15Nglobal_export and related parameters directly from the two coupled ocean-biogeochemistry models described above. The results are given in table S3. As expected from the 2-box model, the offset is small (0.3-0.5 ‰) in models with only internal cycling, and greater in the model that includes N2 fixation (0.7 ‰).

Parameter range

Terrigenous inputs 30 ± 10 TgN/year

Upper ocean pelagic denitrification 60 ± 30 TgN/year

Deep ocean pelagic denitrification 10 ± 5 TgN/year

Upper ocean benthic denitrification 150 ± 60 TgN/year

Deep ocean benthic denitrification 30 ± 20 TgN/year

Mixing between upper ocean and deep ocean 50 ± 10 Sv

upper ocean NO3 16 ± 4 mmol/m3

deep ocean NO3 30 ± 5 mmol/m3

export δ15N uptake fractionation 1.0 ± 1.0 ‰

export fraction of N2 fixation 0.08 ± 0.05

Table S4. Box model parameters. Note that both pelagic and benthic denitrification occur both in the upper ocean and deep ocean boxes.

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Importance of the Southern OceanThe Southern Ocean plays a significant role in determining δ15Nglobal_export, both because of its large contribution to global export (11%) and the fact that it follows a distinct pattern of decreasing δ15N across the deglaciation. The decrease of δ15N is generally thought to reflect a decrease in nitrate consumption as the Southern Ocean High Nitrate Low Chlorophyll region grew in strength15. Whatever the reason for this decrease, it would be expected to have a noticeable impact on the global average sinking flux, which is used to estimate δ15Nmean, as outlined above.

In order to assess the sensitivity of our analysis to this region, we recalculated δ15Nglobal_export

without the Southern Ocean, as shown in Figure S7. This shows that without the Southern Ocean sites, the deglacial change in δ15Nglobal_export would be greater by ~ 0.3 ‰, within our error bars of 0.3 ‰.

Benthic denitrificationThe rate of benthic denitrification was estimated as described by Ref. 16, using a satellite-colour based algorithm for export production, realistic seafloor bathymetry, and four different algorithms for benthic denitrification17-19. These estimates were then modified using a timeseries of sea level change, according to the compilation of Ref. 20. The export production that occurs in shelf regions exposed by a given sea level drop was redistributed globally in proportion to the local export flux, so that global export production was maintained constant regardless of sea level. The four different curves shown in Figure 4d use the algorithms of, from lowest to highest: Ref. 19, Ref. 17 without considering O2 and NO3- concentrations, Ref. 18, and Ref 17 using

510152025303.6

3.8

4

4.2

4.4

4.6

4.8

5

Time (ka)

d15N

Export weighted b15N

Southern Ocean ExcludedSouthern Ocean Included

Figure S7. δ15Nglobal_export calculated with and without the Southern Ocean records.

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modern O2 and NO3- concentrations. The outer envelope in Figure 4d represents a 30% uncertainty in the fractional reduction of benthic denitrification, similar to the effect of uncertainty in the export production field16.

It is important to point out that changes in the global distribution of export production21, and the vertical profile of organic matter respiration22, may have introduced additional variability, which would be worth further investigation with coupled ocean-biogeochemistry models. Also note that this estimate considers eustatic sea level change only; isostatic adjustment would be expected to have altered the flooding history of high latitude shelves with respect to the strict eustatic change, thereby modulating some details of the curve.

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14 Eugster, O., Gruber, N., Deutsch, C., Jaccard, S. L. & Payne, M. R. The dynamics of the marine nitrogen cycle across the last deglaciation. Paleoceanography, n/a-n/a, doi:10.1002/palo.20020 (2013).

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