CLIMATE CHANGE EFFECTS ON PHOTOSYNTHETIC SYMBIONTS IN THE SEA ANEMONE ANTHOPLEURA XANTHOGRAMMICA

A Thesis submitted to the faculty of San Francisco State University In partial fulfillment of ^ the requirements for the Degree

"^Iq L Master of Science

• F5f In Biology: Marine Biology

by

Alison Christine Fisher

San Francisco, California

August 2017 Copyright by Alison Christine Fisher 2017 CERTIFICATION OF APPROVAL

I certify that I have read Climate Change Effects on Photosynthetic Symbionts in the Sea

Anemone Anthopleura xanthogrammiea by Alison Christine Fisher, and that in my

opinion this work meets the criteria for approving a thesis submitted in partial fulfillment of the requirement for the degree Master of Science in Biology: Marine Biology at San

Francisco State University.

Edward J. Carpenter, Ph.D. Professor of Biology

Tomoko Komada, Ph.D. Professor eff Chemistry

f \ Frances P. Wilkerson, Ph.D. RTC Research Professor CLIMATE CHANGE EFFECTS ON PHOTOSYNTHEYIC SYMBIONTS IN THE SEA ANEMONE ANTHOPLEURA XANTHOGRAMMICA

Alison Christine Fisher San Francisco, California 2017

The giant green sea anemone (Anthopleura xanthogrammica) inhabits the rocky intertidal zone in California and Oregon. Two photosynthetic algal symbionts, zooxanthellae and zoochlorellae, make these anemones important primary producers in the intertidal zone. This study investigated the effects of changes in temperature and pH on anemones and their symbionts over a natural environmental gradient along the coast of California and Oregon. Zoochlorellae responded negatively to warmer temperatures and positively to more acidic conditions, while zooxanthellae responded positively to warmer temperatures and lower pH. Temperature and pH did not significantly affect chlorophyll a concentrations or anemone protein biomass. Depending on the magnitude of future changes in ocean temperatures and acidity, changes in the ranges of the two types of symbionts and increased densities of sea anemones in the rocky intertidal could be expected to occur.

I certifyjhat the Abstract is a qorrect representation of the content of this thesis.

lir, Thesis Committee )ate ' ACKNOWLEDGEMENTS

I thank the many people without whom my thesis research would not have been possible.

I thank my advisor, Ed Carpenter, and the rest of my committee, Jonathon Stillman,

Frances Wilkerson, and Tomoko Komada, for their scientific guidance. I thank Andrew

Kalmbach, Karen Backe, Theresa Fisher, and Karl Fisher for assisting me with fieldwork.

I thank Michelle Marraffmi for statistics guidance. I thank Sarah Blaser, Anne Slaughter, and Jen Miller for training me on equipment. I thank my labmates Andrew, Kate,

Morgan, Heather, and Danny, and fellow grad students at RTC, especially Margot,

Karen, and Jennifer, for their support and friendship. I also thank my parents, Anne,

David, and Layla for their support during this time. I especially thank Sam for believing in me.

This work was funded by a research award from the Graduate Student Council in Biology at SFSU and by a COAST Graduate Student Research Award.

v TABLE OF CONTENTS

List of Tables ...... vii

List of Figures ...... viii

List of Appendices...... ix

Introduction...... 1

Methods...... 9

Results...... 15

Discussion...... 19

References...... 42

Appendices...... 52 LIST OF TABLES

Table Page

1. Predictions for mixed effects modeling...... 28 2. Best mixed effect model outputs...... 29 3. Results for mixed effects modeling...... 30

vii LIST OF FIGURES

Figures Page

1. Map of sampling sites...... 31 2. Site Temperatures and pH June-July 2013...... 32 3. Site Temperatures and pH May and August 2016...... 33 4. Percent Zooxanthellae by Month and Site...... 34 5. Symbiont Type by Temperature...... 35 6. Cell Density with Temperature and pH ...... 36 7. Mitotic Index with Temperature and pH ...... 37 8. Zooxanthellae Mitotic Index by Month and Site...... 38 9. Chlorophyll a by Symbiont Type...... 39 10. Anemone Biomass with Temperature and pH ...... 40 11. Anemone Biomass by Symbiont Type...... 41 LIST OF APPENDICES

Appendix Page

1. Mixed Effects Modeling Outputs ...... :..... 5 2 2. pH and Temperature Interaction Plots...... 59

ix 1

Introduction

Climate change background

Earth’s climate is changing at an exceptional rate due to the combustion of fossil fuels and release of anthropogenic greenhouse gases, including carbon dioxide (CO2) into the atmosphere (IPCC 2014). Increased concentrations of CO2 in the atmosphere retain thermal energy, leading to higher temperatures in the atmosphere, on land, and in the ocean. Surface ocean temperatures increased 0.11°C between 1971 and 2010, and are expected to increase by an additional 4°C by the end of the century (IPCC 2014).

Approximately 30% of the anthropogenic CO2 that is released into the atmosphere dissolves in seawater (Sabine et al. 2004), which increases the partial pressure of carbon dioxide (pCO2) in the ocean. The increased levels of CO2 in seawater affect the ocean's natural carbonate buffering system because CO2 reacts with seawater to form carbonic acid (H2CO3); when the carbonic acid dissociates into bicarbonate (HCO3'), carbonate

(CO32"), and hydrogen (H+) ions, it results in a decrease of ocean pH in an effect termed ocean acidification (OA) (Caldeira and Wickett 2003). The pH of the surface ocean has decreased by 0.1 units since the Industrial Revolution, and is expected to decrease by anywhere from 0.06 units in the best-case climate scenario to up to 0.32 units in the business-as-usual climate scenario by 2100 (IPCC 2014).

Ocean warming and ocean acidification both have negative impacts on marine organisms. Warmer temperatures cause heat stress, increased metabolic costs, and can affect species interactions, such as predation and competition (Somero 2002, Sanford 2

1999, Schneider 2008). Many intertidal organisms are close to the maximum temperatures they can survive (Stillman 2002 and 2003), which makes the organisms that inhabit this environment more vulnerable to future warming. In corals, which are close relatives of sea anemones with algal symbionts, warming temperatures also cause the animals to expel their photosynthetic symbionts (Hoegh-Guldberg 1999 and Hoegh-

Guldberg et al. 2007). Living in more acidic water has been shown to have a negative effect on the survival, calcification, growth, and reproduction of a wide range of marine organisms (Kroeker et al. 2010). In sea urchin larvae, more acidic water can increase metabolic costs and cause stress from increased acid-base regulation (Stumpp et al.

2012).

Since ocean warming and acidification are occurring simultaneously, it is important to not only understand the effects of these two changes alone, but together as well (Gunderson et al. 2016). Increased temperatures exacerbate the negative effects of ocean acidification on the survival, growth, and development of marine organisms

(Kroeker et al. 2013), and a combination of warmer temperatures and lower pH can have additive or synergistic negative effects on metabolic rates (Paganini et al. 2014) and coral calcification (Rodolfo-Metalpa et al. 2011). A consequence of ocean warming and acidification may be a change in community structures, where there are fewer calcifying organisms and more non-calcifying organisms, in the community (Hale et al. 2011).

In the California Current System (CCS) along the West Coast of the United

States, surface seawater pH is also influenced by episodic upwelling, where strong 3

alongshore winds push surface waters offshore, allowing deep, nutrient-rich waters to upwell. These deep waters are more acidic than surface waters, due to large amounts of dissolved CO2 from the respiration of benthic and deep sea organisms (Hauri et al. 2009).

Since 1750, mean surface pH along the coast of California has decreased from 8.12 to

8.04 (Gruber et al. 2012), largely resulting from mixing with upwelled water. In 1990,

Bakun predicted that global warming would intensify upwelling, and this has been confirmed by Sydeman et al. (2014). In the CCS, pH levels are predicted to be below their current levels by the year 2040 due to stronger upwelling and rapid ocean acidification (Hauri et al. 2013).

Because the CCS is already experiencing levels of OA not predicted for most surface waters of the ocean until the end of the century (Feely et al. 2008), these regions are of more immediate concern than other regions of the ocean (Hauri et al. 2009). The steep environmental gradients along the West Coast also provide a natural laboratory to study the effects of OA and warming on native marine organisms (Kroeker et al. 2016).

Study organism: Anthopleura xanthogrammica

A number of anemones that occur along the West Coast of the United States harbor symbiotic algae. The two most common are Anthopleura elegantissima and

Anthopleura xanthogrammica, which often contain algae of two different taxa, unlike most cnidarians with symbionts. This study focused on the effects of OA and temperature on the giant green sea anemone Anthopleura xanthogrammica. Adult A. xanthogrammica are found in the rocky intertidal zone, where they eat mussels (Mytilus californianus), sea 4

urchins (Strongylocentrotus pur pur at us), and other intertidal zone organisms and zooplankton, such as crustaceans (Ricketts et al. 1985 and Sebens 1983). Predators of the anemones include nudibranchs (Aeolidia papillosa and Hermissenda crassicornis), sea stars (Dermasterias imbricata), sea spiders (Pycnogonum stearnsi), snails (Opalia funiculata and O. chaseii), and mosshead sculpins (Clinocottus globiceps) (Ricketts et al.

1985, Sebens 1983, Bachman and Muller-Parker 2007, Augustine and Muller-Parker

1998). The anemones typically spawn between July and October, and produce planula larvae through external fertilization (Sebens 1981a). The larvae travel far from their parents, and typically settle inside mussel beds, where they develop into juvenile sea anemones and feed on smaller invertebrates in the mussel bed before moving out of the bed as they mature (Sebens 1981b).

In addition to feeding heterotrophically, A. xanthogrammica also contains two algal symbionts: dinoflagellates commonly called zooxanthellae (Symbiodinium spp.) and green algae called zoochlorellae (Elliptochloris marina) (Muscatine 1971, Lewis and

Muller-Parker 2004, Letsch et al. 2009). These symbionts are acquired during the anemone's larval stage via horizontal transmission from the environment, rather than vertical transmission from their parents (Schwarz et al. 2002). The symbionts are usually ingested along with tissues from settled anemones and incorporated into the endoderm of the larva (Schwarz et al. 2002).

Zooxanthellae and zoochlorellae both fix CO2 through photosynthesis, but they are contained within intracellular structures called symbiosomes in the endoderm of the 5

host anemone and thus do not have direct access to dissolved inorganic carbon (DIC) in seawater (Rands et al. 1993). The anemone takes up DIC primarily in the form of HCO3' via Na+-dependent and Na+-independent HCO3' transport mechanisms (Goiran et al.

1996, Al-Moghrabi et al. 1996). The enzyme carbonic anhydrase is located between the host cells and the symbiont cells, and it converts HCO3' into CO2, which the symbionts can use for photosynthesis (Weis et al. 1989, Weis 1991, Al-Moghrabi et al. 1996, Weis and Reynolds 1999). Because of the higher CO2 concentrations around the symbionts, the symbiosome is more acidic (pH<6) than the intracellular pH of the host cells (pH=7.01-

7.41), which in turn are more acidic than the surrounding seawater (pH=8.1) (Venn et al.

2009).

After photosynthesis, carbon from the symbionts is translocated to the anemone host primarily in the form of glycerol (Trench 1971a, b), which the anemone can use for its own metabolism. In return, the algae are protected inside the anemone and are provided with nutrients, including nitrogen and phosphorus. Sources of nutrients include the anemone's heterotrophic feeding, waste products such as ammonium, and inorganic nutrients that the anemone takes up from the seawater (Cook et al. 1988 and 1992, D'Elia and Cook 1988, Muller-Parker et al. 1990 and 1996). Areal rates of primary productivity in anemones with symbiotic algae are comparable to those of seaweeds, making them major primary producers in the intertidal zone (Fitt et al. 1982).

Both symbionts give about 30% of the carbon they fix to the anemone, using the remainder for their own metabolic processes (Engebretson and Muller-Parker 1999); 6

however, this contribution is highly variable and can range from 30-100% in zooxanthellae and from -3.8-70% in zoochlorellae (Verde and McCloskey 1996, 2001,

2002, 2007; Engebretson and Muller-Parker 1999; Bergschneider and Muller-Parker

2008; Levine and Muller-Parker 2012). In terms of total mass of photosynthetic carbon, zooxanthellae cells contribute more than zoochlorellae cells because they are larger, contain more chlorophyll, and have twice the net photosynthetic rate of zoochlorellae

(Verde and McCloskey 1996). Although the anemones will continue to feed heterotrophically regardless of symbiotic state (Hiebert and Bingham 2012), changes in the relative abundances of zooxanthellae and zoochlorellae could impact anemone productivity and growth.

Latitude, intertidal height, temperature, and pCOi influence the presence and relative abundances of the two symbionts in sea anemones. In field studies, anemones with zooxanthellae are found in the high intertidal and in areas where there are higher temperatures; anemones with zoochlorellae are found farther north, in the lower intertidal, and in areas where there are lower temperatures (Bates 2000, Secord and

Augustine 2000, Levine and Muller-Parker 2012). Zoochlorellae are found farther south in A. xanthogrammica than they are in A. elegantissima (Secord and Augustine 2000). In laboratory experiments on A. elegantissima that manipulate temperature, zoochlorellae abundance typically decreases at high temperatures, whereas zooxanthellae are not affected by high temperature and can withstand temperatures up to 24°C (Saunders and

Muller-Parker 1997, Verde and McCloskey 2001, O’Brien and Wyttenbach 1980, Muller- 7

Parker et al. 2007). Zooxanthellae in A. elegantissima in higherpCOi conditions are more productive, provide more photosynthate to the host anemone, and can prevent cellular acidosis in the host anemone (Towanda and Thuesen 2012, Horwitz et al. 2015, Gibben and Davy 2014), but no similar studies have been conducted to date on zoochlorellae.

Additionally, there are comparatively few studies on symbionts in A. xanthogrammica

(Levine and Muller-Parker 2012), but their symbiotic state may be influenced by environmental factors to a greater extent than is A. elegantissima because they frequently host both zooxanthellae and zoochlorellae; this would make them a better species in which to study environmental effects on the cnidarian-algal symbiosis (Bates et al. 2010).

Although studies have been conducted on the abundance of zooxanthellae and, to a lesser extent, zoochlorellae (see above), it is unknown how the two symbionts respond to different pH and temperature combinations. Additionally, the connection between symbiont complement and anemone health remains largely unexplored; the above studies focus solely on the response of algal symbionts to environmental factors. O'Brien (1980) observed that aposymbiotic anemones were smaller in size, but did not perform any correlation analyses regarding anemone symbiont state and size. Translating data from algal symbionts to overall anemone health is a necessary step that is missing from many studies on zooxanthellae and zoochlorellae.

Research Objective and Hypotheses

The objective of this study was to understand the effects of two abiotic factors associated with climate change, seawater temperature and pH, on the giant green sea 8

anemone A. xanthogrammica and its two algal symbionts, zooxanthellae and zoochlorellae. Natural variations in pH and temperature along the Pacific West Coast were used to explore whether anemones and their algal symbionts showed differences associated with these environmental factors. Based on the results of laboratory studies conducted previously by others (see above), I expected to find that at lower pH levels and higher temperatures, anemones would be larger and more productive, as a result of increases in the relative abundance and primary productivity of zooxanthellae. Based on this assumption, I tested the following hypotheses:

At lower pHs and higher temperatures,

Hypothesis 1: The cellular density of zooxanthellae will be greater than that of

zoochlorellae.

Hypothesis 2: The growth rates of zooxanthellae will be greater than those of

zoochlorellae.

Hypothesis 3: The algal biomass of anemones (measured as chlorophyll a) will be

higher than at higher pHs and lower temperatures.

Hypothesis 4: Anemones will be larger than at higher pHs and lower

temperatures.

In addition to the direct effects of pH and temperature, chlorophyll a concentrations of the anemones and anemone size were both predicted to be greater in anemones with more zooxanthellae relative to anemones with zoochlorellae.

Furthermore, because the anemone samples were taken in different months, at four sites, 9

and in two to three pools at each site, the temporal and spatial aspects of sampling were also predicted to affect the results of the study. A summary of these hypotheses can be found in Table 1.

Methods

Sampling site selection

Anthopleura xanthogrammica tentacles were collected from four sites along the

West Coast of the United States: Fogarty Creek, OR (44°50'17.1"N 124°03’12.8"W),

Cape Arago, OR (43°18'14.0"N 124o23'50.4"W), Cape Mendocino, CA (40°25'12.6"N

124°24'04.1"W ), and Bodega Marine Laboratory, CA (38°19’05.7"N 123°04'18.5"W)

(Figure 1). No sites south of 38°N were chosen because it is the southern limit of zoochlorellae (Secord and Augustine 2000). Sites were selected based on the variability in pH and temperature observed in the long-term monitoring data collected by the Ocean

Margins Ecosystem Group for Acidification Studies (OMEGAS) (Chan et al. 2015).

Based on data for the months of June and July 2013, temperature and pH both decreased with increasing latitude (Figure 2a, 2b). Sites in Oregon, Fogarty Creek in particular, are exposed to pH levels below 7.8 more often than sites in California (Hofmann et al. 2014).

Because the OMEGAS data collection ended in 2013 and the present study was conducted in 2016, pH and temperature data were collected during sampling.

Additionally, unlike OMEGAS, the present study sampled different tide pools at each site; these pools can vary widely in pH and temperature, even within a site, because of factors such as depth, shading, and rates of photosynthesis and respiration throughout the 10

day.

Temperature and pH data collection

Temperature and pH data were taken every thirty minutes from low tide to high tide in each tide pool sampled and in ambient seawater (incoming waves) at each site using a portable Hanna 9126 pH/ORP meter. The pH probe was calibrated using pH 4, 7, and 10 standards prior to field work. The accuracy of the pH probe was 0.01 units, and the readings were precise to ±0.01 units. Readings were taken between 6-10cm depth, depending on the depth of the tide pool being sampled.

Anemone sampling

During each sampling trip, between 13-15 A. xanthogrammica anemones were sampled at each site; A. xanthogrammica anemones were distinguished from A. elegantissima anemones based on their larger size and being solitary versus clonal.

Sampling was conducted twice: May 22-26 and August 4-7, 2016. Photographs were taken of each anemone to estimate anemone size. One to two tentacles from each anemone were removed with surgical scissors and used to quantify the abundance, growth rate, and biomass of the symbionts. This sampling procedure has been used for similar experiments (Saunders and Muller-Parker 1997, Bates 2000). Tentacles from each anemone were placed in a vial, frozen, and kept on dry ice until returning to the laboratory, where they were stored at -18°C.

After returning to the laboratory, the tentacles from each anemone were thawed and homogenized in 4.0mL filtered seawater (FSW) with a borosilicate glass tissue 11

grinder (Wheaton Dounce Tissue Grinder, 7mL). The resulting homogenate was divided into four lmL subsamples: one for cell counts and mitotic index, one for chlorophyll a analysis, one for protein quantification, and an extra vial in case any of the procedures needed to be repeated for a sample (e.g. a test tube for a chlorophyll a analysis broke and leaked during chlorophyll extraction). The vials were stored in the freezer at -18°C until analyzed.

Cell counts and mitotic index

Cell counts of symbionts from homogenized tentacles were done with a Fuchs

Rosenthal Ultra Plane hemocytometer microscope slide on a Zeiss Axioskop at 200x magnification. Since zooxanthellae and zoochlorellae cells are noticeably different in size and color, identification was not an issue: zooxanthellae are yellow-brown and 10-12 jam in diameter, whereas zoochlorellae are bright green and 6-8 pm in diameter (Secord and

Augustine 2000). Cells were counted until 1000 cells had been counted or until all of the cells in the hemocytometer grid were counted, if there were less than 1000 cells. Cell counts were normalized to unit mass of total tentacle protein. Protein from the tentacles was determined using an Agilent/HP 8453 spectrophotometer at 750 nm, following the

Lowry method (Lowry et al. 1951). Bovine serum albumin (BSA) was used as a standard.

This method is often used in studies on cnidarian-algal symbioses (Muller-Parker et al.

1994, Saunders and Muller-Parker 1997).

Although cell counts and chlorophyll a measurements quantify abundance of symbionts, they do not reflect the health of the symbionts. Mitotic index (MI) is 12

commonly used to measure algal growth rates in studies on zooxanthellae and zoochlorellae (Saunders and Muller-Parker 1997, Towanda and Thuesen 2012, Wilkerson etal. 1988).

During cell counts, the number of doublet zooxanthellae and zoochlorellae cells were also counted. These doublet cells are cells that are undergoing cell division.

Because zooxanthellae and zoochlorellae do not follow diel cycles in cell division, MI was measured at a single time point, rather than over a 24-hour period (Saunders and

Muller-Parker 1997, Dimond et al. 2013). Rates of cell division were calculated as the number of counted cells that were undergoing cell division, and expressed as a percent of the total number of cells.

Chlorophyll a analysis

Chlorophyll a concentration was used to measure symbiont biomass. The algal cells were filtered with a 25mm diameter 0.7 (im GF/F filter and placed in a test tube with 5.0 mL of 90% acetone. Samples were kept in a freezer (-18°C) overnight, then thawed to room temperature the next day. The filter was removed and chlorophyll a concentration was determined by fluorometry on a Turner AU-10 fluorometer at 665 nm.

Two drops of 1.2 M HC1 were added to each sample, and the sample was reread to correct for any degraded chlorophyll a in the sample (Parsons et al. 1984, Holm-Hansen et al. 1965). Chlorophyll a was reported per unit mass of animal protein.

Anemone protein biomass

Anemone protein biomass was determined by measuring the area of the oral disk 13

when the anemone was fully open. Open anemones were photographed beside a ruler for scale before tentacle sampling. The oral disk area was calculated from the photographs using ImageJ software (Rasband, NIH 1997-2016). Oral disk area was translated into protein biomass using equations developed by Dimond (2011).

Statistical analyses

The design for this study included both fixed effects (pH, temperature, and symbiont type) and nested random effects (pool nested within site nested within month).

Although some factors, such as pH and temperature, may be correlated with each other, a multivariate approach was not used because the nested nature of the data could have led to some variables being more strongly correlated than they actually are. For this reason, mixed effects modeling was used to determine which fixed and random factors were most important for predicting responses of biological variables to environmental conditions.

Mixed effects models were run for the following biological variables: zooxanthellae density, zooxanthellae mitotic index, zoochlorellae density, zoochlorellae mitotic index, chlorophyll a concentration, anemone protein biomass, and symbiont type.

Random effects factors tested included month, site nested within month, and pool nested within site nested within month for all biological factors. Fixed effects factors tested included pH, temperature, and an interaction between pH and temperatures for all biological factors; symbiont type was also included as a fixed effect factor for chlorophyll a and anemone protein biomass. Symbiont type was only used as a fixed effect for chlorophyll a concentration and anemone protein biomass, and was not 14

included in the models for densities and mitotic indices of zooxanthellae and zoochlorellae, since each symbiont type was modeled separately. Symbiont type was determined based on Bates (2000): an anemone was considered zooxanthellate if it had

>90% zooxanthellae, and zoochlorellate if it had <10% zooxanthellae. Three anemones had mixed symbionts and were removed from further analyses.

Histograms were made for each response variable to determine whether the data had a normal distribution or a Poisson distribution (not shown here). Data that appeared to have a normal distribution was tested for normality using a Shapiro-Wilks test. If the data was normally distributed for a response variable, a linear mixed effects model was built. If the data was Poisson distributed for a response variable, a generalized linear mixed effects model was built. Models were built and selected using the protocol for additive mixed effects modeling from Zuur (2009). All models were built using R Studio

(version 0.98.1028); packages used to generate the models included lme4 (Bates et al.

2015), glmmADMB (Fournier et al. 2012), and nlme (Pinheiro et al. 2017).

To analyze interactions between pH and temperature, pH and temperature levels divided into categories of low, medium, and high. These categories were determined by calculating the quartiles of pH and temperature (not shown here). "Low" was defined as the 25% quartile or below, "medium" was defined as between the 25-75% quartiles, and

"high" was defined as the 75% quartile and above. Low pH was 7.7-7.97, medium pH was 7.98-8.16, and high pH was 8.17-8.36. Low temperature, was 9.63-12.28°C, medium temperature was 12.29-14.78°C, and high temperature was 14.79-18.68°C. 15

ANOVAs, t-tests, and linear regressions were used to further analyze the results of the models. Tukey post-hoc tests were run after the ANOVAs to determine which means differed. Figures were generated in R Studio (version 0.98.1028), using the packages lattice (Sarkar 2008) and ggplot2 (Wickham 2009).

Results

Sampling site characterization

During May sampling, water temperatures at the four intertidal sites followed a similar trend to the OMEGAS data, where the northern sites were colder and the southern sites were warmer (Figure 3a). pH, however, did not show any trend between sites

(Figure 3b). In August, the same latitudinal temperature trend was observed, but the sites were all colder than they had been in May (Figure 3c). pH again did not show a distinct trend, and was not different from May (Figure 3d). Compared to the OMEGAS data, both temperature and pH were more variable, possibly due to variations in individual tide pools.

Mixed effects modeling

Table 2 shows the best models for all of the biological variables. All models run for each variable are listed in Appendix 1, along with their AIC values (Akaike

Information Criterion, which measures the relative quality of multiple models). The results of the mixed effects models are summarized in Table 3.

The best model for symbiont type identified temperature and site nested within month as the most important factors for predicting symbiont type. Temperature, pH, and 16

an interaction between pH and temperature were important factors for predicting zooxanthellae and zoochlorellae density, as well as the mitotic indices of both symbionts.

In the best model for zooxanthellae mitotic index, site nested within month was also identified as an important factor. The only factor that had an effect on chlorophyll a concentration was symbiont type. The best model for anemone protein biomass included pH, temperature, an interaction between pH and temperature, and symbiont type.

However, inclusion in the best model did not mean that a factor had a significant correlation with the biological variable in question. The vast majority of the analyses of the interactions between pH and temperature did not show strong correlations, and they are presented in Appendix 2.

Symbiont type

There was a latitudinal trend in the relative abundance of each type of symbiont

(Figure 4). Anemones at Fogarty Creek had virtually only zoochlorellae; anemones at

Cape Arago had almost equal amounts of each symbiont in May, but had mostly zooxanthellae in August; anemones at Cape Mendocino and the Bodega Marine

Laboratory had virtually only zooxanthellae. The percent zooxanthellae in anemones at

Fogarty Creek was significantly different (ANOVA, p<0.01) from all of the other sites in both months. The percent zooxanthellae in anemones at Cape Arago was significantly different from the other sites in May (ANOVA, p<0.01), but was not different from Cape

Mendocino and the Bodega Marine Laboratory in August (ANOVA, p>0.05). The increase in percent zooxanthellae in anemones at Cape Arago between May and August 17

was significant (ANOVA, p=0.02). The percent zooxanthellae in anemones at Cape

Mendocino and the Bodega Marine Laboratory were not different from each other in either month (ANOVA, p>0.05).

Temperature was also a strong predictor of symbiont type: zooxanthellae were found in anemones at higher temperatures, while zoochlorellae were found in anemones at lower temperatures (Figure 5, t-test, p<0.01).

Symbiont density

The density of both symbionts tended to be lower at higher temperatures, although this trend was not significant (Figure 6a, linear regression, for ZX R2=0.04 and p=0.10, for ZC R2=0.04 and p=0.23). Zooxanthellae density was lower in more acidic conditions, although this was too not a significant trend (linear regression, R2=0.01, p=0.29). Conversely, zoochlorellae density was higher in more acidic conditions (Figure

6b, linear regression, R2=0.24, p<0.01). Only one of the results of the analyses of interactions between pH and temperature for symbiont cell density was significant, and the results of these analyses can be found in Appendix 2, Figures Al and A2.

Symbiont mitotic index

The mitotic indices of zooxanthellae tended to be low, typically between 3-5%, while zoochlorellae mitotic indices were as high as 34%. At higher temperatures, the mitotic index of zooxanthellae was slightly higher, while the mitotic index of zoochlorellae was lower (Figure 7a, linear regression, for ZX R2-0.14 and p<0.01, for

ZC R2=0.0.36 and p<0.01). The mitotic index of both symbionts increased in more acidic 18

conditions, although this was more pronounced in zoochlorellae than in zooxanthellae

(Figure 7b, linear regression, for ZX R2=0.08 and p=0.01, for ZC R2=0.39 and p<0.01).

Although some of the correlations were significant, the results of the analyses of interactions between pH and temperature for symbiont mitotic index were not convincing, and the results of these analyses can be found in Appendix 2, Figures A3 and

A4.

In addition to temperature and pH, site nested within month was a determining factor for zooxanthellae mitotic index. Zooxanthellae were rare in anemones at Fogarty

Creek, so there was no data for zooxanthellae mitotic index at that site. In May, zooxanthellae in anemones at Cape Arago, Cape Mendocino, and the Bodega Marine

Laboratory had similar mitotic indices (Figure 8). In August, when it was colder, the mitotic indices of zooxanthellae in anemones at those three sites were significantly different from each other (ANOVA, p<0.05). Between May and August, the zooxanthellae mitotic indices at Cape Arago and Cape Mendocino both decreased, although the decreases were not significant (ANOVA, p>0.05 for both); the zooxanthellae mitotic indices at the Bodega Marine Laboratory, however, did increase significantly (ANOVA, p=0.03).

Chlorophyll a concentrations

No correlations were observed between pH or temperature and chlorophyll a concentrations. The only factor that had an effect on chlorophyll a concentrations was symbiont type (Table 2): anemones with zooxanthellae had higher chlorophyll a 19

concentrations than those with zoochlorellae (Figure 9, t-test, p<0.01). This agrees with the work of Verde and McCloskey (1996), although the present study saw average chlorophyll a readings in anemones with mostly zooxanthellae approximately five times that of average chlorophyll in those dominated by zoochlorellae, compared to a difference of 1.6 times in the Verde and McCloskey study that worked with symbionts in

A. elegantissima.

Anemone protein biomass

Anemone protein biomass increased with increasing temperature (Figure 10a) and with decreasing pH (Figure 10b), although these were not significant trends (linear regression, for temperature R2=0.01 and p=0.20, for pH R2=0.01 and p=0.45). Two very large anemones were sampled at medium temperature and pH levels, although it is unclear whether finding larger anemones in those conditions was due to anemones possibly performing better in intermediate conditions or simply by chance. No significant trends were seen in the interactions between temperature and pH, and these results can be found in Appendix 2, Figure A5.

Anemones with zooxanthellae were slightly larger than those with zoochlorellae, although this was not a significant difference (Figure 11, t-test, p=0.08).

Discussion

The objective of this study was to understand the effects of seawater temperature and pH on the giant green sea anemone A. xanthogrammica and its two algal symbionts, zooxanthellae and zoochlorellae. I expected to find that at lower pH levels and higher 20

temperatures, zooxanthellae would be the dominant symbiont and would have higher densities and mitotic indices than zoochlorellae, and that anemones would be larger and more productive, as a result of increases in the relative abundance of zooxanthellae.

The results showed that the two algal symbionts harbored by the anemones have different characteristics in warmer and lower pH conditions, and this may affect their responses to future environmental changes. In general, more acidic conditions were favorable to both zooxanthellae and zoochlorellae (increased density and growth rate) whereas warmer temperatures were favorable to zooxanthellae but not zoochlorellae.

Regarding the anemone host relationship to more acidic or warm temperatures, total algal biomass of the anemones showed no difference, and was only affected by symbiont type, as in previous studies (e.g. Verde and McCloskey 1996), with anemones containing mostly zooxanthellae having more chlorophyll a. Although the best model for anemone protein biomass included no significant trends, it had a lower AIC value than the model that was completely random, which suggests that there may be factors that were not measured, and thus not included in the models, that play a role in determining anemone size. Factors that were not measured that may affect anemone size include age and amount of heterotrophic feeding.

Zoochlorellae had lower mitotic indices in warm conditions, so they may not withstand large amounts of ocean warming; in fact, temperatures where zoochlorellae were found never exceeded 16°C; the thermal limit for zoochlorellae is somewhere between 13-20°C (Saunders and Muller-Parker 1997, O'Brien and Wyttenbach 1980), but 21

no experiments have investigated zoochlorellae performance between those two temperatures. The data from this study indicate that the thermal limit for zoochlorellae falls somewhere between 16-20°C. However, zoochlorellae seem resilient to ocean acidification: in more acidic conditions, zoochlorellae had higher cell densities and higher mitotic indices, so they may succeed if ocean acidification or increased upwelling intensity are the major changes in the CCS.

Zooxanthellae had higher mitotic indices in both warmer and more acidic conditions, so they may be able to cope with both warming and acidification in temperate regions. Being able to withstand both of these stressors would give zooxanthellae a competitive advantage over zoochlorellae, which only benefits from acidification. At most sites, temperatures were well below the upper thermal limit of temperate zooxanthellae (24°C), but temperatures in one tide pool at the Bodega Marine Laboratory rose higher than 24°C, so the symbionts in the anemones in this tide pool may be at their thermal threshold already, which would make them more vulnerable to future warming

(Muller-Parker et al. 2007). Although the best model for zooxanthellae density included no significant trends, it had a lower AIC value than the model that was completely random. This suggests that there may be factors that were not measured that affect zooxanthellae density, such as solar irradiance; zooxanthellae have been shown to have higher densities in low light than in high light (Saunders and Muller-Parker 1997).

Values for algal symbiont densities and mitotic indices in this study were either comparable to or higher than those in previous studies. Zooxanthellae cell densities in 22

this study ranged from 534-2598 cells/|ng protein; previous studies have typically recorded zooxanthellae densities in the range of 200-500 cells/p.g protein (e.g. Towanda and Theusen 2012, Bergschneider and Muller-Parker 2008, and Levine and Muller-

Parker 2012), but studies by Verde and McCloskey (2001) and Saunders and Muller-

Parker (1997) recorded zooxanthellae densities of up to 800 cells/|ig protein and 1000 cells/|a.g protein, respectively, and these are values that are within the range of the present study. In the present study, zoochlorellae densities as high as 2609 cells/jag protein were observed, with an average of 982 cells/|j.g protein; these results are comparable to those of Berschneider and Muller-Parker (2008) and Verde and McCloskey (2001), who had zoochlorellae densities of up to 1800 and 1400 cells/jag protein, respectively.

Zooxanthellae mitotic indices are often below 1% (e.g. Towanda and Theusen 2012,

Verde and McCloskey 1996, Levine and Muller-Parker 2012). The present study recorded zooxanthellae mitotic indices up to 5.5%, but this is not unheard of: zooxanthellae mitotic indices of 2-5% have been previously recorded (Bergschneider and

Muller-Parker 2008, Bachman and Muller-Parker 2007). Zoochlorellae mitotic indices are usually much higher than those of zoochlorellae, and can be above 20% (e.g.

Bachman and Muller-Parker 2007, Bergschneider and Muller-Parker 2008, Levine and

Muller-Parker 2012); however, zoochlorellae in the present study had slightly higher mitotic indices of up to 34% with an average of 16%. It is unclear why symbiont densities and mitotic indices were sometimes higher in the present study than in previous literature, since the present study used methods based on the same previous studies 23

mentioned above.

If increased upwelling is the predominant change with climate change predicted for the CCS (Bakun 1990, Sydeman et al. 2014, Hauri et al. 2013), zoochlorellate anemones should remain the dominant symbiont in the north, because waters there will continue to be cold and acidic. However, if ocean warming progresses more rapidly and temperatures in the north begin to regularly exceed the thermal limits of zoochlorellae

(16-20°C), zooxanthellae may be able to outcompete zoochlorellae and be preferred by anemones in the northern sites. This change in symbionts in the northern sites may have further ecological consequences: the mosshead sculpin (Clinocottus globiceps), which is found from southern California to Alaska, preferentially feeds on zooxanthellate anemones over zoochlorellate anemones (Augustine and Muller-Parker 1998), so although the zooxanthellae anemones would be receiving more photosynthate from their symbionts, they would also be more vulnerable to predation.

Northward shifts in species ranges have already been observed in many marine species (Helmuth et al. 2006, Mieszkowska et al. 2006), and a northward shift may already be occurring in anemones containing mostly zoochlorellae. Secord and Augustine

(2000) identified Dillon Beach (38°15'04.8"N 122°58'02.4"W) as the southern limit of zoochlorellae in A. xanthogrammica\ Dillon Beach is approximately 12 km southeast of the Bodega Marine Laboratory (38°19'05.7"N 123°04'18.5"W), so zoochlorellae were expected to be found at the Bodega Marine Laboratory in this study. All anemones sampled at the Bodega Marine Laboratory contained 100% zooxanthellae, which 24

indicates that either there are some environmental differences between Dillon Beach and the Bodega Marine Laboratory that allows anemones to host zoochlorellae in the former but not the latter, or that warming ocean temperatures have already caused a change in the ranges of the two symbionts since 1994 (Secord and Augustine's fieldwork).

Although it is possible that anemones in the Bodega Bay area have already switched symbionts from zoochlorellae to zooxanthellae, it is unclear how readily anemones exchange established symbionts for novel ones and under what conditions they do so. Bates (2000) observed anemones with zoochlorellae from cooler lower tidal heights that had been transplanted into warmer upper intertidal pools shifting to zooxanthellae after 60 days, although the mechanisms for the change in symbionts was not clear. Thus, more investigation is necessary to predict the rate at which zooxanthellae could begin to dominate the northern range of A. xanthogrammica.

Buddemeier and Fautin (1993) suggest that corals and sea anemones have low- level bleaching to eliminate less desirable symbionts and acquire new symbionts that are better-suited to the environmental conditions. If so, this could mean that anemones farther north could change their symbionts from zoochlorellae to zooxanthellae relatively quickly depending on environmental conditions. This further suggests that observed differences in algal symbiont densities and mitotic indices may be regulated by the anemone, so any correlations between environmental conditions, such as pH and temperature, and the symbionts may be an indirect relationship mediated by the host anemone. For example, zoochlorellae are found farther south in the larger A. 25

xanthogrammica than the smaller A. elegantissima (Secord and Augustine 2000), and when both species of Anthopleura are found in the same location in northern latitudes, A. xanthogrammica would harbor zoochlorellae while A. elegantissima would be dominantly zooxanthellae (Bates et al. 2010). This occurs because A elegantissima warm up quickly due to their small body size, while the larger size of A. xanthogrammica allow them to stay comparatively cool (Secord and Augustine 2000). Thus, algal symbiont type within an anemone is more likely controlled by the anemone's internal temperature, which is an interaction between the anemone's size and external temperatures, than by external temperatures alone.

Comparative studies on zooxanthellae and zoochlorellae (e.g. Verde and

McCloskey 1996, 2001, 2002, 2007; Saunders and Muller-Parker 1997; Engebretson and

Muller-Parker 1999; Bergschneider and Muller-Parker 2008) have not reported any symbiont switching, but McCloskey et al. (1996) did observe increased rates of algal expulsion with increasing irradiance and O'Brien and Wyttenbach (1980) observed increased zoochlorellae expulsion at high temperatures. Symbiont switching may not have been observed in the above studies because the zooxanthellate and zoochlorellate anemones were either separated, or it was unclear whether they had been, and the experiments were all 25 days or shorter. Thus, if it takes the anemones 60 days to switch symbionts as suggested by Bates (2000), no change in the symbionts would have occurred within the time span of these studies. Laboratory experiments lasting longer than 60 days with both zooxanthellate and zoochlorellate anemones together at different 26

pH and temperature combinations would elucidate how quickly symbiont shifts occur and in what environmental conditions they occur.

Some tropical species of sea anemones are more abundant and have higher zooxanthellae densities in natural low pH environments (Suggett et al. 2012), so these organisms may be able to dominate the intertidal zone in future conditions of ocean acidification. However, the ecological consequences of climate change on sea anemones and the intertidal zone are complicated: although sea anemones may have a competitive advantage for space with more acidic conditions that may allow them to outcompete calcareous species, other ecological forces, such as predator and prey relationships, should be studied as well.

In conclusion, this study showed that zoochlorellae dominate the symbiont populations in anemones in colder temperatures while zooxanthellae can withstand higher temperatures and make up most of the population in warmer regions, and both symbionts occur in more acidic water. Ocean acidification and increased upwelling should promote both types of symbionts, but ocean warming may cause the domination of zooxanthellae in anemones to shift northward into areas that were previously occupied by anemones that hosted zoochlorellae. More research is needed to determine what conditions are necessary for symbiont switching and expulsion and how quickly this will occur under future climate scenarios. Additionally, sea anemones are predicted to be more abundant due to climate change and ocean acidification, but the myriad species interactions that would facilitate this need to be investigated. It is important to more fully understand the effects of ocean warming and acidification on ecosystems and the organisms that live them so that we will be able to anticipate and mediate the negative effects of these environmental changes. Tables

Table 1: Predictions for mixed effects modeling.

Biological Warmer Pool: Site: Lower pH Symbiont type Month Site: Month Variable Temperatures Month

Larger with Unknown Unknown Anemone Size Larger Larger No effect zooxanthellae effect effect

Higher Higher Higher concentrations Unknown Unknown Chlorophyll a No effect Concentrations concentrations with effect effect zooxanthellae

Zooxanthellae Unknown Unknown Higher Higher No effect density effect effect ZoodtloieHae Unknown Unknown Lower Lower No effect density effect effect

Zooxanthellae Unknown Unknown Higher Higher No effect mitotic index effect effect

Zoochlorellae Unknown Unknown Lower Lower No effect mitotic index effect effect

More Symbiont More More Unknown No effect zoochlorellae Type zooxanthellae zooxanthellae effect in north

to 00 29

Table 2: Best mixed effects model inputs and AIC values for all biological variables

Model Best Model Input AIC Value

Symbiont type ~ 1 + temperature + (1 | month: site) 57.95519 Type

Zooxanthellae densityzx ~ 1 + pH * temperature 1147.164 Density

Zoochlorellae densityzc ~ 1 + pH * temperature 537.9833 Density

Zooxanthellae zxmi ~ 1 + pH * temperature + (1 | month:site) 225.5230 Mitotic Index

Zoochlorellae zcmi ~ 1 + pH * temperature 219.1677 Mitotic Index

Chlorophyll a chla ~ 1 + type -925.256 Concentrations Anemone Protein anemonebiomass ~ 1 + pH * temperature + type 1987.626 Biomass Table 3: Results for mixed effects modeling. indicates results that were different than predicted,"+" indicates non-significant trends (p>0.05)

Biological Wanner Pool: Site: Lower pH Symbiont type Month Site: Month Variable Temperatures Month

Larger with Anemone Size Larger! Larger! No effect No effect1* No effect* zooxanthellae!

Higher concentrations Chlorophyll a No effect* No effect" No effect No effect* No effect" with zooxanthellae Zooxanthellae Lower*! No effect No effect" No effect" density Lower*! Zoochlorellae Higher* Lower! No effect No effect" No effect* density In August, Zooxanthellae decreased at Higher No effect CM and No effect" mitotic index Higher increased at BML*

Zoochlorellae mitotic index Lower Higher* No effect No effect" No effect*

More Symbiont More No effect* No effect zoochlorellae No effect* Type zooxanthellae in north 31

Figures

Figure 1: Map of sampling sites, generated in R (packages used: maps (Becker et al. 2016), mapdata (Becker et al. 2016), and maptools (Lewin- Koh et al. 2011)). a Site Temperatures June-July 2013 b Site pH June^luty 2013

i - ~ ~ ------j------1------r" 10 IS 20 25 7.0 ? J &0 as

Temperature fC ) pH

Figure 2: a) Temperatures at each site in June and July 2013, b) pH at each site in June and July 2013. BML=Bodega Marine Laboratory, CM=Cape Mendocino, CA=Cape Arago, and FC-Fogarty Creek. Data from Chan et al (2015). 33

a Site Temperatures May 2016 b Site pH May 2016

C Site Temperatures August 2016 d Site pH August 2016

Temperature S*CS pH

Figure 3: a)Temperatures at each site in May 2016, b) pH at each site in May 2016, c) Temperatures at each site in August 2016, d) pH at each site in August 2016. BML=Bodega Marine Laboratory, CM=Cape Mendocino, CA=Cape Arago, and FC=Fogarty Creek. 34

Percent Zooxanthellae by Month and Site

120 | May H ] August 100

s o m m 1i £ IO SO KlO c 0CD 1 *

20

3 FC CA CM BML Site

Figure 4: Percent zooxanthellae at each site in May (dark gray) and August (light gray) 2016. BML=Bodega Marine Laboratory, CM=Cape Mendocino, CA=Cape Arago, and FC=Fogarty Creek. Fogarty Creek was significantly different from all other sites in both months (p<0.01). In May, Cape Arago was different from both Cape Mendocino (p<0.01) and the Bodega Marine Laboratory (p<0.01). Percent zooxanthellae at Cape Arago was lower in May than it was in August (p=0.02). Error bars represent ±1SD. found. Zooxanthellae were found in warmer conditions than zoochlorellae (p<0.01) zoochlorellae than conditions warmer in found were Zooxanthellae found. Figure 5: Figure T emperature (°C) CD CM QO Temperature ranges where zooxanthellae (ZX) and zoochlorellae (ZC) were were (ZC) zoochlorellae and (ZX) zooxanthellae where ranges Temperature Symbiont Type by Temperature by Type Symbiont zx Symbiont Type ZC 35 a Cell Density and Temperature b Cell Density and pH

* ZC Low Temp & ZC Low pH 9 ZC Med Temp o ZC Med pH * ZX Low Temp » ZC High pH * ZX Med Temp * ZX Low pH * ZX High Temp ♦ ZXMedpH a ■ ZX High pH

Temperatuie fC) pH

Figure 6: a) Density of zooxanthellae (ZX, closed shapes) and zoochlorellae (ZC, open shapes) with temperature. For zooxanthellae density, y=-52.81x+2120.82, p=0.10, and R2=0.04. For zoochlorellae density, y=-95.77x+2102.85, p=0.2301, and R2=0.04089, b) Density of zooxanthellae (ZX, closed shapes) and zoochlorellae (ZC, open shapes) with pH. For zooxanthellae density, y=327.6x-1272.8, p=0.29, and R2=:0.01. For zoochlorellae density, y =-3744x+31190, p<0.01, and R2=0.24. a Mitotic Index and Temperature b Mitotic fndex and pH

Temperature f €> pH

Figure 7: a) Mitotic indices of zooxanthellae (ZX, closed shapes) and zoochlorellae (ZC, open shapes) with temperature. For zooxanthellae mitotic index, y = 0.25x - 0.99, p<0.01, and R2=0.14. For zoochlorellae mitotic index, y = -3.66x + 59.13, p<0.01, and R2=0.36, b) Mitotic indices of zooxanthellae (ZX, closed shapes) and zoochlorellae (ZC, open shapes) with pH. For zooxanthellae mitotic index, y = -1.88x + 17.83, p=0.01 and R2=0.08. For zoochlorellae mitotic index, y = -61.13x + 509.48, p<0.01, and R2=0.39. 38

Zooxanthellae Mitotic Index by Month and Site

| May I | August

Figure 8: Mitotic index of zooxanthellae at each site in May (dark gray) and August (light gray) 2016. BML=Bodega Marine Laboratory, CM=Cape Mendocino, CA=Cape Arago, and FC=Fogarty Creek. In May, zooxanthellae at Cape Arago, Cape Mendocino, and the Bodega Marine Laboratory had similar mitotic indices (p>0.05). In August, those three sites were all significantly different from each other (p<0.05). At the Bodega Marine Laboratory, mitotic indices were higher in August than in May (p=0.03). Error bars represent ±1SD. 39

Chlorophyll a by Symbiont Type

g o Q_s_ O) o> Ql OS =L

Q.O

O

ZX ZC Symbiont Type

Figure 9: Chlorophyll a concentrations of anemones with zooxanthellae (ZX) and zoochlorellae (ZC). Anemones with zooxanthellae had significantly higher chlorophyll a concentrations than those with zoochlorellae (p<0.01). protein biomass with pH. y = -774.3x + 7641.5, p=0.45, R2=0.005. p=0.45, 7641.5, + -774.3x = y pH. with biomass protein Figure 10: a) 10: Figure Pmmm% Protein 8*c {mg} m Q o o m o O O o t-t o p 8 T id AnemoneProtein Biomass andTemperature Anemone protein biomass with temperature, y = 102.99x + 13.47, p=0.20, R2=0.01 p=0.20, 13.47, + 102.99x = y temperature, with biomass protein Anemone 12 % 1 Temperature C|f Ss 14 ------§b 0 m a.... . 8* no o II 0 tow pHA Mdp Med ^ Temp Medo pH Hg Ho HtQh o Temp High□ pH 18 A a ?J *T* Anemone ProteinBiomass andpH 7*9 T I SO *T pH 0 8: I

it T* P ~fttr b) M T Anemone Anemone &Lm Temp 8.3 41

Anemone Protein Siomass by Symbiont Type o o o €\J

05

m O m O E© 00 bo o c o o -j—<

O — zx zc Symbiont Type

Figure 11: Protein biomass of anemones with zooxanthellae (ZX) and zoochlorellae (ZC). Anemones with zooxanthellae did not have significantly higher protein biomass than those with zoochlorellae (p=0.08). 42

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Appendix 1: Mixed Effects Modeling Outputs

Table Al: Symbiont type models and results. "*" indicates the best model.

Model Model Input AIC Value 1 type ~ 1 + pH * temperature 132.94215 2 type ~ 1 + pH * temperature + (1 | month) 63.39332 3 type ~ 1 + pH * temperature + (1 | month:site) 61.23777 4 type ~ 1 + pH * temperature + (1 | month:site:pool) 70.21151 5 type ~ 1 + pH + (1 | month:site) 63.00274 6 type ~ 1 + temperature + (1 | month:site) 57.95519* 7 type ~ 1 + pH + temperature + (1 | month:site) 59.83098 8 type ~ 1 + (1 | month:site) 61.04461 53

Table A2: Zooxanthellae density models and results. indicates the best model.

Model Model Input AIC Value 1 densityzx ~ 1 + pH * temperature 1147.164* 2 densityzx ~ 1 + pH * temperature + (1 | month) 1149.164 3 densityzx ~ 1 + pH * temperature + (1 | month: site) 1148.733 4 densityzx ~ 1 + pH * temperature + (1 | month:site:pool) 1149.052 5 densityzx ~ 1 + pH 1170.486 6 densityzx ~ 1 + temperature 1173.419 7 densityzx ~ 1 + pH + temperature 1161.506 8 densityzx ~ 1 1182.915 54

Table A3: Zoochlorellae density models and results. indicates the best model.

Model Model Input AIC Value 1 densityzc ~ 1 + pH * temperature 537.9833* 2 densityzc ~ 1 + pH * temperature + (1 | month) 13237.1919 3 densityzc ~ 1 + pH * temperature + (1 | month: site) 10903.6788 4 densityzc ~ 1 + pH * temperature + (1 | month: site :pool) 9047.0760 5 densityzc ~ 1 + pH 564.5894 6 densityzc ~ 1 + temperature 572.6170 7 densityzc ~ 1 + pH + temperature 555.2146 8 densityzc ~ 1 583.5059 55

Table A4: Zooxanthellae mitotic index models and results. indicates the best model.

Model Model Input AIC Value 1 zxmi ~ 1 + pH * temperature 242.1723 2 zxmi ~ 1 + pH * temperature + (1 | month) 237.0066 3 zxmi ~ 1 + pH * temperature + (1 | month: site) 225.5230* 4 zxmi ~ 1 + pH * temperature + (1 | month:site:pool) 227.2348 5 zxmi ~ 1 + pH + (1 | month: site) 231.3959 6 zxmi ~ 1 + temperature + (1 | month:site) 228.8846 7 zxmi ~ 1 + pH + temperature + (1 | month:site) 228.6378 8 zxmi ~ 1 + (1 | month: site) 232.1182 56

Table A5: Zoochlorellae mitotic index models and results. indicates the best model.

Model Model Input AIC Value 1 zcmi ~ 1 + pH * temperature 219.1677* 2 zcmi ~ 1 + pH * temperature + (1 | month) 221.1677 3 zcmi ~ 1 + pH * temperature + (1 | month: site) 221.1677 4 zcmi ~ 1 + pH * temperature + (1 | month:site:pool) 220.8980 5 zcmi ~ 1 + pH 247.1726 6 zcmi ~ 1 + temperature 253.9699 7 zcmi ~ 1 + pH + temperature 236.3089 8 zcmi ~ 1 269.7063 57

Table A6: Chlorophyll a models and results. indicates the best model.

Model Model Input AIC Value 1 chla ~ 1 + pH * temperature + type -919.328 2 chla ~ 1 + pH * temperature + type + (1 | month) -917.090 3 chla ~ 1 + pH * temperature + type + (1 | month: site) -917.094 4 chla ~ 1 + pH * temperature + type + (1 | month:site:pool) -917.092 5 chla ~ 1 + pH * temperature -914.790 6 chla ~ 1 + pH -914.714 7 chla ~ 1 + pH + type -923.298 8 chla ~ 1 + temperature -918.622 9 chla ~ 1 + temperature + type -923.282 10 chla ~ 1 + pH + temperature -916.760 11 chla ~ 1 + pH + temperature + type -921.328 12 chla ~ 1 + type -925.256* 13 chla ~ 1 -916.668 58

Table A7: Anemone protein biomass models and results. indicates the best model.

Model Model Input AIC Value 1 anemonebiomass ~ 1 + pH * temperature + type 1987.626* 2 anemonebiomass ~ 1 + pH * temperature + type + (1 | month) 134454.872 anemonebiomass ~ 1 + pH * temperature + type + (1 | 3 121070.824 month: site) anemonebiomass ~ 1 + pH * temperature + type + (1 | 4 101122.253 month:site:pool) 5 anemonebiomass ~ 1 + pH * temperature 2000.379 6 anemonebiomass ~ 1 + pH 2023.208 7 anemonebiomass ~ 1 + pH + type 2009.541 8 anemonebiomass ~ 1 + temperature 2022.112 9 anemonebiomass ~ 1 + temperature + type 2009.417 10 anemonebiomass ~ 1 + pH + temperature 2011.644 11 anemonebiomass ~ 1 + pH + temperature + type 1998.871 12 anemonebiomass ~ 1 + type 2020.151 13 anemonebiomass ~ 1 2033.811 pedx 2: Appendix

Zooxanthellae Density and Temperature by pH k Zooxanthellae Density and pH by Temperature

Temperature PC} pH

Figure Al: a) Zooxanthellae density plotted against temperature. Symbols indicate different pH categories: low (closed circles), medium (open triangles), and high (x). For low pH, y=207.8x-1765, p=0.32, and R2=0.06. For medium pH, y=-61.76x+2314.17, p=0.08 and R2=0.08. For high pH, y=-57.34x+2242.07, p=0.51, and R2=0.02, b) Zooxanthellae density plotted against pH. Symbols indicate different temperature categories: low (closed circles), medium (open triangles), and high (x). For low temperature, y=129.2x+600.7, p=0.98, and R2=6.07xl0~5. For medium temperature, y=488.6x-2604.7, p=0.20, and R2=0.05. For high temperature, y=- 311.9x+3844.5, p=0.61, and R2=0.01.

VO a Zoochlorellae Density and Temperature by pH b Zoochlorellae Density and pH by Temperature # 13 tl m m m& mC O H o# if 5 0 1 N

Ttmpenfyrt f C| pH

Figure A2: a) Zoochlorellae density plotted against temperature. Symbols indicate different pH categories: low (closed circles), medium (open triangles), and high (x). For low pH, y=75.2x+650.82, p=0.47, and R2=0.08. For medium pH, y=- 221x+3291.7, p=0.08, and R2=0.15. There was not sufficient data to plot a regression line for high pH, b) Zoochlorellae density plotted against pH. Symbols indicate different temperature categories: low (closed circles) and medium (open triangles). No zoochlorellate anemones were found at high temperatures. For low temperatures, y=l 88lx-13831, p=0.38, and R2=0.06. For medium temperatures, y=-5226x+43085, p<0.01, and R2=0.47. a Zooxanthellae Mitotic Index and Temperature by pH b zooxanthellae Mitotic Index and pH by Temperature

Temperature (*C) pH

Figure A3: a) Zooxanthellae mitotic index plotted against temperature. Symbols indicate different pH categories: low (closed circles), medium (open triangles), and high (x). For low pH, y=-0.22x+6.06, p=0.06, and R2=0.01. For medium pH, y=0.23x-0.53, p<0.01, and R2=0.18. For high pH, y=0.43x-4.14, p<0.01, and R2=0.36, b) Zooxanthellae mitotic index plotted against pH. Symbols indicate different temperature categories: low (closed circles), medium (open triangles), and high (x). For low temperatures, y=-26.06x+214.32, p<0.01, and R2=0.54. For medium temperatures, y=-2.2631x+20.45, p=0.01, and R2=0.16. For high temperatures, y=-2.57x+23.95, p=0.06, and R2=0.13. a Zoochlorellae Mitotic Index and Temperature by pH b zoochlorellae Mitotic Index and pH by Temperature

Temperature fC> pH

Figure A4: a) Zoochlorellae mitotic index plotted against temperature. Symbols indicate different pH categories: low (closed circles), medium (open triangles), and high (x). For low pH, y=-0.78x+30.63, p=0.26, and R2=0.15. For medium pH, y=-5.88x+83.67, p<0.01, R2=0.59. There was not sufficient data to plot a regression line for high pH, b) Zoochlorellae mitotic index plotted against pH. Symbols indicate different temperature categories; low (closed circles) and medium (open triangles). No zoochlorellate anemones were found in high temperatures. For low temperatures, y=-1.94x+39.23, p=0.93, and R2=0.0006. For medium temperatures, y=-56.86x+471.07, p<0.01, and R2=0.63. a Anemone Protein Biomass and Temperature by pH ^ Anemone Protein Biomass and pH by Temperature

Temperature PC) pH

Figure A5: a) Anemone protein biomass plotted against temperature. Symbols indicate different pH categories: low (closed circles), medium (open triangles), and high (x). For low pH, y=96.47x+13.99, p=0.42, and R2=0.02. For medium pH, y=135.5x-156.6, p=0.25, and R2=0.02. For high pH, y=-1.40x+920.26, p=0.99, and R2=8.24xl0‘6, b) Anemone protein biomass plotted against pH. Symbols indicate different temperature categories: low (closed circles), medium (open triangles), and high (x). For low temperatures, y=1804x-13426, p=0.74, and R2=0.004. For medium temperatures, y=-343.2x+4109.9, p=0.71, and R2=0.003. For high temperatures, y=-3097x+26858, p=0.23, and R2=0.05.