Phylogeography of a Pantropical Plant with Sea-Drifted Seeds; Canavalia Rosea (Sw.) DC., (Fabaceae) 汎熱帯海流散布植

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（千葉大学学位申請論文） Phylogeography of a pantropical plant with sea‐drifted seeds; Canavalia rosea (Sw.) DC., (Fabaceae) 汎熱帯海流散布植物ナガミハマナタマメ (マメ科)の系統地理

2010 年７月

千葉大学大学院理学研究科地球生命圏科学専攻生物学コース

Mohammad Vatanparast

Phylogeography of a pantropical plant with sea‐drifted seeds; Canavalia rosea (Sw.) DC., (Fabaceae)

July 2010

MOHAMMAD VATANPARAST

Graduate School of Science

CHIBA UNIVERSITY

TABLE OF CONTENTS PAGES

ABSTRACT 1 GENERAL INTRODUCTION 3 Pantropical plants with sea-drifted seeds species (PPSS) 5 A project on the phylogeography of the PPSS 6 A case study of PPSS: Hibiscus tiliaceus L. 7 Canavalia rosea: a genuine pantropical plant with sea-drifted seeds 8 Overview of this study 10 CHAPTER 1 12 PHYLOGENETIC RELATIONSHIPS AMONG CANAVALIA ROSEA AND ITS ALLIED SPECIES 12 1-1 Introduction 12 1-2 Materials and Methods 15 Taxon sampling 15 DNA extraction, PCR, and sequencing 16 Phylogenetic analyses based on cpDNA sequence data 18 Phylogenetic analyses based on ITS sequence data 19 1-3 Results 21 Phylogenetic analyses based on cpDNA sequence data 21 Phylogenetic analyses based on ITS sequence data 22 1-4 Discussion 24 Phylogenetic relationships among C. rosea and its related species 24 The phylogeographic break in the Atlantic Ocean 25 Origin of the Hawaiian endemic species 26 Future prospects for the evolutionary studies among C. rosea and its allied species 27

Tables and figures 29

TABLE OF CONTENTS (CONTINUED) PAGES

CHAPTER 2 40 GLOBAL GENETIC STRUCTURE OF CANAVALIA ROSEA; EVIDENCE FROM CHLOROPLAST DNA SEQUENCES 40 2-1 Introduction 40 2-2 Materials and Methods 44 Sampling 44 DNA extraction, PCR, and sequencing 44 Haplotype Composition and Network of C. rosea and its allied species 44 Population differentiation 45 Historical migration rates between oceanic regions 46 Estimates of recent migration rates 48 2-3 Results 49 Haplotype Composition and Network of C. rosea and its allied species 49 Population differentiation 50 Historical migration rates between oceanic regions 51 Estimates of recent migration rates 52 2-4 Discussion 54 Gene flow in Indo-Pacific Ocean through Long Distance Seed Dispersal 54 A strong genetic difference between the Indo-Pacific and Atlantic populations of C. rosea 56 2-5 Conclusion 59 Tables and figures 60

GENERAL DISCUSSION 74 REFERENCES 76 ACKNOWLEDGEMENTS 82 BIOGRAPHY 83

ABBREVIATIONS

AEP Atlantic East Pacific

AMOVA Analysis of molecular variance bp base pair cpDNA chloroplast DNA

CTAB cetyltrimethyl ammonium bromide

ESS Effective sample size

FST Fixation index (F-statistices)

IGS Intergenic Spacer

ITS Internal Transcribed Spacers

IWP Indo West Pacific

MLE Maximum likelihood estimates nrDNA nuclear ribosomal DNA

PCR Polymerase Chain Reaction

PCR-SSCP PCR amplification with single-strand conformation polymorphism

PCR-SSP PCR amplification with sequence specific primers

PPSS Pantropical Plants with Sea-drifted Seeds

RCA Rolling Circle Amplification

SAMOVA Spatial Analysis of Molecular Variance

iii

ABSTRACT

This study intends to examine the importance of long distance seed dispersal in the recurrent speciation and integration of pantropical plants with sea-drifted seeds (PPSS). I focused on one of genuine member of PPSS; Canavalia rosea (Sw.) DC. and its allied species.

Chapter 1 is concerned with the phylogenetic relationships among C. rosea and its allied species as well as Hawaiian endemic species using chloroplast DNA (cpDNA) and internal transcribed spacers (ITS) of nuclear ribosomal DNA (nrDNA) sequences. Phylogenetic analyses using nucleotide sequences of 6 cpDNA regions (ca. 6000 bp) as well as nrDNA ITS for C. rosea and its related species suggested that rapid speciation might occurred among C. rosea and its related species. The phylogenetic results also suggested that Hawaiian endemic subgenus Maunaloa, was monophyletic and closely related to subgenus Canavalia than to other subgenera (Wenderothia and Catodonia). The results suggests that the Hawaiian subgenus originated by single colonization to Hawaiian archipelagos by sea-dispersal.

In chapter 2, spatial genetic structure of cpDNA sequences were studied for C. rosea and its related species. In total 515 individuals from 48 populations were surveyed based on partial sequences of 6 cpDNA regions (ca. 2000 bp).

Statistical analyses (FST-based and coalescent-based methods) did not show significant genetic differentiation among the C. rosea populations over whole Pacific and Indian Oceanic regions and also within Atlantic region. This suggests that significant gene flow by long distance dispersal of sea-drifted

seeds occurs among these oceanic regions. On the other hand, the results of phylogenetic and population genetic analyses confirm the genetic differentiation of the Atlantic populations. This suggests that African and American land masses played roles as geographical barriers to gene flow by sea-dispersal. However, partial gene flow was detected between Atlantic and Indian oceanic regions which suggest that the unity of the species in global scale is kept by long distance seed dispersal over the African continent. Directional gene flow within Atlantic region might be corresponded to the variation of the strength of tropical Atlantic’s major currents which regarded as transatlantic dispersal in Atlantic region. Moreover, highly differentiated populations of C. rosea were detected in the southern Brazil. The South Equatorial Current bifurcating at the north-eastern horn of Brazil to the northward and southward appears to be potential barrier to gene flow and may promote the genetic differentiation of the C. rosea populations in southern Brazil.

GENERAL INTRODUCTION

“… mammals have not been able to migrate, whereas some plants, from their varied means of dispersal, have migrated across the wide and broken interspaces.”

(Darwin, 1859)

The term dispersal has two different but interrelated functions in most species. The first one is, range expansion of species, and the second one, gene flow within and among populations. Range expansion is necessary for almost all species, so they have various strategies to expand their distribution ranges (Linhart & Grant, 1996). However, the wider distribution range arisen from dispersal causes high genetic heterogeneity among populations because of increased levels of selection within local populations and/or because of limited levels of genetic exchange among the local populations (Heywood, 1991; Hamrick & Nason, 1996; Linhart & Grant, 1996). When genetic heterogeneity among populations becomes significantly enough, local populations can evolve and eventually form a distinct species (Wright, 1931; Ennos, 1994; Bohonak,

1999). Gene flow is one of the most important processes for species to evolve as cohesive units in their distribution range (Mayr, 1963; Levin, 2000; Morjan & Rieseberg, 2004). In fact, if levels of gene flow within and among populations become high (e.g. greater than four migrants per generation), it homogenize the species and prevents genetic divergence of local populations.

In many plant species, populations are spatially isolated from each other, often by hundreds of meters or more and seed dispersal represents the only way by which populations can exchange individuals or to expand the distribution ranges (Cain et al., 2000). As there are geographical, ecological or behavioral barriers to seed dispersal, most plant species are not distributed globally (Howe & Smallwood, 1982; Cain et al., 1998; Willson & Traveset, 2000). The biggest barrier for land plants will be the ocean, so that most of the floristic compositions are generally quite different among continents which are divided by oceans. However, there are a few plant species that characterized by their extremely wide distribution ranges across littoral areas in tropics and subtropics worldwide. They are called “pantropical plants with sea-drifted seeds” (Takayama et al., 2006; 2008), referred to as PPSS. A few PPSS are known from various families which can roughly divide into 2 categories. One is genuine PPSS in which a single species distributes around the globe. Canavalia rosea (Sw.) DC. (Fabaceae) and Ipomoea pes-caprae (L.) R. Br. (Convolvulaceae) are in this category. The other one is Sub-PPSS, in which small numbers of closely related species compose the global distribution in total. Hibiscus tiliaceus L., with H. pernambucensis Arruda (Malvaceae), Vigna marina (Burm.f.) Merr. with V. luteola (Jacq.) Benth. (Fabaceae), and species of Rhizophora L. and Entada Adans. are in this category.

Pantropical plants with sea-drifted seeds species (PPSS)

The main dispersal mode of PPSS is sea-dispersal. Almost all PPSS have seeds or fruits that can float in sea water for long time. The seed coats of these species are hard with lightweight cotyledons and there are air spaces between the folds of the cotyledons which help the seeds to stay impermeable on sea water (Nakanishi, 1988; Loewer, 2005; Thiel & Haye, 2006). Nakanishi (1988) investigated germination and buoyancy of seeds and fruits of seventeen maritime species (including most of PPSS), after immersion in artificial seawater. He revealed that all seeds and fruits tested in the study continued to float in sea water for at least three months (Nakanishi, 1988). These characteristics help PPSS to distribute in wide areas in equatorial belt around the globe. Their distribution ranges are consistent with the areas where the average temperature of Ocean water is around 20 ͦC. In the West Atlantic, they are distributed from Florida to the Uruguay in Southern West Atlantic. In East Atlantic they are distributed from Senegal to the Angola and in the Indian Ocean from Northern part of Indian Ocean to the East Cape of South Africa. In the West Pacific Ocean their northern limit is Ryukyu Islands in Japan and in the south west Pacific is the Brisbane in Australia. In central pacific, their distribution ranges are from Hawaii to Polynesia and in the East Pacific from Sinaloa in Mexico to the Northern part of Peru in the East Pacific seashores (Fig. 1-2A).

The extremely wide distribution range of PPSS has been explained mainly by their high ability of seed dispersal (Sauer, 1988; Whistler, 1992). On the other hand, high dispersal ability with sea-drifted seeds could raise the

potential of population differentiation and speciation. New species could arise independently in remote populations following long-distance seed dispersal and/or adaptation to a new habitat. This kind of speciation process is assumed to occur in PPSS, as the most of the PPSS have some closely related species distributed in limited areas comparing to the mother PPSS (Levin, 2001; Takayama et al., 2006). However, until recently there were no empirical data to explain how PPSS keep the extremely wide range of distribution.

A project on the phylogeography of the PPSS

One of the major difficulties that prevent researchers from performing comprehensive study in PPSS was their extremely wide distribution ranges. The project of PPSS was started more than 10 years ago with the leading of Dr. Tadashi Kajita and with propose of global population sampling as well as performing population genetic analyses using various molecular markers. Accomplishment of this project was facilitated because of development of aviation and transportation systems in recent two decades. Cooperation with oversea researchers and institutes are also promoted the project to go ahead. Until now more than several thousand samples were collected from 30 countries and is ongoing project to performing phylogeographic analyses to reveal the speciation and population differentiation of PPSS.

Phylogeography is a relatively new discipline that deals with the spatial arrangements of genetic lineages, especially within and among closely related species (Avise, 2009). It utilized molecular markers to reveal the evolutionary history of the species at the geographical scale. Novel analytical methods with high output are also recently developed at the population level (e.g.,

application of coalescent-based approaches and tree-based thinking) (Knowles & Maddison, 2002; Knowles, 2009). Using these methods will enable us to study phylogeographic patterns of PPSS.

A case study of PPSS: Hibiscus tiliaceus L.

Recently, one of our colleagues, Koji Takayama studied genetic structure of Hibiscus tiliaceus and its allied species using chloroplast DNA (cpDNA) polymorphisms and Microsatellite markers (Takayama et al., 2006; 2008). Hibiscus tiliaceus is distributed in the East Atlantic and Indo-West Pacific regions and its counterpart species, Hibiscus pernambucensis, is distributed in the East Pacific-West Atlantic regions. All together distribution range of H. tiliaceus and H. pernambucensis covers almost the entire littoral area of the tropics worldwide, a situation that could have been established through dispersal by sea-drifted seeds. Three morphologically similar species to H. tiliaceus are recognized in both the Old World (Hibiscus hamabo Siebold & Zucc.) and New World (Hibiscus glaber Matsum. and Hibiscus elatus Sw.). These three species have limited distribution ranges, which the two island endemic species, H. glaber and H. elatus grow in parallel at inland habitats of islands in both the Old and New Worlds respectively, and H. hamabo grows in temperate areas of West Pacific area beyond the northern limit of distribution of H. tiliaceus (Takayama et al., 2006). The main summary of their finding are as follows:

I. Recurrent speciation from H. tiliaceus has given rise to all of its allied species.

II. Frequent gene flow by long-distance seed dispersal is responsible for species integration of H. tiliaceus in the wide distribution range. III. American and African continents may be geographical barriers to gene flow by sea-drifted seeds among populations of H. pernambucensis and H. tiliaceus, respectively. IV. Introgression between the H. tiliaceus and H. pernambucensis was occurred in the Atlantic region.

All these results are new for a sub-PPSS species and explain their wide distribution range; however we still do not know whether these results are applicable for other PPSS, especially for a genuine PPSS with global distribution. So, to answer this question, I focused on Canavalia rosea (Beach bean), a genuine member of PPSS.

Canavalia rosea: a genuine PPSS

Canavalia rosea (Beach bean) is mostly prostrate herbaceous vine that trails along beach dunes, coastal strand and rocky shores and sometimes climbs into low vegetation (Whistler, 1992). The thick and fleshy stem can grow to 6 m or more in length and more than 2.5 cm in diameter. The stem is rather woody near the base and several branches radiate outward, forming mats of light green semi-succulent foliage. Beach bean has compound leaves with three thick, more or less rounded, fleshy leaflets, each about 5 -12 cm long. The leaflets fold up under the hot sun at midday and are coriaceous, oblong to nearly circular in outline, obtuse to emarginate, often minutely apiculate at tip. Bracteoles are 1.5 mm long. Pedicel is 3 mm long. Calyx 12 mm long; pubescence short, white, sparse to moderately dense; upper lip much shorter

than tube, upper edge constricted behind non-apiculate tip; lowest tooth 2 mm long, acute, slightly exceeding acute laterals. Standard is 3 cm long. The flowers are typical pea flowers, purplish pink, about 5 cm long and borne in erect spikes on long stalks. Beach bean blooms most of the summer and sporadically the rest of the year. The pods are commonly 10-15 cm long, flat, moderately compressed, spirally dehiscent; each valve with sutural ribs and an extra rib ca. 3 mm from ventral rib. They are prominently ridged and woody when mature. Seeds to 18 X 13 X 10 mm, elliptic, slightly compressed, brown with darker marbling, mostly buoyant and indefinitely impermeable to water, at least for a year; hilum ca. 7 mm long (Sauer, 1964). Occasionally it is cultivated experimentally as a sand binder or cover crop. Flowering time is in all seasons, even in the subtropics. The species considered as self-compatible and it can also be pollinated by carpenter bee (Xylocopa) species (Arroyo, 1981; Gross, 1993).

Canavalia rosea is distributed throughout littoral areas of the tropics and subtropics around the world. It is one of the common and most widespread tropical seacoast plants, most commonly trailing on beaches at the outer limits of land vegetation, where it is usually associated with Ipomoea pes-caprae, occasionally climbing on littoral thickets, rarely slightly inland along roadsides or coastal plain lake shores. The seeds float because of a lightweight tissue and air space (Van Der Pijl, 1969; Loewer, 2005) and remain impermeable in water for years while drifting in the sea (Guppy, 1906; Nakanishi, 1988; Thiel & Gutow, 2004). The extremely wide distribution of C. rosea is considered to be a result of long distance seed dispersal by sea-drifted seeds; however, we do not have

any empirical data and don't know whether the gene flow by seed dispersal is kept throughout the distribution range over the globe.

There are three related species to C. rosea; Canavalia cathartica Thouars, C. lineata L. and C. sericea A. Gray from the same subgenus Canavalia, which is distributed in coastal areas of Indo-Pacific Oceanic regions. Their morphological similarity suggests that they might be closely related to each other. Given the wide distribution of C. rosea and the limited distribution of the other three species, the three species of more limited distribution might have diversified from the widely distributed species. Moreover, there are six endemic Canavalia species in Hawaiian Islands (subgenus Maunaloa). There is hypothesis that these species might originate from species which reach to the Hawaiian island by sea drifted seed dispersal (Sauer, 1964). Although the presence of several closely related species with limited distribution are likely to be explained by recurrent speciation from widely distributed species, as were shown in H. tiliaceus; the speciation process among C. rosea and these species is still in question.

The main questions addressed in this thesis are: (1) Have recurrent speciation occurred in the distribution range of C. rosea? and (2) Can a single species keep gene flow over the extremely wide range of distribution?

Overview of this study

In chapter 1, I will study the phylogenetic relationships and evolutionary history among C. rosea and its allied species as well as Hawaiian endemic species based on cpDNA and internal transcribed spacers (ITS) of nuclear ribosomal DNA (nrDNA) sequences, which enable to investigate multiple lines

of evidence. In chapter 2, I will study global phylogeography and genetic structure of C. rosea and its allied species based on the cpDNA sequences, which provide an ideal marker for studying gene flow through seed dispersal. Finally, based on the results obtained in this study, I will discuss importance of sea-drifted seed dispersal for the speciation and integration of C. rosea.

CHAPTER 1

PHYLOGENETIC RELATIONSHIPS AMONG CANAVALIA ROSEA AND ITS ALLIED SPECIES

1-1 Introduction

The genus Canavalia Adans, 1763, is distributed in tropics and subtropics of all over the world (Lackey, 1981; Schrire, 2005). According to the latest taxonomic revision, the genus are further divided into four subgenera, namely, Catodonia (7 species) and Wenderothia (16 species) mostly distributed in the New World, Canavalia (23 species) in both the Old and New World which includes some crop species, and Maunaloa (6 species) which is endemic to Hawaii Islands (Sauer, 1964). Sauer (1964) studied the morphological differences/similarities among species and considered that the most primitive subgenus would be Wenderothia, and subgenera Catodonia and Canavalia would be originated from it. He also considered that subgenus Maunaloa would be originated from subgenus Canavalia because of the presence of a pantropical species, Canavalia rosea, in the subgenus.

Canavalia rosea is a typical member of the plant group called “Pantropical Plants with Sea-drifted Seeds (Takayama et al. 2006, 2008)"; abbreviated as PPSS. These species are distributed in littoral areas of the tropics and subtropics all over the world and their main mode of seed dispersal is sea-dispersal. In addition, C. rosea has some closely related species from subgenus Canavalia which have sea-dispersal, namely, C. cathartica which is distributed over Indo-West Pacific regions, C. lineata in South East Asia and C. sericea in South West Pacific. These species are distributed within distribution range of C. rosea. The other species which is known to have sea-drifted seeds is C. bonariensis of subgenus Catodonia. All other species of genus Canavalia do not have sea-drifted seeds and their main mode of seed dispersal is mechanical (thrown by dehiscent of pods) or gravity dispersal. Although the presence of several closely related species with limited distribution are likely to be explained by recurrent speciation from widely distributed species, as were shown in H. tiliaceus (Takayama et al., 2006); the speciation process among C. rosea and its related species from subgenus Canavalia is still in question. Moreover, given the distribution ranges of the species and their modes of seed dispersal, Sauer (1964) and Carlquist (1966) suggested that the endemic species of Hawaii Islands might be originated from the species that reach to the Hawaiian Islands by sea-dispersal, and the species would plausibly be the pantropical species, Canavalia rosea. However, this hypothesis has never been tested using modern molecular phylogenetic methods.

To test the hypothesis about the origin of Hawaiian endemic species of Canavalia and speciation process among C. rosea and its related species, we employed both nuclear and chloroplast DNA markers. These markers have been successfully used to study the origin of Hawaiian endemic species in other plant groups (Baldwin & Wagner, 2010). Chloroplast DNA is regarded as single locus and maternally inherited through seeds in most angiosperms (Mogensen, 1996), and it has been utilized to discover phylogenetic relationships in many plant species (Soltis & Soltis, 1998). In addition, nuclear DNA markers can also be used in combination with cytoplasmic markers to decipher phylogenetic relationships among closely relates species, as using multiple lines of molecular markers with highly polymorphic loci could give resolved topologies than single locus (Small et al., 1998; Brito & Edwards, 2009; Calonje et al., 2009). Although a recent phylogenetic study on tribe Diocleinae based on nrDNA ITS sequences (Varela et al., 2004) showed that subgenus Canavalia was sister to Catedonia, taxon sampling of the study was not enough to reveal phylogenetic relationships of the four subgenera and the origin of Hawaiian endemic species. I studied all species of subgenus Maunaloa together with other samples of C. rosea and its closely related species, in addition to both representative species of subgenera Wenderothia and Catodonia.

1-2 Materials and Methods

Taxon sampling Leaf samples were collected in large-scale, covering almost all distribution ranges of the species. For cpDNA phylogenetic analyses, in total, 62 individuals from Canavalia rosea, 5 individuals from C. cathartica, 4 individuals from C. lineata, and 3 individuals from C. sericea were included in phylogenetic study (Table 1-1). Moreover, an inland species, Canavalia virosa (Roxb.) Wight & Arn., two crop species, Canavalia ensiformis (L.) DC. (Common Jack bean) and Canavalia gladiata (Jacq.) DC. (Sword bean) from the subgenus Canavalia were added in the phylogenetic analyses (Table 1-1). For nrDNA ITS phylogenetic analyses selective samples from C. rosea and its related species were included (Table 1-2). All Hawaiian endemic species from subgenus Maunaloa including Canavalia molokaiensis Degener & al., C. hawaiiensis Degener & al., C. napaliensis St. John, C. galeata Gaudich., C. pubescens Hook. & Arn., and C. kauaiensis J.D. Sauer (St. John H, 1970; Wagner et al., 1999) were also included in either cpDNA and ITS analyses. Canavalia parviflora Benth. was added in the phylogenetic analyses as a representative species from subgenus Catedonia. Canavalia hirsutissima J.D. Sauer and Canavalia villosa Benth. from

subgenus Wenderothia were chosen as outgroups according to Sauer (1964) and Varella (2004). Voucher specimens were deposited in the herbarium of University of the Ryukyus (RYU), Jardim Botânico, Rio de Janeiro (RBRJ) and Bishop Museum, Honolulu, Hawaii.

DNA extraction, PCR, and sequencing Genomic DNA was extracted from dried leaves using modified CTAB (cetyltrimethyl ammonium bromide) method (Doyle & Doyle, 1987) and DNA concentration was measured by GeneQuant 100 electrophotometer (GE Healthcare, Life Sciences). After an initial screening of 15 cpDNA candidate non-coding regions (Shaw et al., 2007), six highly variable regions including intergenic spacers (IGS) and introns were chosen for further steps (Table 1-3). For nuclear genome, nuclear rDNA ITS was sequenced. Polymerase chain reactions (PCR) were performed in 10-25 µL volume reactions containing 1.25 units ExTaq (TaKaRa), 0.2 mM of dNTPs, 10x PCR buffer contains 1.5 mM MgCl2, 0.5–1 µM of each primer pairs, and 20 ng genomic DNA. The PCR conditions were as follows: 3 min for initial denaturation at 95 °C, followed by 35 amplification cycles of 1 min denaturation at 95 °C, 1-2 min annealing at fragment-specific temperatures (see Table 1-3), 1-2 min extension at 72 °C, and a final 10 min extension at 72 °C. The PCR products were visualized by 0.8 % agarose gel electrophoresis and purified using either GENECLEAN III kit (Qiagen) or ExoSAP-IT (USB Corp., Cleveland, Ohio, USA) following the manufacturer's instructions.

The cycle sequencing reactions were carried out using a BigDye Terminator v. 3.1 Cycle Sequencing Kit (Applied Biosystems) and sequencing

reaction products were purified by ethanol precipitation method. All DNA sequences were determined with ABI 377 or ABI 3500 DNA sequencer (Applied Biosystems). For ITS sequences which direct sequencing yielded unreadable electropherograms, TOPO-TA cloning kit (Invitrogen) was subsequently used according to the manufacturer’s instructions. In total for 19 individuals from 14 species cloning method were used. Twelve colonies from each sample were picked up, purified and amplified via TempliPhi DNA Sequencing Template Amplification Kits (GE Healthcare). This kit utilize bacteriophage Phi29 DNA polymerase and rolling circle amplification (RCA) technology (Polidoros et al., 2006) for rapid amplification of circular template DNA. The products were then sequenced using the ABI Big Dye Terminator v3.1 Cycle Sequencing Ready Reaction kit (Applied Biosystems). Both forward and reverse strands were assembled manually using the Autoassembler 2.1 (Applied Biosystems) with default setting. Sequences manually edited and aligned with Se-Al v2.0a11 (Rambaut, 2002). Seven Indels and inversions from cpDNA sequence data set were coded as separate binary characters according to Kelchner (2000) Simmons & Ochoterena (2000) and Ingvarsson (2003). However, length variations, all gaps containing homopolymers, AT-rich regions and two homoplasious inversions were excluded from all analyses. For the ITS sequence data set, cloned products were assembled and singleton mutations were excluded by comparing to the corresponding direct ITS sequence data of this study. These singletons were presumed as a result of Taq or PCR error in cloning method. I chose a threshold that less than two singletons from aligned sequence data were removed from the data set. After making final dataset, haplotype file in Nexus format was made by the program DNAsp v. 5.10.01

(Librado & Rozas, 2009). Sequences were deposited to the GenBank under the accession numbers ### ###.

Phylogenetic analyses based on cpDNA sequence data As the chloroplast genome is inherited as a single unit without recombination, combining sequences from multiple cpDNA regions can be justified (Soltis & Soltis, 1998). Because all six cpDNA sequenced regions used in this study occur in the haploid chloroplast genome and their histories are linked, there is no priori reason to infer that their resulting gene trees will differ. However, their patterns of evolution might be different (e.g. differences in evolutionary rates and/or base compositions), leading to the incongruence among datasets (Bull et al., 1993; Wiens, 1998). Keeping these in mind, I concatenate all these regions to a single sequence data set.

Maximum parsimony (MP), maximum likelihood (ML) and Bayesian phylogenetic inference were employed for phylogenetic analyses using a concatenate data set (Table 1-3). MP analyses were conducted in PAUP* v.4.0b10 (Swofford, 2002) using heuristic searches, tree-bisection–reconnection (TBR) branch swapping algorithm, and all characters were unweighted and unordered. Branch support was evaluated by bootstrapping method of Felsenstein (Felsenstein, 1985) based on 1000 replicates.

ML analysis was employed using the program RAxML (Randomized Axelerated Maximum Likelihood) version 7.2.6 which implements a rapid hill climbing algorithm (Stamatakis, 2006). The analysis was run with indel and inversion characters removed under the GTR+G model of evolution and best-

scoring ML tree inferences. Rapid bootstrap analysis was conducted with 1000 replications to assess branch support.

Partitioned Bayesian inference were performed with MrBayes v.3.1.2 (Ronquist & Huelsenbeck, 2003). The data set was divided into two partitions; aligned nucleotides and coded indels and inversions. For nucleotide sequences GTR+I model was selected as a best-fit model according to the Akaike information criterion (AIC) by MrModel Test v.2 (Nylander, 2004) and binary model was employed for coded indels and inversions. Two independent Markov Chain Monte Carlo (MCMC) analyses with four simultaneous chains and 5,000,000 generations were run. Trees were sampled every 100 generations and the first 20000 trees were discarded as burn-in. MCMC chains convergence was visualized with Tracer v. 1.5 (Rambaut & Drummond, 2009) and likelihood scores for sampled trees were inspected.

Phylogenetic analyses based on ITS sequence data For nrDNA ITS sequence data, small number of samples were surveyed comparing to the comprehensive cpDNA samples (36 vs. 88). Maximum parsimony (MP) and neighbor joining (NJ) analyses were performed with PAUP* v.4.0b10 (Swofford, 2002) for nrDNA ITS sequences (Table 1-2). MP analyses were conducted using heuristic searches, tree-bisection–reconnection (TBR) branch swapping algorithm, and all characters were unweighted and unordered. Branch support was evaluated by bootstrapping method of Felsenstein (Felsenstein, 1985) based on 1000 replicates. The NJ tree was constructed using the distance set to Kimura 2-parameter model (Kimura,

1980) and bootstrap analysis based on 100 replicates. Combine sequence data set of cpDNA and nrDNA ITS was performed based on NJ method. In the both method Canavalia hirsutissima and Canavalia villosa from subgenus Wenderothia are defined as outgroups.

Network analyses

1-3 Results

Phylogenetic analyses based on cpDNA sequence data The concatenate cpDNA aligned sequence, which consisted of 88 sequences from 16 species, yielded 27 haplotypes (H1-27) with total length of 5654 characters after excluding all gaps and ambiguous characters. In total seven indels and inversions were coded as binary codes. MP analyses retained 16112 most parsimonious trees with tree length of 145, consistency index (CI) of 0.862, retention index (RI) of 0.807 and rescaled consistency index (RC) of 0.696 (Fig. 1-3). One hundred twenty-two characters were variable, of which 57 were parsimony-informative. MP analysis inferred monophyly of all ingroup taxa including members of subgenus Canavalia and subgenus Maunaloa all together with 100% bootstrap support. Although, C. rosea is not monophyletic species, three major clades (I, II and III) were recognized with 93, 88 and 83 bootstrap support, respectively (Fig. 1-3). Clade I consisted of C. rosea haplotypes, H5 from Java in Indian Ocean and H6 from Tanzania in Indian and Brazil in Atlantic Ocean. Clade II comprised 3 haplotypes (H16-18) of C. rosea which are exclusive to the Atlantic region samples. Haplotypes in this strongly supported clade are from both West and East Atlantic Ocean with longer

branch length. Hawaiian endemic species of subgenus Maonalua (clade III) make monophyletic group with high bootstrap support (Fig. 1-3). A major haplotype (H8) was shared among 5 species (C. rosea, C. lineata, C. cathartica, C. gladiata and C. ensiformis) and also shared among 24 samples of C. rosea from very wide distribution range in Indian and Pacific Oceans. Haplotype H2 is exclusive between C. sericea and C. cathartica from Pacific Ocean and 14 haplotypes of C. rosea (H1, H3-4, H7, H9-15 and H19-21) which are mainly from Atlantic Ocean made polytomies in all phylogenetic analyses. Canavalia lineata have only an identical haplotype (H8) with C. rosea, but C. cathartica own two haplotypes (H2 and H8) which are shared with C. sericea and C. rosea, respectively (Figs 1-3 and 2-1). Maximum likelihood tree (not shown) and Bayesian majority role consensus tree (Fig. 1-4) represented an identical topology for the main clades which was found in MP analyses.

Phylogenetic analyses based on ITS sequence data Total sequence length of nrDNA ITS was 782 for 36 samples and aligned sequence after excluding all gaps and ambiguous characters yielded 674 bp (Table 1-2). The analyses inferred monophyly of all ingroup taxa including members of subgenus Canavalia and subgenus Maunaloa all together with 100% bootstrap support same as resultant trees from cpDNA sequences. The Hawaiian endemic subgenus Maunaloa was grouped with subgenus Canavalia rather than other subgenera (Wenderothia and Catadonia) (Fig. 1-5). MP analysis results were revealed that members of subgenus Maunaloa is polyphyletic. Although clear phylogenetic relationships among ingroup taxa

were not obtained (polytomy), Hawaiian endemic species and some species have multiple copies of ITS sequences. A copy is shared among all species including C. rosea and others species (haplotype H1).

Resultant tree from combined dataset of cpDNA and nrDNA ITS show that subgenus Maunaloa is a monophyletic group with high statistical support (bootstrap value 88%; Fig. 1-6). Overall, in the nrDNA ITS trees, also same as cpDNA trees, clear relationships among C. rosea and its allied species was not resolved.

1-4 Discussion

Phylogenetic relationships among C. rosea and its related species Phylogenetic analyses based on ca. 6000 bp cpDNA sequences are revealed a monophyletic group including members of subgenus Canavalia and subgenus Maunaloa (Fig. 1-3) which is disclosed by morphological (Sauer, 1964) and cladistic surveys (De Queiroz et al., 2003). However, our results do not segregate clear species relationship among C. rosea and its allied species even using high variable cpDNA regions (Fig. 1-3). Therefore understanding evolutionary history among these species is rather complicated, and additional sequences from nuclear genome and ecological surveys are essential to address such issues (Cronn et al., 2002). On the other hand, the genealogy of the cpDNA haplotypes appears somewhat “star phylogeny” (Fig. 2-1), with a common ancestral-like haplotypes (e.g. H7 and H8) lie at the central position and recent derivatives (rare haplotypes) independently connected to it by short branches (Avise, 2000). In general, such gene genealogies are interpreted as a result of range expansion (Slatkin & Hudson, 1991; Excoffier, 2004). Considering phylogenetic trees and haplotype network (Figs 1-3 and 2-1), its plausible to suppose that recurrent speciation happened among C. rosea and its allies as reported in numerous plant species (Schaal et al., 1998; Kay et al., 2005; Mort et al., 2007).

Shared haplotypes of C. cathartica with C. rosea (H8) and C. sericea (H2) might be sign of retention of ancestral polymorphisms or traces of recent introgression events. Because I used relatively long cpDNA sequences, this

event could not have been caused by lack of information on cpDNA regions. Therefore the possibility of introgressive hybridization is more likely, however, even extensive organelle sequence data sets may have not sufficient power to conclusively resolve between the ancestral retention and contemporary introgression (Donnelly et al., 2004).

Interestingly, two well-known crop species Canavalia ensiformis (Common Jack bean) and Canavalia gladiata (Sword bean) have completely identical cpDNA sequence haplotype with C. rosea (H8) with using ca. 6000 highly variable regions. This case shows that cpDNA genome of these crop species is same with C. rosea and might suggest that introgression happened among these species and/or they might be derived from C. rosea, however further study is necessary.

The phylogeographic break in the Atlantic Ocean Usually, when there is a sharp geographic boundary between widely distributed clades, researchers assume that such breaks are the result of geographic barriers to dispersal, cryptic species boundaries, or recent contacts between historically allopatric populations (Irwin & Gibbs, 2002). The haplotypes of clade II (H16-18) are specific to Atlantic region with high probability support and Long Branch length (Fig. 1-3). Although possibility of cryptic species cannot be completely rejected and the populations in the African Oceanic regions are not kind of allopatric populations, I considered that long-term geographic barrier to dispersal is responsible to such kind of phylogeographic break in the Atlantic Ocean (Fig. 2-2).

Origin of the Hawaiian endemic species Volcanic oceanic islands such as Hawaii which have never been connected to the continents can be colonize by species which have dispersed to the islands from elsewhere. These islands which separated by thousands of kilometers from a source population are usually colonized by water or animal- dispersed plant species. According to phylogenetic analyses using nucleotide sequences of 6 chloroplast DNA regions (clade III, Fig. 1-3) and combined sequence data set of cpDNA and nrDNA ITS (Fig. 1-6), Hawaiian endemic subgenus, Maunaloa, was monophyletic with high bootstrap support (84% and 88%, respectively) and it was closely related to subgenus Canavalia than to other subgenera. These results suggest that the Hawaiian subgenus is a result of single colonization event to the Hawaiian archipelagos.

Although ancestral lineage of Hawaiian endemic Canavalia was not clearly solved but it is plausible to assume that an ancestral species of Hawaiian endemic species, was somewhat similar to C. rosea which has sea-drifted seed dispersal ability to reach the Hawaiian Islands. Sauer (1964) and Carlquist (1966) reported loss of seed buoyancy for the members of subgenus Maunaloa. The loss of seed buoyancy in these species might be due to decreased air space in the seeds. In C. rosea, air spaces between the folds of the cotyledons help long-term seed buoyancy on sea water (Nakanishi, 1988). Loss of seed buoyancy in oceanic island species is a common phenomenon and occurred in many species in Hawaiian endemic plants (Carlquist, 1974). Loss of seed dispersal ability had occurred in response to the habitat shift toward inlands during the speciation process of members of subgenus Maunaloa.

The important attribute of reduced seed dispersibility is expected to restrict gene flow among local populations within the Islands, and may lead to genetic differentiation among populations. Further studies are required to assess gene flow and population genetic structure in inland species.

Future prospects for the evolutionary studies among C. rosea and its allied species Although with using more than 6000 bp cpDNA sequences I could get overall phylogenetic relationships among C. rosea and its related species, however, clear evolutionary history among them is not resolved. This is not the only case which single locous is not able to decipher phylogenetic relationships among taxa (Cronn et al., 2002). Given the difficulties that closely related taxa such as the C. rosea present in terms of phylogenetic resolution, and the low sequence divergence found in cpDNA and nrDNA ITS sequences, novel approaches are needed to integrate not only a combination of single copy genes, but also multiple molecular markers such as Microsatellite or AFLP markers (Scherson et al., 2005). The use of multiple and independent nuclear loci, promises not only to resolve phylogenetic relationships but also offers a means by which speciation events may be solved in PPSS.

The results of cpDNA phylogeny suggest that recurrent speciation might occur among C. rosea and its allied species in oceanic islands. However, complete segregation has not been established between these species and also some crop species. As theory suggests, long distance dispersal play a role for range expansion of species and because of less flow in marginal

populations, speciation might occur. Taking account the limited distribution range of allied species of C. rosea and also endemic species of Hawaiian Islands, this kind of speciation might occurred among C. rosea and its daughter species (C. cathartica, C. lineata and C. sericea) in Indo-West pacific region and also for Hawaiian endemic species at oceanic islands which produced an endemic subgenus. In terms of speciation, long distance seed dispersal clearly contributed in species diversity in oceanic islands.

Subgenus Taxon Oceanic Region Locality N. Canavalia C. rosea (Sw.) DC. Indian Ocean South Africa Umdloti 2 Tanzania Dar es salaam 2 Sri Lanka Wattala, Negambo 2 Thailand Phuket, Kmala Beach 1 Indonesia Bali 1 Java 1 Sumatra 1 Australia Darwin 2 Headland Harbour 1 West Pacific Thailand Kho Samui 1 Taiwan Houpihu 1 Singapore Singapore 1 Philippine Quezon, Luzon 1 Australia Queensland 2 Japan Iriomote 2 New Caledonia Plage de poe 1 Fiji Korotogo 1 Tonga Sopu 1 Samoa Samoa 1 Marquises Taipivai, Nuku Hiva 1 East Pacific Mexico Nayarit 2 Sinaloa 1 Oaxaca 1 Costa Rica Jaco Beach 1 Panama Veracruz 1 Ecuador Isla Jambel 1 West Atlantic Mexico Coatzcoalcos 2 Costa Rica Puerto Viejo 1 Panama Pina, Colon 4 Cuango, Colon 3 Brazil Para 2 Gaibu Pernanbuco 1 Rio De Janeiro, Arraial do Cabo 1 Rio De Janeiro, Recreio 2 East Atlantic Senegal Joal-Fadiout 8 Ghana Busua beach 4 Angola Musul, Luanda 1 Subtotal 62 Table 1‐1. List of Canavalia samples used for cpDNA phylogenetic analyses. N, number of individuals in each population. (to be continued)

Subgenus Taxon Oceanic Region Locality N. C. cathartica Thouars Pacific Philippine Atimona 1 Samoa Samoa 1 Tonga Tonga 1 Tahiti Tahiti 1 Hawaii Kauai 1 Subtotal 5 C. lineata (Thunb.) DC. Pacific Taiwan Maopi Tao 1 Japan Ishigaki 1 Miyazaki 1 Ogasawara 1 Subtotal 4 C. sericea A. Gray Pacific Tonga Haashini-Lavengatonga 2 Hawaii Maui, Bishop Museum 1 Subtotal 3 C. virosa (Roxb.) Wight & Arn. Atlantic Africa Seed purchased 1 C. gladiata (Jacq.) DC. Pacific Japan Seed purchased 1 C. ensiformis (L.) DC. Pacific Japan Seed purchased 1 Maunaloa C. hawaiiensis Degener & al. Pacific Hawaii Bishop Museum 1 C. napaliensis St. John Pacific Hawaii Bishop Museum 1 C. galeata Gaudich. Pacific Hawaii Bishop Museum 1 C. pubescens Hook. & Arn. Pacific Hawaii Bishop Museum 1 C. kauaiensis J.D. Sauer Pacific Hawaii Bishop Museum 1 C. molokaiensis Degener & al. Pacific Hawaii Bishop Museum 1 C. hawaiiensis Degener & al. Pacific Hawaii Center for Conservation Research and Training (CCRT) 1 C. galeata Gaudich. Pacific Hawaii Center for Conservation Research and Training (CCRT) 1 Catodonia Canavalia parviflora Benth. Atlantic Brazil Jardim Botanico (Rio de Janeiro) 1 Wenderothia Canavalia villosa Benth. Atlantic Mexico MEXU 1 Canavalia hirsutissima J.D. Sauer Atlantic Mexico MEXU 1 Total 88 Table 1‐1. continued

N. Subgenus Taxon Oceanic region Locality DNA voucher Sequence method 1 Canavalia C. rosea (Sw.) DC. Indian Ocean South Africa Umdloti 98 Cloning 2 Tanzania Dar es salaam 184 Cloning 3 Sri Lanka Wattala, Negambo 31 Cloning 4IndonesiaSumatra500Direct 5 Australia Headland Harbour 1 Direct 6 West Pacific Marquises Taipivai, Nuku Hiva 31 Direct 7TongaSopu171Direct 8 East Pacific Mexico Sinaloa 965 Direct 9 Panama Veracruz 202 Direct 10 Ecuador Isla Jambel 1205 Direct 11 West Atlantic Panama Cuango, Colon 110 Direct 12 Panama Pina, Colon 24 Cloning 13 Costa Rica Puerto Viejo 346 Cloning 14 Mexico Coatzcoalcos 71 Cloning 15 Brazil Gaibu Pernanbuco 70 Cloning 16 East Atlantic Senegal Joal-Fadiout 107 & 118 Cloning 17 Ghana Busua beach 5 Direct 18 Angola Musul, Luanda 0 Cloning Subtotal 19 19 C. cathartica Thouars Pacific Philippine Atimona CH10 Cloning Subtotal 1 20 C. lineata (Thunb.) DC. Pacific Taiwan Maopi Tao CL1 Direct 21 Japan Miyazaki 74 Cloning Subtotal 2 22 C. sericea A. Gray Pacific Tonga Haashini-Lavengatonga 42 Direct 23 Pacific Tonga Haashini-Lavengatonga 138 Cloning Subtotal 2 24 C. virosa (Roxb.) Wight & Arn. Atlantic Africa Seed purchased S3F8 Direct 25 Maunaloa C. hawaiiensis Degener & al. Pacific Hawaii Bishop Museum 6 Clonig 26 C. galeata Gaudich. Pacific Hawaii Bishop Museum 7 Clonig 27 C. kauaiensis J.D. Sauer Pacific Hawaii Bishop Museum 9 Clonig 28 C. molokaiensis Degener & al. Pacific Hawaii Bishop Museum 4 Clonig 29 C. napaliensis St. John Pacific Hawaii Bishop Museum 5 Clonig 30 C. pubescens Hook. & Arn. Pacific Hawaii Bishop Museum 8 Clonig 31 C. hawaiiensis Degener & al. Pacific Hawaii Center for Conservation Research and Training (CCRT) C6 Direct 32 C. galeata Gaudich. Pacific Hawaii Center for Conservation Research and Training (CCRT) C7 Direct 33 Catodonia Canavalia parviflora Benth. Atlantic Brazil Jardim Botanico (Rio de Janeiro) 809 Direct 34 Wenderothia Canavalia villosa Benth. Atlantic Mexico MEXU 23 Direct 35 Canavalia hirsutissima J.D. Sauer Atlantic Mexico MEXU 11 Direct Total 36 Table 1‐2 List of Canavalia samples used for nrDNA ITS phylogenetic analyses.

Primer name Length (bp) Primer Pairs Sequence (5'- 3') Annealing Tm. Source atpB -rbcL IGS 518-742 atpB GTGGAAACCCCGGGACGAGAAGTAGT 52 °C Hodges and Arnold, 1994 rbcL ACTTGCTTTAGTTTCTGTTTGTGGTGA Hodges and Arnold, 1994 ndhD -ndhE 670 ndhD GAAAATTAAGGAACCCGCAA 48 °C Xu et. al 2000 ndhE TCAACTCGTATCAACCAATC Xu et. al 2000 psbA -trnH IGS 264-338 psbA CGAAGCTCCATCTACAAATGG 48 °C Hamilton 1998 trnH ACTGCCTTGATCCACTTGGC Hamilton 1998 rps16 Intron 781-850 rps16 F GTGGTAGAAAGCAACGTGCGACTT 52 °C Oxelman et al., 1997 rps16 2R TCGGGATCGAACATCAATTGCAAC Oxelman et al., 1998 trnD -trnT 1036-1055 trnD ACCAATTGAACTACAATCCC 52 °C Demesure et al. (1995) trnT CTACCACTGAGTTAAAAGGG Demesure et al. (1995) trnK 2485-2532 trnK 1L CTCAATGGTAGAGTACTCG 52 °C Lavin et al. (2000) trnK 685F GTATCGCACTATGTATCATTTGA Wojciechowski et al. (2004) matK 789R TAGGAAATCCTGGTGGCGAGATC Hu et al. (2000) matK 1777L TTCAGTGGTACGAAGTCAAATG Hu et al. (2000) matK 1932R CAGACCGACTTACTAATGGG Hu et al. (2000) trnK 2R AACTAGTCGGATGGAGTAG Johnson & Soltis (1994) nrDNA ITS 674 ITS5 GGAAGTAAAAGTCGTAACAAGG 54 °C White et al. 1990 ITS4 TCCTCCGCTTATTGATATGC White et al. 1990

Table 1‐3 List of primers used for amplifications and sequencing of chloroplast regions. PCR amplification primers are shown in bold.

Figure 1‐1. Canavalia rosea and its related species. A: Canavalia rosea, B: C. cathartic, C: C. lineata, D: C. sericea, E: C. ensiformis, F: C. gladiata. G: C. villosa, H: C. pubescens,I: seed of C. ensiformis (1), C. gladiata (2), C. rosea (3), C. lineata (4).

Figure 1‐2. A: Distribution range of PPSS species. B: Distribution range of Canavalia rosea and its related species. In each of the encircled areas, C. rosea, C. cathartica, C. lineata and C. sericea are distributed in the coastal areas and the members of subgenus Maunaloa are distributed in inland areas.

Figure 1‐3. Phylogram of strict consensus tree of 16112 shortest tree based on Maximum Parsimony (MP) analysis from 6 cpDNA regions with ca. 6000 bp for Canavalia species (Tree length=145, CI= 0.862, RI= 0.807 and RC= 0.696). Bootstrap values are shown above branches. Canavalia hirsutissima and Canavalia villosa from subgenus Wenderothia and Canavalia parviflora from subgenus Catedonia are defined as outgroups. Twenty seven haplotypes (H1‐29) were detected for C. rosea and its allied species. Abbreviations in parenthesis are: P (Pacific Ocean); A (Atlantic Ocean); I (Indian Ocean); Numbers in the localities correspond to the number of sequenced individuals in that locality.

Figure 1‐4. The Bayesian phylogram using 80 samples of Canavalia rosea and other species based on concatenate cpDNA data set. Support for nodes is estimated from Bayesian posterior probabilities. Support values ≥70% is given. The legends are as follows: P (Pacific Ocean); A (Atlantic Ocean); I (Indian Ocean).

Figure 1‐5. Phylogram of strict consensus tree of 28 shortest tree based on Maximum Parsimony (MP) analysis from nrDNA ITS for members of subgenus Canavalia and Maunaloa (bold) (Tree length=92, CI= 0.9457, RI= 0.9920 and RC= 0.9381). Bootstrap values are shown near branches. Canavalia hirsutissima and Canavalia villosa from subgenus Wenderothia are defined as outgroups. Abbreviations in parenthesis are DNA voucher numbers. Letters A and P correspond to Atlantic and Pacific Oceanic regions, respectively.

Figure 1‐6. Strict consensus tree resulting from combined cpDNA and ITS sequence data for members of subgenus Canavalia and Maunaloa (bold). Numbers near branches indicate bootstrap values. Canavalia hirsutissima and Canavalia villosa from subgenus Wenderothia are defined as outgroups. Abbreviations in parenthesis are DNA voucher numbers. Letters A and P correspond to Atlantic and Pacific Oceanic regions, respectively.

Figure 1‐7. Haplotype network among Canavalia rosea and its related species based on statistical parsimony method. Each segment of branch shows the one step difference of molecular data. C. rosea has the greatest diversity of haplotypes

in the Atlantic region than Pacific and Indian Ocean. Hawaiian endemic species are more closely related to a haplotype from the Atlantic (Panama‐ Angola) which may suggest that these species are diversified from Atlantic before closure of Panama Isthmus.

CHAPTER 2

GLOBAL GENETIC STRUCTURE OF CANAVALIA ROSEA; EVIDENCE

FROM CHLOROPLAST DNA SEQUENCES

2-1 Introduction Gene flow is considered as a main factor responsible for genetic cohesion among populations of a species (Olmstead & Palmer, 1994). In fact, when levels of gene flow within and among populations become high (e.g. greater than four migrants per generation), it homogenize the species and prevents genetic divergence of populations; otherwise local populations can evolve and eventually form a distinct species (Wright, 1931; Ennos, 1994; Bohonak, 1999). Population differentiation can also results from environmental impediments or intrinsic barriers (Avise, 2000). Therefore sufficient amount of genetic exchange among populations is expected to hold a species as a cohesive unit in spatially continuous populations.

Populations of many plant species are spatially isolated from each other due to presence of physical or ecological barriers such as land masses or water barriers (Cain et al., 2000). As a result, the distribution range of many plant species are structured to the specific localities like Indo West Pacific (IWP) and Atlantic East Pacific (AEP) in some plant species such as mangroves (Duke et al.,

2002; Nettel & Dodd, 2007) and PPSS such as Hibiscus tiliaceus (Takayama et al., 2006). In H. tiliaceus, PCR-SSCP (PCR amplification with single-strand conformation polymorphism) and PCR-SSP (PCR amplification with sequence specific primers) analyses performed on more than 1100 samples from 65 populations worldwide to illustrate genetic structure of populations in very wide distribution range. The results revealed that gene flow occurred among populations of H. tiliaceus in Indo-West Pacific region and also over the African continent due to sea-drifted seeds and introgression was happened between H. tiliaceus and H. pernambucensis populations in the Atlantic region. On the other hand, the American continent was the barrier to gene flow through sea- drifted seed dispersal among populations of H. pernambucensis (Takayama et al., 2006; Takayama et al., 2008). These results suggest the importance of gene flow through sea-drifted seeds over the barriers to keep the unity of the species and also the role of American continent as a strong barrier to gene flow. For globally distributed single PPSS such as C. rosea the existence of these barriers seems to be critical to keep gene flow over its distribution range as the possibilities of cryptic species would be expected.

Presence of cryptic species is popular in many plants species where morphological diversification might not be happened among lineages. In chapter 1, the result of phylogenetic analyses detected some distinct haplotypes which were specific to the Atlantic region (clade II, Fig. 1-3). As discussed in chapter 1, usually when there is such kind of sharp geographic boundary between widely distributed clades, it is assumes that it might be a result of geographic barriers to dispersal or possibility of cryptic species boundaries (Irwin & Gibbs, 2002). However, gross population data is necessary

to infer the existence of gene flow over African and American continents to keep the unity of C. rosea in distant populations. Therefore, the main question targeted in this chapter is: How can a single species keep gene flow over the extremely wide range of distribution?

A variety of genetic markers can be used to quantify the gene flow through seed dispersal. As discussed by Parker (1998), Ouborg (1999) and others, these markers include allozymes, DNA sequences, microsatellites, restriction fragment length polymorphisms (RFLPs), and DNA randomly amplified from the genome (e.g., RAPDs and AFLPs). Many plants species exchange genes among populations by the movement of pollen and seed. Only dispersal via seed directly bears on colonization of new populations. Movement of both pollen and seed, however, leaves a genetic signature within and among populations. Therefore, estimating gene flow among plant populations from nuclear DNA, which is transferred via pollen and seed, may tend to overestimate seed dispersal (Cain et al., 2000). Because of this effect, estimation of the seed dispersal requires appropriate markers inherited only through seeds. In most angiosperms, chloroplast DNA (cpDNA) is regarded as single locus and maternally inherited through seeds (Corriveau & Coleman, 1988; Mogensen, 1996). So, it has been utilized to discover phylogenetic and phylogeographic patterns in many plant species (Schaal et al., 1998; Petit et al., 2005; Soltis et al., 2006; Avise, 2009). On the other hand, uniparentally inherited markers such as cpDNA may be informative at the interspecific and intraspecific level (Wakeley, 2003).

There are many statistical methods for retrieving information from molecular markers to reveal evolutionary relationships among species and

estimating important population parameters (Excoffier & Heckel, 2006). A variety of analytical methods exists to estimates gene flow through seed dispersal such as FST-based methods (Wright, 1951), Likelihood-based methods (Rannala & Hartigan, 1996) and Coalescent-based methods (Beerli & Felsenstein, 1999). Although the latter rely on more realistic parameters than the others (Kuhner, 2009).

For this purpose, I employed molecular markers using short fragments of 6 cpDNA regions and performing population genetic analysis in global scale.

Population genetic analyses based on pairwise FST and coalescent-based methods, were conducted for 515 individuals from 48 populations using more than 2000 bp nucleotide sequences to elucidate the spatial genetic structure of C. rosea populations in its entire distribution range.

2-2 Materials and Methods

Sampling Leaf samples were collected in large-scale, covering almost all distribution ranges of the species. In total, 436 individuals (37 populations) from Canavalia rosea, 25 individuals (5 populations) from C. cathartica, 42 individuals (4 populations) from C. lineata, and 12 individuals (2 populations) from C. sericea were included in this study (Table 2-1). Voucher specimens were deposited in the herbarium of University of the Ryukyus (RYU), Jardim Botânico, Rio de Janeiro (RBRJ) and Bishop Museum, Honolulu, Hawaii.

DNA extraction, PCR, and sequencing DNA extraction, PCR and sequencing methods are same as described methods in chapter 1.

Haplotype Composition and Network of C. rosea and its allied species In chapter 1, I surveyed more than 6000 bp cpDNA sequences for Canavalia samples from wide range of distribution. As sequencing of more than 6000 bp of cpDNA genome for all population samples (515 individuals) is required extra labor and cost, I targeted partial sequences of 6 cpDNA regions (Table 2-2) based on the results of phylogenetic analyses (cf. chapter 1). Several new internal primers were designed for these 6 short fragments and in total

2012 base pairs were sequenced for all individuals. Sequences were edited and aligned as chapter 1 and haplotype composition of each population was recorded. The haplotypes frequency of populations was presented as pie charts on the world map. The genealogical relationships of haplotypes were constructed with TCS program (Clement et al., 2000) using statistical parsimony method with 95% confidence interval (Templeton et al., 1992). For population analyses, all populations of C. rosea were divided into five regional groups (West-East Atlantic Ocean, Indian Ocean and West-East Pacific Ocean) based on geography, phylogenetic results (cf. chapter 1) and observed haplotypes. Populations of C. cathartica, C. lineata and C. sericea were excluded from all population analyses.

Population differentiation To compare chloroplast genetic diversity among population of five oceanic regional groups, I calculated numbers of haplotypes (H), polymorphis site (S), Haplotype diversity (Hd) and nucleotide diversity (π) using the program DnaSP version 5.10 (Librado & Rozas, 2009). To determine the amount of genetic differentiation among populations of C. rosea, F-statistics (FST) analysis (Wright, 1951) performed by the program AREQUIN v. 3.11 (Excoffier et al., 2005).

Pairwise FST was calculated following the method of Weir & Cockerham (1984) and statistical significance was assessed using 1000 permutations. An exact test of population differentiation was performed to examine the null hypothesis of the random distribution of haplotypes across populations (Raymond & Rousset, 1995).

To clarify groups of C. rosea populations which are geographically homogeneous and maximally differentiated from each other, spatial analysis of

molecular variance (SAMOVA; Dupanloup et al. 2002) was conducted. To ensure that the conformation of the groups (K) is not affected by the given initial conditions, the simulated annealing procedure is repeated 100 times (Dupanloup et al., 2002). The analyses were repeated for user-defined groups (K) from 2 to 12, and the highest FCT values was maintained as the best grouping of populations in case there are not included single population (Heuertz et al., 2004). Because SAMOVA analysis uses locality coordination and sampling scale in this study cover the whole equatorial belt, arbitrary coordinates were tried to avoid miscalculation of analyses.

Historical migration rates between oceanic regions To assess migration rates, direction of gene flow and genetic diversity among populations of C. rosea, I applied coalescent approach (Kingman, 1982a, b) using the Maximum likelihood and Bayesian inference methods implemented in MIGRATE-N version 3.1.3 (Beerli & Felsenstein, 1999; 2001; Beerli, 2008). Coalescent based genealogies provide more realistic estimates of population parameters than other summary statistics methods (Kuhner, 2009). I was specifically interested in contrasting the migration rate and direction of gene flow between geographic regions rather than between sampled populations. Hence, all populations were pooled into five regional groups (West-East Atlantic Ocean, Indian Ocean and West-East Pacific Ocean). Given the linear distribution of C. rosea at coastal lines, the stepping stone migration model with asymmetric rates was employed (Kimura & Weiss, 1964).

For each of the five regional groups, the genetic diversity (θ=Neμ, where Ne is the effective population size and µ is the mutation rate per site per generation), pairwise migration rate (M=m/μ, where m is the rate of migration

for each locus) and number of migrants per generation (Nm=Mθ) were estimated. Starting parameters for migrant values and θ were generated from

FST calculation. For Maximum likelihood analysis, 20 short chains (length 5.0 x 104) followed by 5 long chains (length 5.0 x 105) with sample increment of 100 and for both run were conducted and the first 15000 generations were discarded as burn-in at the beginning of each chain. An adaptive heating scheme with 4 chains and a swapping interval of 1 was applied. Maximum likelihood estimates (MLE) were verified with three replicate Markov Chain Monte Carlo (MCMC) simulation runs to ensure convergence of similar values for θ.

Bayesian MCMC coalescent modeling were also used which is provide parameter estimates based on full likelihood estimation and decreased computation time of approximation comparing to Maximum likelihood estimates. Bayesian parameters included an update frequency of 0.5, a Metropolis-Hastings sampling algorithm for both θ and M; uniform priors were placed on θ from 0 to 0.001 and M from 0 to 50000. Starting parameters for migrant values and θ were generated from FST calculation. An adaptive heating scheme with 4 chains and a swapping interval of 1 was applied. I used the Felsenstein 84 model of evolution, and set the transition to transversion ratio to 2 as a default values in the program. Six independent MCMC runs of varying length and burn-in were conducted which produced similar results. Hence, I present results from the longest run which consisted a long chain of 50 million steps with sample increment of 100 and the first 5 million steps were discarded as burn-in. Using tracer v1.5 (Rambaut & Drummond, 2009) convergence of the likelihood in MCMC chains and effective sample size (ESS) observed

following the burn-in. The analyses were considered as converged upon a stationary distribution, if the different runs generated similar posterior density distributions with a minimum ESS of 100 (Hey, 2005; Kuhner & Smith, 2007).

Estimates of recent migration rates Although estimating of gene flow and migration rates using MIGRATE-N based on coalescent methods have many advantages comparing to the other conventional methods, it also has drawback in separation of recurrent gene flow from ancestral polymorphism (Carbone et al., 2004; Brito, 2005; Bowie et al., 2006; Kane et al., 2009). To distinguish whether the estimated migration rates from MIGRATE-N are the result of the retention of ancestral polymorphism or recent gene flow, additional coalescent based analyses were conducted using the program MDIV which is implements both likelihood and Bayesian methods using MCMC coalescent simulations for jointly estimating of the θ and M (Nielsen & Wakeley, 2001).

Theta and M for pairwise comparisons of each of the five oceanic regional groups were estimated. Uniform prior Values for Mmax (maximum value for the scaled migration rate) and θ was set to the 10 and zero, respectively. The program ran under the default finite sites mutation model of HKY (Hasegawa et al., 1985); with Markov chain simulation for 5000000 steps, where the first 500000 were discarded as burn-in. Multiple runs with different random seeds and prior distributions were conducted to determine if the analyses were reached to the convergence in the mode of the posterior distribution (Nielsen & Wakeley, 2001).

2-3 Results

Haplotype Composition and Network of C. rosea and its allied species

For population analyses 2012 bp aligned sequences were attained using partial sequence of 6 cpDNA regions which is including 12 substitutions, 2 indels and one inversion (Table 2-3). Through 21 haplotypes (H1-21) which were detected in chapter 1 by full sequence of 6 cpDNA regions among samples of four species (C. rosea, C. lineata, C. cathartica and C. sericea), I detected 17 haplotypes (H1-17) by partial sequences at population level (Fig. 2-1; Table 2- 1). Four haplotypes, H18 and H19-21 of phylogenetic analyses (chapter 1) could not be detected by partial sequences and therefore they are identical to haplotypes H16 and H7 in population analyses (this chapter), respectively. Haplotype network based on full sequence length were shown in figure 2-1. Colors in the network correspond to the haplotypes which could detect by partial sequence of 6 short fragments (H1-17). All haplotypes were shared among C. rosea populations except haplotype H2 which is exclusive to C. cathartica and C. sericea populations from Pacific Ocean (n= 18; Fig. 2-2; Table 2-1). A major haplotype (H8) was shared among C. rosea, C. lineata and C. cathartica populations from Indian and Pacific Oceanic regions (n=293), (Fig. 2- 2). Notably, all samples of C. lineata (n=42) have an identical haplotype with C. rosea haplotype (H8), however, C. cathartica shares haplotypes with C. rosea (H8, n=19) and with C. sericea (H2, n=6). Another major haplotypes of C. rosea were found in Atlantic and Indian Oceanic region including H7 (n=45), H6 (n=32), H17 (n=29) and H16 (n=25), respectively (Table 2-1). Haplotype H1 (n=7) shared between a population from southern Brazil (n=1) and Panama (n=6) in Atlantic Ocean. Haplotype H3 shared between a population from

Mexico (n=2) and Senegal (n=7) in Atlantic Ocean; haplotype H4 shared between 2 populations from Mexico (Nayarit and Sinaloa, n=9) in Pacific Ocean and haplotypes H5, H9-15 are private haplotypes (haplotypes which is found only in one population) in oceanic regions (Fig. 2-2; Table 2-1).

Population differentiation Total haplotype diversity (Hd) and nucleotide diversity (π) within C. rosea populations were estimated to be 0.69124 and 0.00086, respectively (Table 2-4). The populations at West Atlantic and East Atlantic had the highest haplotype diversity (0.7809 and 0.74.34, Table 2-4) and populations of the West Pacific Ocean share a lowest haplotype diversity and nucleotide diversity (0.03418 and

0.00002, respectively). Pairwise FST analysis detected genetic differentiation in 6 out of 10 pairs of C. rosea populations (5 regional groups) from different oceanic regions (Table 2-5). The FST values between the West and East Atlantic, Indian and West Pacific and between West and East pacific populations were

0.13, 0.19 and 0.16 respectively. The FST value between the Indian Ocean and

East pacific was 0.08. On the other hand the FST values between the East Atlantic and Indian and between East Pacific and West Atlantic and between and East pacific populations were 0.36 and 0.45 respectively. All differentiations were significant using an exact test (P < 0.05; Table 2-5).

The results of SAMOVA are shown in figure 2-3 and Table 2-6. The SAMOVA method did not allow to unambiguously identifying the groups of populations (K) displaying the highest differentiation among groups, FCT. This was because FCT values increased progressively as K was increased, reaching a plateau at K = 8 (Fig. 2-3). The number of K which has highest FCT without single population was K=3 which is divide all populations to three groups

(Table 2-6). First group comprise populations from Ghana, Mexico (A), Panama (colon2), Para and Senegal. Second group includes populations from Pernambuco, Rio De Janeiro (1 and 2) and Java and the last groups corresponds to the rests of populations (Table 2-6). The composition of these three groups is partially corresponding to the geographical distribution of haplotypes visually identified on the haplotype frequency map (Fig. 2-2). From K=4 to K=10 all groups includes at least single population (populations which have private haplotypes) which is not appropriate to the analysis (Heuertz et al., 2004).

Historical migration rates between oceanic regions Coalescent-based maximum likelihood estimates (MLE) from MIGRATE-N indicate asymmetric gene flow along the distribution range of the C. rosea populations (Table 2-7). The MLE showed that genetic diversity was highest in the West Atlantic region (θ = 0.0163), and lowest in the West Pacific region (θ = 0.0069). The most probable estimates of migration rates (M) ranged from 0 to 395.7, with the highest migration observed out of the East Atlantic into the West Atlantic. In contrast, estimates of migration in the both side of Panama Isthmus as well as into the Indian Ocean from the East Atlantic were zero (Table 2-7). Comparing with high migration rates between West-East Atlantic region and between Indian-West Pacific region, migration between the West and East Pacific was low but significantly greater than zero. The direction of migration was asymmetrical, with the West Atlantic region experiencing a greater input of polymorphism due to migration (MEA to WA = 395.7) than the East Atlantic (MWA to EA = 166.4). Based on values of M and θ, I calculated a mean probability of number of migrants per generation (Nm) among 5 regional groups (Table 2-7)

which the highest was greater than 8 migrant per generation within East-West Atlantic region and the lowest was zero between Western and eastern side of American continent and Indian region to the Atlantic region. The estimated number of migrants between Indian-West Pacific pairs and between West-East Pacific pairs were 5.5 and near 1, respectively.

Results of pairwise FST and MIGRATE-N among Indian and West Pacific

Oceanic regions show relatively low genetic differentiation (FST = 0.19, Table 2- 5) and high number of migrants (Nm >5 per generation), respectively (Table 2-

7). Rates of gene flow between West and East Pacific regions (FST = 0.16; Nm ≅ 1) were lower than that of between Indian and West Pacific which may consequence of very long distance between population in pacific Oceans.

Bayesian inference of theta and Migration rates among five groups are plotted on figures 2-4 and 2-5 respectively. Although Bayesian estimation of migration rates looks much bigger than Maximum likelihood estimation but in total estimates of number of migrants (Nm) are almost equal in ML and Bayesian estimation (see fig. 2-6 and Table 2-7). Highest number of migrants was from West Pacific to the Indian Ocean (Nm=10.98; fig. 2-6) and East Atlantic to West Atlantic region (Nm=9.01).

Estimates of recent migration rates Figure 2-7 shows the posterior distributions for migration rates (M) and mutation rates (θ) obtained from MDIV program among population of C. rosea at different regional groups. Results are interestingly comparable with the results of MIGRATE-N (Figs. 2-4, 2-5 and Table 2-7). For example, migration rates between East Atlantic and Indian Oceanic region and also between East

Pacific and West Atlantic region was definitely low among populations comparing to the populations at three other regional groups (Fig. 2-7). These results are concordant with MIGRATE-N results and reveal that observed gene flow within East and West Atlantic, Indo-West Pacific and also between West and East Pacific is likely result of recent gene flow than retention of ancestral polymorphism.

2-4 Discussion

Gene flow in Indo-Pacific Ocean through Long Distance Seed Dispersal Geographical variation of cpDNA haplotypes is expected to indicate gene flow through seed dispersal as chloroplast genome is maternally inherited (Mogensen, 1996). When seed-mediated gene flow frequently occurs among populations, distribution of cpDNA haplotypes will be homogeneous in spatial scale. Population genetic analyses (Fig. 2-2, Tables 2-4 and 2-5) show high levels of gene flow and low levels of population structure both within and between populations of C. rosea across Pacific and Indian Oceanic regions. The major haplotype of C. rosea (H8) has an extremely wide distribution range from South Africa in the West Indian Ocean to Panama in the East Pacific Ocean (Fig. 2-2). Results of Fst, MIGRATE-N and MDIV also show low genetic differentiation among Indian and West Pacific Oceanic regions (FST = 0.19) and high number of migrants (Nm > 5 per generation, Table 2-7), respectively.

Rates of gene flow between West and East Pacific regions (FST = 0.16; Nm ≅ 1) were lower than that of between Indian and West Pacific which may due to very long distance between populations in the Pacific Ocean. According to the theoretical thoughts such amount of migrants is enough to keep the unity of species in such long distances (>25000 kilometers).

If we consider the results of SAMOVA, the populations in the Atlantic region are differentiated from Indo-Pacific regions (table 2-6). In the number of K=3 (Table 2-6), populations of most of Atlantic and one population from Indian Ocean (Java) is grouped in two groups and rest of populations from Indo-Pacific regions are making an integrate group. The result of coalescent methods from MIGRATE-N and MDIV programs are also coherent with

SAMOVA results, as significant differentiation between Indo-Pacific oceanic regions was not detected. Hence, long distance dispersal of drifted seeds by oceanic currents appears to be the most probable explanation for the present distribution patterns of C. rosea haplotypes within Indo-Pacific oceanic. Overall, these results suggest that substantial gene flow occurs among populations of Indo-Pacific oceanic regions by sea-drifted seeds which are impermeable in water for years (Guppy, 1906; Thiel & Gutow, 2005).

Although overall haplotype diversity and population differentiation is very low between the West and East Pacific Oceanic region, however migration rates between these oceanic regions is low comparing to the other regions like between Indian and West Pacific region (Fig. 2-6, Table 2-7). A possible explanation to this outcome can be presence of very long distance between West and East Pacific populations which makes difficult dispersal of seeds by oceanic currents (Figs., 2-2, 2-6 and Table 2-7). Another interpretation can be the role of the East Pacific barrier in this region as similar results have seen in another PPSS, Ipomea pes-caprae (Wakita, unpublished) and Hibiscus tiliaceus (Takayama et al., 2006). Thus, land masses such as African and American continents not only could be barriers to the seed dispersal for C. rosea and also other PPSS but also Ocean currents itself are as intrinsic barriers to seed dispersal which naturally are main barrier to the terrestrial plants (Murray, 1986; Sauer, 1988; Cox & Moore, 2005; Thiel & Haye, 2006).

A strong genetic difference between the Indo-Pacific and Atlantic populations of C. rosea The results of phylogenetic (chapter 1) and population genetic analyses clearly exhibit genetic structure in the populations of Atlantic region even very limited gene flow have occurred between the Atlantic and Indian Oceanic region (H6 shared between Brazil and Tanzania populations, Figs. 2-1 and 2-2).

Pairwise FST analysis revealed presence of genetic differentiation between the

West Atlantic and East Pacific region (FST = 0.45) and between the East Atlantic and Indian Oceanic region (FST = 0.36). Results of migration analyses also unveil that migration to the in and out of Atlantic region is restricted except some migrants from East Atlantic to the Indian Ocean (Nm=1.6; see Table 2-7). These results confirm that African and American land masses are geographical barriers to gene flow through seed dispersal by oceanic currents among C. rosea populations, as observed in another PPSS Hibiscus tiliaceus (Takayama et al., 2006) and Ipomea pes-caprae (N. Wakita, unpublished) and also in mangrove species (Dodd et al., 2002; Duke et al., 2002; Nettel & Dodd, 2007).

Inference of patterns of current or historical gene flow from gene genealogies seems straightforward when there is a sharp geographic boundary between two widely distributed clades (Irwin & Gibbs, 2002). Usually, researchers assume that such boundary is the result of geographic barriers to dispersal or cryptic species boundaries. The haplotypes H16-18 are specific to Atlantic region with high probability support and Long Branch length (Fig. 2-1). Although possibility of cryptic species cannot be completely rejected and the populations in the African Oceanic regions are not kind of allopatric populations, I considered that long-term geographic barrier to dispersal is

responsible to such kind of phylogeographic break in the Atlantic Ocean (Fig. 2-2).

Directional gene flow within Atlantic region was suggested by MIGRATE- N; as migration rates from the East to the West Atlantic were two times larger than vice versa (MEA to WA= 395.65; MWA to EA= 166.42). These results might correspond to the variation of the strength of tropical Atlantic’s major currents which regarded as transatlantic dispersal in Atlantic region (Renner, 2004). Chloroplast DNA sequences detected highly differentiated populations of C. rosea in southern Brazil (H6, Fig. 2-2). Although there are no known barriers, the bifurcating status of the South Equatorial Current at the north-eastern horn of Brazil to the northward and southward (Fratantoni et al., 2000; Renner, 2004), appears to be potential barrier to gene flow. These opposite ocean current directions may promote the genetic differentiation of the C. rosea populations in southern Brazil which is also the case in H. pernambucensis populations (Takayama et al., 2008).

Overall, same haplotypes are distributed in the all range of Indo-Pacific regions and also over Africa (Fig. 2-2). Similar results also were found in other PPSS such as Hibiscus tiliaceus and H. pernambucensis (Takayama et al., 2006; Takayama et al., 2008) and Ipomea pes-caprae (N. Wakita, unpublished). The results suggested that this kind of haplotype distribution patterns was occurred due to long distance dispersal of sea-drifted seeds which keep the unity of these species over such a long distances. However, additional data using molecular markers is necessary to assess the possibility of cryptic species in the Atlantic region for C. rosea populations and also verify presence of the gene

flow over Isthmus of Panama which was restricted by sea-drifted seed dispersal according to the cpDNA sequence results.

2-5 Conclusion

Chloroplast DNA sequence revealed that frequent gene flow through long- distance seed dispersal occurs over the Pacific and Indian Oceanic regions and also within Atlantic region. Chloroplast DNA sequence also revealed partial gene flow has detected between Atlantic and Indian oceanic regions which suggest that the unity of the species in global scale is kept by long distance seed dispersal by ocean currents. The results detected highly differentiated populations of C. rosea overall Atlantic region. This suggests that African and American land masses played as geographical barriers to gene flow by sea- dispersal.

Gene flow across the extremely wide distribution range of C. rosea was kept by long distance seed dispersal through oceanic currents. In terms of long distance dispersal, this scale of gene flow from such widely distributed range of plant species is a new and unique case. And it shows the significance of long distance seed dispersal to keep species integration in worldwide distributed populations.

Although sea currents enable gene flow over the global distribution range of plants with sea-drifted seeds, our study detected highly differentiated populations in southern Brazil which might be the result of bidirectional current of South Equatorial Current. Finally, the results provide good evidence for transatlantic long-distance seed dispersal by sea currents in Atlantic region. Seed dispersal prevented in the Isthmus of Panama and caused a distinct genetic difference in the cpDNA haplotype distribution between the Pacific and Atlantic populations of C. rosea.

Taxon Oceanic Region Locality N. C. rosea (Sw.) DC. H1 H2 H3 H4 H5 H6 H7 H8 H9 H10 H11 H12 H13 H14 H15 H16 H17 Indian Ocean South Africa Umdloti ‐29.67 31.12 22 8 14 Tanzania Dar es salaam ‐6.82 39.32 25 4 21 Sri Lanka Wattala, Negambo 6.97 79.89 11 10 1 Thailand Phuket, Kmala Beach 7.99 98.29 10 10 Indonesia Bali ‐1.08 100.42 33 Java ‐8.73 115.17 10 10 Sumatra ‐2.91 104.71 10 10 Australia Darwin ‐12.44 130.83 10 10 Headland Harbour ‐20.31 118.58 10 10 West Pacific Thailand Kho Samui 9.51 100.06 99 Taiwan Houpihu 38.99 117.56 15 15 Singapore Singapore 1.35 103.99 99 Philippine Quezon, Luzon 16.44 120.33 10 10 Australia Queensland ‐16.73 145.66 10 8 2 Japan Iriomote 24.40 123.76 15 15 New Caledonia Plage de poe ‐21.61 165.39 10 10 Fiji Korotogo ‐18.17 177.54 88 Tonga Sopu ‐21.13 ‐175.21 10 10 Samoa Samoa ‐13.86 ‐171.71 10 10 Marquises Taipivai, Nuku Hiva ‐8.93 ‐140.09 10 10 East Pacific Mexico Nayarit 21.58 ‐105.28 10 5 5 Sinaloa 25.44 ‐108.73 44 Oaxaca 15.94 ‐97.42 10 10 Costa Rica Jaco Beach 9.61 ‐84.63 11 11 Panama Veracruz 8.89 ‐79.62 10 10 Ecuador Isla Jambel 0.74 ‐79.20 10 10 West Atlantic Mexico Coatzcoalcos 18.14 ‐94.41 10 2 8 Costa Rica Puerto Viejo 10.75 ‐83.56 55 Panama Pina, Colon 1 9.28 ‐80.05 10 7 2 1 Cuango, Colon 2 9.55 -79.31 10 6 4 Brazil Para ‐1.32 ‐46.40 11 74 Pernanbuco ‐8.34 ‐34.95 10 10 Rio De Janeiro 1, Arraial do Cabo ‐22.97 ‐42.03 10 10 Rio De Janeiro 2, Recreio ‐23.02 ‐43.44 91 8 East Atlantic Senegal Joal-Fadiout 14.17 ‐16.85 31 7 3 4 17 Ghana Busua beach 4.96 ‐1.73 18 5 10 3 Angola Musul, Luanda ‐8.95 13.06 30 30 Subtotal 4367 0 9 9103245232510141 2 4 2 2529 C. cathartica Thouars Pacific Philippine Atimona 10 10 Samoa Samoa 2 2 Tonga Tonga 5 5 Tahiti Tahiti 1 1 Hawaii Kauai 7 7 Subtotal 25 6 19 C. lineata (Thunb.) DC. Pacific Taiwan Maopi Tao 11 11 Japan Ishigaki 11 11 Miyazaki 10 10 Ogasawara 10 10 Subtotal 42 42 C. sericea A. Gray Pacific Tonga Haashini-Lavengatonga 10 10 Hawaii Maui, Bishop Museum 2 2 Subtotal 12 12

Table 2‐1. Chloroplast DNA haplotype composition and coordinates of populations for our study group. Haplotypes ranged from H1 to H17 and N, number of samples in each population.

Primer name Length (bp) Primer Pairs Sequence (5'- 3') Source atpB partial 590 atpB-146 TTGGTACCATCCAACCAATTC This study ndhD partial 396 ndhD ACATCCGTCCCAAGGTATCA This study ndhE CAACTCGTATCAACCAATCGAA This study psbA 250 psbA CGAAGCTCCATCTACAAATGG Hamilton 1998 rps16 partial 186 rps16-610 CCTTTGAGTTATCGGGTTGC This study trnK 5' flanking 250 trnK5' F GAATGGAAAAAGTAGCATGTCG This study trnK5' R TGCGATACGATCAAAACAGG This study trnK 3' flanking 340 trnK3' F AAAGGTCGGATTTGGTATTTAGA This study trnK3' R TCCTGAATCCCAACTCTTATTACAT This study

Table 2‐2. List of primers used for sequencing of chloroplast regions in population samples. PCR amplification primers are shown in table 1‐2.

atp B‐rbc L ndh D‐ndh E psb A‐trn H rps 16 trn K 5' trnK 3' Taxon Population's Haplotype frequency haplotypes 256 510 267 644 23 155 183 308 682 733 748 155 156 2211 2290 C. rosea C1 7 C G G C0AT2=0TTTC G A C. catharca, C. sericea C2 18 T ...... 2= 0 C ... T . C. rosea C3 9 T ...... 2= 0 . C .. . . C. rosea C4 9 T . A ....2= 0 ...A .. C. rosea C5 10 T ...... 2= 0 ..GA T T C. rosea C6 32 T ...... 2= 0 ...AT T C. rosea C7 45 T ...... 2= 0 ...... C. rosea, C. lineata, C. catharca C8 293 T ...... 2= 0 .... T . C. rosea C9 5 T ..T .. .2= 0 ...... C. rosea C10 10 T ....T . 2= 0 .... T . C. rosea C11 14 T ...1$ ..2= 0 .... T . C. rosea C12 1 T ...... 2+ 0 . C .. . . C. rosea C13 2 T ...... 2+ 0 .... T . C. rosea C14 4 T .....G2+0 ...... C. rosea C15 2 T .....G2=0 . C .. . . C. rosea C16 25 TT ....G2=0 ...... C. rosea C17 29 TT ....G2=1# ...... $ AAAAT; = AGA; + TCT; # TTATT

Table 2‐3. Variable sites of short fragments of 6 cpDNA regions used to determine haplotypes in Canavalia rosea and its related species populations. Dots (•) indicate that character states are same as for C. rosea haplotype C1. Numbers (0, 1 and 2) in sequences indicate indels, with ‘0’ indicating absence, ‘1’ presence and ‘2’ inversion.

Regions N (h) (S) (Hd) (π) West Atlantic 75 7 8 0.7809 0.0014 East Atlantic 79 6 6 0.74034 0.00087 Indian Ocean 111 6 8 0.5507 0.00053 West Pacific 116 2 1 0.03418 0.00002 East Pacific 55 2 3 0.27879 0.00042 Total 436 16* 14 0.69124 0.00086 *, number of haplotypes shared between C. rosea populations

Table 2‐4. Number of haplotypes (h), Polymorphic sites (S), Haplotype diversity (Hd), Nucleotide diversity (π).

IN WP EP WA EA

IN 0 0.1967 0.0826 0.3331 0.3605

WP 0.1967 0 0.1684 0.6454 0.6577

EP 0.0826 0.1684 0 0.4518 0.47

WA 0.3331 0.6454 0.4518 0 0.1309

EA 0.3605 0.6577 0.47 0.1309 0

Table 2‐5. Pairwise FST comparison between 5 geographic regions. All differentiations are significant using an exact test (P < 0.05). (WA: West Atlantic, EA: East Atlantic, In: Indian Ocean, WP: West Pacific, EP: East Pacific).

00.77158 10 KFCT (P < 0.05) 0.76322 9 0.76387 8 0.75362 7 .31 eioNyMxc-i Java (I) Mexico-Nay Mexico-Sin 0.73819 6 0.71847 5 0.68682 4 0.67019 3 0.57801 2 South Africa (A) Africa South Angola (A) Angola Panama-A2 Darwin (I) Darwin Java (I) Java Mexico-Sin (P) Mexico-Sin Senegal (A) Para Panama-A2 (A) Mexico (A) Ghana Senegal (A) Para (A) Panama-A2(A) (A) Mexico (A) Ghana 45678910123 Grouping Table

2 al., the ‐ 6.

2002) grouping Fixation Angola (A) Angola Panama-A2 Darwin (I) Mexico-Nay Mexico-Sin Java (I) Java Mexico-Nay Mexico-Sin (I) Darwin Panama-A2 Darwin (I) Mexico-Nay Mexico-Sin Java Java (I) Mexico-Nay Mexico-Sin Darwin (I) Mexico-Nay Mexico-Sin Java (I) Java Mexico-Sin Mexico-Nay Panama-A2 Para Senegal (A) Mexico(A) (A) Ghana Para Senegal (A) Panama-A2 Panama-A1 Mexico (A) (A) Ghana Java (I) RDJaneiro2 RDJaneiro1 Pernanbuco Rests

indices

a indicate

function Senegal (A) Panama-A2 Panama-A2 Para Senegal (A) Mexico(A) (A) Ghana Mexico-Sin Panama-A1 Costa-A Angola (A) Java (I) RDJaneiro2 RDJaneiro1 Pernanbuco Rests

(FCT)

the

newly of the

user

rosea

separated awn()Mxc-a eioSnJv I Costa-A Panama-A1 Java (I) Mexico-Nay Mexico-Sin Darwin (I) Panama-A2 Para Senegal (A) Mexico(A) (A) Ghana Panama-A1 Costa-A Angola (A) RDJaneiro2 RDJaneiro1 Pernanbuco Rests ‐ defined

population

populations

number Para Senegal (A) Ghana (A) Mexico(A) Panama-A1 Costa-A (A) Angola RDJaneiro2 RDJaneiro1 Pernanbuco Rests

groupings

groups

given obtained Costa-A Panama-A1 Panama-A1 Angola (A) Costa-A RDJaneiro3 RDJaneiro1 Pernanbuco Rests

level

populations.

from

K. Senegal (A) Para Ghana (A) Mexico(A) RDJaneiro3 RDJaneiro1 Pernanbuco Rests

SAMOVA

Bold

(Dupanloup populations Para Para Mexico(A) (A) Ghana RDJaneiro2 RDJaneiro1 Pernanbuco Rests RDJaneiro2 RDJaneiro1 Pernanbuco Rests

et in

Rests

0.05 MLE 0.95 Nm

θWA 0.0133 0.0163 0.0202

θEA 0.0122 0.0144 0.0171

θIn 0.0131 0.0154 0.0184

θWP 0.006 0.0069 0.0081

θEP 0.0071 0.009 0.0119

MEA to WA 302.43 395.65 506.36 6.4491

MEP to WA 1.11E‐07 1.27E‐07 13.0875 0

MWA to EA 119.79 166.42 223.96 2.3964 M In to EA 1.75E‐08 1.99E‐08 8.0529 0

MEA to In 52.7402 105.53 185.43 1.6252

MWP to In 195.14 296.22 422.56 4.5618

MIn to WP 82.1782 146.84 238.55 1.0132

MEP to WP 14.2155 16.2463 58.7398 0.1121

MWP to EP 41.8149 96.8064 186.78 0.8713 MWA to EP 8.31E‐14 9.36E‐14 26.2257 0

Table 2‐7. Maximum likelihood estimates (MLE) and 95% confidence interval of θ and migration rates (M) and number of migrants (Nm) obtained from MIGRATE‐N for 5 regional groups (WA: West Atlantic, EA: East Atlantic, In: Indian Ocean, WP: West Pacific, EP: East Pacific).

Figure 2‐1. Statistical parsimony networks of 21 haplotypes (H1‐21) based on full length cpDNA sequences among C. rosea and its allied species. Symbols, colors and size of each haplotype correspond to species, haplotypes could detect by partial sequence of 6 short fragments and frequencies of the corresponding haplotypes, respectively. The small white circles indicate the undetected intermediate haplotypes.

Figure 2‐2. Distribution map of the cpDNA haplotypes identified by partial sequence (2012 bp) for 48 populations from five oceanic regional groups of C. rosea. Pie charts represent the proportion of haplotypes in each locality and the size of pie charts is proportional to sample size. Haplotypes H1‐21 corresponds to the figure 2‐1.

1 0.9 0.8 0.7 0.6 FST 0.5 F 0.4 FSC 0.3 0.2 0.1 0 024681012

Figure 2‐3. Fixation indices F obtained with the SAMOVA program (Dupanloup et al.

2002) as a function of the user‐defined number K of groups of populations. FST,

differentiation among populations; FCT, differentiation among groups of

populations; FSC, differentiation among populations within groups. . All differentiations were significant (P < 0.01).

Figure 2‐4. Posterior density distribution of Bayesian analysis from MIGRATE‐N for mutation rates (θ). Number 1‐5 corresponds to West Atlantic, East Atlantic, Indian Ocean, West Pacific and East Pacific regions.

Figure 2‐5. Posterior density distribution of Bayesian analysis obtained from MIGRATE‐N for migration rates (M) within C. rosea populations. 71

Number of Migrants (Nm) 12

Figure 2‐6. Estimated number of migrants (Nm) within different Oceanic regions obtained from Bayesian method implemented in MIGRATE‐N program. Calculation was based on 95% credible interval of θ and M values.

Figure 2‐7. The theta and migration rates (M) posterior probability distributions between five oceanic groups of C. rosea populations using MDIV program (Nielsen & Wakeley, 2001). Legends are as follows: WA=West Atlantic, EA=East Atlantic, IN=Indian Ocean, WP= West Pacific and EP= East Pacific. 73

GENERAL DISCUSSION

In this study, I reported the results of phylogenetic analyses among Canavalia rosea, a genuine member PPSS and its related species based on cpDNA and nrDNA ITS sequences and also the result of phylogeographic analyses from a large survey of cpDNA variations among populations of C. rosea.

This phylogeographic study of a genuine PPSS, suggested several interesting findings on a single species that keeps its distribution range by long distance seed dispersal by sea-drifted seeds. Comparing my results with the studies of sub PPSS, H. tiliaceus and its allies, will give us a comprehensive idea about the evolutionary history of PPSS.

I. Closely related species are speciated in the wide distribution range of PPSS. Although we did not have strong evidence of speciation in Canavalia rosea, the widest range of distribution and high haplotype diversity of this species may suggest that some species were speciated from C. rosea as mother species. In the case of H. tiliaceus recurrent speciation from H. tiliaceus has given rise to all of its allied species. II. Substantial gene flow over wide range of distribution is common in both H. tiliaceus and C. rosea, especially over Indo-Pacific region. III. In H. tiliaceus and H. pernambucensis, two species boundary are present: one is the East Pacific and the other is the Atlantic Ocean. It is interesting that both of them are oceanic barriers. In H. pernambucensis in addition, American continents are clear barrier

to shape a clear geographic structure between Pacific and Atlantic regions. In C. rosea, gene flow over East Pacific and Atlantic are observed. These would be caused by the difference of seed dispersibility between the two species group, which suggest that seed dispersibility is the key factor to be a genuine PPSS. IV. The land barriers of Africa and American Continents are common for the both PPSS species which support that sea-drifted seed dispersal is limited by land masses. V. The quite different point between the two studies was the genetic diversity among populations in Pacific and Atlantic regions. Haplotype diversity in the Pacific region for the H. tiliaceus was much higher than that for C. rosea. On the other hand, in the Atlantic region haplotype diversity in C. rosea populations was significantly higher than H. tiliaceus populations. Such interesting results show different evolutionary history of these species and require additional studies to clear up such fascinating patterns.

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ACKNOWLEDGEMENTS I am deeply grateful to my supervisor, Prof. Dr. Tadashi Kajita who encouraging me to do a good research, and challenge me to logical thinking. His efforts, support, and patience in accepting me as a PhD student, will never forget as my dream (study abroad) came true. I am also grateful to my co- supervisor, Prof. Dr. Yasuyuki Watano who always remind me how to learn and Dr. Takeshi Asakawa for his valuable suggestions. I specially thank Prof. Dr. Takayoshi Tsuchiya and Prof. Dr. Sumiko Kimura for their suggestions and comments as referees. I also owe a great debt to Dr. Koji Takayama, who taught me molecular methods and for his valuable comments. I would like to thank Mr. Alvin Y. Yoshinaga from Center for Conservation Research and Training, Hawaii for sending materials. I would like to thank Prof. Dr. Yoichi Tateishi for his helpful comments and allowing me to visit the herbarium of University of the Ryukyus. I am also grateful to Prof. Dr. Masaki Miya for valuable classes in phylogenetic analysis.

I specially thank Dr. Akihisa Shirai, Dr. Norihisa Wakita, Dr. Bayu Adjie, for their help and suggestions. I would also like to thank to all students of Watano and Kajita laboratory for any helps during my researches.

And finally, thanks to my family and all friends for their love, support, and encouragement throughout the years.

My study fully supported by Monbukagakusho (MEXT: Ministry of Education, Culture, Sports, Science and Technology) scholarship.

BIOGRAPHY

Mohammad Vatanparast was born in Urmia, central city of West Azerbaijan province in the North West of Iran in 20 February 1976. He finished his undergraduate level in plant biology from Urmia University in 1999. In 2000 he enter master course in the plant systematic field at Tarbiat Modarres University in Tehran and graduate in 2003. His master thesis was on biosystematics of the genus Trifolium a part of national project about Flora of Iran in Persian language. As his dreams and interest was study abroad to learn novel practical and analytical methods in the plant systematic and evolution, with efforts of

Prof. Dr. Tadashi Kajita, he could enter to the PhD course in his laboratory in

Chiba University, Japan. In October 2006 he entered Japan and after taking 6 month research student course in April 2007 he started his PhD project focusing on “Phylogeography of a pantropical plants with sea-drifted seeds,

Canavalia rosea” by applying large population sampling using molecular methods such as chloroplast DNA sequences and population genetic analyses.