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Title
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An Analysis of the Effects of Eelgrass Beds on the Water Chemistry of Port Gamble, Puget Sound
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Date
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2014
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Creator
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Eng
Tejeda, Carola
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Subject
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Environmental Studies
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extracted text
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AN ANALYSIS OF THE EFFECTS OF EELGRASS BEDS ON THE
WATER CHEMISTRY
OF PORT GAMBLE, PUGET SOUND
by
Carola Tejeda
A Thesis
Submitted in partial fulfillment
of the requirements for the degree
Master of Environmental Studies
The Evergreen State College
June 2014
©2014 by Carola Tejeda. All rights reserved
This Thesis for the Master of Environmental Studies Degree
by
Carola Tejeda
has been approved for
The Evergreen State College
by
________________________
Dr. Erin Martin
Member of the Faculty
_________________________
Date
ABSTRACT
An analysis of the effects of eelgrass beds on the water chemistry
of Port Gamble, Puget Sound.
Carola Tejeda
Since the industrial revolution, our oceans have absorbed about 30% of
the atmospheric carbon dioxide (CO2) emissions. Ocean CO2 uptake has resulted
in ocean acidification, which is a progressive decrease of the pH of the world’s
oceans. Puget Sound has several physical and biogeochemical characteristics that
intensify the effects of ocean acidification.
Scientists expect that the continuous acidification of Puget Sound will
have detrimental effects on the biodiversity, the function of ecosystems, the local
economy, and possibly on human health. Some of these effects have already been
observed.
One of the proposed strategies to combat ocean acidification in Puget
Sound is the transplantation and restoration of eelgrass (Zostera marina) beds in
order to utilize them as a carbon sink. However, the carbon capture and sink
efficiency of eelgrass beds has not been directly quantified in Puget Sound.
This thesis research, which was conducted during January 2014, examined
if eelgrass beds in Port Gamble, WA could significantly increase the pH of the
water column directly above them. The experiment measured the rates of change
of pH over time as water flowed through two ecosystems: eelgrass beds and a
control consisting of mud flats with no eelgrass coverage. Given that eelgrass
takes up CO2 through photosynthesis, we hypothesized that the pH of the water
column would increase over time in the eelgrass treatment as a result of
photosynthesis rates dominating over respiration rates. Similarly, we expected the
pH of the water column in the no eelgrass treatment to decrease over time due to
respiration rates dominating over photosynthesis rates.
For this experiment, we attached a water quality monitoring sonde YSI
6600, two garmin gecko GPS instruments, and two video cameras to a floating
device, which drifted over the two studied ecosystems. The data obtained from
these instruments was used to calculate the rate of change of pH over time for
each ecosystem.
The results showed that both treatments (eelgrass and control) exhibited an
increase in the rate of change of pH over time. The control treatment showed a
more pronounced increase in the rate of change of pH over time (mean=0.00239
pH/minute) than the eelgrass treatment (mean=0.00084 pH/minute). However, a
resmpling t-test indicated that there was a no significant difference between the
rates of change of pH over time for both treatments (=0.05, 1000 trials, and
p=0.136).
The results from this experiment suggest that eelgrass beds in Port Gamble
were not capturing enough carbon during the wintertime to cause a significant
increase in the rate of change of pH over time when compared to the control
treatment.
This experiment was meant to give scientists a snapshot of the dynamic
change of pH that occurs in both ecosystems during the winter; the data presented
in this study is not enough to draw conclusions about the carbon sink capacity of
eelgrass beds in Port Gamble, Puget Sound. Further research that takes into
account variables such as depth, alkalinity, total chlorophyll, irradiance levels, as
well as the rates of photosynthesis, respiration, burial, and export, measured
during periods of 24 hours or longer, during several months of the year (or at least
seasons), are needed to draw definite conclusions about the net carbon sink
capacity of eelgrass beds in this region of Puget Sound.
TABLE OF CONTENTS
I. INTRODUCTION…………………………………………………
II. LITERATURE REVIEW………………………………………...
1
5
WHAT IS OCEAN ACIDIFICATION? ………………………………
5
RATE OF CHANGE F OCEAN CHEMISTRY RELATIVE TO
PAST EVENTS AND CURRENT CAUSES OF OCEAN
ACIDIFICATION………………………………………………...........
14
OCEAN ACIDIFICATION AND PUGET SOUND……………..........
17
a) Puget Sound description……………………………….
17
b) Upwelling……………………………………………...
20
c) Shallow carbonate saturation horizons………………...
23
d) Long residence times…………………………………..
26
e) Eutrophication…………………………………………
28
f) Freshwater inputs ……………………………………...
31
BIOLOGICAL AND ECOLOGICAL IMPLICATIONS OF OCEAN
ACIDIFICATION IN PUGET SOUND……………………….....……
31
a) Phytoplankton…………………………………………...
31
b) Animal calcifiers………………………………………
33
c) Macroalgae and seagrasses…………………………….
37
d) Ecosystems…………………………………………….
SOCIOECONOMIC IMPACTS OF OCEAN ACIDIFICATION IN
PUGET SOUND…………………………………………………..
39
42
a) Economy……………………………………………….
42
b) Tribes…………………………………………………
43
c) Human health…………………………………………..
47
EELGRASS (Zostera marina) BIOLOGY, ECOLOGY, AND
SOCIOECONIMICAL IMPORTANCE IN PUGET SOUND……….
48
iv
a) Eelgrass as a carbon sink……………………………....
48
b) Eelgrass description……………………………………
51
c) Carbon sequestration in seagrass beds………………...
52
d) Carbon burial in seagrass beds……………………..….
56
e) The effects of ocean acidification on seagrasses…..…..
64
f) Eelgrass habitat requirements……………………...…..
68
g) Distribution and density of eelgrass beds in Puget
Sound…………………………………………………..
72
h) Ecological function and socio-economical importance
of eelgrass...…………………………...……………….
75
i) Protective status of eelgrass in Washington State....…..
79
j) Suggestions for future research on eelgrass…………...
80
III. METHODS………………………………………………………
82
PURPOSE OF EXPERIMENT………………………………………...
STUDY AREA……………………………………………….............
EXPERIMENTAL DESIGN……………………………………….
82
82
86
a) Construction of drifting devices………………….........
86
b) Preparation for drifts…………………………………...
87
c) Site selection…………………………………………...
89
d) Drifts……………………………………......…….........
91
e) Video footage analysis………………………………...
93
f) Water chemistry analysis………………………………
93
g) Data organization and statistical analysis……………...
94
IV. RESULTS………………………………………………………..
100
v
V. DISCUSION OF RESULTS…………………………….……...
109
VI. REFERENCES………………………………………………….
116
VII. APPENDICES…………………………………………………...
126
APPENDIX A…………………………………………………….
APPENDIX B …………………………………………………….
APPENDIX C……………………………………………………..
126
129
131
vi
LIST OF FIGURES
Figure 1. Bjerrum plot illustrating the concentration of DIC species……... 8
Figure 2. Molecular structures of calcite and aragonite…………………... 11
Figure 3. The Time Series for Station ALOHA…………………………… 15
Figure 4. Estimated past, present, and future average oceanic pH………... 17
Figure 5. Map of Puget Sound with its respective basins…………….…… 18
Figure 6. Diagram of an upwelling current along the coast of Washington
State……………………………………………………………... 22
Figure 7. Estimated aragonite and calcite saturation horizon depths in
meters, for the Pacific Ocean for the year 2002…………………. 25
Figure 8. Locations of impaired water quality areas in Puget Sound in
2008…………………………………………………………….. 30
Figure 9. Pictures and electron micrographs of scallops grown under preindustrial, current, and future partial carbon dioxide (pCO2)
levels…………………………………………………………….. 35
Figure 10. Dissolution of pterapods shells under pCO2 levels predicted for
2100.…………………………………………………………… 36
Figure 11. Low and high carbon dioxide communities….………………... 40
Figure 12. Illustration of Zostera marina………………………………….. 51
Figure 13. Eelgrass bed on Bainbridge Island, WA.………………….…… 52
Figure 14. Global averages for carbon pools (soil organic carbon and
living biomass) of focal coastal habitats (in tones of CO2
equivalent per hectare per year)……………………………….. 60
Figure 15. Net photosynthetic rates (NPS) of two seagrass species:
Zostera marina and Thalassia testidinum and three marine
macroalgae: Ulva lactuca, Palmata palmate, and Laminaria
saccharina in natural seawater (2. 2mM DIC) following
additions of DIC.……….……………………………………… 65
vii
Figure 16. Site-level minimum and maximum Zostera marina depth
results summarized by Puget Sound regions…………………... 71
Figure 17. Distribution of eelgrass (Z. marina) in Puget Sound…………... 73
Figure 18. The eelgrass meadow: A world of microhabitats……………… 77
Figure 19. Location of Port Gamble (denoted by the red square) within
Puget Sound, Washington……………………………………...
83
Figure 20. Image of one of the drifters…………………………………….
87
Figure 21. Location of each one of the ten drifts within Port Gamble…….
90
Figure 22. Diagram of the reclassification of eelgrass treatment replicates 97
Figure 23. Diagram of the reclassification of no-eelgrass treatment
replicates………………………………………………………
97
Figure 24. Change in pH over time for all of the nine replicates in the
eelgrass treatment……………………………………………… 102
Figure 25. Average rate of change in pH/min for all the replicates in the
eelgrass treatment.…………………………………..………… 102
Figure 26. Change in pH over time for all of the eleven replicates in the
no eelgrass treatment…………………………………………... 103
Figure 27. Average rate of change in pH/min for all the replicates in the
no eelgrass treatment.………………………………………….. 103
viii
LIST OF TABLES
Table 1. Subdivisions of Puget Sound and their relative water volume of
the 168 cubic kilometers of total water volume of Puget Sound…. 19
Table 2. Calculated residence times (replacement times) for the major
subdivisions of Puget Sound during different months…….……… 27
Table 3. Average biomass per meter square of different autotrophic
populations…….…….…….…….…….…….…….…….…….….. 53
.
Table 4. Estimated production rates for Z. marina found in published
literature…….…….…….…….…….…….…….…….…….…….. 61
Table 5. Minimum and maximum estimates of the metabolic carbon sink
capacity of Z. marina, in g C m2/yr, using upper and lower
bounds of net primary production (NPP) and minimum and
maximum estimates of area occupied by Z. marina in different
Basins of Puget Sound…….…….…….…….…….…….…….….. 63
Table 6. Positive change in dissolved inorganic carbon (DIC) and pH
projected for several sites in Puget Sound based on estimates of
abundance, distribution, and regional net primary productivity
(NPP) ……………………………………………………………... 64
Table 7. Length of shoreline with eelgrass, floating and non-floating kelp
by Puget Sound counties…….…….…….…….…….…….………
74
Table 8. Budget calculations for the incorporation C, N, P and metals into
new Zostera marina leaf, rhizome, and root tissues…….…….…..
79
Table 9. Comparison between variables for eelgrass and no–eelgrass
treatment and their respective standard error of the mean (SEM) ..
104
Table 10. Average rate of change of dissolved inorganic carbon (DIC)
over time and its respective standard error of the mean (SEM) for
both
treatments…….…….…….…….…….…….…….…….…….……
106
Table 11. The average values of carbonate chemistry variables and their
respective standard error of the mean (SEM) for each treatment
calculated using the lowest total alkalinity (TA) value available
for Port Gamble…………………………………………………… 107
ix
Table 12. The average values of carbonate chemistry variables and their
respective standard error of the mean (SEM) for each treatment
calculated using the highest total alkalinity (TA) value available
for Port Gamble..….......................................................................... 108
x
LIST OF EQUATIONS
Equation 1. Chemical equations for the dissolution and dissociation of
carbon dioxide (CO2) in ocean water………………………… 7
Equation 2. Definition of pH……………………………………………..... 8
Equation 3. One of the most used definitions of total alkalinity…………... 10
Equation 4. Definition of saturation state………………………………….. 12
Equation 5. Equilibrium between the soluble and insoluble forms of
calcium carbonate at the saturation horizon………………….. 13
Equation 6. Conversion of electric voltage to pH.……………….………... 95
xi
LIST OF ABBREVIATIONS
Ca²+: calcium ion
CA: carbonic anhydrase
CaCO3:calcium carbonate
CO2: carbon dioxide
CO2(aq): aqueous carbon dioxide also known as carbonic acid
DIC: dissolved inorganic carbon
Dif: difference
gdw/m2: grams of dry weight per square meter
H+: proton or hydrogen ion
H2CO3: carbonic acid
HCO32-: carbonate ion
IPCC: Intergovernmental Panel on Climate Change
LAI: leaf area irradiance, usually measured as photosynthetic leaf area per
square meter
NECB: net ecosystem carbon balance
NPP: net primary production
pCO2: partial pressure of carbon dioxide
ppt: parts per trillion
TA: total alkalinity
tCO2 eq/ha*yr: metric tons of CO2 equivalent per hectare per year
WA- DNR: Washington State Department of Natural Resources
[ ]: brackets indicate the “concentration” of the chemical specie placed inside
the brackets.
: delta symbol, defined as the change in a particular variable.
xii
ACKNOWLEDGEMENTS
Many thanks to all those who gave me support with my thesis project. I
especially thank my thesis reader Dr. Erin Martin for encouraging me to pursue a
project related to ocean acidification and providing support, guidance, and
numerous revisions through the thesis process.
I would like to thank Washington’s Department of Natural Resources
(WA-DNR), in particular Dr. Micah Horwith for sharing guidance, inspiration,
and knowledge as to the design of this research project. I would also like to thank
Cinde Donohue for allowing me to be a part of this project and for giving me
access to their water chemistry laboratory. I also thank Dr. Jennifer Ruesnik and
Dr. Alan Trimble for their contributions to my research project.
I would like to thank my family for encouraging me to pursue this degree
and for always supporting me in my pursuit of becoming a scientist. I especially
would like to thank my parents for giving me access to good education and for
always encouraging me to follow my dreams, even when that meant moving to
another country. I also want to thank my husband for his emotional support,
edits, and excel troubleshooting sessions during the course of these last two years.
Finally, I want to thank my friends in the MES program, especially the
girls from the ShutUp and Write group, for sharing innumerable nights writing
and encouraging each other to stay awake
xiii
I. INTRODUCTION
As the global combustion of fossil fuels continues to increase
exponentially, it is estimated that the world’s oceans are absorbing one third of
the anthropogenic carbon dioxide emissions (CO2) or roughly 22 million tons of
CO2 per day (Feely, Sabine, & Fabry, 2006). The intake of massive amounts of
CO2 into the oceans is altering water chemistry, and has resulted in ocean
acidification, which is defined as a reduction in the pH of the ocean for an
extended period, typically decades of longer (IPCC, 2007). Ocean acidification is
having detrimental effects in the biodiversity and function of ecosystems
worldwide (Bloom, 2010; Feely, Klinger, Newton, & Chadsey, 2012).
Puget Sound has several biogeochemical characteristics, such as
upwelling currents and the input of nutrients through runoff, which intensify the
effects of ocean acidification (Feely et al., 2012). Local ocean acidification has
caused large-scale larval mortality in commercial oyster hatcheries, negatively
affecting the economy of the Pacific Northwest (National Research Council,
2013). Ocean acidification is also expected to reduce biodiversity of local
ecosystems as well as the amount and quality of local seafood (Branch, DeJoseph,
Ray, & Wagner, 2013). The deterioration in the nutritional quality of local
seafood could potentially affect human health (Rossoll et al., 2012).
Because ocean acidification can negatively affect Puget Sound’s
environment, economy, and human health, scientists have proposed the use of
seagrass beds as carbon sinks (Greiner, McGlathery, Gunnell, & McKee, 2013;
1
Washington State Blue Ribbon Panel on Ocean Acidification, 2012). Seagrasses
have the capacity to sequester carbon and bury it in sediments where it can be
preserved in the seabed for a period estimated to range from decades to millennia
(Dowty et al., 2005; Greiner et al., 2013).
Of the six species present in the Pacific Northwest, Zostera marina, also
known as eelgrass, is the dominant seagrass in terms of biomass and areal extent,
covering about 200 km2 of the shoreline of Puget Sound (Dowty et al., 2005;
Wyllie-Echeverria & Ackerman, 2003). Thus, Z.marina is often the proposed
specie to be used for ocean-acidification phyto-remediation projects in the Pacific
Northwest ( Shishido, 2013)
However, the effect that eelgrass beds have on water chemistry, which is
reflective of the uptake of CO2 due to photosynthesis, has not been directly
explored or quantified in the Puget Sound region. Estimates of the carbon
sequestration capacity remain theoretical and are based on calculations taking into
account reported values for density, range, distribution, and net primary
production (NPP).
This project represented an effort to explore the carbon capture potential
of local eelgrass beds. The objective was to determine if eelgrass beds in Port
Gamble could significantly alter the pH of the water over time in order to
ameliorate the effects of ocean acidification. The experiment was conducted
during the wintertime, when photosynthetic rates were the lowest in the year, to
determine if the beds had the capacity to ameliorate the effects of ocean
2
acidification all year round.
For this experiment, we attached a water quality monitoring sonde YSI
6600, two garmin gecko GPS instruments, and two video cameras to a pair of
floating devices labeled “drifters.” One drifter was placed over areas that
contained abundant cover of eelgrass and another drifter was placed over areas
that contained no visible eelgrass coverage. Each drifter was allowed to drift
following the direction of the current, while collecting data of water chemistry
parameters. The data from the drifts was used to calculate how the pH of the
water was changing over time.
The results from this project showed that during the winter, eelgrass beds
in Port Gamble were not capturing enough carbon to significantly increase the pH
of the water column over time (pH/min) (=0.005, 1000 trials, p=0.136).
These results are possibly influenced by variables that were not taken into
account in this experiment for simplicity purposes. In fact, we suspect that depth
of the water column might have influenced our results as the areas that contained
no visible eelgrass coverage had a greater increase in pH over time that the areas
that had abundant eelgrass coverage.
Further research that takes into account variables such as depth, alkalinity,
and total chlorophyll, as well as the ecosystem’s rates of photosynthesis,
respiration, burial, and export, during diel cycles and during different seasons, are
needed to determine is eelgrass beds in Port Gamble Bay are a net carbon sink.
This project, which was in collaboration with Washington State
3
Department of Natural Resources (WA-DNR), served as a pilot project to
evaluate the launch of a large-scale multi-location project that will analyze how
seagrass beds in Puget Sound modify seawater carbon chemistry to determine if
they can help mitigate the local effects of ocean acidification.
4
II. LITERATURE REVIEW
WHAT IS OCEAN ACIDIFICATION?
Over the past 250 years, humans have emitted large quantities of carbon
dioxide (CO2) to the atmosphere, increasing the concentrations of atmospheric
CO2. Atmospheric CO2 levels increased by nearly 45% from preindustrial levels
of approximately 270 ppmv (parts per million by volume) to over 400ppmv in
2013 (Bloom, 2010; NOAA, 2013b). This rate of increase, which is driven by
anthropogenic activities, is an order of magnitude faster than has occurred in
millions of years (Doney, Fabry, Feely, & Kleypas, 2009). In fact, studies of air
bubbles trapped in ice cores indicate that current atmospheric CO2 levels are the
highest that have ever been in the past 800,000 years (Doney et al., 2009). The
current accumulation of CO2 in the atmosphere is increasing the natural green
house effect and causing global climatic changes (Bloom, 2010).
Atmospheric CO2 has three fates: it can be absorbed by the terrestrial
biosphere, absorbed by the oceans, or it remains in the atmosphere. Since the year
2000, about 30% of the atmospheric CO2 emitted was absorbed by the terrestrial
biosphere, 30% was absorbed into the oceans, and the remaining 40% has
persisted in the atmosphere (Gattuso & Hansson, 2011). It is estimated that the
oceans are absorbing approximately 22 million metric tons of CO2 each day,
which corresponds to an intake of 8.03 billion metric tons each year (Feely et al.,
2006).
5
In the ocean, carbon dioxide from the atmosphere dissolves in the
seawater , following the concentration gradient, achieving equilibrium with the
concentration of the atmosphere (The Royal Society, 2005). On land, carbon
dioxide is used during photosynthesis and converted into plant tissues ( Beer et
al., 2010).
By taking in some of the atmospheric CO2, the biosphere and the oceans
mitigate the greenhouse effect. If the oceans and the biosphere did not act as
carbon sinks, the current atmospheric CO2 levels would be far above 450ppmv
(parts per million by volume) today, which would translate to a global
temperature increase of 2-3C (Doney et al., 2009). However, the biosphere’s
capability of absorbing carbon is diminishing, leaving the ocean as the main
carbon sink (Doney et al., 2009).
Ocean CO2 uptake is not benign; it causes a reduction in the ocean’s pH
and alters the biogeochemical balance of the ocean. Once the molecule of CO2
dissolves in seawater (H2O), it forms carbonic acid (H2CO3) also known as
aqueous carbon dioxide (CO2(aq)) (Bloom, 2010). Carbonic acid can dissociate to
release a proton (H+) and a bicarbonate ion (HCO3-) (Bloom, 2010). The
bicarbonate ion can subsequently dissociate to release a proton (H+) and become a
carbonate ion (CO3-2) (Equation 1) (Bloom, 2010). Carbonic acid, bicarbonate,
and carbonate ions are collectively referred as dissolved inorganic carbon species,
and the sum of these chemical species is known as total dissolved inorganic
carbon (DIC).
6
Equation 1. Chemical equations for the dissolution and dissociation of carbon dioxide
(CO2) in ocean water. Released protons shown in circles. Figure reprinted from Snow
Crab Love: what is ocean acidification? Retrieved December 15, 2013 from
http://snowcrablove.blogspot.com/2012/03/whats-ocean-acidification.html
The seawater reactions for ocean acidification can be reversible; the
direction that they follow and how much of the CO2 dissociates into its
subsequent chemical species depends on factors such as salinity, temperature, pH,
and water depth (Doney et al., 2009).
The relationship between the DIC species and pH can be modeled by
Bjerrum plot, which keeps salinity, temperature, and quantity of dissolved CO2 at
a constant value. The most common representation of a Bjerrum plot assumes
DIC=2.1mmol/kg, salinity=35, T=25C (Figure1) (Zeebe & Wolf-Gladrow,
2001).The plot shows that as the concentration of protons in seawater increases,
the protons begin reacting with the carbonate ions, consuming CO3-2 and
reforming the bicarbonate molecules. Therefore, as pH decreases the reactions
shift toward a higher percentage of bicarbonate ions and a decrease in the
percentage of carbonate ions (National Research Council, 2013). For example, at
7
pH of 8.1, approximately 90% of the inorganic carbon is in the form of
bicarbonate ion, 9% is carbonate ion, and only 1% remains as dissolved CO2, or
carbonic acid.
Figure 1. Bjerrum plot illustrating the concentration of DIC species based on pH at
DIC=2.1mmol/kg, salinity=35, T=25C.Reprinted fromOcean acidification: a millennial
challenge by M. Hoffman and H.J Shellnhuber, 2010, Energy and Environmental
Science, p1883.
Acidity is measured as the quantity of protons in the water, thus the
increase in protons from CO2 uptake results in “acidification of the ocean.”
Acidity is usually measured on the pH scale, which is an inverse, logarithmic
scale of the concentration of protons in the water.
pH = -log[H+]
Equation 2. Definition of pH
8
Therefore, an increase in the concentration of protons, also known as an
increase in acidity, is manifested as a decrease in pH. Because the pH scale is
logarithmic, a decrease in a unit of pH represents a 10-fold increase in the acidity
of the water.
Because the pH of the ocean can change temporarily due to processes like
volcanic activity and CO2 from ocean floor venting, scientists from the
Intergovernmental Panel on Climate Change (IPCC), define ocean acidification as
“a reduction in the pH of the ocean for an extended period, typically decades of
longer, which is primarily caused by the uptake of carbon dioxide from the
atmosphere” (National Research Council, 2013). Based on ice cores and boron
isotopes, scientist have calculated that since preindustrial times, the average pH in
the ocean surface has fallen from 8.21 to 8.10 which corresponds to
approximately a 30% increase in the hydrogen ion concentration (NOAA, 2013).
How fast and how much the pH of the ocean can change depends on the
alkalinity of the water. Alkalinity can be thought as a measurement of capacity of
seawater to resist changes in pH (Shigui Yuan, 2006). The total alkalinity (TA) is
defined as the number of moles of hydrogen ion equivalent to the excess of proton
acceptors (weak bases) over proton donors (weak acids) in one kilogram of water
(Dickson, Sabine, & Christian, 2007). The following expression represents the
major weak acids and weak bases in seawater:
9
TA= [HCO3-]+ 2[CO32- ]+[B(OH)4- ]+[OH-]+[HPO42]+2[PO43]+
[SiO(OH)3- ]+[NH3]+[HS-]-[H+]-[HSO4-]-[HF]-[H3PO4]
Equation 3. One of the most used definitions of total alkalinity. This definition was
published by Andrew Dickson in 1981. Equation adapted from CO2 in Seawater:
Equilibrium, Kinetics, Isotopes (p.28)by E. Zeebe and D. Wolf-Gladrow, 2001,
Copyright by Elvesier Oceanography Series.
Since ocean acidification diminishes the amount of dissolved carbonate
ions, it also limits the formation of calcium carbonate (CaCO3), which is an
important biological component. Many marine organisms build their shells and
skeletons from CaCO3 by extracting dissolved calcium (Ca²+), and carbonate
(CO32-) ions from the water and combining them to form solid crystals of calcium
carbonate (CaCO3) (Barton, Hales, Waldbusser, Langdon, & Feely, 2012). While
oceanic concentration of Ca²+ is relatively abundant, the concentration of CO32ions decreases along with pH (Barton et al., 2012). Therefore, when ocean
acidification causes a drop in carbonate ions (CO32-), this lowers the potential of
calcium (Ca²+) and carbonate (CO32-) ions to combine and form calcium carbonate
(CaCO3).
Calcium carbonate exists in different forms that are categorized by their
crystal structure and by the proportion of other elements that are sometimes
incorporated in the crystal structure (Fatherree, 2011). The two major forms of
calcium carbonate, aragonite and calcite, have different dissolution properties.
Elements present in the water can slip in from time to time and take the place of a
calcium atom when the crystal is being formed. One of the forms of calcium
10
carbonate, called calcite forms crystals with a rhombohedral pattern and
incorporates magnesium, manganese, and iron (Figure 2) (Fatherree, 2011).
Another form of calcium carbonate, called aragonite, forms crystals with an
orthorhombic pattern and typically incorporates strontium atoms (Figure 2)
(Fatherree, 2011). The structure of aragonite is less stable than that of calcite, so it
is more apt to dissolve under similar conditions. In fact, aragonite is about twice
as soluble as calcite (Barton et al., 2012). All calcifying invertebrates use one or
both of these forms of calcium carbonate to form their skeletons and certain
appendages. However, because aragonite is more prompt to dissolution, the
decrease in oceanic pH caused by ocean acidification is expected to have a greater
impact on calcifying organisms that use aragonite as a building block (Barton et
al., 2012).
Figure 2. Molecular structures of calcite and aragonite. Reprinted from William Pengelly
Cave Studies Trust. Retrived January 4, 2014
fromhttp://www.pengellytrust.org/museum/aragonite.htm.
The “potential” or “energetic favorability” for calcium and carbonate ions
11
to combine and form calcium carbonate (in the form of calcite or aragonite)is
proportional to the saturation state Ω (omega) defined by Equation 3:
Equation 4. Definition of saturation state. Equation reprinted from the “Pacific oyster,
Crassostrea gigas, shows negative correlation to naturally elevated carbon dioxide levels:
Implications for near-term ocean acidification impacts” by A. Barton, et al., 2012,
Limnology Oceanography, 57(3), p698. Copyright 2012 by the Association for the
Sciences of Limnology and Oceanography, Inc.
where the subscript f refers to the phase of the mineral being formed, Ksp,f
is the thermodynamic solubility product of that phase and the braquets indicate
the concentration of such ions (Barton et al., 2012). Essentially Ωf is a ratio of the
concentration of dissolved ions currently present in a seawater to the
concentration of dissolved ions in seawater that is saturated with respect to such
ions (Mackie, McGraw, & Hunter, 2011).
When Ωf >1, the formation of calcium carbonate structures is favored and
excess calcium carbonate precipitates from the water (Barton et al., 2012). The
value at which Ωf =1 is called that saturation horizon, at this value the
concentrations of calcium (Ca2+) and carbonate (CO32-) ions are in equilibrium
with the concentration of their calcium carbonate form (CaCO3) . When Ωf =1 the
rate of dissolution of (CaCO3) into (Ca2+) and (CO32-) is the same as the rate
precipitation of (Ca2+) and (CO32-) into (CaCO3) (Equation5).
12
At Ω=1 CaCO3 (s)
+2
Ca +
CO3-2
Equation 5. Equilibrium between the soluble and insoluble forms of calcium carbonate at
the saturation horizon. Equation adapted from “Future changes in the Baltic Sea acid–
base (pH) and oxygen balances” by A. Omsted et al.,2012, Tellus B: Chemical and
Physical Meteorology Vol 64, Retrieved from
http://www.tellusb.net/index.php/tellusb/article/view/19586/htm. Copyright 2012 by
Tellus B.
When Ωf 1 not only organisms have a hard time extracting the carbonate
ion from the water, but some of their calcium carbonate structures begin to
dissolve as the free floating protons attack the carbonate ions in their shells and
skeletons ( Feely, Sabine, Hernandez-Ayon, Ianson, & Hales, 2008). Omega (Ω)
values are different for calcite and aragonite since these crystal forms have
different solubility. Because aragonite is much more soluble than calcite, the
aragonite saturation horizon is always nearer to the surface than the calcite
saturation horizon (IPCC, 2007). In surface seawater at 25C and 35 salinity the
Ksp (calcite) ≈ 4.3 ×10–7 and Ksp (aragonite) ≈ 6.5 ×10–7 (Doug Mackie, 2011).
The reduction in oceanic pH coupled with the decrease in the percentage
of carbonate ions is changing the structure and productivity of the ocean’s biota.
Marine organisms evolved to pre-industrial pH and carbonate levels. Studies
show that since the Industrial Revolution, oceans have lost approximately 16% of
their carbonate ions, which means that calcifying organisms now have less
available carbonate to build their skeletons and shells (Barton et al., 2012). In
geological time, 250 years is a very short time to adapt to rapidly decreasing pH,
carbonate levels, and an increase in dissolved CO2. As a result, many marine
organisms are now exhibiting a decrease in calcification rates, reproduction rates,
13
abundance, productivity, and range (Portner, 2008). A small number of organisms
seem to be benefiting from the decrease in pH and high levels of CO2 (Portner,
2008). However, the fraction of organisms that are benefiting from these
chemical changes is small in comparison with the fraction of organisms that are
being negatively affected (Portner, 2008).
RATE OF CHANGE OF OCEAN CHEMISTRY RELATIVE TO PAST EVENTS
AND CURRENT CAUSES OF OCEAN ACIDIFICATION
Ocean acidification is a direct consequence of rising atmospheric CO2
levels (Doney et al., 2009). The chemistry behind ocean acidification is well
understood and the causes of ocean acidification have been verified by computer
models, hydrographic surveys, and time series data (Doney et al., 2009).
Several stations around the word have been recording how the decrease in
pH corresponds to an increase in dissolved CO2. The Hawaii Ocean Time-Series
(HOT) station ALOHA has been recording the increase in atmospheric CO2 and
the increase of oceanic dissolved CO2 since 1988 (Figure 3). Other time series
studies have confirmed this trend, studies such as the Bermuda Atlantic Station
Time-Series Study, and European Station Time-Series, have documented the
progressive decrease in oceanic pH since the 1980’s (Doney et al., 2009). All of
these time series studies indicate that the oceanic pH has been decreasing at a rate
of 0.02 units per decade (Doney et al., 2009).
14
Figure 3. The Time Series for Station ALOHA in Mauna Kea Hawaii shows that the
increase in atmospheric carbon dioxide is correlated to an increase in the dissolved CO2
in seawater (pCO2) and a decrease in the pH of the seawater (Doney et al., 2009).
Additionally, studies have confirmed that the increase in atmospheric CO2
is due to anthropogenic CO2 emissions and not due to natural causes such as an
increase in respiration rates. Fossil fuel combustion and the production of cement,
followed by deforestation, are the main causes of today’s ocean acidification
(IPCC, 2013). It has been estimated that between 1800 (the beginning of the
Industrial Revolution) and 1994 the oceans have absorbed about 48% of the total
CO2 emitted by human activities (The Royal Society, 2005).
Furthermore, computerized models that simulate the Earth’s physical
properties (ocean currents, climatic patterns, ocean depth, etc) have predicted
steep decreases in pH if we continue with the current rates of human CO2
emissions onto the future (Doney et al., 2009; National Research Council, 2013).
Computerized models predict a further decrease of 0.3–0.4 pH units, which is
15
equivalent to a 100-150% raise in acidity, by the end of this century (Doney et al.,
2009). The models also indicate that by the year 2100 the ocean pH will reach
between 7.6 and 7.9 pH units if we continue with “business as usual” (The Royal
Society, 2005).
Although fluctuations in atmospheric CO2 levels have been common
throughout Earth’s history, past increases in CO2 occurred over millions of years
and thus the rate of increase of CO2 differs greatly from the current rapid increase
driven by human activities (Figure 4) (National Research Council, 2013). In the
past, when atmospheric CO2 raised slowly, because of increased respiration rates
and volcanic activity, ocean pH and carbonate levels remained relatively stable.
This was because the slow raise in CO2 levels was balanced by the rate of
dissolution of existing calcium carbonate deposits in the ocean (thousands of
years), the weathering of terrestrial rock (hundred thousand years or more) and
release of minerals and gases from tectonic processes (millions of years)
(National Research Council, 2013). However, the current rate of dissolution of
CO2 into the ocean water is faster than the time required for natural processes to
buffer the changes in the pH of the ocean.
16
Figure 4. Estimated past, present, and future average oceanic pH. The pH in Panel A was
calculated from boron isotopes, planktonic foraminifera shells and from ice core records
of pCO2, where alkalinity, salinity, and nutrients were assumed to remain constant. In
panel B, the scale of the x-axis has been expanded to illustrate the pH trend projected
over the next century. Future pH values (average for ocean surface waters) were
calculated by assuming equilibrium with atmospheric pCO2 levels and constant
alkalinity. Future atmospheric pCO2 levels were assumed to follow the business-as-usual
CO2 emissions scenario. Reprinted from “Ocean Acidification: A National Strategy to
Meet the Challenges of a Changing Ocean” by National Research Council, 2010.
Copyright 2010 National Academies Press.
OCEAN ACIDIFICATION AND PUGET SOUND
a)
Puget Sound description
Puget Sound is an inlet of the Pacific Ocean in western Washington State.
Puget Sound is composed of a complex estuarine system of interconnected fjords
and basins comprising 2329 km2 including 168 km2 of water. There are four major
divisions in the Sound that are categorized by presence of sills, or submarine
ridges that constrict the flow of water from one subdivision of the Puget Sound
Basin to the next (Nelson, 1999). These divisions are the Main Basin, Whidbey
Basin, Southern Basin, and Hood Canal Basin. The Main Basin is comprised by
Admiralty Inlet and the Central Basin (Figure 5) (Nelson, 1999).
17
Figure 5. Map of Puget Sound with its respective basins. Reprinted from Wikimedia
Commons: Map of Puget Sound, n.d. Retrieved Octber 28, 2014 from
http://commons.wikimedia.org/wiki/File:Map-pugetsound-vector.svg
18
The relative volume and area, in each basin is illustrated in the following table
(Table 1) adapted froms Julie Nelson’s Physical and biological oceanography of
the Puget Sound (n.d).
Main
Basin
Area
Volume
Admiralty
Inlet
16%
13%
Main
Basin
Central
Basin
30%
46%
Whidbey
Basin
23%
17%
Southern
Basin
Hood
Canal
Basin
16%
9%
15%
16%
Table 1: Subdivisions of Puget Sound and their relative water volume of the 168 cubic
kilometers of total water volume of Puget Sound (Nelson, 1999).
Barring water input from precipitation, water enters Puget Sound from
river and stream runoff at the surface, and from ocean upwelling at the bottom
(Lincoln, 2000). Water mostly exits on the surface, through the seaward end via
Admiralty Inlet and the Strait of Juan de Fuca (Lincoln, 2000). Puget Sound
extends approximately 160 kilometers (100 miles) from Deception Pass in the
north to Olympia in the south (Lincoln, 2000). Its average depth is 62 meters (205
feet) and its maximum depth, off Point Jefferson between Indianola and Kingston,
is 280 meters (930 feet) (Lincoln, 2000). The depth of the Main Basin, between
the southern tip of Whidbey Island and Tacoma, Washington, is approximately
180 meters (600 feet) (Lincoln, 2000).
In Washington, the effects of ocean acidification are intensified by the
ocean circulation patterns and by anthropogenic influences. The relative
importance of these local drivers varies by location and by season (Washington
19
State Blue Ribbon Panel on Ocean Acidification, 2012). For example,
acidification along the outer coast of Washington and Puget Sound is strongly
influenced by coastal upwelling while acidification in shallow estuaries, including
those in Puget Sound, may be particularly influenced by eutrophication
(Washington State Blue Ribbon Panel on Ocean Acidification, 2012).
In Puget Sound, observations show that during the winter the waters are
well-mixed and less acidic, while summer and fall are characterized by poorlymixed, layered waters that confine corrosive waters to deeper subsurface areas
(Washington State Blue Ribbon Panel on Ocean Acidification, 2012). Many parts
of Puget Sound are corrosive to aragonite in the deeper waters. The following
section introduces the local drivers that intensify the effects of ocean acidification
in Puget Sound.
b)
Upwelling
In the Pacific Northwest, upwelling currents bring highly acidified deep
waters to the ocean’s surface (Welch, 2013). In all oceans, only the surface layer
of the ocean (down to about 100 m on average) is well mixed and in contact with
the atmosphere (The Royal Society, 2005). The CO2(gas) dissolves unto the surface
waters following the concentration gradient between the atmosphere (more CO2)
and the ocean (less CO2) (Archer, 2010). The carbonic acid formed gets
transported into the deep ocean by downwelling currents, which occur when
currents converge or when the wind drives the surface waters against the
coastline, and by the biological pump (Archer, 2010; NOAA, 2014).
20
The biological pump is the mechanism by which marine organisms cycle
oceanic carbon (Alley, 2002) Plankton and other photosynthetic organisms take
up CO2 during photosynthesis and convert it to biomass. A portion of this biomass
gets eaten by heterotrophs, which convert the carbon in the biomass into fecal
pellets that sink easily; another part of the biomass dies and sinks to the bottom of
the ocean. The fecal pellets and the dead biomass that sinks into the deep waters
decomposes thanks to the action of detritivores, releasing CO2 back into the
water (Alley, 2002; Archer, 2010). As more CO2 is transferred into deeper colder
waters, these waters become saturated with CO2 and become “acidified” (Welch,
2013). Thermohaline circulation pushes deep cold waters from the North Pacific
Ocean unto the Pacific West Coast (Hickery & Banas, 2003). Once the acidified
deep waters reach the West Coast, they resurface due to a process called
“upwelling.” In the Pacific Northwest, upwelling happens when strong northerly
winds push the surface water away from the coast (Figure 6) (NOAA, n.d.-a).
These winds transport offshore surface water southward (orange arrow in Figure
6), with a component transported away from the coastline due to the Earth’s
rotation (light green arrow) (NOAA, n.d.-a). This makes room for the deeper
colder waters to travel along the continental shelf and replace the wind-blown
waters (dark blue arrow) (Welch, 2013). Thus, upwelling currents bring acidified
waters to the surface. The water that is resurfacing right now in the Pacific
Northwest was last exposed to the atmosphere a half-century ago, when CO2
levels were much lower (Washington State Blue Ribbon Panel on Ocean
Acidification, 2012). This means that the water that will be upwelled in the future
21
will be increasingly be more corrosive.
Figure 6. Diagram of and upwelling current along the coast of Washington State.
Reprinted from Coastal Upwelling by NOAA, n.d. Retrieved from
http://www.nwfsc.noaa.gov/research/divisions/fe/estuarine/oeip/db-coastal-upwellingindex.cfm
In the Pacific Northwest, upwelling winds are prevalent in the late summer
and early fall, usually from April to November, off the Washington and Oregon
coast (Feely et al., 2012). As these winds push the surface water west and away
from the coast, water upwells into the Strait of Juan de Fuca, flowing over into
Puget Sound (Nelson, 1999; Washington State Blue Ribbon Panel on Ocean
Acidification, 2012).
Historically, upwelling currents were considered beneficial for the
economy and for the ecosystems because they brought nutrients back to the
surface. As marine organisms die, most of the carbon is consumed by other
organisms in the surface waters or released back to the atmosphere by the
decomposition process (The Royal Society, 2005). However, some of the organic
material falls as particle sediments to deep waters. Upwelling currents bring large
22
amount of this organic material, which is nutrient rich, back to the surface. This
organic material “fertilizes” the surface waters. Thus, areas with upwelling
currents have high biological productivity and are considered good fishing
grounds (Thomson, 1981). However, as human CO2 emissions increase, the
beneficial effects of upwelling currents are being overrun by the effects of ocean
acidification (Feely et al., 2002).
c)
Shallow carbonate saturation horizons
The North Pacific Ocean has a shallower saturation horizon for both
calcite and aragonite than other regions in the world. Two things account for this
difference in the calcite and aragonite horizons: the latitude, and the deep
ventilation and deep-water currents (Doney et al., 2009; Feely et al., 2002). First,
since calcium carbonate (CaCO3) solubility increases with decreasing temperature
and pressure, carbonate saturation states are lowest in cold high-latitude regions,
such as in the Pacific Northwest and at depth (Doney et al., 2009). Second, the
deep ventilation and deep-water circulation in the Pacific North permit the
accumulation of CO2 from both anthropogenic and natural sources, and as waters
become acidified, the saturation horizon lowers (Feely et al., 2002). The
difference in saturation horizons depths between the North Pacific Ocean and
other regions has been documented. For example, Feely et al (2002) determined
that the aragonite saturation horizon ranges from 120-580 meters in the North
Pacific compared to 200-1320m in the South Pacific.
Human CO2 emissions have resulted in the shoaling of the calcite and
23
aragonite horizons in all oceans; however, in the Pacific Northwest this shoaling
has been more dramatic than in other regions (Feely et al., 2008; IPCC, 2007). In
the Pacific Ocean, there is a pronounced shoaling of the aragonite and calcite
saturation states from south to north and from west to east because of the higher
total dissolved inorganic carbon (DIC) concentrations in northern and eastern
regions relative to the alkalinity concentrations (Figure 7). This means that in the
North Pacific Ocean waters are already naturally more acidic (Feely et al., 2002).
When studies compared the preindustrial saturation horizons to the present-day
saturation horizons, a steep reduction in the saturation horizon depth was detected
in the Pacific North Ocean where the horizon was reduced by 30-100 meters as
compared to 30-80 meters in the South Pacific (Feely et al., 2002).
24
Figure 7: Estimated aragonite (top) calcite (bottom) saturation horizon depths, in meters,
for the Pacific Ocean for the year 2002. Figure reprinted from “In situ calcium carbonate
dissolution in the Pacific Ocean” by Feely et al.,2002, Global Biogeochemical Cycles,
Vol 16, No 14 p91-6.
In Puget Sound, the subsurface waters from the Juan de Fuca Straight to
the Main Basin are usually undersaturated with respect to aragonite in the winter
and summer (Feely et al., 2010). In the summer, upwelling waters enter the Juan
the Fuca Straight and mix with the inland waters of Puget Sound thanks to tidal
25
currents and vertical mixing, thus decreasing Ωaragonite values. In the winter,
decreased photosynthesis and runoff lead to hypoxic conditions and thus to the
undersaturation of aragonite (Feely et al., 2010). The combination of ocean
acidification and the complex pH patterns that exist in Puget Sound, have already
caused a decrease of 0.05–0.15 pH units in surface waters and a decrease of
0.09–0.33 points in the aragonite saturation state (Busch, Harvey, & McElhany,
2013).
d)
Long residence times
An important physical characteristic of an estuary is its ability to exchange
water with the open ocean. Exchange helps cleanse the deep basins of the sound
and prevent them from becoming naturally stagnant from organic decay.
Exchange has also played a role in the transport of pollutants from Puget Sound
into the open ocean. When an estuary, like Puget Sound, has a slow “rate of
exchange” with the open ocean, acidified waters get trapped in the estuary for
long periods of time (Andutta, Ridd, Deleersnijder, & Prandle, 2013).
Residence time, is a measure of how long it takes to completely flush out
an estuary (Andutta et al., 2013). This measurement gives scientists an idea of
how long it takes for an estuary to flush out its water and replace it with new
water. In order to calculate the residence time, scientists usually use computer
models that place tracers on “virtual particles” and then run simulations to
determine of how much time it takes to flush those particles out of the system
(Andutta et al., 2013).
26
The residence time of the different basins in Puget Sound varies according
to the seasonal winds, the freshwater inputs from rivers and melted snow, the tidal
currents inside of Puget Sound, and the upwelling currents in the ocean. In
general, Puget Sound is considered to have slow residence times because most of
the water ends up recirculating multiple times inside the sound before exiting to
the ocean (Table 2) (Washington State Department of Ecology, 1986). For
example, fresh water on the surface of the Main Sub-basin takes about a week to
get from the mouth of the Dunamish River to the Admiralty sill (Entranco
Engineers, Inc, 1988). Then, due to the local current, this water spends about 10
days going back to its starting point; the surface water must make the trip twice,
on the average, before reaching the Strait of Juan de Fuca and exiting to the ocean
(Entranco Engineers, Inc, 1988).
Table 2. Calculated residence times (replacement times) for the major subdivisions of
Puget Sound during different months. Reprinted from “State of the Sound, 1988” report
by Entranco Engineers, Inc, 1988, Puget Sound Water Quality Authority.
27
e)
Eutrophication
The near surface waters of the Puget Sound are highly productive due to
nutrients delivered from upwelled waters and rivers that flow into the estuary
(Washington State Blue Ribbon Panel on Ocean Acidification, 2012).
Human activities often increase the flow of nutrients from land to marine
waters resulting in eutrophication, or the over-abundance of nutrients in the water.
Eutrophication can substantially acidify the water by causing algae blooms
(Washington State Blue Ribbon Panel on Ocean Acidification, 2012). When the
bloom ends, the algae die and sink to the bottom where they are broken down by
decomposing bacteria that consume oxygen and release large amounts of carbon
dioxide (Washington State Blue Ribbon Panel on Ocean Acidification, 2012). If
this happens, the water becomes supersaturated with carbon dioxide which leads
to a higher concentration of protons and thus a considerable decrease in pH (Abril
et al., 2003)
In Puget Sound, agricultural runoff, pollutants, and soil erosion can acidify
coastal waters at substantially higher rates than atmospheric carbon dioxide alone
(Abril et al., 2003; Feely et al., 2010; Kelly et al., 2011). Municipal and industrial
wastewater discharges can significantly reduce the pH of the water near the
discharge point, especially in poorly flushed areas (Washington State Blue
Ribbon Panel on Ocean Acidification, 2012).
Anthropogenic eutrophication has caused several “dead zones” in Puget
Sound throughout the years. A dead zone is an area that does not have enough
28
oxygen to support marine life (NOAA, 2014b). As the oxygen decreases, many
organisms die or leave the area and the zone becomes a biological dessert
(NOAA, 2014b). An area that has had dead zones repetitively through the years
is Hood Canal (Moriarty, 2011). Hood Canal is a popular waterway with a
booming year-round population on Puget Sound’s west side. The dead zones in
Hood Canal have been caused by overloaded and failing septic systems and by oil
spills. Extensive dead zones caused massive fish kills in Hood Canal in 2003,
2006, and 2010 (Moriarty, 2011). Other dead zones have appeared in other Puget
Sound locations such as: West Point in Seattle, Budd Inlet in Olympia, Penn Cove
on Whidbey Island and Bellingham Bay (Moriarty, 2011). In 2008, Washington
Department of Ecology developed a computer model and water-sampling
program to identify the anthropogenic nutrient inputs and points of low dissolved
oxygen in Puget Sound (Mohamedali, Roberts, Sackmann, & Kolosseus, 2011).
This program identified more than 100 locations where the water quality was
impaired due to low oxygen concentrations and/or high levels of pollutants
(Figure 8) (Mohamedali et al., 2011).
29
Figure 8. Locations of impaired water quality areas in Puget Sound in 2008. Reprinted
from Puget Sound Dissolved Oxygen Model Nutrient Load Summary for 1999-2008.
Washington State Department of Ecology, p1.
30
f)
Freshwater inputs
Freshwater inputs from rivers can contribute to ocean acidification by
delivering large quantities of freshwater and dissolved organic carbon. Freshwater
usually has a lower pH than saltwater; the pH of freshwater is dependent on the
dissolved minerals and organic materials that the water carries (Washington State
Blue Ribbon Panel on Ocean Acidification, 2012). pH values for freshwater range
from 6.5 to 8.5 in Puget Sound with values usually averaging around 7 pH units
(Washington State Blue Ribbon Panel on Ocean Acidification, 2012). Since
freshwater is typically more acidic than saltwater, the areas where freshwater and
seawater meet can sometimes be corrosive to calcifying organisms (Washington
State Blue Ribbon Panel on Ocean Acidification, 2012).
BIOLOGICAL AND ECOLOGICAL IMPLICATIONS OF OCEAN
ACIDIFICATION IN PUGET SOUND
a)
Phytoplankton
Phytoplankton, also known as microalgae, are microscopic, free-floating,
unicellular photosynthetic organisms (NOAA, n.d.-b). Like land plants,
phytoplankton have chlorophyll to capture sunlight and turn it into chemical
energy. Phytoplankton consumes carbon dioxide, and release oxygen. All
phytoplankton photosynthesize, but some get additional energy by consuming
other organisms (NOAA, n.d.-b). Phytoplankton are either naked, cells
surrounded by only a cell membrane, or surrounded by calcified structures in the
31
form of scales of shells (Feely et al., 2012).
Ocean acidification is expected to result in substantial alterations the
distribution, composition of phytoplankton populations (Blue Ribbon Panel on
Ocean Acidification, 2012). These effects will influence the composition and
productivity of marine ecosystems, and possibly the global cycling of carbon
(Feely et al., 2012).
Phytoplankton species have shown diverse responses to elevated values of
carbon dioxide partial pressures (pCO2) under laboratory conditions. The partial
pressure of carbon dioxide( pCO2) is defined as the pressure that would be exerted
by the molecules of carbon dioxide if all the other gases were removed from the
air (Jacob & Mickley, 2014). As pCO2 increases more CO2 dissolves in the
surface waters following the concentration gradient. Studies show that an increase
in pCO2 (and correspondingly and increase in dissolved CO2) result in increases
and decreases in growth rate (depending on the specie), change in calcification
rates, decreased size, changes in their nutritive value, and changes in the
production of toxic compounds (Feely et al., 2012). The vast taxonomic diversity
encompassed by phytoplankton contributes to the differences in responses;
genetic variability within the same specie has also been reported to influence
phytoplankton’s response to ocean acidification (Feely et al., 2012).
Phytoplankton’s possible production of toxic compounds in response to
ocean acidification is of concern because such compounds are toxic to humans
and fish. The effects of these toxins will be explored in the following section
32
titled “Socioeconomic Impacts of Ocean Acidification in Puget Sound.”
b)
Animal Calcifiers
In Puget Sound, 30 percent of marine life — some 600 species — draw
upon carbonate ions to grow (Welch, 2013). Puget Sound calcifiers include
calcifying plankton, oysters, clams, scallops, mussels, abalone, crabs, geoducks,
barnacles, sea urchins, sand dollars, sea stars, and sea cucumbers, and many other
organisms. Even some seaweeds produce calcium carbonate structures
(Washington State Blue Ribbon Panel on Ocean Acidification, 2012).
Ocean acidification is affecting shell formation rates, energy usage, and
survival of shellfish larvae (Talmage & Gobler, 2010; Waldbusser et al., 2013).
The larvae of Pacific oyster Crassostrea gigas (Waldbusser et al., 2013), northern
quahog clam Mercenaria mercenaria, and the bay scallop, Argopecten irradians
(Talmage & Gobler, 2010) have all shown increased mortality at current and
future seawater pH levels. As Waldbusser (2013), explains young shellfish larvae
do not have developed feeding organs; thus, they rely on the energy they extracted
from the egg to build their shell. For example, Pacific oyster larvae only have
about 48 hours to precipitate roughly 90 percent of their body weight. Since the
carbonate ion concentrations are very low in acidified waters, calcifiers have to
spend more energy trying to extract these ions from the water. Adult oysters and
other bivalves grow slower because of this increased energy expenditure;
however, shellfish larvae cannot delay their growth, they must build a shell before
they run out of energy. Unfortunately, many larvae do end up running out of
33
energy before they can develop a protective shell and a feeding organ
(Waldbusser et al., 2013).
Ocean acidification can limit the growth of calcifiers. Studies have shown
that planktonic calcifiers such as copepods (small crustaceans) and pterapods
(small snails) grow more slowly in acidified waters (Washington State Blue
Ribbon Panel on Ocean Acidification, 2012). The growth rates of several species
of mussels (Gaylord et al., 2011), oysters (Waldbusser et al., 2013) are also
decreased under acidified conditions.
Laboratory experiments show that bivalves exposed to current levels of
acidity develop shells that are brittle and more easily crushed and bivalves
exposed to future levels of acidity show malformations in their shells. Increased
levels of dissolved CO2 have been correlated to decrease in shell strength and
thickness in many species of bivalves (Gaylord et al., 2011; Talmage & Gobler,
2010). California mussels Mytilus californianus (Gaylord et al., 2011), northern
quahog clam, Mercenaria mercenaria, and the bay scallop, Argopecten irradians
(Talmage & Gobler, 2010) have shown that the structural integrity and strength of
their shell is compromised at concentrations lower than the present levels of
carbon dioxide (390 ppm of pCO2). For example, in 2010 Tamage and Gobler
discovered that scallops grown at pre-industrial levels (250ppm CO2) had shells
with ridges while scallops grown at current pH levels had very few ridges.
Additionally, scallops grown under future CO2 levels (750 ppm) had shells that
were riddled with holes, pockmarks, and crevices (Figure 9)
34
.
Figure 9. Pictures and electron micrographs of scallops grown under pre-industrial,
current, and future partial carbon dioxide (pCO2) levels. Under pre-industrial levels of
pCO2 (250 ppm) scallops have ridges. Under current pCO2 levels (390 ppm) scallops
begin losing their ridges. At future pCO2 levels scallops shells are comparatively small
and smooth; shells also show microscopic holes and ridges. Reprinted from “Effects of
past, present, and future ocean carbon dioxide concentrations on the growth and survival
of larval shellfish” by S. Talmage and C. Gobler, 2010 Proceedings of the National
Academy of Sciences Vol 107(40) p 17250
At high levels of ocean acidification, the exoskeleton of calcifiers begins
to dissolve. Under the pCO2 levels predicted for 2100, the shells of pterapods
completely dissolve in 45 days (Figure 10). Since pterapods are an important
food source for salmon, seabirds, and whales, the increased dissolution of
pterapods shells is expected to disturb the food web of Puget Sound (Washington
35
State Blue Ribbon Panel on Ocean Acidification, 2012)
Figure 10. Dissolution of pterapods shells under pCO2 levels predicted for 2100.
Reprinted from Acid Threat by J.S. Holland, 2007. Retrieved from
http://ngm.nationalgeographic.com/2007/11/marine-miniatures/acid-threat-text.
Copyright by National Geographic.
These changes in organisms shell’s morphology and functionality result in
decrease survival rates. The thinner, frailer shells make individuals more subject
to predation and environmental stressors. Mollusks with thinner shells are more
prone to predation by crustaceans and carnivorous snails (Gaylord et al., 2011).
Additionally, the decrease in shell thickness and strength decreases the odds of
organisms surviving the crushing wave action of storms and desiccation caused
by tides (Gaylord et al., 2011).
Ocean acidification also has ecological implications in Puget Sound.
Calcifiers provide habitat, shelter, and/or food to other organism in the food web;
a decline of calcifiers has rippling effects through the ecosystem. For example,
rockfish and sharks rely on the habitats created by the deep-water corals of the
Olympic Coast (Washington State Blue Ribbon Panel on Ocean Acidification,
2012). Yet, such corals are at the frontier of ocean acidification because cold
waters have lower pH values than the water that bathes shallow reefs (Guinotte et
36
al., 2006). In fact, cold-water corals in the North Pacific are thought to be
surviving at the marginal levels of the aragonite horizon; any further decrease in
pH and these cold water corals will begin dissolving (Guinotte et al., 2006).
c)
Macroalagae and seagrasses
Marine macroalgae (seaweeds) and seagrasses are benthic multicellular
photosynthetic organisms (Feely et al., 2012). As phytoplankton, macroalgae and
seagrasses use the energy from the sun to convert carbon into biomass, releasing
oxygen in the process (Feely et al., 2012). Macroalgae belong to the algae family
and are structurally much simpler than plants; they lack specialized organelles and
cells found in plants. Most species of macroalagae are uncalcified but a few
species are calcifiers. Seagrasses are aquatic flowering plants that have long and
narrow leaves and grow on meadows that resemble as grassland; thus these
marine plants were named “seagrasses” because they superficially resemble the
terrestrial grasses (Larkum, Orth, & Duarte, 2006).
Macroalagae are a very diverse group so their response to ocean
acidification is expected to vary from specie to specie (Feely et al., 2012).
Predictions of their future response to ocean acidification are based on current
observed trends and on their physiological requirements (Feely et al., 2012).
Studies show that the relative abundance of non-calcifying versus
calcifying macroalgae will change with increasing acidification. Porzio et al
(2011) studied the responses of 101 species of macroalgae from around the world
to a natural decrease in seawater pH from 8.1 to 7.8 units. This study reported that
37
there was an overall 5% decrease on macroalgae species richness as the pH
decreased to 7.8. They also found that as the pH dwindled, the abundance of
calcifying macroalgae decreased while the abundance of non-calcifying algae
increased. When the pH reached 6.7, where carbonate saturation levels Ω 1,
calcareous species were absent and there was a 72% reduction in species richness.
Under these high CO2 conditions, Porzio et al. observed an overall decrease in the
reproduction rates of most species, with a few exceptions that showed enhanced
reproduction rates (Porzio, Buia, & Hall-Spencer, 2011).
Studies show that non-calcifying macroalagae and seagrasses have the
potential to increase photosynthesis under acidifying conditions (Feely et al.,
2012). According to Washington’s Blue Ribbon Panel on Ocean Acidification
(2012), most seagrasses and macroalgae are able to use bicarbonate (HCO3) in
addition to CO2 to fuel photosynthesis. Studies have shown that the noncalcifying algae, unaffected by reductions in carbonate ions, have the potential to
increase their growth and photosynthesis under high HCO3 conditions. Noncalcifying macroalgae and seagrasses also appear to be robust enough to
withstand the reduction in seawater pH (Feely et al., 2012).
However, a study by Arnold et al. (2012) indicates than under elevated
pCO2, some seagrasses lose the ability to produce phenolic compounds that
protect these plants against herbivores, pathogens and, damage by UV radiation.
These effects and implications of ocean acidification on seagrasses will be
discussed under the section titled “Eelgrass (Zostera marina) Biology, Ecology
and socioeconimical Importance in Puget Sound”, which appears later in this
38
chapter (Arnold et al., 2012).
d)
Ecosystems
The ecological implications of ocean acidification are critical. Scientist
predict that at the pH forecasted for the year 2100, ecosystems will have a
significant reduction in biodiversity (Washington State Blue Ribbon Panel on
Ocean Acidification, 2012). Such predictions are based on laboratory experiments
that simulate future pH levels, current observations in places with high carbon
dioxide levels, and on paleontological research. Scientists have discovered a few
places where carbon dioxide levels are naturally high, thanks to under-sea volcano
vents. By studying these “natural laboratories” scientist have gained insight on
what ecosystems will look like under future carbon dioxide levels (Riebesell,
2008; Washington State Blue Ribbon Panel on Ocean Acidification, 2012). As
predicted, these studies confirm that at future ocean acidification conditions (pH <
7.5) there is a pronounced loss of biodiversity no indication of adaptation or
replacement of sensitive species by others capable of filling the same ecological
niche (Figure 11) (Riebesell, 2008). Paleontological studies confirm this
conclusion, research on fossils and chemicals in ancient rocks indicates that past
ocean acidification events (due to natural causes such as volcanic eruptions) have
been accompanied by major marine extinctions (Washington State Blue Ribbon
Panel on Ocean Acidification, 2012).
39
Figure 11. Low and high carbon dioxide communities. The figure on the left shows a
diverse marine ecosystem in normal (low) carbon dioxide conditions (mean pH 8.2). The
photo on the right shows a high carbon dioxide ecosystem (pH 7.8) in the volcanic undersea vents of Ischia Island in Italy. The high carbon dioxide ecosystem has less
biodiversity than the low carbon dioxide ecosystem. Reprinted from Ocean Acidification:
From Knowledge to Action, Washington State’s Strategic Response by Washington State
Blue Ribbon Panel on Ocean Acidification, 2012, Washington Department of Ecology.
Copyright by David Littswager (left) and Luca Tiberti (right).
A study done by Busch et al. (2013) showed that ocean acidification will
result in drastic changes to the structure of Puget Sound’s food web. This study
was based on a computer simulation model of Puget Sound’s food web. In this
simulation, scientists removed or decreased the abundance of various functional
groups of organisms, based on the current and predicted effects of ocean
acidification (Busch et al., 2013). The computer analysis showed that ocean
acidification resulted in increases in the biomass of some groups and decreases in
other groups. For example, a decrease in the population of copepods (predator)
resulted in an increase in the population of microzooplankton (prey) and a
decrease in the population of herring (feeds on copepods) (Busch et al., 2013). A
combined scenario, considering multiple decreases in the population of functional
groups affected by ocean acidification, resulted in an overall decrease in the
40
amount of seafood that the food web can produce. For example, a moderate
scenario assuming a 25% decrease in the productivity of Puget Sound’s
ecosystems, showed that the following populations will decrease: shrimp (3%
decrease), cancer crab (12%), bivalves ( 2%) ,salmon (3%), herring (3%), salmon,
rockfish (2%) , sea urchin (1%), among other species (Busch et al., 2013).
Ocean acidification is expected to cause a shift from calcifying benthic
communities to plant-based communities. Since reproductive success of so many
calcifying species will be impaired, there will be a community shift from
calcifier-based ecosystems, such as coral reefs, to non-calcifying based
ecosystems like seaweeds and seagrass beds (Washington State Blue Ribbon
Panel on Ocean Acidification, 2012).
However, non-calcifying autotroph based food webs are not immune to
the effects of ocean acidification. Several studies have shown that ocean
acidification reduces the nutrient content of calcifying and non-calcifying
photosynthetic organisms, inducing food quality deterioration through the food
web (Bellerby et al., 2008; Rossoll et al., 2012; Urabe, Togari, & Elser, 2003).
Increased CO2 stimulates carbon fixation in photosynthetic organisms thereby
reducing the nutrient content relative to carbon (Bellerby et al., 2008; Urabe et al.,
2003). Other studies, point towards an impact in the synthesis of fatty acids by
phytoplankton (Rossoll et al., 2012). Fatty acids play an important role in the
development, growth and reproduction of heterotrophs, who can only acquire the
nutrient through their diet (Rossoll et al., 2012). A decrease in extracellular pH
can affect the intracellular processes of phytoplankton, which control the
41
enzymatic activity for the production of fatty acids (Rossoll et al., 2012). Thus, a
decrease in the phytoplankton’s production of fatty acids is expected to constrain
the development, growth and reproduction rates of heterotrophic organisms
throughout the food web (Rossoll et al., 2012).
SOCIECONOMIC IMPACTS OF OCEAN ACIDIFICATION IN PUGET SOUND
a)
Economy
Washington State is the largest producer of farmed shellfish in the U.S,
with more than 300 farms accounting for 25% of the total domestic production by
weight, and an annual revenue of about $107 million (Pacific Shellfish Institute,
2013). Overall, Washington’s seafood industry generates over 42,000 jobs in
Washington and contributes at least $1.7 billion to gross state product through
profits and employment at neighborhood seafood restaurants (Washington State
Blue Ribbon Panel on Ocean Acidification, 2012).
The Pacific Northwest shellfish industry has experienced major failures in
its oyster hatcheries because the decrease in pH has increased oyster larvae
mortality (National Research Council, 2013). Around 2005, Puget Sound oyster
farmers began noticing elevated larvae mortality rates during certain parts of the
year, namely shortly after the prevailing wind switched and caused seasonal
upwellings along the Washington coast. Initially, the farmers thought that the
deaths were due to a pathogenic bacterium, Vibrio tubiashii, so they invested in
expensive filtration systems that would remove the pathogen from the water.
42
However, the oyster larvae continued dying at an alarming rate. Closer
examination of the dead larvae revealed that they were unable to form the
required shell studies confirmed that the water being pumped into the hatcheries
was acidified (Washington State Blue Ribbon Panel on Ocean Acidification,
2012). In order to utilize water that is suitable for growing oysters, oyster farmers
have begun “buffering” the water in the hatcheries by adding antacid substances
or more calcium carbonate (Washington State Blue Ribbon Panel on Ocean
Acidification, 2012). Antiacid substances and calcium carbonate represent an
extra cost for hatcheries and therefore a increased cost for the oyster consumer.
In order to guard against ocean acidification effects, some Washington
Oyster farmers have relocated their hatchery sites away from Puget Sound.
Goose Point Oysters and Taylor Shellfish have established hatcheries in Hawaii
where they raise their younglings and then ship them back to Washington for the
remainder of their growth cycle. Relocating hatcheries to Hawaii means less jobs
in Washington State; if more hatcheries follow this relocation pattern, the state
economy could suffer.
b)
Tribes
Ocean acidification has also cultural implications. Among Puget Sound’s
population the Native American community has been affected the hardest by the
effects of ocean acidification. Tribes harvest shellfish for subsistence and
ceremonial purposes. In fact, almost all of the commercial wild clam fisheries in
Puget Sound are tribal (Washington State Blue Ribbon Panel on Ocean
43
Acidification, 2012).
The predicted decrease in the abundance of pterapods is expected to result
to have a negative impact on the abundance of fish species that feed on them, such
as pink salmon, mackerel, and herring. These fish species are an important food
source for Washington’s tribes (Washington State Blue Ribbon Panel on Ocean
Acidification, 2012).
The possible decline of salmon is of special importance because in
addition of being a food source, it also has spiritual and cultural significance for
the Pacific Northwest Tribes. For example, many tribes celebrate the annual
salmon return as this event signifies renewal and continuation of life. Salmon is
also offered as one of the traditional fish foods during religious ceremonies and
rituals. One creation legend teaches that salmon is one of the “First Foods”:
When the Creator was preparing to bring humans onto the earth, He
called a grand council of all the animal people, plant people, and
everything else. In those days, the animals and plants were more like
people because they could talk. He asked each one to give a gift to the
humans—a gift to help them survive, since humans were pitiful and would
die without help. The first to come forward was Salmon. He gave the
humans his body for food. The second to give a gift was Water. She
promised to be the home to the salmon. After that, everyone else gave the
humans a gift, but it was special that the first to give their gifts were
Salmon and Water. When the humans finally arrived, the Creator took
away the animals’ power of speech and gave it to the humans. He told the
humans that since the animals could no longer speak for themselves, it
was a human responsibility to speak for the animals. To this day, Salmon
and Water are always served first at tribal feasts to remember the story
and honor the First Foods.(The Columbia River Inter-tribal Fish
Comission, 2014)
44
Salmon is also tied to the tribes’ sense of place and history. They believe
that the creator placed them in the locations where the salmon would return and
that they are obliged to remain and to protect these places. Additionally,
Northwest Tribes were able to flourish thanks to trade economies based on
salmon. Many of the ancient Indian trade routes connected salmon fisheries to
towns. Thus, since ancient times salmon has shaped the lives of the Northwest
tribes and a decline in salmon population would impacts the tribes sense of place
and identity (Columbia River Intertribal Fish Comission, n.d.)
“Without salmon returning to our rivers and streams, we would cease to
be Indian people”
-Indian proverb (Columbia River Intertribal Fish
Comission, n.d.)
“My strength is from the fish; my blood is from the fish, from the roots and
berries. The fish and game are the essence of my life. I was not brought
from a foreign country and did not come here. I was put here by the
Creator”
-Chief Weninock, Yakama, 1915 (Columbia River
Intertribal Fish Comission, n.d.)
A major concern for the tribes is that ocean acidification can be
exacerbated by other climate change variables such as an increase in ocean water
temperatures, eutrophication and changes in rainfall patterns. Certain tribal areas
45
are prone to low levels of oxygen which has historically caused fish and shellfish
mortalities. Now these tribes are facing the double threat of dealing with hypoxia
and ocean acidification at the same time. For example, since 2006, Quinault have
documented the mortality of thousands fish and crab during the late summer
months due to low oxygen conditions (Handsen Terri, 2014). The threat of ocean
acidification combining with low oxygen zones is a concern for the Quinault who
are currently working with University of Washington and NOAA scientists
determined these hypoxia events were also related to ocean acidification
(Handsen Terri, 2014).
Because ocean acidification along with other climate change factors will
affect the tribes’ natural and cultural resources, several Northwest tribes have
already devised climate adaptation plans that include measures to mitigate the
effects of ocean acidification. For example, the Jamestown Sk’lallam Tribe
created a climate change working group that devised strategies to combat the
decline in salmon and shellfish, their strategies include habitat restoration,
employing monitoring programs to ensure sustainable harvesting, restoring the
natural habitats, monitoring water quality, rebuilding stocks and transplanting
shellfish to areas that are more suitable for reproductive success (Jamestown
Sk’lallam Tribe, 2013). In a way tribes are at the forefront of the research and
mitigation strategies for ocean acidification because tribes practice the seventh
generation sustainability principle, which implies that they consider how the next
seven generation will be affected by the decisions they make today. Thus, many
of their mitigation plans consider how the environment will change during the
46
next seven generations (Columbia River Intertribal Fish Comission, n.d.)
In 2012 the Hoh, Makah and Quileute tribes and the Quinault Indian
Nation organized the inaugural First Stewards symposium, a national event that
examined the impact of climate change on indigenous coastal cultures. This event,
hosted in Washington D.C, consisted or a dialogue between native leaders,
climate scientists, policy-makers and non-government organizations, with the
objective of devising adaptations and mitigation strategies to cope with climate
change and ocean acidification. This dialogue explored solutions based on
scientific research as well as in traditional ecological knowledge.
The First Stewards symposiums continue to be organized every year and
the northwest tribes continue to be at the forefront of the mitigation strategies
required to combat ocean acidification.
c)
Human Health
Recent research has demonstrated that the toxicity of some toxin forming
phytoplankton increases under conditions of high CO2 in seawater. These
phytoplankton can produce harmful algae blooms that are characterized by rapid
growth and entrainment of toxins. Such toxins are noxious to humans and fish.
When shellfish consume this phytoplankton, they too become toxic to humans
(Brown, 2012). In the past, harmful algae blooms have resulted in the closure of
recreational and commercial fisheries in Puget Sound. Three species of
phytoplankton (two species of Pseudonitzchia and one of Karlodinium) were
shown to produce more toxins when grown in seawater with high CO2
47
concentrations. These findings suggest that harmful algae blooms inside Puget
Sound could become more toxic under conditions of ocean acidification, with
consequent impacts on food webs, human health, and economy (Brown, 2012;
Feely et al., 2012)
Additionally, the predicted deterioration of nutrient content thorough food
webs and the direct impacts on commercially harvested species caused by ocean
acidification, is expected to reduce the nutritional quality and quantity of seafood
(Branch et al., 2013; Rossoll et al., 2012). As explained in previous sections,
ocean acidification might impair seafood production by changing the biochemical
composition of algae and its transfer to higher trophic levels and by impacting the
metabolism of seafood species (Rossoll et al., 2012). In the future, human
population growth will translate to an increased demand for protein, yet fish and
mollusk protein quantities are expected to decrease under ocean acidification
(Branch et al., 2013). Thus, human diets will be affected and humans will either
be forced to find other sources of protein or their health will bear the effects of an
improper nutrition.
EELGRASS (Zostera marina) BIOLOGY, ECOLOGY, AND
SOCIOECONIMICAL IMPORTANCE IN PUGET SOUND
a)
Eelgrass as a carbon sink
Seagrasses are flowering plants (angiosperms) adapted to the marine
environment that have a grass-like appearance (Larkum et al., 2006; Mumford,
2007). They comprise four marine angiosperm families, 12 genera, and 58 known
48
species (Hartog & Kuo, 2006). All seagrass species evolved from land plants that
returned to the sea approximately 100 million years ago (Touchette & Burkholder,
2000)
Seagrass beds, are one of the most productive ecosystems on Earth and
have capacity to sequester sizable amounts of carbon and store it in their
sediments (Duarte, Kennedy, Marbà, & Hendriks, 2013). It is estimated that even
though seagrass meadows occupy less than 0.1 percent of the world's oceans, they
are responsible for 10-20 percent of all carbon buried annually in the sea (Duarte
et al., 2011; Greiner et al., 2013).
Due to the noticeable carbon sink capacity of seagrass beds, researchers
have proposed that strategies based on the conservation and reforestation of
seagrass beds, along with salt-marshes and mangrove forests, could be used to
mitigate the effects of climate change and ocean acidification by storing carbon
in their sediments ( Duarte et al., 2011).
In the Pacific Northwest, the most abundant seagrass specie is Zostera
marina, a native species also known as eelgrass (S. Beer & Rehnberg, 1997).
While only six species of seagrass are present in the Pacific Northwest, Z. marina
is the dominant seagrass in terms of biomass and areal extent, stretching from
southeastern Alaska to Baja California, Mexico (Wyllie-Echeverria & Ackerman,
2003). In Washington State, Z. marina beds represent 37% of the shoreline
vegetation (Dowty et al., 2005); while in Puget Sound, eelgrass beds are widely
distributed covering about 200 km2 of the shoreline .
49
Due to its due to its abundance and prevalence in the inland waters of
Puget Sound, Z. marina, has the potential to serve as a local carbon sink, thus
contributing to ameliorate the local effects of ocean acidification (Shishido,
2013). In 2012, the Washington State Blue Ribbon Panel on Ocean Acidification,
recognizing the importance of eelgrass, stated the need to “preserve Washington’s
existing native seagrass and kelp populations and, where possible, restore these
populations ” in an attempt mitigate and adapt to the effects of ocean acidification
(Washington State Blue Ribbon Panel on Ocean Acidification, 2012a, p. 30,
Action 6.3.1). Additionally, the panel also recommended the development of
“vegetation-based systems of remediation for use in upland habitats and in
shellfish areas” (Washington State Blue Ribbon Panel on Ocean Acidification,
2012a, p. 30, Action 6.1.1).
These phyto-remediation strategies have been hindered by the gaps in our
knowledge of the mechanisms and rates of carbon sequestration and carbon burial
of local seagrasses, particularly of eelgrass (Duarte et al., 2013). Consequently,
this thesis project represents an attempt to quantify the effectiveness of local
eelgrass beds in mitigating ocean acidification.
The following section represents a summary of the published research on
the habitat requirements of eelgrass, and on the presumed mechanisms of carbon
sequestration and burial.
50
b)
Eelgrass description
Zostera marina plants are easily recognizable. They have long, narrow,
ligulate leaves about 31 to 53 centimeters long (12 to 20 inches) with parallel
edges and three veins running along their length (Figure 12 and 13) (Larkum et
al., 2006). The leaves are usually green, but when cast up on the shore they turn
black, and eventually grayish-white when bleached by the sun (Larkum et al.,
2006). Blade width varies with depth. The blades from deeper plants are one to
two centimeters wide, while intertidal plants are two to five millimeters wide
(Mumford, 2007). Leaves emerge from a perennial creeping rhizome (Larkum et
al., 2006). Roots from the rhizome serve as the main means of nutrient uptake
(Mumford, 2007).
Figure 12. Illustration of Zostera marina. Reprinted from Bilder Ur Nordens Flora by
C.A.M Lindaman 1905. Kessinger Publishing, LLC. Copyright 2010 by Kessinger
Publishing, LL
51
Figure 13. Eelgrass bed on Bainbridge Island, WA. Reprinted from USGS Multimedia
Gallery by David Ayers, 2012. Retrieved from
http://gallery.usgs.gov/photos/11_07_2012_lPGs3WU321_11_07_2012_1#.VF11sPmor0
t
c)
Carbon sequestration in seagrass beds
Seagrasses rank amongst the most productive populations on the biosphere
(Duarte and Chiscano, 1999). Seagrasses only occupy 0.15% of the ocean surface,
yet they contribute to an estimated 1% of the primary net production of the global
oceans (Duarte & Chiscano, 1999). On average, net primary production for a
square meter area covered by seagrass is about 461 gdw/ m2 (grams of dry weight
per meter square) .This means that seagrasses are about 11 times more productive,
in terms of biomass, than macroalgae whose biomass is about 40.7 gdw/ m2
(Table 3) (Duarte and Chiscano, 1999). The productivity of Z. marina is
dependent upon the environmental conditions of each area, but estimates of its net
primary productivity (NPP) range from about 200 to 341.82 g C/m2 *yr (MarikoShishido, 2013)
52
Table 3. Average biomass per meter square of different autotrophic populations. Adapted
from “Seagrass biomass and production: a reassessment” By C.M Duarte & C.L
Chiscano, 1999, Aquatic Botany, 65(4).
In addition to the high productivity of seagrass plants, these plants and
sediment beds usually host a variety of associated microalgae and phytoplankton
that also contribute significantly to total ecosystem production (Sybill Jaschinski,
Daniela C. Brepohl, & Ulrich Sommer, 2008). Thus, even though primary
production is dominated by seagrasses, other organisms such as epiphytes, red
algae, sand microflora, and phytoplankton inhabiting the same ecosystem can also
act as carbons sinks (Sybill Jaschinski et al., 2008) . Seagrass themselves
contribute to a modest 1% of the net primary production, yet their ecosystem
production is estimated to be 12% of that of the global ocean (Duarte & Chiscano,
1999).
53
Most seagrasses, including Z. marina, and other marine macroalgae can
obtain energy from two forms of DIC: aqueous carbon dioxide CO2(aq) and
bicarbonate (HCO3-) (Koch, Bowes, Ross, & Zhang, 2013; Palacios &
Zimmerman, 2007). CO2(aq) is absorbed through passive diffusion, while (HCO3-)
is dehydrated (either internally or externally) and converted back into CO2(aq) for
assimilation (S. Beer & Rehnberg, 1997; Palacios & Zimmerman, 2007).
Eelgrass, as most marine macro-autotrophs, actively secrete hydrogen ions (H+ )
into localized regions of the surface of its leaves, to lower the pH and promote the
dehydration of HCO3- (Carr & Axelsson, 2008; Koch et al., 2013). Z. marina, and
other seagrass species also secrete carbonic anhydrase (CA) from their leaves. CA
is an enzyme that catalyzes the interconversion of HCO3- to CO2(aq); this enzyme
is pH dependent and most effective at low pH values (Koch et al., 2013). It is
worth to note that the reaction catalyzed by CA is reversible and can change
direction under high pH values (Koch et al., 2013). The CO2(aq) formed in these
acid regions of the leaf might be taken up actively, but more likely, it just diffuses
through the plasma membrane (Carr & Axelsson, 2008). CO2(aq) is largely
absorbed by the leaves of seagrasses with a small uptake happening in the roots
and rhizomes (S. Beer, 1989).
The ability of seagrasses and other marine macroalgae to utilize HCO3- is
advantageous as [HCO3-] currently represents about 88% of the total DIC content
of seawater (Palacios & Zimmerman, 2007). Furthermore, because seagrasses
and macroalgae have a higher affinity for CO2(aq) than HCO3-, ocean acidification
is expected to enhance their competitive advantage (Koch et al., 2013). Since
54
seagrasses and macro algae absorb CO2(aq) through passive diffusion and this
process requires less energy than the dehydration or active transport of HCO3-,
these organisms have a higher photosynthetic affinity for CO2(aq) than for HCO3(Koch et al., 2013). It is estimated that marine macroalgae fulfill 80-90% of their
carbon requirements from the dehydration of HCO3-, while only 10% of their
carbon requirements are achieved through the absorption of CO2(aq) (S. Beer &
Koch, 1996; Palacios & Zimmerman, 2007). In contrast, seagrasses fulfill 50% of
their carbon requirements by dehydrating HCO3-, while utilizing CO2(aq) to carry
out the remaining 50% of their carbon requirements (Palacios & Zimmerman,
2007). Consequently, the predicted increase of CO2(aq) due to ocean acidification,
will likely result in a greater competitive advantage for seagrasses than for
macroalgae (S. Beer & Koch, 1996). As the atmospheric [CO2] continues to rise,
by the year 2100, [CO2(aq)] in the ocean will increase by more than 250%, while
[HCO3-] will only increase by 24%, and [CO32-] will decrease by more than 50%
(Koch et al., 2013). Even though in absolute terms (mol/kg) HCO3- will still be
the most abundant specie of DIC, this increase in [CO2(aq)] will reduce the
photosynthetic energy expenditure for seagrasses and macroalgae, which will
probably result in an increase of biomass (Koch et al., 2013). Evidence of this
increase in biomass will be presented later in this chapter.
Once CO2(aq) enters the eelgrass plant, it is photosynthesized using the C3
pathway. Most seagrasses and macroalgae utilize this pathway; however, a few
seagrasses, such as Cimodocea nodosa utilize the C4 pathway (Koch et al., 2013).
High [CO2 ] benefits C3 photosynthesis because high levels of CO2 minimize
55
photorespiration in C3 plants, thus increasing their photosynthetic efficiency
(Koch et al., 2013). In contrast, C4 photosynthesis is saturated at current
atmospheric [CO2], thus C4 plants are operating at their maximum efficiency, and
further increases in [CO2] will not result in higher rates of photosynthesis (Koch
et al., 2013). Additionally, C4 photosynthesis is more energy intensive than C3
photosynthesis, hence C4 plants show less productivity at high [CO2] than C3
plants.
d)
Carbon burial in seagrass beds
The high rates of carbon burial in seagrass beds are due to their high
primary production, their capacity to capture particles from the water column and
deposit them in soils, and their low rate of herbivory (Fourqurean et al., 2012).
Seagrasses develop lush canopies that slow the water flow and trap
sediments and organic matter suspended in the water (Fourqurean et al., 2012).
Depending on shoot density and seagrass species, the flow reduction due to
current deflection by the canopy ranges from 2- to more than10-fold compared to
water flow outside the seagrass bed (Duarte et al., 2013). Seagrass canopies can
also dampen the waves by creating friction against incoming water (Duarte et al.,
2013; van Katwijk, Bos, Hermus, & Suykerbuyk, 2010). This friction reduces the
wave size and leads to a wave induced transport of particles known as Stokes
Drift, which further contributes to the deposition of sediments and organic matter
in seagrass beds (Duarte et al., 2013). Filtering organisms living on the leaves of
seagrasses also contribute to trapping and depositing particles in the bed (Marba,
56
2009). Seagrass meadows retain the particles and sediments they trap because the
canopy prevents their re-suspension, and because the sediments are anchored by a
dense network of clonal rhizomes and roots that can extend several meters below
the ground (Fourqurean et al., 2012; Marba, 2009). In fact, two thirds of the
biomass of seagrasses is buried in soil in the form of rhizomes and roots
(Fourqurean et al., 2012).
Due to the typically high sedimentation rates in seagrass beds, some of the
belowground biomass and the dying annual tissues are progressively buried
(Duarte et al., 2010; Mateo, Romero, Pérez, Littler, & Littler, 1997). The amount
of biomass that is buried can be quite large thanks to low herbivory rates in
seagrasses (Duarte et al., 2010). Duarte and Cebrian (1996) report that only about
18% of the seagrass biomass is consumed by herbivores; in contrast, about 33%
of the biomass of macroalgae is consumed by herbivores.
The low herbivory rates are due to nutrient limited tissues, that are hard to
digest or/and contain unpalatable and, in some cases, toxic compounds (Duarte et
al., 2010; Thayer, Bjorndal, Ogden, Williams, & Zieman, 1984). Seagrasses have
high C:N:P (carbon, nitrogen, phosphorous) ratios, which means that these plants
have a low nutrient content relative to their fiber content. Gattuso, Frankignoulle,
& Wollast, (1998) report that these ratios range from 204:4:1 to 3550:61:1, with
an average of 474:24:1. One study by Duarte (1990) reports a C:N:P ratio of
255:15:1 for Z. marina (Kaldy, 2006). The content of nitrogen (protein) tends to
decline with the age of the leaf, making mature leaves less nutritious (Thayer et
al., 1984). Hence, the relatively low content of nitrogen and phosphorous, coupled
57
with the presence of relatively high amounts of structural carbohydrates, such as
lignin, which have classically been viewed as indigestible to many herbivores,
limit the amount of predation on seagrasses (Thayer et al., 1984).
Many species of seagrass also contain other types of phenols, sulphated
phenols, and sulphated flavones that are toxic, unpalatable, prevent herbivore
settlement, and/or bind to proteins and carbohydrates making them impossible to
digest (Thayer et al., 1984). Zostera marina contains zosteric acid and caffeic
acid, which prevent the settlement of marine bacteria, algae, barnacles, and tube
worms that can pray on its tissues or disrupt their clonal network (Buchsbaum,
1990; Grignon-Dubois, 2010). Z. marina also contains rosmarinic acid, which has
antibacterial, antifungal and antiviral properties (Grignon-Dubois, 2010).
Additionally, seagrasses have relatively high ash (mineral) content (varying
according to specie and location) which is acerbic to herbivores (Thayer et al.,
1984). Thus in addition to having a high amount of fiber compared to a low
concentration of nutrients, seagrasses contain a wide variety of chemical
substances that deter predation.
Due to their high sedimentation rates, abundant underground biomass, and
low rates of herbivory, seagrass beds build thick deposits of carbon (both
autochthonous and allochthonous) that grow at a rate of 1mm per year (Duarte et
al., 2011). The estimated concentration of organic carbon for these deposits is
around 4.1% (Fourqurean et al., 2012) .
However, high organic carbon burial rates do not guarantee a high carbon
58
sink capacity. In order for seagrass beds to be considered effective carbon sinks,
the organic carbon must remain trapped in their sediments for a period ranging
from centuries to millennia (Duarte et al., 2013). As Duarte et al. (2011) explain,
seagrasses have several mechanisms that allow for the millenary preservation of
carbon. First, the low nitrogen and phosphorous content in seagrass tissues makes
them a poor substrate to support microbial growth and therefore the tissues are
recalcitrant to decomposition. Second, seagrass sediments are often anoxic, which
leads to inefficient microbial metabolism, thus favoring the preservation of buried
seagrass tissues. The anoxic conditions are a consequence of the constant
deposition of sediments and particulates in seagrass beds. Third, the rhizomes and
the wave dissipation action of the canopy prevent the resuspension of buried
carbon. Finally, an obvious reason for the preservation of tissues is that
underwater sediments are free of fires, which are responsible for high proportion
of the CO2 that is released from land carbon sinks (Duarte et al., 2013). As Duarte
states, “The combination of all these factors leads to high carbon preservation in
seagrass sediments, which together with high metabolic inputs and particle
trapping rates explain the role of seagrass meadows as intense carbon sinks in
the biosphere”(Duarte et al., 2013).
Coastal vegetated ecosystems store more carbon in their sediments than
tropical forest do in their soils. Estimations point that seagrasses are responsible
10% of the annual carbon burial that occurs in the oceans, or 27.4 Tg C/yr
(Fourqurean et al., 2012). Seagrasses bury more than twice the amount of carbon
in their sediments (500tCO2/ha) than tropical forest do in their soils (200tCO2/ha)
59
(Figure 14) (Murray, Pendleton, Jenkins, & Sifleet, 2011).
Figure 14. Global averages for carbon pools (soil organic carbon and living biomass) of
focal coastal habitats (in tones of CO2 equivalent per hectare per year). Tropical forests
are included for comparison. Only the top meter of soil is included in the soil carbon
estimates. Reprinted from “Green Payments for Blue Carbon: Economic Incentives for
Protecting Threatened Coastal Habitats” by B. Murray et al., 2011. Report by Duke
University Nicholas Institute for Environmnetal Policy Solutions.
The rate of carbon burial in specific seagrass ecosystems is dependent on
many variables including seagrass specie, temperature, irradiance, nutrient load,
sediment characteristics, depth, range, and age of the seagrass meadows (Greiner
et al., 2013). Currently, there are only a few studies that have measured the carbon
sequestration and/or burial rates in mono-specific meadows (Greiner et al., 2013).
For Z. marina reported estimates of carbon burial rage from 36.68 ±2.79 g C m2
/yr (Greiner et al., 2013) to 181 ± 18 g C m2 /yr (Kaldy, 2006). This wide range
might partially be attributed to the inconsistencies among different sampling and
analysis methods (table 4) (Greiner et al., 2013).
60
Table 4. Estimated production rates for Z. marina found in published literature. Reprinted from “Carbon, nitrogen, phosphorus and heavy
metal budgets: How large is the eelgrass (Zostera marina L.) sink in a temperate estuary?” by J.E Kaldy, 2006, Marine Pollution Bulletin,
52(3).
61
In Puget Sound, the carbon sink capacity of eelgrass has never been
directly measured. In 2013, a study by Caitlin Mariko-Shisido calculated the
amount of carbon that could be removed from seawater by eelgrass via
photosynthetic assimilation. Mariko Sishido utilized estimates of eelgrass
abundance, distribution, and regional net primary productivity in order to
calculate the rate of carbon assimilation. This study calculated the carbon uptake
of eelgrass to be 10 billion g C /yr (grams of carbon per year) for the Puget Sound
Basin, and a range from 100 million to 10 billion g C/yr for individual sub-basins
(Table 5) (Shishido, 2013). These estimates show that the maximum daily
increase in pH ranged from 0.02 to 0.05 pH units to a positive daily change in pH
from 0.01 units to 0.05 pH units, which is considered insufficient to offset daily
increases in pH due to anthropogenic carbon (Table 6) (Shishido, 2013). Thus
according to estimates, Z marina might not cause a pronounced shift in the
carbonate chemistry, necessary for mitigating the effects of ocean acidification
(Shishido, 2013).
The lack of direct measurements for the carbon draw-down potential in
different areas of Puget Sound, justifies the methodology and objectives for this
thesis, which attempts to directly measure the carbon sequestration potential of
eelgrass in Port Gamble, Puget Sound.
62
Table 5. Minimum and maximum estimates of the metabolic carbon sink capacity of Z.
marina, in g C m2/yr, using upper and lower bounds of net primary production (NPP) and
minimum and maximum estimates of area occupied by Z. marina in different Basins of
Puget Sound. Reprinted from Carbon draw-down potential by the native eelgrass Zostera
marina in Puget Sound and implications for ocean acidification management by C.
Mariko Shishido, 2013. University of Washington School of Marine and Environmental
Affairs
63
Table 6. Positive change in dissolved inorganic carbon (DIC) and pH projected for
several sites in Puget Sound based on estimates of abundance, distribution, and regional
net primary productivity (NPP). Reprinted from Carbon draw-down potential by the
native eelgrass Zostera marina in Puget Sound and implications for ocean acidification
management by C. Mariko Shishido, 2013. University of Washington School of Marine
and Environmental Affairs
e)
The effects of ocean acidification on seagrasses
As mentioned earlier, ocean acidification is expected to increase the
productivity of seagrasses, such as eelgrass, because high [CO2(aq)] benefits their
carbon sequestration and photosynthetic metabolism. Most experiments studying
how ocean acidification affects seagrasses have been performed under controlled
laboratory conditions and have focused on examining the short-term effects of
[CO2(aq)] enrichment. These show that under elevated [CO2(aq)] seagrasses exhibit
increase photosynthetic rates, reproduction, and underground biomass (Koch et
al., 2013)
Beer and Koch (1996) demonstrated that at elevated [CO2(aq)] both
seagrasses and macroalgae ramp up their photosynthetic rates. Beer and Koch
measured the photosynthetic rates of two seagrasses including Z. marina, and
three macroalgae species at increased concentrations of DIC. The concentrations
of DIC were gradually adjusted by injecting small amounts of 100 mM NaHCO3
64
until the seawater reached a pH of 6; the authors recorded how the photosynthetic
rates of these autotrophs changed in response to each injection. Their experiment
showed that the photosynthetic rates of all autotrophs studied increased due to the
increased availability of CO2(aq) (Figure 15) (S. Beer & Koch, 1996). It is worth
mentioning that although macroalgae also increase their photosynthetic rates
under high [CO2(aq)] conditions, and are sometimes more efficient than seagrasses
in their assimilation of organic carbon, macroalgae do not possess the carbon
burial capacity that seagrasses have because they lack roots and rhizomes.
Figure 15. Net photosynthetic rates (NPS) of two seagrass species: Zostera marina and
Thalassia testidinum and three marine macroalgae: Ulva lactuca, Palmata palmate, and
Laminaria saccharina in natural seawater (2. 2mM DIC) and following additions of DIC
(here labeled as Ci). The additions of DIC consisted of injections of liter amounts of
a100 mM NaHC03 solution. Figure shows that under high CO2 conditions macroalgae are
more efficient at sequestering dissolved inorganic carbon. Reprinted from
“Photosynthesis of marine macroalgae and seagrasses in globally changing CO2
environments” by S.Beer and E. Koch, Marine Ecology Progress Series,141(1), p201.
Jiang et al. (2011) reported a statistically significant increase in leaf
growth rates and belowground nonstructural carbohydrates of [CO2(aq)] enriched
65
seagrass Thalassia hemprichii compared to the un-enriched treatment. The
authors studied the response of these plants under four different concentrations of
[CO2(aq)], which are equivalent to pH values of 8.10 (un-enriched treatment), 7.75
(the projected value for 2100), 7.50 (the projected value for 2200) and 6.2 (an
extreme value)(Jiang, Huang, & Zhang, 2011) .
Hendricks et al. (2013) reported that photosynthetic activity in shallow
seagrass meadows (5-12 feet) of Pocedonia oceanica buffered the local effects of
ocean acidification along the coast of Mallorca, Spain. Hendricks et al. correlated
the diurnal change in seawater pH with the metabolic activity of P. oceanica
meadows (photosynthetic leaf area per m2 (LAI), dissolved oxygen, shoot density,
biomass) while taking into account environmental parameters (temperature,
irradiance, salinity, residence time, etc). The magnitude of diurnal pH variation
was strongly related to seagrass productivity, with the largest ranges coinciding
with the peak in seagrass productivity, which happens in June. The range of pH
measurements was also influenced by oxygen concentrations (max and mean; F =
61.86, p < 0.0001nd F = 18.29, p < 0.01, respectively). The main factor affecting
oxygen concentrations was determined to be LAI which affected both max (r2 =
0.60, F =13.71, p < 0.01), and mean (r2 = 0.60, F = 13.51, p < 0.01) oxygen
concentrations. The authors concluded “that metabolically intense seagrass
meadows actively control the carbonate system in their canopies” (p. 12325) and
that the carbon draw down happening in the seagrass beds minimizes the effects
of ocean acidification and offers a refuge to calcifiers and organisms that are
sensitive to pronounced pH changes (Hendriks et al., 2013).
66
Just as experiments studying CO2(aq) enrichment show an increase in
photosynthetic rates and biomass of seagrasses, an experiment studying a
decrease in [CO2(aq)] showed a decrease in photosynthetic activity. This
experiment, performed by Hellblom and Björk (1999), analyzed the result of
diluting the DIC content while keeping all other variables constant in aquaria
containing Z. marina specimens. Their experiments showed that photosynthesis
was significantly inhibited when the DIC concentration decreased from 2mM to
1mM; however, respiration was not inhibited (Hellblom & Björk, 1999).
Unsworth et al. (2012) developed a computer model that analyzed the pH
buffering capacity of seagrass meadows near scleratinian coral reefs in the IndoPacific Ocean. This study suggested that increases up to 0.38 pH units, and Ω
aragonite increases of up to 2.9 in seagrass meadows (with a 24 h water residence
time and 1 m depth seagrass meadow) could potentially enhance calcification of
scleratinian corals downstream of seagrasses by 18% (Unsworth, Collier,
Henderson, & McKenzie, 2012).
Studies examining the long-term effects of ocean acidification on
seagrasses are scarce, but the results from these few studies are consistent with the
increase in underground biomass observed in short-term studies. For example, a
study by Palacios and Zimmerman (2007) examined the effects of long-term
enrichment of CO2(aq) (over the period of two years) on the performance of
Z.marina growing under 33% surface irradiance. Palacios and Zimmerman
simulated the current [CO2(aq)] and the [CO2(aq)] predicted for the year 2100 (36
mol CO2) and 2200 (85 mol CO2) by injecting flue glass into aquaria. They
67
discovered that even though the enrichment did not alter leaf size or leaf sugar
content, the CO2(aq) enrichment led to significantly higher underground production
of rhizomes and an increase in vegetative proliferation. Shoots growing under
[CO2(aq)] predicted for 2100 were 25% larger than those from current [CO2(aq)],
and shoots grown under [CO2(aq)] predicted for 2200 were 50% larger than those
from current [CO2(aq)] (Palacios & Zimmerman, 2007).
Even though studies show that seagrasses have the potential to reduce the
effects of ocean acidification, experiments also show that under high [CO2(aq)] the
nutritional quality of seagrasses decreases and they lose their ability to produce
anti-herbivory compounds. A study by Arnold et al (2012) indicates than under
elevated pCO2, some seagrasses lose the ability to produce phenolic compounds
that protect these plants against herbivores, pathogens, and damage by UV
radiation. Arnold et al. (2012) reported that the reduction of these defense
compounds resulted in higher rates of herbivory and lower overall productivity.
Since some phenolic compounds are antimicrobial or protect the plants against
UV radiation, the authors of this study expect that the reduction of phenols will
result in increased pathogen infections and increased tissue damage (Arnold et al.,
2012).
f)
Eelgrass habitat requirements
Nutrient requirements: Eelgrass typically inhabits areas that are naturally
phosphorus or nitrogen limited (Touchette & Burkholder, 2007). Seagrasses may
be limited by nitrogen in nutrient poor waters with sandy or shallow organic
68
horizon sediments or limited by phosphorous in carbonate sediments (Touchette
& Burkholder, 2000). Due to this limitation, Z. marina, as most seagrasses,
developed active uptake systems for NO3- and PO4-3) and NH4+ (Touchette &
Burkholder, 2000). Excessive enrichment of nitrogen and phosphorus is
correlated to eelgrass decline. Excess nitrogen in the in the water column can
inhibit seagrass growth by stimulating epiphyte overgrowth and by consuming the
plant’s energy reserves (Touchette & Burkholder, 2000, 2007). Scientists
hypothesize that eelgrass must have evolved in nitrogen-limited waters, where
nitrogen peaks (sudden rises in concentration) were infrequent. Supposedly,
during these peaks eelgrass plants would use energy to assimilate as much
nitrogen as they could and then convert it to amino acids (Touchette &
Burkholder, 2007). Some scientists think that eelgrass plants never developed a
mechanism that stops the uptake of nitrogen; in nitrogen rich waters eelgrass
plants are thought to consume all their energy reserves uptaking more nitrogen
than they need to survive (Touchette & Burkholder, 2007). It is important to note
that external variables, such as irradiance and temperature, affect eelgrass’
assimilation capacity of these nutrients (Peralta, Bouma, van Soelen, PérezLloréns, & Hernández, 2003).
However, due to abundant runoff and freshwater inputs, which act as
nutrient sources, Z. marina in Puget Sound is not limited by the concentration of
nitrogen or phosphorus (Mumford, 2007). In fact, these inputs are believed to be
beneficial as Z. marina has been shown to respond favorably to low or moderate
N and/or P enrichment (Touchette & Burkholder, 2000).
69
Temperature: The ideal temperature for maximum eelgrass growth is
around 20C, but Zostera marina can survive in temperatures that range from 5C
to 30C (Touchette & Burkholder, 2007). Natural populations of eelgrass exist
under temperatures ranging from arctic waters to temperate estuaries (Nejrup &
Pedersen, 2008). Seasonal growth is closely associated with temperature. Low
water temperatures (<5 °C) reduce photosynthesis and growth, and impede sexual
reproduction, but do not affect mortality (Nejrup & Pedersen, 2008). High
temperatures (25–30 °C), on the other hand, increase mortality and decrease the
photosynthesis and growth rates (Nejrup & Pedersen, 2008).
Light and depth: Eelgrass needs high levels of light to grow and
reproduce; because of this, it is typically only found in shallow waters that are
less than 10 meters (Mumford, 2007). Eelgrass habitat is constrained to a depth
gradient that represents at its upper boundary the likelihood of exposure to
desiccation at low tide, and at its lower boundary light attenuation in the water
column (Dowty et al., 2005; Mumford, 2007). A survey by the WA-DNR ongoing
Puget Sound’s Submerged Vegetation Monitoring Project (SVMP) found that
eelgrass depth range varies throughout the sound, with the San Juan Straits having
the widest depth range and Seratoga-Whimbey region having the narrowest depth
range (Figure 16) (Dowty et al., 2005).
70
Figure 16. Site-level minimum and maximum Zostera marina depth results summarized
by Puget Sound regions. Reprinted from Puget Sound “Submerged Vegetation
Monitoring Project 2003-2004 Monitoring Report” by P. Dowty et al., 2005. Published
by Washington State Department of Natural Resources. Retrived from
http://www.dnr.wa.gov/Publications/aqr_nrsh_03_04_svmp_rpt.pdf
Salinity: The optimum salinity for eelgrass is between 10% and 25%,
although eelgrass can be found in waters ranging from 2% to 40% of salt
concentration (Nejrup & Pedersen, 2008). Eelgrass is well adapted to tolerate
changes in salinity, as estuaries often experience variations in freshwater inputs
that cause rapid changes in salinity (Nejrup & Pedersen, 2008). Even though
eelgrass can maintain a positive carbon balance at extreme salinities, studies show
that growth, reproduction, and germination are affected when salinity falls below
or shoots above the optimal parameters (Nejrup & Pedersen, 2008).
Substrate: Eelgrass tends to grow in unconsolidated substrates ranging
from gravelly sand to fine muds and silts, with a general preference towards finer
particle sizes (Kenworthy & Fonseca, 1977). In Puget Sound, Z. marina is
71
primarily found in the subtidal zone, rooted in sand or mud in shallow waters,
where the currents are not too strong (Mumford, 2007). However, in some
moderately high-energy environments, such as Salmon Bank, eelgrass can be
found growing in finer substrates trapped between cobbles and boulders
(Mumford, 2007).
g)
Distribution and density of eelgrass beds in Puget Sound
Eelgrass in broadly distributed through Puget Sound. Thus, eelgrass is
found in areas from +1.8 to -8.8 meters (relative to mean lower low water) in
Puget Sound, with beds being more abundant around 0.0 meters. (Mumford,
2007). In general, eelgrass beds are found throughout Puget Sound except for
south of Anderson Island and Carr Inlet in southern Puget Sound, possibly due to
the extreme tidal range or seasonal lack of nutrients ( Figure 17) (Mumford,
2007).
72
Figure 17. Distribution of eelgrass (Z. marina) in Puget Sound. Reprinted from Kelp and
Eelgrass in Puget Sound by T. Mumford, 2001, Washington Department of Natural
Resources, Aquatics Division.
Eelgrass beds in Washington State have been mapped by the WDNR and
published in the ShoreZone database (Nearshore Habitat Program 2001).
According to the database, eelgrass beds represent 37% of the shoreline
vegetation of Washington State (table 7). Additionally, the Puget Sound
Assessment and Monitoring Program, led by WDNR has been monitoring five
regions within Puget Sound since the year 2000 and has estimated that there are
200 km2 of Z. marina in the shorelines of Puget Sound.
73
Table 7. Length of shoreline with eelgrass, floating and non-floating kelp by Puget Sound
counties (Mumford, 2007). Reprinted from Kelp and Eelgrass in Puget Sound by T.
Mumford, 2001, Washington Department of Natural Resources, Aquatics Division.
The density of the eelgrass beds depends on the conditions of the habitat.
In areas where conditions are thought to be most suitable, beds are dense and
continuous, while other less suitable areas have patchy beds (Mumford, 2007).
Continuous beds are usually found in extensive tideflats, and more fragmented
beds in areas are found raveled edge shorelines (Mumford, 2007). Little is known
about the interannual variation of the density of beds, but the variation is expected
to be less than 10 percent (Mumford, 2007).
Other factors that limit density and distribution of Z. marina include
competitors and water quality degradation. Z. marina has only few competitors;
74
these include the introduced brown seaweed Sargassum muticum, the sand dollar
Dendraster excentricus and possibly the newly discovered kelp species in Hood
Canal, Chorda filum (Mumford, 2007). If the environment has excessive
nutrients, algal species might overgrow and limit photosynthesis for eelgrass. Sea
lettuce (Ulva sp) has been known to grown on the water surface and block
sunlight; similarly, epiphytes can flourish the blades of eelgrass, blocking light,
and gas exchange (Mumford, 2007). Due to their relatively high light
requirements, eelgrass beds thrive in shallow waters, where they are vulnerable to
damage by human activities that reduce the water quality (Fonseca, Kenworthy, &
Thayer, 1998). Increased runoff from nutrient loading activities, such as logging
and agriculture, have resulted in a decrease of eelgrass growth (Wolf, 2007).
Exposure to toxic substances, such as petroleum products and metals like
cadmium, impairs photosynthesis and respiration, and limits eelgrass growth and
distribution (Mumford, 2007). Physical disturbances such as oyster culture, highenergy boat wakes, the dredging and filling required to maintain shipping lanes,
and construction of under and over water , also impact eelgrass habitat (Mumford,
2007; Wolf, 2007)
h)
Ecological function and socio-economical importance of eelgrass
Eelgrass serves a wide variety of ecological functions in Puget Sound
ecosystems, including fueling the food web, stabilizing sediments, and providing
habitat, nursery, and protection to many species (Mumford, 2007). Eelgrass is
highly productive, annually producing large amounts of biomass that fuels
75
nearshore food webs directly through detritus pathways and consumption by
several species of birds and indirectly by feeding many species of invertebrates
(Figure 18) (Larkum et al., 2006; Mumford, 2007).
Eelgrass fuels the food web by providing food to crustacean and bird
species. Ducks, swans and other species of goose, are known to stop in eelgrass
beds during their migrations (Mumford, 2007). For example, the Pacific black
brant migration is closely linked to the distribution of Z. marina beds from
Mexico to Alaska (Larkum et al., 2006). Crustacean species such as members of
the isopod genera Synidotea also feed on eelgrass (Mumford, 2007).
Zostera marina beds provide structure for habitat and nursery of many
species. Many organisms, including microalgae and macroalgae, copepods,
amphipods and snails, inhabit the eelgrass blades and rhizomes (Mumford, 2007).
Marine birds such as the Great Blue Heron feed extensibly on the small
invertebrates found in eelgrass beds (Mumford, 2007). Fishes such as juvenile
salmonids utilize eelgrass beds as migratory corridors, as they pass through Puget
Sound; the beds provide protection from predators and abundant food, such as
small crustaceans (Mumford, 2007). Several species of flounder, weakfish, blue
crab, bay scallops, lobsters and striped bass, require eelgrass habitats at a point of
life history (Mumford, 2007). Additionally, many fish and crustaceans species lay
their eggs on eelgrass, including species of commercial interest such as
Dungeness crab (Metacarcinus magister) and Pacific herring (Clupea pallasii)
(Mumford, 2007).
76
Figure 18. The eelgrass meadow: A world of microhabitats. . Reprinted from Kelp and
Eelgrass in Puget Sound by T. Mumford, 2001, Washington Department of Natural
Resources, Aquatics Division. (Mumford, 2007)
Eelgrass also provides sediment stabilization. Their dense interlocking
rhizomes effectively grab and anchor the sediments, protecting the bottom from
erosion, while the blades slow water currents, dampen waves, and trap sediments,
increasing the rate of deposition (Larkum et al., 2006; Mumford, 2007)
77
The socieconomical importance of eelgrass can be related to its connection
to commercial seafood species and with its cultural significance to Native
American Tribes. In addition to housing many commercial seafood species,
eelgrass is used as ceremonial material in Native American Rituals (Mumford,
2007).
Several studies have attempted to associate a monetary values to eelgrass
habitats, based on their economical contribution. Costanza et al. (1997) calculated
that eelgrass was worth $19,004 per hectare per year, while McArthur and Boland
(2006) found that the loss of 16% of eelgrass on an area corresponding
approximately to 1° latitude and longitude, resulted in an economic loss of
$235,000 per year, due to a reduction of seafood catch.
The ecological and socioeconomical importance of Z. marina was
highlighted in the 1930’s when 90% of the North Atlantic Z. marina died off, due
to “wasting disease” (Larkum et al., 2006). This massive die-off led to reductions
in estuarine and costal food web productivity, which resulted in the disappearance
of the commercially harvested scallop Argopecten irraiance and in a drastic
reduction of brant geese populations (Larkum et al., 2006).
Seagrass plants can absorb heavy metals and incorporate them in their
tissues, thus they have been proposed as a bio-remediation mechanism for dealing
with metal contaminated waters. Similarly, seagrasses can be used as ecological
indicators to assess the water quality and level of metal contamination of an
ecosystem (Thangaradjou, Raja, Subhashini, Nobi, & Dilipan, 2013). Kaldy
78
(2006) determined that Z. marina plants incorporated 73–90% of metals in the
water into new leaf tissue. Nickel and zinc are incorporated into eelgrass tissues
faster than arsenic, cadmium, chromium or copper (Table 8)(Kaldy, 2006).
Because of their high productivity and low herbivory rates, eelgrass plants could
potentially be used to accumulate heavy metals that are dissolved in the water; the
metals could then be extracted from the plants and be disposed in an
environmentally safe way.
Table 8. Budget calculations for the incorporation C, N, P and metals into new Zostera
marina leaf, rhizome, and root tissues. Reprinted from “Carbon, nitrogen, phosphorus
and heavy metal budgets: How large is the eelgrass (Zostera marina ) sink in a temperate
estuary?” by J. Kaldy, 2006, Marine Pollution Bulletin, 52(3)
i)
Protective status of eelgrass in Washington State
Because of the ecological importance of eelgrass and its susceptibility to
human disturbances, eelgrass has been given regulatory protection under a variety
of federal, state and local laws (Mumford, 2007). The EPA is concerned with the
protection of eelgrass under the Clean Water Act; EPA must guarantee that the
water quality does not affect the physical and biological integrity of the nation’s
79
waters (Nelson Walter, 2009). In Washington State, eelgrass has been designated
as critical habitat under the Critical Areas Ordinance by the Department of
Ecology, while WA- DNR has designated areas of Z. marina as habitats of special
concern and has a no-net-loss policy for shoreline development (Dowty et al.,
2005). Additionally, the Puget Sound Partnership designated eelgrass one of the
top five indicator species to estimate the health of the Puget Sound and has
developed a set a target of increasing eelgrass habitat in Puget Sound by 20
percent by the year 2020 (Puget Sound Partnership, 2012).
j)
Suggestions for future research on eelgrass
After reviewing the scholarly literature, it is clear that there are some
robust estimates of the rate of carbon assimilation and the rate of carbon burial of
seagrasses (as a group) at a global scale. There are also estimates of net primary
production (NPP) rates, and amount of carbon stored in sediments and biomass
for tropical and subtropical seagrass species. However, very limited information
was found regarding the rate of carbon uptake and the amount of carbon stored in
biomass and sediments of seagrass beds located in temperate latitudes. Even
through the irradiance levels, and thus NPP rates are lower in temperate regions, it
is important to calculate this rate in order to have a more complete estimate of
how much carbon is stored in seagrass ecosystems at a global and regional scale.
Similarly, there are only a handful of field studies that have directly
measured whether or not seagrass species can increase the pH of seawater to
significantly ameliorate ocean acidification. Most estimates on the change of pH
80
or the change of DIC caused by seagrasses were obtained by ether doing
theoretical calculations of by conducting laboratory experiments that carefully
control most variables that affect photosynthesis. More field studies are needed in
order to have more realistic estimate of the contribution of seagrasses to the
mitigation of ocean acidification.
Only one estimate for the carbon draw-down potential of eelgrass in
Washington State was found. This estimate was theoretical and was calculated
with statistics gathered by past studies on the characteristics of different areas in
Puget Sound. No studies regarding the carbon burial capacity of eelgrass in
Washington State or in the Pacific Northwest were found. More studies, whether
they are in a laboratory or in the field, are needed to examine the carbon uptake of
eelgrass and it subsequent effect on pH in Washington state marine waters. This
thesis represents the first field study that attempted to estimate the change in pH
over time and the change of DIC over time over eelgrass beds located within an
area of Puget Sound.
81
III. METHODS
PURPOSE OF EXPERIMENT
The purpose of this experiment was to compare the rates of change of pH
over time between two ecosystems, Zostera marina beds and bare mud flats,
located in Port Gamble, WA to determine if the carbon sequestration capacity of
Z. marina beds would be capable of locally buffering the impacts of additional
acidity caused by the oceanic uptake of anthropogenic CO2. Our experiment was
conducted during daylight hours of January 19 and January 20, 2014 and thus our
results only represent a snapshot of what the rates of change of pH over time are
like for these two ecosystems during wintertime in Port Gamble. It important to
keep in mind that during the winter, solar irradiance is low which leads to reduced
photosynthesis and consequently reduced carbon sequestration rates, which may
suggest our results represent a minimum (or conservative) uptake. In spite of the
reduced irradiance, we expected to see a positive rate of change of pH over time
for the Z.marina beds as a result of net photosynthesis in this ecosystem. For the
bare mud flats, we expected to see a decline in pH over time, resulting from net
respiration in the ecosystem.
STUDY AREA
The experiment took place in Port Gamble, Kitstap County, Washington
from 9am to 3pm of January 19 and January 20, 2014 (Figure 19). Port Gamble,
also known as Gamble Bay, is an inlet located in the northwestern shore of the
82
Kitsap Peninsula in Kitsap County, Washington, United States. Port Gamble lies
within the Upper Hood Canal Watershed and the mouth of the inlet is located on
the north, where it opens up to Hood Canal.
Figure 19. Location of Port Gamble (denoted by the red square) within Puget Sound,
Washington.
Several factors influenced the selection of this site for the study. The main
factor was that Port Gamble reportedly contained significant intertidal eelgrass
83
beds along the shoreline. Newfields Northwest, and environmental consulting
group, had previously conducted scuba transect surveys in this area and they had
determined the locations that contained Z. marina beds (NewFields Northwest,
2007). Another factor was the ease of access to Port Gamble and the fact that
WA-DNR had already obtained authorization from the S’klallam Tribe to conduct
experimental work within their reservation. A decisive factor was that Port
Gamble is considered to have “excellent” quality marine waters and thus this
decreased the risk of having to account for contamination or other variables that
might have influenced the results of the experiment.
According to the 2013 Water Quality Monitoring Report from the Kitsap
Public Health District, the overall marine water quality for Port Gamble is
classified as “excellent.” The majority of the waters of Gamble Bay are approved
for shellfish harvesting except for the northeast area where there is a permanent
closure zone around the outfall of a sewage treatment plant. All water quality
stations in Port Gamble met the stare bacterial standards during the 2012-2013
year. However, there were temperature exceedances at three of the four stations
during the 2013 summer months (Kitsap Public Health District, 2013).
Additionally, there is concern among the S’klallam Tribe, Washington
Department of Natural Resources (DNR), and Washington’s Department of
Ecology that historical operations of the former sawmill released pollutants to the
water including wood waste, cadmium, mercury, petroleum hydrocarbons,
carcinogenic polycyclic aromatic hydrocarbons (cPAHs), dioxins/furans, sulfide
and ammonia (Port Gamble S’Klallam Tribe, 2014; Washington State Department
84
of Ecology, n.d.). Some of these contaminants have been found on soil
surrounding the mill site and in shellfish tissues, although the these contaminants
are absent in the marine waters of the bay or in concentrations below those that
would risk human health (Kitsap Public Health District, 2013; Washington State
Department of Ecology, n.d.)
Several communities live along the edges of Gamble Bay. Along the east
side of the bay, lies the S’klallam Tribe Indian Reservation and the Little Boston
community. The right side of the Bay contains the town of Port Gamble along
with the remnants of mill that operated under the Puget Sound Mill Company,
later known as Pope & Talbot, Inc, from 1853 to 1995. The mill was removed in
1997 and the fill area has since been leased for log sorting, wood chipping, and
other light industrial activities (Washington State Department of Ecology, n.d.).
The community of Gamblewood is located in the south side of the bay.
Unincorporated residential housing can be found on both sides of the bay. The
communities of Kingston, Poulsbo, and Hansville are located in the vicinity of the
bay (Port Gamble S’Klallam Tribe, 2014).
The surrounding communities harvest shellfish and fish from Gamble Bay.
Gamble Bay is the last bay in Kitsap County open for commercial shellfish
harvesting of geoduck, clams, and oysters (Port Gamble S’Klallam Tribe, 2014).
The Bay also contains Dungeness Crab and shrimp (NewFields Northwest, 2007).
The S’klallam Tribe has a salmon hatchery located in the north west side of the
bay (Port Gamble S’Klallam Foundation, 2014). Salmonoid fish such as Chum,
Coho, Chinook, Pink Salmon, and Cutthrow Trout frequent the waters of Gamble
85
Bay (NewFields Northwest, 2007). Forage fish such as herring, surf smelt and
sand lance inhabit and spawn in the waters of Gamble Bay (NewFields
Northwest, 2007).
Since several communities depend of the marine resources of Gamble
Bay, it is essential that these resources are protected from the effects of ocean
acidification. Eelgrass beds are considered critical habitat for a number of fish and
invertebrate species, and thus are considered protected habitat. In addition to
providing special habitat, eelgrass beds might mitigate the impacts of ocean
acidification. The Olympic Property Group (a real estate subsidiary of Pope
Resources, the former owner of the Port Gamble mill) and DNR have considered
developing eelgrass mitigation and restoration projects in Gamble Bay
(NewFields Northwest, 2007).
EXPERIMENTAL DESIGN
a)
Construction of drifting devices
Four circular floating devices of about 1meter in diameter were
constructed using ½ inch PVC pipes and 1 inch industrial tubing. Each circular
device had console in the center for the attachment of instrumentation; the console
was constructed in a way that allowed the instrumentation to be submerged a
couple of inches from the surface of the water. Two pairs of circular devices were
tied to each other and were referred to as one “drifter” (Figure 20).
86
Figure 20. Image of one of the drifters
b)
Preparation for Drifts
A water quality monitoring sonde YSI 6600 was attached using zip ties to
one console in each drifter in order to measure temperature, salinity, and depth.
The YSI measured these parameters every minute for the duration of the
experiment.
Two GPS Gamin gecko devices were also attached to each drifter (one in
each console). The GPS devices would provide information on the spatial location
of the drifters for every minute of the experiment. Two devices were used to
ensure that if one device failed we would still have spatial data from each drift.
To measure pH, two custom-made voltmeters crafted using two
Honeywell Durafet II electrodes were attached to each drifter, to record voltage
every minute. These pH sensors where built according to specifications in the
87
publication titled Testing the Honeywell Durafet® for seawater pH applications
by Martz, Connery, and Johnson (2010). According to Martz, Connery and
Johnson (2010) the theoretical accuracy of the sensors is ± 0.0005 pH units;
however, based on our experimental test the accuracy of the sensors was 0.001
pH units. Our test consisted of submerging the sensors in a seawater reference
solution of pH 7.95 at room temperature for a period of one hour and then
calculating the pH based on the measured voltage. (Andrew Dickson’s Laboratory
seawater reference solution batch 134, bottled September 27, 2013). Deviations
between the measured pH and the pH of the standardized solution were noted and
later used as correction factors when calculating the measured pH for each drift
Two Go-Pro waterproof cameras were attached to each circular frame
using zip ties in order to record video footage of the underwater ecosystem and
calculate percent cover of eelgrass.
Twenty clean brown beer bottles where disinfected and prepared for the
collection of water samples immediately before commencing the drifts. The beer
bottles were prepared by washing them with 5ml of 38% HCl, followed by a 5ml
wash with commercial bleach.
We also had two kayaks and a small 15-foot aluminum boat. These
vehicles where used to scout the area and in the case of the boat to get information
on depth and presence of eelgrass by utilizing the sonar and depth meter.
88
c)
Site selection
Sites were selected based on the presence of significant subtidal Z.
marina beds that where in proximity of areas that showed no apparent vegetation
coverage and were classified as mud flats. Thus, each was comprised of two
ecosystems: a subtidal Z. marina bed ecosystem, which was referred to as the
“eelgrass treatment,” and a mud flat ecosystem containing little to no observable
vegetation, referred to as the “no eelgrass treatment”. Five areas, each containing
a pair of ecosystems were selected for this study, for a total of five “eelgrass”
treatment replicates and five “no eelgrass” treatment replicates.
For the site selection process, we considered the distance of each site from
the shoreline, the estimated density of eelgrass, and the strength of the current in
each area. The boat sonar was used to confirm the presence and absence of
eelgrass in each of the paired ecosystems. The sonar was also used to estimate the
density of eelgrass in each bed, only beds that resulted in an acoustic signature
characteristic of dense eelgrass beds were selected. Dr. Alan Trimble and Dr.
Jennifer Ruesnik from the University of Washington’s Biology Department
evaluated the sonar signal. After using the sonar, the presence or absence of
eelgrass was confirmed visually by drifting on top of each ecosystem in two
kayaks. Paired ecosystems that had the same composition covering an area of at
least 30x15m, with the longest side of the area parallel to the direction of the
current were chosen. Only areas within five meters from the shoreline where
considered. The areas chosen where then narrowed down by only considering
89
areas that showed they had slow currents (those moving at a speed of less than 3
meters per minute). The intensity of the currents was tested by deploying the
drifters and observing how fast the drifters moved with the current.
The criteria explained above, resulted in a total of five paired ecosystems
contained within two areas, which are delineated by the rectangles in the map
(Figure 21). The relative closeness of the paired ecosystems ensured that
environmental conditions, such as wind and current, were the same for both
ecosystems and therefore the same for both drifters.
Figure 21. Location of each of the ten drifts (five drifts per treatment) within Port
Gamble.
90
We found some of the introduced specie Zostera japonica growing in
close proximity to Zostera marina beds. However, we did not attempt to avoid Z.
japonica in this experiment, as the Z. japonica density was very low (less than 15
shoots per square meter) and the plants were not observed directly on Z. marina
beds. Because the density of Z. japonica was so low, for experimental purposes, it
was assumed that Z. marina was contributing to 99% of the carbon sequestration
of that area, ad that any contribution to carbon sequestration by Z. japonica was
negligible.
d)
Drifts
Each drifter was allowed to drift over the assigned ecosystem in the
direction of the current. The drifters where allowed to drift with the current for a
period that ranged from 35 minutes to one hour. Each drift was ended after the
researchers observed that the drifters where drifting onto a different ecosystem or
onto deeper waters, or after the one-hour period was over.
A kayaker was assigned to each drifter; the kayaker’s job was to ensure
that the drifter stayed in the designated ecosystem, to record information pertinent
to the experiment, and to collect water samples. The kayakers followed the
drifters within a distance of 5 meters to confirm that the drifter was within the
designated ecosystem (eelgrass bed or mud flat) and to keep the drifters from
being run over by boats. The kayaker was instructed to end the drift if the drifter
was driven by wind or currents into a different ecosystem. During the experiment,
there was no reported turbulence created by nearby boats that could have affected
91
the measured parameters. The kayakers also recorded information pertinent to the
experiment, such as the start and end time of each drift, as well as any observable
flora and fauna. The kayakers collected two replicate water samples at the
beginning and end of the drift; these water samples were collected directly next to
the drifter and were intended to provide information on the alkalinity,
spectrophotometric pH, and salinity of the water. The purpose of collecting the
water samples was to determine how the water chemistry changed as the water
moved through each ecosystem. Because we worked with paired ecosystems that
were close to each other, we assumed that any water chemistry changes in each
ecosystem could be attributed to photosynthesis and respiration within each
ecosystem. Immediately after collecting the water samples, the kayakers
transferred them into a the research boat, where the samples were poisoned with
30L saturated mercuric chloride, capped and stored in a cooler for laboratory
analysis.
The procedure of deployment of the drifters and collection of water
samples was repeated ten times, one for each replicate, during the course of two
days. At the end of each day, information from the YSI sensors, GPS equipment,
GoPro cameras, and electrodes was downloaded and transferred into a computer
for future analysis. The water samples were transported to the laboratory at the
end of day, where they were stored at room temperature until analysis.
92
e)
Video footage analysis
The video footage was used in order estimate the percent cover of
eelgrass and confirm that the drifters were placed on top of the desired ecosystem.
The footage for all of the replicates represented more than eight hours of film.
Static frames corresponding to 30 second intervals were studied and percent cover
of eelgrass, algae, and bivalves was estimated. The estimations of percent cover
where done by dividing each frame into four quadrants of equal size and
estimating what percentage of each quadrant was covered by each one of these
organisms. The individual estimates for percent area covered by the organisms in
each quadrant were then added in order to calculate the total percent.
Observations on the species of flora and fauna observed, estimated depth, and
visibility were also noted.
f)
Water chemistry analysis
The replicate water samples collected at the beginning and end of each
ecosystem were analyzed in WA-DNR Water Chemistry Lab located in Olympia,
WA. Samples were analyzed for spetrophotometric pH, total alkalinity (TA) and
salinity. For pH analysis, the Hoffman Lab protocol for determination of the pH
of seawater using indicator dye m-cresol purple was followed (appendix A) using
an Ocean Optics Ocean View Spectrometer. For determination of total alakalinity,
a Mettler-Toledo T-50 automatic titrator was used and the Hoffman Lab Protocol
for total alkalinity titration of seawater was followed (appendix B). For
93
determination of salinity a Milwaukee MA887 digital refractometer was used.
Unfortunately, the results for TA and spectrophotometric pH varied
widely between the replicates and showed large standard errors and coefficients
of variance. Based on the large variation found within replicates and on the fact
both analytical techniques gave accurate values for the reference solutions used, it
was concluded that the bottles were probably contaminated with the residue from
the acid-bleach wash and that this residue was affecting the test results. Because
of the contamination of the water samples, total alkalinity and spectrophotometric
pH could not be accurately determined. The analysis of salinity, on the other
hand, was not affected by the sample contamination. In order to obtain pH values
necessary to calculate the change in DIC for each ecosystem, the pH data
measured by the YSI instruments on the drifters was used. In order to obtain total
alkalinity (TA) values, which are also necessary to calculate the change in DIC,
the lowest and highest values of a range of TA measurements that previously
collected by DNR during March 2014 in Port Gamble were used. The reasoning
behind using the highest and lowest TA values available for Port Gamble was so
that we could capture as much of the natural variability of the real TA values in
Gamble Bay. Also, photosynthesis and respiration do not affect the alkalinity of
the sample, and as such, the eelgrass should not affect these values considerably.
g)
Data organization and statistical analysis
Since the custom-made voltmeter used only measured the change in the
electric potential of the water, these values had to be converted to pH. This
94
conversion was performed using the equation suggested in Testing the Honeywell
Durafet® for seawater pH applications by Martz, Connery, & Johnson (2010)
(Equation 6).
pH = E–E*
S
Where
E= electrode potential (i.e voltage) of the second half-cell forming the circuit in the
custom made pH meter.
E*= electrode potential (i.e voltage) of the first half-cell forming the circuit in the custom
made pH meter.
S = R × T × ln(10)/F (R is the gas constant 8.3145 J/ K*mol, T is temperature in Kelvin;
F is the Faraday constant 96485 C/mol)
Equation 6. Conversion of electric voltage to pH. Adapted from “Testing the Honeywell
Durafet for seawater pH applications” by Martz et al., 2010, Limnology and
Oceanography: Methods, 8
All data corresponding to pH, temperature, salinity, percent cover of
eelgrass, bivalves and macro-algae, and other observations regarding the
ecosystem, were compiled into an excel spreadsheet (Appendix C). Since the YSI
and Durafet electrode only measured the parameters each minute, the values from
the previous minute were assumed to be the same for the subsequent 30 second
interval.
The video footage revealed that there was some eelgrass present in the
mud flats treatment, which was assumed to contain little to no vegetation; the
video also showed that the coverage of eelgrass in the eelgrass treatment was, in
some cases, sporadic with bare patches. Thus, for the five eelgrass beds replicates
95
the average eelgrass coverage was 18% with a median of 15%. For the five “no
eelgrass” replicates the average eelgrass cover treatment was 7% a median of 0%.
In an effort to amplify the difference between the two treatments, each
eelgrass replicate was broken down into ten-minute intervals consisting of 20 data
points (one every 30 seconds) and only the ten-minute intervals that showed
average eelgrass coverage of 20% or more were included on the “eelgrass
treatment.” Similarly, only the ten-minute intervals that showed an average
eelgrass cover of 5% or less were included under the “no eelgrass treatment.” The
10 minute intervals were classified according to the percent cover of eelgrass that
they showed and not according to the initial ecosystem classification. The reclassification of treatments resulted in nine replicates for the eelgrass treatment
and eleven replicates for the no eelgrass treatment (Figure 22 and 23). A
resampling- t test confirmed that the difference between the average eelgrass
cover for the newly classified replicates for eelgrass treatment (mean = 25.15%)
and the no eelgrass treatment (mean=0.60%) was significant (=0.05, p=0.000).
96
Figure 22. Diagram of the reclassification of eelgrass treatment replicates. Only 10
minute intervals that had an average cover of ≥ 20% eelgrass were used to create the nine
10-minute no-eelgrass treatment replicates.
Figure 23. Diagram of the reclassification of no-eelgrass treatment replicates. Only 10
minute intervals that had an average cover of ≤ 5% eelgrass were used to create the
eleven 10-minute eelgrass treatment replicates.
97
Before beginning with the statistical analysis the first 30-second data
point from the reclassified replicate number seven of the eelgrass treatment was
labeled an outlier, because the video footage revealed that the drifter was being
placed in the water at that moment and this affected the pH value of that first data
point. Similarly, the first four 30-second data points for reclassified replicate
seven for the no eelgrass treatment were labeled as outliers for the exact same
reasons. Thus, none of these data points were taken into account for the statistical
analyses.
The change in pH over time (pH/s) was calculated for each of the reclassified replicates by obtaining the slope of pH plotted against time. A Shapiro
Wilks’ test and a Levene’s test was performed in order to determine if the rates of
change of pH over time met the assumptions of normality and homogeneous
variances required to perform a parametric t-test or a parametric one-way
ANOVA. Since the data did not pass the assumptions required for a parametric
test, a resampling t-test was performed in order to evaluate if there was a
significant difference in pH/s between the two treatments. After performing the
resampling t-tests, pH/s was converted into rates of change of pH over each
minute (pH/m) for the rates to be more applicable to field studies.
Lastly, because the water samples were contaminated, the upper and lower
limits of a range of alkalinity values from unpublished data collected by WADNR in Port Gamble during March 2014, were used, along with the pH values
from the custom made pH sensors, to obtain estimates of the DIC values for each
98
replicate using CO2SYS software. DIC measurements where calculated for every
30 second intervals in each one of the 10 minute replicates. The estimates of DIC
were computed by inputting the measured temperature, salinity, pH (from field
voltmeters), pressure (from YSIs estimated by using the conversion that 1m of
depth =1 decibar of pressure) and the upper and lower values for the range of total
alkalinity in Port Gamble. Because we had two different values for alkalinity
(1963.10 mmol/kg = lowest and 2069.1 mmol/kg = highest) we had two different
estimates for DIC for every 30 seconds of the 10-minute replicates.
From the resulting DIC values for each replicate, the rate of change of
total DIC (micromoles per kilogram of seawater) over time (seconds) (mol of
DIC/kg *s) was calculated by plotting the DIC values over time and calculating
the slope.
Four separate resampling t-tests were then performed in order to determine
if there was a significant difference between the DIC/s values for the following
groups: eelgrass using high TA value vs. eelgrass using low TA value, no eelgrass
using high TA value vs. no eelgrass using low TA value, eelgrass using low TA
value vs. no eelgrass using low TA value, eelgrass using high TA value vs. no
eelgrass using high TA value. After performing each test the results were
converted into rates of change of DIC over each minute (DIC/m units=
mol/kg* m) and rates of change of DIC per hour (DIC/m units= mol/kg* h) t
make the results more applicable.
99
100
IV. RESULTS
For the eelgrass treatment, all nine 10 minute replicates showed that pH
increased over time (Figure 24). For this treatment, replicate seven shows the
highest rate of increase in pH over time (Figure 25). The average initial pH for the
eelgrass treatment was 8.022 0.012 (standard error) and the average final pH
was 8.025 0.011 (standard error); a one-way parametric ANOVA revealed that
values were not statistically different from each other (α=0.05, p=0.736). The
maximum absolute difference for this treatment (final pH minus initial pH was
0.018 pH units, while the minimum difference was 0.001 pH units.
For the no eelgrass treatment, nine of the eleven replicates showed that pH
increased over time (Figure 26). Two replicates, replicates 5 and 7, showed a
decrease in pH over time (Figure 27). The average initial pH for the no eelgrass
treatment was 8.1090.026 (standard error), while the average final pH was
8.1580.033(standard error). A one-way parametric ANOVA indicated that these
values were not statistically different from each other (α=0.05, p=0.247). The
maximum absolute difference for this treatment (final pH minus initial pH) was
0.147 pH units (indicating a decrease of pH over time), while the minimum
difference was 0.007 pH units.
The no-eelgrass treatment had a significantly higher average pH, average
temperature, and average salinity than the eelgrass treatment (Table 9). The
results indicated that the no eelgrass treatment had a significantly higher
temperature than the eelgrass treatment (difference=0.35C, α=0.05, number of
101
trials=1000 and p=0.012). Salinity was also significantly higher in the no eelgrass
treatment than in the eelgrass treatment (dif=0.33 ppt, α=0.05, number of
trials=1000, and p=0.001). Similarly, pH was also significantly higher in the no
eelgrass treatment than in the eelgrass treatment (dif=0.12 pH units, α=0.05, 1000
trials and p=0.002).
A resampling t-test was used to asses if there was a significant difference
in the rates of change of pH over time (pH/min) between the eelgrass treatment
(mean=0.000843 pH/minute) and the no eelgrass treatment (mean=0.0239
pH/minute). The results showed that the rates of pH/minute were not
significantly different between treatments (=0.05, 1000 trials and p<0.136)
(Table 9).
102
8.080
8.060
pH
8.040
y=
1.40E-05x
+ 8.023
8.020
8.000
7.980
7.960
7.940
0
100
200
300
400
500
600
Time (s)
Replicate number
1
2
3
4
5
6
7
8
9
average pH/s
Figure 24. Change in pH over time for all of the nine replicates in the eelgrass treatment.
The continuous black line represents the average change pH/s for all the replicates within
this treatment, the equation on the right describes this line. The average rate of pH/s was
then converted to pH/min for statistical analysis.
0.025
Average rate of ΔpH/min
0.020
0.015
0.010
0.005
0.000
1
2
3
4
5
6
7
8
9
-0.005
-0.010
-0.015
Each of the nine replicates from the eelgrass treatment
Figure 25. Average rate of change in pH/min for all the replicates in the eelgrass
treatment. Error bars denote the standard error of the mean.
103
8.35
8.3
y=
2.51E04x +
8.139
8.25
pH
8.2
8.15
8.1
8.05
8
7.95
0
100
200
300
400
500
600
Time(s)
Replicate number
1
2
3
4
5
6
7
8
9
10
11
average pH/s
Figure 26. Change in pH over time for all of the eleven replicates in the no eelgrass
treatment. The continuous black line represents the average change pH/s for all the
replicates within this treatment, the equation on the right describes this line. The average
rate of pH/s was then converted to pH/min for statistical analysis
0.025000
Average rate of pH/min
0.020000
0.015000
0.010000
0.005000
0.000000
1
2
3
4
5
6
7
8
9
10
11
-0.005000
-0.010000
-0.015000
Each of the eleven replicates from the no eelgrass treatment
Figure 27. Average rate of change in pH/min for all the replicates in the no eelgrass
treatment. Error bars denote the standard error of the mean.
104
Eelgrass
treatment
SEM
No
eelgrass
treatment
SEM
25
1
1
0
<0.001
Average temperature (C)
8.49
0.02
8.84
0.08
0.012
Average salinity from
water samples (ppt)
28.91
0.12
29.24
0.03
0.336
Overall average pH
8.02
0.01
8.14
0.03
0.002
Average ΔpH/s
1.40E-05
5.50E-06
3.98E-04
2.51E-04
0.136
Average ΔpH/minute
8.43E-04
3.30E-04
2.39E-02
1.51E-02
0.136
5.06E-02
1.98E-02
1.43E+00
9.05E-01
0.136
Variable
% of estimated eelgrass
coverage
Average ΔpH/hour
p-value
=0.05
Table 9. Comparison between variables for eelgrass and no eelgrass treatments and their
respective standard error of the mean (SEM).
For the eelgrass treatment, using the lowest alkalinity value (1963.1
mol/kg) the rate of change of DIC over each minute (DIC/min) for each
replicate ranged from -0.003 to -0.594 mol of DIC/kg * min (indicating an
increase in pH). Using the highest alkalinity value (2069 mol/kg) the DIC/min
for each replicate in the eelgrass treatment ranged from -0.003 to -0.62 mol of
DIC/kg*min (indicating an increase in pH). The average DIC/min for all
replicates in the eelgrass treatment was -0.18 0.06 mol of DIC/kg (calculated
using low TA) or 0.19 0.06 mol of DIC/kg* min (calculated using high TA).
This rate is equivalent to an uptake of 10.8 3.7 mol of DIC/kg * hour
105
(calculated using low TA value) or 11.2 3.9 mol of DIC/kg* hour (calculated
using high TA value) (Table 10).
For the no eelgrass treatment, using the lowest alkalinity value (1963
mol/kg) the average rate of DIC over each minute (DIC/min) ranged from 6.3
mol of DIC/kg*min (indicating a decrease in pH) to -8.0 mol of DIC/kg*min
(indicating and increase in pH). For the same treatment, using the highest
alkalinity value (2069.1 mol/kg) the rate of DIC/min ranged from 6.6 mol of
DIC/kg*min (indicating a decrease in pH) to -7.9 mol of DIC/kg*min
(indicating an increase in pH). The average (DIC/min) for all replicates in this
treatment was -2.0 1.2 mol of DIC/kg*min (calculated using low TA value)
and -2.0 1.2 mol of DIC/kg*min (calculated using high TA value). This rate of
change is equivalent to an uptake of 117.8 ± 68.7 mol of DIC/kg* hour
(calculated using low TA value) and 121.5 70.2 mol of DIC/kg* hour
(calculated using high TA value) (Table 10).
106
EELGRASS
Average SEM Average
ΔDIC
for
ΔDIC
µmol/kg* average µmol/kg
min
ΔDIC * hour
µmol/kg
* min
SEM
for
average
ΔDIC
µmol/kg
*hour
NO EELGRASS
Average SEM Average
ΔDIC
for
ΔDIC
µmol/kg* average µmol/kg
min
ΔDIC * hour
µmol/kg
* min
SEM
for
average
ΔDIC
µmol/kg
*hour
Calculated
using lowest
alkalinity
value (1963.1
mmol/kgSW)
-0.18
0.06
-10.8
3.7
-2.0
1.2
-117.8
68.7
Calculated
using highest
alkalinity
value (2069.1
mmol/kgSW)
-0.19
0.06
-11.2
3.9
-2.0
1.2
-121.5
70.2
Table 10. Average rate of change of dissolved inorganic carbon (DIC) over time and its
respective standard error of the mean (SEM) for both treatments.
The two resampling t-tests performed to determine if the TA value
used had a significant effect on the average DIC/min within each treatment were
not significant. Hence, the average DIC/min for eelgrass treatment calculated
using the low TA value (1963.1 mol/kg) was not significantly different from the
average DIC/min for the eelgrass treatment calculated using the high TA value
(2063.1 mol/kg), the same result applies for the no eelgrass treatment.
The two resampling t-tests performed to determine if the average
DIC/min between the eelgrass treatment and the no eelgrass treatment was
significantly different when using the same TA value. The results showed that
there was no significant difference between the average DIC/min calculated
using the low TA value for eelgrass (-0.20.1 µmol of DIC/kg*min) and no
107
eelgrass treatment (-2.01.2 µmol of DIC/kg*min) (=0.05,1000 trials, p=0.166).
Likewise, there was no significant difference between average DIC/min
calculated using the high TA value for eelgrass (-2.01.2 µmol of DIC/kg*min)
and the no eelgrass treatment (2.01.2 µmol of DIC/kg*min)( (=0.05,1000
trials, p=0.142).
In general, the calculations for the carbonate chemistry for both treatments
(calculated using the same TA values) showed that the no-eelgrass treatment
resulted in lower average DIC and lower average pCO2 values than the eelgrass
treatment. Similarly, the no eelgrass treatment contained a higher proportion of
the DIC in the form of carbonate ion (CO3-2) than the eelgrass treatment (Table 11
and Table 12).
Experimental variable
Eelgrass
SEM
No
SEM
eelgrass
TA value used
1963.1
N/A
1963.1
N/A
Average pH
8.02
0.01
8.14
0.03
Average temperature (C°)
8.49
0.02
8.84
0.08
Average pCO2 (µatm)
369.7
10.7
278.39
21.01
Total DIC (µmol/kg)
1840.7
3.6
1643.4
12.4
Total H2CO3 (µmol/kg)
17.6
0.5
13.1
1.0
1730.8
5.1
1658.9
18.9
92.26
2.01
120.8
7.5
Ω calcite
2.27
0.05
2.97
0.19
Ω aragonite
1.4
0.03
1.9
0.1
-
Total HCO3 (µmol/kg)
Total CO3
-2
(µmol/kg)
Table 11. The average values of carbonate chemistry variables and their respective
standard error of the mean (SEM) for each treatment calculated using the lowest total
alkalinity (TA) value available for Port Gamble.
108
Experimental variable
Eelgrass
SEM
No
SEM
eelgrass
TA value used
2069.10
N/A
2069.10
N/A
Average pH
8.02
0.01
8.14
0.03
Average temperature (C°)
8.49
0.02
8.84
0.08
Average pCO2 (µatm)
390.2
11.2
293.9
22.2
Total DIC (µmol/kg)
1942.5
3.7
1892.8
12.9
Total H2CO3 (µmol/kg)
18.6
0.6
13.9
1.1
Total HCO3 (µmol/kg)
1826.6
5.3
1751.4
19.8
Total CO3 -2 (µmol/kg)
97.4
2.1
129.33
8.2
Ω calcite
2.4
0.05
3.1
0.2
Ω aragonite
1.5
0.03
2.0
0.1
-
Table 12. The average values of carbonate chemistry variables and their respective
standard error of the mean (SEM) for each treatment calculated using the highest total
alkalinity (TA) value available for Port Gamble.
109
V. DISCUSION OF RESULTS
The results showed that the pH increased over time in all the replicates of
the eelgrass treatment, which suggests that this ecosystem was acting as a net
autotrophic ecosystem during the period when the experiment took place. These
findings are consistent with previous studies (Hendriks et al., 2013; Shishido,
2013; Unsworth et al., 2012) which have shown that the carbon uptake of
seagrasses can lead to an increase in the pH of seawater. Unsworth et al. (2012)
reported an increase between 0.01 and 0.06 pH units for the water column directly
above eelgrass beds located in the Indo Pacific region during winter (with a depth
of 1 meter, 6 hr residence time and 25C) (Unsworth et al. supplemental data).
Shishido (2013) estimated a maximum increase of 0.05 pH units in the water
column above Z. marina beds in Puget Sound (with a 6 h residence time,
temperature and season not specified). If we were to calculate the pH/hr from
the maximum increase in pH reported by these studies, we would obtain a rate of
change of 0.008 to 0.01pH units/hr, which seems very low compared to our
reported rate of 0.05 pH units/hr for the eelgrass treatment. Both Unsworth et al.
(2012) and Shishido (2013) assume a static system, in which the water remains on
top of the seagrass beds for 6 hours as it is being diluted. Thus, it was expected
that the change in pH reported by both studies would be higher than the change in
pH reported in our study, since we witnessed movement of the water column over
time. It is important to emphasize that direct comparisons between the results of
our study and those of Unsworth et al.(2012) or Shishido (2013) are impossible
110
because unlike these studies, we did not take into account net primary production
rates (NPP), shoot density, light intensity, area occupied by the seagrass bed, or
the hydrodynamics of the place.
The results showed that on average, the pH also increased over time in the
no eelgrass treatment; this is contrary to what was expected. We expected that the
no eelgrass treatment would show a decrease in pH over time resulting from
respiration being greater than photosynthesis in this ecosystem. The video footage
revealed that the no eelgrass treatment had a considerable amount of mollusks
(oysters and clams) and echinoderms (sea stars and sand dollars); thus, the
expectation was that the respiration and calcification rates of these organisms
would result in a decrease in pH. Respiration decreases the pH by adding more
carbon dioxide (CO2) to the water and calcification decreases the pH by taking up
carbonate (CO3-2) from the water, thus reducing alkalinity and by releasing CO2
as a by-product of the calcification reaction. However, our results suggest that for
the no eelgrass treatment, other processes that decreased CO2 dominated over the
processes that increased CO2 during the duration of our experiment.
In spite that the no eelgrass treatment had positive average rate of change
in pH/time, there was no significant difference between the pH/ time for both
treatments. The most logical explanation for this result is that photosynthesis rates
were constrained due to winter conditions. It is well known that low temperatures
and low irradiance levels of photosythetically active radiation (PAR) slow
photosynthesis in Z. marina (Larkum et al., 2006; Mumford, 2007; Nejrup &
Pedersen, 2008; Touchette & Burkholder, 2007). Our data shows that during our
111
experiment, the average temperature for the water column above eelgrass beds
was 8.49C. This temperature is quite low considering that the lowest temperature
that Z. marina can survive in is 5C and that the ideal temperature for maximum
eelgrass growth is around 20C (Touchette & Burkholder, 2007). Similarly,
eelgrass is known for needing high levels of light to grow and reproduce. During
the summer, when most of Z. marina growth happens, Puget Sound gets
approximately 5 to 6 hours of peak solar irradiance, while during winter, Puget
Sound only gets approximately 0.8 to 1.6 peak solar irradiance hours (Honsberg
& Bowden, n.d.; National Renewable Enegy Laboratory, n.d.). Thus, it is most
likely that low temperatures and low irradiance levels significantly limited
photosynthesis in eelgrass beds during our experiment.
In addition to photosynthesis being constrained by low irradiance and low
temperatures, it is feasible that other variables, such as the differences in
photosynthesis rates of other species and differences in depth affected the
pH/time for the no eelgrass treatment, resulting in an overall increase of pH/time
(as further explained below). This overall increase in pH/time for the no eelgrass
treatment probably thwarted any significant carbon uptake that occurred in the
eelgrass treatment, which resulted in the rates change of pH/time being
statistically equal between both treatments.
The overall increase in pH/time for the no eelgrass treatment could also be
attributed to shallower water column depth. The video footage showed that the no
eelgrass areas were consistently shallower (approximately 0.5 meters in depth)
112
than the eelgrass areas (approximately 1-1.5 meters in depth). Assuming that
alkalinity was the same for both treatment areas, shallower areas contain less
water and thus are more sensitive to changes in the concentration of hydrogen
ions or DIC for a given amount of biological activity. For example, a decrease in
the concentration of hydrogen ions ([H+]) in a shallower water column would
result in a greater decrease in pH, than if the water column was deeper because
there is proportionately more water to dilute the concentration of H+ in the latter
case. The sensitivity of shallower waters to changes in [H+] is supported by the
data, which shows that the no eelgrass treatment exhibited greater variability,
having a larger standard error than the non eelgrass group. In fact, two of the 11
replicates for the no eelgrass treatment showed a decrease in pH over time, while
none of the replicates for the eelgrass treatment showed a decrease in pH over
time.
A less plausible explanation for the no eelgrass treatment having a higher
(although not significant) pH/time than the eelgrass treatment is that the no
eelgrass treatment had a higher net photosynthesis rate than the eelgrass
treatment. This could be due to the no eelgrass treatment having a higher amount
of non-seagrass photosynthetic organisms and/or due to the eelgrass treatment
having a higher ecosystem respiration rate. The first point is supported by the
video footage, which showed that although the no eelgrass treatment did not
contain a significant amount of seagrass, there were other photosynthetic species
present in this ecosystem. Abundant red and green algae were observed in the no
eelgrass treatment; predominant species were the green algae Ulva sp. and the red
113
algae Hildenbrandia sp and Gracilaria sp. It was not possible to quantify the
percent cover of algae because some video frames where blurry and in many
cases it was impossible to distinguish crustose algae from shadows in the
sediment and rocky structures. Because we did not quantify photosynthetic
activity, the contribution that other photosynthetic organisms (such as algae and
phytoplankton) had on the pH/time for each treatment is unknown. However, a
study by Ziegler & Benner (1999) indicates that the gross primary production of
benthic algae can be about half that of seagrass beds and that occasionally, the
NPP of benthic algae communities can be higher than that of seagrass beds. The
second point, which assumes that the eelgrass treatment had a higher respiration
rate than the no eelgrass treatment, can be attributed to eelgrass beds being a
highly productive ecosystem. Eelgrass beds produce a large amount of plant
biomass that harbors many species of fish and invertebrates and that fuels
detritivorous pathways. Hence, it is reasonable to assume that the eelgrass
treatment might have a higher rate of ecosystem respiration, due to higher
heterotrophic consumption and decomposition, than the no eelgrass treatment.
In conclusion, our experiment showed that eelgrass beds in Port Gamble
did not have a significant effect in the change of pH over time, when compared to
the control treatment. Thus, eelgrass beds in Port Gamble were not capturing
enough carbon to cause a significant change in pH/time during the winter days.
These results are possibly influenced by variables, such as depth of the water
column and difference in respiration and photosynthesis rates between treatments,
which were not taken into account in this experiment for simplicity purposes.
114
The results of this experiment are only applicable to diurnal low tide
winter conditions in Port Gamble. Even though inferences on the carbon
assimilation capacity of eelgrass beds in Port Gamble can be drawn based on this
experiment, further experiments are necessary in order to determine if eelgrass
beds in Port Gamble are net carbon sinks. A carbon sink is an ecosystem that has
a positive net ecosystem carbon balance (Archer, 2010). A net ecosystem carbon
balance (NECB) is defined as the net rate of organic carbon accumulation in (or
loss from) ecosystems. Thus, a NECB implies that the ecosystem absorbs more
carbon than it releases thought a defined period. In order to determine if eelgrass
beds in Port Gamble Bay are carbon sinks, one would need to study how much
carbon is captured and released through a year. Seagrasses, like all photosynthetic
organisms, release carbon dioxide at night when respiration is dominating due to
the lack of photosynthesis. This change in their metabolic cycle is highly
dependent on the amount of irradiance and temperature. It is common knowledge
that some seagrass ecosystems switch from being carbon sinks during the summer
and spring, to being carbon sources during wintertime (Beer & Waisel, 1979).
This happens because as irradiance decreases during the winter, their
photosynthetic rates decrease, sometimes falling below their respiration rates.
Additionally, in certain regions of the world, seagrasses are annual plants with
their leaves dying during the winter (but their rhizomes and roots surviving
underground). The fate of the dead biomass depends on the decomposition and
burial rates of each site. Therefore, in order to determine if eelgrass beds in Port
Gamble Bay are net carbon sinks, one would need to study the ecosystem’s
115
photosynthesis and respiration rates, as well as the burial and export rates, during
night and day and during different seasons of the year. Determining whether an
ecosystem is a net carbon sink is a massive undertaking. Thus, even through
inferences can be made about how eelgrass beds in Port Gamble Bay act during
other months of the year, and at different irradiance levels based on the results of
this experiment, the data presented in this study is not enough to draw definite
conclusions about the net carbon sink capacity of eelgrass beds in this region of
Puget Sound.
116
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VII. APPENDICES
APPENDIX A
Determination of the pH of seawater using the indicator dye m-cresol purple
(Hofmann lab protocol)
We follow SOP 6b (Guide to Best Practices, Dickson et al., edited 1/28/2009) for
the spec pH method. Major alterations we have had to make for our lab are:
-We collect water samples for pH analysis in either 125mL glass
stoppered bottles with no headspace. (SOP 6b indicates that the water
samples should be collected in the optical cells directly. This is not
practical for our lab since we have no good way of storing or warming all
of those cells at once).
-We use a BioSpec 1600 spectrophotometer which holds cells with a 1 cm
path-length (rather than the 10 cm one specified in SOP6b). Therefore, we
add 3mL of seawater sample to each cuvette and 50uL of dye.
Summary of relevant variables:
A1 (absorbance 1) = absorbance at 578nm
A2 (absorbance 2) = absorbance at 434nm
A1/A2=ratio of the two absorbances
A1/A2corr=ratio corrected for the addition of dye.
*730 is a non-absorbing wavelength. This value is used to correct for
background noise associated with the spec
Preparation of dye and determination of dye correction factor
Prepare a 2mmol solution of m-cresol purple in MilliQ. Adjust the pH to
7.9 (i.e. the approximate pH of seawater) using HCl.
For each batch of dye prepared, a correction factor for the addition of dye
must be determined. A full explanation of this is in section 8.3 of the
Guide to Best Practices (Dickson et al., edited 1/2009). Briefly, you
should:
-Prepare seawater samples with three distinct pH values (e.g. 7.8, 8.0, 8.2)
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For each sample:
-Measure and record absorbance of sample at 730, 578, and
434nm.
-Add 50uL of m-cresol purple and measure and record absorbance
at the three wavelengths.
-Add a second 50uL of m-cresol purple and measure and record
absorbance at the three wavelengths.
-Determine A1/A2 for each addition of dye (see SOP 6b and pH calculation
worksheet).
-Perform a linear regression A1/A2 vs. ΔA1/A2
A1/A2corr = (A1/A2)-V[a+b(A1/A2)] (see 8.3, SOP 6b)
Sampling and storage of sample before analysis
Collect seawater sample in 125 mL glass stoppered bottle OR scintillation
vial using silicon tubing1. There should be no headspace in either
collection vessel.
pH analysis should be performed immediately after collection. Place
capped or stoppered samples in 25ºC water bath to begin warming prior to
analysis.
Measurement procedure
Clean and dry a quartz cuvette.
Pipet 3mL seawater sample into quartz cuvette. Cap the sample and
carefully clean the exterior of the cell with a Kimwipe.
Place in warming chamber. Warm sample to exactly 25ºC.
Measure and record the absorbances at the three wavelengths (730nm,
578nm, 434nm).
Pipet 50uL dye into the cuvette, replace the cap, and invert the cell to mix
the sea water and dye.
Return the cell to the spectrophotometer and again measure the
absorbances at the three wavelengths.
1
If doing both pH and TA analysis, we collect sample in 125mL stoppered bottle. pH analysis
only requires 3mL of sample, which we remove from the bottle before performing TA analysis. If
only measuring pH, we use scintillation vials to limit the water being removed from treatment
buckets.
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Calculation and expression of results
See section 8 of SOP6b and annotated pH calculation worksheet
Note: you need salinity to calculate pk2. We use a YSI 3100 conductivity/salinity meter
and generally take one salinity measurement for each bucket once a day and then use that
value for calculation of the pH throughout the day.
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APPENDIX B
Hofmann Lab – Total Alkalinity Titration Protocol
Rivest, E.B., Bitter, M.B., Hancock, J.R., (2013)
1. Turn on Mettler Toledo T50 titrator
2. Open LabX titration on desktop
3. Press Purge option on tablet
a. Leave pH probe and bubbler out
b. Attach purge acid cup
c. Gently dislodge air bubbles from lines between titrant and burette,
and burette and cup, during purge
d. Press back twice to return to home (post purge)
4. Remove Purge acid cup and dispose liquid
5. Rinse all probes with DI water and dry with kimwipe
6. Collect 98-101 grams of filtered sea water (FSW) for titration
7. Collect approximately 75 grams of FSW and measure salinity using
bench-top meter
8. Attach FSW cup to titrator
9. Make sure bubbler is turned on
10. Insert pH probe into sample cup (make sure probe is filled with solution)
11. Open plug on pH probe
12. In Lab X titration, click ‘Analysis tab’. Make sure titrator is in “idle”
mode
13. Right click ‘EQP_Rivest 2012-020’, click “run”
a. Enter sample id and mass
b. Click “start”
14. Once titration begins (propeller begins to spin), insert bubbler into sample
cup
15. Observe first sample trajectory carefully for any abnormal spikes in graph
16. After completion of titration, open R on desktop.
a. Within R program, open ‘TA_Emily (1).R’
17. On desktop, open ‘R data files’ folder
a. Open ‘Result_TA.csv’
18. On LabX, click the ‘Reports’ tab. Find the sample run using the time
stamp. Expand the menus until you select option ‘EQP titration’
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a. Copy and paste the data below the graph into ‘Result_TA.csv’
b. Make sure that there no rows that contain data from a previous
titration. If there are, delete them
c. Save the spreadsheet
19. On R-Script, change the weight, salinity and name of sample.
a. Copy and paste the entire code onto R-console.
b. Actual results will appear in grey
c. For non-poisoned samples, use TA x 1,000,000
d. For poisoned samples, use TA corrected (TA x 1,000,000 x 1.002)
e. Record TA to two decimal places
20. After each titration, rinse and dry all probes
21. Dispose samples into proper waste containers
22. Repeat for second FSW sample and reference both samples for similarity
with each other and with previous dates’ FSW samples
23. Make sure to always record results in general lab notebook as well as your
own.
24. If necessary, continually repeat new FSW samples until results become
consistent.
25. Next, repeat steps 6-21 with CRM from Dickson lab. Use salinity from
CRM certification. Make sure your calculated TA is within +/- 10umol/kg
of certified value.
26. If results are accurate, move on to your samples. For each sample, repeat
steps 6-21.
27. Re-run a CRM sample after every 10 experimental samples and at the end
of your day of titrations. This confirms that the pH probe did not drift
over time.
28. To shut down, rinse and dry all probes. Put the plug back on the pH probe
and store it in its specific storage solution. Place a cup of DI on the
titrator for the other probes. Turn off the bubbler. Shut off the titrator and
close Lab X.
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APENDIX C
First segment showing how data was organized in a spreadsheet
132
Second segment showing how was organized in a spreadsheet
133
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Tejeda_CMESThesis.pdf