Turbulent nitrate fluxes in the Amundsen Gulf
during ice‐covered conditions
P. S. Galbraith,
and Y. Gratton
Received 28 April 2011; revised 21 June 2011; accepted 23 June 2011; published 2 August 2011.
 Turbulence and nitrate measurements collected in the
Amundsen Gulf during ice ‐covered conditions in fall 2007
are combi ned to prov ide mean v ertical pr ofiles of e ddy
K and diffusive nitrate fluxes F.Themean
diffusivity (with 95% confidence intervals) was maximum
near the uppermost sampling depth (10 m) w ith
3(2, 5) × 10
and decreased exponentially to a
depth of ∼50 m, below which it was roughly constant at
the background value
nitraclin e, centered around 62 m de pth, was subject to an
eddy diffusivity close to the background value
mean diffusive nitrate flux across the nitracline was
0.5(0.3, 0.8) mmol m
. These observations are
compared with other regions and the role of vertical mixing
on primary production in the Amundsen Gulf is discussed.
Citation: Bourgault, D., C. Hamel, F. Cyr, J.‐É. Tremblay, P. S.
Galbraith, D. Dumont, and Y. Gratton (2011), Turbulent nitrate
fluxes in the Amundsen G ulf during ice‐ covered cond itions,
Geophys. Res. Lett., 38, L15602, doi:10.1029/2011GL047936.
 Nutrient replenishment of the surface layer in the
Amundsen Gulf occurs principally during ice‐covered con-
ditions (November to May), when primary production is at its
minimum [Tremblay et al., 2008]. Since nitrogen is the lim-
iting element for primary producers in this region, the
strength of its replenishment is thought to control overall
annual productivity [Tremblay and Gagnon, 2009]. Nitrogen
supply to the surface layer may come horizontally, from
rivers and surrounding marginal seas, vertically, from up-
wellings and turbulent diffusion of nutrient‐rich bottom
layers [Lewis et al., 1986], as well as from in situ biological
processes such as ammonification and nitrification [Tremblay
et al. , 2008]. While observations exist about the total con-
tribution of these sources to nitrate uptake in the Amundsen
Gulf [Tremblay et al., 2008], little is known about each
process taken separately. This is particularly true for the
contribution of turbulent diffusion due to past difficulties of
obtaining coincident turbulence and nitrate gradient mea-
surements. While such observations now become more
commonly available in ice‐free environments (see references
in Table 1), they are still rare in mobile ice‐covered arctic
3] In 2007–2008, during the International Polar Year, a
large multidisciplinary research initiative called the Cir-
cumpolar Flaw Lead (CFL) System Study was conducted to
study the general oceanographic conditions in the Amund-
sen Gulf through an annual cycle [Barber et al., 2010]. One
novelty of the sampling strategy consisted in keeping the
Canadian research ice‐breaker CCGS Amundsen mobile
throughout fall and winter in the Amundsen Gulf, in contrast
to the overwintering fixed within the fast‐ice of Franklin
Bay during the Canadian Arctic Shelf Exchange Study
(CASES) [Fortier et al., 2008]. We synthesize here about
five weeks of almost coincident turbulence and nitrate
measurements collected during the CFL campaign to esti-
mate the turbulent nitrate flux in the Amundsen Gulf during
2. Sampling Conditions and Methods
 Measurements were collected aboard the CCGS
Amundsen while drifting with large mobile ice floes in
the Amundsen Gulf (Figure 1) between 16 November and
19 December, 2007, the year with the record‐low ice cover
minimum for the Arctic as a whole [Maslanik et al., 2007].
The mean and standard deviation drift speed during sampling
was 0.08 ± 0.07 m s
, according to GPS records. During the
sampling period ice coverage was greater than 90% and made
principally of first‐year ice, 2–10 km wide vast floes, 50 to
70 cm thick (Canadian Ice Service, Environment Canada,
5] Dissipation rates of turbulent kinetic energy (in
) were calculated as = (15/2)nhu
i, where n is
kinematic viscosity and u
is the microscale (∼cm) vertical
shear [e.g., Sundfjord et al., 2007; Martin et al., 2010;
Schafstall et al., 2010]. The latter is measured with an airfoil
shear probe SPM‐38‐1 and pressure sensor mounted on a
loosely‐tethered free‐fall vertical microstructure profiler
(VMP‐500) manufactured by Rockland Scientific Interna-
tional. The hisymbol represents 4‐m scale averaging with
instrumental noise removed prior to averaging. Such dissi-
pation measurements are generally accepted to be accurate
to within a factor of 2 [Oakey, 1982]. The VMP is also
equipped with SeaBird SBE‐3F and SBE‐4C sensors for
fine‐scale (∼dm) T‐S measurements from which the density
r is calculated using the equation of state of seawater. The
VMP was deployed through the CCGS Amundsen moon
pool. Since the ship draft is 7.18 m, the top 10 m of profiles
are discarded from the analysis to avoid ship contamination.
Institut des Sciences de le Mer de Rimouski, Université du Québec
à Rimouski, Rimouski, Quebec, Canada.
partement de Physique, Université de Sherbrooke, Sherbrooke,
partement de Biologie, Université Laval, Quebec, Quebec,
Maurice Lamontagne Institute, Fisheries and Oceans Canada,
Mont‐Joli, Quebec, Canada.
Centre Eau Terre Environnement, Quebec, Quebec, Canada.
Copyright 2011 by the American Geophysical Union.
GEOPHYSICAL RESEARCH LETTERS, VOL. 38, L15602, doi:10.1029/2011GL047936, 2011
 The turbulent diffusivity of nitrate was calculated as
K = G/N
[Osborn, 1980], with G = 0.2, N
[e.g., Sharples e t al.,2007;Rippeth et al.,
2009; Martin et al., 2010; Schafstall et al., 2010]. Note
that although this model for K was initially derived for shear
mixing it has proven adequate by Sundfjord et al. [2007,
Figure 12] in a similar ice‐covered coastal arctic environ-
ment (Barents Sea) where double‐diffusion mixing may
have been present. Furthermore, the Kelley  parame-
terization for double ‐diffusion of salt applied to our CTD
data suggests that double‐diffusion mixing was negligible in
the Amundsen Gulf during the sampling period (not shown).
7] Overall, 175 VMP profiles collected at 26 different
stations within the Amundsen Gulf were used in the analysis
(Figure 1). Generally, four consecutive VMP profiles were
collected at every station except for two where 55 and 24
profiles were collected. Sampling periods roughly spanned
the range of wind speed conditions occurring during the 5‐
week survey period presented here (Figure 2) with a slight
bias towards low wind conditions; the mean wind speed
during turbulence sampling was 80% of the mean occurring
during the entire survey.
8] Nitrate (NO
) concentrations N (in mmol m
measured with a Satlantic Isus V3 nitrate sensor fixed under-
neath a rosette sampler. At some stations, bottle samples
were also collected and nitrate concentration determined
from la boratory an alyses as detailed by Tremblay et al.
. The Isus sensor measurements were then post‐
calibrated by linear regression against 151 samples from
12 stations. The calibration yielded a correlation coefficient
R = 0.91 and a standard error ±2.2 mmol m
Québec‐Océan, personal communication, 2011), consistent
with the manufacturer accuracy specification of ±2 mmol m
The minimum concentration that could be detected with
this sensor is 0.5 mmol m
. The measurements were then
averaged into 4‐m bins matching the dissipation rate data.
Figure 3 shows a typical 4‐m scale calibrated profile com-
pared with bottled samples. Although the Isus sensor is
characterized by some systematic deviations relative to the
bottle profile, it captures satisfactorily well the position and
strength of the nitracline, which is essential for the analysis
presented here, with around 15% difference in its maximum
gradient and 10% difference in its position as defined by the
maximum gradient. Note also that very low concentrations
(<0.5 mmol m
) near the surface (10–20 m, Figure 3) are
below the reliable detection capacity of the Isus sensor.
Overall, 71 nitrate profiles were grouped and averaged per
station, providing 26 nitrate profiles.
9] Profiles of vertical turbulent nitrate fluxes (in
) were calculated by combining VMP and
nitrate observations through F = −KN
× 86 400 s d
of the 175 K profiles was associated with the closest of the
26 nitrate profiles, providing 175 profiles of nitrate fluxes F.
10] Measurements were synthesized into averaged pro-
files considered to be representative of conditions prevailing
in the Amundsen Gulf throughout the sampling period. As
Table 1. Comparisons of Nitrate Turbulent Fluxes Reported in the
Literature From Different Regions of the World Ocean
Reference Region F (mmol m
Martin et al.  Porcupine Abyssal Plain 0.09
Horne et al.  Georges Bank 0.047–0.18
Lewis et al.  Subtropical North Atlantic 0.14
Law et al.  Antarctic Circumpolar Current 0.17
This study Amundsen Gulf (>90% i.c.) 0.5
Carr et al.  Equatorial Pacific 0.1–1
Sundfjord et al.  Barents Sea (40–90% i.c.) 0.1–2
Rippeth et al.  Irish Sea 1.5
Law et al.  Northern North Atlantic 1.8
Sharples et al.  Celtic Sea Shelf Edge 1.3–3.5
Hales et al.  New England Shelf Break 0.8–5
Hales et al.  Oregon shelf O(10
Sharples et al.  New Zealand Shelf 12
Schafstall et al.  Mauritanian Upwelling Region 120
The v alues reported may represent, depending on studies, the flux
through the nitracline, through the base of the euphotic zone or through
the base of the mixed layer. Values are sorted from lowest to highest. A
was used for converting nitrate concentration
abbreviation i.c. stands for ice coverage.
Figure 1. Map and bathymetry (m) of the Amundsen Gulf
and positions of the 26 stations where turbulence and nitrate
profiles were collected in November–December 2007.
Figure 2. Wind speed observations in the Amundsen Gulf
during the sampling period. NCEP‐NARR reanalysis (solid
curve), CCGS Amundsen navigati on anemomet er reporte d
in the science log book during sampling operations (black
dots), and meteorological science station aboard the CCGS
Amundsen (circles). The black lines at the to p ind icate the
sampling periods reported here.
BOURGAULT ET AL.: NITRATE FLUXES IN THE AMUNDSEN GULF L15602L15602
recommended by Baker and Gibson , the mean (X )of
small data sets (10–100 samples) of turbulence variables
that are approximately lognormally distributed in the ocean,
such as and K, was estimated using the maximum likeli-
X = exp(m + s
/2), where m and s
arithmetic mean and variance of ln(X), respectively. The
mean of other variables (
, N , F ) was estimated using
the standard arithmetic mean.
11] Ninety‐five percent confidence intervals on means
were determined by bootstrap analysis. Unless otherwise
specified the numbers in parentheses provided next to mean
values represent the lower 2.5% and upper 97.5% confi-
dence intervals on the mean. For symmetric confidence
intervals the symbol ± is used.
 On average over the sampling period and region,
nitrate concentrations exhibited a two‐layer structure with
minimum concentration of
= 2.7 ± 0.5 mmol m
near the surface (10–20 m) and maximum N
= 15.6 ±
0.5 mmol m
at 150 m depth (Figure 4). Note however that
very low concentration near the sea surface were not
captured reliably with the Isus sensor (see section 2 and
Figure 3) and bottled samples rather average to
= 0.5 ±
0.3 mmol m
. The mean position, and standard deviation,
of the nitracline was
= −62 ± 12 m, which is roughly 15 m
below the pycnocline (Figure 4), and was characterized with
a mean gradient (
= −2.0 ± 0.1 mmol m
13] Mean dissipation rates of turbulent kinetic energy
were maximum at 10 m depth with
= 4.3(2.6, 7.3) ×
and decreased approximately exponentially
with depth to the minimum value
= 1.5(1.1, 2.1) ×
around 100 m (Figure 4). Note that the gray
zones in Figure 4 show confidence intervals on the means
and thus provide no information on the variability. The
dissipation rate varies by 5 orders of magnitude at 10‐m
depth and are lognormally distributed in the range 10
. At greater depth (>50 m) the variability spans
about 3 orders of magnitude in the range 10
14] Eddy diffusivity was maximum at 10 m, with K
5(3, 9) × 10
, and decayed exponentially to about
50 m depth, below which it stayed approximately constant
down to 150 m (Figure 4). A least squares fit with boot-
strapped 95% confidence intervals yielded the following
piecewise analytical function for the depth‐dependance of
the mean eddy diffusivity:
for 46 z 10 m
for 150 z < 46 m;
= 1.1(0.7, 1.8) × 10
, d = 0.17 ± 0.02 m
= 3.4(2.3, 5.1) × 10
(Figure 4). The
nitracline, being typically located at a greater depth than
46 m, was therefore subject to an eddy diffusivity close to
the background value
15] The mean nitrate turbulent diffusive flux was in the
F < 6 mmol m
throughout the profile
(Figure 4). Through the nitracline it was
= 0.5(0.3, 0.8)
 In comparison to other estimates available throughout
the world ocean, the mean turbulent nitrate flux reported
here for the Amundsen Gulf during ice‐covered conditions
Figure 3. Example of (left) a typical nitrate profile and
(right) its gradient (3 December 2007). The triangles repre-
sent measurements from laboratory analyses of bottled water
samples a nd the solid line s r epresent th e 4‐m scale cali-
brated Isus ‐V3 sensor measurements.
Figure 4. Averages of buoyancy frequency squared N
, dissipation rate , eddy diffusivity K, nitrate concentration N and
vertical nitrate flux
F for the Amundsen Gulf. Gray shadows are 95% confidence intervals. Only positive values greater than
of nitrate fluxes are presented. The black solid line in the third plot is the best fit provided by equation (1)
along with the 95% confidence intervals (dashed lines). Note that the depth scale starts at 9 m.
BOURGAULT ET AL.: NITRATE FLUXES IN THE AMUNDSEN GULF L15602L15602
is comparable, in terms of order of magnitude, to most ice‐
free offshore ocean regions such as the Porcupine Abyssal
Plain, the Northern North Atlantic, the Southern Ocean or
the Equatorial Pacific as well as to the ice‐covered Barents
Sea (Table 1). On the other hand, this mean flux is about an
order of magnitude smaller than values reported for more
energetic environments like shelves, and two orders of
magnitude smaller compared to the Mauritanian upwelling
region (Table 1).
17] While some of the studies listed in Table 1 concluded
that vertical turbulent mixing may dominate nitrate uptake
in surface layers and may control the net community pro-
ductivity [e.g., Lewis et al., 1986; Sharples et al., 2007;
Hales et al., 2009; Rippeth et al., 2009], other studies have
reached opposite conclusions. For example, while Schafstall
et al.  reported one of the highest turbulent nitrate
flux to date (Table 1), they concluded that it only represented
10%–25% of what was required to support the net com-
munity production along the Mauritanian Upwelling Region.
They suggested that vertical advection and lateral eddy fluxes
may provide the missing nitrate supply. Similarly, Martin
et al.  concluded that vertical mixing contributed
little (about 2%) to the total nitrate uptake in the euphotic zone
in the Porcupine Abyssal Plain. They considered other phys-
ical processes, such as those associated with mesoscale phe-
nomena, but also hypothesized that biological nitrification
could provide as much, or perhaps even more, nitrate to the
euphotic zone than turbulent mixing.
18] Returning to the context of the Amundsen Gulf of fall
2007, we found that the total rate of nitrate supply above the
= 14.6 ± 2.7 mmol m
, as deter-
mined from a linear fit to 8 groups of bottle samples col-
lected from 5 November 2007 to 9 January 2008 (not shown
but with R
= 0.81, p < 0.001 and following Tremblay et al.
19] The contribution from turbulent mixing to this rate
could be estimated by dividing the turbulent flux through
the nitracline F
by the thickness of the nitracline ∣z
and averaging over all samples. This gives
9(5, 14) mmol m
from turbulent diffusion alone.
Comparing these values (i.e.
) suggests that turbu-
lent mixing contributed on average to 60% of the total
nitrate uptake in the Amundsen Gulf during fall 2007.
20] This conclusion contrasts with that of Tremblay et al.
 who hypothesized that vertical mixing contributed
little, compared to nitrification processes, to nitrate uptake
under the immobile landfast ice of Franklin Bay (Figure 1)
during fall‐winter 2003/04. However, we note that the
nitracline in Franklin Bay during fall‐winter 2003/04 was up
to an order of magnitude weaker than during fall 2007 with
gradients in the range −0.4 ≤ (N
≤−0.2 mmol m
(determined from Tremblay et al. [2008, Figure 3]), com-
pared to (
= −2.0 ± 0.1 mmol m
for fall 2007.
Assuming that the nitracline in 2003 was subject to the same
background diffusivity as in 2007 of
= 3.4 × 10
and letting the nitracline depth to be 40 m during fall 2003
[Tremblay et al., 2008] yields (
/40 m] ×
86 400 s d
, from turbulent diffu-
sion alone. Comparing this with the total rate reported by
Tremblay et al.  for fall 2003 of (
= 13.2 ±
2.5 mmol m
suggests that 8% to 20% of the nitrate
supply in 2003 may have been from vertical turbulent dif-
fusion. This supports Tremblay et al.’s  hypothesis
that renewal of nitrate from vertical mixing in fall 2003 in
Franklin Bay may not have been the dominant mechanism.
 Our observations show that while the surface layer
may be subject to large diffusivities, the nitracline is
essentially subject to the low background diffusivity
For two‐layer models where the interface is set around the
nitracline, or the pycnocline [e.g., Shadwick et al., 2011], it
appears reasonable to use a constant background diffusivity
to model turbulent diffusive fluxes of tracers across the
layers. However, if mean turbulent diffusivity is needed
within the surface layer [e.g., Else et al., 2011] the empirical
relationship given by equation (1) is proposed.
22] Our analysis supports the conclusion of Tremblay
et al.  that turbulent diffusion may have played a
secondary role in nitrate uptake in Franklin Bay in 2003.
However, we reached an opposite conclusion for the
Amundsen Gulf for fall 2007 where 60% of total nitrate
supply may have come from turbulent diffusion. It is unclear
at this point whether these opposite conclusions were
reached because we are comparing two different regions or
years. However, the observations presented here provide a
source for testing sea ice‐ocean‐biological models [e.g.,
Lavoie et al., 2009] from which insights regarding the
functioning of the coastal arctic ecosystem in a changing
climate could be gained. Such model assessments against
field measurements are critically needed because turbulence
parameterization remains one of the greatest uncertainties in
climate prediction. The information provided here may help
to progress rapidly in that direction.
23] Acknowledgments. Th is compon ent of th e CFL p rogr am was
funded by the Canadian International Polar Year (IPY) program office,
the Natura l Scie nces and Engineering Resea rch Council ( NSERC), a nd
the Canada Foundation for Innovation (CFI) and is a contribution to the sci-
entific program of Québec‐Océan. Thanks to Pascal Guillot for processing
the nitrate data, Matthew Asplin and Brent Else for providing us with GPS
and wind data and Dan Kelley for fruitful discussion on statistics and dou-
 The Editor wishes to acknowledge Tom Rippeth and an anony-
mous reviewer for their assistance in evaluating this paper.
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D. Bourgault, F. Cyr, and D. Dumont, Institut des Sciences de le Mer de
Rimouski, Université du Québec à Rimouski, 310, Allée des Ursulines, CP
3300, Rimouski, QC G5L 3A1, Canada. (email@example.com)
P. S. Galbraith, Maurice Lamontagne Institute, Fisheries and Oceans
Canada, 850 route de la Mer, Mont‐Joli, QC G5H 3Z4, Canada.
Y. Gratton, Centre Eau Terre Environnement, 490 de la Couronne,
Québec, QC G1K 9A9, Canada.
C. Hamel, Département de Physique, Université de Sherbrooke,
Sherbrooke, QC J1K 2R1, Canada.
J.‐É. Tremblay, Département de Biologie, Université Laval, Pavillon
Alexandre‐Vachon, Québec, QC G1V 0A6, Canada.
BOURGAULT ET AL.: NITRATE FLUXES IN THE AMUNDSEN GULF L15602L15602