Journal of Oceanography, Vol. 57, pp. 723 to 734, 2001
The Spring Phytoplankton Bloom in the Coastal
Temperate Ocean: Growth Criteria and Seeding
from Shallow Embayments
DEBBY IANSON 1*, S TEPHEN POND 1 and TIMOTHY P ARSONS2
1
2
Earth and Ocean Sciences Department, University of British Columbia, BC Canada
Institute of Ocean Sciences, Sidney, BC Canada
(Received 19 December 2000; in revised form 12 July 2001; accepted 28 August 2001)
A method based on time-series of conductivity, temperature and depth (CTD) profiles which successfully determines favourable phytoplankton growth conditions for
the spring bloom in nearshore temperate coastal waters was developed. The potential
for shallow embayments to influence phytoplankton species composition in larger
adjacent waters was also investigated. At temperate latitudes, such embayments should
have favourable phytoplankton growth conditions earlier in the spring than open
waters as bathymetry limits vertical mixing and thus increases light availability. The
study area was Nanoose Bay, which is connected to the Strait of Georgia, British
Columbia. Data were collected 2–3 times per week during the winter-spring of 1992
and 1993. A mooring with 5 current meters was placed at the mouth of the bay in
1992. The conservation equation for a scalar was used to estimate the balance between advective transport and biological source and sink terms. Variability in physical conditions and biological response between years was tremendous. Results indicate that seeding from the bay was not possible in 1992 but could have been in 1993.
However, to conclusively determine the importance of Nanoose Bay on the spring
bloom species composition in the Strait of Georgia, more extensive work is required.
Keywords:
⋅ Phytoplankton,
⋅ spring bloom,
⋅ seeding,
⋅ embayments,
⋅ advection,
⋅ flushing,
⋅ diatoms,
⋅ resting spores,
⋅ coastal,
⋅ temperate.
able to phytoplankton. Furthermore, embayments with
limited advective exchange can retain phytoplankton for
time scales longer than their generation time and provide
warmer temperatures for accelerated photosynthesis and
germination (Parsons et al., 1973; Garrison, 1984). Thus,
shallow embayments are likely to form seed populations
or inoccula for surrounding waters. Resuspension of
spores from the sediments can occur when the bay is
mixed to the bottom. In the spring conditions for germination and growth should be favourable earlier than in
adjacent (deeper) waters. Advective flux from the bay
could deliver cells to seed a bloom outside the bay.
Some commonly occurring phytoplankton species are
harmful to penned fish, particularly certain species of
Chaetoceros (Bell et al., 1974; Taylor, 1993). Thus, predicting phytoplankton species composition in coastal areas is important to aquaculture. Monitoring phytoplankton
in an embayment could provide an easy way to forecast
bloom species in surrounding waters.
Coastal spring bloom dynamics were investigated,
focusing on the potential of shallow embayments to influence species composition, for the bloom in the Strait
of Georgia in the vicinity of Nanoose Bay, British Co-
1. Introduction
In temperate oceans a strong spring phytoplankton
bloom occurs when light availability is high enough for
phytoplankton to use abundant nutrients which have been
mixed up during the winter (Sverdrup, 1953). These
blooms are dominated by diatoms, many of which have
the ability to form resting spores (Hargraves and French,
1983; Garrison, 1984). Little is known about mechanisms
for seeding diatom blooms, although in coastal regions
of the temperate ocean, spores are likely to be important
(Garrison, 1984). Gran (1912) provided the original hypothesis for seeding neritic diatom blooms. It involves
the formation and sinking of resting spores when conditions become unfavourable for the diatoms, resuspension,
then germination when conditions are again favourable.
In coastal waters, shallow areas exist where vertical
mixing is limited by bathymetry, making light more avail* Corresponding author. E-mail: [email protected]
* Present address: Department of Oceanography, Texas A&M University, College Station, Texas, U.S.A.
Copyright © The Oceanographic Society of Japan.
723
and factors affecting phytoplankton growth in the study
area before and during the onset of the spring bloom.
Fig. 1. Nanoose Bay and the Strait of Georgia with all sampling locations. Ballenas and Entrance Islands lighthouses
are marked by B and E, respectively, on the inset.
lumbia (Fig. 1). In the Strait, Yin et al. (1997) and St.
John et al. (1993) have shown that the principal influences that trigger the onset of the spring bloom are strong
stratification associated with the spring freshet from the
Fraser River and the absence of local wind-mixing. There
have been no studies of which we are aware that investigate the seeding of the spring bloom in the Strait, although
Haigh and Taylor (1990b) have suggested that sheltered
bays in the northern Strait may be seed beds for cystforming, flagellated phytoplankton that bloom later in the
year. There are many studies on the species that bloom in
the Strait (e.g. Harrison et al., 1983; Haigh and Taylor,
1990a). The spring bloom is dominated by diatoms namely
Thalassiosira spp., Skeletonema costatum followed by
Chaetoceros spp. and many others (Harrison et al., 1983).
Nanoose Bay, located on the eastern side of the central Strait of Georgia, was chosen as a potential seed bed
(Fig. 1). It is quite large, about 5 km2 , and is directly connected to the Strait of Georgia via a narrow (approximately 0.5 km) opening. The bay is shallow enough (about
25 m deep) to be mixed to the bottom during strong wind
conditions typical of winter and early spring. Currents
between the bay and the adjacent Strait appear to be density driven, wind driven and tidal, but are not strong
(Ianson, 1994). Fresh water input to Nanoose Bay is minimal from several small creeks mainly near its mouth (pers.
obs.).
2. Materials and Methods
The sampling program was designed to measure
advective transport, phytoplankton species composition
724
D. Ianson et al.
2.1 Field sampling
In 1992, 3 stations were sampled—inside the bay Nan
10, at the mouth of the bay Nan 20 and outside (but
nearby) the bay Nan 30 (Fig. 1). In 1993, 4 stations were
added (Fig. 1) to increase spatial resolution particularly
at the mouth of the bay so that horizontal gradients could
be estimated. A fifth shallow water station was added to
observe resting spores. Samples were taken 2–3 times per
week. In 1992, sampling began January 27 (Jday 27) and
ended March 21 (Jday 81). The 1993 study began February 4 (Jday 35) and ended April 13 (Jday 103). Longer
sampling was necessary in 1993 as strong southeasterly
winds suppressed a bloom in the Strait. A total of 54 water samples were taken in 1992 and 140 in 1993.
Water samples were drawn using a 3 m integrated
pipe sampler (Sutherland et al., 1992) and 100 ml forced
through a Whatman GF/F filter (nominal pore size, 0.7
µ m) (Parsons et al., 1984). Nutrient analysis (nitrate,
phosphate and, in 1992 only, silicate and ammonium) of
the filtrate was done using a Technicon AutoanalyzerTM.
The methods of Parsons et al. (1984) were used for chlorophyll analysis (on filter). For species composition, a
60 ml glass jar was filled, fixed with Lugol’s iodine solution and analyzed using an inverted microscope (100X
and 400X magnification depending on size of
phytoplankton). Samples were settled for 24 h in 10 or
25 ml settling chambers.
Density profiles were taken using an Inter Ocean S4
current meter as a CTD (Ianson, 1994). All casts were
done to 20 m, which is nearly to the bottom at stations 10
through 15, and then to 40 m in 1993 at station 30 on the
outside to observe the structure in the deeper water of the
adjacent Strait. The S4 was set to sample continuously at
5 s intervals.
To calculate the extinction coefficient, k, Secchi disc
depth was measured at each station. Integrated (24 h)
values of solar radiation were measured using a
pyranometer placed on a piling in Nanoose Bay.
2.1.1 Mooring data
On January 27, 1992 a mooring was placed near the
mouth of Nanoose Bay at station Nan 20 (Fig. 1) to measure the advective exchange in and out of the bay. The
location of the mooring was chosen to be just outside of
the bay to avoid possible difficulties with boat traffic
entering the bay, especially log booms during storms. Inter Ocean S4 current meters were placed at 2, 4, 7, 12 and
20 m below the surface. It was expected that most variation in the currents would appear near the top of the water column as was found in Knight Inlet (Baker and Pond,
1995). The S4s were set to record conductivity, temperature and a 1 min vector averaged velocity every 10 min
24
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
sigma-t
22
23
1993 CTD
•
•
•
•
•
•
21
•
•
•
1992 mooring
1992 CTD
20
•
60
80
100
-10
-5
FI (km/day)
sigma-t
21.5
0
22.5
40
7m
40
60
80
-15
20.5
sigma-t mooring
flushing index
100
Julian day
Fig. 2. 1992 and 1993 density time series at 7 m to indicate intervals during which the current directions were into the bay. 1992
CTD data are shown with the processed mooring density time series and also the flushing index (FI) at that depth. Negative
flushing indices represent times when currents were into the bay.
(Ianson, 1994). Wind data were taken at 10 min intervals
by an Aanderra system (anemometer, compass and thermometer) mounted 4 m above the sea surface on the
Geodyne buoy of the mooring.
2.2 Analysis and calculations
2.2.1 Mooring data processing
Salinity and σt were calculated using the practical
salinity scale and the international equation of state (Pond
and Pickard, 1983). Velocity data were rotated to correct
for the magnetic declination (22 degrees at Nanoose Bay).
Possible spikes were removed and averaged (Ianson,
1994) to give hourly values. Harmonic analysis was done
to calculate the amplitudes of tidal frequencies (Ianson,
1994). The diurnal and semi-diurnal tidal contributions
to the current and density records were then subtracted
yielding residual time series. To remove any high frequency energy still present in the records a moving 25 h
average was used.
2.2.2 Wind
Anemometer wind direction was calculated from the
mooring compass and the anemometer wind vane. These
data were averaged yielding hourly values (Ianson, 1994).
Unfortunately the anemometer failed to record data
for the first 40 d that it was deployed, which happened to
be the portion of the record with stronger winds. For a
complete wind record, lighthouse data from Environment
Canada were obtained from both Ballenas and Entrance
Islands, on either side of Nanoose Bay (Fig. 1). All of the
wind records were filtered. A 25 h running average was
used for the hourly winds and a 24 h running average for
the 3 hourly lighthouse data.
Lagged cross-correlations were done between the
anemometer data and each of Ballenas and Entrance Islands wind records for both u and v components (Ianson,
1994). In the u direction (in and out of the bay) the wind
correlation was the highest (r2 = 0.74) for the Ballenas
Island data. Therefore the Ballenas data were used for
both the 1992 and 1993 seasons.
2.2.3 Estimating currents in 1993
We wanted a proxy for currents in 1993 when we
did not have a mooring deployed. We tried to find a correlation matrix between Ballenas wind data and residual
currents. Straight correlations were very poor at all time
lags (r2 < 0.3). We expected the direction of the wind at
Ballenas not to be the same as the direction of the current
that it produced at the mooring site mainly because of
bathymetry. In the field for example, a wind blowing to
the northwest in the Strait was directed by topography to
blow forcibly westward into the bay. The data were rotated to find their principal axes (Ianson, 1994). Winds
had a strong principal axis in the northwest/southeast direction as expected. Currents however were nearly isotropic above 20 m. To be thorough, currents were rotated
over 100 steps and correlated to the principal axis of the
Ballenas Island wind. All correlations were poor with
Temperate Coastal Spring Phytoplankton Bloom
725
r2 < 0.4 for current directions in and out of the bay and
current lagging wind. No extrapolation of 1993 currents
from wind data was possible. Local wind was not the only
important forcing in the residual circulation.
We looked at the density time series at Nan 20 to see
the influence of horizontal density gradients on the residual currents. At all depths above 12 m during periods
of sustained inflow to the bay there was a large density
decrease (Ianson, 1994). Positive changes in surface density occurred during periods where there was surface outflow or little or no exchange. Such changes could represent mixing events as well as outflow. The 7 m record
(Fig. 2) was chosen to infer current direction at inside
stations as it had a strong signal and less high frequency
noise than the 2 and 4 m data. Thus large negative changes
in σt7 indicated times when surface currents were into
the bay. Positive changes in σt7 put no restriction on current direction. In 1993, σt7 was measured by CTD casts
and the frequency of casts was twice as high as in 1992
(Fig. 2).
For the outside stations wind data were used to infer
current direction in 1993. The correlation between the
principal component of the Ballenas wind and current in
1992 was higher in the v current direction (0.5 at 2 and 4
m) at Nan 20 and may be higher further outside of the
bay. The correlation is not strong, however, it was used
only to indicate direction.
2.2.4 Flushing index for Nanoose Bay
A running integral of the current data (∫0 tu(t)dt units
of distance) shows that transport in one direction was often maintained over a time period long enough for several or more km to pass consecutively (Ianson, 1994).
Scaling the length of the bay by a width factor
(W bayW mouth–1) to account for stronger flow through the
narrows, a distance of 5 km was determined to be reasonable for one complete flushing. Using this distance as a
limit, an index was determined. First u(t) was integrated
with respect to time. The integral started at t1 and continued adding u(t)dt until 5 km (a complete flushing of that
layer) was reached or just exceeded at t 2. This integral
(value 5 km or greater) was then divided by the time interval that it was calculated over as follows.
Flushing index =
1
t2 − t1
∫t u(t )dt.
t2
1
(1)
-5
0
5
2m
40
60
80
100
80
100
80
100
60
80
100
60
80
100
0
4m
0
(km/day)
-5
-10
12 m
0
40
20 m
-10
(km/day)
40
0
5 -15
7m
5
(km/day)
Flushing Index
-10
(km/day)
5
(km/day)
10
It was calculated as a function of t 1. Once the sum of
u(t)dt added to 5 km the integral was set back to zero and
restarted from t1 + dt. Therefore for each time in the record
there is a corresponding index associated with the beginning of that time interval. The index is negative or positive for advection in or out of the bay respectively.
40
Julian day
Fig. 3. A phytoplankton flushing index, 1/(t2–t1){ ∫ u(t )dt }, as a function of t1 for five depths. The negative values are into the
t2
t1
bay and positive values are out of the bay.
726
D. Ianson et al.
Figure 3 shows the flushing index (units km·d–1) as
a function of time for each depth. If the bay is flushed in
a time scale faster than the generation time of
phytoplankton, an increase in primary productivity will
not occur in the bay. Considering the doubling time of
phytoplankton to be around 2 d (Parsons et al., 1973), a
flushing index with the magnitude of 2.5 km·d–1 provides
a ceiling for phytoplankton growth. A flushing index
larger than that corresponds to a complete exchange in a
short time interval and an unfavourable period for
phytoplankton growth.
2.2.5 Vertical mixing
First mixed layer depths were calculated using the
approach of Freeland and Farmer (1980). The density
structure was approximated by a two layer system which
has the same potential energy and first mode internal wave
speed as the actual structure; σt at 2 m was used for the
density of the upper layer. Both up and down casts were
used and the results of each were averaged. Occasionally
the upper layer density had to be changed to that of a
shallower depth.
Density gradients still existed within the region that
was assumed to be well mixed so a gradient Richardson
number (Pond and Pickard, 1983) was used to estimate
the velocity shear necessary for turbulent mixing to occur within that region. The calculated velocity shear was
compared to instantaneous measured velocity shears at
(a)
Nan 20 (Ianson, 1994) to determine whether
phytoplankton were being mixed over the region.
2.2.6 Critical depth
Critical depths were calculated at two day intervals
(the time scale of phytoplankton growth) combining
Secchi disc depths (Ds) and radiation measurements using the equations and constants of Parsons et al. (1973).
A cubic spline was used to determine Secchi disc depths
at two day intervals and a running two day average was
used for solar radiation (Ianson, 1994). Values for reflectance of PAR at 50° N were from Campbell and Aarup
(1989). The extinction coefficient was increased by a factor of 2 to make it correspond to PAR rather than blue
light (λ = 450 nm) as measured by D s. The compensation
light intensity used was the upper limit, 29 µmol·m–2·s –1,
of its range (Parsons et al., 1973). The calculated critical
depths were thus a minimum and were used for qualitative comparison of relative light availability only.
2.2.7 Phytoplankton growth criteria
Based on low phytoplankton abundances after
advective and grazing effects were removed (see below,
Eq. (4)), a shallower mixed layer depth compared to the
critical depth did not provide favourable phytoplankton
growth conditions (i.e. phytoplankton growth rate, µ >
0.5 d–1) in our study area. (Note that we are concerned
principally with diatoms as they are the dominant group
of phytoplankton during the spring bloom (Harrison et
(b)
0
0
NAN 10
NAN 10
5
5
Depth (m)
Depth (m)
NAN 10
10
15
NAN 10
10
15
Feb 18, 1992
Feb 25, 1992
Feb 25, 1993
March 1, 1993
20
Feb 4, 1992
Feb 11, 1992
20
19
20
21
sigma-t
22
22.6
22.8
23.0
sigma-t
23.2
12
14
16
18
sigma-t
Feb 22, 1993
Feb 25, 1993
20
22
22.4
22.6
22.8
23.0
23.2
sigma-t
Fig. 4. Density structure time series: for two time intervals during which phytoplankton growth conditions were (a) favourable
( µ > 0.5) in 1992 between Jdays 49 (Feb. 18) and 56 (Feb. 25) and in 1993 between Jdays 56 (Feb. 25) and 60 (Mar. 1) and
(b) unfavourable ( µ < 0.2–0.5) in 1992 between Jdays 35 (Feb. 4) and 42 (Feb. 11) and in 1993 between Jdays 53 (Feb. 22) and
56 (Feb. 25) (Table 1).
Temperate Coastal Spring Phytoplankton Bloom
727
al., 1983).) Thus an alternate set of criteria were developed from the change in density profiles with time.
A limit of the change in the mean density gradient
over the entire profile with respect to time was set.
∆  ∆σ t 
≥ 0.
∆t  ∆z 
(2a )
As z is depth positive downward, the more stratified the
water column becomes the more positive ∆/∆t(∆σt/∆z) is.
A non-negative value of ∆/∆t(∆σt/∆z) was therefore considered a necessary stability criterion for non-mixing conditions. Secondly the change in σt at 20 m (the lower limit
of most casts) with respect to time was used to indicate
whether or not the same water mass was present.
∆
(σ t 20 ) < 0.05.
∆t
(2b)
A large change in σt20 would indicate new water and thus
unfavourable growth conditions (µ < 0.02–0.5 d –1). The
upper limit was set at 0.05 kg·m –3·d –1 using the 1992 profiles at Nan 20 so that a direct comparison with the mooring was possible (Ianson, 1994). These two criteria form
a minimum requirement for favourable phytoplankton
growth conditions in our study area. Typical examples of
favourable and unfavourable growth periods are shown
in Fig. 4. For each condition (favourable and unfavourable) a well-stratified and a well-mixed example are given.
2.3 Calculation of advective transport
To determine whether or not a bloom is seeded other
than in situ, the general conservation equation for the rate
of change of a scalar in a fluid was used.
∂C
= −∇ ⋅ uC + κ∇ 2 C + Σ(Sources + Sinks).
∂t
(3)
C is a scalar quantity of interest, u is the vector current
velocity and κ is the diffusivity. This equation describes
changes in C at a fixed location. It states that the change
in C with time is due to the net amount of C that is
advected, or is diffused, to or from that location and the
sum of any sources and sinks present. The sources and
sinks come from biological influences and are discussed
below.
Advection usually dominates turbulent (and molecular) diffusion in coastal situations (Hansen and Rattray,
1966), with the exception of areas where strong tidal currents and thus intense mixing exist. Tidal currents at
Nanoose Bay are not strong (i.e. around 2 cm·s–1). It is
therefore assumed that turbulent diffusion is negligible
728
D. Ianson et al.
compared to advection. Vertical gradients were not sampled and since velocity in the vertical is much less than
velocity in the horizontal these terms were neglected.
Equation (3) was evaluated by considering one dimension only, with derivatives calculated as averages over
a single time interval.
dC
dC
= −u
+ C(t )( µ − z − b − s)
dt
dx
( 4)
where µ is the phytoplankton growth rate, z and b are
grazing by zooplankton and oysters respectively and s is
phytoplankton mortality. Terms in Eq. (4) were evaluated
as follows.
C − Ci1
 ∂C 
  = i2
 ∂x  i
t2 − t1
(5a )
1  Ci1 − C(i −1)1 + Ci 2 − C(i −1)2
 ∂C 
  = 
 ∂x  i 4 
x i − x i −1
+
Ci (t ) =
Ci 2 + Ci1
.
2
C(i +1)1 − Ci1 + C(i +1)2 − Ci 2 

x i +1 − x i

( 5b )
(5c)
The indices i and j denote location and time respectively. For locations, i was considered increasing in the
negative x-direction. Derivatives were calculated centred
on one time interval so j was 1 or 2, the beginning and
end of that interval respectively. At end stations, such as
Nan 10, the spatial gradient at the boundary was assumed
to be zero. Nan 25 was used as an end point for calculations involving both inside and outside stations (Fig. 1).
For inside stations (Nan 10–20) the x-direction was eastwest (positive moving out of the bay). For the outside
stations (Nan 25–30), the x-direction was essentially
northwest-southeast, increasing in the northwest direction.
To put more restrictions on the equations the sum of
rates ( µ – b – z – s) was the same for each inside station
and also for each outside station over a given time interval. The rates depend mainly on phytoplankton growth
conditions. Velocities u were also required to be of the
same order and direction at adjacent stations and equal
within the narrows (Nan 12, 15, 20).
A range for the sum ( µ – b – z – s) was chosen using
reasonable estimates for each rate. Afterwards, the corresponding range of velocities required to satisfy Eq. (4)
was calculated and compared either with current data or
tering rates which are of the same order of magnitude
ibid. The result was a range in b of 0.2–0.5 d –1 within
Nanoose Bay. The rate requires that the oysters are being
continually supplied with new water, and thus fresh
phytoplankton. Given the density profiles in 1993 and the
current data in 1992, this assumption seems reasonable.
Where phytoplankton growth conditions were poor,
a maximum decay rate due to sinking or cell death (s)
was set at 0.1 d–1 (Ianson, 1994). When growth conditions were favourable this rate was assumed negligible
when compared with µ in the calculation.
3. Results and Discussion
1000
3.1 1992
The circulation in the bay was dominated by the
Fraser River during the study period in 1992. The surface water of the Strait of Georgia was fresher than in the
bay causing surface inflow to the bay and deep outflow,
thus the bay behaved as a negative estuary. Current data
show that at 4, 7 and 12 m the net flow was inwards,
while at 2 and 20 m currents fluctuated resulting in a net
flow near zero (Ianson, 1994). We assume that the outflow necessary to ensure mass continuity occurred below
-1000
0
Ballenas Island Wind
Nitrate
(uM)
50 0 5 10
20
SE (cm/s) NW
the proxies discussed above. Equation (4) was used in
this manner to test the seeding hypothesis over each time
interval in the data.
2.3.1 Choice of biological rates
If phytoplankton growth conditions were favourable,
µ was 0.5–1.5 d–1 based on water temperature. If conditions were unfavourable, µ was <0.2 d –1 (Harrison and
Platt, 1986).
The upper limit for z was chosen using a maximum
concentration of copepods of 2 L–1 of the dominant
copepod Neocalanus plumchrus during the spring in the
Strait of Georgia (Parsons et al., 1969) and a maximum
filtering rate for each animal of 200 ml·d–1 (Parsons et
al., 1973). Considering the time for 2 copepods to filter
1/e L, z was 1 d –1. At low phytoplankton concentrations
zooplankton do not graze (Parsons and LeBrasseur, 1970).
Thus the range for z was 0–1 d –1.
The oyster concentration was observed to be 30 m –2
on the shoreline and in the shallows of the bay. Using
this concentration for all depths in the bay yields an upper limit of 83 million oysters. Their filtering rates were
taken to be the same as that of mussels in 8.5°C water at
Friday Harbor (from Conover, 1978). Oysters and mussels are classified in the same habitat group and have fil-
NAN 10
NAN 30
30
•
•
Skeletonema
•
•
•
•
•• ••
••
• •
•
•
•
•
••
••
••
••
•
••
••
••
0
-10 -5
(km/day)
Critical depth
NAN 10
NAN 30
5 0
(cells/ml)
100 200 300 0 10
(m)
NAN 10
NAN 30
2m
4m
40
Flushing Index
50
60
70
80
Julian day
Fig. 5. 1992 time series of phytoplankton concentration (Skeletonema) and factors influencing phytoplankton growth for stations
Nan 10 (inside the bay) and Nan 30 (outside the bay). The critical depth and nitrate concentration are shown for both stations
along with the flushing index (defined in Methods) and the principal component of the Ballenas Island wind (positive is
towards NW). The dashed line at 25 m on the critical depth panel is the maximum depth of the bay. Note that S. costatum
concentrations at Nan 30 rise to 3900 ml –1 (outside the range shown on the plot) on Jday 80.
Temperate Coastal Spring Phytoplankton Bloom
729
20 m. Currents at Nan 20 were not correlated with wind
but were related to changes in density such that decreases
in density occurred during periods of sustained inflow.
Phytoplankton concentrations were very low at all
stations (chla < 0.5 µg·L–1) until day 69 when the spring
bloom began and chla rose to 10–15 µ g·L–1 at all stations. Figure 5 shows a time series of phytoplankton concentration at Nan 10 and Nan 30 with other measurements
which may influence phytoplankton growth. Concentrations of Skeletonema costatum are shown as it was the
dominant phytoplankter during 1992 and it was representative of diatom genera (Ianson, 1994). Species composition was similar at all stations. This time series begins just before phytoplankton concentrations increased
and is truncated just after the apparent onset of the spring
bloom. Note that at Nan 30 the concentrations of S.
costatum after day 80 rise to 3900 ml –1, well outside the
range shown on panel 4 of Fig. 5.
Light was not limiting at any time or location according to estimated critical depths (D c), which were
roughly the same for all stations (Fig. 5, panel 3). D c did
not begin to drop until approximately one week after the
bloom began when high concentrations of phytoplankton
began to limit light penetration which invalidates the Dc
model. During the entire period the density structure at
all locations was well stratified. Calculated mixed depths
were less than 12 m everywhere. Often there was strong
stratification at the surface as in the first example of Fig.
4, thus the velocity shear over this depth, which would
be necessary for turbulent mixing was large, indicating
very limited vertical mixing of phytoplankton. Profiles
at a given location did change with time suggesting
advection as measured by the current meters and often
flushing of the bay occurred more rapidly than
phytoplankton could grow (Fig. 3).
During 1992 Nanoose Bay did not provide the seed
stock for the spring phytoplankton bloom in the Strait of
Georgia. Phytoplankton growth conditions were not favourable inside the bay before they were in the Strait with
the exception of one time interval. During this interval,
day 49 through 55, the phytoplankton concentration increased inside the bay as the flushing index (Fig. 3) was
low enough and the phytoplankton growth criteria (Table
1) were met. This increase was the only appreciable one
before a strong bloom in the Strait occurred. The current
data showed that during this time there was a weak inflow, with the exception of a one day interval around day
48 at 2 m (at 4 m there was always net inflow). This event
was terminated by a negative flushing index indicating
that net transport was into the bay at the surface. It is
likely that phytoplankton were grazed by oysters and
flushed out of the bay at depth. Moreover all stations had
similar species composition at all times and the dominant plankton in the Strait of Georgia bloom was present
there in small concentrations from the beginning of the
study.
Table 1. Phytoplankton growth parameters determined from CTD profiles for Nan 10. For favourable growth conditions it is
suggested that over the interval ∆t, both ∆/∆t(∆σ t/∆z) must be positive and |∆/∆t( σt20)| < 0.05. Favourable parameters are
listed in bold. Parameters can be compared with time intervals in composite Figs. 5 and 6.
730
D. Ianson et al.
The large increase in phytoplankton concentration
at Nan 30 began on day 65 and was much stronger than
in Nanoose Bay. In the bay concentrations did not begin
to rise until after day 65; an increase was found on day
69 (the next sampling date). Up to day 67 the flow at 2
and 4 m was into the bay. At this time the circulation coupled with the high oyster population in Nanoose Bay suggest that the bay acted as a phytoplantkon sink (rather
than a source) with respect to the Strait.
-500
500
Ballenas Island Wind
20
Nitrate
10
(uM)
30
SE (cm/s) NW
3.2 1993
In 1993 density profiles were well mixed and surface waters denser (more saline) than in 1992 (Fig. 4).
The bay did not appear to behave as a negative estuary.
Waters were much more homogeneous in time and based
on the phytoplankton growth parameters (see Methods)
there was little advection. The residual circulation was
expected to reflect winds more strongly.
Inside the bay phytoplankton concentrations were
higher throughout the experiment than in 1992, by at least
an order of magnitude. In the Strait no large increase in
phytoplankton occurred as it did in 1992. Concentrations
were generally steady in time and moderately large compared to the early part of the 1992 record. It was found
that samples at Nan 10, 12, 15 and 20 were all similar
and representative of inside stations (Ianson, 1994). Samples from Nan 25, 27 and 30 were representative of outside stations. Figure 6 shows the principal component of
the Ballenas Island wind, nitrate concentrations, critical
depths, Chaetoceros debilis concentrations (all at Nan 10
and 30), and σt7 at Nan 20 in place of the 1992 flushing
indices. During the 1993 season C. debilis dominated the
phytoplankton community; however, species composition
was not similar between inside and outside stations. The
proportion of S. costatum and Thalassiosira spp. to
Chaetoceros spp. was higher in the outside stations
(Ianson, 1994).
In Nanoose Bay density profiles were always mixed
to the bottom (20 m) with the exception of the last sampling date (day 96) (Ianson, 1994). In the Strait the extent of vertical mixing was deeper than 40 m (the depth
of the CTD cast) until the last sampling date when the
calculated mixed depth was 20 m. Although calculated
critical depths (Fig. 6) were generally large, light was limiting outside the bay due to the extent of vertical mixing.
Inside the bay Dc was usually greater than the depth of
the bay. Phytoplankton shading caused Dc to decrease at
times and may have caused decreases in C. debilis concentration. Nitrate fluctuated with phytoplankton concentration but only became limiting at inside stations at the
Critical depth
40
NAN 10
NAN 30
5000 0
NAN 10
NAN 30
2000
C. debilis
23.0
7 m sigma-t at NAN 20
22.6
sigma-t
0
(cells/ml)
20
(m)
60
0
NAN 10
NAN 30
40
50
60
70
80
90
100
Julian day
Fig. 6. 1993 time series of phytoplankton concentration (Chaetoceros debilis) and factors influencing phytoplankton growth for
stations Nan 10 (inside the bay) and Nan 30 (outside the bay). The critical depth and nitrate concentration are shown for both
stations along with σ t at 7 m (an index of current direction into the bay) and the principal component of the Ballenas Island
wind (positive is toward NW). The dashed line at 25 m on the critical depth plot is the maximum depth of the bay.
Temperate Coastal Spring Phytoplankton Bloom
731
end of the study.
In 1993 phytoplankton seeding of the Strait by
Nanoose Bay was possible. C. debilis was not present in
samples at outer stations when the study began. Using
Eq. (4) with Cij representing the concentration of C.
debilis, the first appearance (on day 42) of C. debilis at
Nan 30 requires an advective transport of 1 km·d –1 in a
northwesterly direction over the two previous days. During the interval day 56–57 advective transport of C. debilis
from the bay to the outer stations of 3 km·d –1 is predicted
by Eq. (4). These currents are reasonable compared with
the 1992 data and during both intervals the wind was
blowing to the northwest (Fig. 6).
3.3 Phytoplankton growth criteria
Predicting favourable phytoplankton growth conditions (i.e. µ > 0.5 d–1) in the spring by requiring that vertical mixing be less than the critical depth (Sverdrup,
1953) was not successful in our study. This approach does
not appear to be useful in a nearshore coastal setting.
Mixed layer depths were difficult to estimate because
profiles lacked stable deep structure and surface structure was often complicated with steep gradients due to
fresh water input. Richardson number considerations
showed that vertical mixing was often limited. Critical
depths indicated that light was almost never limiting even
for phytoplankton populations whose use of light is inefficient. Diatoms (the dominant phytoplankter in our study)
are by far the most efficient user of light (Falkowski and
Owens, 1978). However, critical depths provide only an
instantaneous measure of light availability. We found that
advection was important and thus it was necessary to consider temporal variation to determine favourable growth
conditions for phytoplankton. Two parameters were developed based on the change in density profiles with time
(Table 1) and together successfully predicted increases
in phytoplankton concentration both inside and outside
of the bay (see Figs. 5 and 6, panel 4). They also agree
with the flushing index that was determined from current
data (Fig. 3). The flushing index is a desirable means to
predict favourable phytoplankton growth conditions as it
is based on a direct measure of advection. However, this
index requires a mooring and current meters, a considerable undertaking and expense. Use of the growth parameters (Eq. (2); Table 1) requires only CTD casts (roughly
weekly), thus provides a practical method.
In 1992 there was high stratification associated with
the spring freshet from the Fraser River, little wind and
abundant sunshine. The parameters showed that, despite
this apparent ideal environment, phytoplankton growth
conditions were not favourable at any sampling station
until the end of the study. Whereas in 1993, when wind
and cloud cover were strong, phytoplankton growth conditions were favourable inside the bay at all times. Fur-
732
D. Ianson et al.
thermore, although the timing of the spring freshet and
wind mixing do influence the onset of the spring bloom
in the Strait of Georgia (St. John et al., 1993; Yin et al.,
1997) more detailed observations are necessary to determine the timing of the onset.
3.4 Phytoplankton seeding by Nanoose Bay
For shallow embayments to influence spring bloom
species composition in surrounding waters, three conditions must be met. Growth conditions for vegetative cells
and, more importantly, conditions for excystment of resting spores (assuming that they are present) must be favourable inside the bay earlier than outside. There must
be advective flux from the bay, though the number of cells
advected does not need to be large. Lastly, conditions in
the receiving waters must be favourable enough for the
cells to survive until they can reproduce.
It is clear from this study that there is no single
mechanism for seeding the spring bloom in the Strait of
Georgia. Phytoplankton growth conditions are not always
favourable first in shallow embayments as shown by the
1992 data. Also during this year there was little outward
advective flux in the surface from the bay. The bay acted
as a negative estuary due to external fresh water input
from the Fraser River. During the early part of the 1992
study the Fraser outflow was a little stronger than the
average, but more importantly wind conditions were
weak. In situ vegetative cells of Skeletonema costatum
seeded the bloom both inside and outside of the bay (according to Eq. (4)). (Given the negative estuarine circulation in 1992 it is possible that the original seed population of S. costatum in the bay came from the Strait.) S.
costatum is a common spring bloom species in the Strait
(Harrison et al., 1983) and has not been observed to form
resting spores (Garrison, 1984).
In 1993, growth conditions were favourable inside
the bay from the beginning of the study (Feb. 4) onward.
In addition, wind-mixing was strong and was able to
resuspend resting spores within the bay (spores were observed in phytoplankton samples (Ianson, 1994) and density profiles were mixed to the bottom (e.g. Figs. 4(a)
and (b), panel 2) (ibid.)). Large concentrations of
Chaetoceros debilis, which often form resting spores
(Hollibaugh et al., 1981) and is a common spring bloom
species in the Strait (though not usually first in succession) (Harrison et al., 1983) were found in the bay
throughout the study. It is likely that wind-driven
advective flux produced the observed increases in C.
debilis concentration outside the bay, given the strong
concentration gradient at the mouth of the bay and the
wind direction (Eq. (4)). Whether C. debilis was important in the spring bloom in the Strait in 1993 is unknown.
However, the pre-bloom species composition in the Strait
(mainly S. costatum, Thalasiosirra spp. and C. debilis)
was almost certainly influenced by Nanoose Bay.
It is unlikely that C. debilis found in the Strait came
from other sources such as the borders of the Strait or
shallows around islands due to strong and consistent wind
mixing (Fig. 6, panel 1). Excystment requires the same
conditions that vegetative cells need for growth, i.e. nutrients and light (Durbin, 1978; Davis et al., 1980) and
clearly growth conditions were not favourable for vegetative cells in the Strait (note that concentrations of C.
debilis do not show large increases at any time at Nan 30
despite abundant nutrients (nitrate), Fig. 6 panels 2 and
4). Any resuspended spores from shallows would have
been vigorously mixed out of areas with high enough light
availability.
There is a strong potential for Nanoose Bay to influence species composition in the Strait at times of year
other than the spring. Periodic mixing events could
resuspend resting spores and cysts within the bay which
could then be advected out into the Strait where presumably nutrients would be available from the same mixing
event. In 1993 we also noticed small concentrations of
Heterosigma carterae, a small flagellate known to form
cysts and potentially very toxic to penned fish (Yang and
Albright, 1994). H. carterae blooms occur in the Strait
during the summer and have been known to cause fish
kills there (Taylor and Haigh, 1993). (Note that Taylor
and Haigh (1993) suggest that Vancouver harbour was
the seed bed for the bloom in their study.)
Furthermore characterizing advection is difficult as
coastal circulation is a combination of density driven,
wind driven and tidal influences. It was hoped that in
Nanoose Bay, where tidal currents are weak and there is
little local fresh water input, that the low frequency circulation which dominated the exchange of water could
be correlated to local winds, but the correlation was poor.
Even without the clear strong influence of a large nonlocal fresh water source (the Fraser River in 1992)
Holloway (1996) was unable to correlate winds to currents in Jervis Bay, Australia, a similar physical location.
In short, predicting exchange reliably is not possible without current meters.
Determining the influence of shallow embayments
on phytoplankton species composition in surrounding
waters requires intensive study. The main difficulty is in
characterizing advection. Also phytoplankton sampling
at high temporal resolution is necessary. We suggest that
for future research, drogues (with special care taken with
respect to the depths that the drogues are tracing) be used
to track potential seed populations which are observed in
the embayment.
Acknowledgements
We gratefully acknowledge the personnel at C.F.B.
Nanoose Bay for taking extra samples for us, especially
in 1992 and welcoming us at their base. Thanks to the
officers and crew of the C.S.S. Vector for their assistance
with the mooring work. We thank Rick Thomson and the
Institute of Ocean Sciences for providing us with a boat
for the 1993 season. We also thank Paul Harrison and two
anonymous reviewers for helpful comments concerning
the manuscript. This work was financially supported by
NSERC.
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