THE PENNSYLVANIA STATE UNIVERSITY SCHREYER HONORS COLLEGE

DEPARTMENT OF BIOLOGY

THE EFFECT OF A NUTRIENT GRADIENT ON THE PORITES-LITHOPHAGA SYSTEM IN THE

GAVIN VANSTONE SPRING 2017

A thesis submitted in partial fulfillment of the requirements for a baccalaureate degree in Biology with honors in Biology

Reviewed and approved* by the following:

Iliana Baums Associate Professor of Biology Thesis Supervisor

Benoît Dayrat Associate Professor of Biology Honors Adviser

* Signatures are on file in the Schreyer Honors College. i

ABSTRACT

Excess nutrients on reefs can lead to increased bioerosion by boring animals, such as mollusks and sponges. Bioerosion leads to weaker coral skeletons that are susceptible to fragmentation by both abiotic and biotic factors. The Phoenix Islands are an isolated archipelago found in the central Pacific Ocean in which the northern islands, Kanton and Enderbury, lie in the path of the Equatorial Undercurrent (EUC) creating periods of upwelling around the islands.

This creates a nutrient gradient across the northern group and the southern group of islands. Two morphologically similar reef building , Porites evermanni and Porites lobata, were differentially susceptible to bioerosion by Lithophaga mussels, which can increase asexual reproduction rates by fragmentation. Nine of the ten islands studied here exhibited mainly sexual reproduction. Our results suggest a different trophic interaction in the Phoenix Islands than seen in the Eastern Tropical Pacific, where fragmentation by triggerfish leads to increased asexual reproduction.

ii

TABLE OF CONTENTS

Acknowledgements ...... iii

INTRODUCTION ...... 1

MATERIALS AND METHODS ...... 4

Study Sites ...... 4 Sampling Method ...... 4 Genotyping ...... 5 Analysis of Multi-Locus Genotypes (MLGs) ...... 6 Mussel Count Data ...... 7 Population Structure Analysis ...... 8

RESULTS ...... 9

Species Identification ...... 9 Mussel Count Data ...... 9 Multi-Locus Genotype Data ...... 10 Population Structure Data ...... 11

DISCUSSION ...... 12

Appendix A Tables ...... 15

Appendix B Figures ...... 21

BIBLIOGRAPHY ...... 26

iii

ACKNOWLEDGEMENTS

First, I would like to thank Dr. Iliana Baums for all her help and support through this entire project. I would not be the scientist I am today without her guidance. I would also like to thank Dr. Benoît Dayrat and Dr. Michael Axtell for acting as my honors advisors over the past two years. They provided valuable help throughout the entire process.

Secondly, I would like to thank the rest of the members of Baums Lab. Meghann was an absolutely amazing resource and I would not have gotten this project done without her help.

Andie was the perfect person to turn to whenever I had questions or needed direction. Thanks also to Sam and Sheila, who provided help when I had nowhere else to turn. Thanks also to

Caitlyn Kupp who was responsible for helping calculate and assemble the mussel boring data. I also want to thank my family and friends who helped me get through the entire project.

This project was possible because of Randi Rotjan and her leadership over the PIPA 2012

Research Expedition. Thank you to Jenny Boulay and Hanny Rivera for helping collect these samples on the expedition. Without funding from Penn State’s Eberly College of Science, this project would not have been possible. 1

INTRODUCTION

Coral reefs are delicate ecosystems that thrive in nutrient poor tropical and subtropical environments. Even though corals are adapted to thrive under low nutrient concentrations, collectively they create the three-dimensional structure that provides for one of the most productive ecosystems in the world and can support a wide array of marine organisms (Hallock and Schlager, 1986). Unfortunately, small changes in nutrient availability can swing the equilibrium out of favor of corals into favor of other organisms. While there is evidence that increased nutrients could be beneficial to coral under certain conditions, increased nutrient concentrations often favor macroalgae and filter feeders (D’Angelo and Wiedenmann, 2014).

Increased populations of filter feeders are especially threatening to coral reefs because it can lead to increased rates of bioerosion on the reef. Bioerosion occurs when the filter feeders, such as mussels, bore into the coral skeleton (Szmant-Froelich, 1983). Some amount of bioerosion is natural as it allows for another form of asexual reproduction called fragmentation. However, large populations of filter feeders can jeopardize the integrity of the reef by weakening the reef building corals, also known as hermatypic corals.

Porites is one of the most common species of hermatypic corals throughout the Eastern and Central Tropical Pacific. The Phoenix Islands have two common Porites corals, P. lobata and P. evermanni. Both species are morphologically similar, but are genetically different

(Boulay et al. 2013). Scott and Risk (1988) showed that P. lobata is among the weakest hermatypic corals and its skeleton is often heavily bored by Lithophaga mussels. In the Eastern

Tropical Pacific (ETP), P. evermanni is also bored by Lithophaga mussels (Boulay et al. 2013).

Boring by the mussels weakens the Porites already relatively weak skeleton. Reefs with 2 increased nutrient availability, either through natural or anthropogenic causes, have higher rates of bioerosion (D’Angelo and Wiedenmann, 2014). Lithophaga are preyed upon by triggerfish that fragments the coral when it consumes the bored mussel. This is a naturally occurring process and Porites fragments have a 30-50% chance of survival when fragmented from the parent colony (Guzmán and Cortés, 1989). However, excessive fragmentation can be detrimental to the long-term health of the reef due to a decrease in genetic diversity. Decreased diversity of foundation species can make reefs less resilient to changes in the environment, making them more susceptible to disease and disturbance (Reusch et al. 2005).

The Phoenix Islands is an archipelago found in the south central Pacific Ocean. It consists of eight islands and two submerged reefs. The islands are spread over an area that covers more than 100,000 square kilometers of open ocean, meaning there is varying oceanic conditions at each island. The islands also create the Phoenix Island Protected Area (PIPA), which is the largest protected marine area in the world and has helped to limit the amount of local anthropogenic disturbances. Even though there are few local anthropogenic disturbances, the reefs in the Phoenix Islands still must deal with natural fluctuations in the environment. The

Phoenix Islands lie at a similar latitude to Jarvis Island, which experiences large amounts of upwelling caused by the Equatorial Undercurrent (EUC) (Gove et al. 2006). This cold, nutrient rich and eastward flowing current creates a north to south nutrient gradient in the Phoenix

Islands, where there are higher levels of nutrients in the northern Phoenix Islands compared to the southern Phoenix Islands.

Due to natural upwelling events, we would predict a higher degree of Lithophaga boring and thus higher rates of asexual reproduction in the nutrient rich northern Phoenix Islands as compared to the southern Phoenix Islands. Based on previous work in the Eastern Tropical 3 Pacific (ETP), we would also predict that P. evermanni will experience higher rates of mussel boring and therefore higher rates of asexual reproduction as compared to P. lobata (Boulay et al.

2013).

4

MATERIALS AND METHODS

Study Sites

This study analyzed 193 samples collected in 2012 from the Phoenix Islands. There were

121 samples of P. lobata and 72 samples of P. evermanni. The Phoenix Islands are an archipelago found in the central Pacific Ocean containing eight islands and two submerged reefs.

Five of the eight islands within the Phoenix Islands archipelago were used for this study (Figure

1). Two of these islands were in the northern part of the archipelago, Kanton (2.8040° S,

171.6462° W) and Enderbury (3.1272° S, 171.0837° W). Two were in the southern part of the archipelago, (4.6779° S, 174.5196° W) and (4.5150° S, 172.1768° W). The fifth is (3.7209° S, 170.7117° W), which is found in the middle, between the two island groupings. Seventeen reefs were used within these five islands. There were seven sites at

Kanton, five sites at Enderbury, one site at Rawaki, two at Orona, and two at Nikumaroro (Table

1). Many of the sites chosen were ones that were previously sampled before and after the

2002/2003 coral bleaching events.

Sampling Method

Samples were collected in either a random or haphazard sampling method. The process of random sampling followed the same design as Baums et al. (2006). Random sampling involved taking coral samples from randomly generated coordinates within 15 and 25m radius circular plots. SCUBA divers used a compass and a tape measure secured to the center of the plot. The divers swam to the randomly generated coordinates within the plot and sampled the colony underneath each coordinate. A photograph was also taken of each colony for further analysis. 5 The second type of sampling was haphazard sampling. Haphazard sampling involves swimming across the reef and choosing the colonies to sample, instead of using randomly generated coordinates. Since haphazard sampling is not random, it could be biased. There was limited time at each site due to the nature of the expedition, which led to the use of haphazard sampling.

Random sampling takes considerably more time. In sites where there was less time available, haphazard sampling had to be used. Across the species, 32% of P. lobata and 5.6% of P. evermanni were sampled haphazardly.

Genotyping

The genotyping steps followed the same procedure as Boulay et al. (2012). DNA from the samples was extracted using the DNeasy 96 Blood and Tissue Kit (Qiagen, CA). Following the DNA extraction, five polymerase chain reactions (PCRs) were set up for eleven microsatellite loci. Four reactions were multiplex reactions consisting of two or three primers and one was a singleplex reaction (Table 2). The thermal cycling protocol began with a 94°C initial denaturation for 5 minutes, then 35 cycles of a 94°C denaturation step for 20 seconds, a

52–56°C (depending on the plex being run) annealing step for 20 seconds, and a 72°C polymerization step for 30 seconds. The cycle completed with a 30-minute final polymerization step at 72°C to allow for the formation of an adenine tail on each product.

Immediately following the PCR, the products were run through a gel electrophoresis to confirm that the reactions were successful. The PCR products were then sent to the genotyping lab on campus for genotyping on the 3730XL DNA Sequencer. Once genotyped, the alleles were labeled using Genemapper 5.0 (Applied Biosystems, CA). 6 Analysis of Multi-Locus Genotypes (MLGs)

Because both species of Porites used in this study are morphologically similar and are commonly found in the same reefs, each sample had to be classified to a species before any analysis could be completed. To distinguish between the species, a principle coordinate analysis

(PCoA) was run using GenAlEx v6.5 (Peakall and Smouse, 2012). Fifty confirmed genets of P. lobata and fifty confirmed genets of P. evermanni from across the central and eastern Pacific

Ocean were used as control samples in the PCoA (Table 3). Only samples from the Phoenix

Islands with alleles at nine or more loci were considered in this PCoA. The PCoA clustered both the known and unknown Phoenix Island samples, allowing for the unknown samples to be classified as a species based on where they clustered (Figure 1). Once species designation was determined, pie charts were overlaid across a map of the Phoenix Island to show the species distribution across the Phoenix Islands (Figure 2).

Once each sample was identified as one of the two species, genotypic diversity indices were calculated. Genotypic diversity looks at the amount of unique multilocus genotypes in a population and varies on the level of whole organisms. Three indices, genotypic richness

(NG/N), genotypic diversity (GO/GE), and genotypic evenness (GO/NG) were calculated for each species on each island. Genotypic richness is the proportion of the number of unique genotypes

(NG) identified over the total number of colonies sampled (N) (Baums et al. 2006). Genotypic richness is directly proportional to the amount of sexual recruitment in a population.

Genotypic diversity is calculated by taking the observed genotypic diversity (GO) and dividing it by the expected genotypic diversity (GE) (Stoddart and Taylor, 1988). Genotypic diversity nears one in an entirely sexual population. It approaches zero in a population where all colonies are asexually produced. Observed genotypic diversity is calculated by dividing the 7 inverse of the sum of the square of ni (the number of individuals of genotype I found in the total number of samples) by N (Boulay et al. 2012). The expected genotypic diversity is the total number colonies sampled. Expected genotypic diversity does not need to be estimated if the

-7 probability of identity (PID) for each species is lower than 1x10 (Baums et al. 2006). The PID for

P. lobata was 7.2 x 10-14 and for P. evermanni was 3.0 x 10-7. Even though the PID value for P.

-7 evermanni is greater than 1x10 , the analysis was still completed. The PID was calculated using

GenAlEx 6.5 (Peakall and Smouse, 2012). The probability of identity is the probability that two individuals drawn at random from a population have the same genotype at multiple loci (Waits et al. 2001).

Genotypic evenness is related to genet longevity instead of recruitment. It is calculated by dividing observed genotypic diversity (GO) by the number of unique genotypes (NG). When a population is dominated by one genotype, evenness approaches zero. When each genotype has an equal number of member colonies, evenness will approach one.

Mussel Count Data

The amount of boring by Lithophaga mussels was calculated by analyzing pictures taken of each colony sampled using the application ImageJ (Schindelin et al. 2015). After sampling, each colony was photographed with a scale so the total area of the colony could be measured.

Only 164 of the 193 samples had photographs. Each photograph was put into ImageJ and the total colony area was measured for each sample. The amount of visible mussel boring holes on each colony was also counted. This work was done by a previous member of Baums Lab. To determine the amount of boring into a colony, the number of visible mussels was divided by the total area of the colony to give the average number of mussels per cm2 of coral. Once every 8 colony had a value, the values were separated by island and by species (Figure 3). To determine the relationship between location, species, and the amount of mussel boring, a two-way ANOVA was run using Minitab 17 (Minitab, PA). A T-Test was run comparing the location of the sample and the amount of boring in each species (Minitab, PA). The two groups were the northern islands, which included Enderbury and Kanton, and the southern islands, which included Orona and Nikumaroro. Rawaki was excluded in this analysis.

Population Structure Analysis

There was no a priori information available on the likely number of P. lobata and P. evermanni populations in the Phoenix Islands. Therefore, for each species, the number of genetically differentiated populations, K, was estimating by using a Bayesian approach, implemented in the program STRUCTURE (Pritchard et al. 2000; Falush et al. 2003). The program was run without a population prior and each K was run with three replicates. The most likely value for K was determined Structure Harvester (Dent and vonHoldt, 2012). The length of burnin was 100,000 and the MCMC was 1,000,000.

9

RESULTS

Species Identification

Previous work at Kingsman Island in the Central Pacific showed that P. evermanni can be found in reefs that also contain P. lobata (Kenyon et al. 2010). The similar morphology between P. lobata and P. evermanni meant that the species designation of samples had to be classified genetically before any further analysis could be done. Following the genotyping of the species, a PCoA was run using the non-species designated samples from the Phoenix Islands and known P. lobata and P. evermanni samples from sites throughout the Pacific (Table 3). The

PCoA enabled us to classify species based on clustering of the unknown samples with the known samples (Figure 1). Once species designation was determined pie charts were overlaid across a map of the Phoenix Island to show the geographic variation in the species distribution (Figure 2).

There is a clear divide among the species, as P. lobata seems to dominate the northern islands and P. evermanni seems to dominate the southern islands. However, this could be a result of the sampling methods at each site.

Mussel Count Data

Understanding the amount of bioerosion from mussels can provide insight on the types of reproduction used on a reef. When comparing mussel boring density between islands and species using a two-way ANOVA, there was a significant interaction between species and mussel density (p<0.05), location and mussel density, (p<0.05), as well as when both factors, island and species, were considered, (p value<0.05) (Table 4). Mussel boring density was significantly 10 increased in P. lobata as compared to P. evermanni at (Figure 3). Comparisons of mussel density between species at all other islands was not significant.

To see if there was a relationship between location and the amount of mussel boring, a T-Test was run comparing location and the amount of boring. Two groups were created, north and south. The northern grouping of islands included Kanton and Enderbury, the southern grouping of islands included Orona and Nikumaroro. Rawaki was ignored due to a lack of samples. There was a difference in the amount of boring between north and south in P. lobata

(p-value <0.05). There was no difference in the amount of boring between north and south in P. evermanni (p-value>0.05).

Multi-Locus Genotype Data

Biodiversity indices give an indication of types of reproduction found in a population.

One measure, genotypic richness, is directly proportional to the amount of sexual recruitment.

High genotypic richness was found in each island of P. lobata studied, with no island having a richness value less than 0.91 (Table 5). For P. lobata, there was no significant difference across the north to south gradient. There was also high genotypic richness in P. evermanni at each island, in which four of the five islands had richness values greater than 0.9 (Table 6), with the exception of P. evermanni at the southern island of Orona which had a richness value of 0.5.

Genotypic evenness (GO/NG) in a population is a measure of genet longevity. Evenness approaches one in populations where each colony is a unique genotype. There is high genotypic evenness at each island of P. lobata studied. Each island had an evenness value greater than 0.89, showing no significant difference across the nutrient gradient. Four of the five islands of P. 11 evermanni had evenness values greater than 0.94, with again the exception being the southern island of Orona which had a genotypic evenness of 0.36 (Table 6).

Genotypic diversity is maximized in a solely sexual population. Each island of P. lobata had a genotypic diversity value greater than 0.86, even across the north to south nutrient gradient. Four of the five islands of P. evermanni have genotypic diversity values higher than

0.86. However, the southern island of Orona had a genotypic diversity value of 0.18.

Population Structure Data

To gain a better understanding on the genetic interconnectedness of the islands of both P. lobata and P. evermanni, population structure plots were made. Structure Harvester determined the most likely K for P. lobata to be 3 (Figure 4). However, individuals are assigned with a high probability to three different population clusters within an island. This is seen at each island except for Nikumaroro, where all individuals are assigned to the same population cluster (Figure

4). Structure Harvester determined the most likely K for P. evermanni to be 3 (Figure 5). The islands of Enderbury and Nikumaroro appear to be one population cluster, while Kanton and

Orona seem to be two separate population clusters (Figure 5).

12

DISCUSSION

In the Phoenix Islands, Lithophaga mussels are a common bioeroder that can bore into the skeleton of reef builders, such as P. lobata and P. evermanni. Bioerosion is a natural process on coral reefs that can be exacerbated under high nutrient concentrations. (D’Angelo and

Wiedenmann, 2014). In the Phoenix Islands, there is a north to south nutrient gradient that leads to higher levels of nutrients in the northern islands compared to the southern islands. As expected, in P. lobata there was significantly higher mussel boring density in the northern islands of Kanton and Enderbury, as compared to the southern islands of Orona and Nikumaroro.

However, this comparison was not different in P. evermanni. Holmes et al. (2000) found that reefs in Indonesia that were exposed to higher rates of nutrients from anthropogenic causes experienced higher rates of bioerosion compared to reefs that were more isolated. Kanton lies at a more northern latitude than Enderbury, suggesting that the upwelling resulting from the EUC creates a gradient between Kanton and Enderbury. Boring rates in P. evermanni did not significantly vary across islands. There are higher amounts of boring in P. lobata compared to P. evermanni. This is the opposite of what was seen in the ETP. One possible explanation could be that there are different species of Lithophaga mussels in the Phoenix Islands that prefer boring P. lobata skeletons as opposed to P. evermanni skeletons. A more comprehensive study comparing the interactions between the Lithophaga and Porites of the two locations is necessary to help better understand why these differences occur. Understanding the differences between the two systems will help conservation efforts in the future.

Nine of the ten groups of Porites in the Phoenix Islands are mainly of sexual origin. This includes islands from both the northern and southern grouping of islands. The only group that 13 seemed to originate from a mix of asexual and sexual reproduction is the group of P. evermanni on the island of Orona, which is in the southern grouping of islands. These results were unexpected in the Phoenix Islands due to the north to south nutrient gradient that naturally occurs. Overall, boring does not seem to have the same effect in the Phoenix Islands as it does in the ETP. In the ETP, two species of triggerfish prey on Lithophaga mussels, Pseudobalistes naufragium and Sufflamen verres (Boulay et al. 2013). Both species are endemic to the ETP and do not spread into the central Pacific where the Phoenix Islands are. The Phoenix Islands are home to Xanthichthys triggerfishes, which do not consume the Lithophaga mussels like their eastern Pacific counterparts. Instead they consume free floating phytoplankton (Allen and

Bailey, 2011). Losing the triggerfish portion of the three-way interaction would result in less asexual reproduction as seen in these results. The high amounts of sexual reproduced reefs found in this study are similar to what Schweinsberg et al. (2016) found in Tahiti. This suggests that missing the population of triggerfish that consume the boring Lithophaga limits the amount of asexual reproduction possible for P. evermanni and P. lobata. Even though these triggerfish are not present, there is still a trophic interaction between Porites and Lithophaga that needs to be considered when deciding conservation efforts in the future. Understanding these trophic interactions can be important in conservation methods as climate change continues to alter the habitats of different species of marine organisms.

The connectivity of the islands of P. evermanni was unexpected. The northern island of

Enderbury and the southern island of Nikumaroro are spread across 418 kilometers of ocean, but were assigned to the same cluster. A more detailed study on ocean currents around the Phoenix

Islands may be able to explain this connectivity. In addition, when looking at K=4 in the population structure plot, it appears that the islands of Enderbury and Nikumaroro are becoming 14 two separate population clusters. Future work should include adding more unique multilocus genotypes to the dataset to see how it changes the results. In P. lobata there is a high probability of assignment to multiple clusters within one island. These results seem to indicate there are multiple species of Porites being compared, instead of just samples of P. lobata. Many species of

Porites are morphologically similar, and therefore are difficult to discern which species each one is. A recent study in Hawaii (Forsman et al. 2017) used mitochondrial and nuclear gene testing to help differentiate between Porites compressa and P. lobata. Future studies in the Phoenix Islands would be to look at the mitochondrial and nuclear genes of these samples to see if they are actually different species. By understanding the different species that compose the reefs of the

Phoenix Islands, conservation efforts in the future can be more specialized.

Coral reefs are complex ecosystems that foster a myriad of both biotic and abiotic interactions. Many of these interactions are complicated and are still being understood. The more these interactions are understood, the easier it becomes to begin conservation efforts in the face of global climate change and other anthropogenic threats, such as nutrient runoff and eutrophication. In the Phoenix Islands, P. lobata and P. evermanni have been resilient to many bleaching events and in general have maintained a largely sexual population in the face of a nutrient gradient caused by upwelling. By further understanding how the Porites populations of the Phoenix Islands can sustain large sexually reproducing populations, even in the face of a nutrient gradient, it may provide answers to how to better conserve reefs in other areas that are more affected by nutrient swings. 15

Appendix A

Tables

Table 1: Reef sites sampled at each island

Island Site Coordinates Enderbury Lone Palm 3.1182°S, 171.0928°W Enderbury Mystery Wreck 3.1244°S, 171.0787°W Enderbury Observation Spot 3.1423°S, 171.0924°W Enderbury Shark Village 3.1061°S, 171.0926°W Enderbury Short Ride 3.1249°S, 171.0933°W Kanton British Gas 2.8210°S, 171.7175°W Kanton Coral Castles 2.8135°S, 171.6957°W Kanton Kanton Lagoon 2.8460°S, 171.6391°W Kanton Satellite Beach 2.7799°S, 171.7252°W Kanton Six Sticks 2.8055°S, 171.7205°W Kanton Steep To 2.8331°S, 171.7085°W Kanton Weird Eddy 2.8101°S, 171.7185°W Nikumaroro Turtle Nest Beach 4.6668°S, 174.5150°W Nikumaroro Windward Wing 4.6508°S, 174.5425°W Orona Algae Corner N/A Orona Dolphin Ledge N/A Rawaki Deep Water 3.7203°S, 170.7175°W

16 Table 2: Microsatellite loci analyzed

Plex Primer A 0780-vic 0905-ned 1551-pet B 2258-ned 1556-pet C 2069-pet(r2) D 1868-vic(r1) 1629-6fam 1357-pet E 1370-pet 0072-ned

17

Table 2: Samples of Porites lobata and Porites evermanni unique genets included for the PCoA analysis.

Region Reef P. evermanni P. lobata Total Clipperton Clipperton 2 0 2 Ecuador Ecuador 5 0 5 Galapagos Espanola 6 0 6 Galapagos Islands Darwin Islands 3 4 7 Galapagos Islands Marchena 0 2 2 Galapagos Islands Necker 0 1 1 Galapagos Islands Santa Cruz 26 15 41 Galapagos Islands Wolf 0 3 3 Hawaii French Frigate 0 1 1 Shoals Hawaii Gardener 0 3 3 Hawaii Hawaii 0 2 2 Hawaii Maro 0 2 2 Hawaii Molokai 3 0 3 Hawaii Oahu 0 2 2 Hawaii Pearls and Hermes 0 1 1 Johnston Johnston 0 5 5 Christmas Island 1 3 4 Marquesas Montane 0 2 2 Islands Panama Panama 4 1 5 Samoa Islands American Samoa 0 1 1 Samoa Islands Olosega 0 2 2 Total 50 50 100

18 Table 3: Analysis of variance between the islands, species, and mussel count results.

Source DF Adj SS Adj MS F-Value P-Value Species 1 0.00072 0.00072 7.05 0.009 Island 3 0.000891 0.000297 2.91 0.037 Species*Island 3 0.000868 0.000289 2.83 0.04 Error 144 0.014703 0.000102 Total 151 0.020084

19 Table 5: Porites lobata biodiversity measures. N is the number of samples. NG is the number of unique genets. NG/N is the genotypic richness. GO is the observed genotypic diversity. GO/GE is genotypic diversity. GO/NG is genotypic evenness. A incudes genotypic diversity values for both haphazard and random sampling. B only includes genotypic diversity for the random sampling values.

Site N NG NG/N GO GO/GE GO/NG AEnderbury 54 51 0.94 48.6 0.9 0.95 AKanton 33 30 0.91 26.56 0.8 0.89 ANikumaroro 12 11 0.92 10.29 0.86 0.94 AOrona 9 9 1 9 1 1 ARawaki 13 12 0.92 11.27 0.87 0.94

BEnderbury 33 31 0.94 30.25 0.92 0.98 BKanton 16 14 0.88 11.64 0.73 0.83 BNikumaroro 12 11 0.92 10.29 0.86 0.94 BOrona 9 9 1 8 1 1 BRawaki 13 12 0.92 11.27 0.87 0.94

20 Table 6: Porites evermanni biodiversity measures. N is the number of samples. NG is the number of unique genets. NG/N is the genotypic richness. GO is the observed genotypic diversity. GO/GE is genotypic diversity. GO/NG is genotypic evenness. A incudes genotypic diversity values for both haphazard and random sampling. B only includes genotypic diversity for the random sampling values.

Site N NG NG/N GO GO/GE GO/NG AEnderbury 5 5 1 5 1 1 AKanton 14 14 1 14 1 1 ANikumaroro 12 11 0.92 10.29 0.86 0.94 AOrona 40 20 0.5 7.21 0.18 0.36 ARawaki 1 1 1 1 1 1

BEnderbury 4 4 1 4 1 1 BKanton 13 13 1 13 1 1 BNikumaroro 10 9 0.9 8.33 0.83 0.93 BOrona 40 20 0.5 7.21 0.18 0.36 BRawaki 1 1 1 1 1 1

21 Appendix B

Figures

Figure 1: Map Showing Species Distribution of P. lobata and P. evermanni across the Phoenix Islands.

22

Figure 2: PCoA of clustering analysis of samples of unknown Porites species from the Phoenix Islands including reefs Enderbury (EN), Kanton (KN), Nikumaroro (NK), Orona (OR), and Rawaki (RA) with known Porites lobata and Porites evermanni from throughout the Pacific.

23

Figure 3: A comparison of average mussel density between P. lobata and P. evermanni.

24

Figure 4: Bayesian cluster analysis with STRUCTURE for Porites lobata. Panels K=2 (A), and K = 3 (B), K=4 (C). KN=Kanton, EN=Enderbury, RA=Rawaki, OR=Orona, NK=Nikumaroro. The most probable K was 3 (B) based on the mean estimated log probability of the data at a given K (3 replicate runs per K, +/- 1 standard deviation).

25

Figure 5: Bayesian cluster analysis with STRUCTURE for Porites evermanni. Panels K=2 (A), and K = 3 (B), K=4 (C). KN=Kanton, EN=Enderbury, RA=Rawaki, OR=Orona, NK=Nikumaroro. The most probable K was 3 (B) based on the mean estimated log probability of the data at a given K (3 replicate runs per K, +/- 1 standard deviation). 26

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ACADEMIC VITA

Academic Vita of Gavin Vanstone [email protected] 673 Paddock Road Havertown, PA 19083

Education Major: B.S. Biology Honors: Biology Thesis Title: The effect of a nutrient gradient on the Porites-Lithophaga system in the Phoenix Islands Thesis Supervisor: Dr. Iliana Baums

Work Experience Date: August- December 2016 Title: Volunteer Learning Assistant for Biology 230W Description: Biology 230W is a cell biology class for underclassmen majoring in biology. As a learning assistant for the class, I was responsible for attending lecture each day and leading discussions on in class worksheets and clicker questions. I was also responsible for leading one office hour session a week where I assisted students with homework, went over exams, and helped clarify topics talked about in class. Each week, I was also responsible for grading a group of student’s homework and provide feedback on that homework to help them better understand questions they may have gotten incorrect. Institution/Company: Pennsylvania State University Supervisor’s Name: Dr. Jennelle Malcos

Date: September 2014-April 2017 Title: Emergency Room Volunteer/Volunteer Trainer Description: As an emergency department volunteer at Mount Nittany Medical Center, I worked closely with the hospital staff to provide the best care to patients. My duties included patient transport, assisting with the nurses and triage, and helping restock treatment rooms. I also worked as a trainer for volunteering office, training new volunteers in the emergency department. As a volunteer trainer, I showed new volunteers around the hospital and led them through their duties as an emergency department volunteer. Institution/Company: Mount Nittany Medical Center Supervisor’s Name: Meredith Thompson

Grants Received: Eberly College of Science Undergraduate Grant

Community Service Involvement: Springfield Benefiting THON

Penn State Men’s Club Lacrosse

Penn State Legion of Blue