Population Genetics and Phylogeography of Hawaiian Coral Reef Echinoderms

ISLANDS, ARCHIPELAGOS, AND BEYOND: POPULATION GENETICS AND PHYLOGEOGRAPHY OF HAWAIIAN CORAL REEF ECHINODERMS

A DISSERTATION SUBMITTED TO THE GRADUATE DIVISION OF THE UNIVERSITY OF HAWAI‘I AT MĀNOA IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

ZOOLOGY

AUGUST 2012

Derek J. Skillings

Dissertation Committee:

Robert Toonen, Chairperson Brian Bowen Charles Birkeland Andrew Taylor Ronald Bontekoe

DEDICATION

This dissertation is dedicated to my wife, Melissa Kay Skillings.

ACKNOWLEDGEMENTS

First, I would like to thank my committee members who provided essential guidance and encouragement throughout my graduate career. Foremost, I would like to thank my advisor and committee chair Rob Toonen. He has generously offered me a near endless supply of advice and guidance, as he does for anyone who knocks on his door. He also gave me the flexibility and encouragement needed to make getting two simultaneous graduate degrees possible. My graduate career has been very unconventional, and Rob has supported me every step of the way. I would like to thank Brian Bowen for giving me the structure I needed to succeed. Given my tendency to get lost in an always increasing number of projects, I would have never finished in a reasonable amount of time without his firm hand at setting deadlines and his enthusiastic encouragement to meet those deadlines. Rob and Brian gave me the perfect balance of freedom and focus that I needed to succeed. I would like to thank Chuck Birkeland for helping me to put my work in the larger perspective of coral reef ecosystems. Chuck also encouraged my philosophical and historical investigations into biology through insightful conversation; every time I saw he seemed to have a valuable and important text that he wanted to give me for my collection, many from his personal library. I would like to thank Andy Taylor for his critical eye, for being able to see through the details to get at the heart of the problem. Andy first taught me statistics, a field that I didn’t appreciate at first, but have since come to focus on greatly because of his influence. Even though we have come to take different approaches to statistics, he has always challenged me in a way that has made my thinking clearer and has made me a better academic. Finally, I would to thank Ron Bontekoe for his dual service as a committee member for my PhD and as my advisor for my philosophy MA. His insightful questions and critical feedback have pushed my writing leaps and bounds ahead of where I thought it could be.

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Thank you to the facility, staff, and postdoctoral researchers at the Hawai‘i Institute of

Marine Biology and the University of Hawai‘i at Mānoa Zoology department. I would like to thank: Matt Iacchei, Michelle Gaither, Jon Puritz, Joseph DiBattista, Mike Stat, Zoltan Szabo,

Greg Concepcion, Kim Andrews, Marc Crepeau, Steve Karl and the rest of the extended ToBo lab for helpful discussions and support. I would especially like to thank Chris Bird, who spent many hours teaching me the skills I needed to be a successful molecular biologist. This work was made possible by the financial support of several agencies including: National Science

Foundation, Papahānaumokuākea Marine National Monument, Northwestern Hawaiian Islands

Coral Reef Reserve, University of Hawai‘i Art and Sciences Council, and the Jessie D. Kay

Fellowship.

ABSTRACT

Genetic connectivity determines the evolutionary independence of populations and plays

a primary role governing intraspecies evolution. Patterns of genetic connectivity can also be used

to make inferences about macroevolutionary processes. For my dissertation I used mtDNA

sequences in phylogeographic and population level analyses to examine connectivity within and

between Pacific Archipelagos, utilizing four species of tropical echinoderms. First, I review and

prescribe non-lethal sampling techniques for use in genetic studies of many species of marine

invertebrates. Second, I showed that two species of sea cucumber, Holothuria atra and

Holothuria whitmaei, with a similar life history, species range, and habitat usuage cannot be used

as proxies for each other in order to predict phylogeographic patterns, degree of connectivity, and

population genetic structure within the Hawaiian Archipelago. Third, I examined the genetic population structure of H. atra across the central tropical Pacific to show that despite its large range, H. atra has hierarchical, fine-scale population structure driven primarily by between-

archipelago barriers, but with significant differences between sites within an archipelago. Finally,

I compared population genetic patterns in two congeneric brittle stars, Ophiocoma pica and

Ophiocoma erinaceous, across Hawai‘i and Central and Eastern Polynesia. I found contrasting

phylogeographic patterns in these two similar species, as was the case with H. atra and H.

whitmaei. Given the real-world constraints of limited time and money in marine ecosystem management it would be ideal if model species could stand in as proxies for a host of similar species. This dissertation shows that this ideal scenario is unlikely to be the case; similar life

histories and close phylogenetic relationships do not appear to predict population connectivity.

Generalizations based on a few representative taxa are unlikely to offer much in terms of

delineating boundaries for spatial management areas. Though a more inclusive multi-species

v approach is bound to cost more in terms of time and resources, it should ultimately payout as more informed, if complex, management.

TABLE OF CONTENTS Dedication ………………………………………………………………………………… ii Acknowledgements ………………………………………………………………………... iii Abstract …………………………………………………………………………………... v List of Tables ……………………………………………………………………………... ix List of Figures ……………………………………………………………………………... x Chapter 1: Introduction …………………………………………………………………... 1 References ………………………………………………………………………... 5 Table ……………………………………………………………………………. 9 Chapter 2: It’s Just a Flesh Wound: Non-lethal Sampling for Conservation Genetics Studies……………………………………………………………………...…………... 12 Abstract …………………………………………………………………………... 13 Introduction ………………………………………………………………………... 13 Methods ...………………..………………………………………………………... 15 Discussion ………………………………………………………………………... 20 Conclusions ……………………………………………………………………….. 23 Acknowledgements ……………………………………………………………….. 23 References ………………………………………………………………………... 25 Figure ..…………………………………………………………………………...... 27 Chapter 3: Contrasting Phylogeography of Two Coral Reef Sea Cucumbers, Holothuria atra and Holothuria whitmaei ………………….…………………………………….. 28 Introduction ……………………………………………………………………... 29 Methods ……………………………………………………………………...……. 35 Results ……………………………………………………………………...……… 38 Discussion …………………………………………………………………...…… 42 Conclusions ……………………………………………………………………….. 46 References …………………………………………………………………...…… 47 Tables ……………………………………………………………………...……… 60 Figures …………...……………………………………………………...………… 65 Chapter 4: Gateways to Hawai‘i – Genetic population structure of the tropical sea cucumber Holothuria atra ……………………………………………….…………… 68

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Abstract ………………………………………………………...………………… 69 Introduction ………………………………………………………………...……… 69 Methods ……………...……………………………………………………..……. 73 Results ……………………………………………………………………………... 78 Discussion ………………………………………………………………………… 82 Conclusions ……………………………………………………………………….. 88 Acknowledgments ………………………………………………………………… 89 References ………………………………………………………………………... 91 Figures ………………………………………………………...………………… 104 Tables ………………………………………………………………………...…… 106 Appendices ………………………………………………………………………... 110 Chapter 5: Contrasting Phylogeography Patterns in Two Pacific Brittle Stars, Ophiocoma erinaceous and Ophiocoma pica …………..………………………………………...… 113 Introduction ………………………………………………………………...……… 114 Methods ……………...……………………………………………………..……. 119 Data Analysis ……………………………………………………………………... 121 Results ……………………………………………………………………………... 123 Discussion ………………………………………………………………………… 127 Conclusions ……………………………………………………………………….. 131 References ………………………………………………………………………... 132 Tables ………………………………………………………………………...…… 146 Figures ………………………………………………………...………………… 150 Chapter 6: Summary and Synthesis ………………..…………………...………………… 152 Summary ………………………………………………………………...………… 153 Synthesis ………...…...……………………………………………………..……. 155

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LIST OF TABLES

Chapter 3: Contrasting Phylogeography of Two Coral Reef Sea Cucumbers, Holothuria atra and Holothuria whitmaei

Table 3.1 Molecular diversity indices and sample sizes ………...... …………… 61

Table 3.2 Pairwise F statistic comparisons ………………………………...…...… 62

Table 3.3 Pairwise Dest_chao comparisons …………………………………………. 63

Table 3.4 AMOVAs by region ……………………………………………………. 64

Table 3.5 Pairwise population migration rate estimates …………………………... 65

Chapter 4: Gateways to Hawai‘i – Genetic population structure of the tropical sea cucumber Holothuria atra

Table 4.1 Molecular diversity indices and sample sizes ………………………… 107

Table 4.2 Pairwise Dest_chao and FST comparisons ……………………….……….. 108

Table 4.3 AMOVAs for different population groupings ……………………….… 109

Table 4.4 Pairwise population migration rate estimates ………………..………… 110

Chapter 5: Contrasting Phylogeography Patterns in Two Pacific Brittle Stars, Ophiocoma erinaceous and Ophiocoma pica

Table 5.1 Molecular diversity indices and sample sizes ………………………… 147

Table 5.2 AMOVAs by region …………………….…………………….……….. 148

Table 5.3 Pairwise Dest_chao and FST comparisons ……...……………………….… 149

Table 5.4 Pairwise population migration rate estimates ………………..………… 150

LIST OF FIGURES

Chapter 2: It’s Just a Flesh Wound: Non-lethal Sampling for Conservation Genetics Studies

Figure 1.1 Non-lethal sampling of a Crown of Thorns sea star (Acanthaster planci) without removing the animal from the substrate …………………………………… 28

Chapter 3: Contrasting Phylogeography of Two Coral Reef Sea Cucumbers, Holothuria atra and Holothuria whitmaei

Figure 3.1 Map of the Hawaiian Archipelago …..………………………………… 66

Figure 3.2 Haplotype network for Holothuria atra …………….……………….... 67

Figure 3.3 Haplotype network for Holothuria whitmaei …………….…………… 68

Chapter 4: Gateways to Hawai‘i – Genetic population structure of the tropical sea cucumber Holothuria atra

Figure 4.1 Map of Central Pacific with major barriers and migration rates………. 105

Figure 4.2 Haplotype network …………………….………….…………………… 106

Chapter 5: Contrasting Phylogeography Patterns in Two Pacific Brittle Stars, Ophiocoma erinaceous and Ophiocoma pica

Figure 5.1 Haplotype network for Ophiocoma erinaceous ……………………… 151

Figure 5.2 Haplotype network for Ophiocoma pica ………………...…………… 152

CHAPTER ONE

Introduction

Echinoderms play a major role in structuring many marine ecosystems, and many

are described as "keystone species" because of their profound influence on benthic

community structure (e.g., Paine 1969, Power et al. 1996, Lessios et al. 2001, reviewed

by Uthicke et al. 2009). In addition to their important ecosystem functions, many

echinoderm species are also the focus of artisanal or commercial fishing efforts,

particularly the sea urchins and sea cucumbers (Sloan 1984, Sala et al. 1998, Purcell

2010). The influence of echinoderm harvest on a wide range of other commercial fisheries, such as abalone, lobster, kelp and kelp-associated fin fish, has long stimulated

discussions of multispecies approaches to managing their exploitation (e.g., Sloan 1984,

reviewed by Purcell 2010). Delineation of the appropriate spatial scales for management

zones within a spatial management network requires a detailed understanding of dispersal

pathways and population connectivity (reviewed by Hedgecock et al. 2007; Thorrold et

al. 2007; Fogarty & Botsford 2007).

Understanding connectivity in the sea is complicated by the fact that many marine organisms share a biphasic life cycle typified by an adult form that is relatively sedentary and a larval form that can potentially disperse across large expanses of open ocean

(Thorson, 1950; Strathmann, 1993; Kinlan & Gaines, 2003; Kinlan et al., 2005; Paulay &

Meyer, 2006). For example, in the sea urchin genus Tripneustes some well-known biogeographic barriers, such the Isthmus of Panama or the long stretch of deep water in the western Atlantic, are important barriers to dispersal whereas others, such as the

Eastern Pacific Barrier show no evidence for limiting dispersal (Lessios et al. 2003).

However, the geographic limits of such dispersal are uncertain because it is virtually impossible with current technology to directly track these microscopic juveniles during

the pelagic phase (reviewed by Levin 2006) making indirect methods of quantifying

larval dispersal particularly attractive (reviewed by Grosberg & Cunningham 2001;

Hedgecock et al. 2007; Selkoe et al. 2009; Hellberg 2009). Proxies for dispersal, such as

pelagic larval duration (PLD) and geographic range have generally been used as rules of

thumb in the absence of a detailed understanding of connectivity for most marine species.

Unfortunately, intuitive expectations of larval dispersal potential as a function of PLD

and range size are not upheld in recent meta-analyses of the existing literature (Lester et al. 2007; Bradbury & Bentzen 2007; Bradbury et al. 2008; Weersing & Toonen 2009;

Shanks 2009; Ross et al. 2009). Realized dispersal distance is typically less than potential dispersal distance because of the presence of biophysical or biogeographical barriers (Burton & Feldman, 1981; Knowlton & Keller, 1986; Shanks et al., 2003;

Severance & Karl, 2006; Dawson & Hamner, 2008). Barriers that limit dispersal between marine populations include obvious geographical features such as land masses, i.e. the

Isthmus of Panama (Bermingham & Lessios, 1993), but also more subtle factors such as currents and oceanographic regimes (Dawson, 2001; Barber et al., 2002; Sotka et al.,

2004; Baums et al., 2006; Treml et al., 2008). The correlation between geographic distance and the probability of larval exchange among sites is low in many marine systems (e.g., White et al. 2010), and thus quantitative estimates of connectivity are an important prerequisite for delineating the appropriate scale over which marine populations ought to be managed.

In this dissertation I use genetic and statistical tools to examine marine genetic population connectivity in two echinoderm groups: the sea cucumbers (Holothuroidea)

Holothuria atra and Holothuria whitmaei, and brittle stars (Ophiuroidea) Ophiocoma

erinaceous and Ophiocoma pica. The first question I examine is whether congeners with a similar life history, species range, and habitat usuage can be used as proxies for each other in order to predict phylogeographic patterns, degree of connectivity, and population genetic structure. I investigate the usefulness of model species for predicting population structure, population connectivity, and dispersal for use in marine spatial management initiatives for the delineation of marine protected areas and for determining the appropriate scale for coral reef management.

The Hawaiian Archipelago lies at the periphery of the tropical Central Pacific and is the most isolated island chain in the world, making it biogeographically partitioned from the rest of the Pacific Islands (reviewed by Ziegler 2002). This isolation results in one of the highest proportions of endemism in the world (e.g., Briggs 1974; Kay 1980;

Grigg 1983; reviewed by Ziegler 2002; Eldredge & Evenhuis, 2003). Johnston Atoll is believed to be a stepping-stone into Hawai‘i, and simulations of larval dispersal suggest that larvae from Johnston atoll can reach French Frigate Shoals or Kaua‘i along two separate larval corridors (Kobayashi 2006; Kobayashi & Polovina 2006). The second question I examine is whether Johnston Atoll is a stepping-stone into Hawai‘i, whether it tends to be an outpost of Hawai‘i. I also elucidate the historical connectivity pathways between the Hawaiian Archipelago and Johnston Atoll.

Though there are many examples of pan-pacific coral reef organisms in Hawai‘i, the isolation of the Hawaiian Archipelago is thought to limit larval exchange sufficiently that colonization is rare (Jokiel & Martinelli 1992). For example, Kay (1984) estimated that Western Pacific marine species successfully colonize the Hawaiian Archipelago about once every 13,000 years. Unlike the terrestrial fauna, however, the Hawaiian

marine fauna contains a large proportion of endemics that are differentiated but not

diversified from their Indo-West Pacific roots (Kay & Palumbi 1987; Hourigan & Reese

1987; Jokiel 1987; Ziegler 2002). In this scenario Hawai‘i is seen primarily as a dead-

end, an isolated land-mass that does not contribute in a significant way to the overall

diversity of the tropical pacific. Counter to the island biogeography hypotheses of

Hawaiian diversity, Jokiel and Martinelli (1992) proposed the Vortex model of speciation,

wherein the stunning biodiversity of the Coral Triangle is a result of centrifugal

accumulation of species from the peripheral habitats around the Pacific. Though these

two models primarily make predictions about speciation-level processes and do not speak

directly to gene-flow within a species, they do make opposite claims about the dominant

direction of gene-flow and dispersal. The final questions I examine are whether periphery

archipelagos act as a source of genetic diversity in the Pacific, and the likely colonization

routes, into and out of, the extremely isolated Hawaiian Archipelago.

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CHAPTER TWO

It’s Just a Flesh Wound: Non-lethal Sampling for Conservation Genetics Studies

Published as:

Skillings DJ and Toonen RJ (2010) It’s Just a Flesh Wound: Non-lethal Sampling for Conservation Genetics Studies. in Diving for Science. Proceedings of the 29th American Academy of Underwater Sciences Symposium, N. W. Pollock, Ed., Proceedings of the American Academy of Underwater Sciences, AAUS, Dauphin Island, Ala, USA.

ABSTRACT

The Papahānaumokuākea Marine National Monument (PMNM) is a chain

of coral reef atolls and small basalt pinnacles, home to the most beautiful

reefs in Hawai‘i. The size, remoteness, and near “pristine” condition of

PMNM make it a unique and ideal natural laboratory for conservation and

scientific studies. Because PMNM enjoys the highest level of protection

under US law, every effort is made to minimize impacts when performing

research and collecting samples within the borders of the Monument. An

overview of underwater, non-lethal, tissue-sampling techniques is given

for a wide range of invertebrates used for genetic population studies.

Many invertebrates pose a special challenge for non-lethal sample

collecting as defensive chemical and physical structures can make

downstream genetic procedures difficult or impossible if they are not

sampled correctly.

INTRODUCTION

The Hawaiian archipelago stretches more than 2500 km, from the Big Island of

Hawai‘i at its southeast point, to Kure Atoll in the northwest. The Archipelago is commonly divided into two regions: the main Hawaiian Islands (MHI) consisting of populated, high volcanic islands and the Northwestern Hawaiian Islands (NWHI), an uninhabited chain of basalt pinnacles, atolls, shoals, and banks. Although the inhabited

MHI are about on par with reefs in other inhabited areas, partly because of their isolation, the coral reefs of the NWHI are among the healthiest and most extensive remaining in the

14 world (Pandolfi et al. 2003). The reefs of the NWHI represent a nearly undamaged coral reef ecosystems with virtually no human impacts by comparison to the heavily populated

MHI (Selkoe et al. 2009), abundant and large apex predators, and an extremely high proportion of endemic species across many taxa (DeMartini & Friedlander 2004;

Friedlander & DeMartini 2002), . The coral reefs in the MHI, by comparison, are under considerable anthropogenic pressure, reefs near many of the urban areas and popular tourist destinations show significant negative impacts (Friedlander et al. 2004; Rodgers et al. 2009).

The Papahānaumokuākea Marine National Monument (PMNM) was created to protect the nearly 140,000 square miles of the NWHI; home to more than 7,000 species of fishes, invertebrates, marine mammals, and birds. While the full extent of its biodiversity is still unknown, an average of about 27% of the known species are endemics found nowhere else on Earth (Eldredge & Evenhuis 2003). The diverse habitats found in the Papahānaumokuākea Marine National Monument present both opportunity and duty. Its size, remoteness, and near pristine condition make it a unique and ideal natural laboratory for conservation and scientific studies. As one of the last bastions of minimally impacted coral reefs we have a duty to preserve the NWHI. In order to inform ecosystem-based management of the Papahānaumokuākea Marine National Monument, understand the role of NWHI in the management of the MHI, and evaluate the potential for spillover of fisheries species from the protected area, our group has embarked on a genetic survey of reef fishes, corals, and other invertebrates. This survey is designed to address the issue of population connectivity between the Northwestern and Main

Hawaiian Islands. An extended overview of this effort and preliminary research results

can be found in Toonen et al. (2010).

In keeping with conservation ethic every effort is made to minimize impacts when

performing field research and collecting samples for laboratory analysis. This paper is an

overview of underwater, non-lethal, tissue-sampling techniques for a wide range of invertebrates used by our research group for population genetics studies. Many invertebrates pose a special challenge for non-lethal sample collecting; defensive chemicals and physical structures can make downstream procedures difficult or impossible if an appropriate sampling methodology is not followed. We present here common downstream problems and methods for navigating the line between safe, non- lethal sampling and the effective and efficient use of collecting time.

METHODS

Sampling preparation for genetic population studies starts well before getting into the field. The end needs for the study in question must be kept in mind when deciding on the appropriate sampling methodology. This is especially important for our research group because of the isolation of the NWHI. Following a roughly 6 month permit application process, any field expedition is expensive and extremely time-constrained with typically only 1 day to perform collections, and at best 4 days possible at any given site. Thus, in addition to the ethical responsibility to avoid wasting anything collected, it is also important to know exactly what is needed for the study because there may not be a second chance for getting samples. Final sampling methodology is dictated by the following questions, each addressed in turn:

What laboratory procedures will be used?

Lab methodologies for population genetics studies utilize genetic marker variability, or infer genetic variability through fragment length or electrophoretic differences, in order to understand population structure. Genetic variability is generally determined using either direct sequencing of DNA, or size-based scoring of the allele frequencies of genes or proteins. Our research group uses both direct sequencing of mitochondrial (mtDNA) and nuclear genes (nDNA), and the scoring of length variability within nDNA microsatellite markers. The required sample size for using the different types of markers is dependent on the variability both between, and within the chosen markers, and is beyond the scope of this paper (reviewed by Ruzzante 1998; Kalinowski

2005).

Sampling considerations come from three laboratory processing stages necessary for obtaining genetic information: 1) the preservation of the DNA molecules within the whole tissue; 2) the clean extraction in order to isolate molecules of interest; and 3) the amplification of target genetic material. Details for these procedures can be found in

Iacchei and Toonen (2010). The quality of the final product depends largely on type of tissue that is used in the initial extraction. Most extraction procedures are optimized for vertebrate skin, muscle or blood. Invertebrate muscle or epithelial tissue is likewise usually suitable for DNA extraction, depending on the organism in question. Protein extraction may call for specific tissues that have a higher concentration of the protein of interest, and requires fresh tissue or specialized storage conditions (-80ºC).

How much tissue is needed?

Most DNA extraction protocols call for only a few milligrams of tissue per

extraction. Generally the smaller the amount of tissue that is biopsied the greater the

chances are for a quick recovery for the organism, but this is also a trade-off in that very tiny biopsies do not leave a tissue backup for re-extraction if the first sample is lost or contaminated. Thus, it is almost always a good idea to take moretissue than is needed for a single laboratory procedure. A biopsy of 50-500 milligrams of tissue generally allows a reserve to be stored in the case of failed extractions, lost product, multiple analyses, or for an independent extraction should the results need secondary confirmation.

Small tissue biopsies can also make it very difficult or impossible to correctly match a tissue sample to the species from which it was taken at any point down-stream.

This easily overlooked consequence of tissue biopsy sampling can completely derail a research project. Larger tissue samples or samples with important identifying features can help for later identification. Regardless, good field photos, notes, and proper labeling of all tissue are essential and can mitigate this risk almost entirely.

A greater amount of tissue is needed for protein extraction than is needed for

DNA extraction; the total amount of tissue needed will depend on the concentration of the protein in the tissue. Preliminary preservation and extraction tests should be run prior to field expeditions, especially for marine invertebrates which frequently show taxon- specific difficulties for preservation, extraction or DNA amplification (reviewed by

Dawson et al. 1998; Gaither et al. in review). Other considerations include whether the tissue will be shared across multiple labs, if multiple types of analyses will done using the

tissue and if so, how much tissue will be needed for each analysis. Any of these factors

will increase the amount of tissue that will be needed.

What type of tissue is needed?

The type of tissue needed will depend on both the desired end product and the

organism in question. The tissue needed for protein extraction will depend on the type of

protein that is targeted. If DNA is the target then cellular tissue is required generally in

the form of epithelial, muscular, visceral, or reproductive tissue. Structural, skeletal, and

connective tissues rarely contain enough DNA or protein to work with easily. Although it

has been done successfully with special effort, coral skeletons, crustacean

exoskeletons/molts, molluscan shells, and echinoderm tests or spines are not ideal

samples for subsequent genetic analyses.

Many invertebrates also have defensive chemicals that can interfere with the

amplification or sequencing of DNA. These chemicals can be concentrated in tissues or

diffuse throughout the body. The tissue selected for biopsy will then depend on whether

the tissue contains compounds that interfere with downstream procedures and whether

the interference can be removed or mitigated.

Can the study organism be non-lethally sampled?

The amount and type of tissue needed for molecular procedures, taken together

with the idiosyncrasies of the target organism, will determine if non-lethal sampling is

viable. Tiny organisms are more difficult to sample non-lethally as the amount of tissue that is needed might be immediately lethal or significantly decrease the survival rate post- biopsy. Molting, regenerating, or colonial organisms are prime candidates for non-lethal

sampling because they can usually recover quickly from biopsy injuries. Segmented

organisms might also be good candidate if there are replicates of the body part chosen for

sampling or the natural defense strategy of the organism includes autotomy (self

amputation). Finally, the ability to successfully capture, biopsy, and safely release the

organism in a reasonable timeframe will also determine if non-lethal sampling is possible. For example, this last factor is one of the key reasons why small reef fishes are difficult to sample non-lethally.

How will the tissue be preserved?

After the size and location of tissue biopsy is decided, the method of tissue

preservation must be determined. Two of the more common preservatives for genetic

studies are dimethyl sulfoxide (DMSO) salt-saturated buffer (Seutin et al. 1991) and

>70% ethanol (EtOH). Although specimen collection is time consuming and expensive, few laboratories test preservation methods for tissues before setting out on field expeditions. Particularly for marine invertebrates, there are substantial differences among taxa in the efficacy of tissue preservation among methods, and species-specific

differences indicate that preservation comparisons should be undertaken for any long-

term storage of samples destined for PCR study (Dawson et al. 1998; Gaither et al. in

review). In general, DMSO is non-flammable and makes a good preservative for samples

that require shipping or denser tissue; soft tissues can be broken down into a thick,

mucous-like texture, making tissue handling difficult. Ethanol dehydrates tissue, often

hardening it in the process, making it good for soft tissues that must be manipulated

downstream. Ethanol is flammable, however, so samples preserved in EtOH require

special storage, and shipping samples stored in ethanol can be difficult. Protein analyses

usually require deep-frozen (-80ºC) tissue that has not been chemically preserved; this

fact alone makes studies focusing on proteins impractical in many tropical locations,

especially when sampling takes place in remote locations.

DISCUSSION

Marine organisms comprise an extremely diverse category for study, and each

new group presents new challenges. Our research group has experience with about 1/3 of

marine phyla, but this represents only small fractionof the multitude of marine species.

Despite this we have found some general rules-of-thumb that have been helpful when starting work on new organisms.

Sponges and Corals

Sponges and corals are colonial organisms that quickly regenerate damaged tissue and are straightforward to sample non-lethally. Sponges are totipotent and contain equivalent tissue throughout whereas corals are usually comprised of thin tissue covering a dense skeletal structure unsuitable for genetic study. Care must be taken so that the colony attachment point to the substrate is not damaged. Most of the downstream problems involving sponges come from skeletal elements and the myriad array of defensive chemicals that interfere with DNA extraction and amplification. Additionally, we have found that EtOH preservation of both corals and sponges yields poor quality

DNA relative to DMSO (Gaither et al. in review). Troubleshooting generally involves extended cycles of cleaning the DNA or diluting the extraction solution to a point where inhibition drops off but there is still enough template DNA for amplification.

Downstream problems for corals include extreme amounts of mucous production and similar interference from defensive chemicals or metabolites (Concepcion et al. 2006).

Crustaceans

All crustaceans are segmented with articulated joints, and most use autotomy as a defensive mechanism of self-amputation to escape predators. Likewise, most shed their exoskeletons multiple times throughout their lifetimes, and have the ability to completely regenerate lost limbs. Many small crustaceans are difficult to identify to species in the field, and are too small to effectively sample non-lethally. Larger benthic crustaceans such as lobsters, crabs, and shrimp can be often be hand-caught, and many will drop a limb for distraction in the effort to escape capture. This makes sample-collecting easier because the whole organism need not be captured. Even for those who do not autotomize a limb, once caught, a leg joint can be clipped and will often regenerate within a single molt cycle. The sampling goal is obtain muscular tissue and not the strong, chitinous exoskeleton. We often come across empty exoskeletons, or molts, that have been shed in the growing process. Though DNA can occasionally be salvaged from these molts it takes special effort, and is not a preferred sampling strategy. Muscle tissue from a live specimen is the ideal tissue sample.

Echinoderms

Echinoderms are a very diverse group with both physical and chemical defenses to be overcome in the post-sampling analyses. Most echinoderms are capable of extensive regeneration. In the case of urchins and sea cucumbers, most regenerate quickly so long as the body cavity is not exposed and damaged, and in the case of brittle stars and

sea stars, most regenerate quickly so long as the oral disk is left intact. Many sea cumbers

also have defensive chemicals in their skin that interfere with DNA extraction and/or

amplification so it is important to get muscle tissue from the body wall when biopsying.

Care must be taken to not puncture the muscular body wall completely, which will

expose the viscera and frequently result in death via infection or predation as a result.

Whole arms or individual tube feet can be taken in the case of sea stars or brittle stars

(Figure 1). Urchins can be difficult to sample non-lethally, because most of the exposed portion of an urchin is skeletal material which does not contain much tissue. One strategy for urchins that can be picked up is to place them on a hard, clean surface until they attach themselves with their tube feet. They can then be quickly pulled away from the surface; this usually leaves behind a few tube feet which can be collected for subsequent

DNA analyses. Alternatively, urchins with large spines will have muscle tissue and skin at the base attachment point which can be taken after pulling or twisting out spines. It is important to not puncture the test while removing spines or tube feet; this will usually kill the urchin because in our experience damaged urchins on a reef usually suffer predation before the diver reaches the surface.

Molluscs

By comparison to the groups above, most molluscs are fleshy and either slowly regenerating or non-regenerating. Biopsies can create permanent damage but if care is taken the damage can be repaired or very minor. For example, seemingly healthy individuals are seen in the field with old wounds from predators that are far more extreme than damage done by tissue biopsy. Thus small, non-lethal tissue sampling is possible,

and pieces of mantle, foot, or in the case of cephalopods, arm tips are preferred.

CONCLUSIONS

Studies of genetic population connectivity are important for the successful

management and conservation of coral reefs (see Toonen et al. 2010). When performing a

study aimed at conservation and management, we believe every effort should be made to

minimize impacts on the natural resource we are studying. In the case of molecular

genetic studies, the tiny tissue sample needed for research makes non-lethal sampling possible for many species. In order for any study to be successful, it is important to plan sampling methodology and preservation method ahead of time, especially when considering the expense associated with field research across a large and remote geographical area. In the case of remote locations such as the National Monuments in the

Pacific, field expeditions are often one-time opportunities within the career of a graduate student. Thus, knowing the physical and chemical characteristics of target organisms is important to minimize the impact of collections and the chance of insurmountable problems with downstream laboratory procedures while simultaneously maximizing the scientific return on the time and financial investment in the research.

ACKNOWLEDGEMENTS

We thank the Papahānaumokuākea Marine National Monument, US Fish and

Wildlife Services, and Hawai‘i Division of Aquatic Resources (DAR) for coordinating research activities and permitting, and the National Oceanic and Atmospheric

Administration (NOAA) research vessel Hi‘ialakai and her crew for years of outstanding service and support. Special thanks go to the members of the ToBo Lab, UH Dive

Program, NMFS, PIFSC, CRED, A. Wilhelm, R. Kosaki, H. Johnson, M. Pai, D. Carter,

C. Kane, S. Karl, C. Meyer, S. Godwin, D. Minton, P. Reath, J. Zardus, D. Croswell, K.

Holland, M. Stat, X. Pochon, R. Gates, M. Rivera, E. Brown, M. Ramsay, J. Maragos, B.

Walsh, B. Carmen, I. Williams, S. Cotton, T. Montgomery, S. Pooley, M. Seki, E.

DeMartini, J. Polovina, B. Humphreys, D. Kobayashi, F. Parrish, B. Moffit, G. DiNardo,

J. O’Malley, R. Brainard, M. Timmers, J. Kenyon, S. Daley, M. Crepeau, K. Schultz, M.

Duarte, H. Kawelo, T. Daly-Engel, L. Sorenson, L. Basch, A. Alexander, M. Craig, L.

Rocha, C. Musberger, D. White, M. Gaither, G. Conception, Y. Papastamatiou, M.

Crepeau, Z. Szabo, and the HIMB EPSCoR Core genetics Facility.

This work was funded in part by grants from the National Science Foundation

(DEB#99-75287, OCE#04-54873, OCE#06-23678, OCE#09-29031), National Marine

Sanctuaries NWHICRER-HIMB partnership (MOA-2005-008/6882), University of

Hawai‘i Sea Grant College Program, National Park Service PICRP, National Marine

Fisheries Service, Western Pacific Regional Fishery Management Council, NOAA's

Coral Reef Conservation Program, the Hawai‘i Coral Reef Initiative, NSF EPSCoR, EPA

STAR Fellowship, the Watson T. Yoshimoto Foundation, the Jessie D. Kay Memorial

Fellowship, PADI Foundation Research Grant, Charles and Margaret Edmondson

Research Fund, American Malacological Society Student Award, Conchologists of

America Research Grant, Sigma Xi Grants-in-Aid, Society for Integrative and

Comparative Biology Student Award, Western Society of Malacologists Student Award, and the Ecology, Evolution, and Conservation Biology (EECB) NSF GK-12 fellowships.

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Figure 1.1 Non-lethal sampling of a Crown of Thorns sea star (Acanthaster planci) without removing the animal from the substrate. Roughly 1cm is cut off the tip of an arm

in situ to minimize impact to the animal.

CHAPTER THREE

Contrasting Phylogeography of Two Coral Reef Sea Cucumbers, Holothuria atra and

Holothuria whitmaei

INTRODUCTION

Coral reef ecosystems are in peril, some estimates predict that as much as 70% of

the world’s reefs will be gone by 2050 (Wilkinson 2000) or undergo a major shift from

coral-dominated to algal-dominated environments (Pandolfi et al. 2005). The primary

threats to marine ecosystems include overfishing, destructive fishing, pollution, coastal

development and climate change (McCleod and Leslie 2009). In order to help protect

community-wide coral reef biodiversity and the associated ecosystem services it provides

against this host of threats, marine protected areas (MPAs) have been, and are continuing

to be, established worldwide (McCleod and Leslie 2009). Successful spatial management

requires a complex system of zones, each of which seeks to match exploitation to

differences in biological productivity, population levels and socio-economic payoffs

(Sanchirico & Wilen 2005). Delineation of the appropriate spatial scales for management

zones within a spatial management network requires a detailed understanding of dispersal

pathways and population connectivity (reviewed by Hedgecock et al. 2007; Thorrold et

al. 2007; Fogarty & Botsford 2007).

Understanding connectivity in the sea is complicated by the fact that many marine organisms share a biphasic life cycle in which benthic or sedentary adults reproduce through an oceanic phase (eggs and/or larvae), which may be pelagic for as little as a few minutes to in excess of a year depending on the species. Following the pelagic development phase, these larvae settle onto a reef where they may remain through their entire lives, and in cases of sessile organisms, such as corals, the act of settlement includes permanent attachment to a single site. Thus, long distance dispersal is accomplished almost exclusively during the pelagic larval phase, which can potentially

disperse across large expanses of open ocean (Thorson, 1950; Strathmann, 1993; Kinlan

& Gaines, 2003; Kinlan et al., 2005; Lessios & Robertson 2006; Paulay & Meyer, 2006;

Dawson & Hamner 2008). For example, in the sea urchin genus Tripneustes some well-

known biogeographic barriers, such the Isthmus of Panama or the long stretch of deep

water in the western Atlantic, are important barriers to dispersal whereas others, such as

the Eastern Pacific Barrier show no evidence for limiting dispersal (Lessios et al. 2003).

However, the geographic limits of such dispersal are uncertain because it is virtually

impossible to track these microscopic juveniles during the pelagic phase (reviewed by

Levin 2006) making indirect methods of quantifying larval dispersal particularly

attractive (reviewed by Grosberg & Cunningham 2001; Hedgecock et al. 2007; Selkoe et

al. 2009; Hellberg 2009).

Proxies for dispersal, such as pelagic larval duration (PLD) and geographic range

have generally been used as rules of thumb in the absence of a detailed understanding of

connectivity for most marine species. However, intuitive expectations of larval dispersal

potential as a function of PLD are not upheld in detailed meta-analyses of the existing literature (Lester et al. 2007; Bradbury & Bentzen 2007; Bradbury et al. 2008; Weersing

& Toonen 2009; Shanks 2009; Ross et al. 2009). Realized dispersal distance is typically less than potential dispersal distance because of the presence of biophysical or biogeographical barriers (Burton & Feldman, 1981; Knowlton & Keller, 1986; Shanks et al., 2003; Severance & Karl, 2006; Dawson & Hamner, 2008). Barriers that limit dispersal between marine populations include obvious geographical features such as land masses, i.e. the Isthmus of Panama (Bermingham & Lessios, 1993), but also more subtle factors such as currents and oceanographic regimes (Dawson, 2001; Barber et al., 2002;

Sotka et al., 2004; Baums et al., 2006; Treml et al., 2008). The correlation between geographic distance and the probability of larval exchange among sites is low in many marine systems (e.g., White et al. 2010), and thus quantitative estimates of connectivity are an important prerequisite for delineating the appropriate scale over which marine populations ought to be managed.

The Hawaiian archipelago stretches more than 2500 km in length, and consists of two regions: the main Hawaiian Islands (MHI) which are populated, high volcanic islands; and the Northwestern Hawaiian Islands (NWHI) which are an uninhabited string of low islands, atolls, shoals, and banks. Thanks to their isolation, the roughly 4,500 square miles of wild coral reefs found throughout the NWHI are among the healthiest and most extensive remaining in the world (Pandolfi et al. 2003). The reefs of the NWHI represent almost undamaged coral reef ecosystems with abundant and large apex predators and an extremely high proportion of endemic species across many taxa

(DeMartini and Friedlander 2004; Friedlander and DeMartini 2002), and few human impacts compared to the heavily populated MHI (Selkoe et al. 2009). In contrast, coral reefs in the MHI are under considerable anthropogenic pressure from 1.29 million residents (with over 900,000 of those living on the island of Oahu) and more than 7 million tourists visiting the state each year. Coral reefs in many of the urban areas and popular tourist destinations have significant impacts and many show ongoing declines

(Friedlander et al. 2005; Rodgers et al. 2009). The primary anthropogenic impacts to coral reefs in the MHI include coastal development and land-based sources of pollution, overfishing, recreational overuse, and alien species, whereas in the NWHI global impacts

such as climate change, ocean acidification and marine debris are the primary stressors

(Friedlander et al. 2005; Rodgers et al. 2009; Selkoe et al. 2009).

The Hawaiian Archipelago also lies at the periphery of the tropical Central Pacific

and is the most isolated island chain in the world, making it biogeographically partitioned from the rest of the Pacific Islands (reviewed by Ziegler 2002). This isolation results in one of the highest proportions of endemism in the world (e.g., Briggs 1974; Kay 1980;

Grigg 1983; reviewed by Ziegler 2002; Eldredge & Evenhuis, 2003). Though there are many examples of pan-pacific coral reef organisms in Hawai‘i, the isolation of the

Hawaiian Archipelago is thought to limit larval exchange sufficiently that colonization is rare (Jokiel & Martinelli 1992). For example, Kay (1984) estimated that Western Pacific marine species successfully colonize the Hawaiian Archipelago about once every 13,000 years. Unlike the terrestrial fauna, however, the Hawaiian marine fauna contains a large proportion of endemics that are differentiated but not diversified from their Indo-West

Pacific roots (Kay & Palumbi 1987; Hourigan & Reese 1987; Jokiel 1987; Ziegler 2002).

Johnston Atoll is believed to be a stepping-stone into Hawai‘i, and simulations of larval dispersal suggest that larvae from Johnston atoll can reach French Frigate Shoals or

Kaua‘i along two hypothetical dispersal corridors (Kobayashi 2006; Kobayashi &

Polovina 2006).

Delineation of management units is further complicated by the fact that single- species studies are frequently contradictory in their recommendations for management.

Analyses of connectivity frequently focus on single species exemplars which are then extrapolated to the level of the community, but the utility of exemplars in such cases is limited; even among closely-related taxa with similar life history, ecology and geographic

33 ranges, patterns of connectivity can be highly different (Rocha et al. 2002; Bird et al.

2007). In other cases, animals with highly divergent life history, ecology and geographic range (California spiny lobster, Kellet’s whelk & Kelp bass) can have surprisingly similar patterns of connectivity within the Southern California Bight (Selkoe et al. 2010). Such variability among species appears to be the rule rather than the exception, and has led to a call for explicit multi-species comparisons of connectivity across all trophic levels to broadly define the boundaries for management and determine shared borders to exchange among ecosystems. However, few such studies exist (Kelly & Palumbi 2010, Carpenter et al. 2011). The Hawaiian Archipelago makes an ideal system for a case study to determine areas of shared barriers to gene flow across many species at a variety of trophic levels to inform ecosystem-based management.

Echinoderms play a major role in structuring many marine ecosystems, and many are described as "keystone species" because of their profound influence on benthic community structure (e.g., Paine 1969, Power et al. 1996, Lessios et al. 2001, reviewed by Uthicke et al. 2009). In addition to their important ecosystem functions, many echinoderm species are also the focus of artisanal or commercial fishing efforts, particularly the sea urchins and sea cucumbers (Conand 1990; Sloan 1984, Sala et al.

1998, Purcell 2010). Stocks of the most valuable species are severely depleted throughout the Pacific with fishers continually moving to more remote locations and less valuable species (Conand 1990; Conand and Byrne 1993; Conand 1998, 2001; D’Silva 2001;

Buckner et al. 2003; Lovatelli et al. 2004; Uthicke 2004). The influence of echinoderm harvest on a wide range of other commercial fisheries, such as abalone, lobster, kelp and

34 kelp-associated fin fish, has long stimulated discussions of multispecies approaches to managing their exploitation (e.g., Sloan 1984, reviewed by Purcell 2010).

The lollyfish, Holothuria atra, and the black teatfish, Holothuria whitmaei, are two common shallow-water tropical sea cucumbers in the Indo-Pacific that extend to the

Hawaiian Archipelago, where they are locally known as loli (Clark and Rowe 1971;

Uthicke 2001; Uthicke et al. 2003; Conand 1994). Both species perform vital ecosystem services on coral reefs and they support an active fishery in many regions of the Pacific

(Bonham & Held 1963; Uthicke 1999; Purcell 2010). There has been a considerable amount of confusion regarding the names and identification of these Indo-Pacific teatfish

(reviewed by Uthicke et al. 2004). Black, white, and mottled teatfish were all included in the original description of Mülleria (= Holothuria) nobilis (Selenka, 1867). A black teatfish from Samoa was described as Holothuria whitmaei by Bell (1887) because he did not compare it to Selenka’s original description. Cherbonnier (1980) listed the mottled teatfish as a new distinct species, Holothuria fuscogilva, and treated the sympatric black specimens as H. nobilis. Rowe and Gates (1995) realized that the black and white H. nobilis specimens were separate species and the name H. nobilis was assigned to the white specimens and H. whitmaei was assigned to the black specimens. This confusion has led to many authors using H. nobilis for the black H. whitmaei (Uthicke and Benzie

2000, 2003). Uthicke et al. (2004) confirmed with genetic markers and a morphological study that the all-black teatfish is a distinct species and appropriately named H. whitmaei.

Echinoderms are described as a boom-bust phylum in which populations go through natural fluctuations in abundance (Uthicke et al. 2009), an attribute that can compound problems in a harvested population, but may hasten repopulation in previously

impacted areas. Holothurians are particularly susceptible to overexploitation because of their limited mobility, late maturity, density-dependent reproduction and average low rates of recruitment (Uthicke and Benzie 2000; Uthicke 2004; Uthicke et al. 2004). As such, there is a call for the management of sea cucumber harvests (Purcell 2010).

Furthermore, the boom-bust nature of echinoderms has important implications for connectivity in evolutionary time-frames where biological attributes can drive population structure to a greater extent than oceanographic processes as hypothesized in the

Tripneustes sea urchins (Lessios et al. 2003). Together these characteristics make H. atra and H. whitmaei ideal organisms to examine levels of connectivity and historical population dynamics to inform management and to test hypotheses about population connectivity within Hawai‘i connection and between Hawai‘i and its closest neighbor

Johnston Atoll. Here, we compare the mitochondrial genetic population structure of the congeners H. atra and H. whitmaei within Hawai‘i in an attempt to delineate the appropriate scales for management.

METHODS

Sampling, PCR, and Sequencing

Holothuria atra and Holothuria whitmaei were sampled from eleven sites on ten islands within the Hawaiian Archipelago and one site from Johnston Atoll, though both species were not found at every locality (fig. 3.1). Sampling in the Northwest Hawaiian

Islands took place within the Papahānaumokuākea Marine National Monument on research cruises aboard the NOAA R.V. Hi`ialakai. All other samples were collected on shore dives or while snorkeling. Sampling took place between spring 2006 and fall 2009.

Samples were obtained non-lethally through muscle-tissue biopsy and preserved in either

95% ethanol or DMSO-saturated salt buffer, and archived at the Hawai‘i Institute of

Marine Biology at room temperature. Skillings and Toonen (2010) contains an extended discussion of sampling and preservation protocol. No asexual morphs of H. atra --

distinguished by transverse scarring, smaller body size, and their location in lagoonal

habitats -- were found during sampling expeditions and no reports indicate the presence

of the asexual stage in the sampled locations. The asexual morph of H. atra appears to be

located only in the Southern and West Pacific (e.g., Ebert 1983; Conand 1994; Lee et al.,

2008). Asexual forms of H. whitmaei are not reported in the literature. Sample sizes and

locations are provided in Table 3.1

Total genomic DNA was extracted using DNeasy™ Blood and Tissue Kits

(QIAGEN) following the manufacturer’s instructions. Polymerase chain reaction (PCR)

was used to amplify a fragment of the mitochondrial cytochrome c oxidase subunit I gene

(COI) using custom primers created with Primer3 (Rozen & Skaletsky, 2000) targeting

Holothuria spp. : GenHol2L (5’- AACCAAATGGTTCTTGCTTACC -3’) and GenHol2R

(5’TTCTGATTAATCCCACCATCC -3’) (Skillings et al. 2011). The resolved fragment

was 423 base pairs long in H. atra and 446 base pairs in H. whitmaei. PCR was

performed using 15 µL reactions containing 1 µL of diluted DNA extract (one part

genomic extraction to 199 parts nanopure water), 1 µL each of 0.2 µM forward and

reverse primers, 0.6 µL of 0.5 µM BSA, 7.5 µL of Bioline (Bioline) Biomix Red diluted

as per manufacturer’s instructions, and 3.9 µL of nanopure water. PCR was done on Bio-

Rad Icycler™ thermocyclers (Bio-Rad Laboratories) with an initial denaturation at 95°C

for 7 min followed by 35 cycles of a denaturing step at 95°C for 1 min, annealing at 50°C

for 1 min, extension at 72°C for 1 min. A final extension at 72°C was held for 7 minutes.

PCR product (8 µL) was treated with 0.7 µL of Exonuclease I combined with 0.7 µL of

calf intestinal alkaline phosphatase (Exo-CIAP) and incubated at 37°C for 30 minutes

and with a final inactivation step at 85°C for 10 minutes. The treated PCR product was

sequenced using an ABI Prism 3730 automatic sequencer at the Hawai‘i Institute of

Marine Biology’s EPSCoR sequencing facility. All samples were sequenced in the

forward direction; uncertain sequences were also sequenced in the reverse direction for

confirmation. Sequences were compiled and trimmed using Sequencher 4.8 and aligned

using ClustalW implemented in Bioedit 7.0.5 (Thompson et al., 1994; Hall, 1999).

Data Analysis

Statistical parsimony networks of mitochondrial haplotypes were constructed by

creating median joining networks implemented in Network 4.610 (www.fluxus-

engineering.com; Bandelt et al., 1995; Bandelt et al., 1999). Networks were drawn using

Network Publisher 1.3.0.0 (www.fluxus-engineering.com).

Nei’s average pairwise genetic difference (π) (Nei & Li, 1979), haplotype diversity (h), Tajima’s D (Tajima, 1989), and Fu’s FS (Fu, 1997) were calculated in

DnaSP 4.1 (Rozas, 2003). The effective number of alleles (1/(1-h)) was calculated by hand following Jost (2008).

To assess levels of genetic differentiation between sites we calculated pairwise

FST and ΦST values using Arlequin 3.1 (Excoffier et al., 2005). Pairwise Dest_chao values

(Jost 2008) were calculated using SPADE (Chao, A. and Shen, T.-J. (2010) Program

SPADE (Species Prediction And Diversity Estimation Program and User’s Guide

published at http://chao.stat.nthu.edu.tw). ΦST is a fixation index incorporating genetic

distance that ranges from 0-1, where a zero indicates identical haplotypic composition

and a one signifies alternate fixation of alleles and a complete lack of gene flow. Dest_chao

is an index of genetic dissimilarity which does not account for genetic distance among

haplotypes, but also ranges from 0-1 (note that both ΦST and Dest_chao can be slightly

negative due to bias correction for sampling error). In the case of Dest_chao, a zero also

indicates identical haplotypic composition, but unlike ΦST, a one simply indicates that no haplotypes are shared between the populations. The primary difference in interpretation is that in the absence of gene flow ΦST values can be significantly less than one, while

this is not the case for Dest_chao, which is argued to be an advantage of this latter statistic

(Jost, 2008). The Morisita index of dissimilarity was calculated to measure overall

similarity between all sites (Chao 2008).

To correct the critical P value for statistical significance in pairwise comparisons, the family-wise false discovery rate (FDR) correction of (Benjamini et al., 2006) was

implemented. Analysis of molecular variance (AMOVA) was used for hierarchical

analysis of the partitioning of COI diversity among sites within archipelagic regions and

among archipelagic regions using Arlequin 3.1. The pairwise ΦST and AMOVA analyses were conducted using a distance matrix with 50,000 permutations and the Tamura-Nei mutational model (Tamura & Nei, 1993) with gamma = 0.0164. The mutational model

HKY+G was selected using AIC in Modeltest 3.7; the model hierarchy was used to select the closest available model when the best-fit model could not be implemented by the chosen program, as in the case of ARLEQUIN (Posada & Crandall, 1998). The inferences are robust to the mutational model and our conclusions are not altered regardless of

which model is chosen (data not shown). The transition-to-transversion ratio was

calculated using Modeltest.

RESULTS

Holothuria atra

A total of 252 individuals were sampled in this study. We observed 32 haplotypes,

of which 22 were private with 20 of them occurring in single individuals. Due to low

sample size, Niihau (n=5) and Gardner Pinnacles (n=2) were excluded from all between

site population analyses. The number of individuals (N), number of haplotypes (H),

number of unique haplotypes at site (Hu), nucleotide diversity averaged over sequence length (π), haplotype diversity (h), and effective number of alleles (AE) are presented in

the upper half of Table 3.1. Overall nucleotide diversity was relatively low (π = 0.0087 ±

0.0004) while the corresponding haplotype diversity was high (h = 0.88 ± 0.01).

Nucleotide diversity across all sites ranged from π = 0.0033 at Kauai to π = 0.0131 at

Johnston Atoll. Haplotype diversity ranged from h = 0.75 at Kauai to h = 0.89 at Laysan,

excluding Niihau because of low sample. There were no haplotypes shared across all

sites.

None of the site-by-site Tajima’s D values were significant, and only Laysan

deviated from expectation using Fu’s Fs; thus, there is no evidence to indicate that non- neutral processes are responsible for the pattern of COI haplotype diversity presented here.

Two Analysis of MOlecular VAriance were run on the H. atra COI haplotype data

(Table 3.4). Previous studies have shown significant population differentiation between

40 islands in the Northwest Hawaiian Islands and the Main Hawaiian Islands in multiple species (Toonen et al. 2011). We clustered sites into these two general regions, as well as pulling out Johnston Atoll as a separate region - because it lies outside of the Hawaiian

Archipelago - in order to test subdivision using AMOVAs. The two AMOVAs differed in the measure used to determine genetic diversity; FST, or strict haplotype counts, and ΦST, which incorporates genetic distance between haplotypes. Both measures displayed a similar partitioning of among-population-within-region variance, but the among-group partitioning of variance is over twice as high when measured using ΦST. Overall, all tests were significant (P < 0.0001), indicating significant genetic partitioning between regions.

Overall FST = 0.090 (P < 0.0001). Overall ΦST = 0.165 (P < 0.0001). The Morisita dissimilarity was 0.439 +/- 0.042. Pairwise comparisons between sites showed agreement between FST and ΦST measures (Table 3.3). In the Main Hawaiian Islands (MHI), O‘ahu and Kaua‘i are both significantly different from the Kona site on the Island of Hawai‘i.

These two sites were also significantly different than all other sites except Laysan Island.

There was little structure within the Northwestern Hawaiian Islands (NWHI), only

Laysan is significantly partitioned from the other sampling sites, with differentiation between the other sites within the NWHI and Johnston Atoll, but not significantly differentiated from sites within the MHI. Though outside the Hawiian Archipelago,

Johnston Atoll only showed significant differentiation from Laysan, Kauai and Oahu.

Holothuria whitmaei

We observed 27 haplotypes in 273 individuals, of which 15 were private and 15 occurring in single individuals. Due to low sample size, Lisianski (n=2) and Gardner

Pinnacles (n=1) were excluded from population analyses. The number of individuals (N), number of haplotypes (H), number of unique haplotypes at site (Hu), nucleotide diversity

averaged over sequence length (π), haplotype diversity (h), and effective number of

alleles (AE) are presented in the lower half Table 3.1. Overall nucleotide diversity was

relatively low (π = 0.0067 ± 0.0013) while the corresponding haplotype diversity was

relatively high (h = 0.83 ± 0.01). Nucleotide diversity ranged from π = 0.0036 at Nihoa to

π = 0.0251 at Midway. Haplotype diversity ranged from h = 0.52 at Nihoa to h = 0.90 at

Midway. There was one haplotype present at all sites and two haplotypes detected at all

sites except Gardner, Lisianski and Nihoa; three sites when combined had n = 13 with 3

haplotypes.

Tests for neutrality, Tajima’s D and Fu’s FS, are presented in Table 3.1. Midway

was the only site showing a significant Fu’s FS statistic, indicating an excess of low- frequency haplotypes, suggesting either selection or a recent demographic expansion

(Gaither, 2010). Pearl and Hermes deviated from expectation in Tajima’s D test, indicating the genetic distance between haplotypes is greater than expected, also indicating selection or recent demographic expansion. Tajima’s D and Fu’s FS were both

significant for the overall diversity.

Two AMOVAs were also run on the H. whitmaei COI haplotype data with

regional groupings identical to those of the H. atra analysis (Table 3.4). Almost all of the

variance was explained by within-population variance for both genetic measures. The

AMOVA using FST shows a small but significant amount of among-population within-

group variance.

Overall FST was 0.01704 (P = 0.00782). Overall ΦST was -0.00635 (P = 0.65103).

The Morisita dissimilarity index (Chao 2008), or nearly unbiased estimation of haplotypic differentiation, was 0.190 +/- 0.059. The only significant pairwise comparisons were between Nihoa and all other sites except for Kure and Kona, and only with FST (Table 3.3).

DISCUSSION

Holothuria atra and Holothuria whitmaei are the most ubiquitous sea cucumbers on Hawai‘i’s coral reefs, sharing a wide range across the central and Indo-Pacific, with

similar life histories. In this survey of genetic connectivity within the Hawaiian

Archipelago and Johnston Atoll, we were interested in any phylogeographic similarities

between these species that could be used for evaluating or planning marine management

actions. Studies have shown that a single representative or model species is seldom useful

as a proxy for estimating dispersal among marine communities, even in closely related

groups such as the endemic, sympatric, Hawaiian limpets, (Bird et al. 2007; Toonen et al.

2011). Would surveying one species give us the proper foundations for the management

of a group of wide-ranging fisheries animals? With distinct differences in population

structure, the loli, like the opihi, say ‘no’.

Biogeography and range size

If a large species range is a consequence of high dispersal potential, then both H.

atra and H. whitmaei should have little pronounced population structure, especially

across small scales (Thorson 1950; Gilman 2006; Paulay & Meyer 2006). Indeed, this is

the case for many species in the central West Pacific (Lessios et al., 2003; Craig et al.,

2007; Schultz et al., 2007; Eble et al., 2010; Gaither et al., 2010). Despite a species range

which stretches from the Western Red Sea to the eastern Central Pacific we found a

significant restriction on dispersal in H. atra. H. whitmaei, on the other hand, showed

almost no significant population structure despite a more restricted species range. This

pattern is consistent with population genetic survey of H. whitmaei on the Great Barrier

Reef and the Australasian Region, which found structure between regions, but not within

regions (Uthicke and Benzie 2003). These contrasting patterns highlight the dangers of

making predictions about population connectivity and diversity based solely on the

location and size of a species’ range.

The larval life history of H. atra and H. whitmaei are almost unknown, but they

require at least 18-25 days to reach competency to settle, and are capable of traversing

long oceanic distances with sufficient frequency to maintain species cohesion across a

very broad geographic range (Martinez and Richmond 1998; Laxminarayana, 2005).

Counter to intuition, the geographic distance among sites is a poor predictor of the ease

with which larvae can disperse among locations; the “oceanographic distance”

experienced by larvae between sites is uncorrelated with geographic separation between

them (Baums et al. 2006; White et al. 2010). Likewise, recent meta-analyses indicate the relationship between the length of pelagic larval development and dispersal ability is not as tight as has been generally assumed (Bradbury et al. 2008; Weersing & Toonen 2009;

Shanks 2009; Ross et al. 2009; Riginos et al. in press). Finally, a broad meta-analysis by

Lester et al. (2007) indicates the intuitive relationship between range size and larval dispersal potential are poorly correlated overall, but can play an important role in some taxa. Although the mechanism of isolation across small scales remains unknown, our data

clearly indicate that for H. whitmaei and H. atra relative range size does not predict

relative dispersal ability. Given that both species appear to share a similar life history,

have a similar minimum larval duration, occupy the same habitats, are both wide ranging,

and are closely related it would be expected that they would have similar levels of

population partitioning. The simplest explanation is a divergence in larval behavior or

maximum larval duration (Scheltema 1988; Shulman 1998; Riginos and Victor 2001). A

direct comparison of larval biology is lacking, but it would help to illuminate the cause

behind the patterns found in our data. Alternatively, the differences in population

structure may stem from subtle, species-specific disparities in habitat usage that impact genetic structure.

Population structure in the Hawaiian Archipelago and Johnston Atoll

Both species show high haplotype diversity and a low nucleotide diversity in the

16S gene. Except for the H. whitmaei Laysan and Nihoa populations, haplotype diversity was similar at all localities in each species. Nucleotide diversity was higher in H. atra, but there were no other apparent patterns between localities in either species; there were also no apparent patterns between species.

Our mtDNA examination of H. atra and H. whitmaei revealed contrasting patterns

of population partitioning. Regional population partitioning was not detected in H.

whitmaei with AMOVA, whereas significant regional partitioning was detected in H.

atra. Pairwise population comparisons also reflected this pattern. All pairwise H.

whitmaei comparisons had low non-significant values except for the isolation of Nihoa.

Genetic similarity in H. whitmaei is characterized by three haplotypes common

45 throughout the sampled range, the most common of which was not detected in the low number of Nihoa samples. The absence of this haplotype is likely the reason why Nihoa stands out in these comparisons.

Two interesting patterns are revealed by the H. atra population partitioning.

Excluding Laysan Island, there are no significant pairwise differences between any other islands in the NWHI (spanning nearly 2000 km), suggesting that the NWHI, excluding

Laysan, comprises a single, large population. In contrast, there is significant structuring within the MHI (roughly 600 km), and between the NWHI and the MHI. This finding suggests that factors beyond merely geographic distance influence population partitioning in H. atra. All of the population structure in H. atra is driven by the three localities of

Oahu, Kauai, and Laysan. Johnston Atoll, the nearest neighboring land mass, roughly 860 km south of French Frigate Shoals, is genetically distinct from most of the MHI and

Laysan, and genetically similar to all of the NWHI except Laysan.

It has been suggested that Johnston Atoll acts as a stepping-stone into the

Hawaiian Islands (Maragos & Jokiel, 1986). Kobayashi and Polovina (2006) and

Kobayashi (2006) used computer simulations to predict two possible larval transport corridors from Johnston Atoll to the Hawaiian Archipelago: one corridor stretching from

Johnston to French Frigate Shoals in the NWHI, and one from Johnston to O‘ahu in the

MHI. Our data support the predicted larval transport corridor between Johnston Atoll and

French Frigate Shoals, but not the corridor predicted between Johnston Atoll and Kaua‘i.

Migration between areas in the Hawaiian Archipelago is heavily one-sided with migration from the MHI into the NWHI dominating. The effectively one-way migration rates into the NWHI and Johnston Atoll coupled with the strong genetic similarity

between Johnston Atoll and the NWHI suggest Johnston Atoll is an isolated outpost of

the Northwest Hawaiian Islands, providing support for a vortex model (Jokiel &

Martinelli 1992) rather than the stepping stone entry into Hawai‘i (Maragos & Jokiel

1986) for H. atra.

CONCLUSIONS

Many echinoderm species are the focus of artisanal or commercial fishing efforts, and managing these fisheries requires an understanding of dispersal pathways and population connectivity within a spatial management network. The Hawaiian Archipelago lies at the periphery of the tropical Central Pacific and is the most isolated island chain in the world; the question remains as to why some species maintain connectivity and species cohesion between the Hawaiian Islands and the rest of the Pacific, why some species diverge and become Hawaiian endemics, and why other species with similar inferred dispersal ability fail to colonize the Hawaiian Archipelago.

Considerable evidence indicates that it is indefensible to make predictions of connectivity based solely on proxies such as ecological or phylogenetic similarity, pelagic larval duration, or species range sizes (Bird et al., 2007; Lester et al., 2007;

Bradbury et al., 2008; Shanks, 2009; Weersing & Toonen, 2009). The fine-scale structuring of populations in H. atra and H. whitmaei suggest that place-based management approaches, as exemplified by ecosystem based management, are ideal for responding to the complex relationships between genetically distinct populations.

Holothuria atra and Holothuria whitmaei must be managed on a local scale; migration

47 between archipelagos, and often between islands, does not occur in ecologically relevant time frames.

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TABLES

Holothuria atra

Region Site N H H u π ± SD h ± SD A E Tajima's D Fu's Fs Hilo 9 4 0 0.0041 ± 0.0030 0.81 ± 0.08 5.3 -0.27 0.08 Main Kona 21 10 2 0.0078 ± 0.0046 0.87 ± 0.06 7.5 -0.57 -2.21 Hawaiian Oahu 24 7 2 0.0052 ± 0.0033 0.79 ± 0.05 4.7 -0.88 -0.58 Islands Kauai 30 8 3 0.0033 ± 0.0023 0.75± 0.06 4.0 -1.21 -2.61 Niihau 5 4 1 0.0071 ± 0.0052 0.90 ± 0.16 10.0 -0.75 -0.33 French Frigate 28 10 2 0.0082 ± 0.0048 0.88 ± 0.04 8.3 -0.14 -1.12 Gardner 2 1 0 N/A N/A N/A N/A N/A Northwest Laysan 12 8 0 0.0064 ± 0.0041 0.89 ± 0.08 9.1 -1.06 -2.91 Hawaiian Pearl & Hermes 37 10 2 0.0086 ± 0.0049 0.79 ± 0.05 4.8 -1.26 -0.23 Islands Midway 35 14 7 0.0084 ± 0.0048 0.84 ± 0.05 6.2 -0.64 -3.61 Kure 23 8 2 0.0096 ± 0.0055 0.85 ± 0.04 6.9 -0.92 0.47 Johnston 26 7 1 0.0131 ± 0.0073 0.81 ± 0.05 5.3 -0.28 2.96 Overall 252 32 22 0.0087 ± 0.0004 0.88 ± 0.01 8.3 -1.34 -2.49

Holothuria whitmaei

Region Site N H H u π ± SD h ± SD A E Tajima's D Fu's Fs Main Kona 27 7 0 0.0055 ± 0.0034 0.80 ± 0.04 5.0 -0.19 -0.01 Hawaiian Kauai 33 7 1 0.0056 ± 0.0035 0.77 ± 0.05 4.3 0.11 0.15 Nihoa 10 2 0 0.0036 ± 0.0030 0.53 ± 0.09 2.1 1.83 3.34 French Frigate 25 10 2 0.0067 ± 0.0040 0.82 ± 0.06 5.6 -0.82 -2.20 Gardner 1 1 0 N/A N/A N/A N/A N/A Northwest Lisianski 2 1 0 N/A N/A N/A N/A N/A Hawaiian Laysan 21 6 1 0.0044 ± 0.0029 0.66 ± 0.10 2.9 -0.50 -0.01 Islands Pearl & Hermes 57 13 2 0.0057 ± 0.0034 0.86 ± 0.02 7.1 -2.68 1.30 Midway 27 13 6 0.0251 ± 0.0131 0.90 ± 0.04 10.0 -1.19 -4.59 Kure 39 10 2 0.0048 ± 0.0030 0.85 ± 0.03 6.7 -0.10 -1.91 Johnston 31 9 1 0.0078 ± 0.0045 0.85 ± 0.04 6.7 0.27 -0.18 Overall 273 27 15 0.0067 ± 0.0013 0.83 ± 0.01 5.9 -2.63 -9.37

Table 3.1 N sample size, H total number of haplotypes, H u number of unique haplotypes at

site, π nucleotide diversity, h haplotype diversity, A E effective number of alleles in COI. Bolded test values are significant at <0.05

Holothuria atra Morisita Dissimilarity 0.439 +/- 0.042 Region ______Northwest Hawaiian Islands______Main Hawaiian Islands__ Kure Midway Pearl & Laysan French Johnston Site Kauai Oahu Kona Atoll Atoll Hermes Island Frigate Atoll Kure 0.004 -0.013 0.124 0.000 0.278 0.193 0.009 -0.013 Northwest Midway 0.028 -0.012 0.173 -0.012 0.335 0.263 0.016 0.018 Hawaiian Pearl & Hermes 0.008 -0.004 0.194 -0.014 0.341 0.258 0.026 -0.005 Islands Laysan 0.066 0.082 0.119 0.145 0.000 0.018 0.049 0.156 French Frigate -0.005 -0.004 -0.006 0.035 0.305 0.220 -0.006 0.015 Main Kauai 0.144 0.186 0.211 -0.025 0.126 0.050 0.203 0.309 Hawaiian Oahu 0.082 0.161 0.166 0.025 0.091 0.050 0.127 0.231 Islands Kona 0.018 -0.014 0.003 0.019 -0.016 0.109 0.097 0.046 Johnston -0.004 0.019 -0.010 0.110 -0.002 0.204 0.163 0.027

Holothuria whitmaei Morisita Dissimilarity 0.190 +/- 0.059 Region ______Northwest Hawaiian Islands______Main Hawaiian _ Kure Midway Pearl & Laysan French Johnston Site Nihoa Kauai Kona Atoll Atoll Hermes Island Frigate Atoll Kure 0.009 0.000 0.045 -0.002 -0.010 -0.009 -0.009 0.017 Midway -0.004 0.013 0.013 -0.011 -0.035 -0.002 -0.007 -0.005 Northwest Pearl & Hermes 0.000 -0.008 0.030 0.008 0.022 -0.010 -0.018 -0.003 Hawaiian Laysan 0.059 0.052 0.054 0.058 0.160 0.021 0.005 0.027 Islands French Frigate 0.004 -0.012 0.006 0.073 -0.029 -0.021 -0.010 -0.005 Nihoa 0.094 0.126 0.123 0.295 0.140 0.006 0.022 0.023 Main Kauai 0.011 -0.006 0.002 0.026 -0.016 0.186 -0.022 -0.005 Hawaiian Kona -0.006 -0.015 -0.011 0.020 -0.013 0.128 -0.019 -0.022 Johnston 0.029 -0.003 0.006 0.057 -0.004 0.212 -0.004 -0.004

Table 3.2 Pairwise comparisons by site. Fst values are contained in the lower left half of each table and Φst values are in the upper right half of each table. Bolded values signify significant differences after correction using the procedure outlined in Benjamini 2008. Shaded cells signify significant differences between sites in both tests.

Holothuria whitmaei Holothuria - Atoll 0.167 0.000 0.038 0.194 0.000 0.000 0.000 0.708 Johnston Johnston - Kona 0.000 0.000 0.000 0.058 0.000 0.000 0.352 0.144 ------Oahu 0.515 0.782 0.048 0.000 0.010 0.072 0.172 0.000 Kauai 0.495 0.499 0.901 __Main Hawaiian__Main Islands__ - - - - 0.303 0.451 0.422 0.647 0.403 Nihoa - 0.024 0.000 0.035 0.230 0.000 0.000 0.512 0.629 French French Frigate values in are the lower left half whitmaei of the table H. and Holothuria atra Holothuria - 0 0.209 0.203 0.205 0.286 0.122 0.138 0.694 Island Laysan - 0.003 0.000 0.000 0.008 0.000 0.674 0.888 0.744 Pearl & Hermes - Atoll 0.000 0.000 0.555 0.000 0.000 0.093 0.880 0.846 Midway - ______Northwest Hawaiian Islands______Kure Atoll 0.160 0.035 0.483 0.111 0.000 0.666 0.410 -0.030 comparisons by species site. comparisons and H. atra est_chao Site Kure Kona Kauai Oahu Nihoa Laysan Midway Johnston French Frigate Pearl & Hermes sites. Bolded values signify significant differences using outlined the procedure correction after in Benjamini 2008. Table D 3.3 Pairwise Region Islands values in are the half upper right of the table. Cells were withspecies "-" indicate done a comparisons no that for between those Hawaiian Northwest

Table 3.4 Analyses of molecular variance (AMOVA) by region using haplotype distance (ΦST) and non-

distance (FST) measures. Source of % of Species Measure Regions Φ statistics P-Values Variation Variation AG 5.8 F = 0.058 <0.01 MHI; NWHI; CT Holothuria atra F ST Johnston Atoll AP(G) 3.22 F SC = 0.034 <0.01 WP 90.99 AG 12.65 Φ = 0.127 <0.01 MHI; NWHI; CT Holothuria atra Φ ST Johnston Atoll AP(G) 3.84 Φ SC = 0.044 <0.01 WP 83.51 AG -0.77 F = -0.008 0.50 MHI; NWHI; CT Holothuria whitmaei F ST Johnston Atoll AP(G) 2.48 F SC = 0.025 0.01 WP 98.3 AG -0.87 Φ = 0.373 0.87 MHI; NWHI; CT Holothuria whitmaei Φ ST Johnston Atoll AP(G) 0.67 Φ SC = 0.032 0.24 WP 100.2 AG = Among Groups, AP(G) = Among populations within Groups, WP = Within Populations

Table 3.5 Pairwise population migration

rate estimates (N e Μ )based on a Bayesian MCMC simulation. The value of M calculated by Migrate was multiplied by the θ, as calculated by Migrate, of the destination population to estimate migration. The estimates of migration are seperated by direction; the columns are source populations and the the rows are sink populations. MHI NWHI Johnston MHI - 2.59875 1.073025 NWHI 37.65388 - 79.09125 Johnston 0.3135 3.5416 -

FIGURES

The Hawaiian Archipelago Papah ānaumoku

ākea Marine National Monument

Midway Pearl and Hermes

Laysan Gardner Main Hawaiian Islands

French Frigate Shoals Kauai Oahu Maui

Hawaii

Figure 3.1 Map of the Hawaiian Archipelago

Figure 3.2 Haplotype network for Holothuria atra. Each circle represents a unique haplotype connected by a line to those that differ by one base pair. Nodes on lines indicate a missing haplotype and numbers represent multiple missing haplotypes. Each haplotype is color-coded by site and circle size is proportional to frequency. The smallest circles represent one occurrence of a haplotype.

Figure 3.3 Haplotype network for Holothuria whitmaei. Each circle represents a unique haplotype connected by a line to those that differ by one base pair. Nodes on lines indicate a missing haplotype and numbers represent multiple missing haplotypes. Each haplotype is color-coded by site and circle size is proportional to frequency. The smallest circles represent one occurrence of a haplotype.

CHAPTER FOUR

Gateways to Hawai‘i – Genetic population structure of the tropical sea cucumber

Holothuria atra

Published as:

Skillings DJ, Bird CE and Toonen RJ (2011) Gateways to Hawai‘i – genetic population

structure of the tropical sea cucumber Holothuria atra. Journal of Marine Biology.

Article ID 783030:1-16.

ABSTRACT

Holothuria atra is one of the most common and widest ranging tropical, coral reef sea cucumbers in the world, and here we examine population genetic structure based on mitochondrial COI to aid in determining the appropriate scale for coral reef management.

Based on SAMOVA, AMOVA and BARRIER analyses, we show that despite its large range, H. atra has hierarchical, fine-scale population structure driven primarily by between-archipelago barriers, but with significant differences between sites within an archipelago as well. Migrate analyses along with haplotype networks and patterns of haplotype diversity suggest that Hawai‘i and Kingman reef are important centers of the genetic diversity in the region rather than an evolutionary dead-end for migrants from the

Indo-Pacific. Finally we show that for H. atra Kingman Reef is the most likely stepping stone between Hawai‘i and the rest of the Pacific, not Japan or Johnston Atoll as previously presumed. Based on our data, Johnston Atoll can instead be seen as an outpost of the Northwestern Hawaiian Islands rather than a gateway to the Hawaiian

Archipelago.