Introduction
Primary production in the subtropical oligotrophic gyres has been an active
area of study for decades. In particular, scientists have long puzzled over
the seemingly paradoxical drawdown of summertime dissolved inorganic carbon
despite no visible source of nutrients (Michaels et al., 1994). Numerous
studies using geochemical tracers, sediment traps, and bottle incubations
have been performed at the Bermuda Atlantic Time-series Study (BATS) site
over the past several decades (e.g., Brew et al., 2009; Jenkins and Doney,
2003; Jenkins and Goldman, 1985; Spitzer and Jenkins, 1989; Gruber et al.,
1998; Stanley et al., 2012; Stewart et al., 2011; Buesseler et al., 2008;
Maiti et al., 2009, 2012; Owens et al., 2013; Lomas et al., 2010) in order
to quantify various aspects of biological production and to shed light on
this enigma. Floating sediment traps give a direct measure of export
production but may be biased by collection efficiency due to hydrodynamic
biases and swimmers (Buesseler, 1991), as well as by the limited amount of
time they are in the water. Bottle incubations, although primarily used to
determine net primary production (Marra, 2002, 2009), can also be conducted
to give determinations of new production when conducted with 15N
(Dugdale et al., 1992). Bottle incubations give useful information but may be
limited by the so-called bottle effects of constraining organisms to a bottle
(Peterson, 1980; Harrison and Harris, 1986; Scarratt et al., 2006).
Geochemical tracers give large-scale averages of the rates of new production, net
community production, or export production. These rates, however, can be
difficult to interpret since quantitative interpretation of the tracer data
often depends on estimates of physical transport. Thus, it is useful to
calculate rates of production using numerous approaches and to compare them.
One approach that has been used before in the Sargasso Sea is to estimate a
lower bound of new production by calculating the upward physical nutrient
flux (Jenkins and Doney, 2003; Jenkins, 1988b). The global inventory of
natural tritium has been dwarfed by the production of so-called “bomb
tritium” that was created during the atmospheric nuclear weapons tests in
the 1950s and 1960s (Weiss and Roether, 1980). This tritium was deposited in
large part in the Northern Hemisphere (Doney et al., 1992; Stark et al.,
2004) and has subsequently entered the oceanic thermocline and abyss by
subduction, water mass formation, mixing, and advection (e.g., Rooth and
Ostlund, 1972; Ostlund et al., 1974; Broecker and Peng, 1980). Tritium, which
has a half-life of 12.31 years (MacMahon, 2006), decays to 3He, a
stable, inert, and rare isotope of helium. Over the decades since the
bomb transient, a significant inventory of this isotope has accrued within
the main thermocline of the North Atlantic. There is evidence of an efflux of
this isotope via gas exchange from the surface ocean (Jenkins, 1988a, c).
Inasmuch as this tritiugenic excess 3He has a nutrient-like distribution
in the thermocline – it is small in the surface ocean due to gas exchange
loss and reaches a maximum within the thermocline due to in situ tritium
decay – it is tempting to argue that the physical return of this isotope to
the shallow ocean can be used as a “flux gauge” to determine the rate of
physical nutrient supply to the euphotic zone (Jenkins, 1988a; Jenkins and
Doney, 2003). Here, we report the results of a 3-year time series of
helium isotope measurements taken approximately monthly between 2003 and 2006
in the surface ocean near Bermuda that allow another determination of this
nutrient flux. We compare the calculated nutrient flux to the nutrient flux
determined at the same location using the same method for the period of 1985
to 1998 as well as to export production fluxes calculated in the Sargasso
Sea for the time period of 2003 to 2006.
Methods
Data collection
Samples for 3He, a suite of noble gases, and tritium were collected at
the BATS site (31.7∘ N, 64.2∘ W) on core BATS cruises at an
approximately monthly resolution between April 2003 and April 2006. The BATS
site, located in the subtropical North Atlantic, is representative of a
typical oligotrophic gyre. Much biogeochemical research has occurred at that
site because of the long-standing time series measurements carried out there
(Lomas et al., 2013). In particular, as part of the regular time series,
export fluxes are estimated monthly from surface-tethered floating and
upper-ocean sediment traps (Lomas et al., 2010), and rates of net primary
production are estimated monthly from radiocarbon bottle incubations
(Steinberg et al., 2001). In addition, other researchers have measured export
using 234Th (Maiti et al., 2009), neutrally buoyant sediment traps
(Owens et al., 2013), or apparent oxygen utilization rates (Stanley et al.,
2012; Jenkins, 1980). Net community production has been estimated from the
seasonal accumulation of O2 / Ar (Spitzer and Jenkins, 1989) and the
drawdown of dissolved inorganic carbon (Gruber et al., 1998; Brix et al.,
2006; Fernandez-Castro et al., 2012). New production has been estimated from
bottle incubations (Lipschultz, 2001; Lipschultz et al., 2002) and has also
been studied using nitrogen isotopes (Fawcett et al., 2014; Knapp et al.,
2008).
The 3He and noble gas samples for this study were collected from Niskin
bottles by gravity feeding through Tygon tubing into valved 90 mL stainless
steel cylinders. Typically 22 samples were collected within the upper 400 m,
and thus, depending on mixed-layer depth, there were usually several samples
collected within the mixed layer. Within 24 h of sampling, the gas was
extracted from the water stored in the cylinders into ∼ 30 mL
aluminosilicate glass bulbs. The bulbs were then brought to the Isotope
Geochemistry Facility at WHOI (Woods Hole Oceanographic
Institution), where they were analyzed for 3He,
4He, Ne, Ar, Kr, and Xe using a dual mass spectrometric system with the
3He being analyzed by a magnetic sector mass spectrometer and the other
noble gases being analyzed by a quadrupole mass spectrometer (Stanley et al.,
2009a). In particular, the magnetic sector mass spectrometer for 3He
measurements was a purpose-built, branch tube, statically operated,
dual-collector instrument equipped with a Faraday cup and a pulse-counting
secondary electron multiplier. Precision of the 3He measurements, based
on duplicates, was 0.15 %. The focus of this paper is on the 3He
measurements, but the other noble gases were used to calculate gas exchange
fluxes (Stanley et al., 2009b), which is an important term in the calculation
of 3He flux from the 3He data.
Samples for tritium were collected from the same Niskin bottles by gravity
feeding through Tygon tubing into 500 mL argon-filled flint glass bottles,
as described in Stanley et al. (2012). The tritium samples were degassed at
the Isotope Geochemistry Facility at WHOI (Lott and Jenkins, 1998), and then
the resulting 3He ingrowth was measured on a purposefully constructed,
branch tube dual-collector magnetic sector mass spectrometer (a different one
than the one used above for 3He samples). The resulting tritium
concentrations were used to correct for tritium ingrowth in the 3He
samples between the time of collection and the time of measurement.
Calculation of fluxes
The nitrate flux was calculated in a similar way as described in Jenkins and
Doney (2003). The most notable difference was that in this study the dynamic
solubility equilibrium value of 3He was modeled, taking both solubility and bubble injection into account, as
described in more detail below. To calculate the nitrate flux, first a
3He flux was calculated and then the slope of the nitrate : 3He
ratio was applied. The 3He flux was calculated from the gas exchange
parameterization of Stanley et al. (2009b), which was devised specifically
from the noble gas samples collected at the same time as the 3He samples
and thus is well suited to the study site and sampling conditions. In
particular, the 3He flux (FHe3) was calculated as the
product of a gas transfer velocity k, as determined in Stanley et
al. (2009b), and the difference in concentration between the measured
3He concentration (C) and the dynamic solubility equilibrium value
(Ceq):
FHe3=k×(C-Ceq).
The dynamic solubility equilibrium refers to the value of δ3He that
would be observed in the ocean if the atmosphere were in equilibrium with the water. This is governed by the
Henry's law constant for 3He vs. 4He (i.e., the fractionation
associated with solubility) as well as by the fractionating effect of gas
exchange, including bubble processes, on the ratio of 3He and 4He.
Thus the dynamic solubility equilibrium is the required saturation state such
that diffusive gas exchange will balance the bubble effects in a
quasi-steady-state system. Laboratory experiments have determined the isotope
effect in solution for helium in water as a function of temperature (Benson
and Krause, 1980). Given that the helium isotope ratio may be further
affected by isotopic fractionation in molecular diffusion (Bourg and Sposito,
2008) associated with the balance between wave-induced bubble trapping and
air–sea exchange (Fuchs et al., 1987; Jenkins, 1988b), we have used our
observations of the full suite of noble gases on these samples to develop a
much more complete model of this dynamic equilibrium isotope effect. Thus,
the dynamic solubility equilibrium value for 3He, Ceq, was
determined by adding 3He isotopes to a one-dimensional
Price–Weller–Pinkel (PWP) model (Price et al., 1986) subject to 6-hourly
NCEP (National Center for Environmental Prediction) reanalysis forcing
(Kalnay et al., 1996) and QuikSCAT winds from the BATS site (Stanley et al.,
2006, 2009b). The model used the temperature-dependent solubility of 3He
from Benson and Krause (1980) and the molecular diffusivity value from Bourg
and Sposito (2008). The calculated dynamic solubility equilibrium is
sensitive to the amount of air injection, and thus the other noble gases were
used to constrain the air injection (Stanley et al., 2009b; subsequently
referred to as S09). In particular, the dynamic solubility equilibrium was
calculated, including the effects of diffusive gas exchange, partially
trapped bubbles, and completely trapped bubbles according to the equations
below, described in full in S09.
The diffusive gas exchange flux of 3He (or another gas such as 4He)
(in units of mol m-3 s-1) was calculated as
FGE=γG⋅8.6×10-7Sc660-0.5u102Ci,eq-Ci,w,
where γG is a first-order, tunable model parameter that scales the
magnitude of diffusive gas exchange, Sc is the Schmidt number of the
gas (i.e, 3He), u10 is the wind speed in meters per second at a height of
10 m above the sea surface, Ci,eq is the concentration of the gas at
equilibrium (mol m-3), and Ci,w is the concentration of the gas in
the water (mol m-3). For QuikSCAT winds, γG=0.97, and
for NCEP winds γG=0.7.
The flux of 3He (or other gas) due to completely trapped bubbles was
calculated as
FC= 9.1×10-11(u10-2.27)3Pi,aRT,
where Pi,a is the partial pressure of the gas (i.e., 3He) in the
atmosphere calculated from the fractional abundance of the gas and the
variable total atmospheric pressure (Pa), R is the gas constant
(8.31 m3 Pa mol-1 K-1), and T is the temperature (K).
The flux of 3He (or another gas) (in units of mol m-3 s-1)
due to partially trapped bubbles was calculated as
FP=2.2×10-3×(u10-2.27)3αiDiDo23Pi,b-Pi,wRT,
where α is the Bunsen solubility coefficient of the gas (Benson and
Krause, 1980, for 3He), Di is the diffusivity coefficient (for
3He determined with the fractionation factor from Bourg and Sposito
(2008) and the diffusivity coefficient of Jahne, 1987), Do is a
normalization factor equal to 1 which is included in order to simplify the
units (m2 s-1), Pi,b is the pressure of the gas in the bubble
(Pa), and Pi,w is the partial pressure of the gas in the water (Pa).
Pi,b is approximated by
Pi,b=XiPatm+ρgzbub,
where Xi is the mole fraction of the gas in dry air, Patm is
the atmospheric pressure of dry air (Pa), ρ is the density of water
(kg m-3), g is the gravitational acceleration (9.81 m s-2),
and zbub is the depth to which the bubble sinks (m), which is
parameterized according to Graham et al. (2004):
zbub=0.15⋅u10-0.55.
The main numbers reported in this paper (i.e., the total nitrate flux of
0.65 mol m-2 yr-1) were calculated using the S09
parameterization as described above by Eqs. (2) to (6) since it was derived
from a noble gas time series collected concurrently with the helium isotope
data used in this study. Thus, since samples were collected at the same
location and time, S09 is based on exactly the same physical conditions (wind
range, temperature range, etc.) as experienced by the helium isotopes. We
explored the consequence of using other gas exchange parameterizations that
explicitly include bubbles, namely the Nicholson et al. (2011) (subsequently
referred to as N11) parameterization and the Liang et al. (2013)
parameterization (subsequently referred to as L13). N11 is based on a global
inversion of deep N2, Ar, N2 / Ar, and Kr / Ar data and
thus reflects a larger perspective on gas exchange though perhaps one not
quite as suitable to this specific study. N11 has a similar formulation for
air injection to S09 although N11 does not include the effect of the partial
pressure difference between enhanced pressure in the bubbles and pressure in
the water when determining the flux due to partially trapped bubbles. L13 is
based on a mechanistic model that explicitly includes the bubble size
spectrum.
Calculations of the dynamic solubility equilibrium and the flux of 3He
were also made using NCEP reanalysis winds instead of QuikSCAT winds. When
NCEP reanalysis winds were used in the model, the gas exchange
parameterization of Stanley et al. (2009b) was modified to a parameterization
that was calculated using NCEP winds. For example, the gas exchange scaling
factor, γG, is 0.97 when using QuikSCAT winds (as reported in
Stanley et al., 2009b) but is only 0.7 using NCEP winds.
The 3He flux, calculated from Eq. (1), is then corrected for the flux of
3He due to in situ tritium decay (FHeFromTrit):
FHeCorr=FHe-FHeFromTrit.
FHefromTrit is calculated by using the radioactive decay equation
(A=Nλ, where A is activity of 3He, N is the number of atoms of
tritium, and λ is half-life of tritium), the half-life of tritium
(λ=12.31 years), and the mixed-layer tritium concentrations measured
concurrently with the 3He data presented in this study. This yields a
flux of 3He produced in numbers of moles per cubic meter. We then multiply
this flux by 300 m to calculate a flux in units of moles per square meter for the
3He produced by tritium decay in the upper 300 m of the ocean. This flux
equals roughly 15 % of the total 3He flux calculated from Eq. (1)
and is subtracted from the total 3He flux to yield the 3He flux
that must be supported by vertical transport (Eq. 7).
The nitrate flux (FNO3) was then calculated as the product
between the corrected 3He flux and the nitrate : 3He ratio (R):
FNO3=FHeCorr×R.
The ratio R was calculated by determining the slope of a type II regression
of NO3 vs. 3He for samples measured in the upper 400 m of water
during the 3-year time series (N=218). Only data with
[NO3] > 2 µmol kg-1 were used in the regression
since water with NO3 concentration below this threshold represents water
in the euphotic zone where 3He and NO3 are decoupled. Jenkins and
Doney (2003) studied the effect of using different data for the
NO3 : 3He correlation – data based on vertical correlation (as here), on density surfaces, or at base of the winter mixed layer – and
found that the slopes were similar no matter which data set was used.
Results and discussion
The fluxes of helium-3 and nitrate
The 3He and tritium data collected in this study between 2003 and 2006
are presented in Fig. 1. The gradient of 3He with depth is clearly
visible. In contrast, tritium has a more uniform distribution with depth in
the upper 300 m. The lack of excess 3He in the mixed layer (mixed layer
is demarcated by the thick black line) is because of air–sea gas exchange, which
results in a flux of excess 3He out of the ocean into the atmosphere.
This sustained air–sea gas exchange results in a decreasing inventory of
tritiugenic 3He in the ocean over time. Multiple measurements within
the mixed layer were averaged in order to calculate the mixed-layer
concentrations of 3He (Fig. 2a). The dynamic solubility equilibrium
(blue curve on Fig. 2a) is significantly smaller than the 3He
concentrations, resulting in a sea-to-air flux of 3He (Fig. 2c).
A time series of helium isotope ratio anomaly (in percent) relative
to the atmospheric 3He / 4He ratio (upper panel) and tritium (in
tritium units) decay corrected to January 2005 (lower panel) at the Bermuda
Atlantic Time-series Site in the North Atlantic near Bermuda. Sampling,
designated by black dots, was approximately monthly over the ∼ 3-year
period. The black line is the mixed-layer depth estimated from the CTD (conductivity, temperature, depth) data.
Additionally, since we now have a better understanding of the
dynamic solubility equilibrium, both because of the extensive information on
gas exchange garnered from the noble gases and because of more accurate
estimates of molecular diffusivity of 3He, we have also recalculated the
3He and nitrate fluxes for the data from 1985 to 1988 that were
originally presented in Jenkins and Doney (2003). Thus, the 3He
concentrations from 1985 to 1988 as well as the dynamic solubility
equilibrium for that time period are presented in Fig. 2b. Note the
difference of scales in Fig. 2a and b. There is much less 3He in
2003–2006 than in the 1980s because of a decreased 3He source in the
thermocline due to tritium decay over time and decades of outgassing of
3He.
Mixed-layer δ3He data from (a) 2003 to 2006 and (b)
1985 to 1988 as well as the dynamic
solubility equilibrium for δ3He. Error bars represent standard
error of multiple measurements
within the mixed layer. Fluxes of 3He calculated from the data for (c)
2003–2006 and (d)
1985–1988. Note the difference in scales on the y axes for the two time
periods.
The average 3He flux, corrected for tritium ingrowth, over the
2003–2006 time period is calculated to be 7.9 ± 1 pmol m-2 yr-1 (Table 1). The flux due to tritium ingrowth in the
mixed layer, determined using the average tritium concentration and
considering tritium that could be accessed in the upper 300 m of the ocean, was 1.2 ± 0.1 pmol m-2 yr-1 during this period. The
integrated 3He flux is multiplied by a NO3 : 3He ratio of
82.9 × 109 ± 2 × 109 mol NO3 mol-1 3He (Fig. 3) in order to calculate a NO3 flux of
0.65 ± 0.14 mol N m-2 yr-1. The nitrate flux calculated by
the flux gauge method used here represents the lower bound of new production
in the northern half of the subtropical gyre. It represents a lower bound
estimate because it only includes the new production based on the upward
physical transport of nutrients. It does not include any new production due
to nitrogen fixation, zooplankton migration, or atmospheric deposition of
nitrate. At BATS, nitrogen fixation has been estimated to be 0.03 to
0.08 mol N m-2 yr-1 (Singh et al., 2013; Knapp et al., 2008),
which is equivalent to 5 to 12 % of the new production we report from the
flux gauge method. Zooplankton migration from 2003 to 2006 has been estimated
to support a new production of 2 g C m-2 yr-1 (Steinberg et al.,
2012), which is equivalent to 0.025 mol N m-2 yr-1 using the
revised Redfield ratios of Anderson and Sarmiento (1994) and thus is only
4 % of the new production rate estimated by the flux gauge technique.
Estimates of the nitrate supply due to atmospheric deposition range from
0.006 mol N to 0.026 mol N m-2 yr-1 (Singh
et al., 2013; Knapp et al., 2010), thus being at most 4 % of the new
production flux estimated here from the flux gauge method. Thus, in total, the
sources of new nitrate that are not accounted by the flux gauge method may
mean that the new production estimate given here is only about 80 % to
85 % of the total new production rate. The flux estimate represents the
northern half of the gyre – rather than just the BATS site – because the
water in the thermocline that is vertically transported at the BATS site
originates from the northern half of the gyre (Talley, 2003).
Fluxes calculated from the flux gauge technique for two different
time periods. 1σ uncertainty estimates for each flux are given in
parentheses underneath the reported value for each quantity.
QuikSCAT winds
NCEP winds
Time period
NO3 : 3He × 10-3
3He Flux
NO3 flux
3He flux
NO3 flux
(µmol pmol-1)
(pmol m-2 yr-1)
(mol m-2 yr-1)
(pmol m-2 yr-1)
(mol m-2 yr-1)
2003–2006
82.9
7.9
0.65
8.3
0.69
(2.1)
(1.7)
(0.14)
(1.8)
(0.15)
1985–1988
34.5
–
–
30.4
1.05
(1.1)
–
–
(5.4)
(0.2)
The observed relationship between excess (tritiugenic) 3He and
dissolved inorganic nitrate near Bermuda at four points in time. The 1986 and
2005 relations are based on approximately 3-year time series occupations near
Bermuda (the former at Hydrostation S and the latter at BATS). The 1981 and
1997 data sets are from cruise stations within ∼ 500 km of the site.
Only samples with potential density anomalies less than 26.8 kg m-3 are
plotted and used. Note the “waterfall” effect at low 3He and nitrate
concentrations in the euphotic zone, where the two tracers become uncoupled
due to differing boundary conditions. The straight lines, from which the
slopes are obtained, are type II linear regressions of points with nitrate
concentrations in excess of 2 µmol kg-1. The lower bound
nitrate limit was chosen to avoid the tracer-decoupled points.
The nitrate fluxes calculated with the NCEP wind-derived 3He fluxes are
very similar to those calculated by QuikSCAT winds (Table 1). This is because
the gas exchange parameterizations we used to calculate the flux from the
3He concentration data and to calculate the dynamic solubility
equilibrium were separately tuned to observed noble gas data for QuikSCAT and
NCEP. We were able do this since we had the wealth of noble gas data
collected concurrently, allowing for a good model of air–sea gas exchange with
two different wind products.
Uncertainties and sensitivity studies
There are a number of sources of uncertainty in the estimate of nitrate
fluxes from the helium flux gauge technique. Here we describe these
uncertainties and the results of sensitivity studies examining the effect of
the sources of error. Table 2 lists the main sources of uncertainty in the
calculations. One of the largest sources of uncertainty is uncertainty in the
gas transfer velocity k (Eq. 1). Stanley et al. (2009b) illustrate how the
time series of noble gases collected concurrently with this data results in
uncertainties of 14 % in the gas transfer velocity k. Since k is
directly used to calculate the 3He air–sea flux from the difference
between measured 3He concentration and dynamic solubility equilibrium,
this uncertainty directly translates into a 14 % uncertainty in 3He
flux and ultimately in nitrate flux.
The fractional uncertainty caused by different sources in the
calculations of nitrate flux for the 2003–2006 time period.
Source of error
% uncertainty
Reference or method
Air–sea gas exchange
14 %
Stanley et al. (2009)
Dynamic solubility equilibrium
– From diffusivity
10 %
Calculated with range fromBourg and Sposito (2008)
– From bubble treatment
13 %
Calculated with range of gas exchangefrom Stanley et al. (2009)
Measurement error
5 %
Integration of error at each time point
NO3 : 3He slope
2.5 %
Type 2 regression
Tritium correction
1 %
Tritium measurement uncertaintypropagated to 3He flux
The second largest uncertainty in the nitrate flux is the uncertainty in the
dynamic solubility equilibrium caused by uncertainties in the parameterization of
air injection. Three different parameterizations of air injection were used
(see Sect. 2.2) in order to investigate the robustness of the flux gauge
number with respect to air injection. The nitrate fluxes determined using
these three different parameterizations when calculating the dynamic
solubility equilibrium are 0.65 with S09,
0.55 with N11, and 0.48 mol m-2 yr-1
with L13. The standard deviation of these three numbers
(0.08 mol m-2 yr-1=13 % of reported nitrate flux) is used
as a measure of the uncertainty due to air injection. The S09 value was used
for reporting the “base case” number (i.e., the number reported in the abstract
and the conclusion) because S09 is based on data collected at the same time and location
as the 3He data used in this study and thus is likely to reflect gas
exchange best in these conditions. Notably, the root mean square deviation
between observed helium surface saturation anomalies and the saturation anomalies
predicted by the PWP model run with either the S09 or N11 parameterization is
the same (1.3 %). The root mean square deviation, however, for the
model–data fit of the L13 parameterization is almost double that (2.5 %),
suggesting that L13 does not represent air injection at this location and
time as well as S09 or N11. The root mean square deviation between model and
data for surface saturation anomalies for all the other stable noble gases
(Ne, Ar, Kr, and Xe) agrees better for S09 and N11 than for L13 though the
difference becomes smaller for the heavier gases – i.e., the L13 model
matches observed data almost as well for Kr or for Xe as does S09 or N11.
Since the L13 model does not match the surface saturation anomalies of He as
well as S09 or N11 (i.e., double the RMSD), L13 is probably not a good model
to use for air injection in this study, and thus calculating the uncertainty
from the standard deviation of fluxes determined when using all three gas
exchange parameterization leads to a conservative estimate of the total uncertainty
due to air injection. We also examined the effect on the nitrate flux of
using different sets of air injection parameters from the S09
parameterization. Specifically, we use many of the parameter sets determined
in Table 1 of Stanley et al. (2009b), including the sets of parameters
determined for different physical parameters in the model and different
weightings of the cost function. We found that the dynamic solubility
equilibrium changed by only a small amount in these scenarios so that the
overall standard deviation of the 3He flux for all the different
scenarios of S09 was only 2 %.
The third-largest source of uncertainty in the nitrate flux is the
uncertainty in the determination of the dynamic solubility equilibrium due to
uncertainties in the molecular diffusivity of 3He with respect to
4He. The dynamic solubility equilibrium is sensitive to the molecular
diffusivity due to the relative diffusive gas exchange of 3He vs.
4He (i.e., Schmidt number dependence) and due to the effect of the air
injection of partially trapped bubbles – during air injection, 3He
diffuses more quickly out of the bubbles than 4He. We ran sensitivity
studies with the range of molecular diffusivities estimated by Bourg and
Sposito (2008) and found that the 3He flux changed by ±10 %
depending on the molecular diffusivities used. Although experiments with
helium isotopes have not yet been performed to confirm the diffusivities
predicted by Bourg and Sposito (2008), two separate experimental studies
(Tempest and Emerson, 2013; Tyroller et al., 2014) have shown good agreement
with the Ne isotope diffusivities calculated by Bourg and Sposito (2008),
giving us confidence in the Bourg and Sposito (2008) helium predictions.
The effect of the measurement error of 3He is a smaller uncertainty than the
systematic uncertainties listed above but does lead to an error of 5 %
when propagated through all the calculations. Interestingly, for the
1985–1988 period, the absolute 3He concentrations were much higher but
the measurement uncertainty at that time was much worse, resulting in a
similar 5 % contribution of measurement uncertainty during that period as
well.
Uncertainties in the slope of NO3 : 3He feed directly into
uncertainty in the nitrate flux, resulting in a 2.5 % uncertainty in the
nitrate flux. The uncertainties were derived from the uncertainty associated
with the calculation of the slope using a type II regression and appropriate
measurement uncertainties for the individual data points. Additional error in
the 3He flux – and thus propagated to the nitrate flux – comes from
the correction for tritium ingrowth in the water column. However, since the
3He flux due to in situ tritium production is relatively small
(15 % of the total 3He flux), the uncertainty on that number only
contributes to a small fraction of the total uncertainty in the helium and
nitrate fluxes (1 %).
Comparison to 1980s fluxes
The estimated nitrate flux for the period between 1985 and 1988 is 50 %
larger than the nitrate flux for the 2003–2006 period, though over half of
this difference can be accounted for by uncertainties in the flux estimates.
For 1985–1988, our recomputed nitrate flux estimate is 1.05 ± 0.2 mol
N m-2 yr-1 (Table 1), which is 25 % larger than the nitrate
flux calculated for the same time period in Jenkins and Doney (2003). This
difference between the 1985–1988 fluxes calculated here and those
calculated in Jenkins and Doney (2003) stems from this calculation using a
well-modeled dynamic solubility equilibrium. In the earlier study, we did not
have the other noble gas data nor updated estimates of molecular diffusivity
(Bourg and Sposito, 2008) and thus employed a simpler and likely less
accurate estimate of the dynamic solubility equilibrium.
It is interesting to note that although the nitrate flux in 1985–1988 is
only 50 % larger than the nitrate flux in 2003–2006, the 3He flux
in 1985–1988 is 300 % larger than the 3He flux in 2003–2006. This
is because in the 1980s, there was a much larger tritium inventory and
consequently larger concentrations of 3He in the main thermocline
(Fig. 4). However, the slope of the NO3 : 3He relationship also
changes with time. The distribution of nutrients in the main thermocline is in an approximate steady state established by a balance between nutrient
release by in situ remineralization of organic material and removal by
physical processes related to ventilation, advection, and mixing. The
corresponding thermocline distribution of tritiugenic 3He is evolving as
a transient tracer. Over time, as the bomb-tritium pulse penetrates the
thermocline, the resultant 3He maximum deepens and broadens (Jenkins,
1998). Consequently the relationship between 3He and nutrients changes with time. Figure 3 is a plot of the NO3 : 3He
relationship for the upper 500 m of the water column near Bermuda at four
points in time. Notably, the slope of the NO3 : 3He
relationship has increased by over a factor of 2 in the approximately 25
years spanned by this data.
While the nitrate flux is broadly similar between the two time periods, there
is still a 50 % difference with the flux being larger in 1985–1988 than
in 2003–2006. What can account for this difference? It is not because of
NCEP winds being used in the 1985–1988 calculation and QuikSCAT winds being
used in the 2003–2006 calculation because even if we do the 2003–2006
calculation with NCEP winds, we still get a 40 % difference between the
flux in the two different decades (Table 1). It also is not likely to be due
to the 1985–1988 data being from Hydrostation S, whereas the 2003–2006 data
are from BATS. Those two sites are only 28 km apart and since the 3He
flux gauge estimate is reflection of a much broader region, the relatively
small difference in locations of samples likely does not play a role. It
could be, in part, due to a time lag between the evolving subsurface
NO3 : 3He ratio and surface fluxes. Most likely, however, it is
due to a real elevation in new production in the late 1980s compared to the
2003–2006 period. Winter mixed layers in the two time periods are similar,
with the exception of a shallower than typical winter mixed-layer depth in
1986, and thus the difference in time periods is not likely an explanation for the difference in production
between the periods.
Lomas et al. (2010) observed significant changes in export production at BATS
over time, with the period between 1988 and 1995 having lower export fluxes
than the period from 1995 to 2008. They attributed these changes to a shift
in the North Atlantic Oscillation (NAO) from positive in the 1988–1995
period to neutral in the 1996–2008 period. Our older data are from 1985 to 1988 and were not included in the Lomas et al. (2010) study. The winter NAO
index (JFM), which has been shown to be most sensitive to changes in
subtropical mode water formation (Billheimer and Talley, 2013) and primary
production (Lomas et al., 2010), was -1.2, 0.2, and -1.1 for 1985, 1986,
and 1987, respectively. It was -0.3, -0.5, and -0.6 for 2004, 2005, and
2006 respectively. According to Lomas et al. (2010), a more negative winter NAO, as was mostly seen
in the 1985–1988 period, would be associated with
higher production, which is indeed what we found in this study.
A more negative NAO is usually correlated with a greater production of
subtropical mode waters (STMW) via enhanced surface buoyancy loss and
vertical convection (Billheimer and Talley, 2013). Indeed, estimates of Kelly
and Dong (2013) suggest that there was increased formation of STMW in
1985–1988 compared to 2003–2006. We thus find that higher rates of new
production are associated with time periods of a higher generation of STMW.
This is in contrast to the hypothesis of Palter et al. (2005), who suggested
that increased STMW production would lead to a reduction in primary
production due to decreased nutrients below the mixed layer in the vertically
homogenized mode water region since the decreased nutrients would lead to a
smaller nutrient supply from the main thermocline below the mode water region
and thus to smaller rates of primary production.
Representative profiles of δ3He in the upper 1200 m of the
water column in 1986 (black) and 2003–2006 (red). The profiles illustrate
that in 1986 there was much higher δ3He in the main thermocline and
a larger gradient between the thermocline and the mixed layer than there was
in 2006. This drives the observed greater 3He flux in the 1980s compared
to the 2000s.
The highest annual flux in the 1985–1988 period comes from 1987 (Fig. 2d).
Interestingly, while the NAO index of 1987 was similar to that of 1985 and
2003–2006, the NAO index of 1986 was positive. It has been shown that
chlorophyll correlates better with the NAO index at BATS using a 1-year time
lag (Cianca et al., 2012). Thus, potentially, the higher fluxes we see in 1987
are a result of the higher NAO index in 1986. However, this would run counter
to the general trend suggested by Lomas et al. (2010) and seen in the rest of
our data of higher rates of production with more negative NAO indices.
Seasonal cycle
A seasonal cycle in 3He flux is observed in both the 1985–1988 time
period and the 2003–2006 time period (Fig. 5). The 3He fluxes are
highest in wintertime when the deep winter mixed layers at BATS draw water
from the seasonal thermocline, bringing up higher amounts of 3He and
nitrate. But even in the summer, there is an upward flux of 3He,
suggesting an upward flux of nitrate. There is no observable nitrate in the
summer mixed layer at BATS (Michaels et al., 1994; Steinberg et al., 2001),
likely because the organisms consume all the nitrate as soon as it enters the
euphotic zone. Thus the lack of observable nitrate, long known at BATS, does
not mean that nitrate was never there. Hence the “paradox” of how
summertime production can be supported at BATS without observable nutrients
is in some sense answered by this clear sign that there is an upward nutrient
flux, even in the summer. This supports the recent finding of Fawcett et
al. (2014) showing evidence of nitrate supply to the mixed layer at BATS even
in the summer.
The 3He flux as a function of fractional year for the 2003–2006
time period (red) and the 1985–1988 time period (black). The time period
between 0 and 0.4 has been replicated from 1 to 1.4 in order to better
visualize a seasonal cycle.
Comparison to other rates of biological productivity at BATS
The rate of new production estimated by the helium flux gauge technique
presented in this study is larger than most of the rates of new production,
net community production, or export production at BATS derived from other
geochemical tracer approaches. Over long periods of time and on long spatial
scales, new production, net community production, and export production should
be equal (Dugdale and Goering, 1967). In carbon units, using the revised
Redfield ratio of Anderson and Sarmiento (1994) of 106:16, new production
estimated in this study was 4.3 ± 0.9 mol C m-2 yr-1 in
2003–2006 and 6.96 ± 1.3 mol C m-2 yr-1 in 1985–1988.
Because of global and regional variations in the C : N ratio (Lomas et al.,
2013; Martiny et al., 2013; Ono et al., 2001), there are additional
uncertainties when converting nitrate fluxes to carbon fluxes. Additionally,
as noted above, these rates represent new production derived from the physical
vertical supply of nitrate over the northern half of the subtropical gyre.
Export fluxes as estimated by apparent oxygen utilization rates (AOUR) also
represent fluxes over a similar northern region (Jenkins, 1980). Tritium
samples were collected and used in conjunction with 3He and O2 data
from the same cruises in 2003–2006 that the 3He data in this paper come
from to estimate apparent oxygen utilization rates (Stanley et al., 2012).
The AOUR values were integrated to 500 m to yield a lower bound on annual
export from the remineralization and oxygen consumption between 200 and
500 m of 2.1 ± 0.5 mol C m-2 yr-1. Thus, the fluxes
estimated by the helium flux gauge technique are nearly a factor of 2
greater than the fluxes by AOUR, even though both represent a large
geographical region.
A more local estimate of production comes from the seasonal drawdown of DIC (dissolved inorganic carbon) at
BATS or from seasonal accumulation of O2 with respect to Ar. Both
techniques rely on the fact that photosynthesis produces O2 and consumes
CO2, whereas respiration produces CO2 and consumes O2. Thus, the
seasonal changes in O2 or CO2 constrain the net balance between
photosynthesis and respiration. On the same cruises on which data for 3He flux
gauge technique were collected, the seasonal accumulation of O2 and Ar
was measured and used to estimate the rates of net community production of 1.2 to
2.4 mol C m-2 yr-1 (Stanley, 2007). Notably, this rate is
similar to that of the AOUR estimate and a factor of 2 smaller than the
3He flux gauge estimate. The seasonal accumulation of oxygen and argon
has been used at other time periods to estimate the rate of net community
production at BATS to be 2.2 to 3 mol C m-2 yr-1 (Spitzer and
Jenkins, 1989; Luz and Barkan, 2009). Seasonal drawdown of DIC directly as
well as the change in isotopic composition of 13C of DIC have been used
to estimate annual net community production fluxes of 1.7 to 4.9 mol
C m-2 yr-1 (Gruber et al., 1998; Brix et al., 2006;
Fernandez-Castro et al., 2012). The upper end of this range approximates the
rate of new production we find here using the flux gauge technique.
Interestingly, the DIC drawdown and O2 / Ar approaches reflect a
smaller spatial scale than the AOUR estimates but, at least in some cases,
agree better with the 3He flux gauge approach.
On even smaller spatial and temporal scales, 234Th has been used to
estimate export fluxes at BATS, resulting in rates of export production
calculated to be 0.3 to 0.8 mol C m-2 yr-1 (Maiti et al., 2009)
These fluxes are much smaller than the fluxes estimated by other geochemical
tracers, which may in part be due to the fact that the 234Th technique
does not include the contribution of export due to DOC, whereas the other
geochemical techniques do. DOC export in the Sargasso Sea has been estimated
to be up to 1 mol C m-2 yr-1 (Hansell et al., 2012).
Why is the helium flux gauge technique yielding rates of new production at
the high end of the range of rates from other geochemical tracers? In part
this may be due to the broader spatial coverage of the flux gauge technique,
but that is not enough to explain fully the discrepancy since the AOUR
technique has a similar spatial area but smaller fluxes. One reason may be
that 3He and NO3 are decoupled during obduction in the northern
part of the gyre. The northwest Sargasso Sea, where the warm waters of the
Gulf Stream leave the North American continent, is characterized by large
latent heat fluxes and substantial downstream winter mixed-layer deepening
(Worthington, 1972). In effect, upper thermocline isopycnals
outcrop, a process referred to as obduction (Qiu and Huang, 1995).
This outcropping brings remineralized nutrients and tritiugenic 3He
back to the seasonal layer. Whereas the time constant associated with
nutrient removal by biological processes is a matter of days, the exchange
timescale for tritiugenic 3He loss to the atmosphere from a deep mixed
layer may be several weeks. In this respect the nutrients may have been
removed, while the 3He “signal” may persist, so the 3He flux
gauge may measure not only local new production but may also hold a more
“regional” memory of the upstream, previous winter's production.
There are two approaches to estimating this obduction flux of 3He. Given
that they are rather crude in nature and involve rather different assumptions
and, more importantly, scales, exact congruence would be unlikely. All that
one can examine is whether they are broadly compatible with the fluxes
obtained in this study. One way is to compute the eastward transport of
3He through 52∘ W in the upper 300 m. Using the 2003 CLIVAR
(Climate and Ocean: Variability, Predictability and Change) A20 section and
geostrophic velocities relative to 200 dbar (data are publicly available
from http://cchdo.ucsd.edu) (Jenkins and Stanley, 2008), the peak
transport south of 38∘ N is 1.4 µmol s-1. When this
transport is averaged over the area of the northern half of the Sargasso Sea
(approximately 3 × 106 km2), this corresponds to a flux
of ∼ 0.5 amol m-2 s-1 or
∼ 15 pmol m-2 yr-1 in 2003. The second calculation is
based on the work of Qiu and Huang (1995), who estimated an obduction rate
ranging from 50 to 250 m yr-1 in the northern Sargasso Sea (their
Fig. 7f). Typical excess 3He concentrations range from 0.02 to
0.04 pmol m-3 at 300 m depth, so one infers an upward 3He flux
ranging from 1 to 10 pmol m-2 yr-1. The 3He flux determined
in this study is 7.9 pmol m-2 yr-1 and thus fits within the
range of estimates of flux due to obduction.