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Title
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Effects of elevated water temperatures on different populations of Zostera marina
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Date
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2021
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Creator
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Wukasch, JJ
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Identifier
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Thesis_MES_2021_WukaschJ
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extracted text
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EFFECTS OF ELEVATED WATER TEMPERATURES
ON DIFFERENT POPULATIONS OF Zostera marina
by
Johannes J. Wukasch
A Thesis
Submitted in partial fulfillment
of the requirements for the degree
Master of Environmental Studies
The Evergreen State College
December 2021
©2021by Johannes J. Wukasch All rights reserved.
This Thesis for the Master of Environmental Studies Degree
by
Johannes J. Wukasch
has been approved for
The Evergreen State College
by
John Kirkpatrick
Member of the Faculty
12/10/2021
ABSTRACT
Effects of elevated water temperatures on different populations of Zostera marina
Johannes J. Wukasch
I tested the effects of elevated water temperature, in the upper threshold limit, on the ecological
performance of the native eelgrass Zostera marina in a mesocosm experiment to identify the
most resilient population. Five populations (Cherry Point, Elliott Bay, Fidalgo Bay, Nisqually
Reach, and Willapa Bay) spanning the Washington coast and Puget Sound were exposed to four
constant treatment levels (14, 17, 20, 23 °C) during a 6-week hydroponic experiment. Changes in
eelgrass performance were evaluated by measuring morphological changes and photosynthetic
efficiency. The Fidalgo Bay population was more tolerant to thermal stress than Cherry Point,
Elliott Bay, Nisqually Reach, and Willapa Bay populations. By the end of the experiment,
Fidalgo Bay overall had the lowest percentage loss of shoot length (14, 17 and 20°C treatments),
lowest blade loss (14, 17 and 20°C), most growth (14, 17 and 20°C) and highest photosynthetic
yield (14°C). The initial morphological measurements indicated that morphology was possibly
connected to eelgrass performance as Fidalgo Bay had the longest blade length, sheath width,
and sheath length. Fidalgo Bay outperformed all populations even though it has the coolest daily
mean water temperature. Higher temperatures significantly affected growth and survival in
treatment levels 17°C and higher for all five populations. Changes in eelgrass performance
occurred noticeably during week two in all four performance measurements. This indicated that
long-duration thermal stress has negative consequences for eelgrass productivity and resilience.
Table of Contents
List of Figures……………………………………………………………………………………. v
List of Tables……………………………………………………………………………………. vi
Acknowledgments………………………………………………………………………..…….. vii
Literature Review………………………………………………………………………………… 1
Introduction………………………………………………………………………………………. 6
Material and Methods …………………………….……………………………………..………. 8
Sample sites…………………………………………………………………………………... 8
Experimental design……………………………………………………………….…....…… 10
System setup………………………………………………………………………………… 11
Eelgrass specimen collection, pre-treatment, and treatment……………………….……...… 14
Eelgrass morphology………………………………………………………………………... 16
Chlorophyll fluorescence (PAM)………………………………………………….………… 16
Results……………………………………………………………………………….………….. 17
Initial measurements……………………………………………………………….………... 17
Tank temperatures………………………………………………………………..………….. 20
Shoot length……………………………………………………………………….………… 22
Blade count……………………………………………………………………….…………. 25
Growth………………………………………………………………………….…………… 28
Photosynthetic yield……………………………………………………………….………… 31
Discussion…………………………………………………………………………….………… 33
References………………………………………………………………………….…………… 37
iv
List of Figures
Figure 1: A map of the five sample sites ……………………………………………….………. 9
Figure 2: Annual mean daily water temperature …………………………………..…………... 10
Figure 3: System setup ……………………………………………………..………………….. 12
Figure 4: Mesocosm setup ………………………………………………..…………………… 13
Figure 5: System layout …………………………………………………..…………………… 14
Figure 6: Eelgrass attachment ……………………………………………………..….……..… 15
Figure 7: Mean averages for initial measurement of shoot length ……………..…..…….…… 17
Figure 8: Mean averages for initial measurement of photosynthetic yield …………..….….… 18
Figure 9: Morphological differences ………………………………………………..….……... 19
Figure 10: Average tank temperatures ………………………………………….……..………. 20
Figure 11: Comparable changes in shoot length ………………………..………….…..……… 23
Figure 12: Comparable changes in blade count ………………………………….……..……... 26
Figure 13: Comparable changes in growth …………………………………….………..…….. 29
Figure 14: Comparable changes in photosynthetic yield ……………………………………… 32
v
List of Tables
Table 1: Relative std dev of tank temperatures ………………………………….…………….. 18
Table 2: Std dev of initial measurement of shoot length and photosynthetic yield …….……... 20
Table 3: P-values for shoot length ……………………………………………………….……. 22
Table 4: P-values for blade count ……………………………………………………….…….. 25
Table 5: P-values for growth ………………………………………………...………..…….… 28
Table 6: P-values for photosynthetic yield …………………………………………….……… 31
vi
Acknowledgements
This project was made possible with the vision of Cinde Donoghue from the Department of
Natural Resources. Cinde was able to secure the funding necessary and set up an interagency
agreement between The Evergreen State College and DNR. I also thank John Kirkpatrick for his
guidance. And thank you to all my colleagues at DNR that assisted me in the many ways that
you showed up. Lastly, I want to give a special thanks to Cassidy Johnson for spending the
summer with me and taking over 4000 measurements during the experiment—another Hawaii
trip is in order.
vii
Literature Review
Over the last few years, there have been numerous studies that looked at eelgrass loss due to
human activity and natural induced causes (Duarte, 2002; Orth et al., 2006; Short and Neckles,
1999). The goal of this literature review is to highlight some of the most relevant articles that
pertain to the project. Many factors will negatively affect eelgrass but with this review, I will
focus on elevated water temperatures. First, we will look at some of the stressors that will affect
eelgrass, followed by how these stressors will impact eelgrass. Thirdly, we will look at how
climate change might contribute to these stressors and then look at results from stressor studies
done on eelgrass. Lastly, I will discuss the Department of Natural Resources’ ANeMoNe
Network.
A global crisis for eelgrass ecosystems
Orth has written compressive reviews on the value of eelgrass, what makes it unique, and the
threats that it faces. Orth et al. (2006) review the evolutionary history of eelgrass and describe
the characteristics which allow a vascular plant to live underwater. The writer points out that the
rapid shift in eelgrass distribution is a result of human activity. Orth writes that eelgrass is an
indicator of ecosystem health and implies that a loss of eelgrass is a loss of ecosystem services
like nursery grounds, trophic transfer facilitation, current speed reduction which traps and stores
nutrients, carbon sequestration, and enhanced biodiversity. They identified multiple stressors that
led to eelgrass decline including water quality, shifting sediment, increased nutrients, and
increased temperatures. Other emerging threats to eelgrass are aquaculture activities and invasive
species. Lastly, the writer touched on the issues of restoration, conservation, management, and
1
monitoring. Eelgrass is good indicator species, and their loss is usually the symptom of a larger
problem. To effectively conserve eelgrass, resource managers must identify and address
problems that affect coastal systems like water quality and land-use practices. Restoration efforts
should then consider the natural capacity of eelgrass to recover.
Possible effects of climate change on eelgrass
Short and Neckles (1999) evaluated how climate change might affect eelgrass productivity
and distribution by applying current eelgrass biology knowledge and how various taxa respond
to the environment. Two of the major environmental forcing factors that are likely to affect
Zostera marina’s productivity and distribution are rising sea levels and increasing water
temperatures. Depending on the status of the ecosystem and the location of the interaction, these
forcing factors can have compounding effects and may act in a variety of ways.
The first factor, rising sea level, will affect the amount of light that the eelgrass receives as the
amount of light that travels through the water column decreases at an exponential rate the deeper
it must penetrate. The change in water depth will cause a shift in the eelgrass habitat location as
it moves to areas with higher light levels that are better suited for photosynthesis. Beds that
currently exist in the maximum depth distribution area will die off as the light availability
decreases. A coastal squeeze can occur when the beds are prevented from moving shoreward
while losing habitat in the maximum depth distribution area. Previously shallower areas might be
colonized by eelgrass, but it may also be hampered by human modification of the shoreline.
Light availability could also be affected by other factors such as tidal range change, increased
epiphytes, and increased turbidity which will exacerbate any negative effects.
2
The second important factor is increasing water temperatures, eelgrass respiration rate
increases faster than the photosynthetic rate which causes a decrease in the photosynthesis-torespiration ratio. Therefore, the eelgrass has a seasonal growth optimum with decreased
productivity when temperatures go above this optimum. The growth of epiphytes,
dinoflagellates, and diatoms are stimulated by higher water temperatures leading to lower light
availability. Increasing water temperatures are predicted to be detrimental to eelgrass.
Eelgrass response to climate change
Duarte (2002) forecast how eelgrass ecosystems will respond for the next 20 years from the
date published. They mainly focused on the effects of climate change and the pressure of an
increasing human population. It also covered the basic environmental requirements like sediment
type, redox potential, light level, and salinity.
Duarte talked about the effect of human impact on eelgrass ecosystems. The pressure on
eelgrass that stood out to me the most was the cultural eutrophication of coastal waters. This is
an issue that we have been struggling with at MAVEN (DNR’s research facility) where we are
currently growing eelgrass in large tanks outside. The tanks have been plagued with excess algae
growth which I hypothesize is due to the nutrient loading from the LOTT treatment plant in
Budd Inlet. The increasing nutrients in the water column stimulate macroalgae and
phytoplankton growth. As primary producers, they are well suited to take advantage of the
constant nutrient supply. The productivity of eelgrass is reduced when these primary producers
receive less light, by either covering the eelgrass or by filling the water column.
3
Duarte further listed more threats to eelgrass that are linked to the increasing human
population: increased physical disturbances due to human activity; increased nutrient loads, even
with the decline in wastewater treatment; changes in eelgrass coverage and productivity due to
climate change; increase in coastal aquaculture. Present global eelgrass decline is predicted to
worsen which leads to a decrease in biodiversity and modification of food webs.
More knowledge of eelgrass ecosystems is required to better manage and respond to threats
effectively. Duarte highlighted the need for increased monitoring and an early indicator of
decline. Pressures on eelgrass need to be managed with the easiest being mechanical
disturbances as it is a direct effect and easily identifiable. Indirect effects, such as nutrient inputs
from watersheds, are harder to manage and should be coupled with public education and
awareness of eelgrass ecosystems.
Effects of elevated temperature on growth dynamics of eelgrass
Lee et al. (2007) found that the optimal temperature range for Zostera marina growth has an
average of 15.3oC ± 1.6oC and the optimal temperature for eelgrass photosynthesis being 23.3oC
± 2.5oC which can vary by location and species. Lee concludes that photosynthesis and growth
may be inhibited with high summer temperatures and may ultimately be detrimental to the
success of eelgrass.
Lee found that eelgrass exhibits optimal growth at an intermediate temperature in its range of
tolerance while production is almost nonexistent during winter. As light decreases during winter,
the optimal temperature range for photosynthesis also decreases. Again, location determines the
extent to which the eelgrass goes dormant. Lower latitudes will have a shorter period of
4
dormancy or may be completely absent in warmer areas. Shoot growth decreases towards the end
of fall when ambient temperatures drop below the optimal range of 15oC -17oC and during
summer when ambient temperatures rise above the optimal range. The optimum temperature for
photosynthesis depends on light availability and ranges from 16oC to 30oC. Above this range,
eelgrass shows a decrease in productivity.
Puget Sound water temperatures
The Acidification Nearshore Monitoring Network (ANeMoNe) is a Department of Natural
Resources (DNR) water monitoring network that spans the Puget Sound and Pacific coast.
ANeMoNe is a network of sensors that continuously record water chemistry parameters like pH,
temperature, salinity, dissolved oxygen, and chlorophyll. This data can be used to evaluate sitespecific variability in pH, assess impacts on marine organisms, and identify potential sites that
may be more exposed or buffered to changes in marine chemistry. All the ANeMoNe sites are
located within eelgrass beds. Each site has two sensors with a sensor placed both inside and
outside of the eelgrass bed.
Eelgrass for this project was collected from five of the ten ANeMoNe sites. This ANeMoNe
report provided me with the temperature ranges of all five sites. Figure 2 shows the mean high
temperature at 12.4 oC and the low mean temperature at 7.4 oC. The mean temperature was
lowest in Fidalgo Bay at 7.4 oC with a variation of 5.3 oC followed by Cherry Point at 10.3oC
with a variation of 13 oC, Elliott Bay at 10.6 oC with a variation of 6.3 oC, and Nisqually Reach at
11.3 oC with a variation of 13.3 oC. Willapa Bay had both the highest mean temperature at 12.4oC
and the highest variation of 13.9 oC.
5
Introduction
Globally eelgrass is in decline due to threats from climate change, declining water quality,
and sustained pressure from coastal development (Hemminga and Duarte 2000; Orth et al.,
2006). This has resulted in a reduction of fish habitat, changes in coastal productivity, and
increases in erosion (Boese et al., 2008). Eelgrass has been shown to maintain healthy fish
populations (Zeller and Pauly, 2014), provide shoreline protection (Spalding et al., 2014), and
contribute to recreational activities (Barbier, 2010).
Eelgrass beds provide ecosystem services that rate higher than most other ecosystems on
earth, calculated to be US$19,002 ha-1 yr-1 (Costanza et al., 1997). Found in shallow waters along
much of Puget Sound’s shoreline, eelgrass acts as an ecosystem engineer by stabilizing sediment,
taking up nutrients, sequestering carbon, and providing habitat for a vast array of species
including waterfowl, shellfish, shrimp, herring, crab, and salmonids (Heck et al., 2003). Most
eelgrass species inhabit temperate waters of the northern hemisphere (den Hartog, 1970) and is
limited at the equator due to elevated temperatures.
The global average temperature is projected to warm between 2-4°C by 2100, mostly due to
human activity (IPCC 2014) with similar increases projected for marine systems (Sheppard and
Rioja-Nieto, 2005). These temperature changes can result in a slower growth rate, altered
metabolism, shift in distribution, and changes in patterns of sexual reproduction and changes in
their carbon balance (Short et al., 2001; Short and Neckles, 1999).
Temperature is among the most important factors determining eelgrass performance and
distribution. Regional experimental work found that native Z. marina was healthiest at 5–8 °C
and temperatures above 15 °C plants exhibit physiological stress (Thom et al., 2003). Another
study observed a reduction in growth rate and increase respiration rate at higher temperatures
6
(Coles et al., 2004). The reduced productivity for individual species from elevated temperatures
higher than the threshold will cause them to die off. Another study on the temperate Zostera
marina has also shown that a 5°C increase in normal seawater temperature led to a significant
loss in shoot density (Ehlers et al., 2008). However, they also determined that the genetic
diversity of the species indicates that it might be able to recover from extreme temperatures.
Increased water temperature has also been found to affect eelgrass seed germination and
flowering, altering abundance and distribution (Phillips et al., 1983). Additionally, the growth of
competitive epiphytes and algae might increase due to elevated water temperatures which can
reduce light availability hindering their growth (Beer et al., 1996).
Eelgrass is a highly productive photosynthetic marine species that fix large amounts of carbon
(Poppe, 2018). This growth fuels the nearshore food web. They are only found in shallow waters
ranging from 1 meter to 10 meters as they need high light levels to grow and reproduce. It is
therefore totally dependent on the nearshore environment (Mumford, 2007). It requires a welldefined set of physical conditions such as high ambient light and low water turbidity to allow it
to absorb as much light as possible. There is only a narrow band of shallow nearshore area where
adequate light is available, and the proper sandy substrate and sediment type exists. However,
this shallow band of habitability also means that eelgrass communities are prone to fluctuating
water levels that can lead to large and sometimes rapid changes in water temperature (Lartigue et
al., 2003). Therefore, most eelgrass populations must be able to tolerate these temporary
changes. It is known, however, that constant exposure to higher water temperature levels can be
lethal (Lee et al., 2007; Phillips, 1983).
There is an increasing understanding that climate change and other anthropogenic factors
could have a negative impact on eelgrass habitats. Indicators of resistance and recovery are
7
needed, to better understand and predict ecosystem response to environmental change.
Understanding how environmental stressors due to climate change might impact eelgrass
populations can help resource managers develop effective mitigation and restoration strategies.
This study aimed to experimentally evaluate how different populations of Z. marina found
across the Puget Sound and Washington coast respond to elevated water temperatures in the
upper threshold that could potentially limit survival and growth. 70 Eelgrass shoots from 5
populations were exposed to four levels of water temperatures for 6 weeks where shoot length,
blade count, growth rate, and photosynthetic efficiency were measured as response parameters.
Materials and Methods
Sample sites
The five sample sites Cherry Point (CP), Elliott Bay (EB), Fidalgo Bay (FB), Nisqually Reach
(NR), and Willapa Bay (WB) were chosen from DNR’s well-established program ANeMoNe
(Acidification Nearshore Monitoring Network). This network was established in 2015 to study
ocean acidification and climate change in Puget Sound nearshore environments. All ten
ANeMoNe sites are located within eelgrass beds. The five sites chosen represent some of the
main oceanographic regions recognized in the Puget Sound: Coastal (Willapa Bay), Northern
Puget Sound (Cherry Point, Fidalgo Bay), Central Puget Sound (Elliott Bay), and South Puget
Sound (Nisqually Reach). Locations include areas with the lowest mean water temperature
(Fidalgo Bay) and the highest mean water temperature (Willapa Bay).
8
Figure 1:
A map of Puget Sound and the Washington coast indicates the location of the five sample sites:
Cherry Point, Fidalgo Bay, Elliott Bay, Nisqually Reach, and Willapa Bay.
9
Figure 2:
Annual mean daily water temperature variation across all sample sites over the period of an
entire year (2018). The five sample sites: Cherry Point (CP), Elliott Bay (EB), Fidalgo Bay (FB),
Nisqually Reach (NR), and Willapa Bay (WB).
Experimental design
The experiment was conducted for six weeks during May 2021 to determine response to
elevated water temperatures by evaluating eelgrass performance considering variations in
morphological features among different populations. Each mesocosm contained five cages
10
anchoring five eelgrass shoots from each population. The eelgrass was subjected to four constant
water temperatures (14, 17, 20, and 23 °C) with three replicates for each temperature.
System setup
A flow-through system was used to ensure sufficient levels of nutrients and inorganic carbon
were maintained. Bay water was filtered through a sand filter and UV filter (80w) before being
cooled down to 12°C. The chilled water was supplied to a treatment tank (20gal) where the
temperature was raised to the required level by a heater (300w) and circulated into both the
mesocosm (100gal) and treatment tank by a pump (100w). Water temperatures in mesocosm
were maintained by a (100w) heater and water was circulated with a wavemaker (65w). Both
heaters were monitored and adjusted to maintain the required temperature by an Apex Controller.
Standpipes were standardized in length to control the water level of each tank. Water overflowed
through the standpipe removing debris and algae growing on the surface. The Apex continuously
recorded the temperature of each mesocosm. Even light distribution across the 4ft long tank was
provided by fluorescent grow lights (55w). Apex light meter adjusted the light intensity at the
surface to 120 μmol photons m−2 s−1 PAR which is close to the saturating level of eelgrass
(Marsh et al., 1986; Olesen and Sand-Jensen, 1993) on a 12-hour photoperiod. There were six
Apex instruments, each controlling 2 tanks.
11
Figure 3:
Experimental setup depicting all 12 mesocosms and the life support system.
12
Figure 4:
Close-up view of one of the mesocosms depicting the five cages of eelgrass at the bottom of the
tank and arrangement of equipment.
There were 12 mesocosms, each labeled with an associated Apex controller letter (A-F) and a
tank number (1-12). There were four treatment levels (14, 17, 20, and 23°C) and three-level
replicates for each treatment level. Each shoot was tagged with the following labeling scheme:
Site acronym, Apex letter (A-F), tank number (1-12), and shoot number (1-5) (Fig 6). Tanks A1,
A2, and B3 were treatment level 14°C. Tanks B4, C5, and C6 were treatment level 17°C. Tanks
D7, D8, and E9 were treatment level 20°C. Tanks E10, F11, and F12 were treatment level 23°C.
13
Figure 5:
System layout indicating Apex controller and tank labeling as well as temperature treatments.
Eelgrass specimen collection, pre-treatment, and treatment
Established shoots with well-developed rhizomes were collected from each of the five sites
during low tide between depth range of -1.5 and – 2.0 m in late April. Plants were carefully
removed from sediment by hand to ensure an intact rhizome system. Adult shoots bearing a
healthy-looking rhizome, defined as 5-7 internodes, were sampled. Eelgrass was transported in
cooler boxes filled with enough water from the sampling site to submerge all the eelgrass. A wet
cloth was placed on the surface to prevent eelgrass from drying out. On-site eelgrass was kept at
15°C and under saturated light conditions until used in the experiment (24 hrs maximum).
Senescent leaves were removed before transplantation to mesocosms. Shoots were further
standardized by cutting older internodes to leave only four healthy rhizome internodes. No
sediment was used as eelgrass had to be removed every week to be measured. Eelgrass was
attached to plastic mesh which was zip-tied to a cage constructed out of PVC pipe (Fig 6). Holes
14
were drilled in the pipe to allow air to escape once submerged. To prevent detritus buildup in and
around the rhizomes, the cages were designed with a one-inch gap at the bottom to allow a flowthrough of water. Each cage was anchored by a porcelain tile that was zip-tied to the cage.
Figure 6:
Eelgrass attachment to PVC cage and labeling.
Each week all the samples were removed, one population at a time, to be cleaned and
measured. Once removed, it was carefully placed in a tub with seawater of the same temperature
to keep eelgrass submerged while it is being cleaned. Epiphytes were scrubbed using a brush and
15
by running individual blades through fingertips. Initial morphology and PAM fluorometry were
measured at beginning of the experiment and once a week thereafter as described below.
Eelgrass morphology
To measure changes in eelgrass morphology characteristics related to elevated temperatures,
eelgrasses were closely monitored and measured once a week (days 0, 7, 14, 21, 28, 35, 42, and
49) for the duration of the experiment using the protocol outlined by (Short and Duarte, 2011).
Three different random shoots from each population in each tank were chosen weekly for
measurements. We recorded shoot count, shoot length (measuring tape in cm), sheath length
(calipers in mm), sheath width (calipers in mm), and the total number of leaves. Reproductivity
was measured from asexual lateral branching. The growth rate was assessed by using the pinprick method as outlined by (Short and Duarte, 2001) to determine the total leaf growth per shoot
relative to the days since last pricked (new leaf extension cm/day). New growth was measured
from the pinprick below the sheath to the pinprick on the newest inner leaf. Raw values for shoot
length, blade growth, and blade counts were used for statistical analysis.
Chlorophyll fluorescence (PAM: Pulse Amplitude Modulation)
Samples were tested for photosynthetic efficiency (Fv/Fm) by evaluating the chlorophyll
fluorescence of the leaf shoot adjacent to the meristem (youngest leaf) using a Diving PAM-II
Fluorometer (Heinz Walz, Effeltrich, Germany). A different shoot from each population in each
tank was selected so that no leaf was ever measured twice. Plants were tested one hour before the
photoperiod started while it was dark-adapted, and cellular respiration occurred. Fv/Fm readings
on the PAM were used for statistical analysis.
16
Results
Eelgrass performance was assessed using morphology (shoot length and the total number of
leaves), growth (new leaf extension), and photosynthetic efficiency (Fv/Fm) to decern
performance differences between populations. Means summaries were calculated for all
treatment level replicates. The data for shoot length and blade count was normalized as these are
absolute values. Through this loss, percentages were calculated from the initial
measurement/count for each week. A one-tailed T-test was used to see if there was a significant
difference between all the possible pairs of the five different populations. All calculations and
analyses were done in Microsoft Office Excel.
Initial measurements
Average Shoot Length
140.0
120.0
115.7
100.0
96.6
cm
80.0
86.0
60.0
40.0
50.8
54.3
CP
EB
20.0
0.0
FB
Site
NR
WB
Figure 7:
Mean averages for initial measurement of shoot length for each population. The five sample
sites: Cherry Point (CP), Elliott Bay (EB), Fidalgo Bay (FB), Nisqually Reach (NR), and
Willapa Bay (WB).
17
All measurements were taken on day one to establish a baseline. Fidalgo Bay had the longest
average shoot length at 115.7cm followed by Nisqually Reach at 96.6cm, Willapa Bay at 86cm,
Elliott Bay at 54.3cm, and the shortest being Cherry Point at 50.8cm.
Average Photosynthetic Yield
0.860
0.840
0.845
0.840
Fv/Fm
0.820
0.800
0.811
0.804
0.780
0.776
0.760
0.740
CP
EB
FB
Sites
NR
WB
Figure 8:
Mean averages for initial measurement of photosynthetic yield for each population. The five
sample sites: Cherry Point (CP), Elliott Bay (EB), Fidalgo Bay (FB), Nisqually Reach (NR), and
Willapa Bay (WB).
Elliott Bay had the highest photosynthetic yield at 0.845 Fv/Fm followed by Nisqually Reach
at 0.84 Fv/Fm, Willapa Bay at 0.811 Fv/Fm, Cherry Point at 0.804 Fv/Fm, and the lowest being
Fidalgo Bay at 0.776 Fv/Fm.
Table 1:
The relative standard deviation of initial measurements for shoot length and photosynthetic
yield.
CP
EB
FB
NR
WB
Shoot Length
15.1%
13.9%
16.8%
16.1%
12.2%
Photosynthetic Yield
7.4%
7.1%
7.7%
4.7%
6.1%
18
Figure 9:
Morphological differences between the five sample sites: Cherry Point (CP), Elliott Bay (EB),
Fidalgo Bay (FB), Nisqually Reach (NR), and Willapa Bay (WB).
19
Tank temperatures
Average Tank Temperatures
24
23
22
Temperature in °C
21
20
19
18
17
16
15
14
13
A1
A2
B3
B4
C5
C6
D7
D8
E9
E10
F11
F12
Figure 10:
Average tank temperatures over the course of the experiment.
Table 2:
The standard deviation of the tank temperatures is in °C.
A1
0.1
A2
0.1
B3
0.2
B4
0.6
C5
0.7
C6
0.6
D7
0.8
D8
0.7
E9
0.7
E10
0.1
F11
0.2
F12
0.2
20
Tank temperature readings were logged every ten minutes over the course of the experiment.
The average temperature for each tank was: A1=13.99°C, A2=14.02°C, B3=14.05°C,
B4=17.22°C, C5=17.31°C, C6=17.07°C, D7=19.74°C, D8=19.67°C, E9=19.7°C, E10=22.95°C,
F11=22.95°C, F12=23.03°C. The average for the three replicates in treatment level 14°C was
14.02°C, for treatment level 17°C it was 17.2°C, for treatment level 20°C it was 19.7°C and for
treatment level 23°C it was 22.99°C. On days 18, 19, and 20 there was a spike in temperature
due to extremely hot days during which tanks B4, C5, and C6 had more than a degree increase
for six hours.
21
Shoot length
Table 3:
P-values for shoot length from one-tailed T-test for each treatment level. Significance was
determined with a cutoff of p < 0.05. All significant p-values under that threshold are
highlighted in orange.
CP
EB
FB
NR
WB
CP
14°C
EB
0.019
FB
0.056
0.459
NR
0.071
0.010
0.085
WB
0.040
0.465
0.485
0.033
CP
EB
FB
NR
WB
CP
17°C
EB
0.026
FB
0.012
0.101
NR
0.048
0.032
0.033
WB
0.005
0.303
0.119
0.016
CP
EB
FB
NR
WB
CP
20°C
EB
0.060
FB
0.018
0.202
NR
0.067
0.079
0.034
WB
0.081
0.360
0.235
0.109
CP
EB
FB
NR
0.178
0.178
0.178
WB
CP
23°C
EB
0.178
FB
0.178
0.178
NR
WB
0.178
0.178
0.178
0.178
22
Figure 11:
Comparable changes in shoot length for the different populations at each treatment level over
the course of the experiment. The five sample sites: Cherry Point (CP), Elliott Bay (EB), Fidalgo
Bay (FB), Nisqually Reach (NR), and Willapa Bay (WB).
23
The shoot length of all populations decreased in all treatment levels over the course of the
experiment. There was substantial blade loss up to the sheath amongst all populations by week 2
in the 23°C treatment level. Fidalgo Bay had the least percentage loss for treatment level 14°C,
and overall slowest blade loss at 17°C and 20°C. There was a significant difference between
Elliott Bay and Cherry Point in treatment levels 14°C, 20°C, and 17°C. Cherry Point and
Nisqually Reach were significantly different from every other population at 17°C treatment
level. There was no significant difference between the populations at 23°C.
24
Blade count
Table 4:
P-values for blade count from one-tailed T-test for each treatment level. Significance was
determined with a cutoff of p < 0.05. All significant p-values under that threshold are
highlighted in orange.
CP
EB
FB
NR
WB
CP
14°C
EB
0.018
FB
0.024
0.324
NR
0.011
0.208
0.239
WB
0.054
0.319
0.266
0.429
CP
EB
FB
NR
WB
CP
17°C
EB
0.047
FB
0.010
0.003
NR
0.085
0.037
0.007
WB
0.090
0.143
0.005
0.249
CP
EB
FB
NR
WB
CP
20°C
EB
0.364
FB
0.288
0.235
NR
0.156
0.047
0.052
WB
0.393
0.496
0.377
0.160
CP
EB
FB
NR
0.178
0.178
0.178
WB
CP
23°C
EB
0.178
FB
0.178
0.178
NR
WB
0.178
0.178
0.178
0.178
25
Figure 12:
Comparable changes in blade count for the different populations at each treatment level over the
course of the experiment. The five sample sites: Cherry Point (CP), Elliott Bay (EB), Fidalgo
Bay (FB), Nisqually Reach (NR), and Willapa Bay (WB).
26
Fidalgo Bay had the lowest percentage loss for treatment level 14°C, and overall slowest
blade loss at 17°C and 20°C. There was a significant difference between Elliott Bay and Cherry
Point in treatment levels 14°C and 17°C. Fidalgo Bay was significantly different from every
other population at 17°C treatment level. There was no significant difference between the
populations at 23°C.
27
Growth
Table 5:
P-values for growth from one-tailed T-test for each treatment level. Significance was determined
with a cutoff of p < 0.05. All significant p-values under that threshold are highlighted in orange.
CP
EB
FB
NR
WB
CP
14°C
EB
0.009
FB
0.000
0.001
NR
0.004
0.084
0.000
WB
0.016
0.076
0.067
0.156
CP
EB
FB
NR
WB
CP
17°C
EB
0.020
FB
0.005
0.003
NR
0.065
0.141
0.026
WB
0.033
0.070
0.028
0.323
CP
EB
FB
NR
WB
CP
20°C
EB
0.053
FB
0.028
0.032
NR
0.112
0.279
0.023
WB
0.101
0.142
0.041
0.098
CP
EB
FB
NR
0.182
0.182
0.182
WB
CP
23°C
EB
0.182
FB
0.182
0.182
NR
WB
0.182
0.053
0.182
0.182
28
Figure 13:
Comparable changes in growth rate for the different populations at each treatment level over the
course of the experiment. The five sample sites: Cherry Point (CP), Elliott Bay (EB), Fidalgo
Bay (FB), Nisqually Reach (NR), and Willapa Bay (WB).
29
Fidalgo Bay had the most growth for treatment level 14°C whereas Willapa Bay had the most
stable growth. Fidalgo Bay was significantly different from every other population at 17°C
treatment level. There was no significant difference between the populations at 23°C.
30
Photosynthetic yield
Table 6:
P-values for photosynthetic yield from one-tailed T-test for each treatment level. Significance
was determined with a cutoff of p < 0.05. All significant p-values under that threshold are
highlighted in orange.
CP
EB
FB
NR
WB
CP
14°C
EB
0.024
FB
0.063
0.309
NR
0.275
0.026
0.065
WB
0.020
0.028
0.416
0.014
CP
EB
FB
NR
WB
CP
17°C
EB
0.003
FB
0.010
0.165
NR
0.049
0.045
0.050
WB
0.011
0.137
0.430
0.020
CP
EB
FB
NR
WB
CP
20°C
EB
0.054
FB
0.020
0.052
NR
0.042
0.163
0.029
WB
0.046
0.176
0.140
0.107
CP
EB
FB
NR
0.096
0.200
0.088
WB
CP
23°C
EB
0.182
FB
0.105
0.111
NR
WB
0.182
0.099
0.182
0.106
31
Figure 14:
Comparable changes in photosynthetic yield for the different populations at each treatment level
over the course of the experiment. The five sample sites: Cherry Point (CP), Elliott Bay (EB),
Fidalgo Bay (FB), Nisqually Reach (NR), and Willapa Bay (WB).
32
Fidalgo Bay had the highest photosynthetic yield in treatment level 14°C. Cherry Point and
Nisqually Reach were significantly different from every other population in treatment level and
17°C. Cherry Point was significantly different from three other populations in the 20°C treatment
level. Fidalgo Bay and Willapa Bay performed better than the other three populations for the first
two weeks in treatment level 23°C. There was no significant difference between the populations
at 23°C.
Discussion
This single factor temperature experiment considered four water temperatures spanning the
natural upper threshold range of Z. marina (Phillips, 1984; Thayer et al., 1984). The goal was to
identify the most resilient population. Previous work has shown the optimal temperature range
lies between 15° and 23°C, and that temperatures above this were lethal (Lee et al., 2007;
Phillips, 1984). In our mesocosms, we exposed five different eelgrass populations to four
treatment levels. In general, the highest temperature level (23°C) was lethal to all populations
when compared to the lowest treatment level (14°C).
The key finding of this study was that the Fidalgo Bay population was more tolerant to
thermal stress than Cherry Point, Elliott Bay, Nisqually Reach, and Willapa Bay. By the end of
the experiment, Fidalgo Bay overall had the lowest percentage loss of shoot length (14, 17,
20°C), lowest blade loss (14, 17 and 20°C), most growth (14, 17 and 20°C), and highest
photosynthetic yield (14°C). The initial morphological measurements indicate that morphology
was possibly connected to eelgrass performance as Fidalgo Bay had the longest blade length,
sheath width, and sheath length. Fidalgo Bay outperformed all populations even though it has the
33
coolest daily mean water temperature at 7.41°C (Figure 2) which is 2.94°C cooler than the
second coolest site (Cherry Point) and 5.07°C cooler than the hottest site (Willapa Bay).
Willapa Bay performed second-best overall, in the first two weeks, it had a lower percentage
loss of shoot length than Fidalgo Bay in 14, 17 and 20°C, slower percentage blade loss than
Fidalgo bay in 14°C, more growth than Fidalgo Bay in the first three weeks of 14°C, and higher
photosynthetic yield than Fidalgo Bay for the first four weeks in 14°C and 17°C. Cherry Point
performed worst in every measurement in all treatment levels.
The photosynthetic yield was more stable for longer when compared to the other
performance measurements in 14, 17, and 20°C with Fidalgo Bay and Willapa Bay
outperforming the other populations in 23°C for the first two weeks. While photosynthetic yield
was stable, other performance measurements were declining.
The study also showed that higher temperatures will significantly affect growth and
survival in treatment levels 17°C and higher for all five populations. Changes in eelgrass
performance occurred noticeably during week two in all four performance measurements. This
indicates that long-duration thermal stress has negative consequences for eelgrass productivity
and resilience.
The limitations of this project were that not all natural conditions could be simulated in
this artificial environment. The eelgrass was also placed under immense stress once removed
from the sediment and keeping the rhizomes exposed during the experiment contributed to the
mortality and slow growth. Studies focusing on sediment presence suggest that eelgrass produces
more blades and has increased growth rates when rooted in sediment (Biber, 2006). It is
therefore suggested that a future study could be done with all shoots grown in sediment. Further
studies are required to identify other similar or more resilient populations; therefore, it is also
34
suggested that the same study is done with populations that were not included in this experiment
i.e., from the Strait of Georgia, the Canadian coast, and the remaining ANeMoNe sites. Future
studies should evaluate light availability and pH or a combination of two factors like light
turbidity and temperature. Lastly, it is suggested that a lower temperature threshold be selected
as 23°C has shown to be lethal to all populations.
This study corroborates with a study done by Sylvia Yang (personal communication, 2020)
that exposed eelgrass from Cherry Point and Fidalgo Bay to three different water temperatures
(10°C,13°C, and 21°C). The higher treatment level showed a decrease in performance in
evaluating the morphological parameters (shoot length, sheath length, sheath width, total number
of leaves, and dry weight) as well as growth rate and mortality. Fidalgo Bay outperformed
Cherry Point in every response parameter.
Eelgrass communities will face considerable stresses over the next several decades. As shown
by other studies, elevated water temperature is one of the most important negative effects of
climate change. When comparing the four treatment levels, the higher temperatures had notable
higher mortality which indicates that a change to a higher climate regime will cause higher
mortality. However, certain populations appear better adapted to handle higher temperatures. By
identifying which populations are more resilient to these increase water temperatures, it can
assist resource managers to develop effective mitigation and restoration strategies. One such way
would be to use the most resilient population as a donor site for future restoration purposes. This
also prevents the disruption of less resilient population sites that are more vulnerable and
sensitive. There are ethical questions that arise from using one population to restore another as
each population is genetically different and could have irreparable effects if not conducted
35
correctly. This dilemma might also be overlooked due to the urgency of the problem and the
survival of the species. Implications of the loss of species have ramifications for the organisms
that depend on it.
36
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