Mémoire Final

Faculté d’Ingénierie biologique, agronomique et environnementale
Année académique 2012-2013
Effects of Fluctuating pH on the
Development of the Green Sea urchin
Strongylocentrotus droebachiensis
Presented by Astrid Peeters
Promoteurs : Prof. Philippe Baret
(Earth and Life Institute, Catholic University of Louvain)
Sam Dupont
(Kristineberg Marine Research Centre, University of Gothenburg)
Lecteurs : Prof. Cathy Debier
(Earth and Life Institute, Institut des Sciences de la Vie,
Catholic University of Louvain)
Dr. Ana Catarino
(Laboratory for Marine Biology, Université Libre de Bruxelles)
Mémoire de fin d’études présenté en vue de l’obtention
du diplôme de Bioingénieur : Sciences Agronomiques

I
Acknowledgements
First, I thank Samuel Dupont for the warm welcome at the Kristineberg research center and for his
support, guidance and humor throughout this master thesis project.
I particularly acknowledge Philippe Baret for giving me the opportunity to work in this
fascinating field, as well as for his availability and valued advice.
I would also like to thank Jenny Ojhage, Susanne Baden and Marita Nyberg for kindly and
efficiently organizing my stay in Kristineberg.
Special thanks to the ladies from “Sam’s Team”:
Isabel Casties, for guiding me through the experiments, from the very beginning up until the
“monsters/parasites” investigation;
Narimane Dorey for helping me to make my first steps with R; and
Laura Reverter for being my daily companion, from the early mornings to the late night bucket
fillings.
Thanks for the great atmosphere!
My thanks also go to the Kosmos team and the whole Kristineberg crew for the fascinating, cosy,
crazy, and delicious moments spent together in the Kristineberg research center.
Finally, I thank my parents for their continuous support; not only during this master thesis, but
also throughout my studies. I also thank my friends and family, whom I could always count on for
motivation and encouragements during this thrilling adventure.

III
Abstract
Ocean acidification (OA) is an ongoing process which causes a decrease in seawater pH due
to the absorption at an unprecedented rate of atmospheric carbon dioxide (CO2) by the ocean
surface waters. The ocean pH is predicted to fall by approximately 0.4 units by 2100, which will
cause drastic perturbations in the seawater chemistry and in marine ecosystems. Additionally, this
change will add up to the already variable environments experienced by marine organisms; Ocean
Acidification will thus shift naturally fluctuating pH values to lower levels.
The experiment conducted for this master thesis project was designed to determine the
potential effects of OA on a key echinoderm species of marine ecosystems, the green sea urchin
Strongylocentrotus droebachiensis. This species is widely distributed and highly represented in
the oceans around the world. Additionally, S. droebachiensis is easily cultured in the laboratory
and its responses toward OA are well documented.
However, all previous Ocean Acidification studies considered only constant pH levels.
Here, we investigate the impact of short-term (10-12 days) exposure to various pH fluctuation
frequencies and levels on mortality and growth in larvae of the green sea urchin.
In accordance with previous studies, experimental treatments did not affect mortality, but
affected larval developmental dynamics negatively. More surprisingly; only pH levels, but not
fluctuation impacted larval growth rates.
This may be interpreted in various ways; the most noteworthy one is that S. droebachiensis
larvae may be capable of important phenotypic plasticity. More investigation will be needed on
the subject; encountered issues and possible improvements of the protocol are discussed.
Keywords: Ocean Acidification – echinoderms – fluctuating pH –
Strongylocentrotus droebachiensis.

V
Table of content
Acknowledgements....................................................................................................................I
Abstract.................................................................................................................................. III
List of Figures....................................................................................................................... VII
List of Tables............................................................................................................................ X
Part I. General Context ........................................................................................................... 1
Chapter 1. Ocean Acidification (OA) ................................................................................ 1
1.1. The Ocean Acidification process ........................................................................................ 1
1.2. OA and naturally fluctuating pH ....................................................................................... 2
Chapter 2. Strongylocentrotus droebachiensis, a keystone species ................................ 4
2.1. Phylogeny.............................................................................................................................. 5
2.2. Distribution and habitat...................................................................................................... 5
2.3. Life cycle ............................................................................................................................... 6
2.4. Morphological and anatomical description ....................................................................... 7
2.5. Physiological limits............................................................................................................... 8
2.6. Feeding.................................................................................................................................. 9
2.7. Predators............................................................................................................................... 9
2.8. Ecological importance........................................................................................................ 10
2.9. Economical importance..................................................................................................... 11
Chapter 3. Biological impacts of Ocean Acidification (OA), current state of
knowledge .......................................................................................................................... 12
3.1. Impacts of OA are species-specific and life stage-dependent......................................... 12
3.2. Physiological impacts of OA.............................................................................................. 12
3.2.1. Impacts on calcification ................................................................................................................ 13
3.2.2. Homeostasis .................................................................................................................................. 14
3.2.3. Metabolism.................................................................................................................................... 15
3.2.4. Developmental dynamics .............................................................................................................. 15
3.3. OA and Mortality............................................................................................................... 17
3.4. Potential for adaptation and acclimation......................................................................... 17
3.4.1. Phenotypic acclimation/adaptation................................................................................................ 18
3.4.2. Genetic adaptation......................................................................................................................... 19
3.5. Gaps in the knowledge....................................................................................................... 20
Chapter 4. Motivations and aim of the study.................................................................. 21

VI
Part II. Materials, Methods and Data .................................................................................. 23
Chapter 5. Materials and Methods .................................................................................. 23
5.1. Adult and larvae culture.................................................................................................... 24
5.1.1. Adult culture and spawning........................................................................................................... 24
5.1.2. Larvae culture................................................................................................................................ 26
5.2. pH regulation...................................................................................................................... 27
5.3. Seawater carbonate system measurements...................................................................... 29
5.3.1. pH.................................................................................................................................................. 30
5.3.2. Alkalinity measurements............................................................................................................... 32
5.3.3. pCO2 and Ωar.................................................................................................................................. 32
5.3.4. Carbonate system speciation from pH and AT............................................................................... 33
5.4. Biological measurements................................................................................................... 34
5.4.1. Mortality........................................................................................................................................ 34
5.4.2. Body length ................................................................................................................................... 35
5.5. Statistical analyses ............................................................................................................. 36
Chapter 6. Results ............................................................................................................. 37
6.1. Seawater chemistry............................................................................................................ 37
6.2. Mortality............................................................................................................................. 39
6.3. Growth ................................................................................................................................ 42
Part III. Discussion, Perspectives and Conclusion.............................................................. 45
Chapter 7. Discussion and Perspectives .......................................................................... 45
7.1. Mortality............................................................................................................................. 45
7.2. Growth ................................................................................................................................ 46
7.2.1. Within-treatment variability.......................................................................................................... 46
7.2.2. Considerations on acidity and growth ........................................................................................... 47
7.2.3. Potential for pre-adaptation........................................................................................................... 47
7.2.4. Considerations on phenotypic and genetic diversity ..................................................................... 48
7.2.5. Alternative mechanism to ion pumps............................................................................................ 49
Chapter 8. Conclusion and Perspectives ......................................................................... 50
Bibliography ........................................................................................................................... 51
Annex A. Growth results .................................................................................................... 65
Annex B. Mortality results ................................................................................................. 70
Annex C. pH NBS to pH Total conversion........................................................................ 75
Annex D. Feeding ................................................................................................................ 76
Annex E. Seawater chemistry ............................................................................................ 77

VII
List of Figures
Figure 1: The carbonate system (Sabine et al. 2004). ...................................................................... 1
Figure 2 : pH dynamics measured by sensor deployment at 15 locations worldwide in 0–15 m
water depth. All panels are plotted on the same vertical range of pH. The ordinate axis
encompasses a 30-day period during each sensor deployment representative of each site during
the deployment season. From (Hofmann et al. 2011). ..................................................................... 2
Figure 3 : Phylogeny of Strongylocentrotus droebachiensis (Uniprot Consortium 2002)............... 5
Figure 4 : Worldwide distribution of Strongylocentrotus droebachiensis. ...................................... 5
Figure 5 : Life cycle of Strongylocentrotus droebachiensis. From (S. Dupont et al. 2012). ........... 6
Figure 6 : Drawing of a 20-day-old S. droebachiensis. The mouth is at the top of the gut system.
From (Sinervo and McEdward 1988)............................................................................................... 7
Figure 7 : Model of a hypothetical seagrass (e.g. kelp) food web under (a) natural and (b)
anthropogenic-disturbed conditions, showing how disturbances may interact and cause
overgrazing. Grey boxes are different system components, and black boxes represent typical co-
occurring anthropogenic disturbances. Solid arrows indicate direct links, dotted arrows indicate
potential feedback mechanisms. The thickness of boxes and arrows indicate relative importance
for the food web. From (Eklöf et al. 2008)..................................................................................... 10
Figure 8 : A number of physiological processes may be affected directly or indirectly by OA and
thus impair fitness. Adapted from (S. Dupont and Thorndyke 2013)............................................ 13
Figure 9 : Echinopluteus larvae of Tripneustes gratilla reared for 5 days in three pH and two
temperature treatments. Acidification (to pH 7,6) and increased CO2 stunted larval growth,
causing a decrease in length of the arms and the supporting skeletal rods (Sheppard Brennand et
al. 2010).......................................................................................................................................... 13
Figure 10 : Schematic model summarizing the interplay of calcification, pH regulation, and
energetic costs in sea urchin larvae during environmental acidification. PBC= primary body
cavity. pHsw= surrounding seawater pH. pHe= extracellular pH. pHi= intracellular pH. PMC=
Primary mesenchyme cell. ST, stomach; putative transporters are in gray. From (Meike Stumpp et
al. 2012).......................................................................................................................................... 14
Figure 11 : Relationship between S. droebachiensis larval body length growth rates (μm. day-1
)
and mean pHT. From (Dorey, Thorndyke, and Dupont 2013)........................................................ 16
Figure 12 : OA effects on an organism’s life cycle and possibilities of acclimation/adaptation.
From (Sam Dupont and Thorndyke 2008). .................................................................................... 18
Figure 13 : 7-day-old S. droebachiensis larva actively budding at pH 7,7 in our experiment. The
arrow indicates the site of constriction leading to bud formation. ................................................. 18
Figure 14 : Expected trend for S. droebachiensis larvae growth rates in the experimental
treatments. ...................................................................................................................................... 21

VIII
Figure 15 : Experimental pH treatments. ....................................................................................... 23
Figure 16 : Overview of the spawning and fertilization procedure. a) Intracoelomic injection of
KCL (0.5M); b) egg collection in FSW; c) dry sperm collection; d) egg; e) swimming sperm; f)
fertilized egg in fertilization membrane; g) two-cell stage embryo. .............................................. 25
Figure 17 : Overview of the protocol in every culture. The routine protocol and the steps for data
sampling are indicated for each day of the experiment. On day 0 the adults were spawned; the
embryos were transferred in 5L Erlenmeyers (pre-equilibrated at the appropriate pH level for
constant treatments). On day 1, we started pH regulation and daily sampling for mortality and
growth rates. This was continued for the whole duration of the experiment. On days 4, 8 and 11,
the culture water was changed and sampled for AT and pHT measurements. Feeding was started at
day 7 and performed daily until the end of the experiment............................................................ 26
Figure 18 : The CO₂ bubbling system monitored by Aquamedic computers. a) General set-up; b)
set-up in our experiment. (1) CO2-bottle, (2) pressure regulator, (3) valve, (4) connection plug, (5)
pH computer, (6) CO2 bubbling tube, (7) pH probe, (8) culture bottle, (9) wooden airstone........ 28
Figure 19 : Summary of the steps towards speciation of the carbonate system parameters. Green
boxes contain measured parameters; red boxes contain calculated parameters. Numbers on the
arrows indicate the corresponding equations. ................................................................................ 30
Figure 20 : Morphology of a Strongylocentrotus droebachiensis 8days-old 4-arm pluteus larva in
constant pH 8.1 conditions. BL, body length. ................................................................................ 35
Figure 21 : Correlation between pHNBS and pHT............................................................................ 37
Figure 22 : Undesired organisms in our culture bottles. a. Unidentified micro-organism inside a 5-
day old pluteus larva indicated by the black arrows. b. Unidentified micro-organism. c. Copepod.
........................................................................................................................................................ 40
Figure 23 : Gompertz mortality curves for the seven different treatments over all four
experiments. ................................................................................................................................... 41
Figure 24 : Growth rates for every culture. Crashed cultures are indicated in red......................... 42
Figure 25 : Average logarithmic growth curves for the seven different treatments in every
experiment...................................................................................................................................... 43
Figure 26 : Differences in growth rates (i.e. slope of the growth curve) between treatments over all
four experiments. Boxes include the first to third quartiles; boxes are cut by the median value. The
whiskers’ limits mark minimum and maximum values; outliers (i.e. observations with a value
between 1,5 and 3 times the height of the box, counted from the superior or inferior limits) are
indicated by dots............................................................................................................................. 43
Figure 27 : Phenotypic diversity in 8-days old S.droebachiensis pluteus larvae from the 12h
ΔpH=-0.4 treatment in experiment 1.............................................................................................. 48
Figure A.1 : Growth curves for every culture in Experiment 1...................................................... 65

IX
Figure B.1 : Gompertz mortality curves for every culture in experiment 1. No fit was found for
cultures in which no line is drawn.................................................................................................. 70
Figure C.1 : Regression graphs for pH NBS to pH Total conversion for every experiment.......... 75

X
List of Tables
Table 1 : Number of females and males spawned in each experiment. ......................................... 24
Table 2 : Summary of seawater chemistry for all experiments. Mean values +/- standard deviation
and number of observations (n) are indicated for each treatment. pHT= pH total; pCO2=partial
CO2 pressure; Ωar= aragonite saturation state, n=number of observations, At= total alkalinity,
t°=temperature................................................................................................................................ 38
Table 3: Time at maximum density (if not on day 1) for cultures in Experiment 1....................... 39
Table 4 : Days at which experimental cultures crashed. ................................................................ 40
Table 5 : ANOVA results of experimental treatments on mortality parameters in cultures which
had not crashed. A (curve maximum), µ (maximum slope) and λ (lag phase). Mean values +/-
standard deviation and number of observations (n) are indicated for each treatment. Df= degrees
of freedom. ..................................................................................................................................... 41
Table 6: ANOVA results of experimental treatments on growth in cultures which had not crashed.
........................................................................................................................................................ 44
Table A.1 :Growth parameters for every culture, in every experiment. One treatment was
excluded due to budding................................................................................................................. 69
Table B.1 : Gompertz growth parameters for every culture, in every experiment. Absent values
indicate that no fit was found on the data....................................................................................... 74
Table D.1 : Recipe for B1 medium (Guillard and Ryther 1962).................................................... 76
Table E.1 : Seawater chemistry for every culture in every experiment. Mean values +/- standard
deviation and number of observations (n) are indicated for each treatment. XP= Experiments;
pHT= pH total; pCO2=partial CO2 pressure; Ωar= aragonite saturation state, n=number of
observations, AT= total alkalinity, t°=temperature......................................................................... 77
Table E.2 : 0.0019663 mol.kg-1
; the total concentration of boron is 0.0004151 mol.kg-1
. To
calculate the composition at another salinity, [Y]S = [Y]35 x (S/35), where Y refers to species that
are dependent on salinity (e.g. calcium ion concentration or total boron) (A. Dickson, Sabine, and
Christian 2007). The concentrations of the various acid-base species were estimated assuming that
the pH = 8.1 (on the seawater scale), and that the AT = 2300 µmol.kg-1
. The atmospheric CO2
fugacity was chosen as 33.74 Pa = 333µatm, i.e. appropriate for the time period the original
salinity/Conductivity relationship was characterized (Millero et al. 2008). .................................. 78
Table E.3 : Definition of the pH values of the two buffers (TRIS and AMP); with S the salinity,
and T the temperature (in Kelvin) (A. Dickson, Sabine, and Christian 2007):.............................. 78
Table E.4 : Expressions for calculating equilibrium constants (on the total hydrogen ion scale) as a
function of salinity (S) and temperature (T, in Kelvin) (Weiss and Price 1980; A. Dickson, Sabine,
and Christian 2007; Millero 1995). I/m0
= 19.924S/(100 – 1.005S) ≈ 0.02S ; k0
= 1 mol.kg-1
... 79

1
Part I. General Context
Chapter 1. Ocean Acidification (OA)
Ocean acidification (OA) is the ongoing process leading to a decrease in seawater pH. This is
due to the absorption of atmospheric carbon dioxide (CO₂) by surface waters at an unprecedented
rate (Caldeira and Wickett, 2003).
1.1. The Ocean Acidification process
The current rate of CO2 uptake by oceanic surface waters disrupts the carbonate system.
When the atmospheric CO2 diffuses through the ocean’s surface, it forms carbonic acid (H2CO3).
As this is a weak acid, it dissociates to produce hydrogen (H+
) and bicarbonate ions (HCO3
-
).
This hydrogen is susceptible of lowering the water’s pH. Carbonate ions (CO3
--
) from saturated
surface waters react with these hydrogen ions to form more bicarbonate ions.
Figure 1: The carbonate system (Sabine et al., 2004).
Since the industrial revolution, human activities such as increased fossil fuel burning, cement
production and land use changes associated with agricultural activities result in rising atmospheric
CO2 concentrations. Before the industrial period, CO2 emissions were controlled mainly by
geological processes and erosion, which occurred at a much slower rate than the current
anthropogenic CO2 emissions (Kleypas et al., 2006). Atmospheric CO2 levels have risen from 280
to 380 ppm until today and are expected to increase to about 700-1000 ppm by 2100. This rise in
atmospheric CO2 levels is unprecedented throughout earth’s history, and occurs roughly 100 times
faster than over the past 650,000 years (Caldeira and Wickett, 2003; Sabine et al., 2004; Raven et
al., 2005).
This has major consequences on a number of processes (e.g. temperature, sea level, storm
frequency). Additionally, as about a third of this CO2 is being taken up by the oceans, the
buffering system is starting to become overloaded and significant differences in the water’s
chemistry can be observed (Sabine et al., 2004).

2
These levels of atmospheric CO2 generate hypercapnic conditions (elevated levels of
dissolved CO2), which result in a decrease in the average surface ocean pH. This pH had
decreased by 0.1 units compared to the pre-industrial era in 2003, and will further decrease by 0.2
to 0.4 units before 2100 (Caldeira and Wickett, 2003).
1.2. OA and naturally fluctuating pH
pH levels in a given environment may vary considerably. Ocean Acidification will thus also
affect natural pH variability. This is attributable to complex interactions between physical,
chemical and biological processes (i.e. biological activity, temperature, currents, tidal excursions,
background oceanography, riverine inputs (e.g. in estuaries), upwelling). Variations are therefore
highly site-dependent (see Figure 2), with differences in amplitude (e.g. up to nearly 2 units near
hydrothermal vents on northwest Elfuku volcano, Mariana arc (Tunnicliffe et al., 2009); a larger
difference than what is expected for 2100) and frequency of pH variations.
For example, in the Kattegat and the Baltic Sea, seasonally elevated seawater pCO2 levels
(ca. 230ppm) are already occurring (Thomsen et al., 2010). This is caused by upwelling of deep
water masses which are low in pO2 (hypoxic) and high in pCO2 (hypercapnic) due to
stratification and net heterotrophy during summer (Conley et al., 2007; Zillén et al., 2008;
Thomsen et al., 2010).
Figure 2 : pH dynamics measured by sensor deployment at 15 locations worldwide in 0–15 m water depth. All
panels are plotted on the same vertical range of pH. The ordinate axis encompasses a 30-day period during each
sensor deployment representative of each site during the deployment season. From (Hofmann et al., 2011).

3
Ocean Acidification will shift such natural variations towards lower pH levels.
Additionally, decreasing pH causes a reduction in the ability of seawater to buffer changes in
carbon dioxide; this can result in an increased amplitude of diurnal and seasonal fluctuations
(Egleston et al. 2010) and thus periodically cause extreme pH conditions (Hofmann et al., 2011).
This aspect of Ocean Acidification should therefore not be neglected.
However, all previous studies on Ocean Acidification have focused on constant pH
conditions. The biological effects of pH variability are thus currently not known (Hofmann et al.,
2011). To address this question, larvae of the green sea urchin (Strongylocentrotus
droebachiensis) are an excellent model for a number of reasons, given in the next section.

4
Chapter 2. Strongylocentrotus droebachiensis, a keystone
species
The aim of the experiments conducted for this master thesis was to determine the effects of
fluctuating pH on marine organisms.
(Krogh, 1929) stated that “For such a large number of problems there will be some animal of
choice or a few such animals on which it can be most conveniently studied”. The animal of choice
for this problem is the larval stage of the green sea urchin Strongylocentrotus droebachiensis.
This species is convenient for the following reasons;
 It has been extensively studied; a lot of information is thus available
regarding its life cycle, habitat, morphology, feeding behavior, etc (see
Chapter 2) (Stephens, 1972; Hinegardner, 1975; Sivertsen, 1997).
 Low pH/high pCO2 conditions impact the fitness of S. droebachiensis
individuals in various ways (e.g. impacts on survival, calcification
processes, growth rates, reproduction) (see Chapter 3) (Byrne, 2011;
Stumpp et al. 2011a; Dupont and Thorndyke 2009b, 2013; Dorey et al.,
2013).
 Its responses towards OA are well documented (see Chapter 3) (Byrne,
2011; Stumpp et al. 2011a; Dupont and Thorndyke 2009b, 2013; Dorey
et al., 2013).
 Individuals are easy to collect, to spawn and maintain in the lab (see
Chapter 5) (Hinegardner, 1969).
 It is a commercially important species in many regions (see section 2.9)
(Vadas et al., 2000).
 It is a keystone species and impacts on this species can cascade to the
whole ecosystem (see section 2.8) (Norderhaug and Christie, 2009).
The next section will describe this species (particularly its larvae) from the perspectives of
phylogeny, life cycle, habitat, morphology and anatomy, feeding and predators, ecosystemic and
economical functions.
Biological
Socio-
Economical
Practical

5
2.1. Phylogeny
The green sea urchin is part of the Strongylocentrotidae family along with, for example,
the purple (S. purpuratus) and red (S.franciscanus) sea urchins (Myers et al., 2013).
Sea urchins are members of the Echinodermata (“spiky skin”) phylum. It comprises
approximately 7,000 known species subdivided in five classes, such as asteroids (seastars),
ophiuroids (brittlestars), echinoids (sea urchins, sand dollars) and holothuroids (sea cucumbers).
Throughout members of the phylum, adult forms are radially symmetrical, while larval forms are
bilateral. An internal skeleton is always present in adults (Mulcrone, 2005).
Figure 3 : Phylogeny of Strongylocentrotus droebachiensis (Uniprot Consortium, 2002).
2.2. Distribution and habitat
Strongylocentrotus droebachiensis inhabits arctic and boreal coastal ecosystems around the
world and is the most widely distributed species of the Strongylocentrotidae family (Mortensen,
1943; Bazhin, 1998; Scheibling and Hatcher, 2007) Its distribution and that of its associated biota
is influenced by various geographic and environmental factors (e.g. depth, substratum type,
currents, latitude, year) as well as by parasite prevalence (Sivertsen, 1997).
Figure 4: Worldwide distribution of Strongylocentrotus droebachiensis.

6
Green sea urchins occur in shallow subtidal areas as deep as 300m, but they are usually
distributed between 0 and 50m (Jensen, 1974). The habitat they occupy depends on their life
stage.
2.3. Life cycle
S. droebachiensis has an estimated lifespan of 20 years (Pelletier et al., 2001). During the
course of its lifecycle, major ecological and morphological transitions occur. Adult sea urchins
occupy the benthic zone. In early spring (at our sampling site), both male and female adults
release gametes into the water column. When fertilization is successful, embryos and subsequent
larvae (called echinopluteus) are formed. Later, important morphological changes transform them
into juveniles, which crawl on the ocean floor. These juveniles grow into adults, and the cycle
may continue. Each step of this urchin’s life cycle is highly dependent on environmental
conditions (Hinegardner, 1969; Dupont et al., 2012).
Sexual maturity is the result of a trade-off between somatic and gonadic growth. Adult sea
urchins must therefore first undergo an energy accumulation phase. A number of factors influence
the timing, frequency and rate of the onset of the reproductive cycle. These factors are food type
and availability, temperature, certain chemicals and the photoperiod.
Differences in these environmental conditions are the cause of important inter-habitat and
interannual variability in reproductive cycles. Under unfavorable conditions, sexual maturity can
be delayed (from a few days to years) until more propitious conditions return (Stephens, 1972;
Himmelman 1975, 1978, 1986; Scheibling and Hatcher, 2007)
Figure 5: Life cycle of Strongylocentrotus droebachiensis. From (Dupont et al., 2012).
Spawning is triggered by sinking metabolites produced during phytoplankton blooms (highly
variable in timing and intensity, depending on environmental conditions) (Starr et al., 1990, 1992;
Scheibling and Hatcher, 2007). When conditions are adequate, first spawning occurs during
spring in the thirds year of life. It then takes place according to an annual cycle (Raymond and
Scheibling, 1987). The number of eggs released by females (up to several millions per spawning)
is depending on environmental conditions (Hinegardner, 1969). Minor spawning events may also
occur during summer and fall (Keats et al., 1987; Meidel and Scheibling, 1998).

7
Fertilization occurs when male sperm and female eggs meet in the water column. Its success
is dependent mainly on sea urchin density, as proximity to other spawning individuals increases
the chances of egg and sperm encountering (Yund and Meidel, 2003).
The embryos and larvae are planktonic. Larvae in echinoderms are called echinopluteus;
they spend between 4 and 21 weeks (depending on temperature) floating passively with
the currents (Strathmann, 1978; Hart and Scheibling, 1988). Larval survival, dispersal and
recruitment success are influenced by many factors (e.g. currents, upwelling, larval supply…)
(Cameron and Schroeter, 1980; Shanks, 1995).
Once echinopluteus larvae have reached their mature size, they can respond to a chemical cue
(e.g. emitted by coralline algae (Huggett et al., 2006)) and attach to a suitable settlement site
where they undergo two fundamental metamorphoses. The first transforms it into a juvenile,
the second into an adult sea urchin. During these metamorphoses, the urchin develops its mouth,
anus and most of its internal organs (Hinegardner, 1969, 1975).
Under unfavorable conditions, larvae can delay metamorphosis until suitable substrate
and environment are found (Strathmann, 1978). The substrate favored by green sea urchins is
mostly rocky, but they may also occur on gravel bottoms or, less frequently, on sand
(Brady and Scheibling, 2005; Scheibling and Raymond, 1990; Sivertsen, 1997).
2.4. Morphological and anatomical description
S. droebachiensis larvae bear no resemblance to the adults; their organization is as unique
as if they belonged to a different phylum (see Figure 6) (Strathmann, 1971). During the planktonic
larval stage, the embryonic urchin (named rudiment) develops almost like a parasite inside the
growing larva. Few larval organs are maintained in the adult. Therefore it appears that the green
sea urchin larva is nearly exclusively responsible for protection and nutrition of the rudiment
(Hinegardner, 1969).
Figure 6: Drawing of a 20-day-old S. droebachiensis. The mouth is at the top of the gut system. From (Sinervo
and McEdward, 1988).
During the course of larval development, S. droebachiensis echinoplutei undergo remarkable
changes in body shape. These changes have important functional consequences because of the
relationships between larval shape and size, feeding, and metabolic activity (McEdward, 1986).

8
The echinopluteus first initiates the formation of its skeleton. Thereafter, feeding commences
and three main processes may then occur simultaneously: (i) arms are gradually formed until
the maximum of 8 arms is reached. (ii) The rudiment develops; by the end of the larval stage
it will contain spines, tube feet, tests and other parts of the adult body (Yajima and Kiyomoto,
2006). (iii) Endoskeleton formation continues.
Skeleton formation takes place in the primary mesenchyme cells (PMCs) which are located
within the extracellular matrix of the primary body cavity (PBC). PMCs form a syncytium around
the growing spicules (see Figure 10) and are thus in contact with the extracellular environment
of the PBC (Decker et al., 1987; Beniash et al., 1997).
The spicules are composed of high-magnesium calcite (a highly soluble calcium carbonate
form). Spicule formation can be divided into three phases. First, the compounds needed for
calcification are provided by seawater bicarbonate (HCO3
-
, 40%) and generated from metabolic
CO2 (60%) (Sikes et al., 1981). Ca2+
is obtained exclusively from the seawater (Nakano et al.,
1963). Second, an amorphous calcium carbonate (ACC) phase is formed within vesicles in PMCs.
Third, ACC is released into the spicular cavity and acts as a precursor for spicule formation
(Beniash et al., 1997; Raz et al., 2003; Politi et al., 2004, 2008).
The skeleton’s functions include supporting of the projecting arms and associated ciliated
bands (which allow suspension feeding and swimming), providing attachment points for muscles
and the epidermis, adding stiffness and ensuring the vertical orientation of the larvae (Pennington
and Strathmann, 1990; Scheibling and Hatcher, 2007).
Growth and development during the larval stage is the result of an energetic trade-off
between structures. For example, increased investment in arms can cause a decreased or delayed
investment in other structures, such as the rudiment (Strathmann et al., 1992; Heyland et al.,
2004). Moreover, the rudiment does not increase much in size until larval feeding structures are
fully developed (Strathmann et al., 1992; Heyland et al., 2004). When the larval stage is
completed, a majority of larval structures are lost and replaced by new structures, more adapted to
the juvenile and adult benthic lifestyle (Scheibling and Hatcher, 2007).
2.5. Physiological limits
S. droebachiensis is a coldwater, euryhaline species. Because of its capacity of metabolic and
activity adjustments, it is highly adapted to cold and fluctuating temperatures.
The temperature range for larval survival is between 0° and 18°C. Adult green sea urchins
may survive at temperatures up to 22°C, if they were previously acclimated (Percy, 1973;
Scheibling and Stephenson, 1984; Pearce et al., 2005). In winter, adult sea urchins feed at higher
rates than during the warmer months and spend less energy on somatic growth. This allows them
to maintain their gonadal development even during colder months (Percy, 1972, 1973, 1974).
Salinities as low as 20 do not affect survival in larvae of S. droebachiensis (Roller and Stickle,
1985). Adults show contrasted results between populations. For example, a lower lethal limit of
21,5 was found in S. droebachiensis individuals in Norway (Lange, 1964), while in an Alaskan
site (influenced by melt-water), normal activity was maintained through fluctuations from 14 to
28 (Stickle and Denoux, 1976). Tolerance limits towards pH levels will be discussed in section 3.

9
2.6. Feeding
Because of the differences between the larval, juvenile and adult forms of the green sea
urchin, feeding and predatory patterns are contrasted between life stages.
Among others, two main maternal provisioning strategies are recognized in benthic marine
animals. First, planktrotophy, (90% of benthic organisms, including S. droebachiensis), in which
the female produces a high number of eggs (up to millions). The subsequent larvae acquire energy
through exogenous feeding. Second, lecithotrophy, in which the female produces fewer
(thousands) of eggs, packed with yolk (i.e. energy resources) which the larvae will feed on
(Pechenik, 1999).
As the S. droebachiensis echinopluteus is planktotrophic, it floats passively with the currents
and feeds on phytoplankton (mostly single-celled algae), detritus or dissolved organic carbon
(DOC) to cover its energy requirements. Once it has started feeding, egg resources are minor in its
energy supply compared to exogenous sources of food (Meidel et al., 1999).
The ciliated band, which extends into the seawater on the projecting arms, allows food
particles to reach the mouth through both: (i) the creation of a mouth ward current and (ii) direct
contact with food particles. As the larva develops more arms (and thus a longer ciliated band), its
feeding rate increases.
After particles have been ingested, the contraction of circular muscles, combined with the
movement of internal cilia and synchronized sphincter relaxation allow the food to be processed
through the digestive system until it is eventually defecated through the anus (Strathmann, 1971).
Echinopluteus larvae can adapt their feeding behavior in response to their environment.
Ingestion is dependent on the quality of the food particles (Strathmann et al., 1972) and the larvae
are able to change the size of their ciliated band in response to the amount of food; when it is
scarce they may produce longer arms (and thus a longer ciliated band) to maximize food intake.
However, this induces a delay in the rudiment’s development (Strathmann et al., 1992).
Adult and juvenile S. droebachiensis are omnivores, feeding on algae, microbes and animals
when present (e.g. mussels, barnacles, crustaceans, fish, other urchins). Their food preferences are
strongly influenced by environmental factors (i.e. temperature, topography, currents, competition
and predation) and they can survive extended periods without their optimal diets (Himmelman
and Nédélec, 1990; Scheibling and Hatcher, 2007; Vadas, 1990).
Three modes of feeding behavior in juvenile and adult S. droebachiensis were identified
(Mann, 1985): (i) passive detritivory (stationary, depending on drift algae); (ii) dispersed
browsing (low densities of individuals, depending on small algae an other forms of nutrition in
barren grounds) and (ii) aggressive herbivory (massive “grazing fronts” on the margins of kelp
beds, creating barren grounds (Scheibling and Hatcher, 2007).
2.7. Predators
Throughout its life history, S. droebachiensis is prey for a wide range of predators, such as
fish or invertebrates (Scheibling, 1996). Information about predators of the echinopluteus larvae
are scarce; however it appears that scyphomedusae, sponges, tunicates, ophiuroids, ctenophores
and larval fish may consume larval sea urchins (Hooper, 1980; Scheibling and Hatcher, 2007).
Predators of juveniles and adults vary with the urchins’ life stage and size classes; they are
mainly crabs, lobsters, starfish, fish, otters, seabirds, and naturally, humans (see section 2.8.)
(Himmelman and Steele, 1971; Duggins, 1980; Hooper, 1980; Scheibling and Hamm, 1991;
Hagen and Mann, 1992; Scheibling and Hatcher, 2007).

10
S. droebachiensis’ feeding patterns, as well as their predators’ behavior influence not only
sea urchin populations, but also the ecosystem they live in.
2.8. Ecological importance
Green sea urchins play a key ecological role in many boreal regions of the world, mostly
because of their grazing (Norderhaug and Christie, 2009; Scheibling and Hatcher, 2007). This
may lead to two stable states: high-biodiversity kelp forests or species-depleted sea urchin
barrens.
S. droebachiensis is often associated with laminarian kelps, which it grazes on. When sea
urchin populations are absent or regulated, for example when a predator or a parasite (Scheibling
and Hennigar, 1997) is present, highly productive kelp forests may develop. They favor the
establishment of a number of species (e.g. lobsters, sea stars, bivalves, gastropods, the
commercially important cod), by providing nutrition and shelter (see Figure 7a) (Scheibling and
Hatcher, 2007).
Figure 7 : Model of a hypothetical seagrass (e.g. kelp) food web under (a) natural and (b) anthropogenic-
disturbed conditions, showing how disturbances may interact and cause overgrazing. Grey boxes are different
system components, and black boxes represent typical co-occurring anthropogenic disturbances. Solid arrows
indicate direct links, dotted arrows indicate potential feedback mechanisms. The thickness of boxes and arrows
indicate relative importance for the food web. From (Eklöf et al., 2008).
Conversely, in the absence of predators (e.g. otters (Estes and Duggins, 1995)), sea urchin
populations may increase, resulting in destructive kelp bed grazing. This leads to large “barrens”,
where encrusting coralline red algae are dominating. Urchins can survive in this environment, but
this is not the case for organisms that depend on kelp for substrate, nutrition and protection (see
Figure 7b) (Kalas et al., 2006; Scheibling and Hatcher, 2007; Dupont et al., 2012)
As S. droebachiensis plays key roles in both shallow water and deep sea ecosystems
(Lawrence, 1975; Norderhaug and Christie, 2009), any changes in health and performance of
individuals (i.e. due to climate change or fishing activities) will likely have extensive effects on
benthic ecosystems (see Figure 7) (Fabry et al., 2008; Widdicombe and Spicer, 2008).

11
2.9. Economical importance
The green sea urchin may be considered as a pest in some areas, as intensive grazing destroys
kelp habitats and affects the production of commercial species (e.g. cod). Nevertheless, it is
nowadays regarded as a commercially important species as it is fished and cultured in the
Northwest Atlantic and Northeast Pacific (Vadas et al., 2000; Dupont et al., 2012).
Consumption of S. droebachiensis by humans probably started hundreds, or even thousands
of years ago (evidence of prehistoric fishing of S. droebachiensis was found in the bay of Fundy
(Lawrence, 2006)). However, the impact of human activities on sea urchin populations only
became significant in the 1980’s. Since then, the increased demand for sea urchin roe (considered
a delicacy in Japan, France, Italy, etc.) has caused extensive exploitation of populations all over
the world (Lawrence, 2006). The use of drags or dredges to harvest S. droebachiensis
considerably reduces urchin populations and impacts associated fish, invertebrates and
consequently their whole ecosystem (Figure 7) (Keesing and Hall, 1998; Robinson et al., 2001;
Botsford et al., 2004).
Nowadays, efforts are being taken to establish urchin fishing quotas and develop sustainable
urchin aquaculture, with complete life cycles (e.g. in Norway) (Robinson, 2004; Sivertsen et al.,
2008).
These economical activities may be seriously impacted by climate change. Green sea urchin
fisheries are usually situated in the warmer extent of this species’ distribution. Therefore, in the
near future, urchins may retreat to more favorable waters (cooler water in response to temperature
rise, higher pH waters for OA), which could have serious impacts on ecosystems and economies
in these areas (Stephens, 1972).

12
Chapter 3. Biological impacts of Ocean Acidification (OA),
current state of knowledge
To assess the resilience of marine organisms and ecosystems towards the predicted seawater
pH decrease (or pCO2 increase), a deep understanding of its impacts on physiological processes is
needed. Investigation on the effects of OA on marine organisms is currently still in an explorative
phase, but a growing body of information is available (Dupont and Pörtner, 2013; Dupont et al.,
2010a; Gattuso and Hansson, 2011). From this, it appears that OA impacts different species in
contrasting ways and will alter the biodiversity and structure of different ecosystems (Orr et al.,
2009; Hendriks et al., 2010).
As stated earlier, S. droebachiensis has been extensively studied and is an interesting subject
for many reasons. Hereupon is a review of the current knowledge, and gaps regarding this
remarkable species’ responses to Ocean Acidification.
3.1. Impacts of OA are species-specific and life stage-dependent
Responses towards OA vary greatly between species and life-stages. They are generally
negative, but also positive and neutral responses were documented (Dupont and Thorndyke,
2009a; Dupont et al., 2010a; Gattuso and Hansson, 2011).
For example, increases in sperm swimming speed (Psammechinus miliaris (Caldwell et al.,
2011)), in fertilization success (Heliocidaris erythrogramma (Schlegel et al., 2012)), in
calcification rates (Arbarcia punctulata (Ries et al., 2009)); no effect on calcification (Eucidaris
tribuloides (Ries et al., 2009)) were found. Even within a taxonomic group, significant differences
in responses were shown (Dupont et al., 2010a).
Additionally, sensitivity towards environmental stressors in S. droebachiensis is life stage-
dependent. Life stages however form a continuum, and a disturbance in one stage (e.g. due to an
environmental change) can carry over into the following (see Figure 12) (Podolsky and Moran,
2006; Dupont et al., 2012).
Adults and gametes are generally more resilient to ocean acidification compared to early
developmental stages. In S. droebachiensis, the most sensitive stage is the juvenile stage which
shows a significant increase in abnormality and mortality at low pH (Sheppard Brennand et al.,
2010; Byrne, 2011; Dupont et al., 2012; . In S. droebachiensis larvae, direct impacts of OA are
generally negative but sub-lethal in near-future predicted seawater pH conditions (see Figure 11
and see (Dorey et al., 2013; Dupont and Thorndyke, 2013)).
3.2. Physiological impacts of OA
The main sub-lethal impacts of OA on larvae of S. droebachiensis concern calcification, body
fluid pH, growth rates and the energy budget (see Figure 8).
OA may also impact a number of other physiological processes. For example, an increase in
pCO2/decrease in pH may disturb calcium and other ion-transport based activities, which are
essential for physiological processes such as ciliary activity, muscle contraction, neural signaling
and integration. Moreover, the onset of development in many species is triggered by an extensive
calcium transient (Dupont and Thorndyke, 2008).

13
Figure 8 : A number of physiological processes may be affected directly or indirectly by OA and thus impair
fitness. Adapted from (Dupont and Thorndyke, 2013).
3.2.1. Impacts on calcification
Calcification processes in S. droebachiensis larvae are fairly resistant to OA.
In echinoderms, the most sensitive stage is generally the juvenile stage which may show a
significant increase in abnormality in near-future pH conditions (e.g. Heliocidaris erythrogramma
(Byrne et al., 2011)). Sea urchin larvae however are capable of maintaining calcification rates
under acidified conditions when calcification rates are normalized to growth rate (Martin et al.,
2011). This is not true for all echinoderms.
For example, in the brittlestar Ophiotrix fragilis, pH levels of 7.9 caused individuals to be
malformed and short-lived (Dupont et al., 2008).
In two sea urchin species (S. neumayeri and T. gratilla (Clark et al., 2009; Ericson and Miles,
2012)) reared in high pCO2, degradation of the skeletal fine structure was observed and
malformations appeared, such as shorter arms (see Figure 9) (Sheppard Brennand et al., 2010).
Figure 9: Echinopluteus larvae of Tripneustes gratilla reared for 5 days in three pH and two temperature
treatments. Acidification (to pH 7,6) and increased CO2 stunted larval growth, causing a decrease in length of the
arms and the supporting skeletal rods (Sheppard Brennand et al., 2010).
At the molecular level, a down-regulation of genes associated with calcification was observed
under hypercapnic conditions on larval sea urchins (Todgham and Hofmann, 2009; O’Donnell et
al., 2010; Evans et al., 2013).

14
These elements suggest that the biomineralization ability of sea urchins can be affected by
OA, which could alter the composition and mechanical properties of the skeleton (Stumpp et al.,
2011b). In S. droebachiensis larvae however, maintained calcification is the rule; this is
attributable to efficient pH homeostasis (Stumpp et al., 2012a).
3.2.2. Homeostasis
Sea urchin larvae have a leaky integument, which causes the PBC (primary body cavity) to
be in direct contact with the surrounding seawater. Additionally, as invertebrates have a weak
acid-base regulation system that can be disturbed by water chemistry changes (in contrast to
vertebrates) (Melzner et al., 2009), acidosis may occur (i.e. an increase in carbonic acid in the
PBC) and impact pHe (extracellular pH) and pHi (intracellular pH). Compensation for this is
possible, but it comes at a cost.
PBC acidosis can affect many processes (e.g. reproduction, respiration, resistance,
metabolism and behavior). (UNESCO, 2004; Dupont and Thorndyke, 2008).
Adult S. droebachiensis can counterbalance this on the long-term. In echinopluteus larvae, this
remains uncompensated and can cause a suppression of metabolism (Pörtner, 2008; Melzner et al.,
2009). Moreover, a decrease in pHe challenges the intracellular pH (pHi) regulatory machinery
due to decreased proton gradients (see Figure 10) (Stumpp et al., 2012a).
However, PMCs can compensate for an induced intracellular acidosis. Sea urchin PMC’s
contain a large number of genes coding for ion transporters, including Na+
/K+
-ATPase,
Na+
/HCO3
−
cotransporters, and H+
-ATPases (Zhu et al., 2001). This shows that PMCs possess the
necessary molecular machinery to regulate pHi, through HCO3
-
accumulation and proton
secretion. Moreover, it was found that Na+
/K+
-ATPase gene expression (coding for the
Na+
/K+
- ATPase; the main motor of intra- and extracellular acid-base balance (Melzner et al.,
2009), is up-regulated under hypercapnic stress in purple sea urchin larvae (Stumpp et al., 2011b).
Figure 10 : Schematic model summarizing the interplay of calcification, pH regulation, and energetic costs in sea
urchin larvae during environmental acidification. PBC= primary body cavity. pHsw= surrounding seawater pH.
pHe= extracellular pH. pHi= intracellular pH. PMC= Primary mesenchyme cell. ST, stomach; putative
transporters are in gray. From (Stumpp et al., 2012a).

15
The compensation mechanism for intracellular acidosis is highly dependent on Na+
and
HCO3
-
; a bicarbonate buffer mechanism (involving active Na+
-dependent membrane transport
proteins) is thus likely to be involved (Stumpp et al., 2012a). As favorable pH conditions at the
site of skeletogenesis are required in order for calcification to occur normally, maintained pHi
allows calcification to occur despite low pHe (see Figure 10) (Stumpp et al., 2012a).
Maintaining calcification under stressful conditions is however correlated with enhanced
energy costs. Na+
/K+
- ATPase activity alone can account for 77% of the total metabolic rate in S.
purpuratus larvae and 40% of respiratory energy is required for ion balance maintenance. (Leong
and Manahan, 1997). Increased activity of these processes is therefore associated with increased
energy costs. This is likely to be one of the main causes for observed shifts in energy partitioning
which impact growth and indirectly, larval mortality in natural conditions (Stumpp et al., 2012a).
3.2.3. Metabolism
It appears that, under hypercapnic conditions, organisms face higher energetic demands to
supply vital physiological processes. This is associated with shifts in metabolism. In order for
these physiological processes to be sustainable on the long term, energetic demands have to be
met by feeding supplies (see Figure 8).
Metabolism has been found to be up-regulated in a number of invertebrates (e.g. the blue
mussel Mytilus edulis edulis (Thomsen and Melzner, 2010; Thomsen et al., 2010) and the
ophiuroid Amphiura filiformis (Wood et al., 2008)).
In sea urchin larvae, OA has significant impacts on metabolic rates (e.g. a two-fold increase
was found at pH 7.7 (Stumpp et al., 2011a) and on respiration rates (increased by up to 100% at
low pH (Stumpp et al., 2011b; Dorey et al., 2013)).
Complex interactive effects between temperature and OA may also affect metabolism. For
example, in adult Paracentrotus lividus, oxygen uptake was increased under ocean acidification at
10°C but not at 16°C (Catarino et al., 2012). Increased respiration is consistent with the high
respiratory energy demand to maintain ion balance (Martin et al., 2011; Stumpp et al., 2011a).
Feeding is responsible for the amount of available energy for physiological processes.
However, it appears that neither pluteus larval feeding behavior nor feeding efficiency (e.g. lipid
utilization rates, protein content) is affected by OA in S. purpuratus (Stumpp et al., 2011a;
Matson et al., 2012). In adults, feeding is negatively affected by OA (Siikavuopio et al., 2007;
Stumpp et al., 2012b). This lack of positive effects of OA on energy acquisition associated with
increased costs for pHi regulation leads to a shift in the energy budget, causing a decrease in
growth rates (Stumpp et al., 2011a).
3.2.4. Developmental dynamics
As a result of the energetic trade-off between homeostasis and growth, more time is needed
to reach metamorphosis at high seawater pCO2 in most tested species (Byrne, 2011). Embryonic
growth is not significantly affected by OA in sea urchins (Shirayama and Kurihara, 2004; Ericson
and Miles, 2010; Foo et al., 2012; Place and Smith, 2012); however larval, juvenile and adult
growth is impaired at low pH (Shirayama and Thornton, 2005; Albright et al., 2012).
In S. droebachiensis larvae, decreased growth rates are the rule. At low pH, differences in growth
rates between species are correlated with differences in life strategies.

16
Many different life strategies are recognized in marine organisms (e.g. planktotrophy and
lecitotrophy, see section 2.6). They seem to influence organisms’ responses towards OA; while
planktotrophic larvae (e.g. S. droebachiensis ) generally suffer from negative impacts of OA
(Dupont and Thorndyke, 2013), lecitotrophic larvae (e.g. Crossaster papposus) may benefit from
it, showing elevated growth rates at low pH (Dupont et al., 2010b). Life-history strategies such as
an increased maternal investment per egg may therefore be an advantage in stressful
environments.
In planktotrophic echinoid larvae, responses to changes in seawater carbonate chemistry are
generally reduced growth and a developmental delay (e.g. T. gratilla, P. huttoni, E. chloroticus, S.
neumayeri, E. mathaei, and S. droebachiensis (Catarino et al., 2011; Chan et al., 2011; Clark et
al., 2009; Gonzalez-Bernat et al., 2012; Kurihara, 2008; Kurihara and Shirayama, 2004;
O’Donnell et al., 2010; Sheppard Brennand et al., 2010; Uthicke et al., 2012).
For example, sea urchin (S. purpuratus) larvae reared under ΔpH=-0,4 show a 2 days delay in
development (Stumpp et al., 2011a). This implies that at a given time postfertilization, larvae
raised under elevated pCO2 have smaller rod and body lengths compared to controls. (Clark et al.,
2009; Kurihara, 2008; Kurihara and Shirayama, 2004; O’Donnell et al., 2010; Stumpp et al.,
2011a). Additionally, below a certain “tipping point” (< pH 7.2), growth rates are further
decreased in S. droebachiensis larvae and abnormality (arm asymmetry) increases; no
development occurs at even lower pH (< 6.5) (see Figure 11) (Dorey et al., 2013).
Figure 11: Relationship between S. droebachiensis larval body length growth rates (μm.day-1
) and mean pHT.
From (Dorey et al., 2013).
As stated earlier, an up-regulation of genes related to metabolism and a down-regulation of
genes related to biomineralization were observed at high pCO2 (Stumpp et al., 2011b). This
reveals important plasticity at the gene expression level which sustains normal, but delayed
development at hypercapnic conditions (Martin et al., 2011).

17
3.3. OA and Mortality
The predicted increase in seawater pCO2 impacts survival chances differently between
species in experimental conditions. To assess survival in natural conditions, sub-lethal impacts
(see Figure 8) of OA must be taken into account.
In experimental conditions, near-future seawater pCO2 (ΔpH= -0,4 to -0,7) does not directly
affect mortality in a range of echinoid larvae and adults including S. droebachiensis (Chan et al.,
2012; Clark et al., 2009; Dupont et al., 2012; Gonzalez-Bernat et al., 2012; Kurihara, 2008;
Kurihara and Shirayama, 2004; Stumpp et al., 2012a). This is in contrast to the observed 100%
mortality in larvae of the ophiuroid Ophiotrix fragilis exposed to hypercapnia (ΔpH= -0.2). This
species could therefore be eradicated by 2050 (Dupont et al., 2008).
However, when the complexity of biological systems is taken into account, sub-lethal
impacts of OA can affect individual fitness (see Figure 8), and thus indirectly cause increases in
mortality.
Predation pressure is high in the pelagic environment (Hare and Cowen, 1997; Allen, 2008;
Dupont et al., 2010c). This means that a longer time spent in the water column can reduce survival
chances (Gosselin and Qian, 1997; Kurihara et al., 2007; Dupont and Thorndyke, 2008; Findlay et
al., 2008; Byrne, 2011) (e.g. a 2 days delay in development over a 23 days development period
may double the mortality) (Dupont et al., 2010c).
Moreover, ecological processes are often synchronized. Larvae are released coincidently with
the spring phytoplankton bloom; a change in development rate can thus reduce feeding
opportunities) (Dupont et al., 2010c). A delay in settlement may also reduce an organism’s
chances of occupying a high-quality habitat (Miner, 2005; Elkin and Marshall, 2007).
We have seen that hypercapnia may affect marine organisms in many contrasting ways.
However, some organisms, such as S. droebachiensis show potential for adaptation and
acclimation mechanisms. This may ensure individual survival, and even population resilience in
the predicted Ocean Acidification context.
3.4. Potential for adaptation and acclimation
It is important to know whether marine organisms will be able to acclimate (within an
organism’s lifecycle) and/or adapt (between generations) to chronic, long-term exposure to
hypercapnia (see Figure 12). In response to future environmental changes such as OA, marine
invertebrates will:
 respond phenotypically
 respond genetically
 migrate, or
 undergo local/global extinction.
The combination of these individual responses will influence the outcome for populations
(Peck, 2005; Sultan, 2007; Przeslawski et al., 2008; Visser, 2008; Wethey and Woodin, 2008). As
sea urchins cannot easily migrate, only phenotypic and genotypic responses to OA will be
examined.

18
Figure 12: OA effects on an organism’s life cycle and possibilities of acclimation/adaptation. From (Dupont and
Thorndyke, 2008).
3.4.1. Phenotypic acclimation/adaptation
Marine invertebrates may be resilient to environmental stressors (OA, temperature) in the
short term if their phenotypic traits are flexible enough (i.e. if the phenotype expressed by a given
genotype varies in response to the organism’s environment). Only a few examples will be
sketched in this section, regarding developmental plasticity, exposure duration, geographical
range and tolerance limits.
Developmental plasticity will be important to cope with changing environmental conditions.
We have seen that green sea urchin echinoplutei can adapt their arms length in response to
available nutrients (Soars et al., 2009) and that energetic trade-offs may occur between growth,
regulatory mechanisms and reproduction in response to deleterious effects of OA. This highlights
the remarkable plasticity of S. droebachiensis in response to environmental stressors (Martin et
al., 2011; Stumpp et al., 2011b).
In S. purpuratus larvae, OA has been reported to induce high-frequency budding (release of
blastula-like particles, see Figure 13). This reflects a trade-off between short-term benefits
(e.g. metabolic economy and predation escape) and long-term costs (e.g. delayed development,
tissue loss) under stressful environmental conditions (Chan et al., 2012).
Figure 13 : 7-day-old S. droebachiensis larva actively budding at pH 7.7 in our experiment. The arrow indicates
the site of constriction leading to bud formation.

19
Duration of exposure is a key in determining organisms’ sensitivities towards OA.
In adult green sea urchins, OA (<4 months exposure) may impair fecundity. This is due to
increased energy costs needed for the adult’s survival (Yu et al., 2011). These negative effects
may however be compensated when adults are exposed to OA long enough (16 months exposure).
This allows them to replenish their energy stores and thus ensure gonadal function and successful
reproduction (Dupont et al., 2012).
In species with a broad latitudinal distribution, differences in reactions to different thermal
regimes between populations suggest a potential for important phenotypic plasticity in the face of
climate change (Vernberg, 1962; Sokolova and Pörtner, 2001; Stillman, 2003; Visser, 2008;
Zippay and Hofmann, 2009; Byrne, 2011; Sanford and Kelly, 2011).
(Byrne et al., 2011) showed that, in the sea urchin H. erythrogramma, embryos derived
from lower-latitude females are more thermotolerant than those from higher-latitude females. This
was however not shown for other sea urchin species (e.g. S. purpuratus (Hammond and Hofmann,
2010)).
However, when an organism is stressed to the edges of its tolerance window, the energy
required to maintain homeostasis, survival and reproduction increases. This can lead to
unsustainable energy costs, a decrease in fitness and finally, death (Porter, 2007; Pörtner, 2008;
Widdicombe and Spicer, 2008; Hofmann and Todgham, 2010; Byrne, 2011). For example,
massive oyster die-offs were attributed to the upwelling of acidic waters along the US west coast
(Barton et al., 2012).
To ensure long-term resilience towards environmental change, genotypic variability will be
necessary (Fabry et al., 2008).
3.4.2. Genetic adaptation
Population effects, recent adaptations and past conditions give indications as to how
organisms may adapt genetically to environmental changes.
Differences in responses towards environmental stressors have been observed between (Carr
et al., 2006; Moulin et al., 2011) and within populations of the same species (Chan et al., 2011,
2012; Sunday et al., 2011; Foo et al., 2012; Schlegel et al., 2012).
For example, spat of selectively bred lines of the pacific oyster S. glomerata showed only a
25% reduction in shell growth when reared at elevated pCO2, while spat originating from wild
populations showed a 64% reduction. These differences may originate from genetic diversity
among populations of the same species, or from a pre-adaptive capacity, giving individuals a
better resilience towards OA (Parker et al., 2011). They also indicate the existence of selectable
genetic variation for growth under OA conditions.
Marine species may have the potential for adaptative evolutionary responses to climate
change. For example, rapid genetic adaptation towards acidification (pH 6.0-6.8) was documented
for copepods living in lakes affected by SO2 emissions (Derry and Arnott, 2007).
(Sunday et al., 2011) demonstrated that the sea urchin S. franciscanus has a high level of
phenotypic and genetic variation for larval size when exposed to ΔpH=-0.4 and has the potential
for a fast evolutionary response within 50 years.
Organisms exposed to fluctuating pH or temperatures may be more resilient towards the
expected change, as they have already experienced some phenotypic and genetic changes
(Hamdoun and Epel, 2007; Dupont et al., 2010c; Byrne, 2011; Yu et al., 2011).

20
For example, calcifying invertebrates (e.g. barnacles and limpets) are found in volcanic vents
surrounding the island of Ischia (Tyrrhenian Sea, Italy) in seawater pH down to 7.4 (Hall-Spencer
et al., 2008). Through local adaptations, such species are able to develop, survive and reproduce in
extreme (but predictable) environments (Hamdoun and Epel, 2007).
Moreover, various marine species existed under different conditions compared to those they
experience now. This suggests that some species may be “exapted” rather than “adapted” to
current conditions (Jackson and Johnson, 2000) and may explain why some species react
positively towards acidification. The persistence of these species through past climate change and
extinction events shows an adaptative capacity across the ontogenetic stages (Jackson and
Johnson, 2000; Uthicke et al., 2009).
These adaptive changes, which will be very useful in the context of future climate change,
might however not occur quickly enough to confer a real advantage. Indeed, as atmospheric CO2
concentrations are increasing rapidly and as many organisms (including sea urchins) have
relatively long generation times, it is not known whether their evolution will be rapid enough to
avoid local population and species extinctions (Kurihara, 2008).
3.5. Gaps in the knowledge
We have seen that an organism’s response to OA is the result of a large number of factors
(e.g. acclimation and adaptation potential, ecological interactions, multiple stressors and pH
variability). Most studies have focused only on some aspects of this question. Therefore,
information is still lacking at different levels: (i) ecosystems, (ii) populations, and (iii) individuals
(Dupont and Thorndyke, 2008, 2013; Dupont et al., 2010a; Byrne, 2011).
At the ecosystem level, still little is known about the effects of OA on ecological interactions
(e.g. competition, food quantity and quality, chemical ecology, pathogens etc.).
At the population level, information is lacking on regional effects and on differences in
individual responses within and between populations.
At the individual level, information is needed about physiological responses to OA; the
relative contribution of the different processes (e.g. calcification, growth) to the energy budget;
the effects of OA on energetic trade-offs; long-term and trans-life cycle exposure effects
(adaptation, acclimation and carry-over effects); synergistic effects of OA with other stressors
(e.g. temperature rise, deoxygenation, eutrophication, pollution) and the effects of local
environmental pH and its variability.

21
Chapter 4. Motivations and aim of the study
We have seen (see section 1.2) that seawater pH may significantly fluctuate (e.g. diurnally,
seasonally) and reach much higher pCO2 values than those expected for the average surface ocean
within this century (Thomsen et al., 2010; Hofmann et al., 2011). Organisms occupying these
habitats are thus under constant challenge from cyclical changes in pH and carbonate ion
concentration (Yu et al., 2011). As OA lowers ocean pH, its variations will shift. Hence, not only
the intensity but also time that organisms are exposed to unfavorable pH conditions could
increase.
Therefore, it is important to understand species’ environments in order to define their
sensitivity to environmental changes. However, all OA experiments performed until now have
focused solely on comparing current and near-future pCO2 scenarios, without taking into account
geographical or temporal pH variability (McElhany and Busch, 2012).
The aim of this study was thus to assess the biological impacts of pH variability on
Strongylocentrotus droebachiensis larvae. From previous studies (see sections 3.2.4 and 3.3) it
appears that mortality and growth rates are adequate tools to address this question.
Mortality was not affected by OA in previous studies (Dorey et al., 2013; Dupont and
Thorndyke, 2013; Kurihara and Shirayama, 2004); therefore we expect to see no impact of OA on
this parameter.
To assess the effects of OA on growth, a number of considerations must be taken into
account. In a previous study, PMC cells were exposed to pulses of NH3/NH4
+
solution. It was
found that pH was regulated by proton excretion and HCO3
-
accumulation. As this is energy-
consuming, the higher the seawater pH (and thus pHe, see section 3.2.2), the more energy would
be consumed for homeostasis. This increased energetic demand, in turn, is likely to be one of the
causes for observed decreases in growth rates (Stumpp et al., 2012).
From this, it can be hypothesized that growth rates of larvae from fluctuating treatments
would be intermediate between those from the control and the constantly acidified pH treatments.
Indeed, as PMC cells of larvae from fluctuating treatments are exposed to low pH conditions
periodically, pHi needs to be regulated only when pHsw (and thus pHe, see section 3.2.2) is low.
Therefore, energy demands for homeostasis would be fewer than under constantly acidified
conditions.
Figure 14 : Expected trend for S. droebachiensis larvae growth rates in the experimental treatments.

22
Consequently, the hypotheses tested in this study were:
 Low pH conditions will have no effect on mortality rates (as shown by (Dorey et al.,
2013; Dupont and Thorndyke, 2013; Kurihara and Shirayama, 2004).
 Due to the energetic costs of maintaining pHi homeostasis (Stumpp et al., 2012b), growth
rates in fluctuating treatments will be intermediate between those from the control and the
constantly acidified treatments.

23
Part II. Materials, Methods and Data
Chapter 5. Materials and Methods
Four identical experiments were conducted successively in order to assess the impact of
fluctuating pH levels on S. droebachiensis larvae in the near-future Ocean Acidification context.
We cultured S. droebachiensis embryos and the subsequent larvae to different pH fluctuation
frequencies and intensities over a period of 10 (experiments 3 and 4) or 12 (experiments 1 and 2)
days. Our treatments were: three constants (pH 8.1, 7.4 and 7.7), two 12h pH fluctuation
(ΔpH= 0.4 and 0.7) and two 24h pH fluctuation (ΔpH= 0.4 and 0.7) (see Figure 15).
We measured growth and mortality daily to determine OA impacts on these parameters.
Figure 15 : Experimental pH treatments.

24
5.1. Adult and larvae culture
5.1.1. Adult culture and spawning
Adult Strongylocentrotus droebachiensis were collected in the Kattegat (Dröbak, Norway) in
January 2012 and transferred to the Sven Lovén Center for Marine Sciences (Kristineberg,
Sweden). They were fed daily using Laminaria sp. (collected weekly from the Gullmarsfjord) and
kept in flow-through systems with deep-water from the Gullmarsfjord (mesh filter diameter = 1.5
mm) before starting the experiment.
Spawning was induced in March-May 2013 by intra-coelomic injection of 2ml 0.5 M KCl
(see Figure 16) in filtered seawater (FSW; surface water from the Gullmarsfjord flowed through
three successive filters (10, 3 and 0.5 µm respectively)). This alters membrane potentials, causing
the gonads to contract and release ripe gametes.
Eggs were collected (see Figure 16) and kept in FSW to maintain their viability. Sperm was
collected (see Figure 16) and kept dry on ice until use, as contact with seawater (i.e. the pH shock
between the acid gonads and the more basic water) is the trigger for sperm swimming onset.
Because swimming uses sperm energy resources, it is limited in order to ensure a high fertilization
ratio.
To ensure an appropriate amount of eggs and sperm (5.104
embryos/treatment, 7.105
in total),
gametes from a different number of males and females were collected for each experiment (see
Table 1). Egg numbers were estimated by counting in a 20 µl subsample under a binocular
microscope.
The high number of females used for the first experiment (due to low gamete numbers per
female) is explained by the time of the year (mid-March), and thus by the lack of favorable
seawater conditions (e.g. temperature, chemical cues) for spawning. In the last experiment, we
spawned a large number of adults in order to obtain eggs for both ours, and a mesocosm
experiment.
Table 1 : Number of females and males spawned in each experiment.
Experiment I
11/03/2013
Experiment II
01/04/2013
Experiment III
18/04/2013
Experiment IV
01/05/2013
Females 4 3 2 8
Males 3 2 2 8
All eggs were mixed and transferred to a single 1L beaker, where they were fertilized by addition
of dry sperm (concentration of 1000 sperm.mL-1
). A higher sperm density could cause
polyspermy (and thus abnormal larvae) while a lower density would decrease fertilization rates
(below the required minimum of 95%).
Fertilization was followed through a binocular microscope. The oocyte fertilization membrane
(see Figure 16) formed within 5 minutes after fertilization. After 15 minutes, eggs were rinsed
with FSW. Two to three hours later, the first cellular division occurred (see Figure 16).

25
Figure 16: Overview of the spawning and fertilization procedure. a) Intracoelomic injection of KCL (0.5M);
b) egg collection in FSW; c) dry sperm collection; d) egg; e) swimming sperm; f) fertilized egg in fertilization
membrane; g) two-cell stage embryo.

26
5.1.2. Larvae culture
Subsequent cleaving embryos (two cells stage) were placed in FSW-filled 5L Erlenmeyers
(see Figure 18). The FSW was pre-equilibrated at a particular pH level; pH 8.1, 7.7 and 7.4 for
constant treatments. The initial density was of 10 (±2) embryos per mL. Larvae cultures were kept
in the dark, at a salinity of 32.5, a temperature of 9°C and were aerated with a stream of
pressurized air bubbles. The air was injected through wooden airstones (see Figure 18), which
created a slow convective current to avoid disturbances of larvae by strong currents. The different
treatments were placed randomly along the experimental area.
The two first experiments were performed over a period over 12 days. As some of our
cultures crashed (see section 6.2) in experiments 3 and 4, they were conducted over a period over
only 10 days.
We changed the water in each treatment twice (experiments 3 and 4) or three times
(experiments 1 and 2) during the course of the experiment (see Figure 17). It was passed through a
100µm mesh filter to remove larval excretions, dissolving skeletons and other undesired
compounds, but retain larvae.
Figure 17: Overview of the protocol in every culture. The routine protocol and the steps for data sampling are
indicated for each day of the experiment. On day 0 the adults were spawned; the embryos were transferred in 5L
Erlenmeyers (pre-equilibrated at the appropriate pH level for constant treatments). On day 1, we started pH
regulation and daily sampling for mortality and growth rates. This was continued for the whole duration of the
experiment. On days 4, 8 and 11, the culture water was changed and sampled for AT and pHT measurements.
Feeding was started at day 7 and performed daily until the end of the experiment.
Larvae feeding started at day 7 (see Figure 17), once their digestive system was fully
developed. They were fed with Rhodomonas spp. (micro-algae) raised at 20°C under a 12:12h
light:dark cycle in B1 medium (Guillard and Ryther, 1962)(see supplementary Table D.1).
The Rhodomonas spp. culture was supplied with diluted B1 medium daily by removal of 1/3
of the culture and addition of new media. Two 2L bottles of medium (2mL main solution + 0,2mL
vitamin solution in autoclaved (20 min at 120°C) FSW, see supplementary Table D.1) were added
every week. Algal strains were provided by the Marine Algal Culture Centre at Gothenburg
University (GUMACC).

27
Larvae were then fed daily (see Figure 17). To ensure stable food concentrations, algae
concentration and size (equivalent spherical diameter (ESD)) were checked daily using a coulter
counter (Elzone 5380, Micrometrics, Aachen, Germany). The Coulter method for particle sizing
and counting is based on measurable changes in electrical impedance produced by nonconductive
particles (i.e. single-celled algae) suspended in an electrolyte (Hogg et al., 1971).
Algae concentration (cells.L-1
) in the algae culture was estimated on a 2ml sample diluted
(50 times) with 98ml of FWS. Algae concentration in the treatments was estimated on 10ml
samples diluted (2 times) in 10ml FSW. Results were multiplied by the dilution factor to
determine concentrations.
The body shape of Rhodomonas was approximated as a sphere; algal volume (V, in µm³) was
thus estimated from the mean diameter (D) of the algae according to equation (2.1):
V = 4/3 π (0.5D)3
(2.1)
Algal carbon content (C, in pgC.cell-1
) was estimated from cell volume according to (2.2)
(Mullin, Sloan, and Eppley 1966) :
C = 0.513V0.75
(2.2)
The algae solution was supplied to the experimental bottles to reach a maximum
concentration of 150 μg carbon.L-1
(~ 3000 to 6000 cells.mL-1
for algae diameters ranging
between 6 and 8 μm). Seawater pCO2 levels and temperature had no impact on algal growth and
survival at the chosen algae concentration (150µg C.L-1
) and time of exposure (24h, algae added
daily) (Dupont et al., 2012).
5.2. pH regulation
Our treatments were: three constants (pH 8.1, 7.7 and 7.4; 0.05, 0.12 and 0.24 kPa,
respectively), two 12h pH fluctuation (ΔpH= -0.4 and -0.7) and two 24h pH fluctuation
(ΔpH= -0.4 and -0.7) (see Figure 15). Two replicates were used for each treatment.
The two minimum pH values were chosen according to two considerations. We wanted to test
(i) the near-future predicted pH decrease (ΔpH=-0,4) and (ii) the corresponding doubling in [H+
].
As pH is a logarithmic scale (see equation (2.3), this doubling is expressed by a ΔpH of -0.7
compared to the constant pH 8.1 treatment (which was used as control) (see equation (2.4)).
pH = - log[H+
]; (2.3)
7.7 = - log (0.1995); (2.4)
7.4 = - log (0.3981). (2.5)
The water we used in our experiments was surface FSW from the Gullmarsfjord. In each
aquarium, pH was operated continuously by a computerized feedback system
(AquaMedic, see Figure 18) by addition of pure gaseous CO2 directly into the seawater by small

28
pipes (+/− 0.02 pH units; 1 bubble/second), with the exception of the two constant pH 8.1
treatments.
The feedback system was based on a probe that monitored the seawater pH by the means of
the Aquamedic pH computer system, which controlled the opening and closing of a valve. This
valve was connected to both a CO2 bottle and a small bubbling tube inside the aquarium
(see Figure 18).
Figure 18 : The CO₂ bubbling system monitored by Aquamedic computers. a) General set-up; b) set-up in our
experiment. (1) CO2-bottle, (2) pressure regulator, (3) valve, (4) connection plug, (5) pH computer, (6) CO2
bubbling tube, (7) pH probe, (8) culture bottle, (9) wooden airstone.
For example, in a bottle where the required pH was 7.4; if the immersed probe measured a pH of
7.78 (see Figure 18), it would set off the opening of the associated valve, and CO2 bubbling would
start in the water. This bubbling was continued until the probe measured the required pH value
(7.4 in this example). In the fluctuating treatments, the pH computers were turned off periodically
for the wanted period (12h or 24h).
The pH (NBS scale) measured by these probes was recorded three times a day in each culture
except for the constant pH 8.1 bottles (as the amount of pH computers was limited). In all
cultures, seawater was continuously aerated and mixed by air bubbling (see Figures 17 and 18).

29
5.3. Seawater carbonate system measurements
The ocean can be viewed as a dilute solution of sodium bicarbonate; together with other acid-base
species at lower concentrations in a saltwater background (Riebesell et al., 2010). When carbon
dioxide dissolves in seawater, it reacts with the seawater following a series of chemical equilibria
(Riebesell et al., 2010) given in Figure 1. The equilibrium constants for those reactions are the
following ([H2CO3] + [CO2] will be abbreviated as [CO2
*
]) (Riebesell et al., 2010):
K0= [CO2
*
]/p(CO2) ; (2.6)
K1= [H+
][HCO3
-
]/[CO2
*
] ; (2.7)
K2= [H+
][CO3
--
]/[HCO3
-
] ; (2.8)
They are functions of the temperature, pressure and salinity of the seawater and have been
estimated by a number of authors (see supplementary Table E.4).
Other acid-base equilibria take place in seawater. The equilibrium constants for these
reactions (and those for the carbonate system) can be calculated from the equations given in
supplementary Table E.4).
It is possible to obtain a complete description of the carbon dioxide system in a sample of sea
water at a particular temperature and pressure provided that the following information is known
(Dickson et al., 2007):
 the values of at least two of the CO2 related parameters: DIC (total dissolved
inorganic carbon), AT, pCO2, [H+
].
 the solubility constant for CO2 in sea water, K0.
 the equilibrium constants for each of the acid–base pairs that are assumed to exist in
the solution; K1, K2, etc... (see supplementary Table E.2).
 the total concentrations of all the non-CO2 acid–base pairs (obtained by the
equations from supplementary Table E.2; and by published information about the
boron to salinity ratio of the seawater, given in supplementary Table E.2).
The two analytical parameters we measured directly were pH and alkalinity (see sections
5.3.1 and 5.3.2); this allowed us to determine pCO2 (CO2 partial pressure) and the saturation state
of aragonite (see section 5.3.3 and Figure 19).
The equilibrium constants we used were provided by results of the study by (Mehrbach,
1973) and refitted by (Dickson and Millero, 1987). They produced the most accurate results for
calculations of carbon system speciation in both laboratory and field measurements in a number of
previous studies (Clayton et al., 1995; Byrne et al., 1999; Wanninkhof et al., 1999; Lee et al.,
2000).

30
Figure 19 : Summary of the steps towards speciation of the carbonate system parameters. Green boxes contain
measured parameters; red boxes contain calculated parameters. Numbers on the arrows indicate the
corresponding equations.
5.3.1. pH
Seawater pH (moles H+
.kg of solution-1
) can be measured with different scales. In this experiment,
we used both the NBS (pHNBS) and total (pHT) pH scales.
5.3.1.1. pH NBS
The pHNBS scale is defined by a series of certified buffer solutions across a range of pH
values. These solutions however have a low ionic strength compared to that of seawater. As this
difference can cause changes in electrode potential, this scale is not ideal for the characterizing of
seawater pH. The uncertainty it causes on measurements may be as large as 0.005 pH, even for
careful measurements (Riebesell et al., 2010).
In this scale, the definition of pH is:
pHNBS = -log10 [H+
]F (2.9)
5.3.1.2. pH Total
The pHT scale was developed to resolve the pHNBS scale shortcomings.
In an aqueous solution, the H+
ion forms complexes with H2O (all protons are hydrated in an
aqueous solution) and with sulphate ion (following 2.10). The pHT scale takes this into account.
This scale is based on artificial seawater and is defined using a medium containing sulfate ions
which undergo protonation.

31
The pHT scale thus includes the effects of both free hydrogen ions (H+
F) and hydrogen
sulfate ions (HSO4
-
) (Dickson et al., 2007; Hansson, 1973; Mehrbach, 1973):
[H+
]T = [H+
]F + [HSO4
−
]; (2.10)
In this scale, the definition of pH is thus:
pHT = -log10 ([H+
]F + [HSO4
-
]) (2.11)
In our experiments, pHT was measured with a Metrohm (827 pH lab) pH electrode. It works
following (2.12) (Riebesell et al., 2010):
(2.12)
The electrode reversible to H+
was made of glass. The standard buffers for the measurement
of total hydrogen ion concentration we used were TRIS (2-amino-2methyl-1,3-propanediol/HCl)
and AMP (2-aminopyridine/HCl) buffer solutions with a salinity of 32,0 (provided by Unité
d'Océanographie Chimique, Université de Liege, Belgium).
In order to evaluate pHT of a sample, the electrode response (K) to the buffers (TRIS and
AMP) first had to be determined. It was calculated from the e.m.f. of the pH cell in the buffers
(ETRIS and EAMP)(see Equation 2.13). This response was compared with the ideal Nernst value:
RTln10/F. It had to be theoretical (difference <5%). TRIS and AMP pH values were calculated
from their temperature and salinity values (see Annex E).
K = ;
(2.13)
To determine these e.m.f values (EAMP and ETRIS) the buffers needed to be brought to the
same temperature. We therefore took e.m.f. measurements for a range of temperatures on the
TRIS buffer to determine the electrode slope. ETRIS at a certain temperature T (in this case, the
AMP buffer temperature T (in Kelvin)), was then estimated from:
ETRIS = slope (T – TTRIS); (2.14)
It was then possible to determine the pHT of a seawater sample from: (i) electromotive force
(E) measurements on the sample (S) and on the TRIS buffer and (ii) from previously calculated or
measured values (pHTRIS, K, TS, TTRIS)(see equation 2.15). Equation (2.14) was used to determine
ETRIS at the sample temperature (281,65 ± 0,2 K).
pHT(S) = pHTRIS + ( (2.15)
With this method, the overall uncertainty for the pH measurement is less than 0,002 in the pH
range between 7,5 and 8,5, provided that the electrode slope is Nernstian (>99%), or nearly so
(Riebesell et al., 2010).

32
5.3.2. Alkalinity measurements
In order to determine all parameters of the carbonate system, alkalinity (along with pHT) was
measured twice (experiments 1 and 2) or three times (experiments 3 and 4).
The total alkalinity of a sample of sea water (expressed in mol. kg SW-1
) is a form of mass-
conservation relationship for the hydrogen ion. It is defined (Dickson, 1981) as “. . . the number of
moles of hydrogen ion equivalent to the excess of proton acceptors (bases formed from weak
acids with a dissociation constant K ≤ 10–4.5
at 25°C and zero ionic strength) over proton donors
(acids with K > 10–4.5
) in 1 kilogram of sample.” And thus:
AT [HCO3
-
]+2[CO3
2-
]+[B(OH)4
-
]+[OH-
]+[HPO4
2-
]
2[PO4
3-
]+[SiO(OH)3
-
]+[NH3]+[HS-
]+[S--
]...
-[H+
]F-[HSO4
-
]-[HF]-[H3PO4 ]- ...
(2.16)
Although the concentration of each of the species making up the alkalinity changes when
pressure or temperature changes, the linear combination of these concentrations remains constant.
Hence, alkalinity is independent on the temperature and pressure of the sample (Dickson et al.,
2007).
Alkalinity was measured with a Titroline Alpha Plus Titrator twice in each experiment.
AT was assessed on 25mL filtered samples of the culture water (0.2µm mesh; to remove remaining
skeletal fragments, which would increase the measured AT) in borosilicate glass bottles.
The titration was performed with a solution of hydrochloric acid in two stages.
The sample was first acidified to a pH between 3.5 and 4.0 with a single aliquot of titrant. The
solution was then stirred to allow for the escape of CO2 that had evolved.
The titration was then continued until a pH of about 3.0 had been reached. To maintain
approximately constant activity coefficients during the titration, the acid was made up in a sodium
chloride background (to approximate the ionic strength of sea water). The use of an open cell (as
opposed to a closed-cell titration) allowed us to assume that the total dissolved inorganic carbon
(and so the amount of residual bicarbonate ion) was around zero in the pH region of 3.0 to 3.5.
The progress of the titration was monitored using a pH glass electrode/reference electrode
cell, and the total alkalinity (in moles.kg of solution-1
) was computed from the titrant volume and
e.m.f. measurements using a non-linear least-squares approach that corrects for the reactions with
sulfate and fluoride ions (Riebesell et al., 2010).
5.3.3. pCO2 and Ωar
The partial pressure of CO2 (pCO2) and the seawater saturation state with respect to
aragonite (Ωar) were determined from pH and alkalinity measurements.
pCO2, (expressed in µatm) is the partial pressure of carbon dioxide in the gas phase that is in
equilibrium with seawater. It is the product of mole fraction and total pressure, x(CO2).p.
It influences the concentration of other carbonate compounds and thus the solution pH (Dickson et
al., 2007).

33
The saturation state of seawater with respect to aragonite is the product of the concentrations
of dissolved calcium and carbonate ions in seawater divided by their product at equilibrium
(Dickson et al., 2007):
([Ca2+
][CO3
2-
])/[CaCO3] = Ωar (2.17)
The value of Ωar can give three different indications (Dickson et al., 2007):
 When Ωar = 1, the seawater is saturated with respect to aragonite; aragonite does not
dissolve or precipitate.
 When Ωar > 1, the seawater is said to be supersaturated with respect to aragonite; aragonite
will precipitate.
 When Ω < 1, the seawater is said to be undersaturated with respect to aragonite; the
aragonite mineral will dissolve.
5.3.4. Carbonate system speciation from pH and AT
The carbonate system speciation was calculated from pHT and AT using the CO2SYS
software (Lewis et al., 1998). When information about pH and AT is provided,
it calculates the other parameters of the carbonate system as follows (see Figure 19).
The contribution of carbonate species to the total alkalinity (Ac, the carbonate alkalinity) is
defined as:
Ac = [HCO3
-
]+2[CO3
2-
] (2.18)
The contributions of the non-CO2 species to AT are calculated from the expressions given in
supplementary Table E.4, and thus:
Ac = AT–([B(OH)4
-
]+[OH-
]+[HPO4
2-
]
+2[PO4
3-
]+[SiO(OH)3
-
]+[NH3] + [HS-
] + ...
-[H+
]F-[HSO4
-
]-[HF]-[H3PO4 ]-...);
(2.19)
From (2.7),
[HCO3
-
] = ; (2.20)
And from (2.8),
[CO3
2-
] = ; (2.21)
by substitution into (2.18),
[CO2
*
] = (2.22)
and thus,
[HCO3
-
] = (2.23)

34
[CO3
2-
] =
(2.24)
pCO2 was then calculated from equation (2.6).
5.4. Biological measurements
5.4.1. Mortality
In order to assess whether high pCO2/low pH conditions affected mortality, our larvae
cultures were monitored daily in every experiment (see Figure 17). Each day, two 10mL samples
were taken from each culture. Larvae were immediately fixed with two drops of
paraformaldehyde 4% (PFA) in FSW (pH 8.3). A bifocal microscope was used for larvae
counting.
The larvae were then transferred in Eppendorf 1.5mL tubes and fixed in 4% PFA at 4°C for
later analysis. Density at time t (N.L-1
) for each treatment was estimated from the average counted
larvae. We then transformed this density to a relative density (relative to the initial density
reported in each culture, for each experiment). Mortality was determined according to:
Mortality= 1 - (Relative Density) (2.25)
A Gompertz function was then fitted to mortality data for each culture according to:
λ (2.26)
We used this function to ensure an appropriate fit on mortality curves. Indeed, it takes into
account the time points in days (t), the maximum of the curve (A), the maximum slope (µ) and the
lag phase (λ). These different parameters were then used in a two-way ANOVA to check for
significant differences. Models are given in section 5.5.

35
5.4.2. Body length
As stated earlier (see section 3.2.4), growth is a relevant parameter to assess the impacts of
low pH conditions on the development of S. droebachiensis. In order to determine these impacts,
we measured larvae daily. Every day and for each bottle, we photographed 10 fixed larvae
(immediately after counting) with a digital camera mounted on a dissecting microscope using
polarized light to visualize the skeleton. Larval body length (see Figure 20) was measured for
each larva with the software ImageJ (U. S. National Institutes of Health, Maryland, USA).
Figure 20. Morphology of a Strongylocentrotus droebachiensis 8days-old 4-arm pluteus larva in constant pH 8.1
conditions. BL, body length.
A logarithmic function was then fitted to body length data for each culture according to
Equation 2.27:
y(t)= y0 + a.t (2.27)
The arguments are: the slope (i.e. growth rate) of the curve (a), the intercept (y0) and the time
in days (t). These parameters were then used in two consecutive two-way ANOVA’s to check for
significant differences. Corresponding models are given in the next section.

36
5.5. Statistical analyses
Data for mortality and growth were analyzed using a two-way ANOVA (Analysis of Variance)
method. This allowed us to compare the mean responses of different treatments.
The assumptions made for this analysis are :
- Independence of observations
- Normal distribution of the residuals (verified by the Shapiro-Wilk test)
- Homogeneity of variance within the same group (verified by the Levene test)
- Same sample size between groups.
An ANOVA decomposes the total variance in two components; the variability due to the
treatments and the intrinsic variability of each treatment. This analysis of variance thus allows us
to determine if the variability of a sample is a consequence of the treatment or not (i.e. the
variability of the treatment is more important). A two-way ANOVA’s null hypotheses are thus:
1. The population means of the first factor are equal.
2. The population means of the second factor are equal.
There is no interaction between the two factors.
The two independent variables in a two-way ANOVA are called factors. These factors affect the
dependent variable (i.e. growth or mortality). Response variables are all continuous. The factors
have two or more levels within it, and the degrees of freedom for each factor is one less than the
number of levels.
In this experiment, explanatory variables are all categorical:
The experiment (E) is a random parameter and has four levels (i): Experiments n°1 to n°4.
The treatments (t) are fixed and have seven levels (j): constants (pH 8.1, 7.4 and 7.7),
12h pH fluctuation (ΔpH= 0.4 and 0.7) and 24h pH fluctuation (ΔpH= 0.4 and 0.7).
Yij = µ + Ei + tj + Etij + ɛij
1
(2.28)
If no experiment effect was found, data from all four experiments were pooled. If a treatment
effect was found, the following analysis was made:
Fluctuation (f) is fixed and has two levels (k): 0 (no fluctuation) and 1 (fluctuation).
pH level (p) is fixed and has three levels (l): 7.4, 7.7 and 8.1.
Ykl = µ + fk + pl + fpjk + ɛkl
1
(2.29)
All statistical analyses were performed with the free-access software R.
1
This formula describes the sources of variations of the response variable Y (i.e. growth rates and the parameters
of the Gompertz function: A, , and λ): μ is the overall mean, subscripts (i.e. i,j,k) are the different levels of
variation of each parameters. Capital letters represent random parameters whereas lower-case letters represent
fixed parameters. ɛ represents the residuals of the model.

Mémoire Final

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Mémoire Final