Salinity, light, and chlorophyll-a in the Hunter River
Estuary
Brian G. Sanderson and Anna M. Redden
January 14, 2006
Contents
1 Introduction
2
2 Field Excursions
3
3 Results
4
3.1
24/7/05 Fluorescence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4
3.2
9/8/05 Fluorescence, phytoplankton counts, nutrients, chlorophyll-a . . . . . . . .
10
3.3
12/8/05 Dilution experiment: grazing and phytoplankton growth . . . . . . . . . .
22
3.4
16/8/05 Zooplankton trawls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
24
4 Discussion
28
1
Light and chlorophyll-a, Sanderson
1
2
Introduction
The NSW Integrated Monitoring of Environmental Flows program requires information about
planktonic processes in the Hunter River Estuary. Specific planktonic processes that have been
measured and reported here include:
• Results from dilution experiments that determine potential phytoplankton growth rates and
zooplankton grazing rates.
• Dilution experiments were also used to determine the extent that nutrients limit phytoplankton growth.
The present work also reports additional measurements from 4 field trips into the Hunter River
Estuary that supported the above experimental measures of planktonic processes. In particular,
the present work will document:
• Salinity, temperature, and turbidity observations made along the length of the Hunter River
Estuary on each of the 4 sampling days.
• Estimates for chlorophyll-a were obtained from fluorescence measurements made along the
length of the estuary.
• Phytoplankton counts and zooplankton counts are reported at locations along the length of
the estuary.
• Light profiles were measured at locations along the length of the estuary.
• Nutrient concentrations were measured along the length of the estuary.
Relationships between salinity and chlorophyll-a will be examined. Light measurements are
used to determine the light attenuation coefficient κ which is important for understanding light
limitation of primary production in the estuary. Relationships between turbidity and κ is established. This may be useful for future work since turbidity measurements are commonly available.
Light and chlorophyll-a, Sanderson
2
3
Field Excursions
Four field excursions were undertaken:
• On 24/7/05 near-surface in-situ fluorescence (from which chlorophyll-a is estimated) was
measured along the length of the estuary along with profiles of salinity, temperature, turbidity, and dissolved oxygen. The dissolved oxygen sensor was probably reading low, but
spatial structure in the measurements is still represented well. The primary purpose of these
measurements was to provide background information for designing the following program
of biological sampling and experiments.
• More extensive sampling was undertaken on 9/8/05. Near-surface in-situ fluorescence measurements were made in conjunction with salinity, temperature, turbidity, and dissolvedoxygen profiling. Light intensity was measured as a function of depth at 9 stations scattered
along the length of the estuary. Samples were taken for nutrient analysis, chlorophyll extractions, and for obtaining phytoplankton counts.
• On 12/8/05 water samples were obtained from 3 locations in order to undertake dilution
experiments to measure: grazing by zooplankton, whether or not nitrogen was limiting,
and potential phytoplankton growth rates when light is not limiting. Here we also report
the salinity, temperature, and turbidity observations made concurrent with the collection of
water samples for the dilution experiment.
• On 16/8/05 zooplankton tows were made at 4 stations scattered along the length of the
estuary. These measurements were taken after dark. Here we also report concurrent measurements of temperature, salinity and turbidity in order to provide contextual information.
Light and chlorophyll-a, Sanderson
3
4
Results
3.1
24/7/05 Fluorescence
Salinity, temperature, dissolved oxygen, and turbidity profiles were measured along the length of
the Hunter River Estuary (Figure 1). Temperature was about 16 o C near the mouth of the estuary
and fell to 12 o C 40 km upstream at the limit of salt intrusion. The seasonal cycle of heating and
cooling results in cooler conditions inland during the winter. The along-channel temperature
gradient is reversed in summer. Baroclinic circulation (leading to vertical gradients) is driven
mostly by the horizontal density gradient associated with salinity. In winter the temperature
gradient partially reduces the density gradient due to salinity. In summer temperature effects
whereas is reinforces the density gradient due to salinity.
Given the surface-layer of the ocean is usually well-mixed to depths associated with the estuary,
it follows that vertical gradients of salinity are small in the lower estuary. Similarly, there is no
salt in the upper estuary so vertical salinity gradients must also be small there. In between,
baroclinicity associated with the horizontal density gradient causes more dense (saline) water to
slump beneath less dense water. This mechanism constantly generates vertical salinity gradients
which are, in turn, eroded by vertical mixing associated with wind and tide. Salinity typically
varies by about 3 ppt through the water column.
In the upper estuary, there is clear vertical stratification of temperature — although this is
typically ∼0.25 o C from top to bottom.
Figure 2 shows the vertically-averaged salinity, temperature, turbidity, and dissolved oxygen
along the length of the estuary. Sampling was undertaken a long way up the estuary to positions
where the water was essentially fresh. Temperature and salinity decrease upstream whereas turbidity and dissolved oxygen increased upstream. Figure 3 shows chlorophyll-a increases upstream
consistent with increased dissolved oxygen that may be associated with primary production. Plotting chlorophyll-a against salinity (Figure 4), it is clear that the high upstream chlorophyll-a
near the head of the estuary is decoupled from downstream areas that have higher salinity. If
chlorophyll-a was conserved as it mixed downstream then there would be a more linear rela-
Light and chlorophyll-a, Sanderson
5
tionship between salinity and chlorophyll-a (assuming steady-state). The present measurements
indicate upstream phytoplankton suffer severe losses as they are mixed downstream into more
salty water.
Figure 5 shows salinity profiles near the junction of a creek draining Korangang. The main
channel is vertically well-mixed upstream of the junction. Water draining from Korangang is
relatively fresh. This illustrates the way in which horizontal mixing can result from oscillatory
tidal currents and channel junctions. This particular side creek is not explicitly treated in the
hydrodynamic model used for salinity calculations — rather it is parameterized as a horizontal
eddy-diffusivity.
Light and chlorophyll-a, Sanderson
6
Salinity Hunter River estuary, 24/07/2005
Depth (m)
0
−5
20
30
SB
−10
0
5
10
HB
10
RT Hunter River
15
20
25
Distance up estuary (km)
30
35
40
Temperature Hunter River estuary, 24/07/2005
Depth (m)
0
14
−5
12
16
SB
−10
0
5
HB
10
RT Hunter River
15
20
25
Distance up estuary (km)
30
35
40
DO, percent saturated Hunter River estuary, 24/07/2005
Depth (m)
0
−5
70
75
SB
−10
0
5
80
HB
10
15
20
25
Distance up estuary (km)
RT Hunter River
30
35
40
Turbidity Hunter River estuary, 24/07/2005
Depth (m)
0
−5
−10
0
5
10
20
3050
SB
5
HB
10
15
20
25
Distance up estuary (km)
RT Hunter River
30
35
40
Figure 1: Spatial structure of salinity, temperature, dissolved oxygen, and turbidity on 24/7/05.
Light and chlorophyll-a, Sanderson
7
TURB (NTU)
60
40
20
0
0
5
10
15
20
25
Distance up estuary (km)
30
35
40
45
0
5
10
15
20
25
Distance up estuary (km)
30
35
40
45
0
5
10
15
20
25
Distance up estuary (km)
30
35
40
45
0
5
10
15
20
25
Distance up estuary (km)
30
35
40
45
40
S (ppt)
30
20
10
0
T (Celcius)
17
16
15
14
13
12
DO (%)
85
80
75
70
Figure 2: Along-channel distribution of vertically-averaged: turbidity, salinity, temperature, and
dissolved oxygen on 24/7/05.
Light and chlorophyll-a, Sanderson
8
Chl−a (µg/l)
15
10
5
0
0
5
10
15
20
25
Distance up estuary (km)
30
35
40
0
5
10
15
20
25
Distance up estuary (km)
30
35
40
15
TURB (NTU)
10
5
0
−5
Figure 3: Along-channel distribution of near-surface chlorophyll-a on 24/7/05.
15
Chlorophyll−a (µg/l)
Chlorophyll−a (µg/l)
15
10
5
0
0
10
20
Salinity (ppt)
30
10
5
0
0
10
20
30
Turbidity (NTU)
40
50
Figure 4: Relationships between chlorophyll-a and salinity, and chlorophyll-a and turbidity on
24/7/05.
Light and chlorophyll-a, Sanderson
9
A
0
−1
−2
B
−3
A
−4
C
−5
15
20
25
T ( C), S (ppt)
30
o
0
0
−1
−1
−2
−2
−3
−3
C
−4
−5
15
20
25
o
T ( C), S (ppt)
B
−4
30
−5
15
20
25
T ( C), S (ppt)
30
o
Figure 5: Salinity profiles where a creek draining Korangang runs into the Hunter River Estuary
after about an hour of outgoing tide. Profile A is taken in the Hunter River Estuary upstream of
the junction. Profile B is taken in the Hunter River Estuary downstream of the junction. Profile
C is taken in the side creek.
Light and chlorophyll-a, Sanderson
3.2
10
9/8/05 Fluorescence, phytoplankton counts, nutrients, chlorophylla
Vertical gradients are weaker in Figure 6. These measurements of salinity, temperature, and
turbidity are similar to those obtained on the previous survey. Measurements were not made so
far upstream on this occasion, however, so the lowest salinities in Figure 7 are still markedly above
those of freshwater. Thus, although Figure 8 shows chlorophyll-a higher upstream, it does not get
as high as measurements made 24/7/05. Phytoplankton counts were made using two replicates at
each of the 9 measurement sites. The total number of phytoplankton is plotted as a function of
chainage in Figure 8. The large increase in chlorophyll-a near the head of the estuary is reflected
by large phytoplankton counts, but otherwise chlorophyll-a and total phytoplankton count are
poorly related (Figure 9). Given that phytoplankton can have vastly different sizes, it is hardly
surprising that total phytoplankton counts are a poor estimate of the amount of bulk measures of
a phytoplankton community (like chlorophyll-a).
Table 1 documents the distribution of phytoplankton counts among various taxonomic groups.
The very high diatom counts at the upstream site are due to Aulacoseira. Figure 10 shows that
Aulacoseira sp. counts vary exponentially over chainages 20-35 km upstream from the mouth
of the estuary. Aulacoseira is a common freshwater species in the Hunter River and it is not
surprising that its concentration drops by a factor of 3 for every 3.7 km of displacement into more
saline water. It would seem that Aulacoseira suffer mortality when salinity increased and the
distribution of Aulacoseira could be well represented using a mixing model.
The number of species (Table 1) is in the range 15-18 throughout except at the most upstream
sites. High counts of Aulacoseira sp. at the upstream sites are expected to bias the number of
species to lower values, as observed. Overall, it seems that the species richness does not vary
greatly along the length of the estuary for which measurements were made.
Different groupings of phytoplankton vary substantially along the length of the estuary (Table
1 and Figure 11). Diatoms (Bacillariophyceae) are most abundant near the head of the estuary
where there are large numbers of freshwater Aulacoseira. Counts of diatoms are low in mid-estuary
Light and chlorophyll-a, Sanderson
11
Salinity Hunter River estuary, 09/08/2005
Depth (m)
0
30
−5
−10
0
SB
5
10
20
HB
10
RT Hunter River
15
20
25
Distance up estuary (km)
30
35
40
Temperature Hunter River estuary, 09/08/2005
Depth (m)
0
16
−5
−10
0
SB
5
HB
10
RT Hunter River
15
20
25
Distance up estuary (km)
30
35
40
DO, percent saturated Hunter River estuary, 09/08/2005
Depth (m)
0
−5
−10
0
75
SB
5
HB
10
RT Hunter River
15
20
25
Distance up estuary (km)
30
35
40
Turbidity Hunter River estuary, 09/08/2005
Depth (m)
0
5
−5
−10
0
10
SB
5
HB
10
15
20
25
Distance up estuary (km)
RT Hunter River
30
35
40
Figure 6: Spatial structure of salinity, temperature, dissolved oxygen, and turbidity on 9/8/05.
Light and chlorophyll-a, Sanderson
12
TURB (NTU)
20
15
10
5
0
0
5
10
15
20
Distance up estuary (km)
25
30
35
0
5
10
15
20
Distance up estuary (km)
25
30
35
0
5
10
15
20
Distance up estuary (km)
25
30
35
0
5
10
15
20
Distance up estuary (km)
25
30
35
40
S (ppt)
30
20
10
0
17
T (ppt)
16.5
16
15.5
15
14.5
DO (%)
80
78
76
74
Figure 7: Along-channel distribution of vertically-averaged: turbidity, salinity, temperature, and
dissolved oxygen on 9/8/05.
Light and chlorophyll-a, Sanderson
13
Total phytoplankton (#/ml)
10000
8000
6000
4000
2000
0
0
5
10
15
20
25
Distance up estuary (km)
30
35
40
10
Chl−a (µg/l)
8
6
4
2
0
0
5
10
15
20
25
Distance up estuary (km)
30
35
40
0
5
10
15
20
25
Distance up estuary (km)
30
35
40
10
TURB (NTU)
8
6
4
2
0
Figure 8: Top, along-channel distribution of total phytoplankton count on 9/8/05. Middle, alongchannel distribution of near-surface chlorophyll-a on 9/8/05. Bottom, turbidity.
Light and chlorophyll-a, Sanderson
14
9000
8000
Total phytoplankton (#/ml)
7000
6000
5000
4000
3000
2000
1000
0
0
2
4
6
Chlorophyll−a (µg/l)
8
10
Figure 9: Total phytoplankton count is poorly related to chlorophyll-a on 9/8/05.
Light and chlorophyll-a, Sanderson
chainage salinity
15
Bacillario-
Dino-
Chrysophyceae
Chloro-
phyceae
phyceae +Chryptophyceae phyceae
Un-id Total
no.
nano
species
+Euglenophyceae
+Prasinophyceae
+Prasinophyceae
km
ppt
#/ml
#/ml
#/ml
#/ml
#/ml
#/ml
34.3
2.8
7047 (6605)
0
236
885
177
8345
10
32.0
4.0
3389 (3140)
0
74
575
162
4199
10
28.4
6.9
915 (778)
0
171
142
42
1269
14
26.1
10.2
664 (551)
127
365
101
165
1420
15
22.8
14.7
441 (264)
195
420
58
528
1641
16
20.6
19.0
243 (96)
147
611
8
774
1782
17
17.1
22.9
433 (0)
217
541
10
1022
2222
18
11.5
30.3
1396 (0)
176
639
0
776
2986
17
4.5
32.8
1781 (0)
50
393
0
246
2469
18
Table 1: Phytoplankton counts of various groups. The bracketed numbers under Bacillariophyceae
are counts of Aulacoseira sp. which are responsible for the high counts at the upstream sites.
Cyanophyceae counts were zero at all sites.
but increase significantly near the mouth due to the presence of Thalassiosira (Figure 11a). Thus,
diatoms seem to be represented by both oceanic and freshwater species. Green algae are abundant
upstream but counts fall as the salinity increases (Figure 11b) so one might conclude that the
green algae are also associated with freshwater. Dinoflagellates and unidentified nanoplankton are
low near the mouth and head of the estuary but high in mid-estuary. This indicates that the
Dinoflagellates and the unidentified nanoplankton are estuarine in origin — so they grow within
the estuary whereas the green algae and diatoms are mostly associated with boundary conditions.
Figures 12 and 13 show a large number of light profiles made at various distances (chainage)
upstream from the mouth of the estuary. Exponential functions are fitted to each profile to
Light and chlorophyll-a, Sanderson
16
4
10
Aulacoseira (#/ml)
3
10
2
e−folding scale = 3.4 km
10
1
10
20
25
30
35
chainage (km)
Figure 10:
Aulacoseira sp. decay with distance downstream. The concentration changes by a
factor of 3 every 3.7 km along-channel.
Light and chlorophyll-a, Sanderson
17
8000
1000
(a)
green algae
diatoms
4000
2000
0
(b)
800
6000
600
400
200
0
10
20
30
0
40
0
10
Chainage (km)
(c)
200
150
100
50
0
0
10
20
30
40
40
1000
800
600
400
200
0
Chainage (km)
Figure 11:
30
(d)
1200
unID nonoplankton
dinoflagellates
250
20
Chainage (km)
0
10
20
30
40
Chainage (km)
Along-channel distribution of phytoplankton groups. In plot (a) Aulacoseira sp.
make up most of the counts near the head of the estuary whereas Thalassiosira sp. make up
most of the counts at the mouth. The red crosses in plot (d) are a composite of Chrysophyceae,
Chryptophyceae, Euglenophyceae, and Prasinophyceae.
Light and chlorophyll-a, Sanderson
18
determine surface light intensity and the light attenuation coefficient κ. The e-folding scale for
light is given by κ−1 which is the depth (m) of water required to attenuate the light intensity by a
factor of 1/e ∼ 0.37. Light attenuation κ increases progressing upstream. Upstream, the e-folding
scale is 0.5 m. This means that the surface light intensity reduces by a factor of 0.0025 at a depth
of 3 m. High chlorophyll-a concentrations in the upstream waters would seem to require some
buoyancy mechanism to stabilize the water column — perhaps the temperature gradient.
Figure 14 plots light attenuation against chlorophyll-a and also against turbidity. While
chlorophyll-a contributes to light attenuation, it is not the dominant factor. There is a clear
relationship between light attenuation and turbidity.
Light and chlorophyll-a, Sanderson
19
Chainage = 4.5 km
Chainage = 11.506 km
0
0
1200 hrs
1315 hrs
−0.5
z (m)
z (m)
−0.5
−1
−1.5
−1
−1.5
I = 1246EXP(0.603z)
−2
0
500
1000
2
Light (W/m )
I = 1624EXP(1.19z)
−2
1500
0
500
1000
2
Light (W/m )
Chainage = 17.128 km
Chainage = 20.58 km
0
0
1400 hrs
1430 hrs
−0.5
z (m)
z (m)
−0.5
−1
−1.5
−1
−1.5
I = 877EXP(1.01z)
−2
0
200
400
Light (W/m2)
I = 1366EXP(1.15z)
−2
600
800
0
Chainage = 22.763 km
500
1000
Light (W/m2)
1500
Chainage = 25.399 km
0
0
1500 hrs
1535 hrs
−0.5
z (m)
−0.5
z (m)
1500
−1
−1.5
−1
−1.5
I = 1078EXP(1.32z)
−2
0
200
400
600
2
Light (W/m )
800
I = 996EXP(1.41z)
−2
1000
0
200
400
2
Light (W/m )
600
800
Figure 12: Light profiles, along with fitted curves based on a best-fit light attenuation coefficient
and surface irradiance. The coefficient of light attenuation increases with distance from the estuary
mouth (chainage).
Light and chlorophyll-a, Sanderson
20
Chainage = 27.07 km
Chainage = 31.919 km
0
0
1605 hrs
1635 hrs
−0.5
z (m)
z (m)
−0.5
−1
−1.5
−1
−1.5
I = 783EXP(1.53z)
−2
0
200
400
2
Light (W/m )
600
I = 335EXP(1.92z)
−2
800
0
100
200
2
Light (W/m )
300
Chainage = 34.174 km
0
1705 hrs
z (m)
−0.5
−1
−1.5
I = 279EXP(1.96z)
−2
0
100
200
2
Light (W/m )
300
Figure 13: Light profiles, along with fitted curves based on a best-fit light attenuation coefficient
and surface irradiance.
10
8
8
Chlorophyll−a (µg/l)
10
6
4
2
0
0
10
20
Salinity (ppt)
6
4
2
0
30
2
2
1.5
1.5
−1
κ (m )
21
κ (m−1)
Chlorophyll−a (µg/l)
Light and chlorophyll-a, Sanderson
1
0.5
0
5
10
15
Turbidity (NTU)
20
1
0.5
κ = 0.242 + 0.116Turb
0
0
2
4
6
Chlorophyll−a (µg/l)
8
10
0
0
5
10
Turbidity (NTU)
15
Figure 14: Relationships between chlorophyll-a and salinity, and chlorophyll-a and turbidity on
9/8/05. Relationships with light attenuation are also shown
Light and chlorophyll-a, Sanderson
3.3
22
12/8/05 Dilution experiment: grazing and phytoplankton growth
Table 2 presents vertically-averaged properties of the water column at 3 sites where water was
collected for dilution experiments. The dilution site with the lowest salinity still had salinity larger
than 6. From Figures 4 and 14 it is clear that high chlorophyll-a concentrations are restricted
to less saline waters. Chlorophyll-a does not vary greatly in the water samples collected for
the dilution experiment. Note, the highest salinity used for dilution experiments was 18.62 ppt.
Small filamentous macroalgae were found in more saline water and these can disrupt dilution
experiments.
If a water sample is incubated under sufficient photosynthetically active radiation then phytoplankton can be expected to grow. Measuring chlorophyll-a before and after the incubation gives
an estimate of phytoplankton growth minus any losses due to grazing by zooplankton (apparent
phytoplankton growth). If a sample is diluted with filtered seawater, then the grazing will be reduced. Incubating several samples with a range of dilutions gives apparent phytoplankton growth
rate as a function of dilution. Theoretically, the apparent phytoplankton growth rate should reduce as the fraction of unfiltered seawater increases. Fitting a linear line to a plot of apparent
growth rate against fraction of unfiltered seawater gives a fit where the negative of the slope is an
estimate of zooplankton grazing rate and the y-intercept is an estimate of phytoplankton growth
rate.
Figure 15 shows results for samples from 3 sites at locations documented in Table table:dilution.
(Note, location is most logically referenced to salinity in a tidal estuary.) Apparent growth rate
ln(chl-t/chl-i)/∆t is plotted against fraction unfiltered seawater. Here, chl-t is the chlorophyll-a
concentration after a 24 hour incubation and chl-i is the initial chlorophyll-a concentration. (The
incubation period ∆t, being 1 day, is implicit in the y-axis labelling of Figure 15.)
Grazing rates g, growth rates µ, and initial chlorophyll-a chl-i are recorded in Table 2. Initial
chlorophyll-a was in the range 1.5-3 µg/L, as expected given the salinity of the sampling locations.
Growth rates are much higher than grazing rates. Indeed, the average growth rate is 1.23 day −1
which amounts to an increase by a factor of 3.42 in a 1 day period. Subtracting out the effect
of grazing (with no dilution) gives an average growth rate of 1.08 day−1 which still amounts to
Light and chlorophyll-a, Sanderson
23
chainage salinity
temperature DO
turbidity comment
µ
g
chl-i
(km)
(ppt)
(Celsius)
(%) (NTU)
day−1
day−1
µg/L
4.5
32.4
15.4
70
7.1
9.9
28.9
14.0
73
7.6
13.2
23.1
13.7
71
7.1
17.1
16.1
13.5
71
4.0
18.6
18.6
13.8
72
4.1
Dilution 3 1.2
0.17
2.3
22.8
13.6
13.6
70
4.3
24.0
12.6
13.7
71
4.6
Dilution 2 1.2
0.09
1.5
28.4
6.9
13.4
69
7.0
Dilution 1 1.3
0.20
3.0
Table 2: Growth rates µ and grazing rates g from dilution experiments along with contextual
physical information. Salinity, temperature, DO, and turbidity are vertically-averaged through
the water column. The DO sensor was not calibrated so DO is biased low. DO is essentially the
same at all stations.
phytoplankton growing by a factor of 2.95 in a 1 day period. On the other hand, fluorescence
measurements in the Hunter River Estuary are relatively stable in the period 24/7/05 through
9/8/05 and consistent with initial chlorophyll-a values on 12/8/05. Clearly the growth rates
measured by the dilution experiment are potential growth rates whereas something other than
grazing is limiting phytoplankton growth in the estuary.
Some of the samples had bioavailable nitrogen added before incubation. These samples are
plotted in purple in Figure 15. Clearly, samples with added nutrient grew the same as samples for
which nutrient was not added. It follows, therefore, that nitrogen is not limiting phytoplankton
growth rate. Nitrogen is considered the nutrient most likely to limit growth in Australian estuaries
(Harris 199X) so it would seem that nutrients are not limiting phytoplankton growth in the Hunter
River Estuary.
Growth rates (Table 2) are essentially the same at each of the three locations from which
samples were obtained for dilution studies. On the other hand, Table 3 shows that the more
Light and chlorophyll-a, Sanderson
chainage salinity
Bacillariophyceae
24
Dino-
Chrysophyceae
Chloro-
Un-id Total
phyceae
+Chryptophyceae phyceae nano
no.
species
+Euglenophyceae
+Prasinophyceae
km
ppt
+Prasinophyceae
18.6
18.6
2712 (0,2683)
118
265
177
176
3448
10
24.0
12.6
803 (731,24)
24
306
47
165
1345
13
28.4
6.9
1371 (560,206)
133
590
30
542
2666
20
Table 3: Phytoplankton composition in dilution samples. Counts of Cyanophyceae were zero for all
dilution samples. The bracketed numbers under Bacillariophyceae represent counts of (Aulacoseira
sp., Chaetoceros spp.)
saline site was dominated by Chaetoceros spp. which was not abundant at the other sites. It
should also be noted that whereas Chaetoceros spp. dominated samples with salinity 18.6 ppt
on 12/8/05, they were not abundant in samples with similar salinity on 9/8/05. Clearly there
is much spatio-temporal variability in phytoplankton counts that would make them difficult to
model. Bulk properties, such as chlorophyll-a, are more readily modelled.
3.4
16/8/05 Zooplankton trawls
Table 4 shows vertically-averaged water column properties at sites where zooplankton trawls were
done. The most upstream zooplankton trawl site was in water with salinity 3.95 ppt, where
chlorophyll-a concentrations can be expected to be somewhat elevated. Filamentous macroalgae
were present at the more saline sites, but were not so abundant as on the previous field trips
(macro-algae abundance was qualitatively assessed from samples obtained in a small zooplankton
net).
Table 5 shows zooplankton counts/m3 from four sites along the Hunter River estuary. An
ensemble of three tows were made at each site using a 100 µm mesh net. The duration of each
tow was 2 minutes. The most marked features in this data are:
Light and chlorophyll-a, Sanderson
Figure 15: Plots of results from the dilution experiments.
25
Light and chlorophyll-a, Sanderson
26
chainage salinity
temperature DO
turbidity comment
(km)
(ppt)
(Celsius)
(%) (NTU)
9.936
30.71
15.38
74
7.8000
13.190
29.67
15.45
80
9.1667
17.127
24.12
14.89
78
5.0000
18.644
20.23
14.41
78
4.5000
21.469
20.23
14.63
81
5.5857
27.089
14.30
14.37
77
4.5750
28.399
12.27
14.16
73
6.2000
34.289
6.42
14.32
74
8.7000
44.000
3.95
14.53
80
18.3000
Zoop stn 4
Zoop stn 3
Zoop stn 2
Zoop stn 1
Table 4: Contextual information for zooplankton counts.
Quantities are vertically-averaged
through the water column.
• Fish eggs are more abundant in the low salinity waters at the upstream site (site 1).
• Calanoid adults were markedly more abundant in the low salinity waters at the upstream
site (site 1).
• Other copepods (Copepod Nauplii, juvenile Calanoid Copepodites, Cyclopoids, Harpacticoids)
were more broadly distributed through the estuary with a tendency for concentration to
increase somewhat downstream.
• The most downstream site (salinity 30.7 ppt) had markedly high concentrations of Noctiluca,
a marine heterotrophic dinoflagellate. Filamentous algae were also abundant at this site.
Light and chlorophyll-a, Sanderson
Taxa
27
Zoop stn 1 Zoop stn 2
Zoop stn 3
Zoop stn 4
(#/m3 )
(#/m3 )
(#/m3 )
(#/m3 )
Copepod Nauplii
36 ± 4
34 ± 8
34 ± 4
71 ± 30
Calanoid Copepodites (Juveniles)
62 ± 7
15 ± 2
29 ± 2
103 ± 28
Calanoid Adults
243 ± 50
14 ± 1
14 ± 3
8±1
Cyclopoids
0
5±2
16 ± 3
7±3
Harpacticoids
10 ± 0.9
0.67 ± 0.3
18 ± 2
38 ± 8
Noctiluca
0.3 ± 0.3
0.3 ± 0.3
22 ± 6
546 ± 170
Oikopleura (Appendicularian)
3±1
0.3 ± 0.3
1 ± 0.6
0.3 ± 0.3
Polychaete Trochophore/ Larvae
1 ± 0.6
1.3 ± 0.9
36 ± 4
70 ± 30
Bivalve Larvae
0.3 ± 0.3
2±1
2±1
1±1
Gastropod Larvae
4±2
5±3
3.7 ± 2
2.7 ± 1
Fish Eggs
10 ± 2
0.3 ± 0.3
1 ± 0.6
1.3 ± 0.7
Shrimp Larvae
0
0
0
2 ± 0.6
Jellyfish
0
0
0.3 ± 0.3
0
Chironomid
0.3 ± 0.3
0
0
0
Cladoceran
1.3 ± 0.9
0
0.3 ± 0.3
0.67 ± 0.3
Saltwater Mite
0.3 ± 0.3
0
0.3 ± 0.3
0
Crab Zoea
1.3 ± 0.9
0.3 ± 0.3
1 ± 0.6
8±5
Ostracod
0.3 ± 0.3
0
0.3 ± 0.3
0
Barnacle Cypris Larvae
0
0
7.7 ± 3
4±1
Barnacle Nauplii
0
0.67 ± 0.3
181 ± 6
31 ± 15
Snail Egg Case
0
0
0.3 ± 0.3
0
Cumacean
0
0
0.3 ± 0.3
0
Salinity
3.9
12.3
20
30.7
Filamentous algae
none
none
none
large amount
Table 5: Zooplankton counts (number/m3 ) from night tows on 16/8/05 using a 100 µm mesh net.
Tow duration was 2 minutes. Values at each site are an average of 3 tows plus/minus the standard
error.
Light and chlorophyll-a, Sanderson
4
28
Discussion
Upstream chlorophyll-a concentrations are high whereas those near the mouth of the ocean are
low, reflecting ocean conditions. The fact that chlorophyll-a drops rapidly as salinity increases
shows that phytoplankton in the fresh water are lost as they are mixed into more saline water.
Indeed, Aulacoseira counts decay exponentially with distance from the near-freshwater conditions
in the upper estuary. Similarly, it seems that oceanic species, eg Thalassiosira, can be abundant
in the lower estuary but have counts that are low upstream. Dinoflagellates and un-identified
nanoplankton were much more abundant in mid-estuary than near either upstream or downstream boundaries — indicating that conditions within the estuary are favourable for these two
groups.
Dilution experiments showed high potential growth rates with low grazing rates in the estuary
(salinities greater than 6 and less than 20). Further, the phytoplankton growth was not limited
by nitrogen. Incubations in the laboratory are under saturating light conditions. They are also
at slightly higher temperatures than the estuary. It is likely that the availability of light limits
phytoplankton growth in the estuary.
Benthic primary producers are obtain energy from the photosynthetically active radiation
reaching the bottom. The fraction of surface light reaching the bottom is shown as a function of
depth and light attenuation (κ) in Figure 16. Where the water column is deep benthic primary
producers are unlikely to get sufficient light.
Assume phytoplankton are vertically mixed through the water column on a time scale comparable to that over which they grow. Then the vertically-averaged light is an important factor for
controlling primary production of phytoplankton. Figure 17 plots the ratio of vertically-averaged
light to surface light as a function of both water depth and light attenuation κ. Clearly light attenuation and vertical mixing are going to be important factors controlling phytoplankton growth
within the Hunter River Estuary.
Hypsometry and an estimation of the vertically-averaged photosynthetically active radiation
would be a first step for modelling primary production in this estuary. Hypsometry can be cal-
Light and chlorophyll-a, Sanderson
29
2
−1
κ (m )
1.5
0.1
1
0.5
1
2
3
4
Water Depth (m)
5
6
Figure 16: The ratio of bottom light to surface light is contoured as a function of water depth and
light attenuation κ. The contour interval is 0.05. The dark contour is labelled.
culated from bathymetric data. More sophisticated treatments should consider the vertical stratification using a vertical mixing model and the tendency for baroclinicity to stabilize the water
column. Frequent measurement of the vertical and horizontal structure of chlorophyll would provide a data set for development of a primary production model. It must be stressed that the
present chlorophyll-a measurements were of near-surface waters. A proper understanding requires
measuring vertical profiles.
Light and chlorophyll-a, Sanderson
30
2
0.2
−1
κ (m )
1.5
0.4
1
0.5
1
2
3
4
Water Depth (m)
5
6
Figure 17: The ratio of vertically-averaged light to surface light is contoured as a function of water
depth and light attenuation κ. The contour interval is 0.1. The dark contours are labelled.