2.1 CTD and LADCP

Conductivity–temperature–depth (CTD) measurements were performed on a rosette using a SeaBird SBE 9plus instrument. Data were averaged over 1 m bins to filter out spurious salinity peaks using Sea-Bird electronics software. Simultaneously, currents were measured from a 300 kHz RDI lowered broadband acoustic Doppler current profiler (LADCP). LADCP data were processed using the Visbeck inversion method (Visbeck, 2002) and provided vertical profiles of horizontal currents at 8 m resolution. These measurements were performed at all stations with a typical 3 h time interval between each deployment. In addition the ship was equipped with two SADCPs, RDI Ocean Surveyors with frequencies 150 and 38 kHz yielding processed currents averaged over 2 min time intervals and with vertical bins of 8 and 24 m respectively. Shear was computed using finite differences with current vertical profiles interpolated over a 1 m vertical grid with an estimated noise level of $\mathrm{5}\times {\mathrm{10}}^{-\mathrm{4}}$ s⁻¹.

2.2 Microstructure measurements with VMP1000

Microstructure measurements were collected using a vertical microstructure profiler, “VMP1000” (Rockland Scientific). This tethered profiler was equipped with microstructure sensors, two shear sensors, and one temperature sensor, as well as with Sea-Bird temperature and conductivity sensors and a high-frequency fluorometer. A total number of 123 profiles were performed with repeated profiles at LD stations (∼ 30 profiles over three inertial periods) and at least one profile at each SD station except at SD13 (see Table 1 for further details). The dissipation rate of turbulent kinetic energy (ϵ) was inferred from centimeter-scale shear measurements. The vertical wavenumber shear spectrum was computed within the inertial range, typically within meter to centimeter scales. The experimental spectrum was next compared to the empirical spectrum, the Nasmyth spectrum (Nasmyth, 1970), which allowed validation of the estimate of ϵ (Ferron et al., 2014). Shear measurements were processed using the routines developed by Rockland Scientific. Specific noise removal procedures were applied with the spikes in the shear data first removed and spectral coherence between the shear sensors and the accelerometers used to remove vibrational contamination. The first 20 m below the surface were not considered to avoid any contamination from the ship wake as well as the 20 m at the end of the profile because of the decreasing vertical velocity there. More generally ϵ values were excluded when the vertical velocity gradient of the VMP was larger than $\mathrm{2.5}\times {\mathrm{10}}^{-\mathrm{2}}$ s⁻¹. The averaged ϵ from the two shear probes was taken provided that the ratio between the two estimates was smaller than 2; otherwise, the ϵ value with the smallest depth variation (compared to the neighbouring upper and lower ϵ values) was considered. ϵ was computed over a 1 m depth interval, and then a 8 m moving average was applied to this signal. The estimated noise level is $\mathrm{5}\times {\mathrm{10}}^{-\mathrm{11}}$ W kg⁻¹ following Ferron et al. (2014).

Table 1VMP profiles.

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2.3 Diffusivity estimates

The diapycnal diffusivity, K_z, is commonly inferred from the kinetic energy dissipation rate using the Osborn (1980) relationship:

where Γ is a mixing efficiency defined as the ratio between the buoyancy flux and the dissipation rate, $\mathrm{\Gamma }=-\frac{g}{{\mathit{\rho }}_{\mathrm{0}}}\frac{\stackrel{\mathrm{‾}}{{\mathit{\rho }}^{\prime }{w}^{\prime }}}{\mathit{ϵ}}$, with w^′ and ρ^′ the vertical velocity and density fluctuations, and N the buoyancy frequency, inferred from the sorted density profile in order to avoid spurious negative values associated with overturns, $N=\sqrt{-\frac{g}{{\mathit{\rho }}_{\mathrm{0}}}\frac{\text{d}{\mathit{\rho }}_{\text{sorted}}}{\text{d}z}}$, with an 8 m moving average then applied to this signal. Γ was generally set to 0.2 until the recent findings of Shih et al. (2005) and Bouffard and Boegman (2013). These authors found a decrease in Γ for increasing turbulence intensity, I, defined as

where ν is the molecular viscosity, $\mathit{\nu }=\mathrm{1.2}\times {\mathrm{10}}^{-\mathrm{6}}$ m² s⁻¹. In terms of timescales, I is the ratio of the square of the Kolmogorov timescale, namely the dissipation timescale of eddies at the Kolmogorov scale ($\sqrt{\mathit{\nu }/\mathit{ϵ}}$), and the buoyancy timescale (1∕N). Shih et al. (2005) showed in a numerical study that the Osborn relationship overestimated K_z when I>100 and proposed a new parameterization of K_z for this regime. A few years later Bouffard and Boegman (2013) proposed a refined parameterization of K_z including in situ microstructure measurements in lakes as well. They defined different regimes with the following formulations for K_z:

• $K_z={\mathrm{10}}^{-\mathrm{7}}$ m² s⁻¹ within the diffusive sub-regime, I<1.7 ;

• $K_z=\frac{\mathrm{0.1}}{{\mathrm{7}}^{\mathrm{1}/\mathrm{4}}}\mathit{\nu }{I}^{\mathrm{3}/\mathrm{2}}$ within the buoyancy-controlled sub-regime, I within [1.7;8.5];

• K_z=0.2νI, i.e., the Osborn relationship within the intermediate regime, I within [8.5,400]; and

• $K_z=\mathrm{4}\mathit{\nu }{I}^{\mathrm{1}/\mathrm{2}}$ within the energetic regime, I>400.

Note that for the OUTPACE dataset where most I values are smaller than 100, the K_z values inferred from the Bouffard and Boegman parameterization that is applied here do not differ significantly from those inferred from the Osborn relationship.

2.4 Internal forcing: estimates of internal tide generating force and wind power input into inertial motions

The internal tide generation is inferred from the depth integrated generating force following the linear approximation (Baines, 1982) that reads as

where N is inferred from the World Ocean Atlas monthly climatology, ω is the tidal frequency, Q is the barotropic tidal flux, and h is the bottom depth. The barotropic tidal flux is inferred from the $\mathrm{1}/\mathrm{30}{}^{\circ }\times \mathrm{1}/\mathrm{30}{}^{\circ }$ global inverse tidal model TPXO (Egbert and Erofeeva, 2002) for two main constituents, the diurnal K1 and the semi-diurnal M2.

The generation of baroclinic near-inertial waves occurs through inertial pumping at the base of the mixed layer (Gill, 1984; Price, 1984). Insight into possible generation of baroclinic near-inertial waves is estimated from the wind work on inertial oscillations following Alford (2003):

where ${\mathit{\tau }}_{\text{f}}^{\mathrm{2}}$ is the square of the wind stress at the inertial frequency, r is the damping of near-inertial motions in the mixed layer as a result of baroclinic near-inertial wave radiation expressed as a function of the inertial frequency r=0.15f, and H is the mixed-layer depth. The wind stress was inferred from numerical simulations over the time period of the cruise (Skamarock et al., 2005) and the mixed-layer depth from the seasonal climatology.

Figure 2Surface geostrophic currents inferred from AVISO altimetric data (a); longitude–depth section of the 38 kHz SADCP velocity modulus (b); bathymetry along the RV l'Atalante route (c); VMP stations are displayed with magenta circles in (a) and with vertical dashed red lines in (b) and magenta lines in (c).

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Table 2Statistics in the western and eastern parts: percentage of Ri<1 and mean values and standard deviations of ϵ and K_z within a 100–500 m surface layer.

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2.5 Biogeochemical turbulent diffusive fluxes

The vertical components of nitrate and phosphate turbulent diffusive fluxes were computed at all stations, using the diapycnal diffusivity, K_z, inferred from microstructure measurements:

where c_NO3 and $c_{{\mathrm{PO}}_{\mathrm{4}}}$ are the nitrate and phosphate concentrations. Measurements were performed daily at 12 depths in the first 200 m using standard colorimetric procedures Caffin et al. (2018). The quantification limits were 50 µmol m⁻³. At LD stations where six profiles were obtained, the quantification limit for the mean concentration dropped to 20 µmol m⁻³ (i.e., $\mathrm{50}/\sqrt{\mathrm{6}}$). Concentration values below the threshold for quantification were set to NaN. Vertical concentration profiles were interpolated over a 1 m vertical grid and a 10 m moving average was next applied. The top of the nitracline was defined as the depth where nitrate concentration is zero based on an extrapolation from the last detectable concentration (>50 µmol m⁻³) assuming a constant vertical gradient above this depth Moutin et al. (2018). It is only at long-duration stations that the top of the nitracline was defined in isopycnal coordinates: this allows us to get rid of a varying depth of the nitracline because of vertical displacements of isopycnals induced by internal waves Caffin et al. (2018). The minimum turbulent diffusive flux was estimated from the threshold concentration with the molecular K_z value ($K_z\sim {\mathrm{10}}^{-\mathrm{7}}$ m² s⁻¹): 0.4 $\mathrm{\mu }\mathrm{mol}{\mathrm{m}}^{-\mathrm{2}}{\mathrm{d}}^{-\mathrm{1}}$ at SD stations and 0.17 $\mathrm{\mu }\mathrm{mol}{\mathrm{m}}^{-\mathrm{2}}{\mathrm{d}}^{-\mathrm{1}}$ at LD stations where the mean concentration profile was taken to compute the flux. A reference profile was also defined in order to compare the nitrate diffusive flux variations along the OUTPACE within a 100 m layer below the top of the nitracline. To do so vertical profiles of concentration were first shifted vertically so that the reference depth matched with the top of the nitracline and the mean vertical $c_{{\mathrm{NO}}_{\mathrm{3}}}$ profile within the nitracline was inferred from this set of re-scaled concentration profiles. K_z profiles were also rescaled onto this vertical grid and a mean K_z profile inferred. The relative contributions of the variations in K_z and that of ${\partial }_z{c}_{{\mathrm{NO}}_{\mathrm{3}}}$ with respect to the total variations of the flux were also inferred.

Figure 3Log values of the dissipation rate of turbulent kinetic energy (W kg⁻¹) (a) and vertical diffusion coefficient (m² s⁻¹) (b) with N²−S² in background color scale. The number of profiles at each station is displayed with black circles and profiles have been time-averaged at each station for better visualization. The mixed-layer depth is plotted (black dashed curve) as well as the limit between the two regions (dashed white line).

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3.1 Overview

An overview of the spatial pattern of turbulence is given with depth-averaged values of ϵ and K_z below 100 m depth at each station (Fig. 1). Depth-averaged dissipation rates, 〈ϵ〉, vary within an order of magnitude within $[{\mathrm{10}}^{-\mathrm{9.5}};{\mathrm{10}}^{-\mathrm{8.5}}]$ W kg⁻¹. The highest values are observed west of 170^∘ W, in the shallower part, while the lowest values are observed east of 170^∘ W, in the deeper part. The same contrast is retrieved on 〈K_z〉 with values ranging within $[{\mathrm{10}}^{-\mathrm{5.8}};{\mathrm{10}}^{-\mathrm{4.8}}]$ m² s⁻¹. The western part of our study area which shows the highest turbulence level is also the region where the most intense velocities are observed, as illustrated with altimetry-derived currents produced by AVISO along the RV l'Atalante cruise path (Fig. 2a). The vertical section of the total velocity modulus inferred from the SADCP data shows that this contrast is also observed at depth with slightly larger velocities in the western part of our study area (Fig. 2b). There the bathymetry ranges typically from 4000 m up to a few hundred meters locally with significant topographic slopes, which is consistent with the higher velocity signal; by comparison, in the east the bathymetry is almost flat, with ∼5000 m depth. More insights into turbulence are given with vertical sections of ϵ and K_z in Fig. 3a and b. The range of ϵ values covers 3 orders of magnitude, $\sim [{\mathrm{10}}^{-\mathrm{10}},{\mathrm{10}}^{-\mathrm{7}}]$ W kg⁻¹ below the mixed layer (magenta curve in Fig. 3a) down to 500 m depth. ϵ presents a typical patchy pattern with spots of intense turbulence with values up to $\sim {\mathrm{10}}^{-\mathrm{8}}$ W kg⁻¹ down to 500 m. These events are localized over a 10 m vertical scale except at LD-A around 165^∘ E longitude where a 200 m layer of enhanced ϵ is observed. Most of these events are observed in the west, west of 170^∘ W, and the few vertically localized large ϵ observed east of 170^∘ W are no deeper than 200 m depth (Fig. 3a). Statistics of ϵ within a 100–500 m depth interval are given for each region in Table 2. The contrast between the mean 100–500 m depth-averaged ϵ in each of the two regions is a factor of 3 (Table 2). The contrast is larger for the standard deviation, a factor of 10, which points to the larger intermittency of turbulent events west of 170^∘ W. The K_z pattern presents a similar contrast between the western and eastern parts with mean 100–500 m depth-averaged K_z between the two regions differing by a factor of 2 (Table 2). More importantly, the standard deviation of K_z is by far larger west of 170^∘ W, by a factor of 15 (Table 2).

Figure 4Buoyancy frequency, N (a), shear, S (b), and N²−S² (c) as a function of longitude and depth. The locations of the CTD and LADCP profiles are displayed with black dashed lines. S is inferred from LADCP data and N was vertically averaged over 8 m length vertical intervals for consistency with the 8 m bin of the LADCP data.

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Figure 5(a) Depth-integrated generation force for the K1 tidal constituent (log10(m² s⁻²)); (b) same as in (a) but for the M2 tidal constituent. The stations are shown with a red circle and the LD stations are indicated.

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3.2 Shear instability

To gain further insights into the origin of this contrast in turbulence, the possible occurrence of shear instability is addressed with buoyancy frequency, N, shear, S, and N²−S² sections displayed in Fig. 4. The stratification is strong in the first 100 m, with a pycnocline that is generally well marked except westward of 165^∘ E and around 172^∘ W longitudes and a less stratified surface layer above 50 m east of 170^∘ W. The shear is significantly higher west of 170^∘ W, with high values over the 500 m depth layer of the measurements in the west except for a 165–170^∘ E region (Fig. 4a and b). The likeliness of shear instability was estimated from N²−S², displayed in Fig. 4c. The upper 100 m surface layer is the most stable, with the highest N²−S² values as a result of both strong stratification and low shear. Shear instability is more likely to occur west of 170^∘ W below the 100 m surface layer of strong stratification and where the shear is large: the percentage of data points that verifies the criterion for shear instability is 10 times larger west of 170^∘ W than east of 170^∘ W (Table 2). The fact that most of the subcritical Ri, $N^{\mathrm{2}}-S^{\mathrm{2}}<\mathrm{0}$, are observed west of 170^∘ W is consistent with the enhanced dissipation observed there (Fig. 3 and 4c).

3.3 Tidal and atmospheric forcings for the internal wave field

The possible impact of internal waves was estimated indirectly through the two main energy sources of these waves, namely tidal forcing and wind power input (Figs. 5 and 6).

The depth-integrated tidal generation force is displayed in Fig. 5 for the K₁ and M₂ constituents. There is a strong similarity between the two constituents with a generation that is favoured in the western part which is shallower and with stronger topographic gradients than the eastern part of our study area. The westernmost region is characterized by numerous spots of generation with a depth-integrated generation force of 10³ m² s⁻², while eastward of 170^∘ E longitude there is only one main generation site around 180^∘ E longitude (Fig. 5a). This spatial distribution of the internal tide forcing might suggest a similar contrast in the internal-tide-induced dissipation since the high modes responsible for turbulence are expected to dissipate within a few tens of kilometers of the generation site (St Laurent et al., 2002).

Maps of wind power input on inertial motions, also referred to as inertial flux, were computed using the spectral method described by Alford (2003). The wind stress data were inferred from WRF numerical simulations (Klemp et al., 2007; Skamarock et al., 2005) and the seasonal climatology was used for the mixed-layer depth. The power input into inertial motions gives insights into the generation of baroclinic near-inertial waves (niw) at the base of the mixed layer through inertial pumping (Gill, 1984). The maps reveal a strong longitudinal contrast in inertial flux until mid-March (Fig. 6a–e). The strongest wind power input was observed in the western part of our study area. This is consistent with the climatology of storms and cyclones in the area that are typically formed in the south-western tropical Pacific Diamond et al. (2013). At the beginning of the cruise the largest power input was localized south-west of the cruise stations (Fig. 6a). Later a major event was observed (Fig. 6d) during the passage of a tropical cyclone over the area while RV l'Atalante was sampling to the east. Eventually by the end of the cruise the inertial flux was small over the OUTPACE region, with one spot of weak inertial flux observed in the east (Fig. 6f–g). These maps suggest that energetic niw are likely to be generated in the western part of our study area prior to the cruise and until mid-March (Fig. 6a–b). The first event of large inertial flux prior to the cruise may be particularly insightful since it is likely to lead to the generation of equatorward propagation niw within the OUTPACE sampling area, a scenario which is consistent with large ϵ values there (Fig. 1).

Figure 6Maps of inertial energy flux (log10(W m⁻²)) every 7 days during the cruise. Long-duration stations are shown with magenta circles, and LD-A was held during (b) and (c), LD-B during (e), and LD-C during (f). The ship position is displayed with a magenta star.

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5.1 Overview of the OUTPACE section

The distribution of chlorophyll concentrations along the OUTPACE transect is typical of a transition from an oligotrophic area in the MA toward an ultra-oligotrophic area in the SPSG (Moutin et al., 2017) with a deepening of the deep chlorophyll maximum, DCM, from ∼60 to ∼160 m and an increase in the euphotic zone depth (Fig. 10a). There is one noticeable exception to this trend with a near-surface chlorophyll concentration maximum at ∼35 m depth, at LD-B. de Verneil et al. (2017), who focused on the characterization of this anomalous phytoplankton bloom event, explained its occurrence by the main impact of mesoscale advection and an island effect. The deepening of the DCM results from that of the nitracline and from the NO₃ depletion in the first 200 m, an evolution consistent with the increasing oligotrophy to the east (Fig. 10a and c). Moreover, east of 172^∘ W the nitracline is most often deeper than the base of the euphotic layer, which reinforces the oligotrophy. The turbulent diffusive nitrate flux displays the same longitudinal trend (Fig. 10c) with a depth-averaged value in the photic layer that differs by almost a factor of 4 west of 170^∘ W and east of 170^∘ W (Table 4). The standard deviation is also by far larger in the west, by a factor of 15. Whether these flux variations are driven by K_z variations or c_z variations was examined within a 100 m depth interval below the nitracline all along the section. These large variations of the turbulent diffusive nitrate flux at small scales (Fig. 10c) mostly result from K_z variations with a weaker contribution of variations in the vertical gradient of nitrate concentration with a typical ratio of 3 between the two (Table 5). The latter contribution tends to weaken slightly the eastward decrease in the flux due to decreasing K_z. The variation of the nitrate diffusive flux was also examined at LD stations only in order to focus on the impact of the temporal intermittency of turbulent events at each LD station where a large number of VMP profiles were collected. The flux variation resulting from K_z variations, −ΔK_zc_z, and those resulting from c_z variations, −K_zΔc_z, were compared to the averaged flux over the three LD stations. The −ΔK_zc_z always dominates and is by far the largest at LD-A, with a relative value of 105 % compared with the −50 % and −55 % relative values at LD-B and LD-C (Table 5). This shows the major impact of the turbulence intermittency induced by the niw event at LD-A.

Figure 11Time–depth sections of K_z (a, d, g), phosphate turbulent diffusive flux (b, e, h), and nitrate turbulent diffusive flux (c, f, i). The scales of the color bar of the nitrate and phosphate diffusive flux are set to match with the typical Redfield ratio in the area ($N:P=\mathrm{16}:\mathrm{1}$). The mean euphotic zone depth is displayed with a black dashed line. The top of the nitracline is defined by the isopycnal ${\mathit{\rho }}_{{\mathrm{NO}}_{\mathrm{3}}}$ and falls at depths of ∼83.5 m at LD-A, ∼111.2 m at LD-B, and ∼134.6 m at LD-C.

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Phosphate turbulent diffusive flux is on average smaller than the nitrate turbulent diffusive flux, but its relative impact may be rescaled by a factor of 16 : 1 corresponding to the Redfield N : P ratio. Hence, for visual comparison between the two fluxes, the scale for the phosphate turbulent diffusive fluxes differs from that of the nitrate turbulent diffusive flux within the Redfield ratio in Fig. 10 and subsequently. The phosphate turbulent diffusive flux displays a similar longitudinal gradient in the first 200 m but presents an opposite trend in the photic layer, with a depth-averaged value higher by a factor of 1.5 east of 170^∘ W (Table 5). The concentration of phosphate is not as strongly limiting as that of nitrate in the photic layer with significant turbulent diffusive flux, in a few spots, especially around 170 and 190 longitudes (Fig. 10d). Consistently the same trend is obtained for the phosphate concentration in the photic layer, with an eastward increase in the photic layer as opposed to the nitrate concentration that tends to zero at the eastern stations (Fig. 10c and d). The absolute value of the photic layer depth-averaged value of the flux, east of 170^∘ W, is 4.01 $\mathrm{\mu }\mathrm{mol}{\mathrm{m}}^{-\mathrm{2}}{\mathrm{d}}^{-\mathrm{1}}$. Considering a N : P Redfield ratio of 16, the phosphate turbulent diffusive flux is significant compared to the 3.15 $\mathrm{\mu }\mathrm{mol}{\mathrm{m}}^{-\mathrm{2}}{\mathrm{d}}^{-\mathrm{1}}$ value for the nitrate turbulent diffusive flux (Fig. 10e and f, Table 4). This striking difference in phosphate and nitrate turbulent diffusive fluxes within the photic layer may play an important role in the development of micro-organisms as discussed later.

Figure 12Histograms of K_z (a, c, e) and nitrate turbulent diffusive flux (b, d, f) at long-duration stations LD-A, LD-B, and LD-C around the top of the nitracline. The top of the nitracline is defined by the isopycnal, ${\mathit{\rho }}_{{\mathrm{NO}}_{\mathrm{3}}}$, with density values taken from Caffin et al. (2018), Table 4. A density interval of the upper bound equal to ${\mathit{\rho }}_{{\mathrm{NO}}_{\mathrm{3}}}+\mathrm{3}\times {\mathrm{10}}^{-\mathrm{2}}$ kg m⁻³, of a typical vertical extension equal to 3–4 m, was chosen for the statistics. The mean value is shown in each subpanel with a dashed line.

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5.2 Focus on LD stations

Turbulent diffusive fluxes of nitrate and phosphate were further analysed at long-duration stations (Fig. 11). The time–depth evolution of K_z underlines the very large values encountered at the most turbulent station, LD-A, in contrast with values at LD-B and LD-C that show the occurrence of a few spots of intense mixing in a more quiescent background with $K_z\sim \mathrm{3}\times {\mathrm{10}}^{-\mathrm{6}}$ m² s⁻¹ (Fig. 11a, d, and g). The largest nitrate turbulent diffusive fluxes occur at LD-A (Fig. 11b), while the smallest values are observed at LD-B and LD-C (Fig. 11f and i). The averaged values in the photic layer show that it is only at LD-A that there is a small input of nitrate through diffusion with an average flux of 8.41 $\mathrm{\mu }\mathrm{mol}{\mathrm{m}}^{-\mathrm{2}}{\mathrm{d}}^{-\mathrm{1}}$ (Table 4).

In contrast, phosphate turbulent diffusive fluxes are significant well above the euphotic zone depth at all LD stations (Fig. 11b, e, and h), which may have an impact on primary production, whereas the nitrate input by turbulent diffusion is negligible (explanation below). Depth-averaged values in the photic layer are even comparatively larger than that of the nitrate turbulent diffusive fluxes at LD-A if one applies the $P/N=\mathrm{1}/\mathrm{16}$ Redfield ratio (Table 4). Various spots of large phosphate turbulent diffusive fluxes are also evidenced in the first ∼ 20–80 m that can be correlated with events of intense turbulence (Fig. 11b, e, and d). At LD-C the only event of significant phosphate turbulent diffusive flux results from a strong turbulent event (Fig. 11h).

5.2.1 Nitrate input at the top of the nitracline

The input of nitrate through turbulent diffusion was first examined at the top of the nitracline, within a ∼4 m thickness layer, with histograms of the nitrate turbulent diffusive flux (Fig. 12). There is a strong contrast between LD-A and the eastern stations in the shape of the histograms: an atypical shape of the histogram is obtained at LD-A with a large standard deviation, while the distribution of the nitrate turbulent diffusive flux is fairly similar at LD-B and LD-C with one main peak (Fig. 12d and f). The atypical shape obtained at LD-A results from the large intermittency of K_z as illustrated in Fig. 12a. The distribution of K_z values covers 2 orders of magnitude and presents a bimodal distribution. The moderate K_z values are associated with the “background state”, while the large values are associated with intense turbulent events related to the near-inertial baroclinic wave (e.g., Fig. 8a). The mean value of the nitrate turbulent diffusive flux within a ∼4 m layer starting from the top of the nitracline is smaller at LD-B compared to LD-A and LD-C: 24.1 and 18.9 $\mathrm{\mu }\mathrm{mol}{\mathrm{m}}^{-\mathrm{2}}{\mathrm{d}}^{-\mathrm{1}}$ at LD-A and LD-C compared with the mean value of 6.0 $\mathrm{\mu }\mathrm{mol}{\mathrm{m}}^{-\mathrm{2}}{\mathrm{d}}^{-\mathrm{1}}$ at LD-B. This contrast may appear surprising, with a comparable mean value at LD-A and LD-C, but this results from the occurrence of a few turbulent events at LD-C where the nitracline is deepest. Nevertheless, the main point regarding the impact of the turbulent input of nitrate at the top of the nitracline on new primary production is whether or not the top of the nitracline falls within the photic layer. This point is addressed in the following with histograms in the photic layer.

Figure 13Histograms of K_z (a, d, g), phosphate (b, e, h), and nitrate (c, f, i) turbulent diffusive fluxes at long-duration stations LD-A, LD-B, and LD-C within the photic layer (down to 70, 55, and 120 m respectively). At LD-B and LD-C the nitrate turbulent diffusive flux is below the noise level within the considered depth interval (f, i). The mean value is displayed with a dashed black line.

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5.2.2 New primary production sustained by phosphate turbulent diffusive fluxes at the western stations?

Figure 13 summarizes the contrast between long-duration stations in the photic layer with histograms of K_z, phosphate, and nitrate turbulent diffusive fluxes. The euphotic zone depth (EZD) was immediately determined on board from the photosynthetically available radiation (PAR) at depth compared to the sea surface PAR(0+), and used to determine the upper water sampling depths corresponding to 75, 54, 36, 19, 10, 3, 1 (EZD), 0.3, and 0.1 % of PAR(0+) Herbland and Voituriez (1977); Moutin and Prieur (2012). The euphotic zone depth varies within [55–120 m] with a mean value of 70 m at LD-A, 55 m at LD-B, and 120 m at LD-C. As in the previous figures the scales for the nitrate and phosphate turbulent diffusive fluxes match with the Redfield ratio for visual comparison of the relative impact of each of these fluxes on micro-organisms. Significant nitrate turbulent diffusive flux is observed at LD-A as opposed to LD-B and LD-C as a result of shallower nitracline that falls within the photic layer at LD-A (Fig. 13c, f, and i). At LD-B and LD-C where the nitracline is below the euphotic zone depth the nitrate turbulent diffusive flux is zero (Fig. 13f and i). The station average of the phosphate turbulent diffusive flux is of the same order of magnitude at LD-A and LD-B and smaller by a factor of 10 at LD-C (Fig. 13b, e, and h; Table 4). These significant values of the phosphate turbulent diffusive flux observed at LD-A and LD-B suggest an impact on micro-organisms (Fig. 13e). Indeed, the presence of nitrogen fixers Dupouy et al. (2000) and high rates of N input by N₂ fixation were already noticed in the western tropical South Pacific (Moutin et al., 2008) and confirmed in the whole area (Bonnet et al., 2008). In contrast the smallest values observed at LD-C (Fig. 13h) are consistent with low nitrogen fixation rates measured there (Bonnet et al., 2017) or in the whole South Pacific gyre (Moutin et al., 2008), probably because of iron depletion (Blain et al., 2007; Bonnet et al., 2017; Guieu et al., 2018; Moutin et al., 2008). The lack of iron for N₂ fixers may explain their lower presence in the gyre and consequently the relatively higher phosphate concentrations measured there in the upper layer. Phosphate is not depleted by the N₂ fixers even with relatively low turbulent diffusive fluxes of phosphate from below.

Figure 14Time average of vertical profiles of nitrate and phosphate turbulent diffusive fluxes at long-duration stations LD-A (a), LD-B (b), and LD-C (c). The scales of the nitrate and phosphate diffusive flux are set to match with the typical Redfield ratio ($N:P=\mathrm{16}:\mathrm{1}$).

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Figure 14 summarizes the main features of the turbulent diffusive fluxes with time-averaged vertical profiles. The double x axis for the nitrate and phosphate turbulent diffusive fluxes is scaled within a Redfield ratio so that the fluxes are superimposed if they follow the Redfield proportion. At depth, NO₃ and PO₄ fluxes follow the Redfield proportion. Closer to the surface, NO₃ flux decreased: at LD-A there is a small input of nitrate in the photic layer, while at the eastern stations the nitrate flux vanishes above the base of the euphotic zone and reached zero before PO₄ fluxes. These significant phosphate fluxes at shallower depths may potentially be fuelling nitrogen fixation, significant PO₄ sources through turbulent diffusion that are likely to provide the required conditions for the growth of N₂ fixers in the Melanesian Archipelago. Because phosphate availability likely sustains N₂ fixation and therefore N input by N₂ fixation in the WTSP, new primary production (Dugdale and Goering, 1967) might be sustained by new P (or new N including N₂ fixation) in the photic zone.