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Turbulent vertical nitrate fluxes were calculated using new turbulent microstructure observations in the Lower St. Lawrence Estuary (LSLE), Canada. Two stations were compared: the head of the Laurentian Channel (HLC), where intense mixing occurs on the shallow sill that marks the upstream limit of the LSLE, and another station located about 100 km downstream (St. 23), more representative of the LSLE mean mixing conditions. Mean turbulent diffusivities and nitrate fluxes at the base of the surface layer for both stations were, respectively (with 95% confidence intervals): K HLC = 8.6(3.2, 19)  10−3 m2 s−1, K23 = 4.4(2.3, 7.6)  10−5 m2 s−1, F HCL = 95(18, 300) mmol m−2 d−1, and F23 = 0.21(0.12, 0.33) mmol m−2 d−1. Observations suggest that the interplay between large isopleth heaving near the sill and strong turbulence is the key mechanism to sustain such high turbulent nitrate fluxes at the HLC (two to three orders of magnitude higher than those at Station 23). Calculations also suggest that nitrate fluxes at the HLC alone can sustain primary production rates of 3.4(0.6, 11) g C m−2 mo−1 over the whole LSLE, approximately enough to account for a large part of the phytoplankton bloom and for most of the postbloom production. Surfacing nitrates are also believed to be consumed within the LSLE, not leaving much to be exported to the rest of the Gulf of St. Lawrence.
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RESEARCH ARTICLE
10.1002/2014JC010272
Turbulent nitrate fluxes in the Lower St. Lawrence Estuary,
Canada
Fr
ed
eric Cyr
1,2
, Daniel Bourgault
1
, Peter S. Galbraith
3
, and Michel Gosselin
1
1
Institut des sciences de la mer de Rimouski, Universit
eduQu
ebec
a Rimouski, Rimouski, Qu
ebec, Canada,
2
Now at Royal
Netherlands Institute for Sea Research, Den Burg, Netherlands,
3
Ocean and Environmental Science Branch, Department of
Fisheries and Oceans Canada, Maurice Lamontagne Institute, Mont-Joli, Qu
ebec, Canada
Abstract Turbulent vertical nitrate fluxes were calculated using new turbulent microstructure observa-
tions in the Lower St. Lawrence Estuary (LSLE), Canada. Two stations were compared: the head of the Lau-
rentian Channel (HLC), where intense mixing occurs on the shallow sill that marks the upstream limit of the
LSLE, and another station located about 100 km downstream (St. 23), more representative of the LSLE
mean mixing conditions. Mean turbulent diffusivities and nitrate fluxes at the base of the surface layer for
both stations were, respectively (with 95% confidence intervals):
KHLC 58:6ð3:2;19Þ31023m2s21;
K23 5
4:4ð2:3;7:6Þ31025m2s21;
FHLC 595ð18;300Þmmol m22d21;and
F23 50:21ð0:12;0:33Þmmol m22d21.
Observations suggest that the interplay between large isopleth heaving near the sill and strong turbulence
is the key mechanism to sustain such high turbulent nitrate fluxes at the HLC (two to three orders of magni-
tude higher than those at Station 23). Calculations also suggest that nitrate fluxes at the HLC alone can sus-
tain primary production rates of 3:4ð0:6;11ÞgCm
22mo21over the whole LSLE, approximately enough to
account for a large part of the phytoplankton bloom and for most of the postbloom production. Surfacing
nitrates are also believed to be consumed within the LSLE, not leaving much to be exported to the rest of
the Gulf of St. Lawrence.
1. Introduction
Nutrient cycling in the global ocean controls the primary production through nutrients availability in the
euphotic zone. By fixing atmospheric carbon during photosynthesis, phytoplankton growth also plays an
important role in regulating anthropogenic CO
2
concentrations in the atmosphere [e.g., Tsunogai et al.,
1999; Thomas et al., 2004; Arrigo, 2005]. Nutrient and carbon cycles are therefore closely related and their
understanding is crucial for modeling Earth’s future climate.
The coastal oceans play a key role in the dynamics of these cycles because they act as buffering zones
between the continents, from where they receive large amounts of nutrients and organic matter from land
drainage, and the deep ocean, with which they exchange nutrients, particles, and energy. Because of this
buffering effect, they are among the most physically and biogeochemically active regions of the oceans
[Gattuso et al., 1998; Borges, 2005]. Although they occupy a small fraction of the ocean surface (7%), they
sustain about 15–30% of the primary production and contribute to 20–50% of the carbon sequestration in
the oceans [Wollast, 1998; Tsunogai et al., 1999; Thomas et al., 2004; Muller-Karger, 2005]. Large tidally
induced turbulent mixing that typically characterizes coastal zones directly affects the magnitude of the
oceanic carbon uptake, because primary production sustained by turbulent diapycnal nutrient fluxes is
much more efficient for sequestrating carbon than the regenerated production resulting from nutrient recy-
cling [Falkowski, 2000; Richardson et al., 2000; Sharples et al., 2001a; Allen et al., 2004; Rippeth, 2005; Rippeth
et al., 2009]. The aim of this study is thus to explore turbulent diapycnal nutrient fluxes in a region of the
world where strong turbulence is believed to sustain high (nearly as high as spring bloom level) primary
production rates throughout summer: the Lower St. Lawrence Estuary (LSLE), generally considered part of
the Gulf of St. Lawrence (GSL), Canada (Figure 1).
The Gulf of St. Lawrence (Figure 1, inset) is a deep and stratified coastal sea with areas of strong tidally
induced turbulence and/or upwellings, as well as large freshwater inputs. The LSLE is deep in that its typical
depth (>300 m) is much greater than the thicknesses of surface and bottom boundary layers (10 m)
Key Points:
First direct estimation of nitrate
fluxes in the Lower St. Lawrence
Estuary
Fluxes reported are among the
highest found in the world ocean
Fluxes sustain high primary
productivity throughout the summer
Correspondence to:
F. Cyr,
frederic.cyr@nioz.nl
Citation:
Cyr, F., D. Bourgault, P. S. Galbraith,
and M. Gosselin (2015), Turbulent
nitrate fluxes in the Lower St.
Lawrence Estuary, Canada, J. Geophys.
Res. Oceans,120, 2308–2330,
doi:10.1002/2014JC010272.
Received 4 JUL 2014
Accepted 24 FEB 2015
Accepted article online 26 FEB 2015
Published online 27 MAR 2015
Corrected 13 APR 2015
This article was corrected on
13 APR 2015. See the end of the
full text for details.
CYR ET AL. V
C2015. American Geophysical Union. All Rights Reserved. 2308
Journal of Geophysical Research: Oceans
PUBLICATIONS
[Bourgault et al., 2012]. According to Egbert and Ray [2000], the GSL and the Bay of Fundy basins together
occupy the 10th rank among the world coastal seas and shelves for their tidal dissipation level. The GSL is also a
biologically rich area hosting many commercially important fish and crustacean species. With landings of about
3–4 310
5
metric ton (t) a year, it sustained about 20% of the eastern Canadian fisheries prior to the mid-90s
ground fish decline [Chadwick and Sinclair, 1991; de Lafontaine et al., 1991]. Historical research on nutrient
dynamics and primary and secondary production has thus been considerable in the GSL, although some impor-
tant processes are still not fully understood such as the nutrient supply to the system by turbulent mixing and
upwelling.
The surface nutrient distribution was studied during the International Biological Program [Steven, 1971,
1974]. A major result of this program was that nutrient supply to the euphotic zone of the GSL was coming
from upwelling within the LSLE (Figure 1, main plot), a large-scale estuary (the width is many times the
internal Rossby radius) located upstream of the GSL. The nutrient supply to the GSL by the LSLE was
referred by Steven [1971] as the nutrient pump. Further studies suggested that within the LSLE, most of the
nutrient surfacing from deeper layers occurs at a localized area at the head of the Laurentian Channel (HLC)
near Tadoussac [Ingram, 1975; Greisman and Ingram, 1977; Ingram, 1979a, 1983].
The Laurentian Channel is a long (>1000 km) and deep (>290 m) submarine valley that originates on the
continental slope, runs across the Gulf and ends near Tadoussac where the total depth abruptly shallows
from 325 m to about 50 m in less than 15 km (Figure 1). It is also where the Saguenay Fjord connects and
exchange waters with the LSLE. It has been suggested that intense vertical mixing occurs at this sill, but
direct measurements of turbulence have never been collected.
Three water layers are present in the LSLE/GSL system and these circulate with an estuarine-like
dynamics affected by rotation along the Laurentian Channel [e.g., Koutitonsky and Bugden, 1991;
Tadoussac
Rimouski
Pointe−des−Monts
Ile−Rouge
Saguenay
River
Stat. 23
Stat. 25
Stat. 24
Stat. 22
70oW 30’ 69oW 30’ 68oW 30’ 67oW
48oN
20’
40’
49oN
20’
Lon
g
itude
Latitude
Depth (m)
0100 200 300
Cabot
Strait
Laurentian
Channel
Gulf of
St. Lawrence
LSLE
25
24
22 21
20 19 18
17
16
Figure 1. Map and bathymetry of the Gulf of St. Lawrence (inset) and the Lower St. Lawrence Estuary (main plot). Sampling boxes for Stations 16–22, and Stations 24 and 25 have 50 3
50 and 20 320 km
2
, respectively. Location of monitoring Station 23 is also shown. The fixed station occupied twice in September 2012 is represented by a white star. Sites of the turbu-
lence profiles from the 2009 survey are identified with red dots.
Journal of Geophysical Research: Oceans 10.1002/2014JC010272
CYR ET AL. V
C2015. American Geophysical Union. All Rights Reserved. 2309
Saucier and Chass
e, 2000; Saucieretal., 2009]. The surface layer (upper 30–50 m) is generally fresher in
the LSLE compared to the GSL because of high freshwater input from the St. Lawrence and Saguenay riv-
ers. Freshwater inputs also drive the Gasp
e Current, a strong surface coastal jet current that contributes
to most of the LSLE output to the Gulf [Tang, 1980; Benoit et al., 1985; Koutitonsky and Bugden, 1991]. The
bottom layer (roughly below 150–200 m) is composed of salty nutrient-rich waters of Atlantic origin. In
between is found the cold intermediate layer (CIL), a remnant of the previous winter Gulf surface layer
that was trapped under the warmer/fresher surface waters at the onset of spring [Banks, 1966; El-Sabh,
1979; Koutitonsky and Bugden, 1991; Gilbert and Pettigrew, 1997; Galbraith, 2006; Smith et al., 2006].
Waters below the CIL temperature minimum, which lies roughly at a depth of 60–100 m, have high and
almost constant nutrient concentrations [Steven, 1974]. The vertical exchanges between the nutrient-
rich layer and the surface layer are however generally low, because of the weak turbulent ventilation
that is also responsible for hypoxic conditions in the deep LSLE [Gilbertetal., 2005; Bourgault et al.,
2012].
While spring blooms that occur in the Gulf leaves the surface layer generally nutrient-depleted, the nutrient
concentrations in the LSLE surface waters remain high [Steven, 1971, 1974]. This is because both the inter-
mediate and the bottom layers are thought to be partly upwelled and vertically mixed at the HLC [Ingram,
1979a, 1983; Saucier et al., 2009]. About 75% of the surface nutrients found in the LSLE may therefore origi-
nate from the CIL because of this upwelling/mixing mechanism [Greisman and Ingram, 1977; Savenkoff
et al., 2001], the remaining part being attributed to the St. Lawrence and Saguenay rivers discharge. These
vertical nutrient fluxes at the HLC sustain a high primary productivity in the LSLE, with daily production
rates during the summer nearly equivalent to those during spring blooms [Levasseur et al., 1984; Therriault
and Levasseur, 1985; Plourde and Runge, 1993; Plourde et al., 2001]. This high primary productivity sustains
high levels of secondary production that is then exported to the Gulf, mostly via the Gasp
e Current [Fortier
et al., 1992; Plourde and Runge, 1993]. Recently, Ouellet et al. [2013] also suggested that the LSLE has an
important role for the development and growth of the GSL capelin population, which itself is important for
biomass transfer to upper trophic levels. Nutrient pumping at the HLC is thus likely a keystone for food web
dynamics, not only for the LSLE but also for the Gulf.
In contrast to previous studies which indirectly inferred vertical nutrient fluxes at the HLC [Greisman and
Ingram, 1977; Savenkoff et al., 2001], this study presents direct measurements of turbulence profiles from
which vertical nutrient fluxes are derived. The study focuses mainly on nitrate fluxes since dissolved nitro-
gen is thought to be the limiting nutrient in the system [Steven, 1974; Levasseur and Therriault, 1987]. Com-
parison will also be made between observed mixing and fluxes at the HLC and at another station located
about 100 km downstream.
2. Methodology
2.1. Nutrient Concentration Data
Nutrient concentrations were obtained from the Ocean Data Management System public database [Fisheries
and Oceans—Canada, 2013]. All water bottle measurements of NO
3
1NO
2
(nitrate plus nitrite) concentra-
tions available for the period 2000–2012 and between April and November are considered. These measure-
ments are also accompanied with other physical measurements such as temperature and salinity. Except
for Station 23, these measurements are located within a square box roughly the width of the Laurentian
Channel and centered on oceanographic stations 16–25 (Figure 1). These stations were selected since they
have been routinely visited for multidisciplinary studies in the GSL [e.g., Benoit et al., 2006; Lehmann et al.,
2009]. Since Station 23 has been visited quasi-weekly from May to November by scientists from the Maurice
Lamontagne Institute as part of a monitoring program (actual Station Rimouski in the Atlantic Zone Monitor-
ing Program [Plourde et al., 2008; Galbraith et al., 2014]), these measurements were selected. All other meas-
urements were grouped per station. This method is similar to that of Bourgault et al. [2012], except a box of
20 320 km
2
is considered here for Station 25 instead of 10 310 km
2
. On average, 54 profiles were
extracted per station. Station 23 contains the highest number of casts (n5254), while Station 24 contains
the least number (n57).
Since NO
3
1NO
2
concentration measurements are from various investigators, different methods were used
[Clesceri et al., 1989; Grasshoff et al., 1999; Mitchell et al., 2002]. To the best of our knowledge, they were all
Journal of Geophysical Research: Oceans 10.1002/2014JC010272
CYR ET AL. V
C2015. American Geophysical Union. All Rights Reserved. 2310
measured with autoanalyzers, whether of type Alpkem, Technicon II, or Bran-Luebbe 3. For the remainder
of the article, we will refer to NO
3
1NO
2
concentrations as nitrate concentration. This approximation is justi-
fied since for more than 95% of the water samples, NO
2
concentration represents less than 7% of the total
NO
3
1NO
2
concentration.
Another survey conducted 13 h sampling, i.e., covering the semidiurnal tidal period, on both 23 and 29 Sep-
tember 2012 from the R/V Coriolis II in proximity to Station 25 (see white star in Figure 1). During station
occupation, conductivity-temperature-depth (CTD) casts were conducted nearly every hour with a Sea-Bird
SBE 9. Every 3 h, Niskin bottle samples were taken for nutrient concentration analyses. An echo sounder
(Simrad EK-60) and a 150 kHz Acoustic Doppler Current Profiler (RDI-ADCP) were also sampling the water
column during this survey.
2.2. Turbulence Data
Turbulence measurements were collected with a free falling, loosely tethered Vertical Microstructure Profiler
(VMP500) from Rockland Scientific International (RSI), deployed from a small boat. This profiler is equipped with
Sea-Bird Electronic sensors for fine scale (10
21
m) measurements of pressure, temperature T,andpractical
salinity. Salinity measurements presented in this study have been converted to absolute salinity S
A
(g kg
21
)
[McDougall and Barker, 2011]. Along with other microscale (10
22
m) sensors, the VMP is equipped with two
airfoil shear probes (SPM-38 from RSI) that allow measurements of the microscale vertical shear @u0
@z

.
A total of 817 turbulence profiles were collected at Station 23 during summers 2009–2012. Most have
already been used in two previous studies [Cyr et al., 2011; Bourgault et al., 2012]. As they were collected
from a small boat, they were conducted in relatively calm sea conditions. The maximum depth of VMP casts
at this station varied between 180 and 325 m (bottom depth).
Our team also collected 207 turbulence profiles at the HLC near Station 25 between 29 September 2009
and 2 October 2009 (red dots in Figure 1), a period corresponding to a neap-tide phase of the fortnightly
tide cycle (smallest high tide on 27 September). To avoid snagging the profiler on the rocky bottom, profiles
at the HLC were performed as close as possible to the seabed (our target was to reach within 2–5 m of the
seabed) without intentionally hitting it. These observations were also carried out under relatively calm sea
conditions (the wind generally did not exceed 20 km h
21
except for 30 September where it reached 40 km
h
21
for an hour at the nearest meteorological station on Ile Rouge). During the VMP sampling at the HLC, a
600 kHz RDI-ADCP was deployed on the side of the boat at a depth of about 1 m below the surface. The ver-
tical resolution was 0.5 m and ensembles of 35 pings were averaged every 10 s. This allowed current meas-
urements (U,V) from which the vertical shear (S25@U
@z

21@V
@z

2,ins
22
) was calculated.
Turbulence data reduction for both stations was achieved using a procedure similar to that described in
previous studies in the LSLE [e.g., Cyr et al., 2011; Bourgault et al., 2012] and briefly summarized here. Dissi-
pation rates of turbulent kinetic energy (,inWkg
21
) were calculated by [e.g., Lueck et al., 2002; Sundfjord
et al., 2007; Rippeth et al., 2009; Martin et al., 2010]:
515m
2
@u0
@z

2
;(1)
where m5f(T) is the kinematic molecular viscosity (in m
2
s
21
) as a function of temperature and the overline
indicates here a vertical 1 m bin averages. The shear variance @u0
@z

2was obtained by spectral integration
with care taken to exclude, when necessary, high wave number instrumental noise.
Turbulent diffusivities (K,inm
2
s
21
) were calculated from the dissipation rates as:
K5
C
N2:(2)
Here N252g
q
@q
@zis the buoyancy frequency squared (in s
22
), g59:81 m s22the gravitational acceleration, q
the density sorted for inversions (in kg m
23
), and C50.2, the flux parameter, taken here constant [Osborn,
1980; Moum et al., 2002, 2004; Burchard, 2009; Rippeth et al., 2009; Holtermann et al., 2012]. Turbulent fluxes
(F) of any nutrient can be calculated by combining turbulent diffusivity profiles (K(z)) and vertical gradient
of nutrient concentration with
Journal of Geophysical Research: Oceans 10.1002/2014JC010272
CYR ET AL. V
C2015. American Geophysical Union. All Rights Reserved. 2311
FðzÞ52KðzÞ@CðzÞ
@z;(3)
where C(z) is the nutrient concentration profile. As presented further in the text, nitrate fluxes are calculated
here, using the salinity profiles measured by the VMP as proxies for nitrate concentration profiles.
3. Observations
3.1. Nutrient Concentration
Two examples of mean nitrate concentration profiles resulting from our analysis are shown for Stations 25
and 23 (Figure 2). Note that Station 25 has a lower number of observations (n525, including the Septem-
ber 2012 survey) compared to the monitoring Station 23 (n5254). The result of the bootstrap is shown as
error bars where the range is the 95% confidence interval on the mean value. For these two stations in the
LSLE, nitrate concentration profiles exhibit a two-layer structure, with nearly constant lower concentrations
in the top 50 m of the water column and a constant maximum value below about 200 m. Although the
water column is undersampled in the transition zone between these two layers, the gradual decrease of
nitrate concentration between 50 and 200 m suggests that the nitracline lies in this depth range.
Binned observations for all stations were vertically and horizontally linearly interpolated between averaged
values to obtain a nitrate concentration transect along the Laurentian Channel from Stations 25 to 16
0 10 20
0
50
100
150
200
250
300
350
Station 25 Station 23
CNO3
(mmol m−3)
Depth(m)
0 10 20
CNO3
(mmol m−3)
Figure 2. Nitrate concentrations for (left) Stations 25 and (right) 23. Gray dots are all available water bottle samples from 2000 to 2012. Pur-
ple dots on Station 25 profiles are the observations from the two campaigns carried out at a fixed station in September 2012. Error bars
represent the mean value and its 95% confidence interval obtained from bootstrap analysis in 10 m depth bins. Shaded profiles are fits
obtained with equation (3) at Station 23 and at the HLC (the closest VMP sampling to Station 25).
Journal of Geophysical Research: Oceans 10.1002/2014JC010272
CYR ET AL. V
C2015. American Geophysical Union. All Rights Reserved. 2312
(Figure 3). Highest surface nutrient concentrations are found in the LSLE (Stations 25–21). Generally low
nitrate concentrations are found in surface waters for the rest of the Gulf. Deep (>200 m) waters of the Lau-
rentian Channel have more or less a constant nitrate concentration. There is also a subsurface minimum of
nitrate concentration near 50 m between Stations 24 and 22. This suggests that high concentration in sur-
face waters is the result of advection of nutrient-rich waters from upstream (i.e., from the HLC) rather than
local vertical mixing at these stations.
A look at one of the two 13 h time series near Station 25 gives insights on the behavior of the temperature,
salinity, and nitrate concentration at the HLC during a semidiurnal tidal cycle (Figure 4). Visible in tempera-
ture and salinity fields is the large vertical excursions reaching up to 60 m. Such large vertical excursions are
also visible in the nitrate time series, although the lower temporal resolution of the bottle sampling may be
misleading. For example, while the temperature and salinity below 50 m plunge by nearly 60 m between
17:00 and 21:00, nitrate concentration remains constant in the interpolated field because no bottle sample
was taken during this period. The relationship between salinity and nitrate concentration was determined
by a scatterplot of all available measurements in the GSL/LSLE (Figure 5). The relationship is stronger for
data far from the surface and the bottom, i.e., for SA32;34:3gkg
21, for which a linear relationship gives
(gray line in Figure 5a):
~
CNO35aSA1bin ½mmol m23;(4)
with a57:35 mmol m23kg g21and b52227 mmol m23. The salinity range used to establish this relation-
ship was selected from visual inspection of the data set and is a trade-off between the goodness of the fit
(now with a correlation coefficient R50.94) and the desire of taking into account the largest portion of the
water column. Note that this relation was established for profiles taken between April and November, but
the inclusion of winter months does not significantly change the coefficients aand bsince the seasonal
cycle of nitrate concentration is small for this salinity range (not shown). Near the surface, salinities lower
than SA532 g kg21represent the portion of the water column affected by winter mixing and for which the
relationship is not expected to hold. At salinities greater than 34.3 g kg
21
(i.e., near the bottom), nitrate con-
centrations have a small tendency to decrease as the salinity increase. This break from the tight nitrate-
salinity relation for SA32;34:3gkg
21occurs near a deep temperature maximum that corresponds to a
water mass end-member. Waters of higher salinity are a mixture of this end-member with saltier but colder
water waters of lower nitrate concentrations. Denitrification may also play a role in the decrease since the
5
5
10
10
10
10
15
15
15
15
20
20
20
20
20
22
22
22
22
22
22
22
24
24
24
24
24
24
Depth (m)
16171819202122232425
|| LSGELSL
Distance from Stat. 25 (km)
0 100 200 300 400 500 600 700
0
50
100
150
200
250
300
350
400
Figure 3. Climatological nitrate concentrations (in mmol m
23
) along the Laurentian Channel (April–November, 2000–2012). Dashed-lines
represent Stations 25–16 of the transect (see Figure 1).
Journal of Geophysical Research: Oceans 10.1002/2014JC010272
CYR ET AL. V
C2015. American Geophysical Union. All Rights Reserved. 2313
deepest parts of the LSLE are subject to hypoxia. The goodness of the fit for SA32;34:3gkg
21also sug-
gests that this layer is never ventilated throughout its journey from the mouth of the Laurentian Channel to
the HLC, i.e., where it is upwelled/mixed.
The relationship established in equation (3) is used to estimate nitrate concentration profiles from
VMP casts. Examples of such inferred nitrate concentration estimates are presented in Figure 5b for
two profiles from the same semidiurnal tidal cycle, one taken just downstream from the sill (thick
lines) and one taken on the shallow portion above the sill (thin lines). Comparison between both
salinity profiles (black curves) suggests the profile over the sill is essentially a compressed version of
the seaward profile resulting from the advection of the later toward shallower waters. This translates
in the nitrate concentration profiles (cyan curves) by changing the depth range for which the rela-
tion is valid. For the profile downstream from the sill, the relation fails above 60 m, while above the
sill the relation is valid from the bottom (35 m) to a depth of about 15 m. The mean nitrate concen-
tration profiles approximated from the VMP sampling at Station 23 and nearby Station 25 are given
in Figure 2 (gray shades).
0
20
40
60
80
100
120
T (°C)
3
3.5
4
4.5
5
Depth (m)
0
20
40
60
80
100
120
SA (g kg−1)
30
31
32
Time (UTC) − 23 Se
p
t. 2012
12 14 16 18 20 22
0
20
40
60
80
100
120
CNO3
(mmol m−3)
5
10
15
Figure 4. Semidiurnal time series (13 h) of (top) temperature, (middle) salinity, and (bottom) nitrate concentration for a fixed station
occupied on 23 September 2012 (see white star near Station 25 in Figure 1). Temperature-salinity casts are identified with dotted-lines and
water sample bottles with black asterisks. The high tide was at 13:03 and the low tide at 19:03. The nearest maximum spring tide occurred
on 18 September 2012.
Journal of Geophysical Research: Oceans 10.1002/2014JC010272
CYR ET AL. V
C2015. American Geophysical Union. All Rights Reserved. 2314
Internal tides, well known to be generated at the HLC [e.g., Forrester, 1970, 1974; Ingram, 1979b; Wang et al.,
1991; Galbraith, 1992; Cyr et al., 2015], can generate large vertical excursions such as those observed in Fig-
ure 4. At this frequency, the internal tide that predominantly emanates from the head is consistent with a
Poincar
e-type wave in the second vertical mode and first horizontal mode with a wavelength of about 35–
60 km [Forrester, 1974; Galbraith, 1992]. Evidence that the vertical excursions observed for T,S
A
, and CNO3in
Figure 4 are the result of an internal tide is suggested by what resembles a pinching and spreading of the
isopleths at a node located at a depth of about 20–30 m, typical of a vertical mode-2. The clearest illustra-
tion of such behavior is seen the top plot of Figure 4, where isotherms pinching is centered at about 14:00
and spreading is maximum at about 19:00. These occur, respectively, near high and low tides in Tadoussac
(respectively, at 13:03 and 19:03). Surface waters are coldest when isotherms located over the node depth
rise toward the surface at low tide. Nitrate concentrations are also maximum in surface waters near low
tide, likely the result of the same mechanism.
In the salinity field, fresher waters are found in the top 10 m of the water column at low tide. This is con-
trary to what might be expected since saltier water should follow the surfacing of colder and nitrate-rich
water. An increase in the freshwater release from the St. Lawrence and the Saguenay rivers when the baro-
tropic tidal pressure is minimum (i.e., at low tide) may explain this different behavior as suggested by previ-
ous studies [e.g., Drainville, 1968; Saucier and Chass
e, 2000]. In other words, the salt input to the surface
water by the vertical mode-2 internal tide is hidden under a more important freshwater release.
3.2. Turbulence Observations and Nitrate Fluxes
A time series of VMP sampling reveals that very high dissipation rates of turbulent kinetic energy occurred
above the sill (Figure 6a). In comparison, mixing at a sloping boundary about 100 km seaward from the sill
rarely exceeded 51025Wkg
21while above the sill it often exceeded 51024Wkg
21(Cyr et al., 2015).
Note that this figure is presented relative to the time of the profiles rather than the alongshore distance. In
20 25 30 35
0
5
10
15
20
25
SA (g kg−1)
CNO3
(mmol m−3)
a
0−32 g kg−1
32−34.3 g kg−1
>34.3 g kg−1
26 28 30 32 34
0
20
40
60
80
100
120
Depth (m)
SA (g kg−1)
6 8 10 12 14 16
CNO3
(mmol m−3)
Figure 5. Nitrate concentration relationship with other physical data. (a) Scatterplot of nitrate concentration versus salinity for all 4548
measurements available from all stations. In red, measurements with salinities lower than SA532 g kg21. In magenta, measurements with
salinities greater than SA534:3gkg
21. For the 1407 measurements with SA5½32;34:3gkg
21(black), the correlation coefficient with a lin-
ear least squares fit (thin gray line) gives R50.94. (b) Salinity profiles (black) from two casts realized on 1 October 2009. In cyan, nitrate
profiles inferred from equation (3). The first cast was located in the deep area seaward of the sill at 13:32 (thick lines) and the second above
the sill at 18:40 (thin lines). These time references can be found in Figure 6.
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fact, the tidal currents reversed when the boat was nearly above the shallowest portion of the sill (18:45)
and the time series from 17:00 to 20:30 is more or less a back and forth displacement above the sill (see the
inset for profile positions).
Away from the sill (i.e., before 16:30), dissipation rates were relatively low with some higher patches near
the surface and the seabed. As the sill was approached, isopycnals rose by more than 20 m above the first
bathymetric peak (at 17:00) and plunged behind it. This corresponds to high dissipation rates on the lee
side of this peak. These vertical displacements are also visible in the temperature time series (Figure 6b).
The CIL (black lines) that lies at a depth of about 90–100 m before 14:00 is pushed over the sill (20–40 m) at
about 19:00. Isopycnals are also compressed, generating sharp interfaces where, as will be shown later, tur-
bulence driven by shear instabilities likely take place (Figure 6a). On the shallowest portion of the sill (i.e.,
after 17:30), most of the water column is highly turbulent. A lens of lighter water appeared at the surface at
about 17:45, roughly corresponding to high tide. At this time, we visually observed a well-defined front at
the surface. A sharp pycnocline also appears at about 10 m depth, separating two relatively well mixed
water masses. Strongest mixing occurred in the upper layer. Visual surface indications of ascending and
descending motions were also visible from the boat at 20:00 and 20:30. These corresponded to the occur-
rence of steep isopycnals in parts of the water column (Figure 6a). Vertical drops at depths between 10 and
30 m in the temperature panel (Figure 6b) starting at about 17:30 also suggest either high-frequency inter-
nal waves or vigorous mixing in the upper part of the water column.
Depth (m)
a
20
40
60
80
100
120
140
log10(ε / W kg−1)
−9
−8
−7
−6
−5
Stat. 25
13:32
20:32
18:29
01−Oct−2009
Depth (m)
b
14:00 15:00 16:00 17:00 18:00 19:00 20:00
0
20
40
60
80
100
120
140
T (°C)
0
1
2
3
4
5
6
Figure 6. Example of a sampling carried out on 1 October 2009 near Station 25. (a) Dissipation rates of turbulent kinetic energy (). Isopyc-
nals are also plotted in background for reference. Geographical position of each cast can be roughly followed with the inset figure. (b)
Temperature field linearly interpolated between casts. The thick black line is the 1C isotherm. Except for the shallowest portion of the sill,
the gray area for both plots is the maximum depth of the casts which is our best approximation in this rapidly changing topography since
casts were performed as close as possible to the seabed (see section 2). On the shallowest portion of the sill, where the maximum depth is
less than 35 m, the bottom is that estimated from ADCP measurements.
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The relationship established in equation (3) was used to infer, for each VMP cast, a corresponding nitrate
profile (~
CNO3). These were then combined with diffusivity profiles to calculate instantaneous fluxes using
equation (2) with F5FNO3ðzÞand CðzÞ5~
CNO3. These are calculated in mmol m22s21but expressed further
in the text in mmol m22d21. Is worth noting that these fluxes still represent instantaneous fluxes, although
expressed with units where daily time scales appear.
Figure 7 shows nitrate fluxes and concentrations over the sill. Strong turbulence generally resulted in high
nitrate fluxes (FNO3102;103mmol m22d21, Figure 7a). This figure also illustrates how advection/upwell-
ing brings deeper nutrient-rich waters over the sill where they can mix. Nitrate isopleths are also closer to
each other over the sill (see also discussion concerning Figure 5b), generating sharper gradients and likely
enhancing fluxes. As suggested later in the discussion, the interplay between strong turbulence and the
tidal advection of deeper nutrient-rich water above the sill is the key to sustain the high-nutrient fluxes
observed here.
Although mixing mechanisms are difficult to isolate from this time series, observations from the 29 Septem-
ber 2012 13 h survey illustrate one turbulent mechanism leading to high-nutrient fluxes at the HLC (Figure
8). This echogram, combined with currents, density, and nitrate observations, shows how Kelvin-Helmholtz
instabilities develop at early flood tide (14:35–14:40) as a result of a shear layer centered at about 60 m. The
Richardson number Ri 5N2
S2

, an index of the water column stability relative to turbulent shear instabilities,
suggests that the shear was sufficiently strong to dynamically destabilize the stratification Ri <1
4

. Here N
2
and S
2
are averaged over 1 m size vertical bins. These conditions led to the development of 30 m thick
Depth (m)
a
20
40
60
80
100
120
140
log10 (FNO3
/ (mmol m−2 d−1))
−3
−2
−1
0
1
2
3
Stat. 25
13:32
20:32
18:29
01−Oct−2009
Depth (m)
b
14:00 15:00 16:00 17:00 18:00 19:00 20:00
0
20
40
60
80
100
120
140
CNO3
(mmol m−3)
5
10
15
20
Figure 7. Same sampling as in Figure 6, but for (a) nitrate fluxes (FNO3) and (b) nitrate concentrations. For both plots, the white portion in
the upper part of the figures correspond to the portion of the water column where SA<32 g kg21.
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billows that stirred about a quarter of the water column. Such billows eventually break into turbulent mix-
ing and produce important salt, heat, and nutrient fluxes.
Unfortunately, we do not have concomitant turbulent observations with this echogram. We can neverthe-
less provide an order of magnitude estimate of the associated diffusivity and nutrient flux from the vertical
scale H10
1
m of the billows and the measured buoyancy frequency N10
22
s
21
, estimated from the
density profile around the shear layer in Figure 8. An order of magnitude calculation suggests a diffusivity
of order KCNH
2102131022s213102m21021m2s21. The associated nutrient flux using @CNO3
@z
1021mmol m24then suggests F2K@CNO3
@z1022mmol m22s21. This is a high flux (equivalent in other
units to 103mmol m22d21) representative of an episodic but very energetic event.
An example of such episodic events observed during our surveys with the turbulence profiler is provided in
Figure 9. This figure is a subset of data from Figure 6 corresponding to the upper 35 m of the water column,
between about 17:00 and 20:30. Strong shear layers (top plot) generally correspond to regions of high dissi-
pation (middle plot), delimited from the regions of lower dissipation by strong density gradients. Between
18:00 and 18:15, structures resembling Kelvin-Helmholtz billows are visible in the ADCP echogram.
Although these billows are smaller than those presented in Figure 8, VMP casts through them suggest that
the nitrate fluxes involved just below these instabilities are of the same order of magnitude, i.e., FNO3103
mmol m22d21(bottom plot).
To obtain longer-term averaged quantities, we computed averaged profiles for N
2
,,K, and FNO3from our
207 casts at the HLC near Station 25 and from our 817 casts at Station 23 (Figure 10). The envelope of these
profiles is the bootstrapped 95% confidence interval on the average, calculated assuming log-normal distri-
bution of the turbulent variables [Baker and Gibson, 1987]. While sampling at the HLC is slightly biased with
more casts near high tide, the sampling at Station 23 is not (see insets in the leftmost plots). This bias is dis-
cussed later in the text. Since the VMP sampling is slightly outside the square box of Station 25 (see red
dots in Figure 1), these observations are grouped under the tag HLC or Station HLC to make the clear dis-
tinction with Station 25, although they are spatially very close.
The stratification (given by N
2
) was nearly the same between Stations HLC and 23, except for the top 25 m,
where it was higher at the HLC. The dissipation rates () and the diffusivity (K) were higher at the HLC than
Station 23 for most of the depth span. The difference is particularly important in the top 60 m of the water
Figure 8. The nutrient pump in action. Echogram at 120 kHz from an echo sounder mounted below a drifting boat on 29 September 2012 (see location in Figure 1) shows how Kelvin-
Helmholtz instabilities develop at early flood tide (14:35–14:40). Alongshore currents u(east and north currents rotated by 52), density (r
t
), gradient Richardson number (Ri), and nitrate
concentrations (CNO3) are also provided. Note that density and nitrate concentration profiles have been linearly interpolated to their respective time from casts outside the limits of the
figure. These allow an estimation of the instantaneous vertical nitrate flux (see text).
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column where the diffusivity at the HLC was nearly constant with values near K1022m2s21. For the 25–
50 m depth range, a range justified further in the text,
KHLC 54:5ð1:1;13Þ31022m2s21and
K23 54:4ð2:3;7:6Þ31025m2s21, 3 orders of magnitude lower. Here numbers in parentheses represent the
bootstrapped 95% confidence interval on the averaged value.
Mean turbulent nitrate fluxes (FNO3) are also presented in Figure 10. Missing data at the top of the mean
profiles represent the portion of the water column where salinities were always lower than 32 g kg
21
(i.e.,
above 37 m at Station 23 and above 12 m at the HLC). Fluxes at the HLC were higher than at Station 23
for most of the water column, often by orders of magnitude. Since Figure 2a suggests that the nitrate-
Depth (m)
0
5
10
15
20
25
30
35
log10(S2 / s−2)
−6
−5
−4
−3
−2
−1
0
Depth (m)
17:00 18:00 19:00 20:00
0
5
10
15
20
25
30
35
log10(ε / W kg−1)
−9
−8.5
−8
−7.5
−7
−6.5
−6
−5.5
−5
log10(FNO3
/ mmol m−2 d−1)
−2
0
2
01−Oct−2009
17:30 17:45 18:00 18:15 18:30 18:45 19:00 19:15
10
20
30
Figure 9. Close-up view of the time series from Figure 6. (top) The shear (S
2
) from the ADCP recorder and (middle) the dissipation rates of
TKE are presented. (bottom) Enlargement of the middle plot where nitrate fluxes are presented over the ADCP echogram. Note that for a
better visualization, the bottom plot is scaled differently from other plots and only one cast out of two is presented. Missing parts of the
fluxes profiles correspond to the region where SA<32 g kg21.
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depleted layer roughly corresponds to the top 50 m of the water column, we calculated the mean flux
between 25 and 50 m as a measure of replenishment of the surface layer. This depth range is above the
nitracline (estimated to lie between 50 and 200 m in section 3.1), but encompasses the limit often consid-
ered between the surface and the cold intermediate layer [e.g., Sinclair et al., 1976; Therriault and Levasseur,
1985; Plourde and Runge, 1993; Savenkoff et al., 2001; Plourde and Therriault, 2004]. This interval has also
been chosen to represent the flux at the base of the euphotic zone, typically found at a depth of 10–20 in
the LSLE [Therriault and Levasseur, 1985; V
ezina, 1994; Sime-Ngando et al., 1995]. The mean fluxes in the 25–
0
50
100
150
200
250
300
cast dist.(%)
Stat. 23
Depth (m)
−5−3 −1 1 3 5
0
10
20
tHT(h)
10−4 10−3
0
50
100
150
200
250
300
Stat. HLC
cast dist.(%)
N2 (s−2)
Depth (m)
−5−3 −1 1 3 5
0
20
40
tHT(h)
10−810−710−610−510−4
ε (W kg−1)
10−5 10−4 10−3 10−2 10−1
K (m2 s−1)
10−2 100102
FNO3
(mmol m−2 d−1)
Figure 10. Buoyancy frequency squared (N
2
), dissipation rate of TKE (), turbulent diffusivity (K), and turbulent nitrate flux (FNO3) for Stations 23 and HLC, respectively. The gray intervals
are the 95% confidence interval on the averaged profile. Insets in leftmost plots are the distribution of the casts relative to the closest high tide time (t
HT
50 h).
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50 m depth range, expressed with two significant figures, are
FHLC 5120ð23;400Þmmol m22d21and
F23 50:21ð0:12;0:33Þmmol m22d21, respectively, for Stations HLC and 23.
At the transition depth between the bottom layer and the CIL, the nitrate fluxes averaged over the 100–
150 m depth ranges were
FHLC 54:2ð0:4;17Þmmol m22d21and
F23 50:15ð0:10;0:24Þmmol m22d21.
Note that for fluxes calculations at Station 23, the diffusivity profiles used are from the station itself, i.e., far
from the channel sloping boundaries. As suggested by Cyr et al. [2011], the fluxes reported for this station
could be increased by 60% to account for boundary mixing processes.
4. Discussion
4.1. How Representative Are Fluxes at the HLC?
While fluxes calculated at Station 23 are representative of a long-term research effort (2009–2012) and are
not biased toward any tidal phase (semidiurnal or fortnightly), those at the HLC are calculated only from a 4
day campaign. In this section, we explore how representative of the long-term average these fluxes are.
Figure 10 (bottom inset) suggests that the observations at the HLC are biased within a semidiurnal cycle,
with more observations in the reversal phase near the high tide (t
HT
50 h). A closer look at the flux calcu-
lated from single VMP casts suggests that while the vertical nitrate concentration gradients do not change
much during a semidiurnal cycle, the turbulent diffusivities and turbulent fluxes are distributed along a bell-
shaped curve centered at high tide and spanning orders of magnitude on the vertical axis (Figure 11). The
short reversal period between ebb and flood currents thus drives most of the nitrate fluxes at the HLC as
Figure 11. Semidiurnal modulation of the turbulent flux and the terms composing its calculation for observations at the head of the Lau-
rentian Channel. (a) Turbulent diffusivity. (b) Vertical gradient of nitrate concentration. (c) Turbulent nitrate fluxes. Each dot is an average
over one VMP cast in the 25–50 m depth range in relation to its phase relative to the time of the closest high tide in Tadoussac (t
HT
50 h).
The number of points in Figures 11b and 11c are different than in Figure 11a, because for some casts, the relation between S
A
and CNO3
was impossible to establish (salinities are out of the range of validity for equation (3)). The average of all observations (horizontal dashed
line) and its 95% confidence interval (shaded) are also plotted in each plot. Note that the vertical axes are scaled such that all plots span
the same number of orders of magnitude.
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suggested by the averaged values from all our observations (gray shading) that occur toward the top of the
curve. Our sampling thus captured the most important phase for the diffusivity and the flux calculations.
However, assuming that the statistical distributions presented in Figure 11 are representative of a standard
semidiurnal cycle, we can compensate for our observational bias. This can be done by recomputing aver-
ages and 95% confidence intervals by taking care that for each bootstrap random replicate, the number of
cast in the tHT 23;3h interval is approximately the same than in the rest of the semi-diurnal cycle
(tHT <23hort
HT
>3 h). For the 25–50 m depth range, this calculation leads to a slightly reduced nitrate
flux ~
FHLC 595ð18;300Þmmol m22d21. Here the tilde symbol denotes correction for sampling bias. For the
100–150 m depth range, the effect is more important with ~
FHLC 51:9ð0:9;3:7Þmmol m22d21. For the
remainder of the discussion, these corrected flux will be used for Station HLC. Note also that the same cor-
rection for the turbulent diffusivity in the 25–50 m depth range at the HLC leads to
~
KHLC 58:6ð3:2;19Þ31023m2s21.
This exercise confirms that most of the flux occurs in a very short period near high tide. The idea that epi-
sodic and strong mixing events dominate the averaged fluxes is becoming increasingly recognized,
whether for tidal [Sharples et al., 2007; Tweddle et al., 2013] or for wind mixing events [Williams et al., 2013].
It appears that fluxes at the HLC are also driven by episodic mixing events that seem to be occurring princi-
pally near high tides. The mechanisms causing such high fluxes will be explored in section 4.2.
It is also worth noting that the survey at the HLC was realized in neap-tide conditions. Historical observa-
tions in the LSLE however suggest that nutrient enrichment of the surface waters is more efficient in spring
tide conditions [Ingram, 1975; Sinclair, 1978; Demers et al., 1986]. Our estimate of the flux at the HLC may
therefore be conservative. The fortnightly difference of mixing in the LSLE was quantified by Saucier and
Chass
e[2000] in a numerical experiment, where they found that the buoyancy fluxes in the LSLE in spring
tide are more than the double those in neap tide. If the twofold change in buoyancy fluxes between neap
and spring tides reported by Saucier and Chass
e[2000] translates to the same difference in nitrate fluxes,
the nitrate input at the HLC may be higher than our estimate by a factor 1.5.
Finally, how representative are our fluxes measured during the early fall of the extended summer season
(i.e., between April and November)? Since the mixing involved here is mostly tidal, we can therefore
hypothesize that the energy release is about constant throughout the year, with intrinsic modulations due
the different tidal harmonics. It is however possible that variations in the water runoff from the St. Lawrence
and the Saguenay rivers may influence the mixing at the HLC. For the spring freshet (April–June), a recent
numerical study suggests that increase runoff also increases the vertical buoyancy flux in the LSLE, and thus
the vertical resuspension of nutrients [Saucier et al., 2009]. However, this hypothesis has never been vali-
dated with observations and such a task is beyond the scope of this study. Since for months outside of the
spring freshet the runoff is approximately constant on average [Bourgault and Koutitonsky, 1999] and
because September/October 2009 were close to climatological values (i.e., within one standard deviation of
the 30 year climatology) [Galbraith et al., 2010], we can therefore assume that our sampling is at least repre-
sentative of the July–November period.
4.2. The Nutrient Pump Mechanism
Our observations suggest that shear instabilities are one of the mixing mechanisms at work at the HLC. Fig-
ure 8 is a good example of such large instabilities driven by sheared currents that can lead to significant
nitrate fluxes with overturns as large as 30 m. These instabilities are likely driven by a complex mixture of
tidal currents funneled onto the sill, together with frontal activity resulting from the confluence of different
water masses (Figures 6 and 8). Internal tides also can generate turbulence by inducing shear in horizontal
currents during the vertical displacements of the waves. Bottom friction is another mechanism present at
the HLC, as suggested by the high shear and dissipation rates found in the near bottom region of Figure 9.
However, other sill processes are also likely to be encountered here such as lee waves, hydraulic jumps,
nonlinear internal waves, vortical structures, etc. [as documented in other similar coastal systems, e.g.,
Farmer and Armi, 1999; Nash and Moum, 2001; Klymak and Gregg, 2001, 2004; Armi and Farmer, 2002; Cum-
mins et al., 2003; Palmer et al., 2013]. Observational evidence of lee waves has already been reported to
occur in this area downstream of the sill as a result of ebb currents [see Saucier and Chass
e, 2000, Figure 15].
Although mixing through such mechanisms may have been sampled during our campaign (see, for exam-
ple, isopycnals rising over the sill at 17:00 in Figure 6 that may suggest hydraulic control), our limited
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observations likely do not give the complete portrait of turbulence generation at this sill. Although the
study would benefit from new turbulence measurements in the area, one conclusion of this short survey is
that mixing is high in the upper 60 m of the water column. Far from the HLC, it is however below this
depth that the nitrate concentration starts to increase (see, for example, the mean nitrate profile at Station
23, Figure 2). Without nitrate input closer to the upper layer, mixing would thus not sustain high levels of
surface water nitrate enrichment.
In counterpart, some of the mixing mechanisms described above imply large vertical displacements of the
nitrate isopleths. The large vertical displacements driven by the barotropic tide forced onto the sill (which
further generates internal tides, Figure 4) would not enrich the surface layer with nutrients if no mixing was
taking place. Isopleths would instead go up and back down without modifying the mean state. The inter-
play between vertical displacements and mixing is thus required to sustain the nutrient pump since one
mechanism alone is not sufficient to account for such high-nutrient fluxes in surface waters. The role of
intense vertical mixing near the surface as a necessary condition for nutrient enrichment was hypothesized
by Ingram [1975] and by Therriault and Lacroix [1976] who suggested that vertical displacement of deeper
water over the sill by the barotropic tide was not sufficient for the reason mentioned above. Without direct
turbulence measurements, Therriault and Lacroix [1976] had also hypothesized that the top 50 m was
undergoing intense vertical mixing based on a stratification index at the HLC.
As it was shown previously, a node in vertical displacement is present at a depth of about 20–30 m. Obser-
vations suggest that the surface nutrient enrichment by the internal tides occurs in two steps (see sketch in
Figure 12). During the pinching of the isopycnals by the internal tide at the node depth, nitrate isopleths
from below 60 m rise, enter the zone of vigorous turbulence and enrich the subsurface layer (Figure 12a).
When isopycnals diverge, newly enriched waters near the node depth are pushed to the surface by the
wave where further mixing ensues (Figure 12b). Near the HLC, this occurs at low tide, consistent with Figure
4 and with previous observations of Therriault and Lacroix [1976].
It is suggested in section 4.1 that the calculated nitrate turbulent fluxes at the HLC (18–300 mmol m
22
d
21
)
may be conservative estimates. Yet, they are among the highest reported in the literature (see Table 1). This
supports the efficiency of the pumping mechanism described above.
4.3. Contributions to the GSL Nutrient Budget
Sinclair et al. [1976] suggested that nutrient cycling in the LSLE/GSL system was not as hypothesized by Ste-
ven [1971], whereby the LSLE was acting as a nutrient supplier to the GSL. They rather suggested that the
surface estuarine transport of nutrients from the LSLE accounted for less than 1% of the nutrient supply to
the GSL and that its effect was geographically limited to the western portion of the Gulf. On the other hand,
Savenkoff et al. [2001] (from their Figures 6 and 10) calculated by inverse modeling that the nutrient supply
to the GSL by the LSLE could reach 40%.
In order to calculate the amount of nitrates brought to the surface during summer months, a surface area
representative of the flux at the head of the Laurentian Channel must be calculated. The 25 year sea surface
temperature (SST) climatology in the LSLE for the months of May–October, suggests that a cold SST anom-
aly emanates from the HLC (Figure 13). Since surfacing of deeper nutrient-rich waters should be accompa-
nied by cold water (see, for example, Figure 4), we can therefore assume that the region where nitrate are
brought to the surface at the HLC coincides with the coldest part of the SST anomaly. Three contours
(T55.35, 5.55, and 5.65C, thick black lines in Figure 13) were delimited to represent the area where the
fluxes can be hypothesized to occur. They have been chosen to represent 5%, 10%, and 15% of the coldest
pixels within the blue box of Figure 13 (calculated from the cumulative density function of temperature
pixel in the inset figure). These thresholds give estimated areas of 73, 161, and 230 km
2
, respectively. These
areas are also visually similar to the shoaling area suggested by the numerical work in Lavoie et al. [2000,
Figure 7). We can therefore assume that A10
2
km
2
is an order of magnitude estimate for the surfacing
area representative of the nitrate flux at the HLC. Figure 13 also suggests that surfacing nutrients at the HLC
are mostly advected seaward as a part of the estuarine circulation, preferably following the southern coast
of the LSLE (see also Gratton et al. [1988], for a study on surface cold anomalies).
From May to November (i.e., 150 days), the bias-corrected fluxes ~
FHLC 595ð18;300Þmmol m22d21calcu-
lated through this surface would lead to an upward pumping of 20 (4, 63) 310
3
t of nitrate in the surface
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waters of the LSLE. This amount of nitrate is comparable to the estimated seaward nutrient transport of 20
310
3
t of nitrate over the top 50 m, calculated by Sinclair et al. [1976] for the same period at the Rimouski
section, a transect across the LSLE passing through Station 23. These authors however pointed out that
such a seaward flux was insufficient to sustain the primary production in the Gulf of St. Lawrence.
Another study from inverse modeling suggests a mean seaward nitrate flux out of the LSLE of 460 mol s
21
over the top 30 m, equivalent to 83 310
3
t of nitrate if integrated from May to September, i.e., a little more
than our upper bound value [Savenkoff et al., 2001, Figure 6]. Note that this amount of nitrates is in excess of
what is consumed in the LSLE. The vertical nitrate flux integrated over the entire LSLE given by this inverse
model is 685 mol s
21
[Savenkoff et al., 2001, Figure 10]. To better compare with this estimate, we should
also take into account the vertical fluxes at Station 23, because although they are weaker than at the HLC
by two to three orders of magnitude (
F23 50:21ð0:12;0:33Þmmol m22d21), they are representative of a
much wider surface area (LSLE surface is 9000 km2). If we assume that fluxes at Station 23 are distributed
over this surface, and that fluxes at the HLC are distributed over 10
2
km
2
, the total vertical nitrate flux over
the whole LSLE, expressed in the same units as Savenkoff et al. [2001], vary between 33 and 400 mol s
21
,
i.e., smaller than the model result.
Whether this is an overestimation of the vertical nutrient pumping by the model or whether our results
presented here are underestimates is not clear. Additional nitrate sources by the rivers on the north
shore of the LSLE may partly account for this difference since they are not considered in the study of
Figure 12. Sketch of some of the processes leading to nitrate fluxes in the LSLE. The color backgrounds represent nitrate concentration on an arbitrary scale, are but based on the aver-
age transect of Figure 3 (for data within the dashed rectangle). Outside the dashed rectangle, concentration is extrapolated to the nearest value (no concentration data available from
above the sill). Internal tide isopleths heaving for (a) high and (b) low tides at Tadoussac are sketched with thin gray lines for an internal tide of vertical mode-2 with a wavelength of
60 km. Turbulent sill processes are also expected to occur driven by barotropic tidal currents. The interplay between the upwelling of nitrate-rich waters by internal tides and the strong
mixing near the sill leads to higher vertical nitrate fluxes (F) at the head of the Laurentian Channel compared to those at the Rimouski Station (located at about 100 km downstream of
the sill). (b) Surfacing nitrate-enriched water is advected by the estuarine circulation, creating a subsurface nitrate concentration minimum further downstream. Note that the mean
nitrate concentration background is not shown to heave up and down with the internal tide, nor it is shown compressed with isopycnals over the sill.
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Savenkoff et al. [2001], and the inverse model may compensate for missing sources by increasing the verti-
cal pumping. Too high local nitrate consumption in the LSLE or too high-nutrient export to the GSL in the
model may also cause such overestimation. Note however, in a best case scenario, i.e., by considering the
largest surface for the shoaling area (e.g., 230 km
2
) and by increasing the upper bounds of the 95% confi-
dence interval on
FHLC and
F23 by a factor 1.5 and 1.6, respectively (to account for neap-to-spring modula-
tion at HLC and boundary mixing effect in the LSLE), the maximum vertical fluxes would be 1300 mol s21,
enough to account for Savenkoff et al. [2001] results (685 mol s21). Our results suggest however that the
hypothesis from Sinclair et al. [1976] is more likely, i.e., that the LSLE plays a relatively minor role in supply-
ing nutrients to the GSL.
4.4. Nutrient Pumping in Sustaining Primary Production in the LSLE
In an attempt to estimate the LSLE primary production that could be sustained by nitrate fluxes at the HLC,
let us assume that the nitrate brought to the surface water of the HLC (over 10
2
km
2
) during a period of 1
month (30 days) is uniformly distributed over the whole LSLE (9000 km
2
). The resulting apparent nitrate flux
for the LSLE is: Fa595ð18;300Þmmol m22d21330d 3102km2
9000 km2532ð6;98Þmmol m22mo21. Given a Red-
field et al. [1963] uptake ratio by weight (carbon:nitrogen) of 7.7 [see also Levasseur and Therriault, 1987;
Levasseur et al., 1992], this suggests that the nitrate fluxes at the HLC could sustain a carbon (C) production
of about 3:4ð0:6;11ÞgCm
22mo21over the whole LSLE.
30’ 70oW 30’ 69oW 30’ 68oW 30’ 67oW
30’
48oN
30’
49oN
30’
Lon
g
itude
Latitude
30’ 70oW 30’ 69oW 30’ 68oW 30’ 67oW
30’
48oN
30’
49oN
30’
Stat. 25
T(°C)
2
3
4
5
6
7
8
9
10
11
12
2 4 6 8 10
0
0.2
0.4
0.6
0.8
1
CDF
T(°C)
Figure 13. Averaged sea surface temperature from May to October for the 1986–2010 climatology from AVHRR remote sensing at 1.1 km resolution. Black lines correspond to tempera-
ture contours T55.35, 5.55, 5.65C. These correspond to the coldest pixels (5%, 10%, and 15% in the cumulative density function, inset) within the blue rectangle. Square box around
Station 25 from Figure 1 is also shown for reference. These data where obtained from the Maurice Lamontagne Remote Sensing Laboratory and generously provided by P. Larouche.
Journal of Geophysical Research: Oceans 10.1002/2014JC010272
CYR ET AL. V
C2015. American Geophysical Union. All Rights Reserved. 2325
Estimates of the total (i.e., not only nitrate-based) primary production averaged over the whole LSLE are
given by Therriault and Levasseur [1985] and range between 28 and 44 g C m22mo21during the June-July
bloom and from 0:3to17gCm
22mo21for the rest of the year. This suggests that turbulent nitrate fluxes
at the HLC can sustain an important part of the bloom and the majority of the postbloom nitrate-based pri-
mary production in the LSLE. These results thus reaffirm that nutrient input from the St. Lawrence and the
Saguenay rivers plays a modest role in sustaining the primary production [Greisman and Ingram, 1977].
These results also suggest that the nutrient fluxes at the HLC are responsible for the high primary produc-
tion rates found throughout the summer in the LSLE.
Using more recent observations from the monitoring program at Station 23, the mean primary
production for years 2000–2003 between May and August (thus including the bloom), varied between 45
and 75 g C m22mo21and even reached 150 g C m22mo21in 1999 [Starr et al., 2004, Figure 6]. Although
these numbers are higher than those presented above, they may however not be representative of the
whole LSLE since production is spatially heterogeneous and Station 23 is located in the most productive
area [Therriault and Levasseur, 1985]. These budgets however reveal that nitrates pumped at the HLC are
almost entirely consumed in the LSLE, not leaving much for exportation in the Gulf. This is also suggested
by the rapid decrease of nitrate concentration in the surface waters between the LSLE and the GSL (Figure
3). This conclusion also supports the hypothesis that the LSLE exports mostly primary and secondary pro-
duction to the Gulf rather than nutrients [Sinclair et al., 1976; Fortier et al., 1992; Plourde and Runge, 1993].
It must be noted however that the calculation above is based on vertical fluxes derived from measurements
in neap-tide period and are likely a lower bound estimate. Again, the total nitrate input to the LSLE, and
thus the nitrate-based primary production may be raised by a factor 1.5 to account for the fortnightly differ-
ence (see section 3.2). This must be however considered with care and fortnightly changes of nitrate fluxes
should be studied more closely. Finally, if fluxes at Station 23 are also taken into account for the total verti-
cal nitrate fluxes, this would lead to an additional flux of 6:3ð3:6;9:9Þmmol m22mo21. This means that tur-
bulent diffusivity far from the HLC, although representative of a much wider area, can only sustain a modest
fraction of the total turbulent nutrient fluxes in the LSLE (4–60%, using 95% confidence interval extremes).
5. Conclusion
In a step toward constraining the nutrients cycle and therefore the primary productivity budget in the LSLE/
GSL system, nutrient fluxes resulting from strong interaction of the tides with a sill located the upstream
limit of the LSLE (the head of the Laurentian Channel) were calculated. Although a better characterization
of the mixing processes at the HLC is still required, the mechanics of the pump could be understood as an
Table 1. Turbulent Nitrate Fluxes in the World Ocean From Previous Studies (Updated From Bourgault et al. [2011])
a
Reference Region
Fðmmol m22d21Þ
Martin et al. [2010] Porcupine Abyssal Plain 0.09
Lewis et al. [1986] Subtropical North Atlantic 0.14
Law [2003] Antarctic Circumpolar Current 0.17
Horne et al. [1996] Georges Bank 0.047–0.18
Bourgault et al. [2011] Amundsen Gulf 0.5
Carr et al. [1995] Equatorial Pacific 0.1–1
Rippeth et al. [2009] Irish Sea 1.5
Williams et al. [2013] Celtic Sea (background) 1.3–1.6
Law et al. [2001] Northern North Atlantic 1.8
Sundfjord et al. [2007] Barents Sea 0.1–2
Hales et al. [2009] New England (Shelf Break) 0.8–5
Sharples et al. [2007] Celtic Sea (Shelf Edge) 1.3–9
Hales et al. [2005] Oregon Shelf 10
1
Schafstall et al. [2010] Mauritanian Upwelling Region 10
Li et al. [2012] California current system (frontal zone) 0–41
Sharples et al. [2001b] New Zealand Shelf 12
Tweddle et al. [2013] Celtic Sea (Jones Bank) 0.8–52
Williams et al. [2013] Celtic Sea (high wind events) 2–81
This study Lower St. Lawrence Estuary (sill) 18–300
a
The values reported are whether the flux through the nitracline, the base of the euphotic zone or the base of the mixed layer and
are sorted in terms of the higher-bound estimate.
Journal of Geophysical Research: Oceans 10.1002/2014JC010272
CYR ET AL. V
C2015. American Geophysical Union. All Rights Reserved. 2326
interaction between large isopleth heaving over the sill and high dissipation rates in the top 60 m of the
water column. Mechanisms leading to the strong dissipation are likely a mixture of shear instabilities,
hydraulic controls and water masses convergence driven by internal and barotropic tidal currents funneled
on a rough topography.
Calculations of vertical turbulent nitrate fluxes at the head of the Laurentian Channel allow us to put
together pieces of the LSLE/GSL nutrient dynamics puzzle that can be summarized as follows. The so-called
nutrient pump should be better seen as the nutrient supply to the LSLE by the HLC rather than nutrient sup-
ply to the GSL by the LSLE as it was first suggested by Steven [1971]. Results from this study support the
idea that high vertical nutrient fluxes at the HLC can sustain a large fraction of the bloom and postbloom
nitrate-based production in the LSLE. This suggests that the nutrients are consumed locally (in the LSLE),
leaving few for export to the GSL. The nutrient pump can however have indirect effects on the Gulf by feed-
ing secondary and tertiary producers that can be exported out of the LSLE, mostly via the Gasp
e Current.
The role of the LSLE in sustaining vertical fluxes of particulate carbon, and thus carbon sequestration is
indeed still an open question. With data from the GSL only, Rivkin et al. [1996] concluded that unlike other
systems, the gulf exports approximately the same amount of carbon to the bottom whether the surface
waters are undergoing bloom or nonbloom conditions. Since the composition of the export is changing
from more chlorophyllous material in bloom conditions compared to more fecal pellets in nonbloom condi-
tions, it may well be that the LSLE is a source of biogenic carbon for the GSL throughout the summer. In
other words, high primary productivity rates, sustained by high-nutrient input in the LSLE, occur during the
whole summer in the LSLE and may feed higher trophic levels that are rapidly exported to the GSL. Such an
increase of secondary or tertiary producers may lead to high nonchlorophyllous particulate carbon sinking
rates. New information on nutrient fluxes in the LSLE presented here may be used to test this hypothesis in
future studies.
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Acknowledgments
This work was funded by ‘‘Le Fonds de
recherche du Qu
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technologies,’’ the Natural Sciences
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Canada, the Canada Foundation for
Innovation and Fisheries and Oceans
Canada and is a contribution to the
scientific program of Qu
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The authors would like to thank Pierre
Larouche for providing sea surface
temperature data sets, R
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and Paul Nicot who were frequent
crew members during our summer
sampling campaigns, and C
edric
Chavanne, Luc Rainville, and two
anonymous reviewers for the careful
reading and the helpful comments
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available either through the St.
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Erratum
In the originally published version of this article, units where quantities were "per month" (mo
21
) were erroneously printed as "per mol"
(mol
21
). The errors have been corrected, and this version may be considered the authoritative version of record.
Journal of Geophysical Research: Oceans 10.1002/2014JC010272
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C2015. American Geophysical Union. All Rights Reserved. 2330
... The upward and downward [CH 4 ] gradients were, respectively, 0.15 and 0.11 μmol m −4 at station T1 and 0.015 and 0.067 μmol m −4 at station CH 4 . K e has been estimated to be 8.6 (range: 3.2-19) × 10 −3 m 2 s −1 for the 25-50 m depth range at the head of the LC (Cyr et al., 2015) and ∼2 × 10 −5 m 2 s −1 for the 100-275 m depth range determined at a station off Rimouski, about 100 km downstream of the head of the LC (Bourgault et al., 2012). The latter value has also been assumed for the LC in the GSL (Bourgault et al., 2012) and is thus used for station CH 4 in this study. ...
... The latter value has also been assumed for the LC in the GSL (Bourgault et al., 2012) and is thus used for station CH 4 in this study. The much higher K e at the head of the LC has been attributed to various sill-associated physical processes at this locality (Cyr et al., 2015). The net methane production rate (P CH4 , μmol m −3 s −1 ) can then be estimated as: ...
... μmol m −2 d −1 from the SMMax at station T1 to the surface. Taking an area of ∼100 km 2 with a K e value of 8.6 (range: 3.2-19) × 10 −3 m 2 s −1 (Cyr et al., 2015) yields 1.14 (range: 0.42-2.52) × 10 4 mol CH 4 d −1 or 1.03 (range: 0.38-2.28) ...
Article
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We report the first water‐column dissolved methane data set from the Estuary and Gulf of St. Lawrence (EGSL). Per surface‐water methane concentration and sea‐to‐air flux, the upper estuary behaved like a typical shallow macrotidal estuary, while the lower estuary and the gulf resembled outer shelf seas and ocean slopes, respectively. The EGSL emitted 166.3 (71.5–214.4) × 10⁶ mol CH4 year⁻¹ to the atmosphere, representing 0.3% (0.1%–0.4%) of the total emission from global estuarine environments. A net production of 11.7 × 10⁷ mol CH4 year⁻¹ was required to sustain this emission. Methane distributions in the upper estuary were dominated by physical mixing, while those in the lower estuary and the gulf bore characteristic subsurface maxima and deep minima shedding light on the methane consumption and production pathways. Elevated but highly variable near‐bottom methane concentrations (10.4–695.3 nmol L⁻¹) transpired over pockmarks on the seabed of the lower estuary, inferring an upward diffusive flux of up to ∼700 mmol CH4 m² d⁻¹. Hypoxia in the lower estuary bottom water had little influence on methane concentrations. Lab incubations yielded methane cycling rates from a net production of 0.0068 nmol L⁻¹ d⁻¹ to net consumption with turnover times of 33.3–263 days. Methane in the EGSL was isotopically enriched with ¹³C (δ¹³CCH4: −40.9‰ to −27.4‰ relative to Peedee Belemnite). This study reveals that the EGSL is a smaller proportional contributor to methane emission from estuarine environments and that complex physical‐biogeochemical interactions control methane cycling and isotopic composition in this vast estuarine system.
... The accepted view is that nutrients in the surface layer of the lower St. Lawrence Estuary originate from tidal-induced upwelling and internal waves at the head of the channel (Ingram, 1975(Ingram, , 1983Cyr et al., 2015) and/or entrainment of deep nutrient-rich water from the estuarine circulation as fluvial waters from the upper estuary flow to the sea (e.g., Steven, 1971). The magnitude and impact of these two vertical mixing processes on primary production across the whole lower estuary and gulf system are debated amongst observa-C. ...
... The magnitude and impact of these two vertical mixing processes on primary production across the whole lower estuary and gulf system are debated amongst observa-C. E. Bluteau et al.: Nitrate transport pathways tional and modeling studies (e.g., Cyr et al., 2015;Savenkoff et al., 2001;Jutras et al., 2020). Published observations for the St. Lawrence have typically focused on the nutrient transport from vertical mixing dynamics within the lower estuary instead of the fluvial loads. ...
... Using field observations, Cyr et al. (2015) quantified the nitrate supply at the head of the channel from vertical mixing processes in late summer with direct turbulence measurements. Their measured nitrate vertical fluxes ranged between 0.2 and 3.5 µmol m −2 s −1 (95 % bootstrapped confidence intervals). ...
Article
Full-text available
The St. Lawrence Estuary connects the Great Lakes with the Atlantic Ocean. The accepted view, based on summer conditions, is that the estuary's surface layer receives its nutrient supply from vertical mixing processes. This mixing is caused by the estuarine circulation and tides interacting with the topography at the head of the Laurentian Channel. During winter when ice forms, historical process-based studies have been limited in scope. Winter monitoring has been typically confined to vertical profiles of salinity and temperature as well as near-surface water samples collected from a helicopter for nutrient analysis. In 2018, however, the Canadian Coast Guard approved a science team to sample in tandem with its ice-breaking and ship escorting operations. This opportunistic sampling provided the first winter turbulence observations, which covered the largest spatial extent ever measured during any season within the St. Lawrence Estuary and the Gulf of St. Lawrence. The nitrate enrichment from tidal mixing resulted in an upward nitrate flux of about 30 nmol m−2 s−1, comparable to summer values obtained at the same tidal phase. Further downstream, deep nutrient-rich water from the gulf was mixed into the subsurface nutrient-poor layer at a rate more than an order of magnitude smaller than at the head. These fluxes were compared to the nutrient load of the upstream St. Lawrence River. Contrary to previous assumptions, fluvial nitrate inputs are the most significant source of nitrate in the estuary. Nitrate loads from vertical mixing processes would only exceed those from fluvial sources at the end of summer when fluvial inputs reach their annual minimum.
... This particular topography leads to upwelling of deep water under the action of tides, with subsequent mixing of the deep water with surface water (Ingram, 1983;Saucier et al., 2003). These deep waters are rich in nutrients, and with the additional contribution of riverine nutrient and organic matter fluxes (Hudon et al., 2017), it leads to high primary production in the LSLE (Therriault and Lacroix, 1976;Greisman and Ingram, 1977;Therriault and Levasseur, 1985;Cyr et al., 2015) and northwest GSL (nwGSL). The latter is separated from the LSLE by natural topographic features to the west (corresponding to the Pointe-des-Monts transect in Figure 1) and by Anticosti Island to the east. ...
... The shallow southern GSL, represented in large part by the Magdalen Shallows, receives part of the nutrients carried by the relatively fresh surface waters, although the importance of this nutrient source for local primary production is uncertain (Sinclair et al., 1976;de Lafontaine et al., 1991;Levasseur et al., 1992;Cyr et al., 2015). The northeast GSL, on the other hand, is less subject to the direct influence of freshwater runoff. ...
... The average simulated nitrate flux for year 2010 across the 46-m horizon over the area depicted on Figure 1 at the head of the Laurentian Channel (magenta box) is equal to 18 mmol N m −2 d −1 . Cyr et al. (2015) calculated fluxes between 18 and 300 mmol N m −2 d −1 in the area of maximal upwelling, that correspond to the western end of the box depicted in Figure 1. These nutrient-rich waters are mixed with the nutrient-rich fluvial input that lead to high nitrate concentration in the surface layer. ...
Article
Full-text available
The goal of this paper is to give a detailed description of the coupled physicalbiogeochemical model of the Gulf of St. Lawrence that includes dissolved oxygen and carbonate system components, as well as a detailed analysis of the riverine contribution for different nitrogen and carbonate system components. A particular attention was paid to the representation of the microbial loop in order to maintain the appropriate level of the different biogeochemical components within the system over long term simulations. The skill of the model is demonstrated using in situ data, satellite data and estimated fluxes from different studies based on observational data. The model reproduces the main features of the system such as the phytoplankton bloom, hypoxic areas, pH and calcium carbonate saturation states. The model also reproduces well the estimated transport of nitrate from one region to the other. We revisited previous estimates of the riverine nutrient contribution to surface nitrate in the Lower St. Lawrence Estuary using the model. We also explain the mechanisms that lead to high ammonium concentrations, low dissolved oxygen, and undersaturated calcium carbonate conditions on the Magdalen Shallows.
... To convert the vertical nitrate fluxes into mass loadings, we rely on the same techniques as Cyr et al. (2015) to determine the tidal-upwelling zone. This mixing process creates a surface signature of cooler water during summer (see Figure 13 of Cyr ...
... This waterway provides a freshwater source, confirmed by the AZMP's annual helicopter survey a few weeks later (Figure 4b). We attribute the relatively high salinities near the HLC to tidal upwelling and mixing that characterize this region throughout the year (Ingram, 1983;Galbraith, 2006;Cyr et al., 2015). At the HLC, nitrate concentrations in the upper 50-m were also lower than 275 water both upstream and downstream at comparable depths ( Figure 3a). ...
... We observed this subsurface nitrate-poor layer during other seasons (Figure 5b-d). Climatological averages show that a sub-285 surface nitrate minimum is typical of the LSLE's lower reaches during the ice-free months (see Figure 3 of Cyr et al., 2015). ...
Preprint
Full-text available
The St. Lawrence Estuary connects the Great Lakes with the Atlantic Ocean. The accepted view, based on summer conditions, is that the Estuary's surface layer receives its nutrient supply from vertical mixing processes. This mixing is caused by the estuarine circulation and tidal-upwelling at the Head of the Laurentian Channel (HLC). During winter when ice forms, historical process-based studies have been limited in scope. Winter monitoring has been typically confined to vertical profiles of salinity and temperature and near-surface water samples collected from a helicopter for nutrient analysis. In 2018, however, the Canadian Coast Guard approved a science team to sample in tandem with its icebreaking and ship escorting operations. This opportunistic sampling provided the first winter turbulence observations, which covered the largest spatial extent ever measured during any season within the St. Lawrence Estuary and Gulf. The nitrate enrichment from tidal mixing resulted in an upward nitrate flux of about 30 nmol m−2 s−1, comparable to summer values obtained at the same tidal phase. Further downstream, deep nutrient-rich water from the Gulf was mixed into the subsurface nutrient-poor layer at a rate more than an order of magnitude smaller than at the HLC. These fluxes were compared to the nutrient load of the upstream St. Lawrence River. Contrary to previous assumptions, fluvial nitrate inputs are the most significant source of nitrate in the Estuary. Nitrate loads from vertical mixing processes would only exceed those from fluvial sources at the end of summer when fluvial inputs reach their annual minimum.
... Nearshore coastal waters of Québec, specifically the eastern shore of James Bay and the north shore of the estuary and Gulf of St. Lawrence (EGSL), are under the freshwater runoff's influence from the numerous rivers draining the boreal Canadian shield watersheds. The EGSL is one of the major subarctic estuaries characterized by high phytoplankton production sustained by nutrient-rich upwelling in the lower estuary along the north coast (Le Fouest et al., 2006;Cyr et al., 2015), and by fluvial input loaded with nutrients (Therriault and Lacroix, 1976;Hudon et al., 2017). Freshwater runoff brings CDOM and SPM, which by modifying light attenuation and heating the upper part of the water column (Costoya et al., 2016), can affect photosynthesis and primary production of phytoplankton, macroalgae, and seagrass meadows. ...
Article
Full-text available
In most coastal waters, riverine inputs of suspended particulate matter (SPM) and colored dissolved organic matter (CDOM) are the primary optically active constituents. Moderate- and high-resolution satellite optical sensors, such as the Operational Land Imager (OLI) on Landsat-8 and the MultiSpectral Instrument (MSI) on Sentinel-2, offer a synoptic view at high spatial resolution (10–30 m) with weekly revisits allowing the study of coastal dynamics (e.g., river plumes and sediment re-suspension events). Accurate estimations of CDOM and SPM from space require regionally tuned bio-optical algorithms. Using an in situ dataset of CDOM, SPM, and optical properties (both apparent and inherent) from various field campaigns carried out in the coastal waters of the estuary and Gulf of St. Lawrence (EGSL) and eastern James Bay (JB) (N = 347), we developed regional algorithms for OLI and MSI sensors. We found that CDOM absorption at 440 nm [a g (440)] can be retrieved using the red-to-green band ratio for both EGSL and JB. In contrast, the SPM algorithm required regional adjustments due to significant differences in mass-specific inherent optical properties. Finally, the application of regional algorithms to satellite images from OLI and MSI indicated that the atmospheric correction (AC) algorithm C2RCC gives the most accurate remote-sensing reflectance (R rs) absolute values. However, the ACOLITE algorithm gives the best results for CDOM estimation (almost null bias; median symmetric accuracy of 45% and R 2 of 0.78) as it preserved the R rs spectral shape, while tending to yield positively bias SPM (88%). We conclude that the choice of the algorithm depends on the parameter of interest.
... Station 25 is an exception to this trend, appearing similar to stations 16 and 18 where the primary input of OM is from marine primary production. The higher levels of even n-alkanes is likely due to a combination of increased surface water primary production and subsequent increase in heterotrophic bacterial activity, resulting from the upwelling of the deep waters in this area (Cyr et al., 2015). ...
Article
Sediments comprise a multitude of inorganic and organic components, with much of the composition of the organics still not fully characterized. Our research targeted n-alkanes, to determine whether compound specific carbon and hydrogen isotope analysis allows for their source identification in coastal sediments. Here, we map the current abundances and sources of straight chain n-alkanes in sediments of the St. Lawrence Estuary and Gulf using molecular (diagnostic ratios) and isotopic fingerprinting (δ¹³C, δ²H). n-Alkane abundances (117.11 ± 1.61 to 418.64 ± 70.20 µg/g OC), carbon preference index (CPI; 1.95 ± 0.05 to 5.09 ± 0.10), average chain length (ACL; 28.36 ± 0.02 to 28.97 ± 0.01), proportion of aquatic submerged plants and terrestrial plant inputs (Paq; 0.295 ± 0.003 to 0.377 ± 0.002), terrigenous aquatic ratio (TAR; 3.43 ± 0.16 to 7.99 ± 0.05), and n-alkane ratio (NAR; 0.169 ± 0.011 to 0.584 ± 0.011) values varied along the terrestrial-marine continuum. Large differences in the concentration weighted average (WA) δ¹³C and δ²H for odd and even n-alkanes were found, with WA δ¹³C ranging from -30.9 ± 0.3 to -33.4 ± 0.09 ‰ and -28.8 ± 0.01 to -32.3 ± 0.2 ‰, respectively, and 165.6 ± 3.6 to -200.8 ± 2.4 ‰ and -96.0 ± 2.8 to -158.7 ± 2.1 ‰ for δ²H. The diagnostic ratios were shown to misrepresent the input sources of organic matter (OM) and were inaccurate as source indicators when more than one OM source was present. With the addition of compound specific δ¹³C and δ²H analysis of n-alkanes, it was determined that the n-alkanes were predominantly derived from natural, rather than anthropogenic sources, with variations being driven by geographic changes in vegetation type and differing ratios of terrestrial and marine OM inputs. Importantly, compound specific isotope analysis of the even numbered n-alkanes would permit identification and tracking of petroleum-derived contaminants. Molecular data alone are ineffective for this, owing to the similarity in CPI values for petroleum-derived contaminants and highly degraded OM which is discharged by the St. Lawrence River into the estuary.
... On the other hand, a low-flux band was observed along the surface jet where turbulence was inactive. The observed nitrate flux of O(10 3 mmol m −2 day −1 ) represents an extremely large turbulent flux value, apparently larger than any reported for the open ocean, but is of the same order as that of an energetic tidal estuary reported by Cyr et al. (2015). ...
Article
Full-text available
Vertical nitrate fluxes associated with turbulent mixing and upwelling around a small reef in the Kuroshio are quantified by continuously deploying a turbulence microstructure profiler with an attached submersible ultraviolet nitrate analyzer while drifting from the upstream to the downstream of the reef. Flow separations and trains of Kelvin‐Helmholtz billows (thickness = 60 m) are identified using a shipboard ADCP and an echo‐sounder. The turbulence diffusivity associated with the vigorous turbulent mixing reaches up to O(10−1 m2 s−1), resulting in strong nitrate fluxes of O(1–103 mmol m−2 day−1). In addition, large differences between the upstream and downstream density profiles suggest a strong upwelling velocity of O(10−3 m s−1), as well as an upwelling nitrate flux of O(102 mmol m−2 day−1) in the entire subsurface layer.
Article
Full-text available
Difficulties to quantify ocean turbulence have limited our knowledge about the magnitude and variability of nitrate turbulent diffusion, which constitutes one of the main processes responsible for the supply of nitrogen to phytoplankton inhabiting the euphotic zone. We use an extensive dataset of microturbulence observations collected in contrasting oceanic regions, to build a model for nitrate diffusion into the euphotic zone, and obtain the first global map for the distribution of this process. A model including two predictors (surface temperature and nitrate vertical gradient) explained 50% of the variance in the nitrate diffusive flux. This model was applied to climatological data to predict nitrate diffusion in oligotrophic mid and low latitude regions. Mean nitrate diffusion (~ 20 Tmol N y ⁻¹ ) was comparable to nitrate entrainment due to seasonal mixed-layer deepening between 40°N–40ºS, and to the sum of global estimates of nitrogen fixation, fluvial fluxes and atmospheric deposition. These results indicate that nitrate diffusion represents one of the major sources of new nitrogen into the surface ocean in these regions.
Thesis
Full-text available
Oligotrophic regions are characterized by a shortage of nutrients in surface waters, with nitrogen being the main limiting nutrient in most tropical and subtropical regions of the open ocean, as well as in temperate and polar seas during periods of seasonal stratification. Since some of the biological production in the photic layer is exported to the deep ocean (export), the maintenance of biological production will depend on the input of nutrients into the system. Mechanisms contributing to new production include biological nitrogen fixation, atmospheric deposition, and diffusive and advective vertical and horizontal transport of organic and inorganic forms of nitrogen. Calculation of vertical diffusive transport requires estimation of diffusivity (Kz). The methodological difficulties in obtaining Kz estimates led to the use of constant Kz values, and empirical parameterizations of vertical diffusivity. However, the commercialization of microstructure turbulence profilers has facilitated the obtaining of microstructure turbulence observations, which revealed an important Kz variability in the upper layer. Alternatively, the concentration of dissolved inorganic nutrients in the photic layer has been used as an estimator of nutrient availability to planktonic communities. However, under steady-state conditions, such as subtropical gyres, where nutrient supply by diffusion into the euphotic zone is slow, there may be no relationship between nutrient concentration in the photic layer and nutrient supply. The picoplankton refers to the fraction of plankton smaller than 2 µm and consists of Synechococcus, picoeukaryotes, Prochlorococcus and heterotrophic bacteria. The latter can be divided into bacteria with high (HNA) or low (LNA) nucleic acid content. Photosynthetic picoplankton generally dominate biomass and primary production in tropical and subtropical oligotrophic regions, while their contribution is less in nutrient-rich coastal regions. In marine ecosystems, a major source of environmental heterogeneity lies in the temporal fluctuation of nutrient supplies, which controls the diversity of the phytoplankton community. Under steady state conditions, the minimum level of resources that can sustain a population determines competition. Experimental studies and numerical models of competition support this theoretical basis for large phytoplankton. While numerous studies have investigated the effect of nutrient supply dynamics on interspecific competition of large phytoplankton species, their effect on the groups that make up phytoplankton has received much less attention. The main hypothesis of this thesis is that the dynamics of nutrient supply controls the composition of marine picoplankton communities. To achieve this goal, a multidisciplinary approach will be used, combining field observations made during 17 oceanographic campaigns in the Atlantic, Pacific and Indian tropical and subtropical oceans, the Northwest Mediterranean Sea, the Galician coastal upwelling ecosystem and the Antarctic Peninsula with laboratory experiments and ecological modeling of competitive interactions.
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Full-text available
Variable physical conditions such as vertical turbulent exchange, internal wave, and mesoscale eddy action affect the availability of light and nutrients for phytoplankton (unicellular algae) growth. It is hypothesized that changes in ocean temperature may affect ocean vertical density stratification, which may hamper vertical exchange. In order to quantify variations in physical conditions in the northeast Atlantic Ocean, we sampled a latitudinal transect along 17 ± 5∘ W between 30 and 63∘ N in summer. A shipborne conductivity–temperature–depth (CTD) instrumented package was used with a custom-made modification of the pump inlet to minimize detrimental effects of ship motions on its data. Thorpe-scale analysis was used to establish turbulence values for the upper 500 m from three to six profiles obtained in a short CTD yo-yo, 3 to 5 h after local sunrise. From south to north, average temperature decreased together with stratification while turbulence values weakly increased or remained constant. Vertical turbulent nutrient fluxes did not vary significantly with stratification and latitude. This apparent lack of correspondence between turbulent mixing and temperature is likely due to internal waves breaking (increased stratification can support more internal waves), acting as a potential feedback mechanism. As this feedback mechanism mediates potential physical environment changes in temperature, global surface ocean warming may not affect the vertical nutrient fluxes to a large degree. We urge modellers to test this deduction as it could imply that the future summer phytoplankton productivity in stratified oligotrophic waters would experience little alterations in nutrient input from deeper waters.
Article
Full-text available
Due to the dynamic physical environment of the Lower St. Lawrence Estuary, the spring phytoplankton bloom in the Laurentian Channel occurs late in the season, typically in mid-June, but the high phytoplankton biomass is sustained throughout the summer months. In this study, relationships between the phytoplankton production cycle, water temperature, and the reproductive cycle of Calanus finmarchicus Gunnerus, a predominant planktonic copepod in the Lower Estuary, were investigated during spring-summer 1991. Field observations showed that the final stages of oocyte maturation in C. finmarchicus females did not begin until the onset of the spring phytoplankton bloom in mid-June. High egg production rates, as estimated by the number of eggs released by females incubated immediately after capture, commenced 1 wk later and persisted until late August. Egg production rates were significantly correlated with an index of gonadal maturity in females and were consistent with a rectilinear or curvilinear relationship with chlorophyll a standing stock. Laboratory experiments showed that: (1) in presence of food (the diatom Thalassiosira weissfloggii), maturation of oocytes would proceed and females could spawn eggs at least 2 mo before the spring bloom; (2) without food, the oocytes did not develop past immature stages, except in a small minority of the population; and (3) colder temperatures in early spring would prolong the lag between the onset of the spring bloom and the start of egg production by less than 4 d. Combined with concurrent microscopic measurements of oil sac volume, the results do not rule out the possibhty that lipid reserves were used to support the early stages of oogenesis, but do show that the majority of females did not use lipid reserves for vitellogenesis prior to the spring phytoplankton bloom. It is suggested that the Lower St. Lawrence Estuary is an important region of C. finmarchicus production in summer which, because of the residual surface circulation, may act as a Calanus 'pump' to influence levels of zooplankton biomass in the Gulf of St. Lawrence and on the shelf off Nova Scotia.
Article
A 1965 survey of currents and geostrophic currents in the St. Lawrence estuary is described. An innovation employed in the survey was to moor the strings of oceanographic bottles in the cross-section and trip them simultaneously. A tidal oscillation was detected in the vertical shear of the geostrophic current as well as in the vertical shear of the axial and cross-channel current components. The observations qualitatively confirm predictions from a simple theory that is presented for geostrophic response on one-and two-layer canals. The theory suggests that the period of resonant cross-channel oscillation is an important time scale since current fluctuations of much longer periods reflect accurately in the geostrophic current, while fluctuations of shorter periods may appear as considerable distortions in the geostrophic current. From this, it is concluded that a single determination of geostrophic current may represent neither the instantaneous nor the long-term average current. The average geostrophic current over a time interval longer than the resonant period may, however, represent the average current over the same interval. DOI: 10.1111/j.2153-3490.1970.tb01936.x
Article
Based on the results obtained in the East China Sea, we propose a new term, Continental Shelf Pump , as a mechanism for the absorption of atmospheric CO 2 . We investigated the carbonate system of the East China Sea along a single observation line traversing its central part on 5 cruises in various seasons. The directly observed fugacity of CO 2 dissolved in the surface water decreased with decreasing salinity and temperature as well as nutrient content. The relation has been expressed as a simple equation of these 3 parameters. Putting the observed data on the parameters in the various parts of the East China Sea in various months into this equation, we have obtained 55 ± 5 ppm as an annual mean fugacity deficit of CO 2 in the surface water of the East China Sea, which nearly equals the directly measured mean fugacity along the observation line. The net absorption flux estimated from the fugacity deficit has agreed with the amount of carbonate transported out of the East China Sea calculated for the distributions of total dissolved carbonate and alkalinity. The distributions of density and total dissolved carbonate reveal the cause of this large deficiency, described as follows. The shallower shelf zone is more cooled than the open sea when heat is lost from the surface. This cooling produces denser water, which together with photosynthetic activity, accelerates the absorption of CO 2 in the shelf zone. The absorbed CO 2 is transformed to organic carbon and regenerated especially at the shallow bottom. Isopycnal mixing (advection and diffusion) transports the denser coastal water, especially the bottom water enriched in dissolved and particulate carbon, into the subsurface layer of the open oceans. The transport continues in the layer below the pycnocline even in the warm season and maintains the low fugacity of CO 2 in the surface water of the shelf zone. This is the continental shelf pump. The pump would account for a net oceanic uptake of CO 2 of 1 GtC/ yr, if the world continental shelf zone would absorb the atmospheric CO 2 at the rate observed in the East China Sea. DOI: 10.1034/j.1600-0889.1999.t01-2-00010.x
Article
A comparison is made between series of high frequency internal waves observed in the St.Lawrence estuary from an aircraft and in a field program at a later date. Wave generation is associated with the propagation of a warm surface front during each ebb flow. The number of waves, as evidenced by surface slicks, is thought to vary as does the stability of the upper layer of the water column. (A)
Article
Vertical mixing of the water column in estuaries and other coastal environments requires an input of mechanical energy that is mainly provided by the tides, the wind stress on the water surface and the fresh water runoff. Variations in these three sources are known to have a marked influence on the phytoplankton. At the seasonal scale, river runoff has been identified as an important driving force of phytoplankton dynamics. For example, Gilmartin (1964) has shown that the increased river runoff during the winter in Indian Arm (a fjord of Western Canada) destabilizes the water column which favors the replenishment of the surface mixed layer in nutrients. These nutrients are subsequently used for the initiation of the phytoplankton spring bloom, when the water column stabilizes following the decrease in runoff. At the time scale of a few days, physical transient phenomena (wind storms, periodic upwelling, etc.) associated with the passage of frontal disturbances (Heath, 1973; Walsh et al., 1977) are also strong destabilizing agents of the water column. Iverson et al. (1974), Takashi et al. (1977), Walsh et al. (1978), Walsh (1981) and Legendre et al. (1982) have reported intermittent phytoplankton blooms following stabilization of a water column previously destabilized by strong winds.