Does elevated CO2 affect phytoplankton growth and microzooplankton grazing
rates?
Kelly Govenar1, 2
Ocean Acidification Research Apprenticeship
Spring 2013
1
2
Friday Harbor Laboratories, University of Washington, Friday Harbor, WA 98250
School of Aquatic and Fishery Science, University of Washington, Seattle, WA 98105
Contact Info:
Kelly Govenar
5260 17th Avenue NE
Seattle, WA 98105
kgovenar@uw.edu
Keywords: mesocosms, growth, grazing, ocean acidification, phytoplankton,
microzooplankton
Govenar 1
Abstract
Phytoplankton growth and microzooplankton grazing responses to increased
pCO2 levels were investigated in a mesocosm study at the Friday Harbor Laboratories
during spring. Two phases were seen in the experiment, a pre-bloom period with low
biological production and a bloom period with high biological production. Phytoplankton
growth rates and microzooplankton grazing rates were determined using the dilution
method. Dilutions were performed on one control and one high treatment mesocosm
with pCO2 levels of 650 ppm and 1250 ppm respectively. There were no differences
found in growth and grazing rates between the control and high treatments. The grazing
rates were variable but generally decreased over time. The growth rates exceeded grazing
rates in all dilution experiments, which resulted in a net increase of the phytoplankton
standing stock overall. Microzooplankton ingestion rates and biomass-specific
microzooplankton clearance rates were highest on T0 and rapidly decreased after T2,
remaining low for the remainder of the experiment. These results show that the
microzooplankton were feeding on phytoplankton initially; however, the
microzooplankton switched food sources during the pre-bloom period when the
phytoplankton abundance was low.
Introduction
Over the past 250 years, atmospheric carbon dioxide (CO2) levels have increased
by nearly 40% from preindustrial levels of approximately 280 ppmv (parts per million
volume) to nearly 384 ppmv in 2007 (Solomon et al. 2007). The ocean plays a crucial
role in modulating atmospheric carbon dioxide (CO2) and it is the second largest sink for
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anthropogenic carbon dioxide after the atmosphere itself (Riebesell et al., 2007). The
increasing output of CO2 by humans, mostly from the burning of fossil fuels, is altering
the chemical balances and decreasing the pH of the ocean, which is referred to as ocean
acidification (Doney, 2009). Larger pH changes than any inferred from the geological
record of the past 300 million years are predicted over the next several centuries
(Caldeira and Wickett, 2003). As a result of a drop in pH, carbonate saturation is
decreasing, which has been shown in laboratory experiments to reduce calcification and
growth rates of shell-forming organisms like mollusks, echinoderms and corals (Doney,
2009). On the other hand, ocean acidification can cause an increase in carbon fixation
rates in some photosynthetic organisms (Doney, 2009). Both decreasing calcification and
enhanced carbon overproduction have the potential to increase the CO2 storage capacity
of the ocean (Riebesell 2004).
Autotrophic and mixotrophic plankton play a key role in the global carbon cycle as
they fix inorganic carbon, which is transferred to higher trophic levels through grazing
(Suffrian, 2008). Micro-zooplankton grazing is the main predatory pressure on planktonic
primary producers, consuming 60–70% of primary production (Calbet and Landry,
2004). Most of the remaining production is grazed by mesozooplankton (Calbet 2008).
Microzooplankton grazing is suggested to be a key process for the structuring of
phytoplankton biomass and community composition (Steele & Frost, 1977).
The objective of this experiment is to observe how increased carbon dioxide
levels affect phytoplankton growth rates and microzooplankton grazing rates. Very little
is known about the effects of increased CO2 on phytoplankton growth and grazing
interactions. The only two studies that explore this specifically had contrasting results.
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In the mesocosm experiment conducted by Suffrian et al. 2008, increased carbon dioxide
levels had no affect on microzooplankton grazing or phytoplankton growth rates.
However, in another mesocosm experiment conducted in South Korea, Kim et al. 2010
found that grazing rates increased with higher pCO2 levels. There is evidence that
phytoplankton growth can be stimulated by an increase in pCO2 (Tortell et al. 2008). In
our experiment, it is hypothesized that grazing rates will increase with increasing pCO2
because of stimulated growth of prey. The growth and grazing rates will be analyzed to
speculate what is happening in the community in respect to phytoplankton and
microzooplankton.
Methods
Mesocosm set up
A mesocosm experiment was conducted at the Friday Harbor Marine
Laboratories. The 9 mesocosms were made of polyethylene and held approximately
3500 L of water. These mesocosm bags were covered with mesh screening to reduce the
amount of light by about 50% and were attached to metal frames to the dock. A
plastic/Teflon diaphragm pump was used to fill a 1500 L reservoir with seawater
screened through 500 μm mesh to exclude large zooplankton. Each mesocosm was filled
in situ with water from the reservoir at 1 L per minute. A brine solution of 3500 g NaCl
and 15 L deionized H2O was added to the bags to increase the salinity and make them
denser than the surrounding water to increase the stability of the bags. The measured
increase of salinity was used to calculate the total volume of the mesocosm bags. The
mesocosms were manipulated to three pCO2 levels in triplicate. The control mesocosms
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were held at 650 ppm throughout the duration of the experiment. Two treatments, high
and drift, initially started with a pCO2 level of 1250 ppm. One set of three mesocosms
was maintained at 1250 ppm (high treatment) and the other set was allowed to drift
because no CO2 saturated seawater was added after the initial addition. CO2 saturated 0.2
μm filtered seawater was generated and maintained on the mesocosm dock and was
added to the mesocosms with a peristaltic pump.
Growth and grazing experiment
The growth rate of the phytoplankton community and the grazing rate of
microzooplankton were measured using the dilution method (Landry and Hassett, 1982).
These experiments were conducted on mesocosms 4 and 5, control and high treatment
respectively. Twenty liters of water was gently taken from the mesocosms and transferred
to 20 L polycarbonate carboys either using a peristaltic pump or a 5 L Niskin. There was
a 200 μm mesh screen at the intake of the water to prevent large mesozooplankton in the
mesocosms from being transferred into the experimental water. The two treatment whole
seawater was filtered through 3.0 μm and 0.2 μm capsule filters in series into 10 L
polycarbonate carboys to produce filtered seawater. All tubing and containers were acidcleaned in between uses. Whole seawater and filtered seawater were mixed to achieve
desired dilution levels. The dilution levels used in the study were 20% and 100% whole
seawater. Eight bottles per treatment were incubated. Three bottles were used for 20%
whole seawater (0.2 treatment) dilutions and three bottles were used for 100% whole
seawater (1.0 treatment) dilutions. Nutrients were added to all treatment bottles to prevent
nutrient depletion and maintain phytoplankton growth. Final concentrations of nutrients
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per bottle were 6 μmol L-1 NO3, 3.6 μmol L-1 PO4, and 6 μmol L-1 SiO4. Two additional
100% whole seawater bottles were filled without added nutrients to detect nutrient
limitation. The bottles were incubated off the dock next to the appropriate mesocosm for
24 hours at a depth with in situ light levels that matched the light levels in the mesocosm
bags.
Samples were taken for initial chlorophyll analysis. Additional samples taken
from the 20 L polycarbonate carboys were fixed with 0.5% gluteraldehyde and 2% lugols
solutions for initial cell counts of phytoplankton and microzooplankton. After incubation
(24 hours), replicate chlorophyll samples were taken from each bottle. Chlorophyll
samples were immediately filtered onto 25 mm glass microfiber filters, extracted in 6 ml
of 90% acetone and frozen overnight. The following day, chlorophyll samples were read
on a Turner TD 700 fluorometer.
Data analysis
The initial and final chlorophyll levels represented initial (PI) and final (PF)
phytoplankton densities and were used to calculate net growth rate (k), assuming
exponential growth (k = ln(PF/ PI)/t, t=1 because incubation of 1 day). The net growth
rate (k) at two dilution levels were used to find the intrinsic growth rate (μ) and intrinsic
grazing rate (g) based on the equation, k= μ – Dg (D is the dilution factor, i.e., 20%
seawater, D= 0.2) (Landry and Hassett, 1982, Lessard and Murrell, 1998). The intrinsic
growth rate of the phytoplankton should be the same at both dilution levels because we
assume that growth rate of the individual phytoplankton is not directly affected by the
presence of other phytoplankton. The phytoplankton should not be limited by nutrients or
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light; therefore dilution does not affect their growth rate. The grazing impact of
microzooplankton is decreased by dilution because the grazing impact is a direct function
of the rate of encounter of consumers with prey. The microzooplankton encounter their
prey, the phytoplankton, by the factor of the dilution level. If the intrinsic growth rate is
greater than the intrinsic grazing rate, the net growth rate will be positive and there will
be an increase in phytoplankton over time. On the other hand, if the intrinsic grazing rate
exceeds the intrinsic growth rate, there will be a net decrease of phytoplankton biomass
over time. The net growth rate (k) was plotted for the two dilutions. Typically with
dilution experiments with more than two dilution levels, the negative slope of this
relationship is the microzooplankton grazing rate (g) and the y-intercept is the
phytoplankton growth rate (μ). In our case, the net growth rates at two dilution levels
yielded two equations, k0.2= μ – 0.2g and k1.0= μ – g. From measured differences in net
growth rates, the two equations were used to solve for two unknowns, g and μ, where g =
k0.2-k1.0 /0.8 and μ=kD + g.
Experimental estimates of μ and g were used to compute rates of phytoplankton
production, microzooplankton consumption, biomass-specific clearance rates of
heterotrophic protists, and biomass-specific ingestion rates of microzooplankton feeding
on phytoplankton according to Landry et al. 2008. The initial carbon biomass of
phytoplankton, used to solve for production and consumption, was found by multiplying
the amount of chlorophyll by the carbon to chlorophyll ratio of 30:1, which is typical of
this type of environment (Lessard, personal communication).
All statistical analyses were performed using IBM SPSS Statistics 19.
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Results
Temporal development of chlorophyll and nitrate
Two phases were seen in the experiment; a pre-bloom period (T0-T10) and bloom
period (T11-T21). This is shown particularly by the nitrate, chlorophyll, and oxygen data
(Figure 1A, B). The pre-bloom period had a low level of biological production shown by
the little drawdown of NO3 and slow increase of chlorophyll production. After
determining that the mesh screens were fouling and reducing light to very low levels over
time, part of the mesh shading was removed at T10 to increase light penetration.
Subsequently, there was an increase in biological production in the bloom period
evidenced by a rapid increase of chlorophyll till a peak on T19 (Figure 1A) and a rapid
decrease of NO3 (Figure 1B). At the end of the experiment, NO3 was completely depleted
in mesocosm 4 and reached a level of 3.2 μmol/L in mesocosm 5 (Figure 1B).
Trends in phytoplankton growth and grazing
Grazing rates were variable but generally decreased over time. The average
grazing rate in the control treatment (mesocosm 4) was 0.09 day-1 and the high treatment
(mesocosm 5) averaged 0.08 day-1 (Figure 2). The grazing rates were highest for the high
and control treatments on T0 with rates of 0.21 day-1 and 0.23 day-1 respectively. The
grazing rate reached 0 day-1 on T4 for the control and on T19 for both treatments, which
was the last dilution. A Two-Tailed T-test was performed on the grazing rates and there
was no significant difference found between the high and control treatments (p=0.743).
The intrinsic growth rates were variable and ranged from 0.3 to 0.47 day-1 in the
control treatment and from 0.1 to 0.74 day-1 in the high treatment (Figure 3). A
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Wilcoxon-Signed Ranked Test was performed and no significant difference was found
between the intrinsic growth rates of phytoplankton in the bottles with and without
nutrients (p = 0.71). The growth rates of the phytoplankton without added nutrients were
used except for the last dilution experiment on T19, when there was nutrient limitation.
The phytoplankton intrinsic growth rate exceeded the intrinsic grazing rate in all nine
dilution experiments (Figure 4).
The phytoplankton primary production (mg C m-3 day-1, Figure 5) generally
increased with time and hit a peak on T16 in the high and control treatments. On T16, the
control had a much higher primary production value than the high treatment, which was
299 mg C m-3 day-1 for the control and 141 mg C m-3 day-1 for the high. On T19, primary
production decreased in both treatments. The primary production follows the trend of the
estimated phytoplankton biomass, calculated from the chlorophyll values and a carbon to
chlorophyll ratio of 30:1. Both the phytoplankton biomass and the primary production
increased more quickly after T10, when the mesh covering was reduced on the
mesocosms. The decrease of primary production on T19 differs from the continuous
increase of phytoplankton biomass till a peak on T19.
The biomass-specific microzooplankton clearance rates (Figure 6A) were highest
on T0 for both the control and high, which were 158.1 L mg C-1 day-1 and 147.4 L mg C-1
day-1 respectively. On T2, the clearance rates decreased dramatically to 16.1 L mg C-1
day-1 in the control and 19.7 L mg C-1 day-1 in the high. From T4 to T19, the clearance
rates never reached above 2 L mg C-1 day-1 and on T19, both treatments had a clearance
rate of 0 L mg C-1 day-1 (Figure 6B). The clearance rates generally followed a decreasing
trend (Figure 6A,B).
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The microzooplankton ingestion rates followed a similar pattern as the clearance
rates (Figure 7A,B). On T0, the control and high treatments had the highest ingestion
rates of 669% and 578% body carbon consumed day-1 respectively. The ingestion rates
decreased to 96% body carbon consumed day-1 in the control and 114% body carbon
consumed day-1 in the high on T2. From T4-T16, in both treatments, the ingestion rates
ranged from 2-23% body carbon consumed day-1 and reached 0% body carbon consumed
day-1 on T19.
The microzooplankton biomass began to increase on T6, which was before the
bloom period, and reached a peak on T16 (Gravinese 2013). The ingestion rates show
that the microzooplankton were consuming less than 0.25 times their body weight in food
each day during the largest increase in microzooplankton biomass during T6-T16. The
phytoplankton abundance began to increase after T12, close to when the bloom period
began, and was highest on T21 (Stephens 2013).
Discussion
In our experiment, mesh screening was applied to the mesocosm bags to reduce
the light in the bags by about 50%; however, over time the screens decreased the light by
about 90%, likely due to a build up of benthic diatoms on the mesh. The decision to
remove the tops and lower the mesh bags on T10 was made to ensure that a
phytoplankton bloom would occur before the end of the experiment. Before the removal
of the screening, the phytoplankton in the mesocosms were light limited and did not
increase substantially in biomass or abundance. Following screen removal, chlorophyll
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increased rapidly to a peak of 33.9 μg/L in mesocosm 4 and 31.0 μg/L in mesocosm 5 on
T19 (Figure 1A).
The grazing rates on phytoplankton did not impact the phytoplankton standing
stock substantially. This was evidenced by the intrinsic growth rates exceeding grazing
rates in both the control and high CO2 treatments in all dilution experiments (Figure 4),
resulting in an increase in phytoplankton standing stock overall. The grazing rates were
relatively low, especially compared to the equatorial Pacific, another high nutrient low
chlorophyll (HNLC) area, where the grazing rate averaged 0.72 day-1 in the upper
euphotic zone (Landry et al. 1995). It is inconclusive why the grazing rates are so
variable in the dilution experiment. The biomass of individual groups of phytoplankton
could not be resolved with the available data, which made it difficult to determine
reasons for differences in grazing rates day to day.
The variability of intrinsic growth rates could have been due to differences in the
amount of light received during incubations. The low nitrate levels in mesocosms 4 and 5
on T19 (Figure 1B) corresponded to when there was nutrient limitation in the incubation
bottles. The non-nutrient amended growth rate values were used because the conditions
were more similar to the conditions in the mesocosms since no nutrients were added to
the mesocosms during the experiment. The decrease in primary production on T19
(Figure 5) could be attributed to the low nitrate levels. If the primary production had been
found for T20 and T21, they would have mostly likely continued to decrease from T19
levels due to the decreasing trend of nitrate in the mesocosms (Figure 1B).
The low clearance and ingestion rates of microzooplankton on phytoplankton
during the time period that the heterotrophic dinoflagellate biomass was increasing the
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most (T6-T16) suggests that the microzooplankton had an additional food source that
enabled them to grow and increase in biomass. Initially, the microzooplankton fed at
moderate rates on the phytoplankton; however, they seem to have changed their food
source while the phytoplankton biomass was low in the pre-bloom period. The idea of
changing food preference has been described as “switching” by Murdoch (1969). The
microzooplankton may have encountered far less phytoplankton than normally found in
the natural environment and encountered another type of heterotroph, so they switched
feeding mechanisms or types of food. There is some evidence that predator preference is
variable and tends to become stronger or weaker for a prey species as that species forms a
larger or smaller proportion of the food available (Murdoch 1973). The changing of food
preferences could also be related to a change in prey food quality. It is possible that the
physiology of light-limited phytoplankton lowered their food quality and the
microzooplankton switched to higher quality heterotrophic food sources.
The dilution method used here only measures changes in chlorophyll, and
therefore only detects microzooplankton grazing on phytoplankton. If the
microzooplankton were feeding on another food source, the chlorophyll-based dilution
method would not be able to point out the other source of food directly. Data from
Gravinese (2013) suggests that the heterotrophic dinoflagellates were feeding on other
heterotrophic dinoflagellates or other heterotrophs. It has been found that protists can
and do consume other heterotrophic protists (Sherr & Sherr 2002) and it seems plausible
that this is occurring in our mesocosm community. In future mesocosm studies, the
dilution experiment should be modified to determine if microzooplankton are feeding on
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other microzooplankton. This could be done by counting heterotrophs in preserved
samples before and after incubation to measure growth and grazing rates of heterotrophs.
Conclusion
Our results refute the initial hypothesis that grazing rates would increase with
increasing pCO2. It was found that elevated pCO2 levels did not affect growth and
grazing rates. The phytoplankton standing stock showed a net increase overall because
growth rates always exceeded grazing rates. Results showed there was a unique shift in
the food preference of the grazers. The microzooplankton initially fed on phytoplankton
but changed food sources, feeding most likely on other heterotrophs. The change in food
preference was most likely due to the low contribution of phytoplankton to the prey
abundance or due to a change in prey food quality because of light limitation.
Compared to other mesocosm studies that allowed the pCO2 levels to drift, we
kept the pCO2 levels constant in the control and high treatments. This could have greatly
affected the results of the experiment. Light limitation in the pre-bloom period was likely
a significant factor that contributed to the community interactions that we saw. The
grazer on grazer feeding that was most likely occurring may not have occurred if the
mesh bags did not limit the light so greatly. In future mesocosm studies, it would be ideal
to conduct dilution experiments on replicate high and control treatment mesocosms to
have more statistical power; however, this would require an extensive amount of work
and personnel.
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Acknowledgements
I would like to thank Friday Harbor Laboratories and the University of
Washington for providing us with space to conduct our experiment. I would like to give a
special thanks to Jim Murray, Dr. Evelyn Lessard, Mike Foy, Kelsey Gaessner and the
other student apprentices for their help and support throughout the entire experiment.
Lastly, thank you to the Henry and Holly Wendt Endowment to support FHL research
apprenticeships and UW Provost support of FHL apprenticeships. Funding was provided
by the Educational Foundation of America and the National Science Foundation (NSF
Grant #:DBI 0829486).
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Chlorophyll (mg/L)
Chlorophyll
A
40
M1
35
M2
M3
30
M4
25
M5
20
M6
15
M7
10
M8
5
M9
Dock
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
Nitrate
35
B
30
NO3 (mmol/L)
25
20
15
10
5
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
Time (Days)
Figure 1. Graph 1A shows the chlorophyll levels over time for all mesocosms. Graph 1B
shows the nitrate levels over time for all mesocosms.
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Grazing Rates on Phytoplankton
Grazing Rate (Day-1 )
0.27
0.21
control
0.15
high
0.09
0.03
N/A
N/A
0
-0.03
2
4
6
8
10
12
Time (Day)
14
16
18
19
Figure 2. Plot of the intrinsic grazing rates over time. Dilution experiments were not
performed on T12 or T18, which is shown as N/A on the graph. A two-tailed T-test was
performed on the grazing rates and there was no significant difference found between
treatments (t=0.333, p=0.743). Error bars are median standard deviations (MAD=0.05).
0.9
Phytoplankton Growth Rates
Growth Rate (Day-1)
0.8
0.7
control
0.6
high
0.5
0.4
0.3
0.2
0.1
N/A
N/A
0
0
2
4
6
8
10
12
14
16
18
19
Time (Day)
Figure 3. Plot of the intrinsic growth rates over time. Dilution experiments were not
performed on T12 or T18, which is shown as N/A on the graph. Error bars are median
standard deviations. (MAD=0.05).
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Growth vs.
Grazing
Intrinsic Growth Rate (day-1)
0.8
0.7
0.6
0.5
0.4
high
0.3
control
0.2
0.1
0
0
0.1
0.2
0.3
0.4
Intrinsic Grazing Rate
0.5
0.6
0.7
0.8
(day-1)
Figure 4. Plot of intrinsic grazing rate versus intrinsic growth rate. The black line
represents a 1:1 ratio of grazing rate to growth rate, meaning a net growth rate of zero.
Primary Production
Phytoplankton Production (mg C m-3
day-1)
350
300
250
200
control
150
high
100
50
0
0
1
2
3
4
5
6
7
8 9 10 11 12 13 14 15 16 17 18 19
Time (Day)
Figure 5. Plot of phytoplankton primary production over time.
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Biomass-specific Microzooplankton Clearance Rates
Clearance Rate (volume cleared mg C-1 day-1 )
180
A
160
140
120
100
Control
High
80
60
40
20
0
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20
3
Clearance Rate (volume cleared mg
day-1)
3.5
C-1
4
B
2.5
2
1.5
1
0.5
0
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20
Time (Day)
Figure 6. Both graphs show the clearance rates over time. Graph 6A shows the rates over
the entire experiment. Graph 6B shows a close up of the clearance rates from T4 to T19.
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Ingestion Rate (% body C cosumed
day-1)
800
700
Microzooplankton Ingestion Rates
A
600
500
Control
400
High
300
200
100
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Ingestion Rate (% body C cosumed d^-1)
30
25
B
20
15
10
5
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Time (day)
Figure 7. Both graphs show ingestion rates over time. Graph 7A shows the rates over the
entire experiment. Graph 7B shows a close up of the ingestion rates from T4 to T19.
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