Estuarine, Coastal and Shelf Science 65 (2005) 421e439
www.elsevier.com/locate/ECSS
Biological and physicochemical factors controlling
short-term variability in phytoplankton primary
production and photosynthetic parameters in a
macrotidal ecosystem (eastern English Channel)
Fabien Jouenne a,*, Sébastien Lefebvre a, Benoı̂t Véron a, Yvan Lagadeuc b
a
Laboratoire de Biologie et Biotechnologies Marines, Universite´ de Caen Basse-Normandie, 14032, CAEN Cedex, France
b
FR/IFR CAREN; UMR-CNRS Ecobio, Universite´ de Rennes 1, 35042 RENNES Cedex, France
Received 22 November 2004; accepted 30 May 2005
Available online 2 August 2005
Abstract
Links between short-term variability of phytoplankton primary production and community structure changes have been studied
rarely. This has been examined in a macrotidal ecosystem, the Baie des Veys (eastern English Channel, France), in 2003 and 2004,
over the complete tidal cycle (semi-diurnal mode, 12 h). Within this area, primary production and photosynthetic parameter
estimates, according to the 14C incorporation technique, were supported by an exhaustive taxonomic study and measurements of
physicochemical factors to illustrate the environmental framework. Related to the river Vire discharge, daily interactions between
estuarine and bay waters were demonstrated. Depth-integrated primary production Pz was maximal around noon in the bay (48.7e
68.0 mg C m2 h1) and decreased through the day in the mouth of the river. Photosynthetic parameters’ variations and
photoacclimation were influenced by the ecosystem variability level: short-term photoacclimation was possible in low mixing
conditions. Changes in taxonomic composition according to tidal forcing led to variations in primary production levels. Large
species, associated with high photosynthetic parameters, were observed in the bay, whereas small ones were present in the mouth of
the river, when low primary production was measured. On a short-time scale, a positive relationship was observed between species
diversity and primary production. This work emphasizes the need to focus on changes in phytoplankton community structure in
order to understand short-term variability in primary production.
Ó 2005 Elsevier Ltd. All rights reserved.
Keywords: phytoplankton; short-term variability; primary production; photosynthetic parameters; macrotidal; species composition; eastern English
Channel
1. Introduction
Shallow and macrotidal estuaries are highly variable
systems in the short term due to strong influences
exerted simultaneously by tides and river flow on their
hydrological structure (Trigueros and Orive, 2000). In
* Corresponding author.
E-mail address: [email protected] (F. Jouenne).
0272-7714/$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved.
doi:10.1016/j.ecss.2005.05.023
the natural environment, especially turbid, well-mixed
temperate estuaries, algae will seldom experience constant conditions (Kromkamp and Peene, 1995). As
variations in light climate are regular and rapid, it is
difficult to understand and define a system without
studying its variations on different spatial and temporal
scales. Previous studies have addressed the variability of
primary production on seasonal (e.g. Mallin et al., 1991;
Macedo et al., 2001; Ignatiades et al., 2002), daily
422
F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
(e.g. Prézelin and Matlick, 1980; Côté and Platt, 1983;
Valdez-Holguin et al., 1998), diel (Lizon et al., 1995;
Goosen et al., 1999; Brunet and Lizon, 2003) and both
daily and diel scales (e.g. MacCaull and Platt, 1977;
Madariaga, 1995; MacIntyre and Cullen, 1996). Studies
focussing on within-day variability have often been
based on three sample points per day (Neale and
Richerson, 1987; Madariaga, 1995; MacIntyre and
Cullen, 1996). Since the rate of diel changes in the
photosynthetic parameters aB (the light-limited slope)
and PBmax (the light-saturated rate) is high, realistic
characterization of the amplitude and timing of the cycle
requires reasonably high sampling frequencies (%2 h)
(Behrenfeld et al., 2004). In addition, Côté and Platt
(1983) showed that changes in both aB and PBmax are
negatively correlated with mean cell volume changes,
highlighting the need to analyse community structure. A
consistent relationship between aB or PBmax and species
composition was not, however, achieved in their work,
despite supporting microscopic identifications. Microalgal population determination is essential for understanding the dynamics of the primary production
because it is known that the species composition can
play a dominant role in the variations of production,
especially in well-mixed interface areas, such as estuaries
(Falkowski and Owens, 1980; Malone and Neale, 1981;
Pennock and Sharp, 1986; Videau et al., 1998; Shaw and
Purdie, 2001; Behrenfeld et al., 2004).
The Baie des Veys is an estuarine intertidal ecosystem
(macrotidal) in Normandy, north-west of France, where
tidal forcing leads to a variability in a large range of time
scales. This interface area has here been used for a study
of short-term variability in phytoplankton primary
production and microalgal community structure. Few
quantitative estimates of biological transport between
estuaries and the sea exist and the role of biological
transport is uncertain (Dame and Allen, 1996). The
current study is based on two questions: (1) what is the
short-term variability of phytoplankton primary production and photosynthetic parameters in a high
variability interface area? (2) and which forcing parameters (biotic and abiotic) can influence this production
on a temporal micro-scale and what is the influence of
phytoplankton community structure variations on
primary production? These links between primary production and microalgal flora have been studied rarely,
and an influence of phytoplankton community structure
changes on primary production variations was expected.
Sampling was carried out in the Baie des Veys, in 2003
and 2004 over the tidal cycle (semi-diurnal mode). Six
sampling missions were undertaken through each day,
where primary production, photosynthetic and physicochemical parameters were measured. An exhaustive
phytoplankton identification was also made for each
sample, including qualitative determination, cell counting and biovolume measurement.
2. Materials and methods
Abbreviations and units used are summarised in
Table 1.
2.1. Sampling area and methodology
The Baie des Veys is located in the north-west of
France, in Normandy, in the western Bay of Seine
(Fig. 1). This is an intertidal ecosystem with a maximum
tidal range of 8 m (macrotidal), an area of 35 km2 and
a catchment area of 3000 km2 (Ducrotoy and Sylvand,
1991). Freshwater inputs derive from the discharge of
four rivers (Fig. 1) notably the main river, the Vire.
Sampling was undertaken on two occasions (26th
June 2003, during low river discharge period, and 29th
April 2004, at the end of high river discharge period) in
the Baie des Veys, each over a whole tidal cycle (semidiurnal mode) with sampling every 2 h (Table 2). Two
stations were sampled: one in the north of the bay (bay)
and an estuarine station in mouth of the river Vire
(Estuary) (Fig. 1). The sampling frequency was not
always constant because of the intertidal characteristics
and difficulties in reaching the north of the bay. Two
depths were sampled: at the surface (incident light
intensity E0) and at depth (E20 corresponding to 20% of
E0; depth was chosen because of the low water mean
depth of the study area).
2.2. Biomass and physicochemical measurements
Chlorophyll biomass was estimated by fluorimetry
(TD700, Turner Designs, Sunnyvale, California, USA)
Table 1
Abbreviation and units
S
T
SPM
POM
PIM
k
DIN
Si(OH)4
PO4
H#
Ez
E0
E20
Em
chl a
B
PBmax
aB
bB
Ek
PB
Pz
Salinity
Temperature ( C)
Suspended particulate matter (mg l1)
Particulate organic matter (mg l1)
Particulate inorganic matter (mg l1)
Light extinction coefficient (m1)
Dissolved inorganic nitrogen Z nitrate C nitrite
C ammonium (mM)
Silicate (mM)
Phosphate (mM)
Species diversity
Measured light at depth z (mmol photons m2 s1)
Incident light (mmol photons m2 s1)
20% of incident light (mmol photons m2 s1)
Mean light in the water column (mmol photons m2 s1)
Chlorophyll a
Biomass (mg chl a m3)
Maximum photosynthetic rate (mg C mg chl a1 h1)
Maximum light utilization coefficient (mg C mg chl
a1 h1 (mmol photons m2 s1)1)
Photoinhibition parameter
Light saturation parameter (mmol photons m2 s1)
Photosynthetic rate (mg C mg chl a1 h1)
Depth-integrated primary production (mg C m2 h1)
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F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
UK
English Channel
France
N
W
E
S
49°25’N
Ste Marie
du Mont
Bay
Grandcamp-Maisy
Douve
Estuary
Aure
49°20’N
Carentan
Isigny sur Mer
Taute
VIRE
49°15’N
1 km
1°15’W
1°10’W
1°05’W
1°00’W
0°55’W
0°50’W
Fig. 1. The Baie des Veys. Stars show sampling stations, bay (49 24#N, 01 06#W) and estuary (49 20#N, 01 05#W).
Table 2
Sample set details (GMT): tidal and atmospheric conditions (data:
Météo-France, DIREN). Because of inclement atmospheric conditions
on the 29th of April 2004, the bay station was not sampled at 16:00 and
18:00
June 26, 2003
Tidal height (m)
High tide time
Low tide time
Second high tide time
Sampling time
5.17 (neap tide)
06:15
12:00
18:00
8:00, 10:00, 11:00,
14:00, 16:00, 18:00
River Vire discharge (m3 s1) 2.1
(month average)
Total rainfall (mm)
0.2
Tair ( C) (mean G SD)
16.6 G 0.7
Wind (m s1) (mean G SD)
5 G 0.8
April 29, 2004
4.58 (neap tide)
04:00
11:00
17:00
7:00, 9:00, 13:00,
15:00, 16:00, 18:00
5
8.8
10.5 G 0.4
6.1 G 3
according to Aminot and Chaussepied (1983) and
further modified by Welschmeyer (1994). Suspended
particulate matter (SPM), particulate organic matter
(POM) and particulate inorganic matter (PIM) were
measured according to a standard weight measurement
(Aminot and Chaussepied, 1983). Temperature, salinity
and depth measurements were obtained with a CTD
Seabird probe (Turner Designs, Sunnyvale, California,
USA). Light was measured with a water 4p sensor
(LI-COR LI1400, Lincoln, Nebraska, USA). Nutrients
(NO3, NO2, Si(OH)4, PO4) were measured with a TechniconÒ Autoanalyzer AA II and NH4 with a spectrophotometric method according to Aminot and
Chaussepied (1983). Nitrate, nitrite and ammonium
have been integrated in this work into dissolved
inorganic nitrogen (DIN).
424
F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
2.3. Phytoplankton community structure
For each station and both depths, 500 ml of seawater
were sampled for the study of the microalgal flora.
Microalgal identification, measurement and counting
were carried out, using light microscopy. Samples were
fixed with glutaraldehyde (1% of final volume) and
counting was conducted on Sedgewick-Rafter cells, less
than six months after fixation. Measurements of the
dimensions of individual cells were carried out according to Hillebrand et al. (1999) with a micrometer and
using image analysis software (PEGASE Pro, 2I System,
Paris, France). The median of measured dimensions was
retained for the final calculation of species biovolume.
Mathematical formulae associating each microscopic
alga with geometrical forms were used for biovolume
calculation (Hillebrand et al., 1999). When possible, 10
specimens per species were measured. Hillebrand et al.
(1999) advised glutaraldehyde measurement of a total of
25 specimens for a robust analysis. Nevertheless, with 10
measures, standard errors did not exceed 10% of the
mean (Hillebrand et al., 1999) and this total is
considered appropriate for in situ experiments. Cell
density and biovolume data were used to determine
dominant species. Mean cell volume was determined for
each microalgal cell measured and linked to cell density
in order to obtain biomass in mm3 l1 (microalgal
volume per litre of seawater). Species diversity was
calculated following Shannon and Weaver (1949) in
Frontier and Pichod-Viale (1998) as:
X
H 0Z fi log2 fi
Where fi (species i relative frequency)
P Z Ni/N (Ni: species i cell density in cells l1; N Z Ni).
2.4. Primary production
Characterizing short-term responses requires rapid
and precise measurements and it is recommended to run
brief simulated in situ incubations immediately after
sampling (Henley, 1993). Thus, primary production
measurements were conducted using the 14C incorporation method (Steemann Nielsen, 1952). Simulated in situ
incubations were conducted in a radial photosynthetron
(Lewis and Smith, 1983; Babin et al., 1994) for 40 min,
to avoid photoacclimation in the flasks (Lizon and
Lagadeuc, 1998). As soon as possible after sampling
(within 30 min), the seawater was dispensed into culture
flasks of 50 G 0.2 ml. Fifty microlitres of sodium
bicarbonate, marked with 14C (2 mCi) in aqueous
solution (pH Z 9.5), was added. The flasks were placed
in the black boxes of the photosynthetron and optical
filters (Neutral Density 0.3, 1 Stop) were inserted
between the flasks in order to create a gradient of
light: 1300, 1100, 900, 750, 350, 150, 50, 25 and
10 mmol photons m2 s1. The last flask was in the dark
(Zblank, 0 mmol photons m2 s1). A 1000 W Metal
Halogene PowerstarÒ HQI lamp (OSRAM, Winterthur,
Switzerland) was used as the light source. The temperature within the boxes was controlled by a seawater
circuit. At the end of the incubation, 250 ml of 37%
formaldehyde was added in order to stop photosynthetic
activity (Tuomi et al., 1999). In the laboratory, the
subsamples were filtered (Whatman GFC, 25 mm,
Brentford, Middlesex, UK) and the filters placed in
20 ml scintillation vials. HCl 1 N (250 ml) was pipetted
onto each filter in order to degas any radioactive
inorganic carbon (Lean and Burnison, 1979; Parsons
et al., 1984a). Fifteen minutes later, 10 ml of scintillation
cocktail (Hionic Fluor, Perkin Elmer Life Sciences,
Boston, Massachusetts, USA), containing a chemoluminescence self-extinguisher, was added to the filters.
Radioluminescence from scintillation vials was counted,
at a rate of 2 min per vial, with a counting window
ranging between 10 and 156 keV. From disintegrations
per minute (DPM) counts, primary production estimates were obtained in mg C m3 h1 using conversion
formulae (Parsons et al., 1984). The estimated value for
blanks was subtracted from all others and results
obtained were standardized according to the chlorophyll
a biomass in order to obtain estimates of primary
productivity in mg C mg chl a1 h1. The model of Platt
et al. (1980) was employed to fit the P vs. E curves
(Systat 10 software (SPSS, Chicago, Illinois, USA),
nonlinear regression model) and to estimate photosynthetic parameters: maximum photosynthetic rate (PBmax),
maximum light utilization coefficient (aB), the light
saturation parameter (Ek Z PBmax/aB) and the photoinhibition parameter (bB). Estimates of the light
extinction coefficient k were made using in situ light
measurement in order to calculate depth-integrated
primary production Pz. Ez is the light measured at
depth z and Em is the mean light in the water column.
Ratios Ek/Ez and Pz/Em were calculated. Em is estimated
with E0, k and maximal depth. Ratios Ek/Ez close to 1
illustrate a photoacclimated state (Ek and Ez are almost
equal), at ratios above 1 light is insufficient for optimal
production (light limitation), and under 1 light is too
high to be efficiently transformed into chemical energy
(Tillmann et al., 2000).
2.5. Numerical analysis
Difference between surface and depth were estimated
using the Wilcoxon test, a non-parametric test for paired
samples without normal distribution (Zar, 1999). Coefficient of variation (CV) was used to analyse variability
(Zar, 1999). A principal components analysis (PCA) was
performed upon data to analyse the relationships
between physicochemical and biological parameters.
Biomass of dominant species was plotted in this study
F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
as illustrative variables in order to appreciate the
distribution of these species among active variables
which build the axes. PCA was conducted with SPAD v.
4.5 software (CISIA, Montreuil, France).
425
Mean depth varied between 5.4 G 0.2 m at high tide
and 2.1 G 0.2 m at low tide at the bay station and varied
between 4.1 G 0.2 m at high tide and 0.8 G 0.2 m at low
tide at the estuary station. According to the Wilcoxon
tests, water column temperature was homogenous
(Fig. 2a, Table 3), whereas salinity showed variations
between surface and depth, especially in June 2003
(Fig. 2b, Table 3). Surface salinity was lower in the
bay at low tide. There was a significant vertical
difference for SPM in June 2003 (Table 3). Concerning
SPM fractions, the measurements in June 2003 and
April 2004 revealed significant correlations between
PIM and SPM (PIM Z 0.85 SPM 2.3; R2 Z 1, n Z 44,
P ! 0.01), and POM and SPM (POM Z 0.15
SPM 2.3; R2 Z 0.9, n Z 44, P ! 0.01). PIM concentrations were always higher than those of POM (data
not shown). On both sample dates, SPM increased at
low tide (Fig. 2c).
No significant difference in nutrient concentrations
between surface and depth was revealed by the
Wilcoxon test (Table 3). However, it should be noted
that values measured at the surface were sometimes
higher than those of deeper waters, particularly at the
estuary station in June 2003 at the beginning of the day
(Fig. 2d, e). DIN concentrations in the bay were near
zero in June 2003 (Fig. 2d, Table 3). A strong correlation existed between DIN and silicate (Si(OH)4 Z
0.28 DIN C 4.5; R2 Z 0.96, n Z 44, P ! 0.01), but
not between DIN and phosphate. In April 2004,
nutrients levels were relatively high in the estuary
(Table 3).
In the estuary during April 2004, greater variability in
water temperature and salinity was shown by the
coefficients of variation (Table 3). Temperature variability was always low, whereas salinity fluctuations in
the estuary reached 164% in the second sample set. SPM
was more variable in the river Vire in both sample sets
and coefficients of variation were higher in June 2003
(Table 4). DIN values varied by up to 100% in the
estuary in June 2003, whereas they were more variable in
the bay (36%) than in the estuary in April 2004.
reached 1.7 G 0.2 at the bay and 1.5 G 0.2 at the
estuary. Members of the class Bacillariophyceae, i.e.
diatoms, were most common (64% of total species).
Five species are regarded as dominant at the two sites
(Table 5). Rhizosolenia stolterfothii dominated the bay
throughout the day (Fig. 3a) and its biovolume and
biomass reached high levels at both stations. In the river
Vire, its vertical distribution showed significant differences (Table 5) with higher biomass at depth and
significant temporal variability (Table 4). At low tide
and during ebb, microscopic observations showed that
Asterionellopsis glacialis (CV Z 194%) and Chaetoceros
socialis were present as well as R. stolterfothii, but their
respective biomasses were insignificant compared to
R. stolterfothii (Fig. 3a). These two species were also
present in the estuary (Fig. 3b), A. glacialis with the
higher biomass (Table 5). Nevertheless, its predominance in the estuary was reduced by the presence of
R. stolterfothii at high tide (Fig. 3b). Moreover, at 14:00,
Scenedesmus quadricauda (Fig. 3b), various unidentified
flagellates and Gymnodinium species (data not shown)
were observed in the estuary while R. stolterfothii
declined. A difference of biovolume between these latter
microalgae within the bay and those of dominant species
in the estuary was observed (40 100 G 4700 mm3 for
R. stolterfothii vs. an average of 330 G 180 mm3 in the
river Vire).
In April 2004, 49 species were observed in the Baie
des Veys and the Vire estuary (see Appendix A). H# was
1.9 G 0.2 at the bay station and 1.2 G 0.2 in the river
Vire. Diatoms were again the major class (65%), five
species dominating the Baie des Veys (Table 5). Within
the bay, Cerataulina pelagica and Lauderia annulata
were the main species (Fig. 3c). At 09:00, during the ebb,
a non-negligible presence of Cyclotella sp. at the marine
station was observed. Its rapid appearance is confirmed
by a high CV at the bay (245%, Table 4). As in June
2003, Chaetoceros socialis was observed in the estuary
(data not shown), but its contribution to the overall
biomass was diminished by the predominance of Cyclotella sp. which regularly exceeded 60% of the total
biomass (Fig. 3d). Only two marine species, C. pelagica
and L. annulata, which presented high CVs in the
estuary (Table 4), shared the total biomass with Cyclotella in the channel at high tide (Fig. 3d). The vertical
distribution of Cyclotella showed significant differences
with higher biomass at the surface (Table 5). As
observed in 2003, the biovolume at the estuarine station
was lower than that at the marine station (an average of
16 500 G 3600 mm3 in the bay vs. 1460 G 80 mm3 for
Cyclotella sp. in the estuary).
3.2. Microalgal flora
3.3. Photosynthesis and primary production
In June 2003, 73 species were observed at both
sample stations (see Appendix A). Species diversity H#
In June 2003, photosynthetic parameters’ estimates
showed a significant positive correlation between aB and
3. Results
3.1. Physicochemical factors
426
F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
June 2003
April 2004
T
(a)
22
22
18
18
14
14
10
10
6
6
6
7
8
9
10
11 12
13 14 15
16 17 18
19 20
S
(b)
40
40
30
30
20
20
10
10
6
7
8
9
10
11 12
13 14
15 16 17 18 19 20
(c)
160
120
120
80
80
40
40
SPM
160
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
(d)
DIN
8
9
10
6
7
8
9
10 11 12
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
GMT
11 12
13 14 15
16 17 18
19 20
13 14 15 16
17 18 19
20
0
0
360
360
300
300
240
240
180
180
120
120
60
60
0
0
6
PO4
7
0
0
(e)
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
10
10
8
8
6
6
4
4
2
2
0
0
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
GMT
Bay depth
Bay surface
Estuary depth
1
Estuary surface
Fig. 2. Physicochemical parameters. (a) Temperature in C; (b) salinity; (c) SPM in mg l ; (d) DIN in mM; (e) phosphate in mM. : low tide; : high
tide.
F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
Table 3
Physicochemical parameters: mean (SE), n Z number of samples,
*significant vertical difference, P ! 0.05
June 2003
T ( C)
S
SPM (mg l1)
DIN (mM)
PO4 (mM)
April 2004
Bay
(n Z 6)
Estuary
(n Z 6)
Bay
(n Z 4)
Estuary
(n Z 6)
17.6
32.2
46.1
1.4
0.6
20.6
17.1
72.1
36.6
5.1
11.3
31.5
15.6
13.3
0.7
12.1
3.9
19.7
286.7
3.9
(0.1)
(0.4)*
(3.5)*
(0.1)
(0.1)
(0.2)
(2.7)*
(10)*
(10.6)
(0.6)
(0.4)
(2)
(1)
(1.7)
(0.1)
(0.5)
(1.9)
(2.3)
(14.6)
(0.1)
PBmax in the estuary (R2 Z 0.91; n Z 12; P ! 0.01) but
not in the bay (Fig. 4a). PBmax was maximal around noon
(Fig. 5a) whereas aB was relatively constant at the bay
(Fig. 5b, Table 4). Greater variability occurred in
photosynthetic parameters at the estuary (Fig. 5aec,
(Table 4). For vertical distribution, significant differences were accepted only for PBmax and PB in the bay
(Table 6). In the estuary, values of PBmax and aB were the
same at surface and depth at 11:00 and 14:00, at low tide
and during ebb (Fig. 5aeb). Photoinhibition occurred at
both stations (Table 6). Chlorophyll a biomass increased
slightly at 14:00 in the bay (Fig. 5d) and no difference
was noticed within the water column (Table 6). In the
river Vire, the biomass increased between 10:00 and
11:00 then stayed constant and decreased from 16:00 to
18:00. Moreover, biomass variability was lower in the
estuary than in the bay (Table 4). The depth-integrated
primary production was maximal around noon at the
bay and decreased through the day at the estuary
(Fig. 5e). It ranged from 14.1 to 68.0 mg C m2 h1 at
the bay and from 11.8 to 161.0 at the estuary. Its CV
ranged between 46 and 75% through the day (Table 4).
In June 2003, incident light was higher during the two
Table 4
Coefficients of variation CVs (%). n.o. Z not observed. Biomasses of
microalgal species were used for calculation
June 2003
T
S
SPM
DIN
A. glacialis
R. stolterfothii
Cyclotella sp.
C. pelagica
L. annulata
B
PBmax
aB
Pz
April 2004
Bay
(n Z 6)
Estuary
(n Z 6)
Bay
(n Z 4)
Estuary
(n Z 6)
3
5
27
26
194
109
n.o.
n.o.
n.o.
36
24
12
46
5
54
48
100
76
139
n.o.
n.o.
n.o.
27
65
108
75
10
18
18
36
n.o.
n.o.
245
26
105
23
56
51
62
14
164
41
18
n.o.
n.o.
32
172
269
15
99
124
70
427
days before sampling and reached 2200 mmol
photons m2 s1 (Fig. 6a). The ratio Ek/Ez was close
to 1 at the surface at the estuary and at depth at the bay
while it was always less than 1 at the surface at the bay
and above 1 at depth at the estuary (Fig. 6b). No linear
relation was apparent in the ratio Pz/Em at both stations
(Fig. 7, black symbols).
In April 2004, PBmax and aB covaried in the estuary
2
(R Z 0.84; n Z 12; P ! 0.01) but not in the bay
(Fig. 4b). Although variations in photosynthetic
parameters were of lower amplitude than in 2003
(Fig. 5aec), CVs were higher (Table 4). The Wilcoxon
test revealed no significant differences in photosynthetic
parameters between surface and depth. Photoinhibition
was low at both stations (Table 6). Biomass was
constant at both stations and depths (Fig. 5d, Table 4).
Pz was maximal around noon at the bay and near high
tide in the estuary (Fig. 5e). It ranged from 12.3 to
48.7 mg C m2 h1 at the bay and from 4.6 to 27.5 at
the estuary, and exhibited a variability comparable to
2003 (Table 4). In April 2004, light intensity was lower
in the morning than in June 2003 and the sampling day
irradiance was again lower than the two previous days
(Fig. 6c). In April 2004, Ek/Ez was less than 1 except
for certain measurements at depth at the estuary
around tidal slacks (Fig. 6d). The ratio Pz/Em was
variable throughout the day and at both stations
(Fig. 7, white symbols).
3.4. Environmental and biological spatial comparisons
3.4.1. June 2003
Component 1 is characterized by a geographical
factor (Fig. 8a). The left part of the factor loadings plot
represents the estuary and the right part of the bay. On
the one hand, the estuary is defined by high nutrients,
SPM, biomass and temperature and, on the other hand,
the bay shows high salinity, photosynthetic parameters
and biovolume. Component 2 is built by light and it can
be related to the vertical distribution. The light is not
correlated to photosynthetic parameters. As expected
(Fig. 3), Rhizosolenia stolterfothii and Paralia marina are
located in the bay side of the plot and Asterionellopsis
glacialis, Chaetoceros socialis and Scenedesmus quadricauda in the estuary side, with a higher weight for A.
glacialis.
Sample ordination plot shows distinction between the
two stations (Fig. 8b). Bay samples are tightly grouped
in clusters which are located close to each other, whereas
estuary samples are loosely grouped in clusters which
are widely spaced. The low tide sets (11:00 and 14:00)
are widely spaced in the bay but close in the estuary.
ED8 and ED10 are closer than the other estuarine
samples to the bay side of the plot.
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F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
Table 5
Dominant species: biovolume and biomass (mean (SE)); n Z number of samples; *significant vertical difference, P ! 0.05; n.o. Z not observed
Biovolume (mm3)
June 2003
Asterionellopsis glacialis
Chaetoceros socialis
Paralia marina
Rhizosolenia stolterfothii
Scenedesmus quadricauda
660
36
1440
40 100
290
April 2004
Cerataulina pelagica
Chaetoceros socialis
Cyclotella sp.
Lauderia annulata
Rhizosolenia delicatula
15 300
180
1460
23 300
11 060
Biomass (106 mm3 l1)
Bay
Estuary
(65)
(4)
(270)
(4700)
(120)
(n Z 6)
6.7 (3.8)
0.5 (0.2)
6 (2.2)
3860 (1220)
n.o.
(n Z 6)
5790 (1270)
83.7 (11.6)
n.o.
4340 (1740)*
38.3 (21.6)
(1250)
(50)
(80)
(1820)
(2200)
(n Z 4)
280 (20)
2.2 (1.1)
11.7 (10)
290 (110)
30 (12)
(n Z 6)
820 (390)
10.6 (5.2)
10 400 (950)*
1150 (890)
n.o.
3.4.2. April 2004
The two components are defined, as in June 2003,
with a geographical gradient on the first and the vertical
distribution on the second (Fig. 9a). Therefore, SPM
was related to the incident light in April 2004 but, in
fact, maximal SPM at the estuary occurred simultaneously with the maximum light. On the other hand,
light was not correlated to aB or PBmax, the latter which
was negatively correlated to temperature. As expected,
marine species are situated in the bay side of the plot
and estuary is ruled only by Cyclotella sp.
For April 2004, the sample ordination plot (Fig. 9b)
shows higher distinction between the two stations than
in June 2003. Bay sample clusters are still tight, whereas
estuary sample clusters are wide and superimposed.
Nevertheless, concomitant surface and depth samples at
the estuary are less spaced than in June 2003. The 13:00
and 15:00 sample sets are the closest for the estuary.
ED7 and ED18 are closer than the other estuarine
samples to the bay side of the plot.
4. Discussion
4.1. The Baie des Veys: a short-term high variability
interface
The Baie des Veys is a restricted macrotidal ecosystem
(35 km2) with small catchment area (3000 km2) compared
to, for example, the Bay of Somme (eastern English
Channel, area 72 km2, catchment area 6000 km2; Ducrotoy and Sylvand, 1991; Rybarczyk et al., 2003) or the
Schelde estuary in the Netherlands (area 269 km2,
catchment area 22 000 km2; Middelburg and Nieuwenhuize, 2000). According to the present short-term results
(Table 3), it has a low turbidity (c.f. Seine estuary, mean
SPM: 260 mg l1, Rybarczyk and Elkaı̈m, 2003; Gironde
estuary, up to 1150 mg l1, Irigoien and Castel, 1997;
Middelburg and Nieuwenhuize, 2000), with intermediate
nutrients’ levels (c.f. Seine estuary, DIN 400e700 mM,
Aminot et al., 1998; Douro estuary, DIN 5e100 mM,
Middelburg and Nieuwenhuize, 2000). The maximum
photosynthetic rate PBmax and photosynthetic efficiency aB
estimates (Table 6) are coherent with those of previous
studies (c.f. Elbe: PBmax between 2 and 4 mg C mg chl
a1 h1 (Goosen et al., 1999); Biscay Bay, aBmean Z
0.034 mg C mg chl a1 h1 (mmol photons m2 s1)1
(Madariaga, 1995)).
An ecosystem such as the Vire estuary is a two-layer
circulation water column within which seawater is
measurably diluted with freshwater derived from land
drainage (Lohrenz et al., 1999; Elliott and McLusky,
2002). Biological and physicochemical interactions
between bay and estuarine waters occurred throughout
the day, on both sample dates. The two studied sites,
bay and estuary, were obviously separated by the PCA
(Figs. 8 and 9), reflecting distinct characteristics.
Nevertheless, the results illustrate the daily interactions
between these two stations. There was a daily freshwater
input at the surface of the bay station each low tide and
each sample date (Fig. 2b) and salinity showed a
significant vertical difference in June 2003 (Table 3).
As for the estuary, in June 2003, samples ED8 and ED10
were located close to the bay side of the ordination plot
(Fig. 8b) indicating the marine influence on the river at
high tide (Fig. 2b). Moreover, the salinity measurements
showed significant vertical difference in the estuary
(Table 3). The same process was observed in April 2004
with samples ED7 and ED18 (Fig. 9b) and with salinity
measurements (Fig. 2b) but it was less pronounced
because of weaker tidal forcing (extreme neap tide) and
a higher river discharge than in June 2003 (Table 2), an
observation confirmed by the negative Wilcoxon test on
salinity (Table 3). Regular exchanges of a similar nature
have also been observed in the Bay of Somme,
concerning nutrients (Loquet et al., 2000), and in the
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F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
June 2003
April 2004
(a)
8
(c)
10
14
11
16
18
7
9
13
15
16
18
Cp
Ag
Cs
Cy
La
Pm
Rs
8
10
11
14
16
18
7
(b)
8
9
13
15
16
Rd
18
(d)
10
11
14
16
18
Ag
7
9
13
15
16
18
Cp
Cs
Cy
Sq
Rs
8
La
10
11
14
16
18
7
9
13
15
16
18
%
100
50
0
8
10
11
14
16
18
GMT
Fig. 3. Phytoplankton community: species biomass from biovolume calculations (relative frequencies). (a) June 2003, station bay; (b) June 2003,
station estuary; (c) April 2004, station bay; (d) April 2004, station estuary. : low tide; : high tide. Species: Ag, Asterionellopsis glacialis, Cp,
Cerataulina pelagica, Cs, Chaetoceros socialis, Cy, Cyclotella sp., La, Lauderia annulata, Pm, Paralia marina, Rd, Rhizosolenia delicatula, Rs,
Rhizosolenia stolterfothii, Sq, Scenedesmus quadricauda.
Chesapeake bay with an annual transport of a dinoflagellate over a distance of 240 km due to the salinity
gradient (Tyler and Seliger, 1978).
Dame and Allen (1996) indicated that river flow is
a major cause of transport from estuaries to the sea and,
on the other hand, intrusion of marine waters at depth
in riverine estuaries exists and depends on tidal forcing.
The present work illustrated these exchanges. Twice
a day, in a semi-diurnal tidal modality (M2 component),
the Vire estuary is a source of surface freshwater, SPM,
nutrients, chlorophyll biomass and phytoplankton
species for the Baie des Veys. On the other hand, tidal
currents transport species to the depth of the river each
high tide. The short-term dynamics of DIN and silicate
are highly correlated, suggesting that these nutrients
have the same origin. The channel of the river Vire is
430
(a)
F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
5
y = 65.898x + 0.7652
R2 = 0.9083
n = 12; P < 0.01
PB max
4
3
2
1
0
0
0.01
0.02
0.03
0.04
0.05
0.06
0.02
0.025
0.03
B
(b)
2
y = 60.7x + 0.0603
R2 = 0.8403
n = 12; P < 0.01
PB max
1.5
1
0.5
0
0
0.005
0.01
0.015
B
Bay
interactions are influenced by the mixing level. In June
2003 the water column was pseudo-stratified, whereas
turbulence was more pronounced in April 2004 (higher
river discharge, stronger wind (Table 2), lower biomass
and DIN CV (Table 4)). Although a stratification index
was not calculated, several results indicate this distinction. The Wilcoxon tests on salinity, SPM, PBmax and PB
are the best illustration as there was a significant
difference between surface and depth in June 2003 and
not in April 2004 (Tables 3 and 6). Furthermore, sample
ordination plot show visible heterogeneity at estuary in
June 2003, while in April 2004 estuary clusters are
superimposed, which suggests a higher level of mixing in
the river. Distinction between the two stations is more
visible in April 2004 (Fig. 9b) when less marine influence
was observed in the estuary (Fig. 2b). These interactions
linked to hydrodynamics have previously been studied
from different contexts (Dustan and Pinckney, 1989; Bel
Hassen, 2001; Gargett et al., 2003; Wells and van Heijst,
2003).
Estuary
Fig. 4. Relationships between photosynthetic parameters. (a) June
2003; (b) April 2004; PBmax in mg C mg chl a1 h1, aB in mg C mg
chl a1 h1 (mmol photons m2 s1)1.
a nutrient-rich water mass compared to the Baie des
Veys sensu stricto (Table 3) and is the main source of
nutritive resources for the bay. A minor increase in
chlorophyll biomass was measured in the bay at low tide
in June 2003 (Fig. 5d) and a simultaneous decrease in
the estuary was observed at 14:00. Thus the estuary can
be considered as a source of phytoplankton biomass for
the bay. Asterionellopsis glacialis appeared in the bay at
low tide in June 2003 (Fig. 3a) and Cyclotella sp.
reached the marine station in April 2004 (Fig. 4a), both
having been transported from the estuary where they
were abundant (Fig. 3b, d). In June 2003, the marine
microalga Rhizosolenia stolterfothii entered the Vire at
depth at high tide (Fig. 3b) and Cerataulina pelagica and
Lauderia annulata were observed at high tide in the
estuary in April 2004 (Fig. 3d). High coefficients of
variation of these five species at the station where they
were not permanently abundant illustrate a transport
between bay and estuarine waters (Table 4). Previous
studies have demonstrated that vertical migration due to
phototactism and two-layer estuarine circulation are
able to induce a horizontal transport of phytoplanktonic
populations (Tyler and Seliger, 1978, 1981; Trigueros
and Orive, 2000). Brunet and Lizon (2003) indicated
that tidal currents cause periodical horizontal advection
of biomass at the surface with every low tide.
These interactions between bay and estuarine waters
have been termed ‘‘outwelling’’ (from estuary to the sea)
and ‘‘inwelling’’ (from the sea to estuary) (Odum, 1980
in Dame and Allen, 1996). In the present work, these
4.2. Primary production in a high variability ecosystem
Within the Baie des Veys, the trend in primary
production scheme seems to be coherent with other
studies on different sites, both for Pz (Fig. 5e) and
PBmax (Fig. 5a). Primary production maxima have been
previously measured in the morning hours or near zenith
and minima late in the photoperiod or early in the
evening (MacCaull and Platt, 1977; Platt et al., 1980;
Henley, 1993; MacIntyre and Cullen, 1996; Behrenfeld
et al., 2004). This trend was not visible in the Vire
estuary where the production dynamics showed greater
variability (Fig. 5a, e, Table 4). High values of PBmax at
high tide in the river (Fig. 5a) are coherent with previous
results in the Gironde estuary (Goosen et al., 1999),
where a tidal signal was revealed, with high rates at high
tide and low rates at low tide. Coefficients of variation of
Pz (Table 4) were high at both stations for both sample
dates, illustrating the dynamic behaviour of primary
production within a day. In a higher temporal scale
study (e.g. daily or seasonal variability), estimates of
primary production in a given area should be made at
the same hour of the day (around zenith, at optimal
production) in order to avoid diel variability effects and
overestimation of variations in primary production.
Neale and Richerson (1987) pointed out that studies
suggesting that production was insensitive to mixing had
not considered potential diel stratification or diel
variation of photosynthetic parameters. In fact, lightshade acclimation, involving fluctuations of these
parameters, occur only in stable light conditions (Tillmann et al., 2000), as in June 2003. In a well-mixed
ecosystem, such as the Vire estuary, phytoplankton cells
adapt themselves to a mean light environment (MacIntyre
and Cullen, 1996; Videau et al., 1998). Photoacclimation of
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F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
June 2003
April 2004
PB max
(a)
4
4
3
3
2
2
1
1
0
0
6
αB
(b)
7
8
9
10 11 12 13 14 15 16 17 18 19 20
0.06
0.06
0.05
0.05
0.04
0.04
0.03
0.03
0.02
0.02
0.01
0.01
0
Ek
7
8
9
10 11 12 13 14 15 16 17 18 19 20
300
300
250
250
200
200
150
150
100
100
50
50
6
B
8
9
10 11 12
15 16
17 18
19
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
0
0
(d)
7
0
6
(c)
13 14
20
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
70
70
60
60
50
50
40
40
30
30
20
20
10
10
0
0
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
Bay surface
Bay depth
Estuary surface
Estuary depth
175
(e)
175
150
150
125
Pz
125
100
100
75
75
50
50
25
25
0
0
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
6
7
GMT
8
9
10 11 12 13 14 15
16 17 18 19 20
GMT
Bay
Estuary
Fig. 5. Photosynthetic parameters, chlorophyll a biomass and primary production. (a) PBmax in mg C mg chl a h1; (b) aB in mg C mg
chl a1 h1 (mmol photons m2 s1)1; (c) Ek in mmol photons m2 s1; (d) B in mg m3; (e) Pz in mg C m2 h1; : low tide; : high tide.
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F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
Table 6
Biological and physiological parameters: mean (SE), n Z number of samples, *significant vertical difference, P ! 0.05. n.d. Z no data. Pz in
mg C m2 h1, PB and PBmax in mg C mg chl a1 h1, aB in mg C mg chl a1 h1 (mmol photons m2 s1)1, bB dimensionless, Ek in
mmol photons m2 s1, B in mg chl a m3
June 2003
Pz
PB
PBmax
aB
bB
Ek
B
April 2004
Bay (n Z 6)
Estuary (n Z 6)
Bay (n Z 4)
Estuary (n Z 6)
40.6
1.7*
2.3*
0.037
0.001
63.5
7.4
73.5
0.8
1.8
0.015
0.055
163.7
43.4
26.3
0.5
0.7
0.015
0.0005
58
10.8
12.2
0.14
0.2
0.003
n.d.
107
45.2
(5.4)
(0.2)
(0.2)
(0.001)
(0.0001)
(5.3)
(0.8)
(15.9)
(0.2)
(0.3)
(0.005)
(0.022)
(16)
(3.4)
June 2003
(a)
(2.5)
(0.04)
(0.1)
(0.001)
(21)
(1.9)
April 2004
(c)
2500
2000
2000
1500
1500
E
E
2500
1000
1000
500
500
0
0
D-2
D-1
D
D-2
(d)
1,5
1
0,5
0,5
0
D
0
-0,5
-0,5
-1
-1
-1,5
D-1
1,5
1
log Ek/Ez
(b)
log Ek/Ez
(5.8)
(0.1)
(0.1)
(0.003)
(0.0002)
(12)
(0.9)
-1,5
6
8
10
12
14
16
18
20
6
8
10
GMT
Bay depth
12
14
16
18
20
GMT
Bay surface
Estuary depth
Estuary surface
Fig. 6. Light history, incident light (E in mmol photons m2 s1) on day of sampling and two previous days (data: Météo-France). D Z day of
sampling. Ek/Ez during day of sampling. : low tide; : high tide.
F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
3
2.5
Pz/Em
2
1.5
1
0.5
0
6
8
10
12
14
16
18
20
GMT
Bay June 2003
Bay April 2004
Estuary June 2003
Estuary April 2004
Fig. 7. Ratio Pz/Em for both sample sets and stations.
phytoplankton to a given light intensity can occur at neap
tide, in shallow coastal waters where the physical structure
of waters is homogeneous (Lizon et al., 1995). In the
eastern English Channel, the same authors demonstrated
that when vertical mixing is moderate, light oscillations are
slower than the physiological adaptation time of phytoplankton, highlighting the strong link between photoacclimation and mixing. In the bay, the results showed that
PBmax and aB were not correlated and varied separately
(Fig. 4). In June 2003, PBmax was the parameter driving the
variation of Ek, the light saturation parameter, whereas aB
stayed constant (Fig. 5a, b). Ek is known as a photoacclimation index (Henley, 1993; Behrenfeld et al., 2004),
thus microalgae present in the bay adjusted their PBmax to
photoacclimate whereas their aB stayed relatively constant.
According to Behrenfeld et al. (2004), this process in the
bay belong to a certain category of P vs. E curve variability,
the ‘‘Ek-dependent variability’’, where physiological adjustments in response to changing light are one of the bases of
photosynthesis. In June 2003, the vertical difference of
PBmax or PB (Table 5), the increase of PBmax at zenith (Fig. 5a)
and the high ratio Pz/Em in the early hours of the day (Fig. 7)
are illustrations of the optimization of primary production
according to different light climates. Thus, at the bay, in June
2003, short-term photoacclimation was possible in low
mixing conditions. In April 2004, no significant differences
were found between surface and depth (Table 6), while
photosynthetic parameters (Table 4) and the ratio Pz/Em
(Fig. 7) were variable, indicating poor light harvesting and
optimization. Whatever the light climate during April 2004,
no short-term photoacclimation occurred because of
the unstable conditions (Table 4). In addition, primary
433
production levels were higher at the bay than at the estuary,
highlighting a better light harvesting capacity in the less
variable part of the sampling area (Table 4).
Behrenfeld et al. (2004) proposed a second category
of P vs. E curve variability, the ‘‘Ek-independent
variability’’, where parallel changes in PBmax and aB are
one of the bases of photosynthesis. In this case,
however, no clear physiological explanation is forthcoming. Potential explanations are based on pigment
variability (Behrenfeld et al., 2004), nutrient availability
(Platt and Jassby, 1976) or taxonomy (Platt and Jassby,
1976; Côté and Platt, 1983). The light history of
microalgal cells also influences primary production
and physiological state, especially PBmax (Malone and
Neale, 1981). It is suggested that the high level of
physicochemical and biological variability of the river
Vire was the forcing parameter that made short-term
photoacclimation difficult. ‘‘Ek-independent variability’’,
i.e. variability of primary production without optimized
short-term photoacclimation, might occur in a high
variability ecosystem, like an estuary where light climate
is regularly changed. In the estuary, PBmax and aB
presented a significant positive correlation (Fig. 4). In
June 2003, Ek/Ez was sometimes close to 1 (Fig. 6b)
which illustrates a photoacclimated state of the populations observed at the studied stations. This physiological state may have been influenced by previous
exposure to high light (Fig. 6a). In April 2004, the ratio
Ek/Ez was regularly under 1, except during the slacks
(Fig. 6d). Under more turbulent conditions (Table 2),
microalgae at both stations were not light acclimated.
Pennock and Sharp (1986) showed that in the Delaware
estuary, photoacclimation is slower than the vertical
mixing rate and that it was less influent factor than
expected in the system. As an alternative to photoacclimation, Henley (1993) reported that the diel
changes of PBmax are not necessarily related to chlorophyll a content, photoinhibition or nutrition; rather they
seem to be endogenous and probably free-running.
Shaw and Purdie (2001) highlighted a paradox in the
theory of light-shade acclimation: these authors found
a negative correlation between aB, PBmax and light, which
contradicts the generally accepted theory that
PBmax decreases when phytoplankton are acclimated to
low light. They stressed the role of temperature-dependent enzymatic processes controlling PBmax. Besides,
MacIntyre and Cullen (1996) reported that in the San
Antonio bay, PBmax was inversely correlated with the
mean irradiance in the water column, leading to the
suggestion that a new way of thinking of the dynamics
of photosynthetic parameters is required, without focus
on light as is generally the case. Behrenfeld and
Falkowski (1997) stated that the widespread use of light
as the principal forcing component in primary production models might be re-evaluated in order to
understand causes of variability in the physiological
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F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
Fig. 8. June 2003, PCA. (a) Factor loadings plot, black full arrows are related to active variables and green dotted arrows are related to illustrative
variables (species biomass). Ag, Asterionellopsis glacialis, Cs, Chaetoceros socialis, Pm, Paralia marina, Rs, Rhizosolenia stolterfothii, Sq, Scenedesmus
quadricauda. (b) Sample ordination plot. B: bay, E: estuary, S: surface, D: depth (example: BS8 Z sample from the station bay, at the surface, at
8:00).
F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
435
Fig. 9. April 2004, PCA. (a) Factor loadings plot, black full arrows are related to active variables and green dotted arrows are related to illustrative
variables (species biomass). CP, Cerataulina pelagica, Cs, Chaetoceros socialis, Cy, Cyclotella sp., La, Lauderia annulata, Rd, Rhizosolenia delicatula.
(b) Sample ordination plot. B: bay, E: estuary, S: surface, D: depth (example: BS7 Z sample from the station bay, at the surface, at 7:00).
436
F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
factors which are most influential on primary production dynamics. A study made by MacCaull and Platt
(1977) already established that the in situ PBmax variation
was a compromise between forcing environmental
factors and an inherent rhythmicity in the potential of
the organism.
4.3. Phytoplankton community structure impact
Photosynthesis variations are related to exogenous
and endogenous characteristics, i.e. physical and biological properties. Phytoplankton primary production
in estuaries can reach high levels in comparison to
coastal areas due to high nutrient concentrations, but
this potential production is not always attained because
of turbidity, which defines light availability for primary
production, algal productivity and population growth
(Alpine and Cloern, 1992; Kromkamp and Peene, 1995).
In addition, the timing of sampling and salinity stress
strongly influence phytoplankton primary production
estimates (Goosen et al., 1999). Côté and Platt (1983)
pointed to the importance of the relationship between
changes in community structure and changes in the rate
of production in short-term dynamics. Other studies
have investigated this relationship and emphasized the
role of the nature of the phytoplankton community (e.g.
Falkowski and Owens, 1980; Malone and Neale, 1981;
Pennock and Sharp, 1986; Videau et al., 1998; Shaw and
Purdie, 2001; Behrenfeld et al., 2004). Côté and Platt
(1983) also indicated that physical transients can alter
community structure which includes species composition, cell size and species diversity. It has been shown
that estuaries undergo large natural fluctuations in
abundance of species and are susceptible to invasion by
exotic species (Alpine and Cloern, 1992). In this study,
the estuarine waters were most productive at high
tide when bay species entered at depth, thus changing
the taxonomic composition (Figs. 5a, e, and 3b, d).
Interactions between both ecosystems, bay and estuary,
took place on both sample dates because of tidal mixing.
Variability of taxonomic composition and transport of
organisms were major causes of the dynamic behaviour
of the interface studied here. Large diatoms were
observed in the bay, whereas small species were present
in the estuary (Table 5, Figs. 8a, and 9a) where shortterm photoacclimation seems to have been difficult and
where primary production was low. In the present work
it cannot be confirmed that cell size plays a major role in
the dynamics of primary production, but a hypothesis
can be put forward according to the results of the PCA
(Figs. 8a, 9a). High values of PBmax and aB were
associated with high biovolume. By contrast, Côté and
Platt (1983) found a negative correlation between
PBmax and mean cell volume and they explained this in
terms of cell volume affecting PBmax through the dependence of nutrient uptake rates on surface/volume
ratio of phytoplankton cells. They observed large
variations in average cell volume of phytoplankton
community through the tidal cycle. More recently,
Brunet and Lizon (2003) showed that cell responses to
environmental changes differ between large and small
cells and consequently that opportunistic and/or welladapted phytoplanktonic groups could increase their
production. In the Baie des Veys in this study, species
diversity H# was higher at bay than at estuary. The
results indicate that species diversity is positively
correlated to primary production over a tidal cycle.
Thus, species biovolume and species diversity could be
major factors influencing photosynthesis, but further
studies are required to clearly establish this hypothesis.
5. Conclusions
Species composition, cell size and species diversity
might modify photosynthetic responses in an estuarinebay ecosystem ruled by tidal mixing as shown here in the
eastern English Channel. Phytoplankton community
structure plays a major role through taxonomic
variability in photoacclimation (Forbes et al., 1986 in
Behrenfeld et al., 2004) and a link between ecosystem
variability level, taxonomic composition and the expression of ‘‘Ek-independent variability’’ (Behrenfeld et al.,
2004) could be made. The Baie des Veys is a high
variability interface with daily interactions between bay
and estuarine waters. Primary production dynamics
depend on the capacity of phytoplankton to optimize
their light harvesting, but light-shade acclimation is not
always applicable in situ because of significant shortterm variability, especially in the nature of the phytoplankton community. As primary production has
a significant short-term variability, the timing of the
sampling must be constant to avoid overestimation of
the variations in primary production. As in previous
studies (Côté and Platt, 1983; Macedo et al., 2002), this
work emphasizes the need for greater understanding of
factors governing phytoplankton community structure
in the study of short-term phytoplankton primary
production dynamics, especially in well-mixed ecosystems. A new approach to the study of photoacclimation
strategies should be adopted through integration of
community structure surveys in order to study biological
influences on the variability in P vs. E curves. Long-term
surveys of photosynthetic parameters would be of
particular interest in order to further characterize the
links between primary production and phytoplankton
community structure.
Acknowledgements
This work was supported by the Conseil Régional de
Basse-Normandie, the Agence de l’Eau-Seine-Normandie,
437
F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
the Direction Régionale de l’Environnement and the
Direction Régionale des Affaires Maritimes through an
IFOP grant. The authors wish to thank the following
people for their assistance, J.-P. Lehodey, A. Savinelli,
J.-P. Desmasures, F. Guyot and P. Hérisson (Centre
Régional d’Etudes Côtières, Luc-sur-Mer) for logistical
support during cruises, Dr. I. Probert, Dr. P. Claquin,
Dr J.-C. Marin, B. Le Roy, G. James et T. Lampin for
support and help during cruises and biovolume measurements, O.-P. Duplessix (IFREMER, Port-en-Bessin)
for nutrient measurements, and Dr. J.-C. Brun-Cottan
(Laboratoire de Morphodynamique continentale et
côtière, Université de Caen Basse-Normandie) for the
loan of CTD probe. Finally, the authors would like to
thank Dr. Ian Probert for reviewing the English.
Appendix A. List of phytoplanktonic taxa. (B: observed
in bay, E: observed in estuary, BE: observed in
both ecosystems)
June 2003
Bacillariophyceae
Benthic
Amphora sp.
Craticula cuspidata
Diploneis sp.
Didymosphenia sp.
Entomoneis alata
Ephemera planamembranacea
Fragilaria sp.
Licmophora sp. (epiphytic)
Lyrella sp.
Mastogloia grana
Melosira sp.
Navicula spp.
Nitzschia longissima
Nitzschia sp.
Pinnularia sp.
Plagiotropis lepidoptera
Podosira stelliger
Striatella unipunctata
Synedra sp.
Benthic (tychopelagic)
Actinoptychus senarius
Bacillaria paxillifera
Gyrosigma sp.
Paralia marina
Pleurosigma sp.
Pelagic
Asterionella formosa
Asterionellopsis glacialis
Cerataulina pelagica
Chaetoceros curvisetus
Chaetoceros decipiens
Chaetoceros densus
Chaetoceros diadema
Chaetoceros socialis
Chaetoceros spp.
Chaetoceros tortissimus
B
BE
E
April 2004
BE
B
BE
B
B
BE
B
B
BE
E
BE
B
B
E
E
E
E
B
BE
E
BE
BE
E
BE
B
BE
BE
BE
BE
BE
BE
BE
E
BE
BE
BE
E
BE
BE
BE
BE
BE
E
June 2003
Coscinodiscus sp.
Cyclotella sp.
Cylindrotheca closterium
Ditylum brightwellii
Eucampia sp.
Eucampia zodiacus
Grammatophora serpentina
Guinardia flaccida
Lauderia annulata
Leptocylindricus minimus
Odontella aurita
Odontella regia
Pseudo-nitzschia fraudulenta
Pseudo-nitzschia pungens
Pseudo-nitzschia sp.
Rhizosolenia delicatula
Rhizosolenia fragilissima
Rhizosolenia imbricata
Rhizosolenia setigera
Rhizosolenia stolterfothii
Stephanodiscus sp.
Thalassionema nitzschioı¨des
Thalassiosira anguste-lineata
Thalassiosira levanderi
Thalassiosira nordenskioldii
Thalassiosira rotula
Dinophyceae
Akashiwo sanguinea
Gymnodinium chlorophorum
Gymnodinium spp.
Gyrodinium crassum
Gyrodinium lachryma
Gyrodinium opimum
Gyrodinium spp.
Gyrodinium spirale
Katodinium glaucum
Katodinium rotundatum
Polykrikos schwartzii
Protoperidinium bipes
Protoperidinium brevipes
Protoperidinium conicum
Protoperidinium minutum
Protoperidinium punctulatum
Protoperidinium sp.
Scrippsiella trochoidea
Unidentified armored dinoflagellates
Chlorophyceae
Chlamydomonas sp.
Kirchneriella lunaris
Monoraphidium sp.
Oocystis sp.
Pediastrum sp.
Scenedesmus armatus
Scenedesmus quadricauda
Scenedesmus spp.
Staurastrum sp.
Unidentified Chlorococcales
Cryptophyceae
Chroomonas sp.
Plagioselmis sp.
Rhodomonas sp.
Unidentified species
E
E
April 2004
BE
E
E
E
E
E
BE
BE
BE
BE
BE
BE
BE
B
BE
B
BE
E
BE
E
B
BE
BE
B
B
B
B
BE
B
BE
B
BE
BE
B
E
BE
B
B
B
B
B
B
BE
B
BE
BE
BE
BE
E
BE
BE
BE
E
E
E
E
E
BE
B
B
E
E
BE
BE
BE
BE
E
BE
E
E
(continued on next page)
438
F. Jouenne et al. / Estuarine, Coastal and Shelf Science 65 (2005) 421e439
Appendix A (continued )
June 2003
Chrysophyceae s.l.
Pseudopedinella sp.
Synura sp.
E
Euglenophyceae
Phacus sp.
Unidentified species
E
BE
April 2004
E
Charophyceae
Closterium sp.
E
BE
Prasinophyceae
Pyramimonas sp.
BE
Prymnesiophyceae
Phaeocystis globosa
B
B
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