Does elevated CO2 affect phytoplankton growth and microzooplankton grazing

rates?

Kelly Govenar1, 2

Ocean Acidification Research Apprenticeship

Spring 2013

1Friday Harbor Laboratories, University of Washington, Friday Harbor, WA 982502School of Aquatic and Fishery Science, University of Washington, Seattle, WA 98105

Contact Info:Kelly Govenar5260 17th Avenue NESeattle, WA 98105kgovenar@uw.edu

Keywords: mesocosms, growth, grazing, ocean acidification, phytoplankton, microzooplankton

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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 acid-

cleaned 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 Wilcoxon-

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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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0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 210

5

10

15

20

25

30

35

40

Chlorophyll

M1

M2

M3

M4

M5

M6

M7

M8

M9

Dock

Chl

orop

hyll

(mg/

L)A

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 210

5

10

15

20

25

30

35

Nitrate

Time (Days)

NO

3 (m

mol

/L)

B

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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0 2 4 6 8 10 12 14 16 18 19-0.03

0.03

0.09

0.15

0.21

0.27

control

high

Time (Day)

Gra

zin

g R

ate

(Day

-1 )

N/AN/A

Grazing Rates on Phytoplankton

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 2 4 6 8 10 12 14 16 18 190

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

controlhigh

Time (Day)

Gro

wth

Rat

e (D

ay-1

)

N/A N/A

Phytoplankton Growth Rates

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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0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.80

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

highcontrol

Intrinsic Grazing Rate (day-1)

Intr

insi

c G

row

th R

ate

(day

-1)

Growth vs. Grazing

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.

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 190

50

100

150

200

250

300

350

controlhigh

Time (Day)

Phyt

opla

nkto

n Pr

oduc

tion

(mg

C m

-3

day-

1)

Primary Production

Figure 5. Plot of phytoplankton primary production over time.

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0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

20

40

60

80

100

120

140

160

180

ControlHigh

Cle

aran

ce R

ate

(vol

ume

clea

red

mg

C-1

day

-1 ) A

Biomass-specific Microzooplankton Clearance Rates

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

0.5

1

1.5

2

2.5

3

3.5

4

Time (Day)

Cle

aran

ce R

ate

(vol

ume

clea

red

mg

C-1

day

-1)

B

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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0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

100

200

300

400

500

600

700

800

ControlHigh

Inge

stio

n R

ate

(% b

ody

C co

sum

ed

day

-1)

AMicrozooplankton Ingestion Rates

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

5

10

15

20

25

30

Time (day)

Inge

stio

n R

ate

(% b

ody

C co

sum

ed d

^-1

) B

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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