Effects of High CO2 on Primary
Production in a Boreal Fjord
—A five month mesocosm
study in Gullmarsfjord
Anna Maria Forsberg Grivogiannis
Degree project for Master of Science in
Biology and Marine Sciences
Degree course in BIO761 45 hec
2013–2014
Department of Biological and Environmental Sciences
University of Gothenburg
Examiner: Kristina Sundbäck
Department of Biological and Environmental Sciences
University of Gothenburg
Supervisor: Angela Wulff
Department of Biological and Environmental Sciences
University of Gothenburg
Abstract
Increasing levels of carbon dioxide (CO2 ) in the atmosphere, as a result of human activity,
inevitably increases the CO2 concentration of the ocean water causing a drop in pH
(ocean acidification) and affecting marine ecosystems. Phytoplankton, at the base of
most marine food-webs, are sensitive to changes in the carbonate system. This study
aimed to investigate the effects that future levels of ocean CO2 could have on the carbonuptake capacity of natural phytoplankton communities. In February of 2013 ten Kiel OffShore Mesocosms for Future Ocean Simulations (KOSMOS) were deployed in Gullmarsfjord, Sweden –five controls and five with elevated CO2 levels. During five months
samples were collected every fourth day and using 14 C incubations (24h), the sensitivities
in primary production (PP), particulate organic carbon (POC) and dissolved organic
carbon (DOC) were tested. The bloom-patterns of the phytoplankton communities in
each mesocosm were remarkably similar, even after being isolated for several months.
The cumulative primary production was found to be significantly higher in the highCO2 mesocosms while the chlorophyll a levels did not differ. In contrast to previous
experiments, no significant difference in DOC-levels was detected between treatments.
During the first bloom there was an unexpected observation of a DOC-productivity-peak
prior to the POC-productivity peak. Being the first of its kind in terms of length and
size, this experiment-design provides a platform for ecosystem-studies leaving room for
improvements and variations. The resolution at this stage is low, i.e. positive growth
of one phytoplankton species could be shadowed by negative growth of another. Future
experiments should include DNA-sequencing and move on to examine aspects like the
adaptation potential of marine organisms.
Contents
1 Introduction
1.1 Ocean Acidification . . . . . .
1.1.1 Carbonate Chemistry
1.1.2 Carbon Cycle . . . . .
1.2 Primary Production . . . . .
1.2.1 14 C Method . . . . . .
1.3 Knowns and Unknowns . . .
1.3.1 Climate Proxies . . . .
1.3.2 Previous Studies . . .
1.3.3 Why Mesocosms? . . .
1.4 Location – Gullmar Fjord . .
1.5 Aim . . . . . . . . . . . . . .
2 Material and Methods
2.1 Experimental Design . . . . .
2.1.1 KOSMOS . . . . . . .
2.1.2 CO2 Manipulation . .
2.1.3 Volume determination
2.2 Sampling and Analysis . . . .
2.2.1 Sampling . . . . . . .
2.2.2 Primary productivity .
2.2.3 Chlorophyll a . . . .
2.2.4 Statistical Analysis . .
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3 Results
3.1 Bloom Development . . . . . . . . . . .
3.2 Primary Production of Organic Carbon
3.3 Particulate Organic Carbon (POC) . . .
3.4 Dissolved Organic Carbon (DOC) . . . .
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CONTENTS
4 Discussion
19
4.1 Interpretation of Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.2 Method Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.3 Future Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Bibliography
30
A Appendix
A.1 Table of Primary Production . . . . . . . . . . . . . . . . . . . . . . . . .
A.2 Graph of High CO2 Treatment . . . . . . . . . . . . . . . . . . . . . . . .
A.3 Graph of Low CO2 Treatment . . . . . . . . . . . . . . . . . . . . . . . . .
ii
31
32
33
34
1
Introduction
ne of the most abundant gases in the earth’s atmosphere is carbon dioxide
(CO2 ), right next to nitrogen, oxygen and argon. Oceans cover 71% of the
worlds surface (361×106 km2 ) and looking at the combined atmosphere-ocean
system, 98% of the CO2 dissolves and reacts with water forming carbonate
and bicarbonate ions (Zeebe and Wolf-Gladrow, 2001). This ion production in turn,
lowers the pH of the ocean, a process called acidification. Over the past decade the
interest in the potential effects of ocean acidification, also referred to as “the other CO2
problem” (Henderson, 2006; Turley, 2005), has been growing rapidly. The first CO2
problem refers to the accumulation of anthropogenic CO2 in the atmosphere, generating
climate changes by increasing the natural greenhouse effect.
Ocean acidification events have occurred on several occasions throughout the earth’s
history as a consequence of perturbations of the carbon cycle of different origins, rates
and sizes. For the past 800 000 years the concentration of CO2 in the atmosphere has
been in the range of 172-300 parts per million by volume (ppmv) (Loulergue et al., 2008).
During the industrial era the concentration exponentially increased to reach 384 ppmv
in 2007 (Solomon et al., 2007) whoile future levels may reach 1071 ppmv in the year 2100
(Plattner et al.). Huge amounts of CO2 are exchanged between the atmosphere and the
ocean and an estimate indicates that about 25% of what has been emitted by human
activity since 1800, has been absorbed by the surface water of the oceans (Sabine et al.,
2004).
O
1.1
Ocean Acidification
1.1.1
Carbonate Chemistry
When CO2 dissolves in seawater it changes the chemistry of the water by increasing the
concentration of bicarbonate ions ([HCO–3 ]) and total dissolved inorganic carbon (CT ).
This, over time, generates a reduction in the mean surface-ocean pH, a process referred
1
1.1. OCEAN ACIDIFICATION
CHAPTER 1. INTRODUCTION
to as ocean acidification. Acidification in this case does not mean that the surface waters
are becoming acidic which would imply a pH of below 7.0 (neutral). The reported average
pH-decline lies between 0.1-0.2 units from the preindustrial level (Orr et al., 2005) and
is currently around 8.1. Global-scale modeling predicts a further decrease of up to 0.35
units reaching 7.8 by the end of this century (Caldeira and Wickett, 2005).
Four different inorganic forms of carbon dioxide exist in the ocean. Free/aqueous
2–
carbon dioxide (CO2 (aq)), bicarbonate (HCO–1
3 ), carbonate ion (CO3 ) plus a small
amount (<0.3%) of true carbonic acid (H2 CO3 ), the sum of which is called total dissolved inorganic carbon, denoted by DIC. In typical seawater conditions dissolved carbon
dioxide is present in small amounts, while the dominate species are bicarbonate and carbonate ions. The electrically neutral carbonic acid and aqueous carbon dioxide are not
chemically separable and therefore they are denoted H2 CO*3 in the following equilibrium reactions, where brackets represent total stoichiometric concentrations (Zeebe and
Wolf-Gladrow, 2001).
CO2 (g) ←→ CO2 (aq)
(1.1)
The concentration of CO2 is given by Henry’s law.
CO2 (g) + H2 O ←→ H2 CO∗3 (aq)
(1.2)
K0 −[H2 CO∗3 ]/f (CO2 )
H2 CO∗3 (aq) ←→ H+ (aq) + HCO−
3 (aq)
(1.3)
+
∗
K1 −[HCO−
3 ][H ]/[H2 CO3 ]
2−
+
HCO−
3 (aq) ←→ H (aq) + CO3 (aq)
(1.4)
+
−
K2 −[CO2−
3 ][H ]/[HCO3 ]
The electrically neutral carbonic acid and aqueous carbon dioxide are not chemically
separable and therefore denoted [H2 CO∗3 ]. Where:
[H2 CO∗3 ]−[CO2 ] + [H2 CO3 ]
K0 is the solubility coefficient of CO2 in seawater while K1 and K2 are the first
and second dissociation constants of carbonic acid, respectively and are influenced by
pressure, temperature and salinity. [H+ ] refers to the hydrogen ion concentration but
represents hydrate complexes like H3 O+ , since free hydrogen ions exist in insignificant
concentrations in aqueous solutions. The concentration of the total alkalinity (At ) is a
–
measure of how much CO2 has reacted with seawater to form CO2–
3 and HCO3 . The
higher the At concentration the more complete is the reaction.
It is important to note that it is not the pH that controls the relative proportions
of the carbonate species in seawater but rather, that the carbonate system is a natural
buffer of ocean pH. This buffer capacity is however, not infinite and will eventually
decrease with increasing levels of atmospheric CO2 .
2
1.2. PRIMARY PRODUCTION
1.1.2
CHAPTER 1. INTRODUCTION
Carbon Cycle
The marine carbon cycle is driven by two independent gradient makers or “pumps”. The
solubility pump (Volk and Hoffert, 1985) and the biological carbon pump, which in turn
can be divided into the, so called, carbonate pump and the soft tissue pump.
The solubility pump refers to a downward transport of CO2 -enriched water and is
connected to the large scale ocean circulation. As is common for most gases, the solubility
of carbon dioxide increases with decreasing temperature. Cold CO2 -rich waters formed
at high latitudes become deep water while flowing towards lower latitudes creating a
surface-to-depth gradient of CT simultaneously increasing stratification. The soft tissue
pump is related to the photosynthetic fixation of carbon dioxide in the surface ocean and
seems to on one hand, reinforce the carbonate pump by contributing to the CT gradient,
while on the other it counteracts it in terms of the CO2 exchange between atmosphere
and ocean (Heinze et al., 1991).
1.2
Primary Production
All ecosystems require an input of energy. In the case of most marine ecosystems the
source of energy is sunlight, converted to chemical energy by the process of photosynthesis. Autotrophic microalgae or phytoplankton account for 50% of all photosynthetic
activity on earth (NASA, 2009). By turning dissolved carbon dioxide into organic carbon, phytoplankton form the base of almost all aquatic food webs and are hence called
primary producers. The term phytoplankton refers to all autotrophic marine organisms
in the water column and incorporates protistan eukaryotes and both archaebacterial and
eubacterial prokaryotes. Such wide phylogenetical diversity, implies a large diversity of
photosynthetic apparati amongst phytoplankton, and most likely also, a varying sensitivity to CO2 concentrations. Ribulose-1,5-bisphosphate carboxylase oxygenase (commonly
RuBisCO or RuBp), is the enzyme responsible for the first major step of carbon fixation
and the most abundant protein on earth. Due to its surprisingly low affinity for its
substrate (CO2 ), some phytoplankton have, through the course of evolution, developed
different types of carbon concentrating mechanisms (CCMs), at the chloroplast level
(Badger et al., 1998a; Falkowski and Raven, 2007). Species who lack CCMs are likely to
show higher sensitivity to elevated CO2 levels, a hypothesis tested in this experiment.
1.2.1
14
C Method
Primary production in a water sample can be determined in different ways by measuring
either the uptake of carbon dioxide, the amount of dissolved O2 produced, the amount
of nutrients consumed or the difference in biomass at different times. The 14C method
was first outlined by E. Steeman-Nielsen (Steeman-Nielsen, 1952), further developed
by numerous marine scientists and summarized by Gunni Aertebjerg Nielsen in the
“Guidelines for the Measurement of Phytoplankton Primary Production” (Nielsen and
Bresta, 1984). The principle of the technique is as follows:
3
1.3. KNOWNS AND UNKNOWNS
CHAPTER 1. INTRODUCTION
A radioactive solution of 14C is added to a water sample in the form of
NaH14 CO2 . The water sample is incubated under controlled conditions,
while the tracer is incorporated into organic matter by photosynthesizing algae. After several filtration steps (see Material and Methods) and removing
all remaining inorganic 14C the radioactivity of the sample is measured, allowing determination of both particulate and dissolved organic matter (DOM).
The rate of primary production can be calculated, given that the total content of CO2 in the experimental water is known and that the amount of
added 14CO2 is known (Nielsen and Bresta, 1984).
1.3
1.3.1
Knowns and Unknowns —Past, Present and Future
Climate Proxies
A proxy is a measurement of a physical quantity that is used as an indicator of the value
of another, which can not be directly measured. Climate proxies are preserved physical
characteristics that enable scientists to reconstruct climatic conditions that prevailed
on earth before record keeping began (1880s). Past temperatures for example can be
determined by analyzing the isotopic composition of water molecules in ice core samples
(eg. European Greenland Ice Core Drilling Project, 1989-1992). The geological record
indisputably provides valuable information about how terrestrial and marine systems
responded to massive and rapid carbon input in the past, but what can they say, if
anything, about the future?
Towards the end of the Permian, 251 million years (Myr) ago, at the PalaeoceneEocene Thermal Maximum (PETM, 55 Myr ago) and during the deglaciations (that
started about 1.8 Myr and ended 10 kyr ago) the pH of the ocean was lower than today
(Zachos, 2005). What these events, referred to as “ocean acidification events”, have in
common is that they were followed by global warming, stronger stratification of the
water column and decreased deep-sea oxygenation. It would be extremely challenging
to forecast the timing and magnitude of the responses since they are often nonlinear.
There are considerable differences though, between all such events- including the one
earth is currently facing, and for an event to qualify as a future analogue, it is important
to consider the relevant timescales involved, as well as the climatic and ocean carbon
chemistry conditions prior to the event (Gattuso and Hansson, 2011).
The estimates of carbon release during the PETM (approx. 1 Pg carbon yr-1) is of
similar proportion as that of the last 50 years due to anthropogenic sources, which is one
of the reasons this event is considered to be one of the closest analogues for assessing
the current and near future human-induced carbon perturbation (Haywood et al., 2011).
Nevertheless, also here, there are important differences between modern conditions and
the carbon cycle boundary conditions before the PETM. A different base climate, ocean
chemistry, continental configuration and not least -absence of continental ice, are all
factors that limit the PETM as the perfect analogue.
There are reasons to expect that the consequences of the anthropogenic ocean acid-
4
1.3. KNOWNS AND UNKNOWNS
CHAPTER 1. INTRODUCTION
ification will be more severe than any recorded so far. Never before has the rate of
change been this high. Furthermore this appears to be the first time that both the pH
and the average saturation state of the ocean seem to be declining at the same time.
During previous acidification events these factors were decoupled. During the PETM the
concentrations of calcium and the total alkalinity of the ocean were higher than today,
resulting in an average saturation state still favourable to calcifiers.
1.3.2
Previous Studies
On the first “Ocean in a High CO2 World” symposium in Paris, May 2004, more than 150
scientists from SCOR (Scientific committee on Oceanic Research), IOC (International
Oceanographic Commision) and IGBP (International Geosphere Biosphere Programme)
came together to exchange and discuss the first clear evidence for the biological impacts of
ocean acidification (OA). The awareness of the potential threats posed by OA to marine
organisms and ecosystems increased throughout the whole marine scientific community.
As did the number of scientists working and publishing in this area, illustrated in figure
(BIOACID p. 5) (Gattuso and Hansson, 2011). The vast majority of these studies
are conducted in laboratories and concern mainly single-species responses, leaving out
synergistic and antagonist effects of multiple stressors, that accompany OA, such as
increased temperature, stratification and light intensity. Studies with a crossed factorial
design should prioritize the factors CO2 and warming since these are inevitably linked by
the greenhouse effect (Sommer, U., BIOACID Phase II proposal, consortium 1, 2012).
Community level studies are rare and little is known about the potential for evolutionary adaptation of marine organisms to OA. Some modeling results suggest that
adaptive evolution might be prevented due to diversity at the species level (De Mazancourt et al. 2008) but there is no empirical data so far. There is an increasingly obvious
need for appropriately scaled field studies (Carpenter, 1996).
1.3.3
Why Mesocosms?
Most modeling studies have used global ocean models as opposed to regional models, although socio-economic consequences of OA are highly region specific (Cooley and Doney,
2009). Furthermore different regional ecosystems might also have specific features such
as presence/absence of toxic dinoflagellates or calcifying plankton, a factor that must be
taken into account when predicting potential community responses to high CO2 . Coastal
(eutrophic waters) and oceanic (oligotrophic waters) phytoplankton are expected to react
differently to OA. Therefore, the BIOACID (Biological Impacts of Ocean Acidification)
community, proposed a series of mesocosm experiments to be conducted in three different
ecosystems. The subtropical North Atlantic Ocean near Cape Verde, The Baltic Sea and
the North Sea (eg. Gullmar fjord). One of the goals was to assess how species-specific
CO2 sensitivities translate to the ecosystem level and the factors responsible for such
species-specific differences. The Kiel Offshore Mesocosms for Future Ocean Simulation
(KOSMOS, see section 2.1.1) with volumes of up to 80 m3 are deployed in situ, allowing
an ecosystem oriented approach.
5
1.4. LOCATION – GULLMAR FJORD
1.4
CHAPTER 1. INTRODUCTION
Location – Gullmar Fjord
The word “Gullmarn” is an old Scandinavian word, meaning “Gods sea” (Hellqvist,
1980). The Gullmar Fjord is located on the west coast of Sweden (58°150 N, 11°250 E)
and represents the coastal, eutrophic North Sea ecosystem in the series of mesocosm
studies. The main fjord is 25 km long and with it´s two branches, “Färlev-fjord” and
“Saltkälle-fjord” it reaches 35 km. It is between 1-3 km wide with a maximum depth
of 118,5 m. Marine research has been performed in the near by Sven Loven Center
for Marine Sciences in Kristineberg for over a 100 years. Typical spring blooms in the
fjord consist of diatoms (e.g. Skeletonema sp.), while the summer blooms can comprise
harmful algal blooms (HAB) species e.g. Gyrodinium sp. and large dinoflagellates like
Ceratium sp. (Saravanan and Godhe, 2010; Lindahl et al., 2009).
1.5
Aim
The purpose of this particular experiment was to study the effect of ocean acidification on the phytoplankton community in the Gullmar Fjord, reflected on carbon-uptake
effectiveness. The hypothesis was that a higher pCO2 would enhance photosynthesis
and carbon fixation, causing a stronger build-up of biomass and a faster reduction in
nutrients. For five months samples were taken from ten mesocosms and the fjord outside Kristineberg. Primary production rates were calculated by measuring contents of
dissolved and particulate organic carbon and further correlated with chlorophyll a concentration.
6
2
Material and Methods
2.1
Experimental Design
Figure 2.1: Kiel Off-Shore Mesocosm for future Ocean Simulations (KOSMOS).
7
2.1. EXPERIMENTAL DESIGN
2.1.1
CHAPTER 2. MATERIAL AND METHODS
KOSMOS
In order to enable pelagic manipulation experiments, Ulf Riebesell and his colleagues
from GEOMAR Helmholtz Centre for Ocean Research in Kiel (Germany), created an
innovative experiment environment. A giant test tube called the ‘Kiel Off-Shore Mesocosm for future Ocean Simulations’ (KOSMOS) for simplicity referred to as “mesocosm”.
The idea was to create a hybrid between a controlled laboratory environment and a natural one, by enclosing a natural water column in a floating, transparent, plastic cylinder.
A KOSMOS (fig.2.1) consists of two main components, a floating device and a cylindrical, thermoplastic polyurethane sac. The floating device is approximately 8 m high
and built up of six fiberglass pylons connected by a supportive, steal construction which
is stabilized vertically in the water by weights hanging off its base. The plastic tube is
attached in the center of the floating device. In this experiment each sac measured 2 m in
diameter and had a volume of 55 m3 ! To prevent addition of nutrients to the system, by
straying birds, a transparent roof was rigged on top of each mesocosm. In order to study
sedimentation of organic matter, a sediment trap—a 2 m funnel made out of the same
material as the bag, was installed above the bottom plate. Ten KOSMOS mesocosms
were transported from Kiel by the German research vessel ALKOR and deployed in the
Gullmar Fjord, west Sweden, outside the Sven Lovén center for Marine Sciences.
2.1.2
CO2 Manipulation
After deploying the sacs into the fjord, they were left open at the top and bottom,
allowing water to pass in through a net, excluding e.g. fish and jellyfish. To make
sure the bags were rinsed from any contaminants and to minimize differences between
the enclosed water masses, the mesocosms were left open for several days. One of the
challenges to be faced was deciding when to close the bags. In a fjord like Gullmar there
is occasional influx of high salinity Atlantic water, which is significantly heavier than
the water normally found on the Swedish west coast. On the first try, the water masses
captured had a salinity of 33.3 psu, which over the next few weeks almost caused the
mesocosms to sink, even though a number of fenders had been installed to increase the
buoyancy. After the final opening and closing of the bags the salinity of the water was
29 psu. In five of the mesocosms the CO2 concentration was manipulated to the levels
predicted in the sea for year 2100, based on IPCC’s 2007 “business as usual scenario” IS
92a ( the target pCO2 value was 900.000 ). This was done by stepwise adding known
volumes of filtered (2 µm), UV-irradiated, CO2 saturated water using a gadget called
the “spider” (fig. 2.2) developed by Jan Czerny (IFM–GEOMAR, Germany). The spider
consists of narrow pipes of various lengths through which liquid can be pumped out. By
lowering and raising the spider inside the mesocosm, the fluid was distributed evenly in
the water column with no need for further mixing. Parameters like temperature, salinity,
chlorophyll a (chl a) and pH were monitored daily throughout the experiment by using
a special probe designed for measuring conductivity, temperature and depth (CTD).
8
2.2. SAMPLING AND ANALYSIS
CHAPTER 2. MATERIAL AND METHODS
Figure 2.2: A sketch (by Ulf Riebesell—GEOMAR, Germany) of the setup used for CO2
manipulation. CO2 -enriched water is pumped from carboys via a garden hose into a dispersion device called “spider” and distributed evenly throughout each mesocosm.
2.1.3
Volume determination
The flexible material of the mesocosm allowed for differences in the total water volumes of
each sac. It was crucial to determine the exact volume of each enclosed water column for
further manipulations, as well as later interpretation of experimental data and calculation
of parameters like sediment export. To do this, first, a sodium chloride solution of known
concentration and volume was uniformly pumped into each mesocosm through the spider
(mentioned previously), causing a tiny change in the salinity of the water. The sensitivity
of the CTD allowed determination of the change in salinity with a precision of 0.2%,
which then could be used to calculate the exact volume of each mesocosm.
2.2
2.2.1
Sampling and Analysis
Sampling
The sampling took place between 9:00-11:00 am every fourth day for five months. The
sampling was conducted with a Hydro-Bios water sampler with a volume of 5 l, equipped
with a motor and a pressure-sensitive plate. By lowering the sampler from the surface
to a depth of 19 m, a depth integrated water sample was obtained. The water was
poured directly from the sampler into glass bottles and brought to shore. The samples
were stored at in situ temperatures in the dark and usually processed within a couple of
hours.
9
2.2. SAMPLING AND ANALYSIS
2.2.2
CHAPTER 2. MATERIAL AND METHODS
Primary productivity
Eleven integrated water-samples, one from each mesocosm and one from the fjord, were
collected in 250 ml Schott-bottles. Prior to treatment all water was carefully filtered
through a 500 µm mesh in order to get rid of copepods and other organisms of similar
size. In earlier experiments of this type (EPOCA Arctic Mesocosm experiment, summer
of 2010), the water was filtered through 200 µm mesh limiting the background signal
and giving a “cleaner” sample. This mesh-size is to be preferred when sampling in
areas where phytoplankton species are predominately solitary (ex. Coscinodiscus sp.).
By examining a number of random water samples from the Gullmarsfjord we found
Skeletonema sp., Thalassiosira sp., Pseudo-Nitzschia sp. amongst other diatoms and it
became clear that the chain-forming portion of the phytoplankton community was too
significant to risk excluding it by picking a too small mesh-size. To prepare the two sets of
incubations (light and dark) water was poured into twenty-two, clean, 40 ml vials. From
each Schott-bottle 40 ml of water was transferred to a corresponding transparent vial of
the light treatment and 40 ml to a black incubation vial covered with aluminum foil. An
extra 40 ml vial was filled with water from the fjord, later used for standardization and
determination of the total spike-addition.
Each vial was spiked with approximately 8 µCi NaH14 CO3 from a pre-diluted stock.
The eleven dark incubations were placed in a box covered with a black cloth and put on
an orbital shaker, to avoid sedimentation of the algae. The eleven light incubations were
placed in a rack on the same orbital shaker, positioned in front of a light source, adjusted
so that the light intensity in the vials corresponded to 50% of the surface values from
the previous sampling day. The light levels had to be adjusted stepwise several times
over the 5 months of the experiment but only when absolutely necessary. The aim was
to keep the parameters constant as long as possible in order to avoid misinterpreting
differences over time as community changes instead of just light acclimation.
The temperature in the incubator was adjusted stepwise so that it was comparable
to the field. After regulating the clock-timer to provide a 16:8 h light-dark phase the
samples were incubated for 24 h (chosen for conventional reasons, see section 4.2). The
incubations were stopped at aproximately the same time.
The following day the incubations were stopped by filtrating the samples over a GF/F
filter. The filtrate for DOC measurements, was collected by placing a 50 ml tube-holder
inside of the filtration cylinders. After removing the filtrate, the vials and the filtration
device were rinsed twice with sterile filtered (<0.2 µm) seawater (SW). The water was
sucked through the filter by turning the pump on and off in intervals avoiding to create
the kind of pressure that would cause the cells to burst. A characteristic transit of
the strained noice of the filtration device to a more airy sound signaled the filter was
dry enough. Each filter was removed with a tweezer and placed flat on the bottom of a
labeled 20 ml scintillation-vial. To remove any inorganic carbon, the filters were acidified
by pipetting 500 µl of 3 M HCl on each, whereafter the vials were left open under a fume
hood to degas for at least 60 minutes. After 60 min, 10 ml scintillation-cocktail (Ultima
Gold AB) was added and vials were closed. Before counted in a Liquid Scintillation
Analyser the samples were thoroughly mixed by vortexing.
10
2.2. SAMPLING AND ANALYSIS
CHAPTER 2. MATERIAL AND METHODS
Dissolved Organic Carbon
Dissolved organic carbon, PPDOC , was determined from the filtrate. After transferring
6 ml of filtrate to scintillation vials each sample was acidified with 1.5 ml HCl (6M) in
order to remove inorganic carbon. The samples were placed under fume hood and left
to degas over two nights. Two days later 10 ml scintillation-cocktail was added and the
vials were closed and counted in a Liquid Scintillation Analyser (Beckmann LC 6500).
2.2.3
Chlorophyll a
The most commonly used proxy of phytoplankton biomass is the chlorophyll a (chl a)
concentration. To determine chlorophyll a concentrations, 500 ml water samples were
collected from all mesocosms and the fjord, every second day throughout the experiment.
The samples were filtered through 25 mm Whatman GF/F filters and stored frozen(-20)
until fluorometrically analyzed with a Turner fluorometer 10-AU (Turner BioSystems,
CA, USA), according to (Welschmeyer, 1994).
2.2.4
Statistical Analysis
Statistical tests and calculations were performed with the software packages Microsoft
Excel for Mac:2011 and R—a language and environment for statistical computing (Ihaka,
1998). The data set was tested for significance with repeated measurement ANOVA.
11
3
Results
3.1
Bloom Development
Changes in chlorophyll a concentration indicated the development of two phytoplankton
blooms peaking on days 31 and 53 respectively (see fig. 3.1). In all mesocosms the first
spring bloom was delayed relative to the fjord by approx. 3 weeks while the blooming
Chlorophyll a !
9,3 Chlorophyll α (µg/L) 8,3 7,3 6,3 Ambient 5,3 4,3 High 3,3 2,3 1,3 0,3 -­‐2 18 38 58 78 day of experiment 98 118 Figure 3.1: Biomass changes of the phytoplankton community as indicated by chlorophyll a
(chl a) concentration, during the full length of the experiment. The red line represent the
five high pCO2 mesocosms and the blue line the five ambient (sampling data collected by
Matthias Fischer).
12
3.2. PRIMARY PRODUCTION OF ORGANIC CARBON CHAPTER 3. RESULTS
18 Primary Production µmol C( l-­‐1 d-­‐1) 16 y = 1,9643x + 0,1279 14 R² = 0,80085 12 y = 1,6541x + 0,495 10 R² = 0,78913 8 6 y = 0,9207x + 2,253 Ambient high Djord R² = 0,22498 4 2 0 0 1 2 3 4 5 6 7 Chlorophyll α (µg/l) Figure 3.2: Correlation of total primary production (PP) and chlorophyll a concentration.
Red symbols represent high pCO2 mesocosms, blue symbols ambient mesocosms and green
symbols the fjord. Trendlines and R2 values follow the same colour code.
patterns seemed to be similar in-between mesocosms. Dominating species in all mesocosms during the first bloom were diatoms (Arcocellulus sp. and Minidiscus sp., 2-8µm)
and no clear difference in chlorophyll content was observed between the high and low
pCO2 treatments. The highest measured chlorophyll a concentrations belonged to the
high pCO2 mesocosms, averaging on 7.6 µg/l for the high pCO2 treatments compared
to 6.1 µg/l for the ambient. The second bloom was also dominated by eukaryotic nanoand picoautotrophs (0.8-2 µm) but here the difference between treatments was more pronounced, indicating that the additional CO2 stimulated the abundance of chlorophyll a
. For the high pCO2 treatments the average chlorophyll a concentration during the 2nd
bloom peak was approx. 5.2 µg/l compared to 3.7 µg/l for the low.
3.2
Primary Production of Organic Carbon
Primary production (PP = PPPOC +PPDOC ) varied between mesocosms and the highest
concentrations were consistently measured in the high pCO2 mesocosms. Seen over the
full length of the experiment, primary production was slightly higher (although not
statistically significant) in the high pCO2 treatment (4.4 µmol C l−1 d−1 ), while the
average concentration in the control mesocosms was very close to that of the fjord (3.7
vs 3.9 C l−1 d−1 respectively), as seen in A.1.
There was a significant correlation between PP and chlorophyll a content (fig. 3.2),
meaning that PPPOC (fig 3.7) as well as PPDOC increased with increasing phytoplankton
biomass. Cumulative PP (fig.3.3) was significantly higher in the high pCO2 treatment
and estimated to 123.8 µmol C l−1 compared to 103.8 µmol C l−1 for the ambient.The
interaction between treatment and time was significant (p<0.002).
13
3.3. PARTICULATE ORGANIC CARBON (POC)
140 Cumulative Primary Production 100 µmol C l-1 d-1
Cumulative PP 120 CHAPTER 3. RESULTS
80 60 Ambient 40 High 20 0 ar ar ar ar ar ar Apr Apr Apr Apr Apr ay ay ay ay ay Jun Jun Jun Jun Jun -­‐Jul
M
M
M
M -­‐
M
M
5
6 12-­‐ 18-­‐ 24-­‐ 30-­‐ 6-­‐M 2-­‐M 8-­‐M 4-­‐M 0-­‐M 5-­‐ 11-­‐ 17-­‐ 23-­‐ 29-­‐
1-­‐ 7-­‐ 13-­‐ 19-­‐ 25-­‐ 31-­‐
1
1
2
3
Figure 3.3: Cumulative primary production (PP) in µmol C l−1 for the high (red line),
ambient (blue line) pCO2 treatment, as determined from 14C sample incubations.
Particulate Organic Carbon (POC)
POC production rate [µmol C l-­‐1 d-­‐1 ] 18 250 POC-­‐productivity 16 200 14 12 High 10 Ambient 8 Fjord 6 Light Light [µE] 3.3
150 100 4 50 2 0 3-­‐M
ar -­‐M
11
ar -­‐M
19
ar -­‐M
27
ar 4-­‐A
pr -­‐A
12
pr -­‐A
20
pr -­‐A
28
pr 6-­‐M
ay -­‐M
14
ay -­‐M
22
ay -­‐M
30
ay n n un
-­‐Ju
-­‐Ju
7-­‐J
15
23
ul 1-­‐J
ul 9-­‐J
0 Figure 3.4: Primary POC production (PPPOC ) rates of the high (red line), ambient (blue
line) pCO2 treatment and the fjord (black line). The light intensity was stepwise adjusted
to fjord-levels (yellow line).
Primary POC productivity is shown in 3.4. During the first and last weeks of the experiment POC production rates were constant and of similar magnitude in both ambient
and high pCO2 treatments. Two major peaks are distinguished on day 32 and between
day 55 and 60 for all mesocosms, assumed to coincide with the bloom phases. At the
14
3.4. DISSOLVED ORGANIC CARBON (DOC)
CHAPTER 3. RESULTS
peak of each bloom phase the average POC productivity rates tended to be higher (no
statistical significans) in the high pCO2 mesocosms than in the ambient. The highest
rates measured during the first bloom of the high CO2 treatments averaged on 15.9 µmol
C l−1 d−1 compared to 12,2 µmol C l−1 d−1 for the ambient, although the difference
was most pronounced during the second bloom, where the high CO2 treatments reached
an average of 11.1 µmol C l−1 d−1 , as opposed to 6.9 µmol C l−1 d−1 in the ambient.
The fjord did not follow the same bloom pattern as the mesocosms and had an earlier
springbloom (peaked 20 days prior to the mesocosm-blooms).
250 POC normalized to Chl a 50 High 200 Ambient 40 Fjord Light [µE] µg C Chl a -1 d-1
POC production rate
60 150 Light 30 100 20 50 10 0 0 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 r-­‐1 ar-­‐1 ar-­‐1 ar-­‐1 pr-­‐1 pr-­‐1 pr-­‐1 pr-­‐1 ay-­‐1 ay-­‐1 ay-­‐1 ay-­‐1 Jun-­‐1 Jun-­‐1 Jun-­‐1 Jul-­‐1 Jul-­‐1
a
-­‐
-­‐
-­‐
-­‐
1
9
7-­‐
4-­‐A 12-­‐A 20-­‐A 28-­‐A
3-­‐M 11-­‐M 19-­‐M 27-­‐M
6-­‐M 14-­‐M 22-­‐M 30-­‐M
15
23
Figure 3.5: Primary POC productivity (PPPOC ) normalized to chlorophyll a concentrations of the high (red line), ambient (blue line) pCO2 treatment and the fjord (black line).
The light intensity was stepwise adjusted to fjord-levels (yellow line)
When normalized to chlorophyll α production (3.5) the difference between the treatments is a lot less pronounced with exception of the second bloom phase (day 55-60),
where the highest productivity rates were measured in the high CO2 treatments.
Cumulative POC production (fig.3.6a) between experiment day 1 and 109 was significantly higher (p<0.05) for the high pCO2 treatment. Maximum difference in cumulative
production was observed on the 11th of april and 1st of May (fig.3.6b) which correlate
with the POC production peaks (fig.3.4), and estimated to 112.4 µmol C l−1 compared
to 92.4 µmol C l−1 for the ambient and 96.6 µmol C l−1 for the fjord.
3.4
Dissolved Organic Carbon (DOC)
Primary DOC productivity of the high pCO2 treatment (red line), ambient (blue line)
and fjord (black line) water is shown in fig. 3.8. Three major peaks were distinguished
for each mesocosm. The first on 11th of April (day 33), 5th of May (day 57) and between
15
3.4. DISSOLVED ORGANIC CARBON (DOC)
140 Cumulative Primary Production 120 100 µmol C( l-1 d-1)
Cumulative PP CHAPTER 3. RESULTS
80 60 Ambient 40 High 20 0 1-­‐
M
ar
ar ar ar ar ar Apr Apr Apr Apr Apr ay ay ay ay ay Jun Jun Jun Jun Jun -­‐Jul
M
M
M
M -­‐
M
5
6 12-­‐ 18-­‐ 24-­‐ 30-­‐ 6-­‐M 2-­‐M 8-­‐M 4-­‐M 0-­‐M 5-­‐ 11-­‐ 17-­‐ 23-­‐ 29-­‐
7-­‐ 13-­‐ 19-­‐ 25-­‐ 31-­‐
1
1
2
3
POC High / POC Ambient (a) Cumulative primary POC production (PPPOC ).
Difference in POC productivity between treatments 1,6 1,4 1,2 1 0,8 r r ar
ar
ar
ar
ar
ar
pr
pr
pr
pr
pr
ay
ay
ay
ay
ay
ay
ay
ay
Ap
Ap
-­‐A
-­‐A
-­‐A
-­‐A
-­‐A
M
M
M
-­‐M 4-­‐M 8-­‐M 2-­‐M 6-­‐M 0-­‐M
-­‐M 7-­‐M 1-­‐M 5-­‐M 9-­‐M
3-­‐
7-­‐
1-­‐
5-­‐
9-­‐
3
11
15
19
23
27
10
1
1
2
2
3
1
1
2
2
2
(b) POC-ratio between high and ambient pCO2 treatments.
Figure 3.6: Shown in (a) is the cumulative primary POC production in µmol C l−1 for
the high (red line), ambient (blue line) pCO2 treatment, as determined from 14C sample
incubations. In fig. (b) the maximum difference (red markers) in cumulative POC production, is presented as a ratio between the POC productions of the high pCO2 vs the ambient
treatment.
16
3.4. DISSOLVED ORGANIC CARBON (DOC)
CHAPTER 3. RESULTS
8 POC production rate µmol C( l-­‐1 d-­‐1) R² = 0,74532 7 R² = 0,70528 6 5 Low CO2 High CO2 4 Fjord 3 Linear (Low CO2) Linear (High CO2) 2 1 0 0 2 4 6 8 10 12 14 16 18 Chlorophyll α (µg/l) Figure 3.7: Correlation of particulate organic carbon productivity (PPPOC ) and chlorophyll a concentration. Red symbols represent high pCO2 mesocosms, blue symbols ambient
mesocosms and green symbols the fjord. Trendlines and R2 values follow the same colour
code.
the 14th (day 97) and 22nd (day 95) of June. The lowest and highest DOC productivity
rates were measured on the same days for both treatments. There appeared to be no
significant differences in DOC productivity between high and ambient pCO2 mesocosms.
In contrast to POC, the DOC productivity pattern of the fjord was comparable to the
mesocosms with highest measured rates on the 5th of May and the 14th of June. When
1,4 High 1 0,8 Ambient 250 200 Fjord 150 Light 0,6 100 0,4 Light [µE] DOC production rate µmol C l-­‐1 d-­‐1 1,2 DOC productivity 50 0,2 0 0 ar ar ar ar ar ar pr pr pr pr pr ay ay ay ay ay Jun Jun Jun Jun Jun 5-­‐Jul 1-­‐M 7-­‐M 13-­‐M 19-­‐M 25-­‐M 31-­‐M 6-­‐A 12-­‐A 18-­‐A 24-­‐A 30-­‐A 6-­‐M 12-­‐M 18-­‐M 24-­‐M 30-­‐M 5-­‐ 11-­‐ 17-­‐ 23-­‐ 29-­‐
Figure 3.8: Primary DOC production (PPDOC ) rates of the high pCO2 treatment (red
line), ambient (blue line) and fjord (black line) water. The light intensity was stepwise
adjusted to fjord levels (yellow line).
normalized to chlorophyll α production (fig. 4) the difference between the treatments is
17
3.4. DISSOLVED ORGANIC CARBON (DOC)
DOC normalized to Chl a High Ambient 12 Fjord 10 Light 250 200 150 8 100 6 4 Light [µE] 14 µg C Chl a -­‐1 d-­‐1 DOC production rate 16 CHAPTER 3. RESULTS
50 2 0 1-­‐
M
a
7-­‐ r M
13 ar -­‐M
19 ar -­‐M
25 ar -­‐M
31 ar -­‐M
ar
6-­‐ Ap
12 r -­‐A
p
18 r -­‐A
p
24 r -­‐A
p
30 r -­‐A
p
6-­‐ r M
12 ay -­‐M
18 ay -­‐M
24 ay -­‐M
30 ay -­‐M
ay
5-­‐ Ju
11 n -­‐Ju
17 n -­‐Ju
23 n -­‐Ju
29 n -­‐Ju
n 5-­‐
Ju
l 0 Figure 3.9: Primary DOC productivity (PPDOC ) normalized to chlorophyll a concentrations of the high (red line), ambient (blue line) pCO2 treatment and the fjord (black line).
The light intensity was stepwise adjusted to fjord-levels (yellow line).
a lot less pronounced with exception of the second bloom phase (day 55-60), where the
highest productivity rates were measured in the high pCO2 treatments.
18
4
Discussion
4.1
Interpretation of Results
The only statistically significant effect observed, is a higher cumulative primary production (PP) at increased CO2 concentrations. This outcome accords well with our
expectations as well as the results of previous mesocosm studies (Engel et al., 2012;
Egge et al., 2009) and laboratory experiments (Rost et al., 2008). It has been confirmed
that there is a Michaelis-Menten (rectangular hyperbolic) type relationship between the
rate of carbon-specific growth and the extracellular DIC concentration as first described
by (Clark and Flynn, 2000).
It is important to keep in mind that the dataset collected in this experiment was based
on incubated samples, which represent newly fixed carbon, and are therefore limited as
representatives of the mesocosms they were taken from. Activities like cell-lysis inside
the mesocosms result in the real DOC levels being higher than those indicated from
extrapolating the values obtained from the incubations. What was measured through
the incubations is a production potential. Another fact affecting the interpretation of
this data is that during the first half of the experiment the water inside the mesocosms
was homogenous and circulating, leading to each plankton cell spending at least part
of the day in the upper photic zone. On April 15 stratification occurred and lasted
throughout the second half of the experiment, leading to a higher primary production
in the upper part of each mesocosm. This indicates that an integrated sample from the
second period contained different plankton-communities that were more and less adapted
to light.
The phytoplankton spring bloom inside the mesocosms was delayed relative to the
fjord. This could be due to light limitations caused by the polyurethane bags. In light
transparency measurements the PVC roof revealed 80% light transparency below 400 nm
wavelength and the TPU foil 100% absorbance of UV light (Riebesell et al., 2013). The
generally different bloom pattern of the fjord could also be attributed to stratification and
19
4.1. INTERPRETATION OF RESULTS
CHAPTER 4. DISCUSSION
a suspected stronger grazing pressure inside the mesocosms. It is remarkable however,
how similar to each other the bloom patterns of the mesocosms were, even several months
after the water masses were isolated from each other. This fact definitely adds to the
strengths of the experiment. One of the concerns expressed by “mesocosm-sceptics” is
that isolated water masses are likely to behave completely different from each other and
may therefore not be comparable over time.
The experiment was designed to measure primary production rates and their variation in-between treatments. To further process the results, they had to be normalized
to either biomass (organic carbon content), volume or, as was our choice, chlorophyll a
content. Chlorophyll/cell ratio is not a constant though, and is affected by light, cellsize, species, nitrogen availability etc. Whether it is affected by high CO2 concentrations
has yet to be established. Studies on the diatom Thalassiosira pseudonana revealed that
elevated CO2 concentrations caused reduction of chlorophyll content, carbon fixation
per chlorophyll and growth rates (Sobrino et al., 2008). Phytoplankton cells of different
species can differ in chlorophyll content meaning that an increase of chlorophyll concentration can be attributed either to a higher number of phytoplankton cells or an
increased chlorophyll-to-carbon ratio within the cells. The decision to use chlorophyll a
concentration as a proxy for biomass was based on the assumption that the variability
of this ratio can be successfully corrected for and usefully interpreted (Cullen, 1982).
The chlorophyll a levels did not differ significantly between the treatments at any
time during the experiment and the peaks correlated closely with those of POC and DOC
in terms of timing. Upon analyzing the POC and DOC rates we could not prove any
statistically significant differences between the two treatments, although previous experiments showed significantly higher DOC levels in high CO2 treatments. However, there
was a clear tendency for higher primary production rates in the high-CO2 mesocosms.
These tendencies have been attributed to the higher biomass present at the time rather
than an improved photosynthesizing capacity of the plankton cells. This conclusion is
supported by the lack of this tendency when the POC curves where normalized to chlorophyll (fig. 3.5). In other words, if a difference in primary production between treatments
could not be attributed to a difference in biomass, this would suggest a difference in the
photosynthetic efficiency of the plankton communities.
An unexpected observation was that during the first bloom period, the DOC productivity peak appears prior to the POC productivity peak, see fig. 3.8 and 3.4. No
satisfactory reason for this has yet been proposed.Normally a build-up of POC is followed
by a breakdown of POC translated into increasing levels of DOC. It is also notable that
the DOC contribution to the PP was very small (note scale difference in fig. A.1 and A.2)
during the whole course of the experiment. In the Svalbard experiment the DOC productivity was estimated to between 3-4% of the POC productivity (Engel et al., 2012).
In the Bergen experiment in Norway the net growth rate and the PIC:POC production of the coccolithophore Emiliania huxleyi decreased at 410 ppm and 710 ppm CO2
compared with 190 ppm (Engel et al., 2005), while primary production was unaffected
(Delille et al., 2005).
During the last weeks of the experiment, Synechococcus sp. was an important con-
20
4.2. METHOD EVALUATION
CHAPTER 4. DISCUSSION
tributor to primary production. This picoautotroph can occur in sizes smaller than the
pore size of the GF/F filters used during filtration (<0.8µm) resulting in part of the
POC fraction ending up in the filtrate. This gives a distorted DOC depiction and can
explain the large DOC peak seen in 3.9 towards the end of June.
It is possible that an overall statistically insignificant effect on the general phytoplankton carbon-uptake efficiency might turn out to be significant on a community level
(negative growth of one community + positive growth of another = No overall effect).
Experimental evidence supports that marine eukaryotic (Beardall and Morris, 1975; Zenvirth and Kaplan, 1981) and prokaryotic (Badger and Andrews, 1982) phytoplankton
utilizes inorganic carbon concentrating mechanisms (CCMs) to facilitate photosynthesis,
necessitated by the inefficiency of RubisCO (as mentioned in the introduction). There
has been an inconsistency of results during various field experiments, where in some cases
there was a significant stimulation of primary production when the CO2 (aq) concentration was increased, while others showed no response (Hein and Sand-Jensen, 1997; Tortell
et al., 1997), leading to the proposal that some phytoplankton species might be limited
by CO2 (Reinfelder, 2011) despite the currently rising concentration. A somewhat surprising suggestion, considering the millimolar concentration of CO2 , compared to the
nanomolar concentration of nitrogen and phosphorus or the picomolar concentrations
of micronutrients (Fe, Zn, Mg etc) in the surface ocean (Reinfelder, 2011). Elaborate
studies, conducted the last decade, have showed that marine diatoms and certain populations of the genus Phaeocystis are capable of direct or indirect HCO–3 uptake (Tortell
et al., 2002; Tortell and Morel, 2002; Cassar et al., 2004; Martin and Tortell, 2006), leading to the conclusion that these species are not limited by carbon (Goldman, 1999). In
contrast, coccolithophores (Sekino et al., 1996; Riebesell et al., 2000; Rost et al., 2003)
and dinoflagellates may be undersaturated with respect to CO2 in surface waters (Ratti
et al., 2007; Riebesell et al., 2007).
4.2
Method Evaluation
In this experiment the CO2 concentration of the mesocosms were regulated by adding
known amounts of CO2 -saturated solutions. There exist various experimental manipulation methods of the carbonate system and the best approach depends on the experimental design of the study (scale, required sensitivity, oceanographic settings in field
experiments etc). The two fundamental approaches consist of either changing dissolved
organic carbon (DIC) concentration while keeping the total alkalinity (TA) constant or
by changing the TA at constant DIC. Moreover, depending on the aim of the study, one
can either decrease or increase the DIC at constant TA by bubbling seawater with air
or injecting CO2 enriched seawater at target CO2 levels. Each method has advantages
and disadvantages that must be taken into consideration when interpreting the results.
As an example, in pH manipulation experiments, the growth rate of Emiliana huxleyi
increased with increasing CO2 , whereas bubbling resulted in slightly lower growth rates
at high CO2 than did acidification (Shi et al., 2009). Adding saturated CO2 solutions
has shown to be ideal when dealing with large water volumes, even though the precise
21
4.2. METHOD EVALUATION
CHAPTER 4. DISCUSSION
adjustment of the carbonate chemistry can be difficult (Schulz et al., 2009). One liter
of CO2 enriched seawater per cubic meter is estimated to reduce pH by about 0.2 units.
(For a detailed description of the experimental methods as well as the advantages and
disadvantages of each see Egge et al. (2009); Shi et al. (2009); Schulz et al. (2009)).
Evaluation procedures for the determination of the most suitable method are required
for every stage of an experiment. For measuring phytoplankton carbon uptake, the
14C-tracer method was considered the best approach because of it’s high sensitivity.
As a drawback though, there was no way of directly estimating respiration during the
normal incubation procedures. Meaning that the resulting data will always be implying
a positive carbon uptake, even if the carbon content of the cell is declining (SteemanNielsen, 1952). A sensitive method like this is usually also sensitive to mistakes, making
the handling of the samples very challenging. Exposure of a sample to light may cause
photoinhibition of a cell adapted to low light within minutes, while contact with materials
like plastic hoses, iron, plywood and Nyoprene will result in decreased 14-C carbon
uptake (Doty and Oguri, 1959). Filtration of the samples holds another set of challenges
since it has to be done directly after the end of the incubation period. If the filtration
pressure is not kept low enough there is a risk of damaging the cells, which would lead
to misinterpretation of the DOC value, since the contents will be flushed through the
filter and into the filtrate. On the other hand, a pressure not strong enough might cause
retention of water in the filter pores, which in turn might lead to an overestimation of
the POC content (Peterson, 1980).
The length of the incubations, 24 hours (16h light and 8h dark), was chosen for
conventional purposes and aimed to give results comparable with the rest of the series of
mesocosm experiments conducted in higher latitudes. The disadvantage lies in that the
PP rates determined do not represent neither the gross nor the net primary production,
but something in between (Peterson, 1980). Long incubations tend to measure net
photosynthesis, while short incubations provide a gross rate of carbon fixation. The
values for carbon uptake in the dark incubations can either be subtracted from those
obtained from the light incubations, recorded separately or omitted, depending on the
focus of the study (Peterson, 1980). In this case we prioritized the light-uptake of carbon
and therefore the dark-incubation-data is not presented in this paper.
It is almost impossible to separate microzooplankton from phytoplankton, and it can
be hard enough to exclude larger net zooplankton from the sample bottles. During the
experiment, all samples were filtered through a 500 µm mesh in order to avoid larger
zooplankton, the presence of which could seriously interfere with the carbon profile.
There are however several species of chain-forming algae that might have been excluded,
because of this. It is therefore possible that an important part of the phytoplankton
community was not accounted for in this experiment. A way to compensate for this
error would have been to get frequent estimates of the relative abundances of chain
forming algae by analyzing integrated samples beforehand. Lack of time and manpower
did not make this possible for our team but is recommended in future experiments.
22
4.3. FUTURE OUTLOOK
4.3
CHAPTER 4. DISCUSSION
Future Outlook
Overall, we observed higher cumulative PP rate in mesocosms with increased CO2 levels.
It is difficult to conclude whether the lack of statistical significance observed in this
experiment is due to absence of an effect, lack of precision during measurement or, as
stated previously, low resolution (positive and negative trends of specific species could
add up to an overall undetectable effect). It is important that the weaknesses of methods
and experimental designs are exposed and that improvements are integrated into new,
more reliable standard protocols. Which is why this paper focuses more on highlighting
the areas of the experiment that need improvement and less praising its virtues. This
is however truly a unique experiment in terms of scale, duration, complexity, design
and equipment. The mesocosms hold a great deal of potential of getting answers that
could help unravel the complexity of marine ecosystems and what affects them. These
are the kind of answers that would enable us to make reliable predictions and affect
policy-makers.
As progress is being made and experience gained, future experiments should shift
increasingly towards the direction of examining the interactive effects of multiple environmental factors. Gradually scientists must move from description to actual underlying
mechanisms. I believe that the natural next step in the ocean acidification study is to
find ways to examine the adaptation potential of marine organisms, as opposed to acclimation that primarily is the focus of today.
23
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30
A
Appendix
31
A.1. TABLE OF PRIMARY PRODUCTION
A.1
APPENDIX A. APPENDIX
Table of Primary Production
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Table A.1: Compilation of primary POC production (PPPOC ), primary DOC production
(PPDOC ) and total primary production (PP = PPPOC + PPDOC ) rates ( µmol C l−1 d−1 ),
based on 14C sample incubations. The maximum values are highlighted in yellow to facilitate comparison between high pCO2 (High) and ambient (Ambient) treatments. Time
averaged (day1-109) production rates are found on the last row, where the highest PP value
is highlighted in green.
32
A.2. GRAPH OF HIGH CO2 TREATMENT
A.2
APPENDIX A. APPENDIX
Graph of POC and DOC of High CO2 Treatment
Figure A.1: Primary POC (dark red line) & DOC (light red line) production rates of the
high CO2 treatment during the full length of the experiment.
33
A.3. GRAPH OF LOW CO2 TREATMENT
A.3
APPENDIX A. APPENDIX
Graph of POC and DOC of Low CO2 Treatment
Figure A.2: Primary POC (dark blue line) & DOC (light blue line) production rates of
the low CO2 treatment during the full length of the experiment.
34