Salinity, light and chlorophyll-a in the Hunter River Estuary · Light and chlorophyll-a, Sanderson 6 0 5 10 15 20 25 30 35 40 −10 −5 0 SB HB RTHunter River Distance up estuary

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 2

1 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 phytoplank-

ton 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 estab-

lished. This may be useful for future work since turbidity measurements are commonly available.


2 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, tur-

bidity, 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 mea-

surements were made in conjunction with salinity, temperature, turbidity, and dissolved-

oxygen 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 ex-

tractions, 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 mea-

surements of temperature, salinity and turbidity in order to provide contextual information.


3 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 oC near the mouth of the estuary

and fell to 12 oC 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 oC 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 tur-

bidity and dissolved oxygen increased upstream. Figure 3 shows chlorophyll-a increases upstream

consistent with increased dissolved oxygen that may be associated with primary production. Plot-

ting 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-


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.


0 5 10 15 20 25 30 35 40−10

−5

0

SB HB RTHunter River

Distance up estuary (km)

Dep

th (

m)

102030

Salinity Hunter River estuary, 24/07/2005

0 5 10 15 20 25 30 35 40−10

−5

0



Dep

th (

m)

1214

16

Temperature Hunter River estuary, 24/07/2005

0 5 10 15 20 25 30 35 40−10

−5

0


Dep

th (

m)

7075 80


DO, percent saturated Hunter River estuary, 24/07/2005

0 5 10 15 20 25 30 35 40−10

−5

0



510 203050

Dep

th (

m)

Turbidity Hunter River estuary, 24/07/2005

Figure 1: Spatial structure of salinity, temperature, dissolved oxygen, and turbidity on 24/7/05.


0 5 10 15 20 25 30 35 40 450

20

40

60


TU

RB

(N

TU

)

0 5 10 15 20 25 30 35 40 450

10

20

30

40


S (

ppt)

0 5 10 15 20 25 30 35 40 4512

13

14

15

16

17


T (

Cel

cius

)

0 5 10 15 20 25 30 35 40 4570

75

80

85


DO

(%

)

Figure 2: Along-channel distribution of vertically-averaged: turbidity, salinity, temperature, and

dissolved oxygen on 24/7/05.


0 5 10 15 20 25 30 35 400

5

10

15


Chl

−a

(µg/

l)

0 5 10 15 20 25 30 35 40−5

0

5

10

15


TU

RB

(N

TU

)

Figure 3: Along-channel distribution of near-surface chlorophyll-a on 24/7/05.

0 10 20 300

5

10

15

Chl

orop

hyll−

a (µ

g/l)

Salinity (ppt)0 10 20 30 40 50

0

5

10

15

Chl

orop

hyll−

a (µ

g/l)

Turbidity (NTU)

Figure 4: Relationships between chlorophyll-a and salinity, and chlorophyll-a and turbidity on

24/7/05.


A

B

C15 20 25 30

−5

−4

−3

−2

−1

0

A

T (oC), S (ppt)

15 20 25 30−5

−4

−3

−2

−1

0

B

T (oC), S (ppt)

15 20 25 30−5

−4

−3

−2

−1

0

C

T (oC), S (ppt)

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.


3.2 9/8/05 Fluorescence, phytoplankton counts, nutrients, chlorophyll-

a

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


0 5 10 15 20 25 30 35 400

5

0


1020

30

−1

−


Dep

th (

m)

Salinity Hunter River estuary, 09/08/2005

0 5 10 15 20 25 30 35 4010

−5

0


16

−


Dep

th (

m)

Temperature Hunter River estuary, 09/08/2005

0 5 10 15 20 25 30 35 400

5

0


75

−1

−


Dep

th (

m)

DO, percent saturated Hunter River estuary, 09/08/2005

0 5 10 15 20 25 30 35 4010

−5

0


510

Turbidity Hunter River estuary, 09/08/2005

−


Dep

th (

m)

Figure 6: Spatial structure of salinity, temperature, dissolved oxygen, and turbidity on 9/8/05.


0 5 10 15 20 25 30 350

5

10

15

20


TU

RB

(N

TU

)

0 5 10 15 20 25 30 350

10

20

30

40


S (

ppt)

0 5 10 15 20 25 30 3514.5

15

15.5

16

16.5

17


T (

ppt)

0 5 10 15 20 25 30 3574

76

78

80


DO

(%

)

Figure 7: Along-channel distribution of vertically-averaged: turbidity, salinity, temperature, and

dissolved oxygen on 9/8/05.


0 5 10 15 20 25 30 35 400

2000

4000

6000

8000

10000


Tot

al p

hyto

plan

kton

(#/

ml)

0 5 10 15 20 25 30 35 400

2

4

6

8

10


Chl

−a

(µg/

l)

0 5 10 15 20 25 30 35 400

2

4

6

8

10


TU

RB

(N

TU

)

Figure 8: Top, along-channel distribution of total phytoplankton count on 9/8/05. Middle, along-

channel distribution of near-surface chlorophyll-a on 9/8/05. Bottom, turbidity.


0 2 4 6 8 100

1000

2000

3000

4000

5000

6000

7000

8000

9000

Chlorophyll−a (µg/l)

Tot

al p

hyto

plan

kton

(#/

ml)

Figure 9: Total phytoplankton count is poorly related to chlorophyll-a on 9/8/05.


chainage salinity Bacillario- Dino- Chrysophyceae Chloro- Un-id Total no.

phyceae phyceae +Chryptophyceae phyceae 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


20 25 30 3510

1

102

103

104

chainage (km)

Aul

acos

eira

(#/

ml)

e−folding scale = 3.4 km

Figure 10: Aulacoseira sp. decay with distance downstream. The concentration changes by a

factor of 3 every 3.7 km along-channel.


0 10 20 30 400

2000

4000

6000

8000

Chainage (km)

diat

oms

(a)

0 10 20 30 400

200

400

600

800

1000

Chainage (km)

gree

n al

gae

(b)

0 10 20 30 400

50

100

150

200

250

Chainage (km)

dino

flage

llate

s

(c)

0 10 20 30 400

200

400

600

800

1000

1200

Chainage (km)

unID

non

opla

nkto

n

(d)

Figure 11: 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.


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.


0 500 1000 1500

−2

−1.5

−1

−0.5

0Chainage = 4.5 km

Light (W/m2)

z (m

)

I = 1246EXP(0.603z)

1200 hrs

0 500 1000 1500

−2

−1.5

−1

−0.5

0Chainage = 11.506 km

Light (W/m2)

z (m

)

I = 1624EXP(1.19z)

1315 hrs

0 200 400 600 800

−2

−1.5

−1

−0.5


Light (W/m2)

z (m

)

I = 877EXP(1.01z)

1400 hrs

0 500 1000 1500

−2

−1.5

−1

−0.5


Light (W/m2)

z (m

)

I = 1366EXP(1.15z)

1430 hrs

0 200 400 600 800 1000

−2

−1.5

−1

−0.5


Light (W/m2)

z (m

)

I = 1078EXP(1.32z)

1500 hrs

0 200 400 600 800

−2

−1.5

−1

−0.5


Light (W/m2)

z (m

)

I = 996EXP(1.41z)

1535 hrs

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).


0 200 400 600 800

−2

−1.5

−1

−0.5


Light (W/m2)

z (m

)

I = 783EXP(1.53z)

1605 hrs

0 100 200 300

−2

−1.5

−1

−0.5


Light (W/m2)

z (m

)

I = 335EXP(1.92z)

1635 hrs

0 100 200 300

−2

−1.5

−1

−0.5


Light (W/m2)

z (m

)

I = 279EXP(1.96z)

1705 hrs

Figure 13: Light profiles, along with fitted curves based on a best-fit light attenuation coefficient

and surface irradiance.


0 10 20 300

2

4

6

8

10

Chl

orop

hyll−

a (µ

g/l)

Salinity (ppt)0 5 10 15 20

0

2

4

6

8

10

Chl

orop

hyll−

a (µ

g/l)

Turbidity (NTU)

0 2 4 6 8 100

0.5

1

1.5

2

Chlorophyll−a (µg/l)

κ (m

−1 )

0 5 10 150

0.5

1

1.5

2

Turbidity (NTU)

κ (m

−1 )

κ = 0.242 + 0.116Turb

Figure 14: Relationships between chlorophyll-a and salinity, and chlorophyll-a and turbidity on

9/8/05. Relationships with light attenuation are also shown


3.3 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 phyto-

plankton 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 re-

duced. 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 re-

duce 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


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


chainage salinity Bacillariophyceae Dino- Chrysophyceae Chloro- Un-id Total no.

phyceae +Chryptophyceae phyceae nano 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:


Figure 15: Plots of results from the dilution experiments.


chainage salinity temperature DO turbidity comment

(km) (ppt) (Celsius) (%) (NTU)

9.936 30.71 15.38 74 7.8000 Zoop stn 4

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 Zoop stn 3

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 Zoop stn 2

34.289 6.42 14.32 74 8.7000

44.000 3.95 14.53 80 18.3000 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.


Taxa 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.


4 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 down-

stream 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 compa-

rable 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 at-

tenuation 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-


Water Depth (m)

κ (m

−1 )

0.1

1 2 3 4 5 60.5

1

1.5

2

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 strat-

ification 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 pro-

vide 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.


Water Depth (m)

κ (m

−1 )

0.2

0.4

1 2 3 4 5 60.5

1

1.5

2

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.

Documents

Salinity, light and chlorophyll-a in the Hunter River Estuary · Light and chlorophyll-a, Sanderson 6 0 5 10 15 20 25 30 35 40 −10 −5 0 SB HB RTHunter River Distance up estuary