The Effects of Increased Oceanic Co2 on Tide Pool Communities

THE EFFECTS OF INCREASED OCEANIC CO2 ON TIDE POOL COMMUNITIES

by Brendan C. Gillis

B.A. in Biology with a Specialization in Marine Science from Boston University

A thesis submitted to

The Faculty of the College of Science of Northeastern University in partial fulfillment of the requirements for the degree of Master of Science

April 16, 2014

Thesis directed by

Matthew E.S. Bracken Associate Professor of Biology

ACKNOWLEDGEMENTS

First and foremost, I would like to thank my advisor, Dr. Matthew Bracken. Without his support and guidance I would have not been able to accomplish what I am presenting here.

I also owe a huge debt of gratitude to my committee, Dr. Donald Cheney and Dr. Jonathan Grabowski, who both provided valuable feedback on my research.

Additionally, I thank the other members of the Bracken lab, who have provided priceless insight into various problems that I invariably encountered.

Lastly, I thank my friends and family, both those gone and those still here today, for all of the support over the years. You’ve certainly put up with a lot.

ABSTRACT OF THESIS

Due to anthropogenic emissions of CO2, the world’s oceans are becoming more acidic. Ocean pH levels have decreased by 0.1 units since 1850 and are expected to decrease by another 0.3-0.4 units over the next 100 years. Predicting the impacts of ocean acidification on marine communities requires understanding the consequences for individual species and their interactions with other species. This change in pH is likely to have major effects on calcification, metabolic stability and larval development for a wide variety of organisms. Not all organisms are expected to be adversely affected, however, and it is predicted that some algal species may thrive in an acidified ocean environment.

Due to respiration (especially at night) and photosynthesis during low tide, the pH of seawater in tide pools can vary dramatically throughout the day. This daily change is orders of magnitude more extreme than what is expected for the ocean at large over the next century. In order to examine how these communities may respond to this aspect of climate change, I exposed both natural tide pools and tide pool mesocosms to high CO2 conditions. To do this, I utilized yeast reactors to maintain low pH conditions within the range of natural pH variation seen in tide pools. Natural tide pools were used for field portions of the experiment, while split mesocosms were used in running seawater tables to examine species interactions. In response, the green alga Ulva increased in growth and cover under high CO2 conditions. High CO2 treatments also resulted in increased grazing by the herbivorous snail, Littorina littorea. Tissue analyses suggest that shifts in stoichiometry may be the reason for this behavioral shift. I also observed transient, but significant, decreases in metrics such as diversity, richness and evenness in natural tide pools following CO2 enrichment. As one of the first in natura studies of this issue, my

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work highlights the utility and importance of considering ocean acidification effects in a community context.

TABLE OF CONTENTS

Acknowledgments ii

Abstract iii

Table of Contents v

List of Figures vi

List of Tables vii

Chapter 1: Introduction 1

Chapter 2: CO2 enrichment modifies growth, tissue composition

and consumption of an intertidal seaweed 8

Chapter 3: CO2 enrichment reduces diversity in tide pool communities 21

Appendix A: Supplemental Tables 32

Literature Cited 34

LIST OF FIGURES

Figure 1. Observed pH in field and mesocosm experiments 11

Figure 2. Enhancement of seaweed cover in tide pools associated with addition of CO2. 14

Figure 3. Growth (A) of Ulva and change in consumption (B) of Ulva by Littorina littorea in high CO2 and ambient treatments 15

Figure 4. Consumption of Ulva by Littorina littorea over the course of 3 day feeding assay under ambient conditions after Ulva was exposed to ambient or elevated CO2 levels for 4 weeks 16

Figure 5. Change in Ulva tissue carbon over the course of 4 week exposures to ambient and elevated CO2 on three separate instances 18

Figure 6. Algal diversity (H’) in high and ambient CO2 treatments over the course of the experiment. 24

Figure 7. Species richness (S) in high and ambient CO2 treatments over the course of the experiment. 26

Figure 8. Basal species diversity (H’) in high and ambient CO2 treatments over the course of the experiment. 27

Figure 9. Algal evenness (J’) in high and ambient CO2 treatments over the course of the experiment. 29

Figure 10. Cover of the blue mussel, Mytilus edulis in high and ambient CO2 treatments over the course of the experiment. 30

LIST OF TABLES

Table S1. List of all species present in tide pool communities. 32

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CHAPTER 1: INTRODUCTION

It was over 50 years ago that Hutchison famously asked “Why are there so many kinds of animals?” (Hutchinson 1959) and in the subsequent years, countless hours of research have been (and are still being) spent trying to further elucidate this subject.

Approaches taken to try to understand large ecological questions such as these have changed much over the years, from smaller scale studies of patterns (Hutchinson 1953,

Connell 1961, Lubchenco 1978) to much larger, contextualized or multidisciplinary efforts (Menge et al. 2003, Ehlers et al. 2008, Boyer et al. 2009). However, the goal of enhancing our understanding of biological diversity, the structure and functioning of communities and ecosystems, and ultimately the biosphere remains.

The nature of research on biodiversity, that is, the number and abundance of species in a location has also changed substantially over the years. Hutchinson’s question has largely been supplanted by inquiries into the value and methods for the conservation of biodiversity (Humphries et al. 1995, Hector et al. 2001, Duffy 2002, Naeem 2002,

Stachowicz et al. 2002, Steneck 2009, Cardinale et al. 2012, Hooper et al. 2012). While there has been debate regarding the effects of biodiversity on ecosystem function (Naeem

2002), it is clear that species loss can impact a number of ecosystem properties (Naeem et al. 2012). This is especially important as many believe we are entering into the planet’s sixth mass extinction, largely due to anthropogenic factors such as habitat loss and climate change (Barnosky et al. 2011).

Climate change is predicted to increase stress for temperature-sensitive species. As global temperatures increase, we would expect alterations in species distribution patterns

(Fields et al. 1993). Though shifts will occur, not all organisms will be able to simply

move to a new location with an appropriate temperature, as barriers to migration may exist and some species (e.g., long-lived plants) are considerably less mobile than others.

In the case of intertidal organisms, the assumption that stress decreases with latitude does not hold in all locations because of interactions between tidal emersion and solar irradiance (Helmuth et al. 2002). Equatorial organisms are not necessarily the most stressed by increased temperature, preventing polar migrations for many organisms. We also do not expect climate to have the same direction and magnitude of change in every location on the earth. For example, coastal upwelling intensity is predicted to increase as the land warms, resulting in decreased sea-surface temperatures in Eastern Boundary

Current Systems (Snyder et al. 2003). This alteration in upwelling regimes also has the potential to alter ecological subsidies to coastal regions from the deep sea (Bakun 1990).

Furthermore, thermal stress can interact with a host of other processes to create for organisms and communities (Harley et al. 2006). Fishing, habitat loss and chemical changes to the environment all may have synergistic effects on biota.

One such chemical change to the environment is the process of ocean acidification.

As we are emitting increasing amounts of CO2 into the atmosphere, some remains in the atmosphere which can then trap radiative heat, leading to climate change. The ocean, however, acts as a sink for CO2, absorbing approximately 30% of the CO2 emitted to atmosphere (Feely et al. 2004). This CO2 and subsequently reacts with the water in the ocean:

− + 2− + CO2 (aq) + H2O <=> H2CO3 <=> HCO3 + H <=> CO3 + 2 H

This reaction yields hydrogen ions, which subsequently decreases oceanic pH. Over the next 100 years, as we are expected to approximately double atmospheric pCO2 (from

~400 ppm to ~800 ppm) we expect pH to decrease in turn by 0.3-0.4 units (approximately

100% increase in hydrogen ions) (Feely et al. 2004, Orr et al. 2005). This is not the only chemical change that occurs in this reaction, however. The conditions of the ocean and

- the thermodynamics of the reaction favor increases in bicarbonate (HCO3 ) and a

2- decrease in carbonate (CO3 ).

It is this reduction in available carbonate that makes ocean acidification a particularly potent threat to calcifying organisms (Doney et al. 2009). In addition to reducing available carbonate, thereby reducing an organism’s ability to deposit new shell, low pH conditions leads to shell dissolution (Feely et al. 2004). Organisms are therefore less capable of replacing shell that is lost. Some calcifying organisms produce biogenic habitat. Oysters and corals in particular are likely to be adversely affected in a future ocean, which may impact organisms that use the structure they create as habitat (Anthony et al. 2011, Waldbusser et al. 2011). Additionally, larval calcifiers use a form of carbonate that is 30 times more soluble than the forms used by most adults, leaving them even more vulnerable to these shifts (Caldeira and Wickett 2005, Orr et al. 2005, Ross et al. 2011).

Though ocean acidification is a substantial threat to calcification, it also has been shown to affect other processes. Processes such as fertilization, cleavage, larval development, and larva survival have all been shown to be impacted in various taxa

(Kurihara et al. 2007, Dupont et al. 2008, Parker et al. 2009, Ross et al. 2011). Immune response may also decline under high CO2 conditions (Bibby et al. 2008, Hernroth et al.

2011). Fish have been shown to have decreased olfactory capabilities and anitpredator responses (Munday et al. 2009, Dixson et al. 2010, Ferrari et al. 2011b). There is also

evidence of adverse metabolic and cardiac effects in fish (Fabry et al. 2008, Ishimatsu et al. 2008, Pörtner 2008).

Microalgae are particularly important organisms due to the amount of primary production they are responsible for in the ocean (MacIntyre et al. 1996). Because of this, there has been much research into the potential effects of increased oceanic CO2 on the calcifying phytoplankton coccolithophores (Delille et al. 2005, Engel et al. 2005,

Iglesias-Rodriguez et al. 2008, Langer et al. 2009, Beaufort et al. 2011). Though there has been some debate over methodology (Riebesell et al. 2008, Hurd et al. 2009), it is becoming clear that the calcification rate of these organisms will be adversely impacted by ocean acidification (Beaufort et al. 2011). Additionally, iron uptake decreases with decreased pH, further decreasing functional availability of what is already one of the biggest limiting nutrients in the open ocean (Shi et al. 2010). Ultimately, because of variation in responses between planktonic groups, we can expect shifts in planktonic community structure going forward (Hays et al. 2005).

Much like microalgae, macroalgae display a wide array of responses to low CO2 – conditions. Increased photosynthetis in high CO2 conditions is seen in various macroalgal groups (Giordano et al. 2005). Calcifying macroalgae, such as crustose coralline algae, are expected to decline despite any potential increased photosynthesis (Kuffner et al.

2008, Martin and Gattuso 2009). Though When entire algal communities are examined, a shift away from these calcifying species, as well as turf forming species may be expected, with species composition being affected more strongly than diversity (Porzio et al. 2011).

Species interactions are also likely to change in a future ocean. Positive interactions may change as one of the species exhibits an altered physiological response (Doropoulos

et al. 2012). Competetive interactions between species can be expected to be modified, causing phase shifts in communities (Kroeker et al. 2012). Predator-prey interactions may also be altered (Ferrari et al. 2011a). Food quality (e.g. fatty acid content or palatability) has also been shown to decresase in a high CO2 environment (Rossoll et al. 2012, Poore et al. 2013). It is clear that communities can be expected to face substantial change in a future ocean (Hall-Spencer et al. 2008, Hale et al. 2011, Kroeker et al. 2011, Porzio et al.

2011).

Tide pools provide a unique habitat for manipulating of naturally occurring communities. In particular, they are well suited to chemical manipulations, such as CO2 enrichment, for ecological studies due to their daily isolation at low tide, which provides discrete units of replication. Despite a natural daily tide pool variation in pH levels between 6 and 10 (Truchot and Duhamel-Jouve 1980) intertidal organisms do not seem particularly well prepared for a more acidic ocean, as major physiological effects can be seen with small changes in pH. For example, the inducible defenses of the periwinkle

Littorina littorea, a dominant grazer in local tide pool habitats (Lubchenco and Menge

1978, Altieri et al. 2009), are adversely affected by a decline in pH of approximately 1.3 units (Bibby et al. 2007). Furthermore, a 0.5-unit decline in ocean pH is enough to produce considerable effects on the development of Littorina obtusata embryos (Ellis et al. 2009).

- Another common tide pool species, the ephemeral alga Ulva, is an HCO3 utilizing alga, which means it utilizes a carbon concentrating mechanism (CCM) to obtain CO2 for photosynthesis (Cornwall et al. 2012). These CCMs are required in organisms that have inadequate dissolved CO2 available for passive absorption alone. When exposed to

elevated CO2 levels, species like Ulva typically exhibit increased growth rate as they shift to a less energetically expensive, passive manner of carbon acquisition. This shift has been shown to exert selective pressure to downregulate CCMs (Collins and Bell 2004).

Though an increased rate of growth may be seen, photosynthetic efficiency may decline under increased pCO2 conditions (Xu and Gao 2012).

Thus far, much ocean acidification research has focused on single species from groups such as coccolithophores (Engel et al. 2005), molluscs (Kurihara et al. 2007,

Beesley et al. 2008, Comeau et al. 2009, Waldbusser et al. 2010, Crim et al. 2011,

Cummings et al. 2011, Melatunan et al. 2011, Waldbusser et al. 2011), echinoderms

(Dupont et al. 2008, Hernroth et al. 2011), and arthropods ( McDonald et al. 2009).

Though species responses can be informative, it is important to consider a broader environmental context for these effects, including biological communities and species interactions (Russell et al. 2011). Because of the difficulty of manipulating water chemistry in situ, the vast majority of community-oriented studies have occurred either in the lab or in naturally occurring CO2 vents (Hall-Spencer et al. 2008, Cigliano et al. 2010,

Rodolfo-Metalpa et al. 2010, Porzio et al. 2011, Johnson et al. 2012, Lidbury et al. 2012).

While this approach is useful for identifying potentially patterns, there is a clear need for manipulative field CO2 experiments.

Objectives

My research aims to examine various potential responses of marine species and communities to the stress associated with increased CO2 in seawater. Due to

methodological issues with most forms of in situ CO2 enrichment (e.g., equipment, maintenance, and pseudoreplication), as well as the benefits discussed above, my thesis research was conducted in tide pools, which I used as a model community to describe potential impacts of elevated CO2 on rocky shores. The discrete nature of tide pools allows for replication as well as ease of access for maintenance of any device used to manipulate CO2. Yeast reactors provide a rugged and low cost manner of manipulating tide pool CO2 (Pedersen et al. 2007). This methodology was used to examine various elements of tide pool communities in order to see how communities may respond in the coming years to this aspect of anthropogenic environmental change. My objectives were as follows:

Objective #1: To examine the effects of increased CO2 on algae in the field using natural tide pools by measuring change in Ulva cover.

Objective #2: To evaluate the effect of increased CO2 on interactions between Littorina littorea and Ulva lactuca in outdoor mesocosm experiments by measuring growth and consumption rates.

Objective #3: To test potential mechanisms for changes in the alga-herbivore interaction by examining tissue content before and after treatment CO2 treatment.

Objective #4: To examine the community response to increased CO2 in natural tide pools by measuring effects on diversity, richness, evenness and community composition.

CHAPTER 2: CO2 ENRICHMENT MODIFIES GROWTH, TISSUE

COMPOSITION AND CONSUMPTION OF AN INTERTIDAL SEAWEED

Introduction

Ocean acidification (OA) is a uniquely large threat to calcifying organisms due to decreased availability of carbonate for calcification (Doney et al. 2009). Increased pCO2 has been shown to negatively impact some non-calcifying organisms (Fabry et al. 2008) as well as impede larval development (Kurihara 2008). In contrast, certain macroalgal species show increased levels of photosynthesis at higher concentrations of CO2

(Giordano et al. 2005), suggesting that some algae will thrive under acidified conditions.

These contrasting effects of OA on individual species highlight the difficulty of predicting effects on communities of interacting species. Much of the work of the effects of ocean acidification on communities has occurred in areas naturally acidified by CO2 vents (Hall-Spencer et al. 2008, Kroeker et al. 2011, Porzio et al. 2011, Johnson et al.

2012). Additional, a recent study has utilized lab based artificial “communities” to examine the interaction between producers and consumers (Asnaghi et al. 2013).

Combined with single-organism studies, these experiments further highlight the potential importance of species interactions in understanding global change.

Here, were revisit a classic interaction on rocky shore, the consumption of the seaweed Ulva by the periwinkle snail Littorina in tide pools (Lubchenco 1978), to show how OA impacts snails, seaweeds, and their interaction. Tide pools are an ideal model system for studying the ecological effects of OA because daily isolation allows for experimental manipulation of replicated, natural communities (i.e., different tide pools) in a system characterized by substantial natural daily variation (Truchot and Duhamel-Jouve

1980).

We therefore evaluated the impacts of elevated CO2 exposure on the interaction between Littorina littorea and Ulva spp. We anticipated an increased abundance of Ulva in tide pools, manifested through increased algal growth and decreased grazing pressure associated with stress. Grazer preference was then further isolated using a feeding assay with naïve snails. We also examined the stoichiometric effects of this exposure on algal tissue, with increased exposure to high CO2 conditions expected to increase tissue C:N.

Methods

Tide pool experiment

Beginning in June 2012, Tide pools (N=10) around East Point, Nahant,

Massachusetts of a similar size (perimeter: 3.1 ± 0.1 m [P=0.57]; volume: 31.3 ± 3.6 L

[P=0.52]; surface area: 0.52 ± 0.03 m2 [P=0.99]) and elevation (1.9 ± 0.1m above mean lower low water [P=0.65]) were randomly assigned to either a High or an Ambient CO2 treatment. Each High CO2 tide pool received CO2 from a sealed 1.5-L container

(OtterBox 3500) containing water, 400 g of sugar, ~5 g of yeast, and 0.25 g of NaHCO3 to buffer internal pH of the reactors. Yeast concentrations were varied with anticipated weather to account for temperature-related changes in CO2 production. Airline tubing from each reactor delivered CO2 via an airstone into the tide pool, causing a decrease in pH when tide pools were isolated at low tide. Alkalinity (Hanna Instruments HI 901) and pH (Hanna Instruments HI 9828) were measured to allow for calculation of pCO2 using the CO2calc software (Ambient: pH 8.05  0.07, 339ppm pCO2; High CO2: pH 7.80 

0.07, 658ppm pCO2 [P=0.018]; Figure 1). The solution in each container was replaced weekly to maintain the High CO2 treatments.

Percent cover surveys were conducted approximately biweekly in order to assess community composition of algae and invertebrates present. Before surveying, the perimeter of the tide pool was marked with a transect line, and all water was pumped from the pool, with the volume noted. Surface area and percent cover were measured using mesh netting (Bracken and Nielsen 2004). Pools were surveyed at weeks 0, 3, 5, 7 and 10. ANCOVA was used to assess the impact of increased CO2 on Ulva spp. cover at each recorded interval. Repeated measures ANCOVA, with initial Ulva cover as a covariate, was also performed. Due to a significant interaction between initial cover and

CO2 treatment, the interaction terms were not removed from the models. The slope of the relationship between initial Ulva cover and cover measured at weeks 3, 5, 7, and 10 of the experiment was used to quantify effect size over time.

Mesocosms

In order to examine the effects of acidification on algal growth and herbivory, in

July 2011 we crossed a High CO2 and Ambient CO2 treatment using paired chamber mesocosms containing the green alga Ulva lactuca and the herbivorous snail Littorina littorea. Paired mesocosms (12.5 x 8.5cm) were placed into artificial tide pools (26 x

9cm). Pools were then randomly assigned to one of two flow-through running seawater tables (1.83 x 0.91 x 0.25m), with lobster caging placed on top to weigh down mesocosms and ensure constant submersion. Tables were plumbed so that immersion and

emersion mimicked conditions experiences at +1.75 m above mean lower-low water

(Bracken 2004). High CO2 artificial tide pools received an influx of CO2 from a yeast reactor placed above the seawater table (Ambient: pH 7.93  0.02, 459ppm pCO2 ; High

CO2: pH 7.27  0.04; 2433ppm pCO2 [P<0.001]; Figure 1). Treatments were divided evenly between tables and assigned randomly within each table.

Figure 1. Observed pH ( SEM ) in field and mesocosm experiments (P=0.018 and P<0.001 respectively)

Yeast reactors consisted of a 0.59 L bottle, filled to a volume of 0.44 L with 200g of sucrose dissolved in water, 1g of instant dry yeast, and 0.25 g NaHCO3. Airline tubing

capped with an airstone ran to each treated mescosom, where the tubing was secured to the lobster caging.

Mesocosms contained mesh screening, with one side containing U. lactuca alone to measure autogenic growth, and the other containing U. lactuca and L. littorea to examine herbivore consumption. Consumption was calculated from the difference between U. lactuca alone and U. lactuca with L. littorea (Long et al. 2007).

All Ulva lactuca and Littorina littorea were collected from the intertidal zone of

East Point, Nahant, Massachusetts the day the experiment began. The experiment was run from July 21th to August 11th 2011. Weekly growth of Ulva and snails and snail consumption were analyzed with ANOVA.

Feeding assay and Tissue analysis

To examine how effects on algae altered snail grazing, a 4 week exposure assay was performed. Ulva was grown under ambient or high CO2 conditions during this time period. After the treatment had concluded, naïve snails were presented with either ambient CO2 treated Ulva or High CO2 treated Ulva for 3 days under ambient watertable conditions after which consumption was measured.

To assess the effect of exposure to high CO2 conditions on Ulva tissue content, 4- week exposure assays were performed in watertable mesocosms as described above on three separate occasions. Tissue was collected before and after the treatment. Tissue carbon content was measured using a NC Soil Analyzer Flash EA 1112 Series

(ThermoFisher Scientific, Waltham, MA). Experiments were pooled, and ANOVA was

performed to ascertain effect of CO2 on tissue carbon, accounting for any variation between experiments.

Results

Field

After 5 weeks of High CO2 exposure there was a twofold increase in the cover of

Ulva spp. (F1,16=13.084, P=0.002; Figure 2). This difference continued over the subsequent two weeks (F1,16=6.548, P=0.021), before equalizing by week 10 as seasonal changes led to a decline in overall Ulva abundance (Figure 2). This difference was more pronounced in pools with higher initial Ulva cover during weeks 5 and 7 (Treatment x

Initial Cover; Week 5: F1,16=8.964, P=0.009; Week 7: F1,16=5.417, P=0.033)

Figure 2. Enhancement of seaweed cover in tide pools associated with addition of CO2. Values are cover of the seaweed Ulva normalized by Ulva cover in pools prior to experimental manipulation, calculated as the slope of the relationship between initial Ulva cover and cover measured 3, 5, 7, and 10 weeks after the experiment was started. Values above 1 indicate an increase in cover while values below 1 indicate a decline. Cover was higher in elevated CO2 treatments 5 weeks (P = 0.0072) and 7 weeks (P = 0.0345) after initiation of CO2 additions

Mesocosms

U. lactuca showed a significant increase in growth in high CO2 treatments compared to ambient CO2 (Week 1: F1,26=7.921, P=0.01; Week 2: F1,26=7.607, P=0.01;

Week 3: F1,26=3.925, P=0.06; Week 4: F1,26=7.607, P=0.04; Figure 3a) After 4 weeks there was nearly a twofold difference in the percentage of U. lactuca consumed by L.

littorea in High CO2 treatments (F1,26=6.413, P=0.02; Figure 3b), with no difference in mass of Ulva present between treatments.

Figure 3. Growth (A) of Ulva and change in consumption (B) of Ulva by Littorina littorea (both percent change from initial Ulva mass  SEM) in high CO2 and ambient treatments over the course of the experiment. N = 14 replicates and * indicates P < 0.05 based on Student’s t-test.

Feeding assay and Tissue analysis

Snails consumed over 14 times the amount of Ulva grown under high CO2 conditions compared to ambient. (F1,18= 7.134, P= 0.02, Figure 4). There was a 2.44% increase in tissue carbon in Ulva exposed to high CO2 conditions (F1,80= 174.379, P=0.03; Figure 5).

Trial date did not have an effect on tissue content (F2,80= 23.987, P=0.513)

Figure 4. Consumption of Ulva by Littorina littorea (+ SEM) over the course of 3 day feeding assay under ambient conditions after Ulva was exposed to ambient or elevated CO2 levels for 4 weeks (P=0.02).

Discussion

As predicted, increased CO2 concentrations lead to increased growth of ephemeral algae. This change in growth also altered the stoichiometry of the algal tissue and the rate at which it was consumed by herbivores. These shifts were manifested in either increased algal growth rates or enhanced cover and have the potential to further modify community interactions.

In the field, increased exposure to high CO2 conditions led to higher than ambient cover of Ulva spp. This increase was transient, though the degree to which this transience was due to algal acclimation or seasonal die-off is unclear. As field surveys were not enclosed and did not include grazing measurements, we could not assess from this experiment alone whether the source of the change in cover was increased growth or decreased grazing, though grazing was enhanced by elevated CO2 in mesocosms. This is particularly noteworthy as Ulva abundance decreased in ambient pools throughout the treatment, while increased CO2 delayed this decline. While this may suggest a release of top down control by grazer under high CO2 conditions, there was no difference in snail abundance between High and Ambient CO2 pools (data not shown).

Figure 5. Change in Ulva tissue carbon ( SEM) over the course of 4 week exposures to ambient and elevated CO2 on three separate instances (P=0.03).

This result was paralleled by our mesocosm study. Increased exposure to high

CO2 increased growth in Ulva. This increase appeared rapidly and was followed by an increase in consumption of algal tissue by snails (i.e., growth differences occurred after 1 week, but consumption differences did not emerge until 4 weeks into the experiment).

Despite this increase in consumption, no evidence of increased snail growth was observed. Associated with this change in Ulva growth was an increase in the algal tissue carbon concentration. This may explain the change in feeding patterns observed, as snails would have been forced to increase consumptive rates to account for the relative decrease

in nitrogen (protein) per unit of algae (Raubenheimer and Simpson 2009). This shift in feeding has the potential to fundamentally alter the manner through which these communities function (Polis and Strong 1996). For example, an increased requirement for feeding means more risk of predation altering the behavioral tradeoff between safety and feeding (Schoener 1971).

Ulva have shown an ability to create blooms, which can be damaging ecologically and economically, and may be allelopathic (Valiela et al. 1997, Nelson et al. 2003).

While these blooms are generally associated with eutrophication, our work suggests that increases in seawater pCO2 will likely alter algal growth patterns from the bottom-up as well as alter top-down control by herbivores, with the potential for fundamental alteration of bloom dynamics by ocean acidification (Lapointe 1999).

Although the CO2 additions utilized in our experiments represent extreme values relative to predicted open-ocean conditions (Wootton et al. 2008), the declines in pH achieved in this study (Figure 1) were well within the natural range that can occur during an evening low tide, and thus do not represent unrealistic conditions. Our methods provide an inexpensive, easy to use way to manipulate CO2 levels in the field within the natural context of the system, providing more realistic results that capture the natural variation in the system as with higher levels of replication (McElhany and Shallin Busch

2012).

We are beginning to understand the impacts of global change processes on individual species, which can provide valuable information for managers. However, our understanding of how these species-specific effects will scale up to communities of interacting organisms remains much more limited. Manipulations like ours, utilizing

natural habitats and multiple species, therefore provide novel and invaluable information that is crucial for understanding the large-scale functional effects of climate change at the community level.

CHAPTER 3: CO2 ENRICHMENT REDUCES DIVERSITY IN TIDE POOL

COMMUNITIES

Introduction

In nature, communities are often comprised of multiple interacting species. Thus, in order to understand patterns of species’ distributions and abundances, it is important to examine not only their interactions with the physical environment, but also their interactions with each other (Metaxas and Scheibling 1993). Furthermore, interactions between species can mediate the productivity of ecosystems, which in turn affects ecosystem goods, services, and functions (Menge et al. 1997). Given the complexity of the abiotic and biotic processes that influence communities, it is important to understand how changes in the abundance or attributes of one species affect the other species in the system. Looking at global change through the lens of ecology is a necessary basis for any prediction of the shape of communities and ecosystems in the future biosphere (Vitousek

1994).

Over the last 150 years, global oceanic surface pH has decreased by 0.1 units, with a decrease of 0.3-0.4 units expected within the next 100 years due to the process of ocean acidification associated with increases in CO2 concentrations in seawater

(Intergovernmental Panel on Climate Change 2000, Feely et al. 2004, Orr et al. 2005).

Ocean acidification (OA) has been demonstrated to adversely affect calcifying as well as non-calcifying organisms in a number of ways (Fabry et al. 2008, Kurihara 2008, Doney et al. 2009, Kroeker et al. 2010, Shi et al. 2010, Whiteley 2011)). Algal responses to CO2 additions in seawater have been mixed, with winners and losers often defined by

functional group (Giordano et al. 2005, Kuffner et al. 2008, Martin and Gattuso 2009,

Porzio et al. 2011)

Because of the variability in how species respond to OA, as well as the potential myriad indirect effects that may result from these different responses, predicting how OA will affect community structure is an extremely difficult task. Thus, community-based investigations are necessary. Most community level OA research has occurred in CO2 vent areas, which provide a natural CO2 gradient, or in controlled, lab-based mesocosm assays (Hall-Spencer et al. 2008, Kroeker et al. 2011, Porzio et al. 2011, Johnson et al.

2012, Asnaghi et al. 2013). Though these experiments provide key insights into potential response patterns, there remains a relative dearth of manipulative field experiments in this field that examine mechanistically how OA impacts community structure.

By examining a classic habitat on rocky shores, the tide pool, we aim to examine how ocean acidification may affect natural communities (Lubchenco 1978). Due to daily isolation at low tide, tide pools provide an opportunity for experimental manipulation of

OA in replicate, natural communities (i.e., different tide pools) (Truchot and Duhamel-

Jouve 1980). Therefore, we evaluated the impacts of elevated CO2 exposure on naturally occurring tide pool communities. We anticipated increased abundance of fast growing, ephemeral species resulting in a decline in perennial species and leading to an overall reduction in species diversity.

Methods

Tide pools (N=10) around East Point, Nahant, Massachusetts of a similar size

(perimeter: 3.1 ± 0.1 m [P=0.57]; volume: 31.3 ± 3.6 L [P=0.52]; surface area: 0.52 ±

0.03 m2 [P=0.99]) and elevation (1.9 ± 0.1 m above mean lower low water [P=0.65])

were randomly assigned to either High or Ambient CO2 treatment. Each High CO2 tide pool received CO2 from a sealed 1.5-L container (OtterBox 3500) containing water, 300 g of sugar, ~5 g of yeast, and 0.25 g of NaHCO3 to buffer internal pH of the reactors.

Yeast concentrations were varied with anticipated weather to account for temperature- related changes in CO2 production. Airline tubing from each reactor was delivered CO2 via an airstone into the tide pool, causing a decrease in pH when tide pools are isolated at low tide (Ambient: pH 8.36  0.08, 223 ppm pCO2; High CO2: pH 8.07  0.10, 507ppm pCO2 [P=0.019]). The solution in each container was replaced weekly to maintain the

High CO2 treatments.

Percent cover surveys were conducted approximately biweekly in order to assess algal cover. Before surveying, the perimeter of the tide pool was marked with a transect line and all water will be pumped from the pool, with volume noted. Surface area and percent cover were measured using mesh netting (Bracken and Nielsen 2004).

The manipulation ran from April to October, and pools were surveyed approximately biweekly. I measured percent cover of all basal species using the mesh netting described above, as well as determined abundance of mobile invertebrates by counting them. Species richness, algal and basal diversity (H’), algal and basal evenness

(J’) and mobile invertebrate density were calculated at each interval. Total algal cover was used as a proxy for biomass and compared across treatments. Differences in these metrics between treatments were examined for each sample date using ANOVA, with repeated measures ANOVA being used to examine the overall effect throughout the experiment. Community composition was examined using PERMANOVA (Clarke, KR,

Gorley, RN, 2006. PRIMER v6: User Manual/Tutorial. PRIMER-E, Plymouth)

Results

Algal diversity remained relatively stable in the high CO2 treatment over the first

8 weeks (i.e., from late April to late June), while increasing approximately 30% in ambient pools (F1,18= 5.889, P=0.03; Figure 6). Beginning in early July, a series of heat waves likely reduced algal diversity in both treatments, and diversity in high- and ambient-CO2 pools became indistinguishable by late July.

Figure 6. Algal diversity (H’) in high and ambient CO2 treatments over the course of the experiment. N = 10 replicates and * indicates P < 0.05 based on Student’s t-test.

This pattern was mirrored in species richness (F1,16=6.554, P=0.02; Figure 7) as well as total basal diversity (F1,16= 8.255, P=0.01; Figure 8), with maximum effect sizes

(i.e., reductions in diversity in high-CO2 pools) occurring in mid-June. These effects were ephemeral, as declines were seen in these metrics in both treatments by the end of

July. In spite of this reduction in species, there was a lingering effect on evenness that persisted for another 4 weeks (F1,18= 5.845, P=0.03; Figure 9). There was also a shift in community composition, which rapidly converged by the end of the first month

(PERMANOVA: Treatment x Time: Pseudo-F1,18= 5.246, P(perm)<0.01). There was no effect on L. littorea density (F1,18= 0.207, P= 0.655) or mobile species richness (F1,18=

2.342, P= 0.143).

Figure 7. Species richness (S) in high and ambient CO2 treatments over the course of the experiment. N = 10 replicates and * indicates P < 0.05 based on Student’s t-test.

Discussion

Whole community effects developed rapidly, with the most pronounced effect occurring in algal diversity (Figures 6-9). Though there were higher levels of diversity, richness and evenness in ambient pools, this was not achieved through species loss. As the treatments began early in the season, diversity increased in the ambient pools over the following weeks. Increased CO2 prevented the natural seasonal increase in these metrics.

These effects were short lived however, as large scale die-offs began in the beginning of

July coinciding with a heat wave. Ambient pools maintained a higher amount of evenness

after other metrics such as richness and basal diversity began converging. This may in part be related to differential effects on Mytilus cover around that time, with a larger decrease in cover in high CO2 pools during the height of summer (P<0.05 for weeks 16-

20). Though there was a slight, short term change in composition, most differences that were seen were in relative abundance.

Figure 8. Basal species diversity (H’) in high and ambient CO2 treatments over the course of the experiment. N = 10 replicates and * indicates P < 0.05 based on Student’s t-test.

Though there was a clear effect on diversity, there was no lasting overall effect on community composition. There is evidence that certain growth forms of algae may respond more to high CO2 conditions (Porzio et al. 2011), but the effects of high

temperature appear to have overridden any effects of added CO2 in the system. Of the species present in the pools, only Mytilus and Chondrus displayed a measurable response to OA, with both exhibiting slight declines in cover under high CO2 conditions (Figure

10). This decline in Mytilus did not appear to be caused by predation, as shells were still intact and attached to the substrate. It is possible that these subtle shifts in abundance may have led to further competitive imbalances had the experiment been able to extend in length (Connell and Russell 2010, Kroeker et al. 2012). It is also not clear whether the convergence between treatments is fully attributable to the change in temperature experience during that time period - determining this would require experimental manipulation of temperature – or some degree of acclimation. Though we would not necessarily expect a particularly robust response to OA from many of these species

(Bibby et al. 2007, Ellis et al. 2009, Melatunan et al. 2011, Kerrison et al. 2012), it is possible that they are still more well suited to a higher pH environment than conspecifics

that colonize emergent rock.

Figure 9. Algal evenness (J’) in high and ambient CO2 treatments over the course of the experiment. N = 10 replicates and * indicates P < 0.05 based on Student’s t-test.

The pH conditions reported in this study are relatively variable for OA research.

This is due to the highly variable nature of tide pools (Truchot and Duhamel-Jouve

1980). Because of the variation that these organisms witness every day, we deemed it appropriate to press CO2 to a given magnitude rather than utilize the stable conditions seen in most other OA studies (McElhany and Shallin Busch 2012). By manipulating a highly variable system in such a way, we operated within the framework of the system itself. Due to flushing at high tide, it is likely that the treatments were, on average,

relatively conservative estimates of conditions a future ocean.

Figure 10. Cover of the blue mussel, Mytilus edulis in high and ambient CO2 treatments over the course of the experiment. N = 10 replicates and * indicates P < 0.05 based on Student’s t-test.

Though community-level research is becoming more prominent in the field of climate change, it is crucial to continue to examine these systems. Because of the complexity and interconnectivity the natural world, it is crucial that we continue to utilize new approaches to try to disentangle the various interactive effects of physical and biological processes to understand how it is changing before us. Predicting and mitigating climate change effects will not be possible with lab experiments, natural experiments or even manipulative field experiments in isolation. This study is, to my knowledge, the first

of its kind. By utilizing natural habitats, we gain a different perspective on how communities may change. Further research of this type along with a multidisciplinary and interconnecting approach to global change will be necessary to gain the most information possible about how the biosphere is changing.

Appendix A: Supplemental tables

Effect of increased CO2 on Species Type cover/abundance Ascophyllum nodosum Brown algae - Chordaria flagelliformis Brown algae - Desmarestia sp. Brown algae - Ectocarpus sp. Brown algae - Elachista fucicola Brown algae - Fucus spp. Brown algae - Laminaria digitata Brown algae -

Leathesia sp. Brown algae Petalonia fascia Brown algae - Ralfsia spp. Brown algae - Scytosiphon lomentaria Brown algae Berkeleya hyalina Diatom - Chaetomorpha spp. Green algae - Cladophora spp. Green algae - Codium fragile Green algae - Rhizoclonium sp. Green algae -

Ulva spp. Green algae Anenomes Invertebrate - Asterias vulgaris Invertebrate - Carcinus maenus Invertebrate - Colonial ascidians Invertebrate - Crepidula fornicata Invertebrate - Hemigrapsus sanguineus Invertebrate - Littorina littorea Invertebrate / Littorina obtusata Invertebrate - Littorina saxatilis Invertebrate -

Mytilus edulis Invertebrate Nucella lapillus Invertebrate - Semibalanus balanoides Invertebrate Stalked hydroids Invertebrate - Tectura testudinalis Invertebrate - Ahnfeltia plicata Red algae - Ceramium spp. Red algae - Chondrus crispus Red algae Corallina officianalis Red algae - Crustose Corallines Red algae - Dumontia contorta Red algae -

Hildenbrandia spp. Red algae - Mastocarpus stellatus Red algae - Polysiphonia spp. Red algae - Porphyra spp. Red algae - Vertebrata lanosa Red algae -

Table S1. List of all species present in tide pool communities. Up arrows indicate the species significantly increased in abundance after being exposed to high CO2 conditions, while the down arrows indicate a decline. Up and down arrows together indicate the species exhibited an increase and a decrease at different points in the experiment. Dashes indicate there was no significant effect.

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