Journal oj’kfarine Research, 54, 311-342,1996
Impact of the North Equatorial
Current meandering
on a pelagic ecosystem: A modeling approach
by I. Dadou’, V. Gargon’, V. Andersen*, G. R. FlierI and C. S. Davis4
ABSTRACT
A modeling study was conducted to investigate the effects of time-dependentmesoscale
meanderingof the North Equatorial Current on a pelagic ecosystemin the southwestern
Canary Basin.The North Equatorial Current jet wasrepresentedasa quasi-geostrophicflow
using a two-layer model; a standard bulk mixed layer model is included. Two casesfor the
biological/physicalcoupledmodel were examined: (a) a nutrient-phytoplankton-zooplankton
(APZ) modeland (b) the addition of a sinkingdetritus pool (APZD) in the ecosystem.
The horizontal length scaleof simulatededdiesis 100to 200km. The surfaceeddy kinetic
energy hasa peak value of 110cm*/s*and a meanvalue of 26 cm*/s*in the simulatedNorth
Equatorial Current. Maximum vertical velocity is of the order of 1.5 m/day at 100m depth, the
baseof the mixed layer. The additional nutrients due to eddy upwelling lead to a maximum
increaseof phytoplankton biomassup to 26% located at the edgeof eddies.This trend is even
more pronouncedwhen introducing a detritus pool with a 1 m/day sinking velocity into the
ecosystem(33%). When upwelling events are seldompresent at “mooring” sites, it is the
particulate organic carbon input by horizontal advection which feeds the carbon loss by
detritus sinking. At “mooring” sitesundergoingupwelling events, the upwelled carbon flux
largely dominateslossesby sedimentationand leadsto a 10% enhancementof the sinking
exported carbon flux. When the eddies are resolved, the mean values of the primary and
exported productionsin the jet zone are doubled.The resultssuggestthat the vertical motion
due to eddiesand eddy-eddy interactions in a weak (10 cm/s) horizontal current suchasthe
North Equatorial Current can be a non-negligible sourceof nitrogen-nutrients for oceanic
plankton production in the mixed layer.
1. Introduction
Vertical motion of water, associated with strong currents and eddies such as in the
Gulf Stream or Kuroshio, plays a crucial role not only in the physical structure of the
currents but also in the biological processes. Upward motion of water transports
nutrients from deeper waters into the euphotic zone, making them available for
1. Unite Mixte de Recherche
39, Centre
National
de la Recherche
Scientifique,
GRGS,
18 Av. E.
Belin, 31400 Toulouse,
France.
2. Station Zoologique,
URA 716, BP 28,06230
Villefranche
sur Mer, France.
3. Department
of Earth Atmospheric
and Planetary
Sciences,
M.I.T.,
Cambridge,
Massachusetts,
02139, U.S.A.
4. Woods Hole Oceanographic
Institution,
Woods Hole, Massachusetts,
02543, U.S.A.
311
312
Journal of Marine Research
15472
phytoplankton production. Biological production and carbon export from the surface
to the deep ocean represent key issues in ocean biogeochemical cycling, and their
accurate estimation constitutes one of the major goals of the international
JGOFS
(Joint Global Ocean Flux Study) program (National Research Council, 1984).
Plankton production due to eddies and fronts could significantly alter these estimations and has to be studied in order to fully understand the oceanic carbon cycle.
In the Gulf Stream, Kuroshio and other western boundary currents, measurements and modeling studies have provided evidence that the vertical velocity could
be large enough to influence ecosystem dynamics (Yoder et al., 1981; Flier1 and
Davis, 1993). However few studies have focused on areas of weak eddy kinetic energy
(less then 300 cm2/s2) representing the major part of the world ocean (Shum et al.,
1990). Although the eastern part of the Subtropical North Atlantic gyre was
traditionally thought to be governed primarily by Sverdrup dynamics, recent observational programs have revealed the existence of upper ocean fronts and mesoscale
eddies in the southeastern part of the gyre (Barton, 1987; Fiekas et al., 1991; Zenk et
al., 1991). Our purpose here is to investigate the possible influence of weak
mesoscale hydrodynamic variability ( < 300 cm2/s2) on biological dynamics by a
modeling process study.
The North Equatorial Current (NEC) forms the southern dynamic boundary of
the North Atlantic Ocean’s subtropical gyre and transports nearly pure North
Atlantic Central Water (NACW) southwestward, west of the Cape Verde Islands.
Immediately
south and southeast of this dynamic boundary lies the Central Water
Boundary (CWB ), a major thermocline discontinuity separating NACW and South
Atlantic Central Water (SACW) masses (Hagen, 1985; Emery and Meincke, 1986).
Both boundaries together are defined as the Cape Verde Frontal Zone (CVFZ)
located between 15N and 25N in this area (Zenket al, 1991) (Fig. 1). McDowell et al.
(1982) Cox (1985) and Keffer (1985), analyzing the structure of the NEC potential
vorticity fields, found the conditions necessary for baroclinic instability to be satisfied
in the NEC. In a numerical model of the CVFZ area, Onken and Klein (1991)
showed that baroclinic instability results in the generation and growth of meanders
followed by eddy formation. Eddies have typical horizontal length scales of 100 km in
the few observational studies (Zenk et al., 1991) as well as in model predictions
(Onken and Klein, 1991). The eddy containing region between NACW and SACW
varies between 300-500 km (Cox, 1985; Onken and Klein, 1991).
Do we have evidence of the influence of eddies on biological processes in the area
of the NEC? The EUMELI project, realized in the framework of the JGOFS-France
program, gave the opportunity to study the internal variability of the water column at
three typical sites (eutrophic, mesotrophic and oligotrophic),
located near 20N of
latitude in the southern Canary Basin. At the oligotrophic site (21N, 31W) (Fig. 1) in
the NEC, no variability was observed on the chlorophyll phytoplankton
concentration during the EUMELI
cruises (Claustre, 1994). CZCS images have shown
19961
1ee
Dadou et al.: Impact of NEC meandering on a pelagic ecosystem
TV
1
Azores
Current
313
Azores
3
longitude
(OW)
Figure 1. Schematic of the Canary basin showing the upper currents in the eastern basin of
the North Atlantic Ocean. The star indicates the position of the EUMELI oligotrophic site.
CVFZ represents the Cape Verde Frontal Zone as defined by Zenk et al. (1991).
phytoplankton concentration variability in the NEC area (Berthon, 1992) but the
author did not study the possible interaction between the current meandering and
the satellite chlorophyll variability. It is true that the EUMELI cruises were not
planned for a mesoscale survey.
Fortunately, the German JGOFS program during the NABE (North Atlantic
Bloom Experiment) in 1989 planned a “classical” and a drifter survey around 18N
and 30W with a resolution not too far from mesoscale. On the basis of data from the
drifter survey, Jochem and Zeitzschel (1993) divide the water column into an
oligotrophic layer and a subsurface maximum layer. They found a ratio of chlorophyll
concentration of the subsurface maximum layer to the oligotrophic layer of 2:l to 4:l.
These ratios are low compared to ratios typical of oligotrophic steady state systems
(5:l to 1O:l) (Jochem et al, 1993). They conclude that the 18N study site system can
be regarded as still far from a steady-state oligotrophic epipelagic system. What are
the mechanisms responsible for this perturbation?
Nitrate supply to the euphotic zone by seasonal deepening of the mixed layer could
be invoked. However in this region, the nitracline is usually below the fall and winter
mixed layer depths (JGOFS-France EUMEL13, 1992; Dadou and Garcon, 1993;
Koeve et al., 1993). Model calculations (Lewis et al., 1986; Bigg et al., 1989) have
revealed that in this context, this process could not be a significant contribution to
the nitrate flux in the euphotic zone.
Journal of Marine Research
314
[54,2
Another possible mechanism responsible for this deviation from steady state is
eddy activity. A cyclonic eddy-like feature occurred in the survey area during the 16
days of measurement of the drift experiment. The mesoscale variability of the
nitracline is correlated with the cyclonic-like eddy. The highest chlorophyll values in
the mixed layer (ML) were located at the northeastern edge of the cyclonic eddy
(Podewski, pers. corn.) along with doublings of the primary production (Jochem and
Zeitzschel, 1993). During this survey, it was not however clearly demonstrated that
the cyclonic eddy was the only process which could have high impact on biology.
Ekman pumping (downwelling) and diapycnal mixing which occur in this area might
also be important.
Our concern is to examine the influence of NEC eddies due to baroclinic
instabilities on the behavior of a pelagic ecosystem in a simple way. We therefore
developed a coupled physical-biological
model characteristic of this area. In Section
2, we present the physical model, a conventional two-layer quasi-geostrophic model
(Flier& 1978). Evolution equations and parameter calibration of the biological
models are explained in Section 3. In Section 4, the three different formulations of
the coupled models tested in this study are described. The results of the simulations
are presented in Section 5. The possible impact of mesoscale hydrodynamic variability in the NEC area on the biological dynamics and carbon cycle is then discussed in
Section 6.
2. Physical dynamics
In order to study the evolution of the meandering North Equatorial Current
(NEC) as observed during German oceanographic surveys in this area (Zenk et al.;
1991; Fiekas et al., 1991) the two-layer quasi-geostrophic (QG) model of Flier1
(1978) is used. Indeed, the QG approximation
is valid in this area since the Rossby
number is small. The NEC is characterized by a horizontal velocity U, of the order of
10 cm/s and a typical length scale L (jet half width) of 150 km (Fig. 2). At a latitude
of 20N, the Coriolis parameter is equal to 5.10-5s-1 giving a Rossby number of the
order of 10p2.
We integrate the vorticity conservation equation on the l3 plane in the two layers
(Fig. 2). With the assumption of flat bottom and rigid upper lid and in the absence of
bottom friction, the dimensionless equations in each layer are:
$ Qj + J(qj, Q,) + p z Qj = -v,V6q, withj
= 1 to 2.
(2.1)
These equations represent the advection and deformation of potential vorticity in
the upper (j = 1) and lower (j = 2) layers, the effect of the gradient of planetary
vorticity and the small-scale dissipation. J( ) is the usual two-dimensional Jacobian
operator, p the planetary beta-effect, vq is the friction parameter, which strongly
19961
Dadou et al.: Impact of NEC meandering on a pelagic ecosystem
mode’
i
315
,i - - -
2nd
layer
of the
QG
model
r
Figure 2. Schematic view of the physical model.
dissipates enstrophy in the high wave number range. The potential vorticity Q is the
sum of the horizontal velocity curl and of the vertical vortex stretching:
Q, = V*O, + F(q2 - ‘u,) and Q2 = V*q, + Fg
(q, -
‘u*>
where ‘Jri is the stream function in the layer j, F is the Froude number (LIRd)*, Rd is
the internal deformation radius, Hj is the thickness of layer j and His the total depth
of the model.
The vertical velocity w is defined at the interface between the layers 1 and 2, and
scaling w by U HI/L, the dimensionless vertical velocity satisfies
d
w=EF-jp2-31)
(2.2)
where E is the Rossby number and dldt = [a/at + J(W, )] with * defined as * =
(H2’4’1+ Z&‘t’&H.
a. Initial conditions. The initial conditions are chosen to represent an idealized
version of the NEC in the first layer of the QG model. The general form of the initial
stream function is:
Qr(x, y, 0) = - U,,L tanh
(Y - Yo> - YY5Y)
L
I
Journal of Marine Research
316
[54,2
wherex is positive to the east,y to the north, U0 the maximum velocity of the jet, L the
half-width of the jet profile,y,, the half-width of the model domain in they-direction.
In order to simulate the growth of meanders, a perturbation field from the zonality
is superimposed on that basic state:
j&y)
= A0 exp [-(~Iwid)~
- (Y/L)~]
where A0 is the amplitude and wid the length scale of the perturbation. We use an
amplitude throughout of 100 km (A,) and a length scale (wid) of 50 km.
In the second layer of the QG model, no motion is assumed; the initial stream
function is equal to zero.
b. Boundary conditions, calibration and parameters. Our domain model is 2000 x
2000 km square, the domain is doubly periodic. The numerical code is pseudospectral with 128 x 128 grid points. The grid spacing used is 15.63 km. With such a
grid spacing, the jet is adequately resolved, as confirmed by higher resolution
simulations (256 x 256 points) (not shown here). The friction parameter v4 is set to
3.4 x 1012 (m4 s)-l.
We calibrate the model with hydrographic data from Zenk et al. (1991). We use a
velocity scale of U0 = 10 cm/s, typical of the North Equatorial Current near the
surface and a jet half-width of L = 150 km. The radius of deformation is Rd = 32 km.
The domain is centered around 20N. The Coriolis parameterfo is equal to 5.104 s-l.
The l3 parameter is set to 2.5 lOPi1 (m s)-l. The first layer of the model, where the jet
is present, is 160 meters deep (depth of the thermocline).
The total depth of the
domain is 3000 m.
3. Biological
dynamics
The model framework for the plankton dynamics (Fig. 3) is a conventional one
(e.g. Steele, 1977; Franks et al., 1986). We consider two different biological models.
Their state variables are modeled in terms of their nitrogen content, nitrogen being
the assumed limiting nutrient. The first model (NPZ) is composed of three state
variables: phytoplankton (P), zooplankton (Z) and dissolved inorganic nitrogen (N).
In the second model (NPZD), a detritus pool (0) is added with its remineralization
and sedimentation.
a. NPZ model. The evolution
equations for the plankton model are:
dP
z = uZ(z)NP
- gNpzPZ = RN&P,
dZ
z = agNpzPZ - dZ = RNpz(Z,
dN
- = -uZ(z)NP
dt
+ (1 - a)g,pzPZ
z)
Z)
+ dZ = RNpz(N, z)
(3-l)
19961
Dadou et al.: Impact of NEC meandering on a pelagic ecosystem
317
with the terms representing uptake of nutrients (ul(.z)NP), grazing (gNpzpZ), assimilation of grazed material by zooplankton (agNpzPZ) and zooplankton death and
excretion (dZ). In this model, the total amount of nitrogen in the system, P + Z + N
is conserved. z is the vertical coordinate. The different trophic relations for the NPZ
model are summarized on Figure 3a.
The lack of vertical migration and the rapid remineralization
of the zooplankton
products imply that they more closely represent microzooplankton
consumers, and
to a lesser extent mesozooplankton
(copepods), than large grazers such as salps or
euphausiids. In a neighboring area, Lenz et al. (1993) found that day/night differences of mesozooplankton
standing stocks amounted to about 20%. We therefore
choose to neglect, as a first step, die1 vertical migration. In the absence of accurate
information on mathematical
relationships describing the trophic interactions, we
have chosen to use the simple formulations given above for the different biological
terms, as in Flier1 and Davis (1993). The phytoplankton growth rate is considered to
be linearly dependent upon light and nutrients; the zooplankton grazing rate is
linearly dependent upon phytoplankton
biomass and the closure is a simple linear
form with Z. The light intensity is assumed not to vary with time and to fall off
exponentially with a scale of 19 m (which gives an extinction coefficient of 0.05 m-l).
The light intensity is normalized so that the integral from 0 to 100 m of I(z) is 1.
e(-Zl19)
‘(‘)
= (19/1()0)[1
- &100/19)]
(3.2)
The purpose of the EUMELI
project was to evaluate and compare the sedimentary, biological and carbon fluxes at three typical sites in the Southern Canary Basin:
eutrophic in the upwelling of Mauritania, mesotrophic in the CVFZ and oligotrophic
in the large horizontal expanse of the NEC. These sites have been occupied five times
between the years 1989 to 1992. Parameter values for biology were chosen to
approximate oceanic conditions at the oligotrophic site (21N, 31W). For the calibration of the biological model, we use information coming from the EUMELI
5 cruise
(December 1992). The units are days, mmol N/m3 and km. The mixed layer depth is
taken to be 100 m which corresponds to a winter situation in this subtropical area
(Fig. 4).
In a mixed layer of 100 m depth, the mean concentrations of P, Z, N deduced from
EUMELI
5 are 0.15, 0.05 and 0.03 mmol N/m3, respectively and we take these
as steady state values (Ps, Z,, and N,, respectively). We assume that half the
zooplankton mass is lost to mortality and excretion per day (d = 0.5 day-i) and that
zooplankton assimilates 70% of the food they graze (a = 0.7). This value agrees with
assimilation coefficient values for copepods (Conover, 1966) and microzooplankton
(Verity, 1985). The equilibrium condition of the NPZ model gives u = 7.93 (mmol
N/m” day)-’ for the growth rate of phytoplankton
and gNpz = 4.76 (mmol N/m3
day)-’ for the grazing rate of zooplankton. With those values at equilibrium,
the
growth rate of phytoplankton (uN~) is equal to 0.24 day-’ which falls within the range
318
Journal of Marine Research
[54,2
grazing
fecal
pellets
P
moi ality
r?
uptake of nutrient
I
Figure 3. (a) Schematic of the NPZ model, (b) Schematic of the NPZD model.
of in situ measurements of this growth rate (Claustre, pers. corn.) made during the
EUMELI cruises. At equilibrium, zooplankton ingests 71% (gNPz.P,) of its initial
body weight in one day, in agreement with observations on copepods (Mullin and
Brooks, 1970) and on microzooplankton (Verity, 1985). The values of the biological
parameters are summarized in Table 1.
b. NPZD rqodel. The equations for this second model are:
dP
z
=
uWNP
- gNPZ##z
dZ
- = agNpzo(e$ + e&Zdt
dN
-z-=
dD
dt
=
dZ+
(1
-
= RNPZL@>
Z)
dZ - eZ = RNpzo(Z, 2)
(3.3)
-uZ(z)NP
akNPZd@
+
+ eZ + rem D = RNpzo(N, z),
dV
-
gNPZD@z
-
rem
D
= RNpzD(D,
4
with the terms representing uptake of nutrients (uZ(z)NP), zooplankton grazing on
phytoplankton (gNpz@?#z), assimilation of grazed phytoplankton (agNpz&#z) and
19961
Daa!ou et al.: Impact
of NEC
meandering on a p&&c
ecosystem
319
r
ingd
fecal
Pe
excretion
uptake
of nutrient
!
mortality
remineralization
I
sinking
i
Figure 3. (Continued)
grazed detritus (agNpzoeDDZ), zooplankton excretion (eZ), zooplankton death (dZ),
zooplankton fecal pellets (1 - a) g NpzD (epP + efl) Z and detritus remineralixation
(rem D). The different trophic relations are summarized on Figure 3b.
The essential difference between the NPZD and NPZ models is the way organic
matter is remineralized. The new D compartment can be considered as a simple
microbial loop where the detritus remineralixation
rate (rem) is the rate at which
“idealized” bacteria would convert detritus-nitrogen
into dissolved inorganic nitrogen. Incorporating a D compartment allows us also to consider the sinking process of
organic material. Zooplankton in the second model grazes upon phytoplankton but
also upon detritus. Indeed, copepods have been shown to ingest nonliving food
particles (such as dead phytoplankton cells and fecal pellets) at lower or similar rates
than they ingest living phytoplankton cells of the same size (Paffenhiifer and Van
Sant, 1985; Lampitt et aL, 1990).
Since we want to understand the influence of a detritus pool, we keep the same
values for the steady state as those of the NPZ model (Ps = 0.15, Zs = 0.05,
320
Journal of Marine Research
250
14
16
18
Temperature
20
22
("0
24
0
4
8
Nitrate
(a)
12
16
(PM)
:
(b)
0,
/
"7
50 I
+
25Ou
0
II
0.1 0.2
Chlorophyll
0.3
(4
0.4
0.5
(p&l)
0.6
250
0
0.01
Zooplankton
0.02
0.03
0 14
bmnol
N/d)
(d)
Figure 4. Vertical profiles of temperature (“C), nitrate (pm), chlorophyll (kg/l) and zooplankton (mmol N/m3) at the oligotrophic site during the EUMELI 5 cruise (Pujo-Pay and
Raimbault, 1993; Grisoni et al., 1994; Gorsky, pers. corn).
NS = 0.03 mmol N/m3). We also keep similar values for the parameters u, g and a as
in the NPZ model. Indeed, since we have introduced a preference factor for the
zooplankton grazing, the Value of ep. gNpzD is equal to gNpz. For the zooplankton
grazing preference factors, ep (preference
for phytoplankton)
equals 90% and eD
(preference for detritus) equals 10% which seem to be reasonable values. We have
allowed zooplankton to graze upon nonliving material in the trophic chain; however
19961
Dadou et al.: Impact of NEC meandering on a pelagic ecosystem
321
Table 1. Biological parameter values used for the NPZ and NPZD models.
Biological
parameters
u
g
Definition
phytoplankton growth rate
zooplankton grazing rate
I
Value
Unit
I
7.93
(mmol N/m3 day)-’
ghipz = 4.76
(mmol N/m3 day)-’
RNPZD
I
= 5.28
-
a
assimilation coefficient
0.7
6
capture efficiency of phytoplankton
by zooplankton
0.9
capture efficiency of detritus by
zooplankton
0.1
d NPZ
zooplankton excretion and death
rate
0.5
day-i
d NPZD
zooplankton death rate
0.4
day-l
e
zooplankton excretion rate
0.15
day-’
rem
remineralization rate
0.2
day-l
-
as already mentioned, copepods do not dominate within this group; assigning a 10%
value to eD will reflect the zooplankton composition. At model equilibrium, the
zooplankton ingest 79% (g NpzD(epP, + e&)) of their initial weight in one day, still
in agreement with literature values.
The determination of the detritus pool concentration at steady state was not easy
since we have no direct information on the magnitude of this pool from the EUMELI
cruises. We therefore assumethe detritus concentration (0) to be of the order of the
phytoplankton concentration at the equilibrium state, so we choose Ds equal to 0.14
mmol N/m”. Since we have three independent equations and five chosen parameters
over eight, and knowing Ps, Zs, Ns and Ds, the three remaining parameters
(d, e, rem) can be determined. We calculated values of 0.4,0.15,0.2 day-i ford, e and
rem, respectively. The value of 0.15 for the excretion rate is consistent with values
given by Corner and Cowey (1968) for copepods and by Goldman and Caron (1985)
for microzooplankton. The decomposition rate, rem equal to 0.2, is similar to those
used in other ecosystem models: 0.5 (O’Brien and Wroblewski, 1973) or 0.1 (Vinogradov et al., 1973). The values of the biological parameters for the NPZD model are
also listed in Table 1.
4. Coupling between physics and biology
Biological dynamics take place mainly in the first hundred meters of the water
column. Following Flier1 and Davis (1993) we use a simple representation of the
mixed layer (ML) based on the standard “bulk” mixed layer model (Niiler, 1977).
This is combined with the deeper geostrophic flow calculated by the two layer QG
model (see Section 2) thereby yielding a 2 iI* layer model. The equation for any
322
biological
Journal of Marine Research
[54,2
property B in the ML is
;
(1)
+ u . VB = -s(B
(2)
- B-)
+ R(B, h) - v,V6B
(3)
(4)
(4.1)
(5)
where u is the horizontal mesoscale velocity calculated by the QG model, B- is the
value of the property B just below the mixed layer and h is the depth of the ML. At a
hxed depth, S, the entrainment term due to vertical advection by eddies is defined as
s = s * Hv(S)
where S represents the stretching term, equal to w(h)lh = w(H~)IH,. w is the vertical
velocity created by mesoscale motions in the two layer QG model (see Eq. 2.2) and
Hv is the Heaviside step function (zero when its argument is negative; implying
downwelling through the ML base; and one- when its argument is positive; for
upwelling across the ML base).
The different terms of Eq. (4.1) represent: (1) the change of the property B with
time, (2) the mesoscale horizontal advection of the property B, (3) the mesoscale
vertical advection of the property B, (4) the source/sink term, R(B, h), representing
all the biological interactions which may alter the concentration within the ML (see
previous section) and (5) the horizontal advection of the property B. The authors
refer the reader to Flier1 and Davis (1993) for a complete explanation of Eq. (4.1).
As explained before, we choose a fixed depth of 100 m for the ML corresponding
to a winter situation in this subtropical area. Only the coefficient for uptake of
nutrients is dependent on z, so when the biological equations are integrated over the
ML, the interaction terms R can be written as a function of the ML biological
quantities and the ML depth h.
We consider three different coupling strategies between the 21’2 layer model for
the physics and the biological models (NPZ and NPZD models) (Fig. 5). For case A,
we follow the same approach as Flier1 and Davis (1991). We assume biological
processes occur only in the ML and plankton is remineralized instantaneously within
the ML. There is conservation of P + Z + N in the ML equal to the deep nutrient
pool under the ML. This deep nutrient pool is equal to the total N (NT = 0.23 mmol
N/m”) below the ML in the first layer of the QG model, and is unrealistic in
comparison with the observations. This pool is upwelled and partitioned by biological processes into N, P, Z in the ML. For full details of case A, the reader is referred
to Flier1 and Davis (1991). Cases B and C will be explained in more detail. In each of
these coupling cases, the initial conditions for the biological state variables are
considered as the steady state values and homogeneous all over the domain.
a. Case B. In case B, we assume that plankton
can be present under the ML and we
also increase the nitrate pool under the ML, closer to reality. In the area of the
EUMELI oligotrophic site, in winter, the chlorophyll phytoplankton subsurface peak
19961
Dadou et al.: Impact of NEC meandering on a pelagic ecosystem
323
Om
Bottom of
theML
loom
Bottom of -140
m
first layer of
QG model
Bottom of the
second layer of QG model
Bottom of
the ML
Bottom of
first laver
I~ of
QG model
a
3000 mU
*
loom.
-160111.
NPZ
b
QG model
OIll
Bottom of
&ML
Bottom of
first layer of
QG model
NPZD
+
-160
Bottom of the
second layer of -3000
QG model
loom
In
NPZD.
C
m
Figure 5. Schematic of the different waysof coupling the biology and the physics for (a) case
A, (b) case B and (c) case C.
is centered around 100 m. Below 100 m, the observed plankton concentration is not
equal to zero. This scenario will document the influence of including biological
processes under the ML in such process studies.
The equations using the NPZ model are for case B:
% + u, * VP, = -sB(Po - PI) + R,,,,,(P,, z/r)- v,V6Pk
z
+ lq . vz,
%
= -&(Zo
- Z,) + RN&.&,
zk) - v,V6Zk with k = 0 to 1
+ u1 . VN, = -sL(No - N,) + RNpz(Nk, qJ-
(4.2)
v,VNk
where u, is the mesoscale horizontal velocity in the first layer of the QG model and
the index k refers to layer k. k = 0 is the layer from the air-sea interface down to
324
Journal of Marine Research
[54,2
100 m. k = 1 is the layer under the ML from 100 to 160 m, (zi = 60 m). The
entrainment term in layers 0 and 1 is:
sg = SHv(S);
s1 = SHv(-S)
&
1
with Hv being the step function and s the entrainment term as defined previously. In
case B, we use the same total amount of nitrogen in the ML, as for case A, NT, equal
to 0.23. The steady state in the ML is then the same as case A. The light intensity
integrated over the 100 m ML depth is equal to 1 based on the selected light function
(Eq. 3.2). Under the ML, the light intensity integrated from 100 m to 160 m, is equal
to 0.01. In this case B, we take into account the nitrate concentration increase under
the ML around 120 m as observed from the data (Fig. 4). So, under the ML, the
corresponding values of phytoplankton,
zooplankton and nitrogen-nutrient
for the
steady state of model B are 0.15, 3.67 10v2 and 2.2 mmol N/m3, respectively. These
values are similar to the loo-160 m integrated concentrations measured during the
EUMELI
5 cruise (Fig. 4). In case B, we assume also conservation of total nitrogen
on the two layers between 0 and 160 m.
b. Including a detritus pool: Case C. In this last case of coupling,
we investigate the
influence of the detritus pool D by using the NPZD model. Plankton dynamics within
and below the ML are linked via both the mesoscale vertical velocity and the detritus
sedimentation. The equations using the NPZD model are for case C:
% + u, . VP, = -s,z(PO - P,) + RNPZD(Pk,zk)- v,V6Pk
%
+ u1 . VZ, = -sk(ZO - Z,) + R,,&Zk,
zk) - v,V6Z,
with k = 0 to 1
(4.3)
2
2
+ u, . VN, = -QN,,
- NJ + RNPZD(Nk,zk)- v,V6Nk
+ u1 . VD, = -s,(D, - DI) + Ws,D,, + R,,r,,,(D,, zk) - v,V6D,.
Notations are identical to those for case B. Dk refers to the detritus concentration
layer k.
The mean detritus sinking rate over the ML, Wskis equal to:
WD
WsO= -kandW,l=H,-h
in
wD
where wD is the sinking velocity of detritus. The steady state of case C in the ML,
without considering the sinking term, is the same than that of cases A and B. The
19961
Dadou et al.: Impact of NEC meandering on a pelagic ecosystem
325
only difference is the introduction of a detritus pool equal to 0.14 mmol N/m3. Under
the ML, due to the light attenuation, the steady state values are 0.15, 3.67 10m2, 2.2
and 0.103 for P, 2, N, D, respectively. Again, we assume conservation of total
nitrogen on the two layers between 0 and 160 m.
5. Results
We will now investigate the influence of the meanders and eddies of the NEC on
the biological dynamics. The QG model has been integrated over 300 days. Simulations including the biological models have started at day 200, (which is the formation
time of the first eddies) and have been run over a 100 day period.
of the simulated meandering NEC. The 300 day time integration of our
model is longer than in the Onken and Klein (1991) study. Indeed, the evolution of
the baroclinic disturbances is slower than in the model they used for two reasons:
one, Onken and Klein (1991) used a primitive equation model with several layers on
the vertical which gives a more complex and realistic representation of the NEC;
second, we use a flat bottom instead of the bottom slope of the Cape Verde Plateau
used by Onken and Klein (1991). They showed that a sloping bottom would
accelerate the growth of perturbations.
Figure 6a shows a sequence of first-layer stream function fields. On day 0, the
streamlines are strictly zonal except for the deviation caused by imposing the
specified perturbation on the basic state. After 100 days, meanders have developed
with peak-to-trough ranges of about 100 km. Between day 100 and 200, meander
growth continues. The dominant meander wave length is about 200 km (day 180). At
day 200, the first eddy became detached to the south of the meandering jet. A
comparison of subsequent positions of meander troughs and ridges during this time
period gives a meander phase speed of about 3 cm/s westward, slightly larger than
that of Onken and Klein (1991). After day 200, several eddies became detached from
the front to the north (cyclonic) and to the south (anticyclonic). The initial jet has
been split up into an eddy field which has a north-south extent of roughly 400 km
beginning at day 260. The eddies are initially around 100 km across; but by the end of
the simulation
(day 300) the eddies have become elongated, with lengths of
O(200 km).
In the simulated NEC current, the surface eddy kinetic energy (EKE) levels
(layer 1) have maximum peak values of about 110 cm2/s2 and a mean value of
26 cm2/s2 which well compare with EKE levels found by different authors in the
NEC. Beckman et al. (1994) provided different estimations of EKE levels in the NEC
along a meridian section at 30W based on drogued drifter and Geosat altimeter data.
Their estimations vary from 30 to 200 cm2/s2, the smallest corresponding to the
drogued drifter data and the largest to the altimeter Geosat results. Current meter
data in the area show an EKE level around 20-30 cm2/s2 (Miiller and Siedler, 1992).
a. Evolution
Journal of Marine Research
326
[54,2
1000
3
500
20”N
0
._.............................
-
-500
_
Max
Min.
= 1336.
=-1255.
-1000
day
I
-500
-1000
,
I
0
Longitude
1000
Isocontour
’
interval
I
500
0
I
1000
(km)
’
_
I
: 200
’
’
_
km2/day
500
2
2
4
2
20”N
0
%
b:
4
-500
Max
=
1347.
-1000
-1000
-500
0
Longitude
500
1000
(km)
Figure 6. The evolution of (a) the stream function (km2/day) (contour interval is 100
km2/day) and (b) vortex stretching S (day-‘) ( contour interval is O.O025/day) in the first layer
of the QG model. In (a), at day 0, the stars indicate the positions of the nine model moorings
(see paragraph 5c)
Le Traon (pers. corn.) confirms eddy energy level from the combined
altimeter data set in the NEC area is less than 200 cm*/s*.
ERSl/TOPEX
Vertical motion associated with the stretching term S could be estimated with Eq.
2.2. This term is important in the evolution equations as it is directly responsible for
the nutrient intrusion in the ML. In Figure 6b, at day 200, downwelling and upwelling
Dadou et al.: Impact of NEC meandering on a pelagic ecosystem
327
1000
0
20”N
-500
1000
-1000
Max
Min.
I
=
=-
1394.
1262.
, /
I
-500
I
0
Lorwitude
-1000
,
-500
200
500
1000
500
1000
(km)
0
Longitude
day
(km)
Figure 6. (Continued)
regions are associated with different parts of the meander. Upwelling occurs when
approaching an anticyclonic curve from a cyclonic curve (implying a flow divergence)
and downwelling when approaching a cyclonic curve from an anticyclonic curve
(implying a flow convergence). The maximum positive stretching term S is equal to
0.015 d-l at the end of the simulation (day 300). It corresponds to a maximum
vertical velocity of 1.5 m/d at 100 m depth and 2.4 m/day at the base of the first layer
of the QG model (160 m depth). In comparison with typical vertical velocity values
created by other processes, the value of 2.4 m/d (2.7 10e3 cm/s) is less than vertical
Journal of Marine Research
Max
= 0.0092
fSOCOntour
- 1000
interval
-500
: O.OOZS/day
Longi,4,
500
1000
(km)
Figure 6. (Continued)
velocities observed in the Gulf Stream (0.21 cm/s) or created by a hurricane (0.1
cm/s) but compared to the mean Ekman pumping (2. low4 cm/s), it is substantial.
We can thus expect a certain influence on biology.
b. Case B. For the NPZ biological model with the case B coupling, the biological
fields at day 300 (Fig. 7) show a response influenced by both upwelling and horizontal
advection created by eddies in the ML.
The integrated phytoplankton distribution in the ML (Fig. 7a) presents a patchy
Dadou et al.: Impact of NEC meandering on a pelagic ecosystem
19961
looo~’
.
I
.
.~
1
_
f_.
interval
Isocontour
j”..
.-...
--
: 0.005
.---__
_
_‘
I-.
“._-r
_._.rl__.*_
329
\
P.
7nnaoW/7n3
4
4
-500
-1000,
‘ . * . + 11 , * + . ++ 1 $t * . i i#
Max
Min
= 0.19
= 0.147
a)
interval
Isocontour
: 0.05
7n7nolN/m3
2’
500
OI
s
20”N
0
.f:
2
I
-1
-500.
Max
j
,ooo~
)
=
0.32
Min = 0.02
I . I i + *
- -i
interval:
Isocontour
I_ +--*0.05
-c-----L
-+--L--C_-+--:
b,:
N!
nwnolN/m3
i
20”N
4
-500
/
Max
Min
= 0.189
= 0.014
41
-1000
-1000
-500
0
Longitude
500
1000
(km)
Figure 7. Horizontal distributions (mmol N/m3) in the mixed layer at day 300 for the case B
(a) for phytoplankton concentration (contour interval is 0.005 mmol N/m3), (b) for zooplankton concentration (contour interval is 0.05 mmol N/m3) and (c) for nutrient concentration
(contour interval is 0.05 mmol N/m3). The color code is as follows: - if the concentration of
a biological variable B is I B, (initial value), the color code for B is white and the isocontour
line is dotted; - for B > B,, increasing concentration is represented by increasing color
from white to dark grey; - black patches represent positive vertical velocities.
330
Journal of Marine Research
[54,2
field with dimensions between 100 and 200 km. Phytoplankton
nitrogen has large
values near the regions of mesoscale upwelling. The increase of phytoplankton due
to the eddy field is not negligible. At day 300, the maximum value is 0.19 mmol N/m3.
We can calculate a “maximum variation,” ratio between the difference of maximum
concentration between day 300 and day 200 and the concentration at day 200 which
for phytoplankton is 25%. The maximum variation occurs at day 240 with 31%. There
is a good spatial correlation between upwelling and phytoplankton
patches. The
maximum primary production in case B is an order of magnitude higher than in case
A, up to 23. mmol N/m2/d. It seems that taking into account biological processes
under the ML has a great impact on both phytoplankton concentration and distribution. A second point to take into account is the large difference in concentration of
the nitrogen-nutrient
reservoir under the ML, which could explain the difference in
phytoplankton growth kinetics. In general, phytoplankton-limited
areas correspond
to zooplankton-rich
region in Figure 7b. These rich zooplankton patches are
localized in the anticyclonic eddies in the southern part of the simulated domain
adjacent to nutrient-rich upwelling areas. However because of the longer lifetime of
the zooplankton, they can also be advected into the mean jet by horizontal advection
processes (u.VZ). This does not occur for phytoplankton
(Fig. 7a) due to the
zooplankton grazing. The importance of horizontal advection is confirmed by a
simulation without horizontal advection; in this case, the zooplankton patches
remain in the location of their formation.
Nutrient and zooplankton fields look similar; the zooplankton excretion and death
rate is high; this zooplankton death is remineralized instantaneously into nutrient.
The flux of remineralized nutrient is too weak to allow phytoplankton-rich
patches
with sufficient quantities that will not be grazed by zooplankton. Maximum concentrations of nitrogen-nutrient
and nitrogen-zooplankton
reach 0.189 mmol N/m3 and
0.32 mmol N/m3, respectively at the end of the model run.
Following Flier1 and Davis (1993), we define an “upwelled” production due to the
upwelling of new nutrients @(No-Ni)) and a “regenerated”
production due to
recycling of nutrients (fecal pellets and death of zooplankton); we also define a ratio
between the “upwelled”
and “regenerated”
productions. In case B, upwelled
production can reach half the regenerated production. When we don’t take into
account the step in nitrate concentration between the ML and under the ML (i.e.,
case A), we found a very low maximum ratio value of 0.1. For the Gulf Stream case,
Flier1 and Davis (1993) found during upwelling events, a ratio equal to 1, upwelled
and regenerated production having the same order of magnitude.
In summary for case B, the phytoplankton
distribution seems to be a signature of
vertical velocities, whereas the zooplankton and nutrient fields are governed by
horizontal advection.
of introducing detritus into the ecosystem: Case C. In case C, we
investigate the impact of the detritus pool D. As for case B, the phytoplankton field is
c. Importance
19961
Dadou et al.: Impact of NEC meandering on a pelagic ecosystem
331
well correlated spatially with the vertical velocity field (Fig. 8a). Two major differences can be found when introducing detritus into the ecosystem for the P distribution. First, a depleted phytoplankton
area exists near each enriched patch in
phytoplankton. Secondly, the P patches are also more localized and intense than in
the case without detritus. For this region of study, we chose a weak detritus sinking
velocity, 1 m/d typical of microzooplankton
products (Siegel et al., 1990) since our
zooplankton compartment
includes mostly microzooplankton
consumers with a
small fraction of copepods. Doubling the detritus sinking velocity produces an
increase of the maximum variation of phytoplankton biomass from 33 to 44% at day
300. In this case at day 300, maximum primary production is equal to 8.6 (7.3) mmol
N/m*/d for a 1 (2) m/d sinking velocity. As for case B, the 2 field (Fig. 8b) is spatially
correlated with the stream function, and rich zooplankton patches are localized in
the southern part of anticyclonic eddies. Zooplankton biomass does not reach such
high levels as in case B: with a detritus sinking velocity of 1 and 2 m/d, the maximum
2 concentration varies from 0.139 to 0.117 mmol N/m3. The nitrogen-nutrient
field
presents the same characteristics as the 2 one (Fig. 8~). Highest nutrient concentration values over the domain are 0.08 and 0.065 mmol N/m3 for a 1 and 2 m/d sinking
velocity, respectively. The maximum ratio between “upwelled” and “regenerated”
production (detritus remineralization
and zooplankton excretion) as defined previously is equal to 0.9 for case C with 1 m/d sinking velocity and even higher with a
2 m/d sinking velocity.
Introducing detritus leads to an increase in phytoplankton
concentration and a
decrease in zooplankton and nutrient concentrations. As the sinking velocity increases, this tendency is even more pronounced. This process is confirmed by looking
at the time evolution of the maximum value of phytoplankton concentration over the
domain for the different sinking velocities and different cases (A, B and C) (Fig. 9).
Case B (with no detritus) gives the highest concentration of P during the first 20 days.
For case C, the maximum variation in P is observed after day 40 with a 2 m/day
sinking velocity.
Information
about the temporal variability of the flow field and the biological
dynamics was obtained from an array of 9 “moorings” deployed across the frontal
zone, each having “bio-physics” sensors within and under the ML. The positions of
the model moorings are denoted by stars in Figure 6 and labelled by numbers in
Figure 6a at day 0. As an example, time series of the different fields: s(PO - PI), u .
VP, ~(2, - Z,), u . VZ, s(N, - N,), u . VN, s(DO - Dl), u . VD, P, Z, N, D and
components of the biological equations budget are displayed in Figure 10 for the
mooring 2.
During the first 25 days, positive vertical velocities of up to 0.4 m/d occurred at the
base of the ML. The biological fields show a response influenced by both the vertical
forcing and advection. In response to upwelling in the ML, nitrogen-nutrient
concentration increases in the very first days followed by a 28% increase of the
332
Journal of Marine Research
P472
-G
i
-500
Yax
= 0.20
0
-500
Longitude
,-. -...“.f
1000’
1
Isocontour
.
interval
,
500
1000
(km)
,
: 0.01
.T ..“.
_
_
rnmoW/na3
,
,
2
500
2
Q
0
I
2r’
*!
:
-2O”N
i
-500
-1000
-1000
Max
= 0.139
Min
= 0.014
4
.
* .
-500
i
.__&_A
0
Longitude
.
500
.
b) :
_
1000
(km)
Figure 8. Horizontal distributions (mmol N/ m3)in the mixed layer at day 300for the caseC
(a) for phytoplankton concentration (contour interval is0.01 mmolN/m3) (b) for zooplankton concentration (contour interval is 0.01mmol N/m3), (c) for nutrient concentration
(contour interval is 0.01mmol N/m3) and (d) for detritus concentration (contour interval is
0.05mmol N/m3). The color codeis the samethan Figure 7.
uptake of nutrient by phytoplankton. A phytoplankton peak (0.17 mmol N/m3)
occurs at day 5, followed by a zooplankton peak (0.08 mmol N/m3) due to a grazing
increase of 58%. Zooplankton death and fecal pellets fluxes then increase by 60%
and 58%, respectively; they create a maximum in detritus concentration at day 15
(Fig. 10). Due to a 36% increase of remineralization, around day 20, a second
Dadou et al.: Impact of NEC meandering on a pelagic ecosystem
333
500
3
?.
0)
2
-2O”N
0
z
-500
!
i
-1000;
-1000
Max
=
Min
= 0.008
_ ‘ 1
-500
”
0.08
1
‘
L- 2.. _. *.
0
Longitude
(km)
A .
. f
Isocontour
interval
_ _I . ..”
500
4’:
I
1000
, ,.....
i ” .._....-..../
: 0.05
”
D
mmoW/m3
-2O”N
-500
Maz
Min
= 0.3
= 0.046
.‘
500
-1000
-500
-1000
0
Longitude
_/
d
1000
(km)
Figure 8. (Continued)
maximum of nutrient concentration takes place. During these first 40 days, the
different fields are mostly affected by vertical velocities. After day 40, horizontal
advection begins to play a crucial role (Fig. 10). In the mooring 2 area, a patch with a
poor content in phytoplankton
and a rich content in zooplankton, nutrient and
detritus is advected (Fig. 10). After day 90, another upwelling period occurs.
d. Significance
duration. Figure 11 shows the time evolution of the
(N, P, Z, D) for 25 days at two different moorings 2 and 8
model behavior is different over this period at the two
of upwelling
biological concentrations
(Fig. 6a). The biological
Journal of Marine Research
334
0.12
,,I,
0
/I,,
20
I
40
I,
60
Time
[54,2
80
I
100
120
(day)
Figure 9. Evolution with time of the maximum and minimum values of phytoplankton
concentration (mmol N/m3) for the different casesand different sinkingvelocities (1 and
2 m/day).
mooring locations because of upwelling duration. At mooring 2, where the upwelling
duration is 29 days, the temporal evolutions of N, 2, and D are very similar. At
mooring 8, where the upwelling duration is only 19 days, we do not observe the same
features. The maximums of 2, D and N are slightly offset in time and the associated
curves have different shapes. The phase shift between phytoplankton peak and
zooplankton, nitrate and detritus peaks is also reduced. As pointed out by Flier1 and
Davis (1993), the wave length or frequency of an eddy is important for the biological
dynamics. The importance of vertical velocity duration on the biological dynamics is
confirmed by sensitivity studies we performed. We integrated in the ML the NPZD
biological equations with zero dimension over time and clearly identified two
upwelling episodes of different durations which characterized the two different
behaviors observed in the QG coupled layer model.
6. Discussion and conclusion
a. SigniJicanceof modeled meandering on plankton distribution and activity. Within the
framework of the EUMELI program, we have explored the influence of meanders
and eddies of the NEC on the biological dynamics. The latter have been obtained
19961
335
Dadou et al.: Impact of NEC meandering on a pelagic ecosystem
0.00
0
20
40
60
80
100
0
20
40
60
80
0.10
100
9.12
0
20
40
60
80
100
0
20
40
60
80
100
0
20
40
Time
60
(day)
80
100
0
20
40
0
20
40
Time
Figure 10. Evolution in the mixed layer at mooring
s(P, - P,) and horizontal advection of phytoplankton:
60
80
100
60
(day)
80
100
2 of (a) dilution of phytoplankton:
u.VP, (b) phytoplankton
concentra-
tion and balancesof terms in the phytoplankton equation; (c) dilution of zooplankton:
s(Z, - Z,) and u.VZ; (d) zooplankton concentration and balancesof termsin the zooplankton equation; (e) dilution of nutrient: s(Na - Nt) and u.VN, (f) nutrient concentration,
regeneratedand “upwelled” production and their ratio; (g) dilution of detritus: s(Da- Dt)
and u.VD; (h) detritus concentration and balancesof termsin the detritus equation.
through a conventional
scenarios between the
dynamics models have
pumping nor diapycnal
description of two biological models. Three distinct coupling
21/2 layer QG model for the physics and the two plankton
been considered. At this stage of our study, neither Ekman
mixing is considered in such a simple model.
336
Journal of Marine Research
0
10
30
20
0.060.""":""""'
[54,2
0
IO
20
30
" "
Zooplankton
I
0
IO
20
30
0
10
20
30
0
IO
20
30
0
IO
20
30
0
10
Time
20
30
0
10
20
30
0.040.
0.038:
(days)
Mooring
Time
8
(days)
Mooring
2
Figure 11. Evolution of phytoplankton, zooplankton, nutrient and detritus concentrations
(mmolN/m3) for two different upwellingdurations at moorings2 and 8.
Our simulations have shown that mesoscale hydrographicvariability
seems to have
a significant impact on the biological dynamics in the NEC. In fact, in the model,
meanders and eddies formed by baroclinic instabilities cause upward motion of
water transporting nitrogen into the euphotic layer. This nitrogen induces an
enhancement of production and of biomass of phytoplankton.
In the jet zone, the
simulated primary production integrated over the ML ranges between 0.51 and
19961
Dadou et al.: Impact of NEC meandeting on a pelagic ecosystem
337
0.72 gC/m2/day. This is low compared with the values of 0.6 to 1.3 gC/m2/day for the
Almeria-Oran
frontal zone in the occidental Mediterranean
Sea (Lohrenz et al.,
1988); but is substantial compared with the values of 0.22 to 0.27 gC/m2/day
associated with the ML dynamics at Station P in the North Pacific Ocean (Prunet et
al., 1995). Maximum
vertical velocities occur during the periods of eddy-eddy
interactions. Enhancement of the phytoplankton biomass seems well correlated with
high vertical velocities and localized at the edge of eddies. In different parts of the
world oceans, maximum phytoplankton
concentration at the edge of a vortex has
been observed in many warm core rings and eddies (Tranter et al., 1983; Nelson et al.,
1985; Woods, 1988). The processes causing these maxima have been investigated by
models. For example, Yoshimori
and Kishi (1994) used a barotropic
quasigeostrophic model to investigate the interaction between eddies of the Kuroshio
current and biology. They found the main mechanism responsible for the phytoplankton enrichment at the edge of eddies to be the interaction between two warm core
rings.
A modeling approach allows one to quantify the components of the biological
budget over time which is unrealistic with in situ measurements. Figure 12a displays
the nitrogen budget for mooring 2 integrated over the 100 days of simulation, using
the case C model with a 1 m/d sinking velocity. In terms of the physics, the main
source of nutrient is upwelling due to eddies. The upwelled nutrient flux is 1.6 mol
N/m2 over the 100 days. It can reach 5.7 mol N/m2 over the 100 days for mooring 6
(Fig. 12b). Nitrate flux associated with the ML dynamics in the Sargasso Sea (Doney
et al., 1996) is low (0.27 mol N/m2/100 d) compared with the nitrate flux associated
with the mesoscale circulation in the NEC, but nitrate flux associated with the ML
dynamics at station P (Prunet et al, 1996) is comparable (4.5 mol N/m2/100 d).
The nutrient uptake is balanced by grazing. Zooplankton death and fecal pellets
represent 63% and 37% of the detritus flux, respectively; only 4% of this detritus flux
sinks into the aphotic layer and 78% is remineralized
in the euphotic layer. As
already pointed out in part 5c, between days 240 and 290, horizontal advection plays
a crucial role in the variability of zooplankton, nitrate and detritus concentration,
even if the integrated effect of horizontal advection over the 100 days is small.
We define two quantities which characterize the biological pump efficiency. The
first one is the ratio between total uptake (ulNP) and exported production (WsDO),
the second is the ratio between the “upwelled” production and the export production which quantifies the importance of vertical upwelling to the exported production. We examined these two ratios at the nine mooring sites in the ML during the
100 days of simulation in case C with a 1 m/d sinking velocity. The ratio (uZNPI
WsDo) ranges between 30. and 26. The variation of this ratio can be as high as 17.4%
at mooring 6 (Fig. 12b). The ratio s(No - N1)/WsDO ranges from 0.008 at mooring
3 to 4.4 at mooring 6. At mooring sites undergoing frequent upwelling episodes
(Fig. 12b), the two ratios as defined above display rather high values. The “upwelled”
338
Joumai of Marine Research
[54,2
17.4%
MOOR 6
Biological
pump, - -t&
uw +u.vz
+u.vN+u.vD
uINP/WSDO=30.
s(NO-Nl)
5.7
81
Ws Do (b)
1.3
I
Figure 12. (a) Schematic of the mean nitrogen cycle (mol N/m2/100 day) for 100 days at
mooring 2 in using the model C with a 1 m/day sinking velocity integrated over the mixed
layer. Dashed and oblique arrows represented horizontal advection and horizontal dissipation, respectively. Numbers in each box indicate the storage values for the different
biological state variables integrated over the 100 days. Evolution of the nitrogen flow (mol
N/m21100 day) and carbon flow (shaded numbers represent values in gC/m2/100 day)
contributing to the biological pump at different moorings in the simulated domain integrated over the mixed layer: (b) at mooring 6, (c) at mooring 2 and (d) at mooring 3.
Nitrogen flow is converted in carbon flow using a C/N ratio of 105/l%
nitrogen (carbon) flux largely dominates the nitrogen loss by detritus sinking, instead
the net upward flux roughly equals the nitrogen output by horizontal advection. On
the contraq, at mooring locations rarely visited by upwelling events (Fig. 12d), these
two ratios are low; here the carbon input by advection feeds the carbon loss by
biogenic sedimentation.
b. Regional influence of the meanakring NEC. The net effect of the frontal zone on the
whole domain is significant. The jet zone contributes to 48% of the primary
production
of the entire simulated domain, although the jet zone contributes
only
30% of the surface area. For the exported production, this contribution is 46%. We
compared two model simulations: one eddy-resolving (with a 15 km space resolution) and the second noneddy resolving (with a 125 km space resolution) and found
‘the mean values of the primary and exported productions in the jet were doubled by
the presence of eddies.
19961
Dadou et al.: Impact of NEC meandering on a pelagic ecosystem
339
Sinking velocities in the present study were low (1 and 2 m/d; Siegel et al., 1990)
because the major group in abundance is microplankton.
In nature, we could expect
a higher response of phytoplankton with a higher sinking velocity, due for example to
aggregation or to a change in the size of the plankton population (diatoms or
macrozooplankton).
The interactions between the sinking velocity, and the horizontal and vertical velocities associated with eddies are very important in determining
the flux of particles between the euphotic layer and the deep ocean. This feature had
project, sediment
already been pointed out by Siegel et al. (1990). In the EUMELI
traps were deployed over a two-year period at the oligotrophic site. The carbon flux
from the sediment trap located 200 m above the bottom presents a fluctuation with a
30-40 day period (Khripounoff et al., 1994). Comparison of data from two 2000 m
deep sediment traps, just 100 km apart (one from EUMELI-19N,
21W and the
second from the BOFS project) shows clearly mesoscale variability, the particle flux
being different with time between the two traps (Newton et al., 1994).
In summary, we have investigated the influence of weak mesoscale hydrodynamic
variability on plankton dynamics as observed in the North Equatorial Current
(Southern Canary Basin) using coupled physical/biological
models. Despite the
simple features of our pelagic ecosystem models, results presented here show clearly
that the North Equatorial Current meandering can cause significant perturbations to
planktonic populations and to the biological pump efficiency.
Acknowledgments. This study has been funded jointly by a grant from the Centre National de
la Recherche Scientifique (JGOFS-France:
Modelling
program) to UMR39 and URA716,
and by two grants: ONR-URIP
N00014-92-J-1.527 and NSF/NOAA
GLOBEC NA366P0289
to G. F. and C. D. The model computations were carried out on the CNES (Centre National
d’Etudes Spatiales) Cray-2 machines. We wish to thank Steve Meacham who provided
assistance to I. D. during her three-month
stay at WHO1 in summer 1993 at the early stage of
this work. We also thank F. Jochem, S. Podewski, R. Morrow and three anonymous reviewers
for critical reading of the manuscript. This work benefited from constructive advice from S.
Podewski and scientists involved in the EUMELI
field program. The EUMELI
data which
they provided is most appreciated.
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