Life History of Millepora Hydrocorals : New Ecological and Evolutionary Perspectives from Population Genetic Approaches Caroline Eve Dube

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Caroline Eve Dube. Life History of Millepora Hydrocorals : New Ecological and Evolutionary Per- spectives from Population Genetic Approaches. Populations and Evolution [q-bio.PE]. École pratique des hautes études - EPHE PARIS, 2016. English. NNT : 2016EPHE3075. tel-02105217

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Mention « Systèmes intégrés, environnement et biodiversité »

École doctorale de l’École Pratique des Hautes Études USR 3278 CRIOBE EPHE-CNRS-UPVD

Life History of Millepora Hydrocorals

New Ecological and Evolutionary Perspectives from Population Genetic Approaches

Par Caroline E. DUBE

Thèse de doctorat de Biodiversité, Génétique et Évolution

Sous la direction de M. Serge PLANES, Directeur d’Etudes Sous le co-encadrement scientifique de Mme. Emilie BOISSIN

Soutenue le 29 Novembre 2016

Devant un jury composé de:

M. Mehdi ADJEROUD Directeur de Recherche, IRD – Examinateur Mme. Sophie ARNAUD-HAOND Chargé de Recherche, IFREMER – Rapporteur Mme. Emilie BOISSIN Dr., CRIOBE – Co-encadrant M. Pim BONGAERTS Dr., Global Change Institute – Examinateur M. Pierre CHEVALDONNE Directeur de Recherche, CNRS – Examinateur M. Claude MIAUD Directeur d’Etudes, CEFE – Examinateur M. Serge PLANES Directeur d’Etudes, CRIOBE – Superviseur M. Lorenzo ZANE Professor, University of Padova – Rapporteur

In the middle of every difficulty lies opportunity. Albert Einstein

To my family and loved ones,

ACKOWLEDGEMENTS

First, I wish to express my gratitude to Mehdi Adjeroud, Sophie Arnaud-Haond, Pim Bongaerts, Pierre Chevaldonné, Claude Miaud and Lorenzo Zane for agreeing to be a part of this PhD committee and for sharing their expertise.

This PhD thesis would not have possible without the hard work of many people. First and foremost, I would like to thank my advisor Serge Planes for giving me the opportunity to do this PhD and for being so enthusiastic about fire coral clones and dots! I am sincerely grateful for his support and guidance throughout this project, but also for his generosity and for giving me the opportunity to remain independent during my field and lab work. I was also very fortunate to receive support from Emilie Boissin who taught me so much during the last three years. I would like to give her many thanks, not only for her availability and support regarding our research, but also for her friendship. It was a great pleasure to live this experience at her side and to share incredible adventures, such as conferences in Italy and Hawaii, but also our everyday life here in Perpignan. Despite the hard work, we had so much fun!

This PhD would also not have been possible without the help of my collaborators who generously offered their time and expertise. I would like to thank Véronique Berteaux for her valuable advices and discussions throughout this entire PhD. I am sincerely grateful to Mark Vermeij for his patience and for sharing his knowledge on coral reproduction and reef ecology. It was very rewarding to work with him, as always. I also wish to express my gratitude to Jeff Maynard for his patience and especially for giving me fair advices to improve my writing skills. I also thank Jeanine Almany for her generosity and for reviewing most of my manuscripts.

I would also like to thank Franck Lerouvreur and Mark Besson for their help on the field and Nathalie Tolou and Yuxiang Zhou for their help in the lab. My thanks to all the CRIOBE staff for making this journey such a memorable experience, Yannick Chancerelle, Pascal Ung, Gilles Siu, Benoit Espiau, Cécile Berthe, Christine Sidobre, Elina Burns, Aurélie Mariotti, Peter Esteve, Fabien Morat and Guillaume Iwankow. I am also grateful to all the researchers for valuable discussions and funny times, Joaquim Claudet, Rita Sayoun, Laetitia Hedouin, Suzanne Mills, Ricardo Beldade, Maggy Nugues, Valeriano Parravicini, Gaël Lecellier, David Lecchini, Pierre Sasal, Bruno Delesalle, Catherine Gobin and René Galzin.

While doing research, we always make new friends who are making this experience unique, inspiring and unforgettable. I would like to thank Martin Romain and Florent Bignon for their

craziness and for their support and amazing friendship! Johann Mourier for being so easily ambushed (sorry Jess)! My crazy fur-banister ladies Ornella Weideli and Myriam Reverter with whom I shared so many incredible adventures, I can’t wait for those to come! I’m also thankful to Gaëlle Quéré for her constant support and friendship. It was so nice to have you around! A special thanks to Erwan Delrieu-Trottin and Valentina Neglia for their gin tonics and lasagnas! To Océane Salles for being my PhD buddy, to Carole Blay for her kindness and support, especially at the very end! To Mélodie Dubois, Louis Bornancin, Lauric Thiault, Noa Nukamura, Antoine Puisay and Pierpaolo Brena for all the moments shared and many apéros. I also thank my Curaçao buddies, Amanda Ford and Brittany Alexander for their good friendship. A special thank you to my very best friend Valérie Chamberland, it all started with her and our dreams!

Finally, I wish to thank my friends and family, who have always been there for me despite the distance. A special thanks to my parents and brother for encouraging me along this journey. I wish I could have fulfilled my dreams by working on the cold St-Laurent River and be close to home… although this is not entirely true! So I am very grateful for their understanding and for believing in my dreams. Thank you to my family in law for taking good care of me and for always feeding me with good food and wine! A very special and sincere thanks to my partner Alexandre Mercière, not only for his help on the field, or with statistics or with graphs, but for his patience and kindness, and for always taking such a good care of me during the ups and downs of the last four years. His love and support were a source of strength to accomplish this thesis.

This Research received funding from the Fonds Québécois de Recherche sur la Nature et les Technologies for a graduate scholarship.

TABLE OF CONTENTS

CHAPTER 1: INTRODUCTION AND THESIS OUTLINE ...... 25 INTRODUCTION ...... 26 1. CORAL REEFS: BIODIVERSITY AND THREATS ...... 26 2. SPECIES’ RESPONSE TO ENVIRONMENTAL CHANGES ...... 27 3. OVERVIEW OF LIFE HISTORY TRAITS IN COLONIAL REEF SPECIES ...... 28 3.1. REPRODUCTIVE STRATEGIES...... 28 3.2. LARVAL DEVELOPMENT ...... 29 3.3. MODULARITY AND GROWTH ...... 29 3.4. MORPHOLOGICAL PLASTICITY ...... 31 4. MILLEPORA HYDROCORALS ...... 31 5. REEF HABITATS IN MOOREA, FRENCH POLYNESIA ...... 34 6. INSIGHT FROM POPULATION GENETIC APPROACHES ...... 35 THESIS AIMS AND OUTLINE ...... 36 CHAPTER 2: OVERGROWTH OF SCLERACTINIAN CORALS BY MILLEPORA ...... 41 CHAPTER 3: POPULATION STRUCTURE OF MILLEPORA ...... 45 1. INTRODUCTION ...... 47 2. MATERIALS AND METHODS ...... 49 2.1. STUDY SITES AND FIELD SURVEYS ...... 49 2.2. SPATIAL DISTRIBUTION PATTERNS ...... 50 2.3. COLONY SIZE DISTRIBUTION ...... 51 2.4. RECRUITMENT DYNAMICS ...... 51 2.5. COLONY MORPHOLOGY ...... 51 2.6. POPULATION STRUCTURE ASSESSMENT...... 52 3. RESULTS ...... 52 3.1. SPATIAL DISTRIBUTION OF MILLEPORA PLATYPHYLLA ...... 52 3.2. SIZE STRUCTURE OF MILLEPORA PLATYPHYLLA ...... 54 3.3. RECRUITMENT OF MILLEPORA PLATYPHYLLA ...... 55 3.4. MORPHOLOGY OF MILLEPORA PLATYPHYLLA ...... 56 3.5. POPULATION STRUCTURE ASSESSMENT...... 57 4. DISCUSSION ...... 59 CHAPTER 4: GENETIC DIVERSITY AND DIFFERENTIATION IN MILLEPORA ...... 69 1. INTRODUCTION ...... 71 2. MATERIALS AND METHODS ...... 73 2.1. PREPARATION OF GENOMIC DNA FOR 454 SEQUENCING FOR THE TARGET SPECIES ...... 73

2.2. MICROSATELLITE DISCOVERY AND PRIMER TESTING ...... 74 2.3. SAMPLING, GENOTYPING AND CROSS-SPECIES AMPLIFICATION ...... 74 2.4. PHYLOGENETIC ANALYSES ...... 75 2.5. DATA ANALYSES ...... 75 3. RESULTS ...... 77 3.1. DEVELOPMENT OF DE NOVO MICROSATELLITES IN MILLEPORA PLATYPHYLLA ...... 77 3.2. CROSS-SPECIES AMPLIFICATION IN MILLEPORIDAE ...... 78 4. DISCUSSION ...... 81 4.1. DEVELOPMENT OF MICROSATELLITES AND THEIR TRANSFERABILITY IN MILLEPORIDAE 81 4.2. USEFULNESS OF CROSS-SPECIES AMPLIFICATION IN INDO-PACIFIC MILLEPORIDAE ...... 81 4.3. PATTERNS OF GENETIC DIVERSITY AND POPULATION STRUCTURE IN MILLEPORIDAE ...... 82 5. CONCLUSIONS ...... 83 CHAPTER 5: FIRE CORAL CLONES DEMONSTRATE PHENOTYPIC PLASTICITY ... 91 1. INTRODUCTION ...... 93 2. MATERIALS AND METHODS ...... 95 2.1. MODEL SPECIES ...... 95 2.2. FIELD SURVEYS ...... 95 2.3. MORPHOLOGY ASSESSMENT ...... 96 2.4. DNA EXTRACTION AND MICROSATELLITE GENOTYPING ...... 96 2.5. BALANCE BETWEEN SEXUAL AND ASEXUAL REPRODUCTION ACROSS HABITATS ...... 97 2.6. DISTRIBUTION AND MORPHOLOGY OF CLONAL LINEAGES ...... 97 3. RESULTS ...... 98 3.1. SEXUAL VERSUS ASEXUAL REPRODUCTION ...... 98 3.2. MORPHOLOGY OF SEXUAL AND CLONAL RAMETS ...... 100 3.3. DISTRIBUTION AND MORPHOLOGY OF CLONAL LINEAGES ...... 100 4. DISCUSSION ...... 101 4.1. GENETIC DIVERSITY ...... 101 4.2. CLONE DISTRIBUTION ...... 103 4.3. PHENOTYPIC PLASTICITY AND FUTURE RESEARCH ...... 104 4.4. CONCLUSIONS ...... 105 CHAPTER 6: DISPERSAL LIMITATIONS AND SIBLING AGGREGATIONS IN MILLEPORA ...... 121 1. INTRODUCTION ...... 123 2. MATERIALS AND METHODS ...... 125 2.1. POPULATION SAMPLING AND MICROSATELLITE GENOTYPING ...... 125 2.2. MULTILOCUS GENOTYPES AND POPULATION GENETIC ANALYSES ...... 126 2.3. PARENTAGE ANALYSIS ...... 126 3. RESULTS ...... 127

3.1. POPULATION SAMPLING AND CLONES ...... 127 3.2. GENETIC DIVERSITY AND MICROSATELLITE PANEL ...... 129 3.3. PARENTAGE ANALYSES AND RECRUITMENT ...... 129 3.4. DISPERSAL DISTANCES AND SIBLING DISTRIBUTION PATTERNS ...... 130 4. DISCUSSION ...... 132 4.1. HIGH SELF-RECRUITMENT RATES AND LIMITED CONNECTIVITY AMONG HABITATS ...... 133 4.2. DISPERSAL OF EARLY LIFE STAGES WITH REEF CURRENTS ...... 135 4.3. GAMETE DISPERSAL AND FERTILIZATION LEAD TO SIBLING AGGREGATIONS...... 136 4.4. IMPACT OF CLONAL REPRODUCTION ON SELF-RECRUITMENT AND DISPERSAL ...... 137 5. CONCLUSIONS ...... 138 CHAPTER 7: INTRACOLONIAL GENETIC VARIABILITY IN MILLEPORA ...... 145 1. INTRODUCTION ...... 147 2. RESULTS ...... 149 2.1. COLONY REPRODUCTION AND MORPHOLOGY ...... 149 2.2. IDENTIFICATION OF INTRACOLONIAL GENETIC VARIABILITY ...... 149 2.3. CLUSTERING ANALYSES ...... 150 3. DISCUSSION ...... 152 3.1. PATTERN OF INTRACOLONIAL GENETIC VARIABILITY AMONG REEF HABITATS ...... 152 3.2. MOSAICISM ...... 154 3.3. CHIMERISM ...... 156 3.4. EVOLUTIONARY AND ECOLOGICAL IMPLICATIONS ...... 157 4. METHODS ...... 157 4.1. SAMPLING ...... 157 4.2. MICROSATELLITE GENOTYPING ...... 158 4.3. MOLECULAR ANALYSES ...... 158 CHAPTER 8: CONCLUSIONS AND NEW DIRECTIONS ...... 163 GENERAL DISCUSSION ...... 164 1. LIFE HISTORY OF MILLEPORA HYDROCORALS: ARE THEY ‘WINNERS’? ...... 165 1.1. HIGH CLONAL PROPAGATION OF LOCALLY ADAPTED OFFSPRING ...... 165 1.2. FUSION AND MUTATION: ADDITIONAL SOURCE OF GENETIC DIVERSITY ...... 167 1.3. MORPHOLOGICAL PLASTICITY: A MEANS TO PROMOTE CLONAL REPRODUCTION ...... 168 1.4. MILLEPORA PLATYPHYLLA: A COMPETITIVE AND RESILIENT SPECIES ...... 169 1.5. IS MILLEPORA A GOOD MODEL TO PREDICT ADAPTATION OF REEF CORALS? ...... 171 NEW DIRECTIONS ...... 172 CONCLUSIONS ...... 174 CHAPTER 9: REFERENCES ...... 179

LIST OF FIGURES

Fig. 1.1 Grime’s triangle of life history strategies applied to reef corals from Darling et al. 2012. Principal Coordinates ordination of 143 coral species with four life history strategies (red: competitive, green: weedy, blue: stress-tolerant, grey: generalist). Arrows indicate trait loadings and traits are numbered from most important to least important in differentiating the life history strategies: (1) domed morphology (2) growth rate (3) brooding reproduction (4) fecundity (5) broadcast spawning reproduction (6) branching morphology (7) colony size (8) skeletal density (9) plating morphology (10) corallite diameter (11) depth (12) symbiont diversity (13) generation length and (14) solitary colonies...... 27

Fig. 1.2 Spread of somatic mutations in corals from van Oppen et al. 2011. A: Mutant cells arisen in the upper part of the coral polyp migrate into the budding polyp; B: Massive coral colony in which a mutation has arisen and spreads as the colony grow. Partial mortality can divide the colony into two physically separated units that are of different genotypes (i.e. wild and mutant) and C: Branching coral in which a mutated branch has broken and re-attached to the substratum. The wild genotype colony produces wild gametes only, while the mutant genotype colony produces both wild and mutant gametes as corals are diploid and only half of their gametes in a heterozygous individual will carry the mutation following meiosis...... 30

Fig. 1.3 Relation between coral growth forms and their vulnerability to wave-induced breakage. Branching morphologies are more vulnerable to fragmentation and occur in low wave energy reef zones. Silhouettes of characterized morphologies are from Madin 2005; branching, tabular, corymbose, convoluted hemispherical, massive and encrusting coral growth forms are shown from the left to the right...... 31

Fig. 1.4 The position of hydrozoans, such as Millepora, in the animal tree of life from Houliston et al. 2010. Hydrozoans, cubozoans and scyphozoans are medusozoans and hermatypic corals are anthozoans...... 32

Fig. 1.5 Millepora life cycle. Millepora platyphylla is a gonochoric broadcast spawner that reproduces sexually by producing medusoids and planula larvae. The medusoids release the gametes in the water column for external fertilization. The ciliate larvae sink and crawl on the reef substratum and metamorphose in a new calcifying polyp. M. platyphylla also relies on clonal propagation through fragmentation...... 33

Fig. 1.6 Wave energy dispersal on a barrier reef modified from Monismith 2007 and Ferrario et al. 2014. The fore reef experiences strong wave action from incoming waves that break on the

reef crest, near the upper slope, with a significant decrease in swell exposure towards deeper waters. The reef crest dissipates ~70% of the incident swell wave energy with gradual wave attenuation from the back reef to nearshore fringing reefs...... 35

Fig. 2.1 Millepora platyphylla corals (*) at Moorea overgrowing living corals of various scleractinian species: a and b at back reef Porites sp. (°); c Pocillopora meandrina (+) and d Porites sp. (°) and Pocillopora meandrina (+) on fore reef, 6 m depth; e Phymastrea curta (§) on fore reef, 12 m depth...... 43

Fig. 3.1 Aerial views of the locations of each transect in the five surveyed habitats in Moorea, French Polynesia. The names of these surveyed locations are: (A) Tiahura, (B) Papetoai, (C) Cook’s Bay and (D) Temae. Map data © 2015 Google...... 49

Fig. 3.2 Morphologies of M. platyphylla colonies in habitats experiencing contrasting hydrodynamic regimes. (A) Massive wave-tolerant morphology in the patch reef, a lagoonal habitat (photo credit Gilles Siu); (B) encrusting wave-tolerant morphology in the mid slope, a fore reef habitat at 13 m and (C) sheet tree morphology vulnerable to wave-induced breakage in the upper slope, a fore reef habitat at 6 m...... 52

Fig. 3.3 Index describing the spatial distribution of M. platyphylla colonies across the five surveyed habitats. (A) density (B) cover (C) distribution index and (D) mean neighborhood distance. Values were average per habitat and error bars show the standard error for transect replicates. Similar letters indicate no statistical difference in post-hoc comparisons among habitats (P > 0.5)...... 53

Fig. 3.4 Size-frequency distributions of M. platyphylla across the five surveyed habitats. Colony 2 size (cm ) data were distributed among 10 size classes based on a logarithm scale (log2). Frequencies (%) for each size class were averaged by habitats with total population size (N in Table S2) and error bars show the standard error for transect replicates...... 54

Fig. 3.5 Recruitment dynamics across the five surveyed habitats. Proportions of recruits (< 1 cm2), juveniles (1–20 cm2) and adults (> 20 cm2) were averaged by habitats with total population size (N in Table S2) and error bars show the standard error for transect replicates. Similar letters over each set of bars indicate no statistical difference in post-hoc comparisons for a given life history stage among habitats (P > 0.05)...... 56

Fig. 3.6 Stock-recruitment relationship between the abundance of adults and coral new recruits and juveniles. (A) Significant positive relationship in the lagoon (i.e. back, fringing and patch reefs) and (B) no stock-recruitment relationship in the fore reef (i.e. mid and upper slopes).

Each circle represent the mean abundance for each transect surveyed. Note the different scales on x and y axes...... 57

Fig. 3.7 Morphology of M. platyphylla adult colonies across the five surveyed habitats. Proportions of colonies with encrusting, sheet tree and massive morphology were averaged by habitats and error bars show the standard error for transect replicates. Similar letters over each set of bars indicate no statistical difference in post-hoc comparisons for a given life history stage among habitats (P > 0.05). See Fig. 3.2 for photos of each of the morphologies...... 58

Fig. 3.8 Non-metric multidimensional scaling (MDS) plot of M. platyphylla population structure across the five surveyed habitats. Different shapes indicate the three transects for each habitat and grey lines show clusters given by dendogram based on Eucledian distance of 4 at a stress level of 0.09. The surimposed red lines define the Eucledian distance coefficient on normalized data based on Spearman ranking, with each vector having lengths ≥ 0.4: density, cover, distribution index, mean neighborhood distance, mean height and size of adults, and proportion of recruits (< 1 cm2), juveniles (1–20 cm2) and adults (> 20 cm2). The second transect of the fringing reef is shown as a single group mostly related to a small population size (i.e. 27 colonies, Table S2)...... 59

Fig. 4.1 Proportion of missing data (A) and observed heterozygosity (B) per microsatellite locus (circles) in five Millepora species plotted against phylogenetic distances (16S gene) from the target species Millepora platyphylla (p, red) to other species; Millepora intricata (i, green), Millepora dichotoma (d, pink), Millepora tenera (t, purple), Millepora complanata (c, blue) and Millepora exaesa (e, yellow)...... 80

Fig. 5.1 Spatial distribution of sexual versus asexual M. platyphylla colonies (left) and morphologies (right) across all five surveyed habitats. Photo series shown is of clones of the same clonal lineage found on the mid slope, upper slope, and back reef, respectively (see Fig. S7 for location of these colonies). The inset photo for sheet tree shows the horizontal view of this morphology; the vertical blades make the morphology vulnerable to fragmentation in the high energy upper slope habitat. Data shown are for the transect with the greatest sample size (See Figs. S3 and S4 for all transect replicates)...... 99

Fig. 5.2 Spatial distributions of clonal lineages identified on the mid slope, upper slope and back reef (left) and clones shared between at least two of these habitats (right). Clonal lineages are represented by a unique color. Data are for the transect with the greatest sample size (See Figs. S5 and S7 for all transects)...... 101

Fig. 6.2 Spatial distribution and size of the 3160 colonies sampled across the three surveyed habitats within three belt transects (300 x 10 m). Adult colonies (potential parents, N = 2101) are represented in grey and juvenile colonies (< 20 cm2, N = 1059) in white. Assigned offspring to parents sampled within the study area, as revealed by parentage analysis, are shown in red (N = 216)...... 128

Fig. 6.3 Dispersal patterns of four local families. Two are of parents with unique genotype (A) P1 with seven assigned offspring and (B) P2 with five assigned offspring, and two are of parents with clonal genotype (C) P3 and P4 (D) with five assigned offspring each. Dispersal estimates for parent-offspring relationship and mean dispersal distance among siblings are given in Table S3. One full sib relationship was found for P1 and an unknown parent with a distance of 723.41 m between the two full siblings...... 131

Fig. 6.4 Dispersal distance distribution of assigned offspring within the entire surveyed area (9000 m²). Observed dispersal distribution, determined using parentage analyses, is given by the percentages of dispersal events (N = 216) distributed among ten distance classes, assigned at 100 m each over the entire dispersal range (A) and assigned at 10 m each over the first hundred meters of the dispersal range (B)...... 132

Fig. 6.5 Dispersal distance distribution of siblings (full- and half-sibs) within the entire surveyed area (9000 m²). Observed dispersal distribution of full-sibs (A) and half-sibs (B), determined using parentage analyses, is given by the percentages of dispersal events (N = 78 of full siblings; N = 132 of half siblings) distributed among nine distance classes, assigned at 100 m each over the entire dispersal range...... 134

Fig. 7.1 Aerial views of the locations of the five surveyed habitats in Moorea, French Polynesia. The names of these surveyed locations are: (A) Papetoai and (B) Temae. Map data © 2015 Google...... 149

Fig. 7.2 Intracolonial genetic variability detected in M. platyphylla colonies in the five surveyed habitats. Frequency (%) of deviating genotypes caused by chimerism are shown in black; by mosaicism, i.e. somatic mutations, in grey and single genotypes, i.e. most common genotypes, are shown in light grey...... 151

Fig. 7.3 Frequency (%) of deviating genotypes caused by one-step to four- to twelve-step mutations over all loci in all surveyed habitats. Notice that the back reef is not shown since no deviating genotype was found within this habitat...... 152

Fig. 7.4 Assignment analyzes based on Bayesian clustering showing mosaic colonies and chimeras in the five surveyed habitats. Bar plot for N colonies and K clusters are shown per habitat. The x-axes show colony identification and whether they belong to clonal (asexual reproduction: A) or single genotype (sexual reproduction: S), and y-axes shows the cluster membership. Samples marked with M show deviating genotypes due to mosaicism, C are chimeras (P > 0.6) and each number beside M and C represents one deviating genotype...... 153

Fig. 8.1 Summary of life history strategies in M. platyphylla in Moorea, French Polynesia. M. platyphylla heavily relies on asexual reproduction through fragmentation for local replenishment (80% of the colonies are clones), allowing population growth and the persistence of a genotype over time when sexual reproduction is impeded. Although only 20% of the colonies of M. platyphylla are produced through sexual reproduction, its population is sustained via a high contribution from self-recruitment (58% of juveniles are self-recruits). Mosaicism and chimerism also contribute in creating novel genotypic diversity in the population...... 168

Fig. 8.2 Evolutionary perspectives for M. platyphylla. Self-seeding and intracolonial genetic variability (mosaicism and chimerism) create novel genetic diversity within M. platyphylla population, while colony fragmentation allows the persistence of these genotypes (shown as genotypes a–e). The interaction of these processes generates a high level of genetic variability required for adaptation via genetic changes. Also, each of these genotypes can express different phenotypes in response to environmental changes and even clones have demonstrated phenotypic plasticity. Further investigations on how fire coral-associated microbial communities (A–E) are impacted by variation in environmental conditions are needed to detangle adaptive plasticity, genetic adaptation and co-speciation of the holobionte...... 170

LIST OF TABLES

Table 3.1 Index describing the population size structure and recruitment for M. platyphylla across the five habitats...... 55

Table 4.1 Characterization of de novo microsatellite loci and genetic variation in the target species M. platyphylla collected in Moorea, French Polynesia...... 76

Table 4.2 Summary of genetic distances (GD) based on the mitochondrial 16S gene between the target species and other Millepora species together with indices indicating the microsatellite transferability and genetic diversity...... 78

Table 4.3 Nuclear (FST) and mitochondrial (p-distance) genetic distances among Millepora species...... 78

Table 5.1 Proportion of clones with encrusting, sheet tree and massive morphology for six clonal lineages shared among habitats...... 101

Table 6.1 Details of Millepora platyphylla population sampling based on colony size (ramet level) and parentage assignments across the three surveyed habitats at Moorea. Number of colonies surveyed (# col), number of adults (# adu, > 20 cm2) and number of juveniles (# juv, < 20 cm2) are given. Percentages give the proportions of juveniles within that habitat that were i) offspring of parents sampled at the same habitat (SR = self-recruitment), ii) offspring of parents sampled at other habitats (HC = habitat connectivity), or iii) were not assigned to parents sampled within the entire area surveyed (UA = unassigned)...... 127

Table 6.2 Summary results of parentage analysis in Millepora platyphylla within the entire reef area (9000 m2). Characteristics of parents contributing to self-recruitment and comparisons between clonal and single genotype parents are given: number of potential parents surveyed in the study area; number of parents assigned to an offspring within the surveyed area with their mean colony size (cm²), standard error (SE) and median; total number of assigned offspring and mean number of assigned offspring to one single parent with standard error (SE), maximum and median. All values are presented at the genet level (i.e. without clonal replicates). Estimates of offspring dispersal within the study area are shown: mean distance between the parent and their assigned offspring with standard error (SE), minimum, maximum and median...... 133

Table 7.1 Sampling pattern among the five surveyed habitats. Number of colonies (# Col), number of replicates within a single colony (# Repl), total number of samples (# Sam), number of

detected multilocus genotypes (# Gen), number of clones in sampled colonies (# Clon), percentage of genetically heterogeneous colonies (% Het), number of colonies displaying massive (M), encrusting (E) or sheet tree (ST) morphology and mean colony size are given for the 51 colonies sampled. The number of colonies sampled belonging to a clonal (asexual reproduction) or single genotypes (sexual reproduction) according to an exhaustive sampling and genotyping of M. platyphylla colonies (performed by Dubé et al. unpublished data1) are also shown...... 150

CHAPTER 1

Introduction and Thesis Outline

Introduction

1. Coral reefs: Biodiversity and threats

Although coral reefs were formed only 230 million years ago (Veron 1995) and are largely limited to warm shallow waters, they have succeeded in becoming one of the most productive and diverse ecosystem on Earth (Hughes et al. 2003). Often called the rainforest of the sea due to their outstanding biodiversity, coral reefs only cover less than 0.1% of the ocean seafloor (Spalding and Grenfell 1997; Copper 1994) or approximately 5% that of rainforest (Reaka-Kudla 1997). Coral reefs thrive under nutrient-poor and oligotrophic waters (Odum and Odum 1955; Hatcher 1990; Atkinson and Falter 2003), but yet harbor more than 25% of all marine species (McAllister 1991; Knowlton et al. 2010). This paradoxal ecosystem is sustained through efficient nutrient recycling strategies developed by corals (Wild et al. 2004) and algae (Haas et al. 2010), the primary reef producers, and other key organisms, i.e. microbes (Azam et al. 1983) and sponges (De Goeij et al. 2013).

In coral reef ecosystems, there are many calcifying benthic organisms that contribute to reef accretion and build the complex and massive tridimensional structure of reefs, among them scleractinian corals (Bellwood and Hughes 2001), hydrocorals (Cairns 1992; Lewis 2006) and coralline algae (Steneck 1986). These reef-building organisms are key components of coral reef health and biodiversity as they offer food and shelter for thousands of reef-dwelling organisms and fishes (Bellwood et al. 2006). Nevertheless, coral reefs are increasingly threatened by chronic and acute stressors (Bellwood et al. 2004) and are expected to be highly vulnerable to future climate change due to rapidly increasing sea surface temperatures and ocean acidification (Hoegh-Guldberg et al. 2007; Pandolfi et al. 2011). Several reports on reef degradation and coral cover loss were related to their vulnerability to human impacts (Gardner et al. 2003; Bruno and Selig 2007; De’ath et al. 2012). Human activities have altered both global (climate change associated with CO2 emissions) and local reef health (e.g. poor water quality, over exploitation, destruction and invasive species) (Lesser 2007). These antropogenic disturbances further change the biodiversity in coral reefs and hamper their capacity to deliver important sources of ecosystem services to more than 500 million people (Wilkinson 2008; Cardinale et al. 2012). Because of the imminent disappearance of modern reefs, more information is needed to determine whether and how reef species can adapt and survive to such devastating disturbances.

2. Species’ response to environmental changes Because of the uncertainty on how coral reef ecosystems will respond to the inevitable increase of 1 human activities and global change, evaluating life history of keystone species can benefit our

ability to predict long-term consequences on community dynamics, a prerequisite for reef conservation (Garrabou and Harmelin 2002; Darling et al. 2012, 2013). Life history strategies describe the species traits in terms of their survival, growth and reproduction and define how they can interact with their surrounding environment (Grime and Pierce 2012). Identifying species that may ‘win’ or ‘lose’ in the face of environmental changes remains a challenge. For instance, a recent trait-based classification approach has identified four life history strategies in scleractinian corals, the primary framework of coral reefs: competitive, weedy, stress tolerant and generalist, whereby

colony morphology, growth rate and reproductive mode are the primary traits leading to these ThesisIntroductionOutline and contrasting life histories (Darling et al. 2012, Fig. 1.1). Competitive species are dominant in productive environments, weedy species are found in recently disturbed environments and stress tolerant species can succeed in harsh environments.

Such classification was based on interspecific variation in phenotypic traits at a global scale, although the combination of phenotypic and genetic data can provide additional information on species’ life history strategies in response to local stress, e.g. growth, morphological plasticity, clonal propagation and dispersal patterns. Several important environmental gradient (temperature, light, wave and water quality condition) and disturbances (storms and eutrophication) occur over a relatively small spatial scale within reefs (Glynn 1996; Vermeij and Bak 2002; Nugues and Roberts 2003; Fabricius 2005; Monismith 2007). More information on species’ life history traits in populations exposed to local environmental and/or anthropogenic stress is thus needed.

3. Overview of life history traits in colonial reef species

3.1. Reproductive strategies

Although only a few species are exclusively reproducing asexually, clonality has evolved repeatedly in many reef organisms (Highsmith 1982; Jackson et al. 1986; Sherman et al. 2006; Foster et al. 2013). In coral reef ecosystems, there are many organisms that can reproduce through both sexual and asexual reproduction, among which scleractinian corals (Harrison 2011) and coralline algae (Pearson and Murray 1997) are the major reef-builders, in addition to sea anemones (Sherman and Ayre 2008), gorgonians (Kahng et al. 2011) and sponges (Whalan et al. 2005). Asexual reproduction produces genetically identical offspring, often leading in local populations dominated by few adapted clones (Miller and Ayre 2004; Gorospe and Karl 2013; Baums et al. 2014). In the contrary, sexual reproduction enables genetic recombination and production of genetically diverse propagules, thus generating the genotypic variation required for adaptation (Rice and Chippindale 2001) and colonization of new habitats (Williams 1975). In many colonial reef organisms, asexual reproduction can occur through fragmentation, fission, budding, polyp expulsion or polyp bail-out (Brazeau and Lasker 1990; Ereskovsky and Tokina 2007; Reitzel et al. 2007; Harrison 2011). Sexual reproduction often involved a wide range of reproductive strategies, i.e. gonochorism, hermaphroditism, internal (brooders) and external fertilization (spawners) (Gutiérrez‐Rodríguez and Lasker 2004; Harrison 2011). Because each reproductive mode confers different advantages under variable environmental conditions (Williams 1975; Eckert 2002), determining the relative contribution from both sexual and asexual reproduction in natural populations can provide valuable insights to understand reef species’ response to local stress.

3.2. Larval development

For most colonial reef species whose adults are sessile, their early life history includes a reproductive pelagic stage. These propagules represent the first step for successful recruitment and 1

have profound implications for their population dynamics and renewal, which ultimately affect their evolutionary history (Gaines et al. 2003; Ayre and Hughes 2004). Dispersal in colonial organisms is mostly mediated by the release of gametes and/or larvae during sexual reproduction events, together with the continuous supply in asexual propagules. In many reef species, the extent of dispersal is largely governed by the reproductive biology and early life history ecology. Molecular studies and oceanographic models have uncovered a wide range of dispersal patterns (i.e. dispersal kernels) in coral reefs, from populations primarily sustained by self-recruitment due to limited dispersal

potential through ecologically significant gene flow and connectivity among adult populations Introduction and ThesisIntroductionOutline and (Steneck 2006). For instance, brooded larvae settle and metamorphose rapidly after being released, which is most likely to enhance local dispersal patterns, while broadcast larvae require a planktonic development phase and settle further away from the parental source (Harrison 2011). On the other hand, clonal propagation can allow populations to expand locally under unfavourable conditions. Such conditions include: fragmented (Adjeroud et al. 2014), marginal (Baums et al. 2014) and highly disturbed habitats (Foster et al. 2013), where clonal reproduction reinforce local adaptation process and population genetic heterogeneity due to restricted dispersal potential of asexual offspring (Combosch and Vollmer 2011; Pinzόn et al. 2012). Uncovering the dispersal patterns of both sexual and asexual propagules is thus critical for understanding population replenishment and colonization of fragmented habitats, and how such populations can recover from local disturbances.

3.3. Modularity and growth

Modularity is a well established life history strategy among colonial reef invertebrates, i.e. corals, gorgonians, sea anemones, hydroids, hydrocorals, bryozoans and sponges (Hughes 2005). Modular organisms grow in size via the repeated, vegetative formation of genetically identical modules, referred as asexual budding, whereby all modules are derived from the same initial zygote to form a colony (Jackson 1977, 1985). Colony size often correlates with many fitness advantages in responses to both physical and biological stressors. For instance, larger colonies can survive better towards predation (Hughes and Jackson 1980) and competition (Hughes 1989), and their fecundity is often increased due to the large number of polyps that contributes to sexual reproduction (Hall and Hughes 1996). Modules usually remain physiologically interconnected, but may also separate from the colony through fission or fragmentation and persist as discrete units (Wood 1999), thereafter reducing colony size. Some marine modular organisms, e.g. corals and ascidians, can

29 grow larger and quicker via the fusion of distinct colonies that are isogeneic (same species, same genotype) or allogeneic (same species, different genotype) (Pineda-Krch and Lehtilä 2004). Allogenic fusion results in genetically heterogeneous colony, also referred to as chimera, and usually occurs during early ontogeny due to a delay in maturation of the allorecognition system (Frank and Rinkevich 2001). The occurrence of chimeras is more common in species with early life stages that settle and grow in close proximity (i.e. mainly brooding species) (Puill-Stephan et al. 2012a; Forsman et al. 2015). In addition to chimerism, somatic mutations may arise within a colony, which also results in intracolonial genotypic variability. In long-lived modular organisms, where germ cell differentiation occurs continuously from stem cells, these mutations can be passed on to the next sexual generation and asexual colony fragments and be spread in the population (van Oppen et al. 2011, Fig. 1.2). Both chimerism (fusion) and mosaicism (somatic mutation) are important source of genetic variation and raise questions on their implications regarding adaptive responses of reef-building species to environmental changes.

3.4. Morphological plasticity

Plastic developmental responses are often induced during ontogeny of modular organisms with persistent effect on adult phenotypes (Pineda-Krch and Lehtilä 2004). These phenotypic responses 1

can change independently from the genetic pool (acclimatization), but often rely on a genetic basis

(adaptation) (Agrawal 2001; Beaman et al. 2016). In coral reefs, some calcifying species, such as corals and hydrocorals, are known to have a high degree of morphological plasticity in response to hydrodynamic changes and light availability, which strongly influences their performance (Muko et al. 2000; Todd 2008; Hennige et al. 2010). Branching and plating growth forms grow quickly into large arborescent colonies in shallow reef environments, where irradiance is high and water flow is low, which makes them effective competitors for space (Denny 2014; Swierts and Vermeij 2016),

light and food (Baird and Hughes 2000). However, this growth strategy renders them extremely Introduction and ThesisIntroductionOutline and vulnerable to breakage when large waves and storm events occur, often resulting in fragmentation or coral mortality (Madin 2005; Madin et al. 2014) (see Fig. 1.3). Nonetheless, intraspecific morphological variation has been reported in many colonial reef organisms in response to environmental gradients, which ultimately affect their survival and growth (Ayre and Willis 1988; West et al. 1993: Bruno and Edmunds 1997; Hill and Hill 2002). Considering the unpredictability of the reef environment, phenotypic plasticity can provide another means of adaptation in reef- building organisms, and especially in population with lowered genetic diversity.

To date, the vast majority of studies on species’ life history traits in coral reefs have mainly focused on scleractinian corals due to their key role in providing much of the habitat framework and structural complexity of reefs (Hughes and Tanner 2000; Garrabou and Harmelin 2002; Vermeij 2006; Darling et al. 2012, 2013; Kayal et al. 2015). Although the extent to which other non- scleractinian reef-building organisms might rescue reef populations in response to environmental changes is largely unknown, more information on how these organisms can survive and adapt is still

31 needed. Millepora hydrocorals, also called fire corals, are an important component of reefs communities worldwide where they, similar to scleractinian corals, contribute to reef accretion and community dynamics (Nagelkerken and Nagelkerken 2004). Millepora species are hydrozoans and, similar to hermatypic corals (anthanzoans), belong to the phylum Cnidaria (Fig. 1.4), while their life cycle includes both polyp and medusa stages (Fig. 1.5).

Fire corals are abundant in many Indo-Pacific reefs, where they can dominate shallow water communities in some coral reef ecosystems (Andréfouët et al. 2014). Like scleractinian corals, hydrocorals feed heterotrophically on a variety of resources (Lewis 1992, 2006) and rely on a mutualistic symbiosis with Symbiodinium algae for autotrophic nutrition and calcification (Banaszak et al. 2006). Many studies have described these hydrocorals as opportunistic species that show rapid growth rates, with high fecundity and the ability for clonal propagation through fragmentation (reviewed in Lewis 2006). Although fire corals compete with other corals, they also contribute to coral survival during Acanthaster outbreaks, highlighting their key ecological role in reef resilience (Kayal and Kayal 2016). Despite their major importance for reef conservation, fire corals have been relatively understudied and not much is known with respect to their reproduction and dispersal patterns. Millepora hydrocorals are gonochoric broadcast spawners that reproduces sexually by producing medusoids and planula larvae. In hydrozoans, medusoids are formed via asexual budding from the lateral wall of polyps and undergo sexual reproduction. Medusoids produce the gametes and release them in the water column in one hour post-spawning for external fertilization. The larvae sink and move epibenthically (i.e. crawling not swimming) on the reef substratum and metamorphose into a new calcifying polyp in one day post-spawning (Bourmaud et al. 2013), suggesting some limited dispersal abilities (Fig. 1.5). Although milleporids rely on

32 asexual reproduction through fragmentation (Edmunds 1999; Lewis 2006), the production of asexual larvae has never been documented within this genus.

Introduction and ThesisIntroductionOutline and

Fire corals are also known for their extensive morphological variability and vulnerability to fragmentation varies greatly among their morphologies (Edmunds 1999; Lewis 2006). While the corallivorous predator Acanthaster planci tend to avoid Millepora species (Glynn 1990), these zooxanthellate hydrocorals are extremely sensitive to coral bleaching (Marshall and Baird 2000), i.e. the functional loss of their endosymbiotic algae (Glynn 1996), and can be threatened by future climate change. All these life history traits suggest that fire corals are competitive species and typically efficient at using local resources in productive environments (Grime and Pierce 2012; Darling et al. 2012).

The present thesis focuses on Millepora platyphylla, which is the only species of fire corals found in French Polynesia, where it thrives in a wide range of reef environments (Bosserelle et al. 2014). Studying its reproduction and dispersal patterns, along with its morphological variation across

33 various reef habitats in Moorea, will provide more information to determine whether and how this important reef-building species respond to local environmental stress.

5. Reef habitats in Moorea, French Polynesia

Recent genetic studies have uncovered that geographically isolated populations, such as those of Moorea, appear to be more dependent on self-recruitment for local replenishment and sustainability (D’Aloia et al. 2013; Cuif et al. 2015), highlighting the importance of studying local patterns of life history traits in keystone species. Moorea is a high volcanic island surrounded by a barrier reef with extensive fringing reefs and lagoon systems (Galzin and Pointier 1985). Lagoons and deep interrupted channels separate the fore reefs from the island, and the lagoon is connected to the oceanic waters via deep passes through the barrier reef. Such linear barrier reef provides us with the opportunity to gain insights on M. platyphylla life history traits across various reef habitats, where they experienced contrasting environmental conditions.

To determine whether and how the environment affects its life history, five habitats where M. platyphylla are found were selected on the north shore of Moorea; two on the fore reef: the mid slope (13 m depth) and upper slope (6 m depth) and three in the lagoon (< 1 m depth): the back reef, fringing reef and patch reef. These habitats greatly differ in terms of water flow and solar irradiance. The fore reef experiences strong wave action from incoming waves that break on the reef crest with a decrease in swell exposure and irradiance towards deeper waters (Lesser 2000; Monismith 2007, see Fig. 1.6). Variations in temperature are small in the fore reef environment due to continuous waves that break on the reef crest, which fills the lagoon with oceanic water. Inside lagoons, internal waves and flows drive circulation and water exchange with the surrounding ocean via deep passes (Hench et al. 2008; Leichter et al. 2013). In lagoonal environments, the wave energy and oceanic influence decrease from the reef crest towards nearshore fringing reefs (Monismith 2007; Ferrario et al. 2014). Consequently, wave energy is higher on the back reef, near the reef crest compared to the fringing reef, a nearshore reef experiencing great variations in temperature and high irradiance (Fig. 1.6). Although the patch reef is located in a nearshore narrow channel, the wave energy there is also higher than on the fringing reef due to its proximity to the reef crest and to the currents that run on either side of the channel (pass circulation). Despite their proximity (< 1 km to 15 km), these habitats offer a large variety of environmental settings, in which M. platyphylla can be found. Furthermore, coral reefs surrounding Moorea Island in French Polynesia have undergone a massive decline in coral cover from a recent outbreak of Acanthaster planci and cyclone Oli (Kayal et al. 2012), which provides a unique perspective from which to comprehend how fire corals can survive and recover to such disturbances.

Introduction and ThesisIntroductionOutline and

Fig. 1.6 Wave energy dispersal on a barrier reef modified from Monismith 2007 and Ferrario et al. 2014. The fore reef experiences strong wave action from incoming waves that break on the reef crest, near the upper slope, with a significant decrease in swell exposure towards deeper waters. The reef crest dissipates ~70% of the incident swell wave energy with gradual wave attenuation from the back reef to nearshore fringing reefs. 6. Insight from population genetic approaches

Evaluating life history traits in natural populations, such as reproductive strategies and dispersal patterns, is one of the greatest challenges in marine ecology and conservation biology (reviewed in Jones et al. 2009). Clonality appears to be a ubiquitous feature of colonial reef organisms, which has prompted many issues for population genetic studies due to the difficulty in discriminating genetically distinct individuals and clonal replicates (Hey and Machado 2003). Because gametes and larvae of most colonial reef organisms are relatively small and difficult to track in the pelagic environment, many studies investigating their dispersal have relied on virtual simulations of hydrodynamics rather than empirical estimates (Treml et al. 2008; Andutta et al. 2012; Wood et al. 2014). Improvement in genetic analysis and genotyping techniques using microsatellite markers has overcome these problems. Many microsatellite loci show high mutation rates (10–2 – 10–6 mutation per locus per generation), resulting in high allelic diversity (Selkoe and Toonen 2006). Genetic studies based on individual multilocus genotype using a combination of many microsatellites loci allow the characterization of each individual within a population (Reviewed in Sunnucks 2000). Such ability to discriminate each individual creates new opportunities to investigate life history strategies in natural populations of colonial reef species, such as evaluating the level of clonality 35 through the identification of repeated genotypes and estimating dispersal patterns using parentage analysis of georeferenced colonies. To assist conservation management, molecular data are often used to determine the levels of genotypic diversity and potential for adaptation. Such conservation studies rely on the concept of individuality, where each individual represents the unit on which selection pressures occur (Williams 1966). However, recent studies have shown the occurrence of genetically heterogeneous colonies in some modular reef species (Maier et al. 2012; Schweinsberg et al. 2015). More studies considering intracolonial genetic variability are needed to fully understand the evolutionary consequences of both chimerism and mosaicism in threatened species such as reef-building corals. While our understanding of population genetics and life history of scleractinian corals has improved considerably over the last decade (van Oppen et al. 2008; Noreen et al. 2009; Darling et al. 2012, 2013; Warner et al. 2016), such information remains very scarce and unavailable for Millepora hydrocorals, despite their significant contribution to the accretion of reefs. This gap is mostly related to the lack of highly variable genetic markers for this genus until very recently (Ruiz-Ramos and Baums 2014; Heckenhauer et al. 2014). Gathering geographic, phenotypic and genotypic data from extensive field surveys in natural populations, in addition to applying several genetic population approaches, provide valuable insights to understand reef species’ response to local environmental stress. Studies based on such sampling design in natural populations of a single species exposed to different local environmental settings have, to our knowledge, never been performed. This approach will increase our knowledge on life history strategies in reef-building corals and how such populations can persist and survive to environmental changes.

Thesis aims and outline

The overall aim of this study is to improve our understanding of life history strategies and the renewal mechanisms in populations of the fire coral M. platyphylla in response to local stress and to determine whether this species may ‘win’ or ‘lose’ under expected environmental changes. To ensure accurate evaluation of its life history, an exhaustive sampling of georeferenced colonies of fire corals were performed and the subsequent phenotypic and genotypic datasets were gathered and analyzed to answer the following key questions:

Chapter 2: Do Millepora hydrocorals have growth strategies that make them effective competitors for space on coral reefs?

Stolonal expansion of encrusting bases and fast linear growth of branches in milleporids have been described in the 1980s as aggressive strategies to preempt substratum space (Wahle 1980; Müller et al. 1983). Here, we investigated whether this opportunistic spread of Millepora platyphylla in 36

Moorea, where a massive decline in coral cover was reported, may become an important component for their recovery.

Chapter 3: How do different reef habitats with contrasting water regimes affect the population 1

structure of Millepora platyphylla?

Diversity in species’ life history traits plays a key role in structuring populations exposed to different local environmental conditions. Given the difficulties in quantifying key demographic parameters, such as growth rates, longevity and recruitment, valuable insights into life histories of reef-building organisms are often inferred from individual traits based on their size (Hughes 1984). Here, we investigated the colony size distribution, morphological variation and recruitment dynamics to assess to what degree the variability in the population structure of M. platyphylla among reef habitats can be attributed to different flow regimes. Such information is needed to ThesisIntroductionOutline and unveil the processes underlying their colonization success.

Chapter 4: Are microsatellite markers useful to infer patterns of genetic diversity and differentiation in Millepora hydrocorals?

The development of new molecular markers is required for understanding population genetics and species’ life histories (Selkoe and Toonen 2006). Here, we developed fifteen microsatellite loci for M. platyphylla and tested these new markers for cross-species amplification in five other Millepora species. Determining patterns of genetic diversity and differentiation within the Millepora genus is crucial to shed light on biological, ecological and evolutionary processes underlying their population persistence.

Chapter 5: How does sexual and asexual reproduction and fire coral morphologies vary among habitats?

Clonal populations are often characterized by reduced levels of genotypic diversity, which can translate into lower numbers of functional phenotypes, both of which impede adaptation. Study of partially clonal animals enables examination of the environmental settings under which clonal reproduction and morphological plasticity are favored. Here, we investigated the relationship between levels of clonality in Millepora and reef habitats using a contemporary genetic and georeferencing characterization of clones, and examine the effect of habitats on the morphology of fire coral clones.

Chapter 6: What is the relative contribution from self-recruitment and gene flow in the local replenishment of Millepora platyphylla population?

Determining direct genetic estimates of dispersal and subsequent recruitment is crucial for understanding marine population dynamics and replenishment (Jones et al. 2009). Using parentage analysis, we investigated dispersal patterns of sexual propagules of fire corals and estimated the contribution from self-recruitment in the population maintenance. Such information will provide important insights on their reproductive biology and early life ecology.

Chapter 7: How common is intracolonial genotypic variability in Millepora platyphylla due to mosaicism and chimerism processes?

Our understanding of life histories largely relies on the concept of the individual, where intra- individual genetic homogeneity is assumed (Santelices 1999). Nonetheless, an increasing number of studies have revealed intracolonial genetic variability in many modular organisms (Pineda-Krch and Lehtilä 2004). Here, we investigated the occurrence of mosaicism and chimerism within populations of the hydrocoral M. platyphylla across various reef habitats; both of which are processes leading to intracolonial genetic variation.

Chapter 8: What can we learn from population genetic approaches on the adaptive potential of Millepora hydrocorals to future environmental changes? Are they ‘winners’ or ‘losers’?

This chapter discusses the main findings of this PhD thesis in light of whether the life history of Millepora hydrocorals can benefit their survival and persistence to future environmental changes. Futures scientific directions on ecological and evolutionary processes involved in species’ responses to local stress are also discussed, such as local genomic adaptation and/or physiological plasticity of fire corals and their associated microbial organisms.

Introduction and ThesisIntroductionOutline and

CHAPTER 2 Overgrowth of living scleractinian corals by the hydrocoral Millepora platyphylla in Moorea, French Polynesia

Published as: Dubé CE, Boissin E, Planes S (2016) Overgrowth of living scleractinian corals by the hydrocoral Millepora platyphylla in Moorea, French Polynesia. Marine Biodiversity, 46, 329–330.

Overgrowth of living scleractinian corals by the hydrocoral Millepora platyphylla in Moorea, French Polynesia

Caroline E. Dubé1, Emilie Boissin1, Serge Planes1

Received: 30 May 2015 / Revised: 24 August 2015 / Accepted: 26 August 2015 © Senckenberg Gesellschaft für Naturforschung and Springer-Verlag Berlin Heidelberg 2015

1 USR 3278 CRIOBE EPHE-CNRS-UPVD, Laboratoire d’Excellence “CORAIL”, BP 1013, 98 729 Papetoai, Moorea, French Polynesia

Competitive interactions among reef-building organisms are among the major processes regulating coral reef communities (Chadwick and Morrow 2011). Hydrozoan corals of the genus Millepora are abundant in many Indo-Pacific reefs, and by a high cover can dominate shallow-water communities in some coral reef ecosystems (Andréfouët et al. 2014). Many studies have described these hydrocorals (also called fire corals) as opportunistic species that show rapid growth rates, with both high fecundity and the ability for clonal propagation through fragmentation (reviewed in Lewis 2006). Stolonal expansion of encrusting bases and fast linear growth of branches in milleporids have been described as aggressive strategies to pre-occupy substratum space. Interactions involving fire corals can lead to the overgrowth of other sessile organisms. Previous studies have reported the overgrowth of branching Millepora on gorgonians (Wahle 1980) and scleractinian corals such as Porites murrayensis (Müller et al. 1983).

Coral reefs surrounding Moorea Island in French Polynesia have undergone a massive decline in coral cover from a recent outbreak of Acanthaster planci and cyclone Oli, which provides a unique perspective from which to comprehend competitive interactions among reef species under environmental stress. Here, we provide the first report of the overgrowth of living scleractinian corals by the encrusting hydrocoral Millepora platyphylla, Hemprich & Ehrenberg, 1834. During field surveys undertaken at Moorea in 2013, M. platyphylla was found to overgrow several coral taxa, including Porites spp. (Fig. 2.1a, b, d), Pocillopora meandrina (Fig. 2.1c, d) and Phymastrea curta (Fig. 2.1e). The original morphologies (skeleton and corallites) of overgrown taxa remained visible (Fig. 2.1), suggesting a thin layer of superficial overgrowth smothering these corals. A white band discerned at the edge of living corals delimits the growth area of the hydrocoral spreading from its encrusting base towards an adjacent coral colony. Our observations also revealed that such overgrowth triggers the damage and partial death of underlying coral colonies.

Millepora

nian corals nian by the hydrocoral

Fig. 2.1 Millepora platyphylla corals (*) at Moorea overgrowing living corals of various scleractinian species: a and b at back reef Porites sp. (°); c Pocillopora meandrina (+) and d Porites sp. (°) and Overgrowthof living scleracti Pocillopora meandrina (+) on fore reef, 6 m depth; e Phymastrea curta (§) on fore reef, 12 m depth.

This opportunistic spread of Millepora on living scleractinian corals confirm previous descriptions of overgrowth as a strategy employed by fire corals to quickly monopolize substratum space (Brown and Edmunds 2013). This growth strategy may become an important component in the modeling of competition for space among benthic community assemblages in coral reefs.

Acknowledgements

We thank A Merciere for support on the field. We additionally thank three anonymous reviewers and the editor for comments that greatly improved this manuscript. CED and EB are financially supported by the Fonds Québécois de Recherche sur la Nature et les Technologies (FQRNT) and the Marie Curie fellowship MC-CIG-618480, respectively.

CHAPTER 3 Population Structure of the Hydrocoral M. platyphylla in Habitats Experiencing Different Flow Regimes in Moorea, French Polynesia

In revision: Dubé CE, Merciere A, Vermeij MJA, Planes S. Population Structure of the Hydrocoral Millepora platyphylla in Habitats Experiencing Different Flow Regimes in Moorea, French Polynesia. PLoS ONE

Population Structure of the Hydrocoral Millepora platyphylla in Habitats Experiencing Different Flow Regimes in Moorea, French Polynesia

Caroline E. Dubé 1,2*, Alexandre Mercière 2¤, Mark J. A. Vermeij 3,4, Serge Planes 1,2

1 EPHE, PSL Research University, UPVD-CNRS, USR 3278 CRIOBE, F-66860 Perpignan, FRANCE 2 Laboratoire d’excellence “CORAIL”, EPHE, PSL Research University, UPVD-CNRS, USR 3278 CRIOBE, BP 1013, 98729 Papetoai, Moorea 3 Carmabi Foundation, Willemstad, Curaçao 4 Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands ¤ Current address: Centre de Formation et de Recherche sur les Environnements Méditerranéens, UMR 5110, Univ. Perpignan Via Domitia, F-66860 Perpignan, France *Corresponding author: [email protected]

Abstract

While the fire coral Millepora platyphylla is an important component of Indo-Pacific reefs, where it thrives in a wide range of environments, the ecological and biological processes driving its distribution and population structure are not well understood. Here, we quantified this species population structure in five habitats with contrasting hydrodynamic regimes in Moorea, French Polynesia; two in the fore reef: mid and upper slopes, and three in the lagoon: back, fringing and patch reefs. A total of 3651 colonies of fire corals were mapped and measured over 45,000 m2 of surveyed reef. Due to the species’ sensitivity to fragmentation in response to strong water movement, hydrodynamic conditions (e.g. waves, pass and lagoonal circulation) corresponded to marked differences in colony size distributions, morphology and recruitment dynamics among habitats. The size structure varied among reef habitats with higher proportions of larger colonies in calm nearshore reefs (fringing and patch reefs), while populations were dominated by smaller colonies in the exposed fore reefs. The highest densities of fire corals were recorded in fore reef habitats (0.12–0.20 n.m-2) where the proportion of recruits and juveniles was higher at mid slope populations (49.3%) than on the upper slope near where waves break (29.0%). In the latter habitat, most colonies grew as vertical sheets on encrusting bases making them more vulnerable to colony fragmentation, whereas fire corals were encrusting or massive in all other habitats. The lowest densities of M. platyphylla occurred in lagoonal habitats (0.02–0.04 n.m-2) characterized by a combination of low water movement and other physical and biological stressors. This study reports the first evidence of population structure of fire corals in two common reef environments and 46 illustrates the importance of water flow in driving population dynamic processes of these important reef-building species.

1. Introduction

Coral reefs exhibit a remarkable diversity of organisms that reside within highly variable environments resulting in strong spatial variability in species’ distribution patterns (Wilkinson 2008). For scleractinian corals, spatial differences in temperature, light, water flow and water quality conditions can influence their distribution and population dynamics (Glynn 1996; Vermeij and Bak 2002; Fabricius 2005; Monismith 2007). Millepora hydrocorals, also called fire corals, are an important component of reefs communities worldwide where they, similar to scleractinian corals, 3 contribute to reef accretion and community dynamics (Nagelkerken and Nagelkerken 2004; Lewis

2006). Fire corals are gonochoric broadcast spawners that can colonize a wide range of reef

s environments through sexual reproduction (Lewis 2006; Bourmaud et al. 2013) and colony

fragmentation (Edmunds 1999; Lewis 2006). Fire corals often grow into large colonies that preempt

ydrocoral h space and compete with scleractinian corals (Andréfouët et al. 2014; Dubé et al. 2016). On the other hand Millepora species also contribute to the survival of corals during Acanthaster outbreaks as this corallivorous predator tends to avoid Millepora species (Lewis 2006; Kayal and Kayal 2016). Millepora

Hydrodynamic forces in the form of water-displacement, velocity and acceleration have been tructure of recognized as a key factor in determining the shape and occurrence of many reef-building s organisms (Madin et al. 2006; Williams et al. 2013). In coral reef ecosystems, the magnitude of

water flow is mostly related to the wave energy dispersal (Monismith 2007). On barrier reefs, the Population amount of wave energy is highest on the reef crest, where waves break, and subsequently attenuates towards fore reef and lagoonal environments (Monismith 2007; Ferrario et al. 2014). Inside lagoons, internal waves and flows drive circulation and water exchange with the surrounding ocean (Hench et al. 2008; Leichter et al. 2013). Such variation in hydrodynamic regimes, combined with other physical factors (e.g. light, nutrients and disturbances), differently affect the performance of individuals (Hoogenboom and Connolly 2009; Madin et al. 2012a; Darling et al. 2012) resulting in corresponding changes in population structure and community composition.

Water flow can drive the spatial distribution in adult populations through the distribution and dilution of larval settlement cues (Koehl and Hadfield 2004) and dispersal of reproductive propagules (Edmunds et al. 2010; Gleason and Hofmann 2011). Many studies have related the contribution of recruitment to colony size variation in scleractinian corals (e.g., Meesters et al. 2001; Harris et al. 2014) and the size structure of a population often reflects other species specific responses to environmental conditions and disturbances as well (Hughes 1984; Albright and 47

Langdon 2011; Madin et al. 2012b). The size-frequency distribution of fire coral populations could therefore provide insights on which biotic (e.g., recruitment of larvae and asexually produced fragments) and abiotic (e.g., wave energy) factors influence their population structure and dynamics.

Water flow also influences colony growth and morphology (Storlazzi et al. 2005; Madin and Connolly 2006). Under the increasing influence of hydrodynamics, delicate branching corals transform into growth forms able to withstand strong water movement such as compact, robust plating or thick branching morphologies (Kaandorp and Sloot 2001; Chindapol et al. 2013). Such inter- and intraspecific variation resulting in different coral morphologies affects not only their mechanical strength but also their ability to compete for space (Jackson 1979; Denny 2014; Swierts and Vermeij 2016) and capture light and food (Darling et al. 2012; Baird and Hughes 2000). Branching scleractinian corals, such as Acropora cervicornis, often grow into large and delicate arborescent colonies in areas of relatively high water flow (Tunnicliffe 1981), but this growth strategy also renders them extremely vulnerable to breakage when large waves and storm events occur, often resulting in fragmentation or coral mortality (Madin et al. 2014). Asexual reproduction through colony fragmentation can be a successful reproductive strategy to sustain local population growth in some species of scleractinian corals (Tunnicliffe 1981; Baums et al. 2006; Aranceta- Garza et al. 2012). Fire corals are also known for their extensive intra- and interspecific morphological variability across hydrodynamic gradients with consequences due to their vulnerability to wave-induced breakage (Jackson 1979; Weerdt 1981; Edmunds 1999; Lewis 2006). Determining to what degree the population structure of fire corals depends on water flow has so far not been determined.

In this study, we investigated whether and how different reef habitats with contrasting water regimes affect the population structure of Millepora platyphylla, the only species of fire coral identified in French Polynesia (Bosserelle et al. 2014). Surveys of M. platyphylla were conducted in five habitats on the north shore of Moorea with differing amounts of water flow: fore reef habitats with high water movement, especially on the upper slope and decreasing with depth to the mid slope. Lagoonal habitats (back reefs, fringing reefs and patch reefs) are sheltered from waves and oceanic swell, except during storms, and water movement in these habitats is less than on the fore reef (Monismith 2007; Ferrario et al. 2014). We examined colony size distribution, morphological variability and recruitment dynamics to assess to what degree the variability in the population structure of M. platyphylla among reef habitats can be attributed to different flow regimes.

2. Materials and Methods

2.1. Study sites and field surveys

Between April and December 2013, a series of surveys were conducted on the north shore of Moorea, French Polynesia, in the South Pacific Ocean (17,5267 S, 149,8348 W), at four different locations (Tiahura, Papetoai, Cook’s Bay and Temae). Five habitats with contrasting water flow regimes were selected; two in a fore reef environment: the mid slope (13 m depth) and the upper slope (6 m depth), and three in the lagoon (< 1 m depth): the back reef, fringing reef and patch reef (Fig. 3.1 and Table S1). These habitats greatly differ in terms of water flow. The fore reef experiences strong wave action from incoming waves that break on the reef crest with gradual swell 3 wave attenuation towards deeper waters (Hearn 1999; Monismith 2007). Because of this strong

linear relationship between wave forcing and water depth (Hearn 1999), we assumed that the s colonies of M. platyphylla growing within fore reef habitats are exposed to lower wave energy on

the mid slope compared to the those growing on the upper slope, near where the waves break. In the

ydrocoral h

lagoon, the wave energy disperses from the reef crest towards nearshore reefs (Monismith 2007).

Millepora

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s Population

Using a meta-analysis approach, a recent study on wave energy across reef environments revealed that the reef crest dissipated 70% of the incident swell wave energy with gradual wave attenuation from the back reef to the shore (Ferrario et al. 2014). Consequently, we assumed that wave energy is higher on the back reef, near the reef crest compared to the fringing reef, a nearshore reef. Although the patch reef is located in a nearshore narrow channel, the wave energy there is also higher than on the fringing reef due to its proximity to the reef crest and to the currents that run on either side of the channel (i.e. pass circulation). Variations in other physical constraints exist between the fore reef and lagoonal habitats in terms of e.g., temperature, water clarity, nutrient and disturbances (Done 1982; Witman 1992). Within each habitat, three 300 m long by 10 m wide belt transects were laid over the reef parallel to shore, at least 30 m apart, resulting in a total of 45,000 m2 reef area being surveyed. All colonies of M. platyphylla that were at least 50% within the transect borders were measured, photographed and georeferenced using SCUBA.

2.2. Spatial distribution patterns

All M. platyphylla colonies were georeferenced by determining their position along the transect-line (0 to 300 m) and straight-line distance from both sides of the transect (0 to 10 m). From these measures, each colony was mapped with x and y coordinates, from which the distribution index (DI) and mean neighborhood distance (ND) were calculated using the spdep package (Bivand et al. 2013) in R (R Development Core Team 2013). The DI is based on Ripley’s method (Ripley 1976) and calculated for each transect to determine whether colonies were having a contagious (DI > 1), random (DI ≈ 1) or homogenous (DI < 1) pattern of distribution (Urban 2000). The mean distance to each colony’s 10 nearest neighbors was estimated and the mean ND was calculated for each transect. The mean colony density (n.m-²) and cover (%) were also calculated for each transect (i.e. 3000 m2). Using these variables, variability in the spatial distribution among habitats was quantified by one-way PERMANOVA tests in PRIMER 6 software (Clarke et al. 2008), since assumptions of parametric testing could not be met. Pair-wise tests followed the PERMANOVA to assess the degree of similarity among habitats. In order to determine how different habitats with contrasting water regimes affect the spatial distribution of M. platyphylla, we assumed that swell wave energy exposure decreases with habitat depth and its proximity to the coastline, as demonstrated in previous studies (Hearn 1999; Ferrario et al. 2014). Consequently, the density, cover, DI and ND were regressed against the mean depth and mean distance from shore estimated from the three transects within each of the five surveyed habitats and Pearson’s r coefficient was used to test for significant correlations.

2.3. Colony size distribution

The size-frequency distributions of M. platyphylla populations were generated from estimates of colony sizes computed from 2D photographs. Each colony size (projected surface) was then measured (in cm²) using ImageJ 1.4f software (Abràmoff et al. 2004). The size-frequency distribution for each transect was given as percentages of all colonies belonging to 10 size classes on a logarithmic scale. Data were then analyzed using basic statistical measures of size hierarchies

(Bendel et al. 1989): the coefficient of variation (CV) and skewness (g1), indicative of the relative abundance of small and large colonies within a population. CV and g1 were computed for each habitat per transect together with standard descriptive statistics, such as 95% percentile of the mean (describes the maximum colony size reached within a population, see Soong 1993) and the 3 probability that the data are normally distributed (Kolmogorov-Smirnov test, Pnorm). Differences

in size-frequency distributions among habitats were quantified using one-way PERMANOVA based s on normalized abundances. Spearman’s rank coefficient and pair-wise tests followed the

PERMANOVA to assess the degree of similarity among habitats.

ydrocoral

2.4. Recruitment dynamics Millepora The mean abundance and proportion of recruits, juveniles and adults were estimated for each

transect whereby the three life stages were defined based on colony size. Colonies with a size below tructure of 1 cm² were considered as recruits, colonies with a size between 1 and 20 cm² were juveniles and s colonies with a size above 20 cm² were adults (Penin et al. 2010). Differences in abundance and

proportion (the fraction in the entire population) of early life stages (both recruits and juveniles) Population among habitats were quantified using one-way PERMANOVA, followed by a pair-wise test. Pearson’s correlation coefficient was used to determine whether the abundance of early life stages increased with the abundance and cover of adults, and whether differences in their proportions among habitats correlate with higher or lower water movement, i.e. depth and distance from shore.

2.5. Colony morphology

For each colony, the maximum height was recorded and the colony size was obtained from photographs. Colonies < 20 cm2 were removed from our dataset to only estimate the mean height and size of adults for each transect. Adult colonies were assigned to one of these morphologies: 1) massive: solid colonies, roughly hemispherical in shape (Fig. 3.2A), 2) encrusting: thin colonies growing against the substratum (Fig. 3.2B) and 3) “sheet tree”: encrusting bases with platelike outgrowths facing wave energy (see Jackson 1979) (Fig. 3.2C). Difference in morphology among habitats was quantified with one-way PERMANOVA and pair-wise tests.

2.6. Population structure assessment

Similarities in population structure based on the following parameters: density, cover, DI, ND, mean adult colony size and height, and proportion of recruits, juveniles and adults were calculated and visualized using a hierarchical complete-linkage agglomerative clustering (CLUSTER) method and a non-parametric multidimensional scaling (MDS) ordination on normalized data. Multivariate PERMANOVA on aforementioned characteristics was used to determine differences in population structure of M. platyphylla among the five surveyed habitats, i.e., those on the fore reef (mid and upper slopes) and those in lagoonal habitats (back, fringing and patch reefs).

3. Results

3.1. Spatial distribution of Millepora platyphylla

M. platyphylla was found in all habitats, but its population composition differed among habitats. A total of 3651 colonies of M. platyphylla were counted in the five surveyed habitats. Most colonies (77.7%) occurred on fore reef habitats, whereas M. platyphylla colonies on patch reefs accounted only for 5.2% of all colonies (Table S2). Colony density differed among habitats (PERMANOVA test, P < 0.01) and was higher on the upper slope (0.20 ± 0.03 n.m-2, N = 1761) and mid slope (0.12 ± 0.05 n.m-2, N = 1075), i.e. fore reef habitats, compared to lagoonal habitats (back reef: 0.03 ± 0.01 n.m-2, N = 324, fringing reef: 0.04 ± 0.03 n.m-2, N = 302 and patch reef: 0.02 ± 0.00 n.m-2, N = 189) (Fig. 3.3A). M. platyphylla cover also differed among habitats (PERMANOVA test, P < 0.01) and was again highest on the upper slope (3.2 ± 0.4%, Fig. 3.3B). Colonies on the fringing reef, mid slope and upper slope occurred in a contagious pattern of distribution (DI: 2.74–4.18), while colonies in the back and patch reefs were more evenly distributed (≤ 1.93) (Fig. 3.3C, PERMANOVA test, P < 0.05). Colonies occurred closer together on the mid slope (6.64 ± 1.86 m)

52 and upper slope (4.09 ± 0.34 m) where the average distance among neighboring fire coral colonies was 4.3 times smaller compared to lagoonal habitats (back reef: 18.39 ± 1.10 m, fringing reef: 14.31 ± 4.41 m and patch reef: 36.51 ± 2.95 m) (Fig. 3.3D, PERMANOVA test, P < 0.01).

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3.2. Size structure of Millepora platyphylla

Across all habitats, 85% of the surveyed colonies were smaller than 1000 cm² and approximately one third (30%) of aforementioned colonies fell in recruit and juvenile size classes, i.e. were smaller than 20 cm². The size-frequency distributions of M. platyphylla populations differed among certain habitats, but were similar among the lagoonal fringing and patch reefs with populations dominated by both small and large colonies resulting in bimodal size-frequency distributions (Fig. 3.4, Spearman’ rank coefficient 87.9%, P < 0.05).

Fig. 3.4 Size-frequency distributions of M. platyphylla across the five surveyed habitats. Colony size (cm2) data were distributed among 10 size classes based on a logarithm scale (log2). Frequencies (%) for each size class were averaged by habitats with total population size (N in Table S2) and error bars show the standard error for transect replicates.

All fire coral populations were characterized by relatively symmetrical size distributions (g1: –0.01– 0.71), but the degree of skewness was again lower on the fringing and patch reefs (Table 3.1). The maximum colony size differed among habitats and was smallest on the mid slope (95%: 1295 cm2) and back reef (2512 cm2) compared to other populations (upper slope: 8514 cm2, fringing reef: 7107 cm2 and patch reef: 9890 cm2) (Table 3.1). With 64% of all colonies falling in a few medium size classes (32–512 cm2, Fig. 3.4), colonies comprising back reef populations were very similar relative to each other as indicated by the lowest coefficient of variation (CV: 0.33, Table 3.1) of all habitats. Overall, the composition of M. platyphylla populations in terms of colony density and size differed among the five habitats, except between the two lagoonal habitats, the fringing and patch reefs, located closest to shore. 3 Table 3.1 Index describing the population size structure and recruitment for M. platyphylla across the five habitats.

Habitat Colony size (cm²) Recruitment s Non-transformed ln-transformed Abundance (n) Proportion (%)

ydrocoral

Mean (SE) 95% Pnorm CV g1 Recruit Juvenile Recruit Juvenile h

Patch 3090.48 (1293.52) 9889.89 <0.01 0.51 –0.01 1.00 (1.73) 11.30 (3.06) 1.47 (2.55) 17.93 (4.52)

Fringing 1590.07 (328.94) 7107.16 <0.01 0.49 0.14 1.33 (0.58) 21.33 (17.21) 1.74 (1.86) 24.00 (8.20) Millepora

Back 509.87 (97.07) 2512.02 <0.01 0.33 0.68 --- 13.00 (7.55) --- 11.77 (5.94)

Upper 2308.20 (115.84) 8513.79 <0.01 0.54 0.42 9.33 (3.51) 161.00 (32.70) 1.57 (0.53) 27.26 (3.53)

tructure of s

Mid 819.04 (73.30) 1295.23 <0.01 0.63 0.64 12.00 (4.36) 159.00 (53.33) 3.44 (0.40) 45.86 (5.15)

Population 3.3. Recruitment of Millepora platyphylla

In total, 71 recruits (2%) and 1094 juveniles (30%) were observed within the five surveyed habitats (Table S2). The abundance of recruits and juveniles differed among habitats (PERMANOVA test, P < 0.05 and P < 0.01, respectively) with 96% of all recruits and juveniles occurring in fore reef habitats (48% for both the mid and upper slopes) and only small numbers were observed in lagoonal habitats (Table 3.1). The fraction of the entire population consisting of recruits and juveniles differed among habitats (PERMANOVA test, P < 0.01). Recruits (3.4 ± 0.4%) and juveniles (45.9 ± 5.1%) dominated populations occurring on the mid slope, i.e. deeper waters, compared to shallow waters in both fore reef and lagoon (Table 3.1; Fig. 3.5). Only in lagoonal habitats did the abundance of adults, not their total cover, and the abundance of both recruits and juveniles increase simultaneously suggesting the presence of a stock-recruitment relationship (Fig. 3.6A), that was not observed in fore reef habitats (Fig. 3.6B).

3.4. Morphology of Millepora platyphylla

M. platyphylla colonies ranged in size from 0.18 cm² to 189 062 cm² (projected surface) and 0.1 cm up to 130 cm in height. Mean colony size and height of adults (i.e., all colonies > 20cm2) differed among habitats (PERMANOVA tests, P < 0.01). Fire corals were approximately 4 times larger on average in the upper reef slope (2308 ± 115 cm2), fringing (1590 ± 329 cm2) and patch reef (3090.48 ± 1294 cm2), compared to colonies growing in the back reef and mid slope (510 ± 97 cm2 and 819 ± 73 cm2, respectively, Table 3.1). The average height of fire coral colonies was highest in fringing (24 ± 5 cm) and patch reefs (25 ± 8 cm), i.e. nearshore habitats (Table S2). Morphologies of adult colonies differed among habitats (PERMANOVA test, P < 0.01). Massive morphologies dominated nearshore reefs (fringing reef: 79.7 ± 8.3% and patch reef: 59.0 ± 9.9%) whereas colonies were mostly encrusting on the mid slope (79.9 ± 1.1%) and back reef (74.5 ± 5.2%) (Fig. 3.7 and Table S3). On the upper slope, 69.5% (± 3.2) of the colonies displayed the sheet tree morphology, while the remaining colonies were encrusting.

ydrocoral

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recruitment relationship in the fore reef (i.e. mid and upper slopes). Each circle represent the mean Population abundance for each transect surveyed. Note the different scales on x and y axes.

3.5. Population structure assessment

Combining all variables into a single multivariate analysis, the population structure of M. platyphylla varied significantly among reef habitats (PERMAVOVAs, P < 0.01). Based on MDS, two main clusters can be distinguished: one with populations from wave exposed fore reef habitats, i.e. mid and upper slopes, and a second cluster consisting of populations from lagoonal habitats, i.e. back, fringing and patch reefs (Fig. 3.8) where calmer waters prevail. The main differences between these two clusters are that fore reef populations are characterized by a high relative abundance of recruits and juveniles (mid slope), or a high density and cover (upper slope). Populations from lagoonal habitats are characterized by large colony size and height (both fringing and patch reefs) and widely spaced colonies. Back reef populations are characterized by the dominance of adult colonies.

Using all variables of each transect surveyed within the fore reef habitat (i.e. six replicates), we found that adult colonies became smaller (i.e. colony size decreases) with increasing depth where wave energy was lower compared to shallow reefs (r = –1.00, P < 0.001; N = 6). Fractions of recruits and juveniles increased with increasing depth (r = 0.91, P < 0.05 and r = –0.92, P < 0.05; N = 6), while total cover decreased (r = –0.97, P < 0.01; N = 6). Colonies grew in an encrusting morphology at mid depth and in the sheet tree morphology in shallow waters (Fig. 3.7). Among shallow lagoonal habitats, we found that adult colonies became smaller towards the back reef, far from shore (r = –0.76, P < 0.01; N = 9), where wave energy was higher and colonies mostly occurred in the encrusting morphology (Fig. 3.7). Total cover increased with increasing distance from the coast (r = –0.69, P < 0.05; N = 9).

ydrocoral h

Fig. 3.8 Non-metric multidimensional scaling (MDS) plot of M. platyphylla population structure across the five surveyed habitats. Different shapes indicate the three transects for each habitat and grey lines show Millepora clusters given by dendogram based on Eucledian distance of 4 at a stress level of 0.09. The surimposed red lines define the Eucledian distance coefficient on normalized data based on Spearman ranking, with each vector having lengths ≥ 0.4: density, cover, distribution index, mean neighborhood distance, mean height and 2 2 2 tructure of size of adults, and proportion of recruits (< 1 cm ), juveniles (1–20 cm ) and adults (> 20 cm ). The second s transect of the fringing reef is shown as a single group mostly related to a small population size (i.e. 27 colonies, Table S2).

4. Discussion Population

In Moorea, M. platyphylla colonized a wide range of habitats reflecting its ability to adapt and survive in a large variety of environmental settings and this study is, to our knowledge, the most extensive sampling ever conducted to assess local patterns in population structure of Milleporid corals. Reef habitats where M. platyphylla colonies were found were selected because of their difference in water regimes according to their depth and proximity to the coastline (see Materials and Methods for details). Due to M. platyphylla’s sensitivity, especially of larger colonies to fragmentation induced by wave action or water movement (Fig. 3.2), we sought for possible relationships between hydrodynamic conditions and the population structure of fire corals on Moorea. Differences in population size structure, recruitment and morphology existed among habitats and confirmed expected relationships between such characteristics and the amount of water flow in several of the five surveyed habitats (i.e. mid slope, upper slope, back reef, fringing reef, and patch reef). The highest densities of fire corals, including that of recruits and juveniles,

59 occurred on the exposed fore reef (i.e. mid and upper slopes) whereby colonies were often observed growing in contagious pattern of distribution. In calm lagoonal environments (i.e. back, fringing and patch reefs) fire coral colonies occurred in low densities, where the number of recruits and juvenile was low and colonies grew in a random pattern of distribution. Variability in density among fore reef and lagoonal habitats has been described for numerous other sessile organisms and related to a large number of environmental factors such as water flow, solar irradiance, sedimentation and/or species’ life history traits (e.g., reproductive mode, competitive ability, morphological plasticity; (Vermeij et al. 2007; Roth and Knowlton 2009; Doropoulos et al. 2015; Adjeroud et al. 2015).

Although differences in size-frequency distributions among habitats were found, e.g. few larger colonies in the calm fringing and patch reefs, smaller colonies in the mid slope and medium size colonies in the back reef, the degree of skweness was similar among all habitats with populations consisting of both small and large colonies. This result likely reflects low mortality in small size classes, as well as the persistence of the larger ones (Adjeroud et al. 2007). Our results showed that the proportion of recruits and juveniles was highest on the mid slope, an exposed reef where wave energy is reduced due to increased depth (Hearn 1999). Earlier reports have also shown the influence of depth and water flow on the recruitment dynamics in some scleractinian coral species in many reef locations (Chiappone and Sullivan 1996; Penin et al. 2007; Penin and Adjeroud 2013). These studies revealed an increase in the occurrence of recruits and juveniles with increasing depth. Another study compiling juvenile data of all coral species surveyed in Palmyra Atoll in the central Pacific has shown that most juveniles were growing at middle depth (i.e. 14 m) in a fore reef habitat (Roth and Knowlton 2009), as for M. platyphylla. Water flow is also considered as an important factor influencing a colony’s morphology (Veron 2000; Todd 2008), generally showing a transition from easily fragmented morphologies towards more robust morphologies with increasing water movement (Kaandorp and Sloot 2001; Chindapol et al. 2013). This study shows a similar trend whereby large and high colonies were more common in protected nearshore habitats (i.e. fringing and patch reef) and small and encrusting in exposed mid slope and back reef habitats. On the upper slope, near where the waves break, fire corals are large, but largely encrusting, and of the unusual sheet tree morphology of Millepora that was only observed in low proportions in all other habitats (0–9%).

Fire corals, like many other reef-building organisms, reproduce through both asexual and sexual reproduction with a dimorphic life cycle, with a pelagic dispersive phase (i.e. medusoids and larvae), followed by a sessile adult phase (Lewis 2006). If dispersal distances are small due to low water movement or retention, the spatial distribution of adults could influence the distribution of

60 young colonies as previously shown for scleractinian corals (Edmunds 2000; Penin et al. 2007; Vermeij and Sandin 2008; Penin and Adjeroud 2013). On Moorea the abundance of M. platyphylla recruits and juveniles could not be related to adult population size in fore reef habitats. The proportions of recruits and juveniles were highest at mid-depths (13 m) on the fore reef where wave energy and solar irradiance are lower compared to the shallower depths (as described in Roth and Knowlton 2009). Low wave energy can indeed increase settlement success of both coral larvae and fragments (Price 2010). At shallow depths (6 m) on the fore reef, high wave energy and irradiance can reduce the abundance of settlement cues (Price 2010), but also indirectly affect settler survival through high grazing pressure by herbivorous fishes at this depth which constitutes a major source of mortality for juvenile corals on the upper slope in Moorea (Penin et al. 2010). The abundance of coral fragments that re-attached to the reefs can also be reduced due to high wave energy and 3

subsequent increased mortality (Highsmith 1982). Such physical and biological constraints in a

dynamic environment likely reduce local recruitment rates and prevent high coral cover (Hughes s and Connell 1999). However, the highest cover of M. platyphylla (3.2%) occurred on the upper

slope where wave breaking first occurs, i.e. wave energy is the highest. Many studies investigating ydrocoral

h spatial distributions in coral reef communities often find that high energy reef zones restrict species’

distributions and cover (Dollar 1982; Storlazzi et al. 2002). M. platyphylla shows the opposite Millepora trend: we observed high density and cover in the upper slope, a high energy reef zone, where

colonies are growing in a contagious pattern of distribution. Such differences in fire coral tructure of distribution patterns in habitats of high energy are mostly related to the wave-vulnerable sheet tree s morphology of Millepora. This growth form occurred nearly exclusive on the upper slope, while

colonies were massive or encrusting in other habitats. The unusual sheet tree morphology observed Population in the upper slope has been described as a successful strategy exploited by Millepora to preempt the space and to compete with other coral taxa (Jackson 1979; Dubé et al. 2016). Waves can easily break the blades and enhance population size through clonal propagation (Edmunds 1999), while the encrusting bases remain intact and grow through stolonal spreading (Dubé et al. 2016). The fact that M. platyphylla can rapidly overtake newly available space through clonal propagation and stolonal spreading may explain the increase of fire coral cover on Moorea’s reefs following the massive decline in coral cover from the Acanthaster outbreaks and cyclone Oli (Kayal et al. 2012). Between 2006 and 2010, M. platyphylla cover was stable at approximately 1% at 6 m on the fore reef, i.e. more than 3 times lower than in 2013 at the same location. On the other hand, fragmentation usually induces corals to regress in size and increases mortality, especially in small size classes (Wallace 1985). Here, the sheet tree morphology is more easily fragmented, but the unilateral growth of Millepora allows them to reach larger sizes. This study shows that asexual reproduction through fragmentation and stolonal spreading likely play a key role in structuring M.

61 platyphylla populations where water flow is high and where fire corals suffer wave-induced breakage.

In the lagoonal environment, the wave energy is reduced by the reef crest (Ferrario et al. 2014) likely explaining the positive stock-recruitment relationship found in these habitats. There is evidence showing that the fecundity in populations of sessile marine broadcast spawners, such as Millepora species, is strongly determined by the local density of adults (Coma and Lasker 1997; Hughes et al. 2000), and especially where water movement is reduced and local retention occurs. The low abundance of early life stages observed in all lagoonal habitats may result from competition with macroalgae and sediment smothering affecting back, patch and fringing reefs inside the lagoon of Moorea (Galzin and Pointier 1985). The presence of macroalgae and high sedimentation can additionally reduce adults’ fecundity (Richmond 1993; Hughes et al. 2007; Foster et al. 2008), larval settlement cues (Kuffner et al. 2006), larval survival (Gilmour 1999) and settlement space (Box and Mumby 2007). Greater impacts of anchoring and poorer water quality compared to fore reef habitats also likely contribute to the low abundance of Milleporid corals inside the lagoon (Fichez et al. 2005; Cooper et al. 2007). The back and patch reefs are the nearest to the reef crest where waves break resulting in low residence times and high flushing rates from large incoming waves that break on the north shore of Moorea during the austral summer (Hench et al. 2008). These dynamics of water flow are known to negatively affect local recruitment rates of sexual propagules in scleractinian corals on the back reef of Moorea (Edmunds et al. 2010) and could also apply to M. platyphylla. In the lagoon, fire corals are characterized by wave-tolerant morphologies (i.e. encrusting and massive) suggesting that asexual reproduction through colony fragmentation is less likely of structuring importance compared to fore reef habitats. Colonies on the fringing reef, where wave energy is typically low, were distributed in patches. In Moorea, the fringing reef is exposed to large waves in the austral summer (Hench et al. 2008), which has the potential to enhance the breakage of the colonies during short periods. Subsequent calm periods can facilitate fragment survival and reattachment resulting in the patches of M. platyphylla observed.

It must be noted that abundance of recruits and juveniles was likely underestimated in this study as they are difficult to find due to their small size during field surveys. Still, we identified 32% of 2 colonies < 20 cm (recruit and juvenile), a higher fraction than observed for 14 different genera of scleractinians corals in Moorea (13–29%, see Penin et al. 2007). The abundance of fire corals around Moorea is also higher compared to more diverse and healthy reefs, such as the Great Barrier Reef (Done 1982) and the shallow fringing reefs in the Virgin Islands (Brown and Edmunds 2013). Our results thus suggest that fire coral populations are relatively resilient in the face of recent and major disturbances that have impacted Moorea’s reefs. The maintenance and recovery of fire coral

62 populations are foremost sustained by the growth of remnant colonies, local recruitment through sexual reproduction where wave energy is low and clonal propagation in high wave energy zones.

Acknowledgements

We are grateful to F Lerouvreur and M Besson who contributed to the fieldwork and E Boissin for valuable discussion. We also thank the CRIOBE staff for technical and logistic support.

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Supporting Information

Table S1 Locations of each transect surveyed in the five habitats.

Distance Distance Habitat Latitude (°S) Longitude (°W) Depth (m) to coast (m) to crest (m)

Patch 1 17.4775 149.7673 35.40 66.47 0.97 Patch 2 17.4759 149.7699 20.28 52.78 0.90 Patch 3 17.4742 149.7726 26.91 58.98 0.59

Fringing 1 17.4881 149.8967 331.05 564.65 0.79

Fringing 2 17.4902 149.8676 323.32 561.96 0.84 Fringing 3 17.4836 149.8165 40.07 1198.13 0.80

Back 1 17.4838 149.8742 917.83 87.80 0.65

Back 2 17.4834 149.8773 1074.67 65.50 0.81 Back 3 17.4832 149.8805 927.40 37.72 0.76

Upper 1 17.4820 149.8755 1110.26 84.56 6.09

Upper 2 17.4818 149.8786 1176.29 93.45 5.95 Upper 2 17.4822 149.8816 995.20 76.98 5.65

Mid 1 17.4816 149.8755 1155.73 122.36 13.17 Mid 2 17.4813 149.8785 1215.28 135.54 12.99

Mid 3 17.4819 149.8817 1034.70 118.32 12.59

Table S2 Index describing the spatial distribution, recruitment and morphology for Millepora platyphylla across the five surveyed habitats.

Spatial Distribution Recruitment Morphology Habitat N % Adult N Density (n.m-2) Cover (%) DI ND Recruit Juvenile Adult Recruit Juvenile Adult size (cm2) Height Patch 1 62 0.02 0.61 1.60 39.81 --- 8 51 --- 13.56 86.44 4074.63 20.84 Patch 2 68 0.02 0.29 2.35 34.13 3 12 53 4.41 17.65 77.94 1625.37 19.62 Patch 3 59 0.02 0.60 1.82 35.60 --- 14 48 --- 22.58 77.42 3571.44 33.81 Tot / Mean (SE) 189 0.02 (0.00) 0.50 (0.18) 1.92 (0.39) 36.51 (2.95) 3 34 152 1.47 (2.55) 17.93 (4.52) 80.60 (5.06) 3090.48 (1293.52) 24.76 (7.86) Fringing 1 78 0.03 0.27 3.05 15.83 --- 14 64 --- 17.95 82.05 1255.04 23.15 Fringing 2 27 0.01 0.11 6.38 17.76 1 9 17 3.70 33.33 62.96 1912.57 30.41 Fringing 3 197 0.07 0.82 3.10 9.34 1 41 154 1.52 20.71 77.78 1602.59 19.03 Tot / Mean (SE) 302 0.04 (0.03) 0.40 (0.37) 4.18 (1.91) 14.31 (4.41) 2 64 235 1.74 (1.86) 24.00 (8.20) 74.26 (10.02) 1590.07 (328.94) 24.20 (5.76) Back 1 101 0.03 0.15 1.28 19.66 --- 12 89 --- 11.88 88.12 499.72 7.69 Back 2 119 0.04 0.20 1.25 17.79 --- 21 98 --- 17.65 82.35 611.62 9.37 Back 3 104 0.03 0.14 1.44 17.73 --- 6 98 --- 5.77 94.23 418.27 8.35 Tot / Mean (SE) 324 0.03 (0.01) 0.16 (0.03) 1.32 (0.10) 18.39 (1.10) --- 39 285 --- 11.77 (5.94) 88.23 (5.94) 509.87 (97.07) 8.47 (0.85) Upper 1 510 0.17 2.78 4.07 4.37 6 124 380 1.17 24.27 74.36 2189.29 9.26 Upper 2 656 0.22 3.66 3.61 3.71 9 173 474 1.37 26.37 72.26 2314.60 7.55 Upper 3 595 0.20 3.22 4.34 4.20 13 186 398 2.18 31.16 66.67 2420.71 6.26 Tot / Mean (SE) 1761 0.20 (0.03) 3.22 (0.44) 4.01 (0.37) 4.09 (0.34) 28 483 1252 1.57 (0.53) 27.26 (3.53) 71.10 (3.98) 2308.20 (115.84) 7.69 (1.51) Mid 1 542 0.18 0.86 2.64 4.68 17 219 306 3.14 40.41 56.46 840.45 8.07 Mid 2 230 0.08 0.26 2.20 8.38 9 117 105 3.90 50.65 45.45 737.43 6.11 Mid 3 303 0.10 0.45 3.38 6.86 10 141 152 3.30 46.53 50.17 879.25 5.62 Tot / Mean (SE) 1075 0.12 (0.05) 0.52 (0.31) 2.74 (0.59) 6.64 (1.86) 36 477 563 3.44 (0.40) 45.86 (5.15) 50.69 (5.52) 819.04 (73.30) 6.60 (1.30) N, population size; DI, distribution index; ND, Neighborhood distance; Recruits, < 1 cm2; Juveniles, 1–20 cm2. Values in bold were average per habitat and SE for variation among transects.

Table S3 Average percentages of adult colonies for M. platyphylla with encrusting, sheet tree and massive morphology across surveyed habitats.

Habitat Encrusting Sheet tree Massive

Mid Slope 73.95 (1.10) 6.63 (2.41) 19.42 (1.77)

Upper Slope 30.51 (3.21) 69.49 (3.21) ---- Back Reef 74.51 (5.21) 9.25 (3.16) 16.24 (2.06)

Fringing Reef 20.28 (8.30) ---- 79.72 (8.30) Patch Reef 37.83 (9.41) 3.14 (3.14) 59.03 (9.91)

ydrocoral

Millepora

tructure of

s Population

CHAPTER 4 Genetic diversity and differentiation in Millepora species, as revealed by cross-species amplification of novel microsatellite loci

In press: Dubé CE, Planes S, Zhou Y, Berteaux-Lecellier V, Boissin E. Genetic diversity and differentiation in reef-building Millepora species, as revealed by cross-species amplification of fifteen novel microsatellite loci. PeerJ

Genetic diversity and differentiation in reef-building Millepora species, as revealed by cross-species amplification of fifteen novel microsatellite loci

Caroline E. Dubé1,2, Serge Planes1,2, Yuxiang Zhou1, Véronique Berteaux-Lecellier2, Emilie

Boissin1,2

1 EPHE, PSL Research University, UPVD-CNRS, USR 3278 CRIOBE, F-66860 Perpignan, FRANCE

2 Laboratoire d’excellence “CORAIL”, EPHE, PSL Research University, UPVD-CNRS, USR 3278

CRIOBE, BP 1013, 98729 Papetoai, Moorea

Corresponding Author: Caroline E Dubé Email address: [email protected]

Abstract

Quantifying the genetic diversity in natural populations is crucial to address ecological and evolutionary questions. Despite recent advances in whole-genome sequencing, microsatellite markers have remained one of the most powerful tools for a myriad of population genetic approaches. Here, we used the 454 sequencing technique to develop microsatellite loci in the fire coral Millepora platyphylla, an important reef-builder of Indo-Pacific reefs. We tested the cross- species amplification of these loci in five other species of the genus Millepora and analyzed its success in correlation with the genetic distances between species using mitochondrial 16S sequences. We succeeded in discovering fifteen microsatellite loci in our target species M. platyphylla, among which twelve were polymorphic with 2 to 13 alleles and a mean observed heterozygosity of 0.411. Cross-species amplification in the five other Millepora species revealed a high probability of amplification success (71%) and polymorphism (59%) of the loci. Our results show no evidence of decreased heterozygosity with increasing genetic distance. However, only one locus enabled measures of genetic diversity in the Caribbean species M. complanata due to high proportions of null alleles for most of the microsatellites. This result indicates that our novel markers may only be useful for the Indo-Pacific species of Millepora. Measures of genetic diversity revealed significant linkage disequilibrium, moderate levels of observed heterozygosity (0.323– 0.496) and heterozygote deficiencies for the Indo-Pacific species. The accessibility to new polymorphic microsatellite markers for hydrozoan Millepora species creates new opportunities for

70 future research on processes driving the complexity of their colonization success on many Indo- Pacific reefs.

1. Introduction

Coral reefs are increasingly threatened by chronic and acute stressors (Bellwood et al. 2004) and are expected to be highly vulnerable to future climate change due to rapidly increasing sea surface temperatures and ocean acidification (Hoegh-Guldberg et al. 2007; Pandolfi et al. 2011, Kuffner et al. 2015). These anthropogenic disturbances can further change the biodiversity in coral reefs and may hamper their capacity to deliver important sources of ecosystem services to millions of people (Wilkinson 2008; Cardinale et al. 2012). The capacity of reef organisms to survive and adapt to such environmental changes will partially depend on their levels of genetic diversity, which is key for a species’ ability to persist in changing environments (Frankham 2005; Barrett and Schluter 2008; Hoffmann and Sgrò 2011). Many studies have focused on elucidating the underlying mechanisms of the origin and maintenance of genetic variation in populations of scleractinian corals 4 as they provide much of the habitat framework and structural complexity of reefs (e.g. Baums et al.

2005; Baums 2008; Davies et al. 2015).

For long-live sessile organisms, such as reef-building corals, patterns of genetic diversity at both Millepora local and global scales are highly governed by the dispersal of sexual larvae (Baird et al. 2009;

Harrison 2011). Molecular studies have uncovered a wide range of dispersal patterns in building - scleractinian corals, from populations primarily sustained by self-recruitment (Gilmour et al. 2009; Mokhtar-Jamaï et al. 2013) through ecologically significant gene flow and connectivity among their populations (van der Ven et al. 2016; Lukoschek et al. 2016). Furthermore, the degree of genetic variation in partially clonal reef organisms is heavily influenced by the relative contribution from sexual and asexual reproduction for local population maintenance (e.g., Baums et al. 2006; Pinzόn et al. 2012; Adjeroud et al. 2014). While our understanding of population genetics in scleractinian corals has improved considerably over the last decade, such information remains unavailable for Millepora hydrocorals (‘fire corals’).

Millepora hydrocorals are an important component of reef communities worldwide where they, Geneticdiversity and reef differentiation in similar to scleractinian corals, significantly contribute to reef accretion (Nagelkerken and Nalgelkerken 2004; Lewis 2006). Although fire corals compete with other reef-building taxa (Wahle 1980; Dubé et al. 2016), they also favor coral survival during Acanthaster outbreaks, highlighting their key ecological role in reef resilience (Kayal and Kayal 2016). Despite their major importance for reef conservation, fire corals have been relatively understudied and not much is known with respect to their genetic diversity, population structure or life history (e.g. reproductive strategies). 71

Few studies have shown that Millepora species can colonize a wide range of reef environments via both sexual propagules (Lewis 2006; Bourmaud et al. 2013) and asexual reproduction through fragmentation (Edmunds 1999; Lewis 2006). While they are sessile and have limited tolerance to environmental changes (Lewis 2006), species of Milleporidae have a wide distribution range, i.e. circumtropical (Boschma 1956). Fire corals are also known for their extensive morphological variability, which has caused problems in resolving their systematics (Boschma 1948). There is currently no agreement regarding the number of Millepora species and no phylogenetic study investigating the genetic relationships among them (but see Ruiz-Ramos et al. 2014 for a species complex in the Caribbean). Although microsatellite loci have been identified in Millepora alcicornis (Ruiz-Ramos and Baums 2014), there was a lack of highly variable genetic markers for this genus until very recently (but see Heckenhauer et al. 2014). The development of new molecular markers for Millepora species will increase our knowledge on the genetic diversity of a conspicuous reef-building organism across its geographic range. These microsatellite markers will enable further studies on the biological, ecological and evolutionary processes underlying the population persistence of Millepora hydrocorals.

Microsatellites, also known as simple sequence repeats (SSRs) or short tandem repeats (STRs), have emerged as one of the most powerful genetic markers in population and evolutionary genetics (Selkoe and Toonen 2006). Improvements in next generation sequencing techniques have provided new opportunities for microsatellite isolation in non-model organisms (i.e. with no genetic information available) (Zhang et al. 2011), with a good representativeness of loci across the genome (Martin et al. 2010). Because microsatellites are codominant (Estoup et al. 1993), highly polymorphic (Schlötterer 2000) and transferable among closely related species (Cheng et al. 2012), they are commonly used for a remarkable array of applications, such as inferring genetic diversity (Silva and Gardner 2015; Nakajima et al. 2016) and population structure patterns (Noreen et al. 2009; Boissin et al. 2016), evaluating reproductive strategies (Baums et al. 2014; Ardehed et al. 2015) and parentage screening (Mourier and Planes 2013; Warner et al. 2016). Cross-species transferability has been successful in many species (Barbará et al. 2007; Reid et al. 2012; Maduna et al. 2014; Pirog et al. 2016) allowing for genetic studies in closely related species. However, the few studies that have investigated the efficiency of cross-species transferability of microsatellite loci have demonstrated a negative correlation between the genetic distance and the amplification success (Carreras-Carbonell et al. 2008; Hendrix et al. 2010; Moodley et al. 2015). This constraint can hamper accurate comparisons of genetic diversity among more distantly related species.

Here, we used 454 GS-FLX sequencing technology to develop an additional set of de novo microsatellite markers for Millepora platyphylla to first assess its genetic diversity on Moorea’s

72 reefs in French Polynesia. Secondly, we tested these new microsatellite loci for cross-species amplification in five other Millepora species: the branching Millepora intricata, Millepora dichotoma and Millepora tenera, the plate-like species Millepora complanata and the encrusting Millepora exaesa (Boshma 1948). Lastly, genetic distances based on the 16S mitochondrial gene were estimated among these species and M. platyphylla to identify the transferability success of these newly developed microsatellites across the Milleporidae.

2. Materials and Methods

2.1. Preparation of genomic DNA for 454 sequencing for the target species

The calcification processes (Stanley 2006) and metabolic pathways (Trench 1979) of calcareous hydrozoans are supported by a symbiotic association with protozoan dinoflagellate algae of the genus Symbiodinium. To design species-specific markers, genomic DNA of Symbiodinium was removed from the animal tissue using a succession of extraction techniques. Candidate 4 microsatellite repeats were isolated from a pool of 14 partially bleached fragments of M. platyphylla

collected in situ on Moorea’s reefs to minimize the quantity of Symbiodinium in their tissues.

Further mechanic (centrifugation) and genetic (positive and negative controls in PCR) techniques

were applied to ensure microsatellites belonged to the animal only (see below). Fragments were Millepora

homogenized in 1000 µL of CHAOS buffer (4 M guanidine thiocyanate; 0.5% N-lauroyl sarcosine; building

25 nM Tris-HCl pH 8; 0.1 M 2-mercaptoethanol) modified from Fukami et al. (2004). Samples - were incubated at 60 ºC for 2 hr while rotating and then centrifuged at 1500 rpms for 30 sec to precipitate symbiont algae expelled from host cells. 20 µL of the aqueous phase was examined under microscope to confirm the absence of Symbiodinium. Further potential contamination was tested by running microsatellites on pure cultures of zooxanthellae DNA (see below). 350 µL of CHAOS solution containing animal tissues was transferred to a new vial and 350 µL PEB (protein extraction buffer) was added (100 mM Tris pH 8; 10 mM ethylenediaminetetraacetic acid (EDTA); 0.1% Sodium dodecyl sulfate (SDS)). DNA was purified with phenol/chloroform (24:1) and precipitated with isopropanol as described by Mieog et al. (2009). Samples from the 14 colonies

were pooled together to increase detection of polymorphism. A total of 1 µg of genomic DNA was Geneticdiversity and reef differentiation in sent to GenoScreen platform (Lille, France) for the development of the microsatellite library using 454 GS-FLX Titanium reagents as described in Malausa et al. (2011). Briefly, total DNA was mechanically fragmented and enriched for TG, TC, AAC, AAG, AGG, ACG, ACAT and ACTC repeat motifs. Enriched fragments were subsequently amplified and PCR products were purified and quantified. GS-FLX libraries were then carried out following manufacturer's protocols and sequenced on a GS-FLX PTP. The Quality Detection Device (QDD) pipeline (Meglécz et al. 2010)

73 was used to analyze the 454 sequences and to design primers for amplification of the detected microsatellite motifs. Primer pairs were then selected depending on the motif (di-, tri-, tetra- nucleotide), the number of repeats (≥ 5) and the product size (≥ 100 bp) and tested on agarose gels for amplification.

2.2. Microsatellite discovery and primer testing

A panel of 16 M. platyphylla colonies was used to optimize PCR amplification and identify polymorphic loci. Small fragments of tissue-covered skeleton (< 2 cm3) were incubated at 55 ºC for 1 hr in 450 µL of digest buffer with proteinase K (QIAGEN, Hilden, Germany). Genomic DNA was extracted using a QIAxtractor automated genomic DNA extraction instrument, according to manufacturer’s instructions. PCRs were performed in a final volume of 10 µL including 5 µL Type- it Multiplex PCR Master Mix (1x) (QIAGEN, Hilden, Germany), 3 µL RNase-free water, 1 µL primers (2 µM for both forward and reverse primers diluted in TE buffer) and 1 µL of template (10 to 50 ng/µL). The PCR program included an initial denaturing step of 5 min at 95 ºC, followed by 40 cycles of 30 sec at 95 ºC, 90 sec at optimal temperature (57–60 ºC) depending on the microsatellite locus (see Table 4.1), and 30 sec at 72 ºC, followed by a final 30 min elongation step at 60 ºC. The PCR products were electrophoresed on 2% agarose gels. For loci with high-quality and consistent amplification, the PCR was repeated on DNA template isolated from Symbiodinium strains (clade A to F identified based on 23S chloroplast rDNA, Table S1) to identify coral specific loci and to exclude putative Symbiodinium specific loci. Symbiodinium strains were provided by the BURR laboratory at Buffalo, US (BURR; http://www.nsm.buffalo.edu/Bio/burr/). For the loci that are specific to Millepora, the forward primer was fluorescently labelled with the G5 dye set including 6-FAM, VIC, NED and PET (Applied Biosystems, Foster City, CA). Amplified fragments were visualized on an Applied Biosystems 3730 Sequencer using a GeneScan 500 LIZ ladder.

2.3. Sampling, genotyping and cross-species amplification

The optimized loci were genotyped in our target species in addition to five other Millepora species to test for their transferability. For the characterization of newly developed microsatellites, small fragments (< 2 cm3) from 50 M. platyphylla colonies were collected on the reefs of Moorea in French Polynesia (CITES - FR1298700028-E). For cross-species amplification transferability tests, samples were collected from various locations in the Indo-Pacific and the Caribbean for five other species of fire corals: 11 M. intricata in Papua New Guinea, 30 M. dichotoma in Europa Island (Mozambique Canal), 30 M. tenera and 14 M. exaesa both in Reunion Island and 30 M. complanata in Curaçao (Table S2). DNA from the 165 Millepora colonies was extracted as described above and optimized loci were combined in four multiplex panels according to their allele size range and 74 primer annealing temperature (see MP in Table 4.1). PCRs (10 µL) were performed with 2 µM of labelled forward primer and reverse primer with the same amplification conditions described above. PCR products were sent to GenoScreen (Lille, France) for fragment analysis and were visualized using an Applied Biosystems 3730 Sequencer. An internal size ladder (GeneScan 500 LIZ, Applied Biosystems) was used for accurate sizing and alleles were scored and checked manually using GENEMAPPER v.4.0 (Applied Biosystems, Foster City, CA). Samples that were ambiguous in scoring were re-amplified and re-scored. All peak profiles that were faint or ambiguous (i.e. multiple peaks) were considered as missing data.

2.4. Phylogenetic analyses

Additionally, a 461 bp portion of the mitochondrial 16S gene was amplified for 30 specimens (five colonies per species) and used to estimate the genetic distances among the six Millepora species. The PCR amplifications were performed using the primers 16S-SHA and 16S-SHB (Cunningham and Buss 1993) in 20 µL reactions containing: 1.5 mM of MgCl2, 0.2 mM of each dNTP, 1X final 4 concentration of buffer, 0.5 µM of each primer, 0.25 unit of Red Hot Taq polymerase, 2 µL of DNA

template (80 to 100 ng/µL) and sterilized water up to 20 µL. The cycling parameters were as follows: an initial denaturation step of 5 min at 94 °C, followed by 35 cycles of 1 min at 94 °C, 1

min at 50 °C, 1.5 min at 72 °C and a final elongation step of 5 min at 72 °C. Sequencing of the PCR Millepora

products was performed by GenoScreen (Lille, France).

building - 2.5. Data analyses

Control for the presence of null alleles, scoring errors and large allele dropout were performed with MICROCHECKER v.3.7 (van Oosterhout et al. 2004). To assess the discriminative power of the microsatellite markers, the genotype probability (GP) was estimated for each locus and for a combination of all loci using GENALEX v.6.5 (Peakall and Smouse 2006). Repeated multilocus genotypes (MLGs) were also identified in GENALEX and were considered as clone mates at GP <

0.001. The probability of identity, P(ID), was computed to evaluate the power of our microsatellites to accurately distinguish closely related genotypes from those produced by asexual reproduction

(Waits et al. 2001). Population genetic analyses were then performed after the removal of all clonal Geneticdiversity and reef differentiation in replicates.

Table 4.1 Characterization of de novo microsatellite loci and genetic variation in the target species M. platyphylla collected in Moorea, French Polynesia.

Locus Primer Sequence 5'-3' Dye MP Motif TA (°C) # GenBank N Size (bp) Null LD Na HO HE FIS

Mill07 F: TAGTACATCGGGCATGAGCA 6-FAM 3 (CA)16 57 KX670763 50 92–144 ------13 0.760 0.855 0.121* R: GTACTCTACGGCGTGTGCGT

Mill27 R: CTTTCGTTTCCGATCATTCC VIC 3 (TG)10 57 KX670764 50 136–148 --- 0.044 5 0.600 0.636 0.067 R: TGCCAGAACTAAGTTATCACAGC

Mill30 F: AGTTGGCTCTGAGTGCGAGT NED 2 (TG)11 57 KX670765 50 203–211 --- 0.025 4 0.680 0.648 –0.039 R: CCTCGGTTTATGGCTGAGAT

Mill47 F: AAGCGTGTAATGCACTCAAAGA NED 2 (GA)8 57 KX670766 50 118–162 0.101 0.057 10 0.600 0.766 0.227** R: AACAGAAGTCGAACTGAGTCAAAA

Mill52 F: CCCTGAGGCATCGAAATATAA 6-FAM 1 (AC)9 60 KX670767 50 94–98 ------2 0.420 0.412 –0.010 R: TGCAATTGATGGTATTTGCATT

Mill56 F: TCTGCAGATTTTGCATCTCG PET 1 (AGA)6 60 KX670768 50 194 ------1 0 0 --- R: TAGCAACAATGCTTCGCTGA

Mill61 F: AAATGAACTCGCCCAAAAGA PET 4 (CAA)7 57 KX670769 50 163–166 --- 0.048 2 0.480 0.467 0.044 R: ACACTGTCGATTGTGTTCCAA

Mill67 F: TTGCGAGTTTACTTACCAGGC VIC 1 (TAGA)6 60 KX670770 50 259–359 0.144 0.039 11 0.420 0.588 0.294** R: TGAAGCAAATGACAAGAGCAA

Mill86 F: GCGCGAAAATAAATTAAGGAA NED 4 (GTT)5 57 KX670771 50 106 ------1 0 0 --- R: TCCAATCTGAATTCCACCCT

Mill91 F: CACTTTCGCCATTGTTGCTA PET 4 (CAA)6 57 KX670772 50 116 ------1 0 0 --- R: AACGGAATTCGAATCATTGC

Mill93 F: TGAAATTTTCCAGTGACATCAAA 6-FAM 2 (TGT)7 57 KX670773 50 91–100 --- 0.055 3 0.260 0.339 0.243 R: GCTAATTATGAAATAGCAACTCCTAAA

Mill94 F: GCATAAAGAATAAAGCAGAGGCA 6-FAM 3 (GAA)7 57 KX670774 50 131–140 --- 0.016 2 0.480 0.461 –0.032 R: CAATTGTGGGGAAGTTCGTT

Mill95 F: TCCATAGCTTCTGCCTCCTC 6-FAM 1 (TTG)7 60 KX670775 50 123–138 --- 0.022 3 0.320 0.304 –0.042 R: GCTGATGATGCTGTCGAAGA

Mill101 F: AGTCCTTCAATTGGTGGGTG PET 2 (CAA)6 57 KX670776 50 132–135 ------2 0.640 0.493 –0.289 R: GAGATGATGACTGAGCAGCAG

Mill103 F: TTAAAGCCAGAGACAGAGAGACA VIC 3 (AG)7 57 KX670777 50 94–100 --- 0.017 4 0.700 0.621 –0.117 R: ATCAACAGTTTCCCCTGTGC

MP, multiplex panel in which each locus was included; TA, primer temperature annealing; N, number of individuals with reliable amplification; Null, proportion of null alleles; LD, proportion of allele comparisons showing significant linkage disequilibrium (P < 0.05); Na, number of alleles; HO, observed heterozygosity; HE, expected heterozygosity; FIS, inbreeding coefficient. Significant values of FIS are indicated by bold values with * P < 0.05 and ** P < 0.001.

Indices of genetic diversity were estimated for each species in all locations using GENALEX, including Na, the total number of alleles per locus, observed (HO) and expected (He) heterozygosity

(Weir and Cockerham 1984). The inbreeding coefficient FIS and linkage disequilibrium were estimated using GENETIX v.4.02 (Belkhir et al. 1996), applying a permutation procedure (1000 permutations) to assess statistical significance. GENETIX was also used to estimate genetic distance among populations of M. platyphylla and the other Millepora species with the microsatellite dataset using the θ estimator of FST (Weir and Cockerham 1984) based on a permutation procedure (1000 permutations). Genetic p-distances among species at the mtDNA 16S gene were calculated in Mega v.6 (Tamura et al. 2013). In addition to the p-distance, we also computed other genetic distances (i.e. Kimura-2-Parameters, Tamura & Nei and Maximum composite Likelihood, all available in the software Mega v.6) and found similar species rank among all measures tested. We also examined the cross-species amplification success of the new microsatellite markers by plotting the genetic diversity (Ho) and the proportions of missing data (non amplified loci after 3x repeat PCR, and this at different annealing temperatures) in each 4 species against genetic distance (16S) and relationships were tested using Pearson’s correlation coefficient.

3. Results Millepora

building

3.1. Development of de novo microsatellites in Millepora platyphylla - eef Sequencing of the microsatellite-enriched library from 14 partially bleached fragments of M. platyphylla yielded 78,784 reads. The Quality Detection Device (QDD) for bioinformatic filtering resulted in a final set of 5976 sequences containing microsatellite motifs. For the characterization of new microsatellites, 127 primer pairs (out of the 186 resulting from the QDD filtering, 68.3%) were tested in 16 individuals of M. platyphylla collected on Moorea’s reefs. Fifteen loci showed clear amplification profiles and no Symbiodinium specific locus was identified, proving the efficiency of the DNA extraction technique. For the 50 M. platyphylla colonies collected on Moorea’s reefs,

twelve loci were polymorphic (from 2 to 13 alleles) and three additional monomorphic loci were Geneticdiversity and r differentiation in retained for further cross-species transferability tests (Table 4.1). Contig sequences containing the microsatellites identified in this study are available in GenBank (KX670763– KX670777, Table 4.1).

Significant linkage disequilibrium was identified and distributed among all microsatellite loci in M. platyphylla. 9.1% of the pairwise locus combinations showed a significant probability of linkage disequilibrium at P < 0.05 (Table 4.2). The presence of null alleles was detected at Mill47 and

Mill67 with frequencies of null alleles at both loci estimated at 10.1% and 14.4%, respectively. These two loci were removed from our dataset for further genetic analyses, although there was no

evidence of scoring error or large allele dropout for any locus. Given the low P(ID) value estimated (1.3E–6), our panel of microsatellites had a high power to distinguish colonies that were clonal replicates. For the ten polymorphic loci showing no evidence of null alleles, the mean number of alleles (Na) per locus was 3.462 and the observed heterozygosity (Ho) was 0.411 (Table 4.2). Only three loci out of fifteen showed significant deficiency in heterozygotes compared to HWE and only

one of them showed no evidence of null alleles (Mill07, FIS: 0.121, Table 4.1).

Table 4.2 Summary of genetic distances (GD) based on the 16S gene between the target species and other Millepora species together with indices indicating microsatellite transferability and genetic diversity.

Clonal Amp Pol Null LD Species Locality N MLG P GD Na Ho MLG (ID) (%) (%) (%) (%)

M. platyphylla Moorea 50 50 --- 1.3E-6 --- 100 80.0 13.3 9.1 3.462 0.411

M. intricata Papua 11 10 1 1.1E-6 0.048 73.3 60.0 --- 12.1 3.909 0.405

M. dichotoma Europa 30 24 4 4.1E-7 0.049 86.7 60.0 7.7 10.3 3.417 0.323

M. tenera Reunion 30 24 6 3.1E-7 0.049 80.0 73.3 58.3 23.0 4.833 0.439

M. complanata Curaçao 30 30 --- 1.3E-6 0.130 53.3 46.7 75.0 10.2 4.000 0.250

M. exaesa Reunion 14 14 --- 3.9E-6 0.149 60.0 53.3 11.1 17.6 3.625 0.496

N, sample size; MLG, number of multilocus genotypes; Clonal MLG, number of multilocus genotypes with clonal replicates; P(ID), Probability of Identity; Amp, percentage of loci amplified; Pol, percentage of polymorphic loci; Null, percentage of loci showing evidence of null alleles; LD, percentage of allele comparisons showing significant linkage disequilibrium (P < 0.05); Na, mean number of alleles; HO, mean observed heterozygosity. Na and Ho were estimated based on loci showing no evidence of null alleles and clonal replicates were removed from our dataset for these measures of genetic diversity.

3.2. Cross-species amplification in Milleporidae

Assessment of the mtDNA genetic distances (GD) within the Millepora genus revealed that branching species, i.e. M. intricata, M. dichotoma and M. tenera, were more closely related (0.048– 0.049) to our target species, with haplotypes shared between M. dichotoma and M. tenera (Table 4.3 and see Appendix S1 for the haplotype network). The plate-like M. complanata (0.130) and encrusting M. exaesa (0.149) were more genetically distant from M. platyphylla. The mean amplification success for cross-species amplification was 70.7% (~11 loci out of 15) and the mean polymorphism was 58.7% (~9 loci out of 15). Cross-species amplification decreased significantly with mtDNA genetic distance (r = –0.931, P = 0.007), with a reduced amplification success in the most divergent species, i.e. M. complanata (53.3%) and M. exaesa (60.0%), and higher for M. intricata (73.3%), M. tenera (80.0%) and M. dichotoma (86.7%) (Table 4.2). Cross-species

78 amplification also revealed a significant decrease of polymorphism with increasing mtDNA distance (r = –0.857, P = 0.029), with lower percentages of polymorphic loci for non-target species (≤ 73.3%, Table 4.2). No relationship was found between the percentage of loci showing evidence of null alleles and genetic distance (r = 0.331, P = 0.521). The highest percentage was recorded for M. complanata (75.0%), while lowest for M. intricata (0%). The proportion of missing data per locus increased significantly with increasing level of genetic distance (Fig. 4.1A, r = 0.214, P = 0.044).

Table 4.3 Nuclear (FST) and mitochondrial (p-distance) genetic distances among Millepora species.

M. platyphylla M. intricata M. dichotoma M. tenera M. exaesa

M. platyphylla 0.343 0.373 0.339 0.167

M. intricata 0.048 0.031 0.065 0.181

M. dichotoma 0.049 0.051 0.062 0.221

M. tenera 0.049 0.051 0.000 0.293

M. exaesa 0.149 0.143 0.150 0.150

Values above the diagonal are the FST calculated on the microsatellite dataset, values with P < 0.001 are in bold and the remaining values are NS. Values below the diagonal are genetic distances (p-distance) based on the mitochondrial 16S 4 gene.

Clonal replicates were found in the three branching species: 1 clonal MLG in M. intricata, 4 in M. dichotoma and 6 in M. tenera (Table 4.2). The mean observed heterozygosity per locus was highly variable in all species, although more limited in M. tenera and M. complanata due to high Millepora

proportions of null alleles in both species (Fig. 4.1B and Table S3). No significant correlation was building

found between the genetic diversity and mtDNA genetic distance (r = –0.175, P = 0.101). The mean - eef observed heterozygosity was slightly reduced for M. complanata (0.250) compared to other species (0.323 for M. dichotoma ≤ Ho ≤ 0.496 for M. exaesa) (Table 4.2). However, Ho estimate in M. complanata was based on only one microsatellite locus (Mill 103, Fig. 4.1B). For the four other non-target species, 2 loci out of 15 showed significant deficiencies in heterozygotes compared to

HWE in M. dichotoma (Mill07 and Mill67, FIS: 1.000) and another one in M. intricata (Mill101,

FIS: 0.500) (Table S3).

The transferability of microsatellites in the Milleporidae also revealed strong genetic differentiation

among some species (Table 4.3 and see Appendix S2 for the Bayesian clustering analysis). No Geneticdiversity and r differentiation in significant genetic differentiation was observed for the closely related branching species (i.e. M. intricata, M. dichotoma and M. tenera). For all comparisons involving our target species M. platyphylla, the lowest value of FST (≤ 0.167) was recorded for the most divergent species M. exaesa. No relationship (r = 0.150, P = 0.679) was found between the nuclear (FST from microsatellite data) and mitochondrial (p-distance from 16S) genetic distances.

Fig. 4.1 Proportion of missing data (A) and observed heterozygosity (B) per microsatellite locus (circles) in five Millepora species plotted against genetic distances (16S gene) from the target species Millepora platyphylla (p, red) to other species; Millepora intricata (i, green), Millepora dichotoma (d, pink), Millepora tenera (t, purple), Millepora complanata (c, blue) and Millepora exaesa (e, yellow).

4. Discussion

4.1. Development of microsatellites and their transferability in Milleporidae

To date, there is no study assessing the genetic diversity and population structure of fire coral species. This gap is mostly due to the lack of highly variable genetic markers in the genus until very recently, whereas microsatellite loci have been identified in the Caribbean species Millepora alcicornis (Ruiz-Ramos and Baums 2014). Heckenhauer et al. (2014) have succeeded in developing eleven microsatellite markers for M. dichotoma from the Great Barrier Reef and showed that their transferability was successful between geographic regions (Red Sea) and the species M. platyphylla. Their study has shown that eight of the eleven microsatellite markers (72.7%) were transferable to M. platyphylla which is less to what we had in the present study (i.e. 86.7% between M. dichotoma and M. platyphylla). Six of their loci had only 2 alleles for M. platyphylla, which is not informative enough depending on the analyses performed (e.g. parentage analyses). Furthermore, most of the microsatellite markers developed by Heckenhauer et al. (2014) were characterized by significant 4 deficiencies in heterozygotes, whereas only two of our loci showed such HWE disequilibrium in both of these species. Depending on the target species, a combination of markers from the two studies would thus seem a good strategy for population genetic approaches in Millepora

hydrocorals. Millepora building

Our cross-amplification tests show a higher cross-taxon transferability success (73.3–86.7%) for a - genetic distance below 5% from our target species (i.e. M. intricata, M. dichotoma and M. tenera) eef and a reduced transferability above this level (≤ 60% for M. complanata and M. exaesa). Overall, our results show a high probability to amplify a microsatellite locus within the genus Millepora, where 71% of the loci were successfully amplified in the five non-target species. This value is slightly lower to what was demonstrated for the Caribbean Montastraea species complex (scleractinian corals), i.e. ~80% of amplification success in two other species within the same location (Davies et al. 2013). Our lower value, while still very high, is not surprising as we tested cross-amplification between six species of the genus Millepora (i.e. no species complex as for

Montastraea spp), which were also collected throughout their entire geographic range. The non- Geneticdiversity and r differentiation in amplification of some microsatellite loci in the non-target species is most likely due to specific mutations in the primer binding sites in M. platyphylla, i.e. null alleles (Paetkau and Strobeck 1995). These loci, specific to Moorea’s population, may result from local evolutionary processes at this location, such as bottlenecks, expansions, life history traits, inbreeding and outbreeding (Keller and Waller 2002; Leffler et al. 2012; Romiguier et al. 2014). Our cross-amplified loci show a high probability to be polymorphic in non-target species (58.7%), which is much higher to what is

81 generally found in other taxa, such as fishes (~25–30% in Barbará et al. 2007; Reid et al. 2012) and birds (~20–50% in Dawson et al. 2010). Many other studies using cross-amplification have shown a significant decrease in the transferability success and polymorphism with evolutionary distance from the target species (Jan et al. 2012; Maduna et al. 2014; Moodley et al. 2015).

4.2. Usefulness of cross-species amplification in Milleporidae

The level of genetic diversity is key for the persistence of a species in changing environments and represents a fundamental aspect of biodiversity (Romiguier et al. 2014). Quantifying the genetic diversity in natural populations and species is critical to address ecological and evolutionary questions (Nair 2014), which requires the development of suitable molecular resources. In this study, our cross-species amplification approach for the development of new microsatellites shows no significant evidence of lower genetic diversity nor greater proportion of null alleles with increasing genetic distance from our target species, which is in contradiction with previous studies (Carreras-Carbonell et al. 2008; Hendrix et al. 2010; Moodley et al. 2015). Our results also show that most of our microsatellite markers are not useful to estimate the genetic diversity in the Caribbean species M. complanata due to the high proportion of null alleles. Hence, this study reveals that the transferability of our microsatellites ensures comparable estimations of the genetic diversity among closely related Millepora species, although restricted to the Indo-Pacific region. Further investigations with other Caribbean species, such as M. alcicornis, are needed to test their transferability in this geographic region.

In this study, we also found that genetic distance from interspecific microsatellite data were not congruent with mtDNA distance among the studied species. It is not surprising as such highly variable markers would suffer from homoplasy as one look into higher taxon relationships, while microsatellites are well-known to be mostly useful for intra-specific studies (Selkoe and Toonen 2006). Nonetheless, assessment of the population structure among closely related Indo-Pacific species revealed a clear genetic differentiation between the branching species and the plate-like M. platyphylla. Our panel of new microsatellite loci is therefore useful for species delineation and can help resolve the century-old species problem in Milleporids (Boschma 1948).

4.3. Patterns of genetic diversity and population structure in Milleporidae

The first evaluation of genetic diversity among species of Millepora across its geographic range in tropical reefs reveals moderate levels of heterozygosity and allelic richness. The lowest genetic diversity was found for the Caribbean species, M. complanata, likely resulting from the low proportion of polymorphic loci (46.7%) and the high proportion of loci showing evidence of null

82 alleles (75.0%). Nonetheless, levels of genetic diversity estimated in this study are similar to what was described for many tropical scleractinian species (Baums 2008; Shearer et al. 2009) and to what is expected in populations of partially clonal organisms. In this study, linkage disequilibrium, relatively high levels of allelic and genetic diversity, and heterozygote deficiencies were estimated for the six studied hydrocoral species, as previously described in some scleractinian corals (Baums 2008). Overall, these new microsatellites are suitable to infer genetic diversity and to evaluate reproductive strategies in the partially clonal fire corals.

5. Conclusions

This study highlights the utility of cross-species amplification of microsatellites in assessing population genetics of the Millepora genus in the Indo-Pacific region. Surprisingly, this approach does not result in lowering genetic diversity (Ho) in non-target species, thus ensuring an unbiased estimation of genetic diversity among fire coral species. The development of microsatellites can be complex and difficult in many taxa, such as birds (Primmer et al. 1997) and plants (Lagercrantz et 4 al. 1993), due to biological constraints that can affect the abundance and motif repeats of

microsatellites in the genome (Tόth et al. 2000). A recent study has demonstrated high microsatellite coverage in several species of cnidarians, including Millepora alcicornis (Ruiz-

Ramos and Baums 2014), indicating that there is no biological constraint for the development of Millepora

microsatellite markers in this phylum. The availability of numerous microsatellite markers for reef- building

building Millepora species creates new opportunities for future research into the processes driving - eef the complexity of their colonization success on many Indo-Pacific reefs.

Acknowledgements

We are grateful to Alexandre Mercière, Maggy Nugues, Nicky Gravier-Bonnet, Chloé Bourmaud, Julia Leung, Suzie Mills and Ricardo Beldade who contributed to sample collection, Nathalie Tolou for technical advice and Jeanine Almany for English improvements on the manuscript. We are also grateful to Mary Alice Coffroth and her laboratory for providing us cultured Symbiodinium strains.

We also thank Iliana Baums and one anonymous reviewer for their thoughtful comments on the Geneticdiversity and r differentiation in manuscript.

Supporting Information

Table S1 Symbiodinium strains used to identify coral specific loci.

Culture ID Host Location 18S rDNA Genotype (23S chloroplast rDNA)

FLAP1 Aiptasia pallida Florida A A193

Cass KB8 Cassiopea sp. Hawaii A A194

Pe Porites evermanni Hawaii B B184

FLAP2 Aiptasia pallida Florida B B184

Mp Mastigia paupa Palau C C180

A001 Acropora sp. Okinawa D D206

A014 Porites australiensis Okinawa D D206

CCMP421 unknown New Zealand E E202

Pd Porites divaricata Florida F F178

Sin Sinularia sp. Guam F F179

See http://www.nsm.buffalo.edu/Bio/burr/ for more details on the Symbiodinium strains.

Table S2 Locations for Millepora spp. sampling.

Species Locality Latitude (D.d) Longitude (D.d) Year 4

M. platyphylla Moorea 17.4816 S 149.8755 W 2013

M. intricata Papua New Guinea 4.9937 S 146.3299 E 2014

M. dichotoma Europ a 20.3472 S 40.3667 E 2013 Millepora M. tenera Reunion 20.9029 S 55.3537 E 2009

M. complanata Curaçao 12.1202 N 68.9696 W 2014 building M. exaesa Reunion 20.9029 S 55.3537 E 2009 -

eef Geneticdiversity and r differentiation in

Table S3 Cross-species transferability of fifteen microsatellite loci isolated from Millepora platyphylla (Moorea) in five others species of Millepora.

Locus TA (°C) Species N Namp Size (bp) Null LD Na HO HE FIS Mill07 57 M. intricata 11 0 0 ------0 ------M. dichotoma 30 8 96–102 --- 8 4 0.000 0.688 1.000***

M. tenera 30 0 0 ------0 ------

M. complanata 30 9 92–106 0.237 6 9 0.444 0.839 0.515***

M. exaesa 14 0 0 ------0 ------

Mill27 57 M. intricata 11 11 156–188 --- 4 15 0.900 0.920 0.052 M. dichotoma 30 30 150–190 --- 8 16 1.000 0.914 -0.073

M. tenera 30 30 138–198 --- 9 15 1.000 0.901 -0.089

M. complanata 30 0 0 ------0 ------

M. exaesa 14 0 0 ------0 ------

Mill30 57 M. intricata 11 0 0 ------0 ------M. dichotoma 30 0 0 ------0 ------

M. tenera 30 12 203–213 0.295 8 5 0.300 0.680 0.594***

M. complanata 30 19 205–211 0.368 5 4 0.118 0.642 0.910***

M. exaesa 14 9 203–209 --- 3 4 0.556 0.685 0.245

Mill47 57 M. intricata 11 11 116–122 --- 4 4 0.700 0.715 0.018 M. dichotoma 30 26 116–128 0.374 7 5 0.150 0.779 0.816***

M. tenera 30 30 114–128 0.144 8 5 0.542 0.691 0.236

M. complanata 30 30 118 ------1 0 0 ---

M. exaesa 14 7 116–120 --- 2 3 0.429 0.602 0.357

Mill52 63 M. intricata 11 10 94 ------1 0 0 --- M. dichotoma 30 30 94 ------1 0 0 ---

M. tenera 30 30 94–96 0.189 4 2 0.083 0.219 0.632*

M. complanata 30 0 0 ------0 ------

M. exaesa 14 14 94–126 --- 1 4 0.429 0.612 0.333

Mill56 63 M. intricata 11 11 194–197 --- 2 2 0.200 0.180 -0.053 M. dichotoma 30 30 194–200 --- 5 3 0.458 0.378 -0.193

M. tenera 30 30 194–197 --- 2 2 0.708 0.457 -0.533

M. complanata 30 30 169–200 0.201 1 3 0.200 0.383 0.490**

M. exaesa 14 14 194 ------1 0 0 ---

Mill61 57 M. intricata 11 0 0 ------0 ------M. dichotoma 30 0 0 ------0 ------

M. tenera 30 0 0 ------0 ------

M. complanata 30 0 0 ------0 ------

M. exaesa 14 0 0 ------0 ------

Mill67 63 M. intricata 11 5 249–265 --- 4 3 0.250 0.531 0.636 M. dichotoma 30 14 255–261 --- 5 2 0.000 0.153 1.000*

M. tenera 30 29 241–261 0.271 9 4 0.304 0.678 0.566***

M. complanata 30 0 0 ------0 ------

M. exaesa 14 0 0 ------0 ------

Mill86 55 M. intricata 11 0 0 ------0 ------M. dichotoma 30 30 97 ------1 0 0 ---

M. tenera 30 0 0 ------0 ------

M. complanata 30 0 0 ------0 ------

M. exaesa 14 0 0 ------0 ------

Mill91 57 M. intricata 11 11 116 ------1 0 0 --- M. dichotoma 30 30 116 ------1 0 0 ---

M. tenera 30 30 116 ------1 0 0 ---

M. complanata 30 25 101–194 0.410 4 7 0.08 0.7192 0.893***

M. exaesa 14 0 0 ------0 ------

Mill93 57 M. intricata 11 11 91–103 --- 5 4 0.500 0.655 0.359 M. dichotoma 30 30 91–100 --- 7 3 0.458 0.499 0.103

M. tenera 30 29 94–97 0.291 7 2 0.174 0.454 0.630**

M. complanata 30 0 0 ------0 ------

M. exaesa 14 8 91–97 --- 2 3 1.000 0.555 -0.061

Mill94 57 M. intricata 11 11 122–140 --- 2 4 0.500 0.415 -0.176 M. dichotoma 30 30 128–140 --- 6 4 0.750 0.635 -0.161 4 M. tenera 30 30 128–137 --- 8 4 0.333 0.411 0.209

M. complanata 30 25 128–140 0.224 4 5 0.292 0.673 0.581***

M. exaesa 14 7 128–138 0.372 1 4 0.143 0.684 0.818*

Mill95 63 M. intricata 11 11 123–126 --- 2 2 0.500 0.455 0.000

M. dichotoma 30 30 120–126 --- 6 3 0.667 0.622 -0.051 Millepora

M. tenera 30 30 123–126 --- 6 2 0.292 0.457 0.381

M. complanata 30 28 120–171 0.186 5 7 0.357 0.576 0.396***

building - M. exaesa 14 9 111–141 --- 1 7 0.889 0.796 -0.058 eef Mill101 57 M. intricata 11 11 132–138 ------3 0.100 0.185 0.500* M. dichotoma 30 30 135 ------1 0 0 ---

M. tenera 30 30 132–138 0.214 5 3 0.125 0.291 0.584***

M. complanata 30 0 0 ------0 ------

M. exaesa 14 9 132–144 --- 3 4 0.444 0.451 0.072

Mill103 57 M. intricata 11 11 94–104 --- 2 4 0.800 0.625 -0.151 M. dichotoma 30 30 94–96 --- 6 2 0.542 0.492 -0.079

M. tenera 30 29 94–96 0.389 9 2 0.043 0.496 0.916***

M. complanata 30 28 92–98 --- 3 4 0.429 0.580 0.278*

M. exaesa 14 9 94–98 --- 1 3 0.222 0.364 0.439 Geneticdiversity and r differentiation in TA, primer temperature annealing; Sp, Species; N, sample size; Namp, number of individuals with reliable amplification; Null, proportion of null alleles; LD, proportion of allele comparisons showing significant linkage disequilibrium (P < 0.05) ; Na, number of alleles; HO, observed heterozygosity; HE, expected heterozygosity; FIS, inbreeding coefficient. Significant values of FIS are indicated by bold values with * P < 0.05, ** P < 0.01 and *** P < 0.001. Clonal replicates were removed from our dataset for the measures of genetic diversity.

Appendix S1 Haplotype network of 16S sequences.

Each pie represents one 16S haplotype (with its area proportional to the number of individuals in which it was detected). The lengths of the grey lines connecting the 16S haplotypes are proportional to the number of mutations separating them with the number of mutations shown in red on each line. This haplotype network was reconstructed using the median joining algorithm (Bandelt et al.1999) in Network v5 (www.fluxus- engineering.com).

Appendix S2 Bayesian clustering analysis.

Assignment analyses based on Bayesian clustering analysis using STRUCTURE (Pritchard et al. 2000) for five of the six studied species: (1) M. platyphylla, (2) M. exaesa, (3) M. intricata, (4) M. dichotoma and (5) M. tenera. The x-axis shows species identification and y-axis shows the cluster membership (K=2). Initial STRUCTURE runs were used to determine the most likely number of clusters (K). Runs were performed with the default setting, a burn-in period of 50000, 50000 MCMC repeats and 10 iterations per K. The results were uploaded to STRUCTURE HARVESTER (Earl and vonHoldt 2011) and the most likely K was retained for a second run in STRUCTURE with a burn-in period of 500000, 500000 MCMC repeats, 10 iterations and

uniform prior setting. 4

Millepora

building

eef Geneticdiversity and r differentiation in

CHAPTER 5 Fire coral clones demonstrate phenotypic plasticity among reef habitats

Submitted as: Dubé CE, Boissin E, Maynard JA, Planes S. Fire coral clones demonstrate phenotypic plasticity among reef habitats. Molecular Ecology

Fire coral clones demonstrate phenotypic plasticity among reef habitats

Caroline E. Dubé*†, Emilie Boissin*†, Jeffrey A. Maynard†‡, Serge Planes*†

*EPHE, PSL Research University, UPVD-CNRS, USR 3278 CRIOBE, F-66860 Perpignan, FRANCE †Laboratoire d’excellence “CORAIL”, EPHE, PSL Research University, UPVD-CNRS, USR 3278 CRIOBE, BP 1013, 98729 Papetoai, Moorea ‡SymbioSeas and Marine Applied Research Center, 8826 Ramsbury Way, Wilmington NC 28411, USA

Keywords Reproduction · Clonal dispersal · Genetic diversity · Morphology · Wave energy · Millepora

Correspondence: Caroline E. Dubé, USR 3278 CRIOBE, Fax: +33-468-503-686; E-mail: [email protected]

Running title: Phenotypic plasticity among fire coral clones

Abstract

Clonal populations are often characterized by reduced levels of genetic diversity, which can translate into lower numbers of functional phenotypes, both of which impede adaptation. Study of partially clonal animals enables examination of the environmental settings under which clonal reproduction is favored. Here, we gathered genotypic and phenotypic information from 3651 georeferenced colonies of the fire coral Millepora platyphylla in five habitats with different hydrodynamic regimes in Moorea, French Polynesia. In the upper slope where waves break, most colonies grew as vertical sheets (‘sheet tree’) making them more vulnerable to fragmentation. Nearly all fire corals in the other habitats are encrusting or massive. M. platyphylla population is highly clonal (80% of the colonies are clones), while characterized by the highest genotype diversity ever documented for terrestrial or marine populations (1064 genotypes). The proportion of clones varies greatly among habitats (≥ 58–97%) and clones (328 clonal lineages) are distributed perpendicularly from the reef crest, perfectly aligned with wave energy. There are six clonal lineages with clones dispersed in at least two adjacent habitats that strongly demonstrate phenotypic plasticity. 80% of the colonies in these lineages are ‘sheet tree’ on the upper slope, while 80 to 100% are encrusting or massive on the mid slope and back reef. This is a unique example of phenotypic plasticity among reef-building coral clones as corals typically have wave-tolerant growth forms in high-energy reef areas.

1. Introduction

There are terrestrial and marine species that can reproduce both sexually and asexually, including: bacteria, fungi, plants and invertebrates. Each reproductive mode confers different advantages under variable environmental conditions (Williams 1975; Eckert 2002). Sexual reproduction produces genetically diverse propagules able to survive within a range of environmental conditions and generates the genotypic variation required for adaptation (Rice and Chippindale 2001). Asexual reproduction allows the propagation of locally adapted genotypes and their persistence in the absence of sexual partners (Miller and Ayre 2004; Gorospe and Karl 2013; Baums et al. 2014). However, the production of asexual offspring only preserves existing genotypic diversity, because it prevents recombination (Honnay and Bossuyt 2005). Determining the relative contributions of sexual and asexual reproduction to population persistence can reveal insights into species’ response to local stress.

Our understanding of how the contribution of each reproductive mode affects the genetic makeup and connectivity of marine species has improved considerably over the last decade (Pinzόn et al. 2012; Adjeroud et al. 2014; Baums et al. 2014). This research has shown that clonal reproduction can be an efficient means to expand populations locally when unfavorable conditions impede sexual reproduction. Such conditions include: fragmented (Adjeroud et al. 2014) and marginal habitats 5

(Baums et al. 2014), high disturbance frequency (Foster et al. 2013), or high stress related to human

activities (Oliva et al. 2014). Many coral reef organisms can reproduce through both sexual and asexual reproduction, such as scleractinian corals (Harrison 2011), hydrocorals (Lewis 2006), coralline algae (Pearson and Murray 1997) and sponges (Whalan et al. 2005). Environmental conditions (e.g. temperature (Glynn 1996), light (Vermeij and Bak 2002), water flow (Monismith 2007) and water quality conditions (Fabricius 2005)) vary greatly among coral reef habitats and these conditions can impose divergent selection pressures. Consequently, populations of reef- building organisms can evolve differences in morphology, reproductive modes and dispersal abilities (Sanford and Kelly 2011; Darling et al. 2012).

Most reef-building corals (e.g. scleractinian corals, gorgonian corals and hydrozoan corals) are vulnerable to wave-induced breakage and dislodgment, and rely on a pelagic dispersal phase for subsequent recruitment. For that reason, hydrodynamic forces, especially flow velocity (Lenihan et clones coral Fire demonstrate phenotypic plasticity al. 2015), are key factors in determining coral distribution patterns and life history traits (Brown 1997; Madin et al. 2006; Denny and Gaylord 2010). In most reefs, water flow velocity is driven by wave energy dispersal (Hearn 1999; Hench et al. 2008; Lowe et al. 2009; Monismith et al. 2013). On barrier reefs (as in Moorea), the amount of wave energy is highest on the upper slope and reef

93 crest, where wave breaking first occurs, and subsequently attenuates towards lagoonal environments (Monismith 2007; Ferrario et al. 2014). This gradient in wave energy (and flow velocity), combined with other specific habitat physical factors (e.g. light, nutrients) and disturbances (e.g. cyclones, Acanthaster outbreaks, sewages) can influence coral performance (Lenihan et al. 2015). Wave energy gradients can also mediate the distribution of corals within reefs due to its influence on colony growth and skeleton density (Highsmith 1982; Heyward and Collins 1985; Bruno and Edmunds 1997). Further, wave energy gradients can affect the local dispersal of both sexual and asexual propagules (Lirman 2000; Harrison 2011).Though all corals reproduce sexually and grow using asexual budding (i.e. modular organisms) (Jackson 1977), colony dispersal through fragmentation is generally restricted to corals with morphologies vulnerable to wave-induced breakage (Storlazzi et al. 2005; Madin and Connolly 2006). Patterns of morphological plasticity driven by wave energy in corals have been modeled in a general form, with spherical and compact morphologies more prevalent in high energy reef habitats (Kaandorp and Sloot 2001; Chindapol et al. 2013). However, the vast majority of studies on clonal reproduction and phenotypic plasticity in reef-building organisms have focused on scleractinian corals. The focus here is on Millepora hydrocorals (‘fire corals’), which are component of reef communities worldwide and significantly contribute to reef accretion (Nagelkerken and Nagelkerken 2004; Lewis 2006).

Millepora species are conspicuous reef-builders that have successfully colonized a wide range of reef environments via both sexual propagules (Lewis 2006; Bourmaud et al. 2013) and clonal reproduction through fragmentation (Edmunds 1999; Lewis 2006). Fire coral morphologies vary across the wave energy gradient in reef environments and vulnerability to fragmentation varies greatly among these morphologies (Lewis 2006). Millepora platyphylla is an important reef-builder in the Indo-Pacific, where it can dominate shallow reef communities (Andréfouët et al. 2014). This species can be encrusting or massive and can also grow as vertical sheet on encrusting bases (i.e. the ‘sheet tree’ morphology, Jackson 1979). However, it is unknown whether/how phenotypic responses can govern clonal reproduction dynamics in natural populations. Assessing phenotypic plasticity within species exposed to contrasting environmental conditions requires clonal replicates of a single genotype.

We conducted an extensive field survey in five reef habitats in Moorea to examine the distribution of fire coral clones among reef habitats and assess whether/how morphologies vary among habitats. We genotyped all georeferenced colonies of M. platyphylla (N = 3651) observed in five habitats using microsatellite markers and classified them into distinct morphologies to address these questions: (i) How does sexual and asexual reproduction and coral morphologies vary among

94 habitats? (ii) What are the patterns of distribution and dispersal of asexual fragments? (iii) Are there clonal lineages with clones shared among habitats that display phenotypic plasticity?

2. Materials and methods

2.1. Model species

Millepora platyphylla is a gonochoric broadcast spawner that reproduces sexually by producing medusoids and planula larvae (Lewis 2006). The medusoids release the gametes in the water column in one hour post-spawning and then external fertilization occurs. The larvae sink and move epibenthically (i.e. crawling not swimming) on the reef substratum and metamorphose in a new calcifying polyp in one day post-spawning (Bourmaud et al. 2013). M. platyphylla also relies on clonal propagation through fragmentation (Edmunds 1999; Lewis 2006) and stolonal spreading of their encrusting bases (Dubé et al. 2016). The production of asexual larvae has never been documented within the Millepora genus.

2.2. Field surveys

Between April and December 2013 a series of surveys were conducted on the north shore of Moorea, French Polynesia, at four different locations (Tiahura, Papetoai, Cook’s Bay and Temae) 5

across five distinct habitats; two on the fore reef: the mid slope (13 m depth) and upper slope (6 m

depth), and three in the lagoon (< 1 m depth): the back reef, fringing reef and patch reef (Fig. S1 and Table S1). Wave energy generates an across-reef horizontal pressure from offshore reef towards the reef flat and lagoon (Monismith 2007). The fore reef experiences strong wave action from incoming waves that break on the reef crest with a significant decrease in swell exposure towards deeper waters (Hearn 1999; Monismith 2007). Fire coral colonies growing in the mid slope, at mid depth, are thus exposed to lower wave energy compared to those growing in the upper slope, near where waves break. A recent study demonstrated that the reef crest dissipates 70% of the incident swell wave energy with gradual wave attenuation from the back reef to nearshore fringing reefs (Ferrario et al. 2014). Although the patch reef is located in a nearshore narrow channel, the wave energy there is similar to the back reef due to its proximity to the reef crest and is also influenced by the currents that run on either side of the channel (i.e. pass circulation). In summary, wave energy is low on the mid slope, high on the upper slope near where waves break, medium on the back reef clones coral Fire demonstrate phenotypic plasticity and within patch reef and low on the fringing reef, a typical linear barrier reef environment. Within each habitat, three 300 m long by 10 m wide belt transects were set along the reef parallel to shore, representing 45,000 m2 of reef. All colonies observed in our surveys were measured, photographed

95 and georeferenced. Maps of the locations of each colony were produced using R (R Development Core Team 2013).

2.3. Morphology assessment

All colonies were classified as one of these morphologies: 1) encrusting: thin colonies growing against the substratum, 2) sheet tree: encrusting bases with vertical blade-like outgrowths and 3) massive: solid colonies, roughly hemispherical in shape (see photo series in Fig. 5.1). Colonies below 50 cm2 were removed from our dataset to avoid misidentifying small colonies of M. platyphylla whose morphology is less distinct. Morphological variation among transects and habitats were quantified with a permutational multivariate analysis of variance using Bray-Curtis similarity coefficient (permanova test; PRIMER 6 software) (Clarke et al. 2008).

2.4. DNA extraction and microsatellite genotyping

Samples were preserved in 80% ethanol until DNA extraction. Small fragments of tissue-covered skeleton (< 2 cm3) were incubated at 55 ºC for 1 hr in 450 µL of digest buffer with proteinase K (QIAGEN, Hilden, Germany). Genomic DNA was extracted using a QIAxtractor automated genomic DNA extraction instrument, according to manufacturer’s instructions. Samples were amplified and genotyped at 12 microsatellite loci shown to be coral-specific and polymorphic in M. platyphylla. The primers used are listed in (Table S2). PCRs were performed in a final volume of 10 µL including 5 µL Type-it Multiplex PCR Master Mix (1x) (QIAGEN, Hilden, Germany), 3 µL RNase-free water, 1 µL primers (2 µM of fluorescently labelled forward primer – G5 dye set including 6-FAM, VIC, NED and PET – and reverse primer diluted in TE buffer) and 1 µL of template (10 to 50 ng.µL-1). The PCR program included an initial denaturing step of 5 min at 95 ºC, followed by 40 cycles of 30 sec at 95 ºC, 90 sec at optimal temperature (53–63 ºC) depending on the microsatellite locus (see Table S2), and 30 sec at 72 ºC, followed by a final 30 min elongation step at 60 ºC. PCR products were sent to GenoScreen platform (Lille, France) for fragment analysis and were visualized using an Applied Biosystems 3730 Sequencer. An internal size standard (GeneScan 500 LIZ, Applied Biosystems) was used for accurate sizing and alleles were scored and checked manually using GENEMAPPER v.4.0 (Applied Biosystems, Foster City, CA). Samples that were ambiguous in scoring were re-amplified and re-scored. All peak profiles that were faint or ambiguous (i.e. multiple peaks) were considered as missing data. Control for the presence of null alleles and large allele dropout were performed with MICRO-CHECKER v.3.7 (van Oosterhout et al. 2004).

2.5. Balance between sexual and asexual reproduction across habitats

Assessment of the relative contribution of sexual and asexual reproduction required assignment of identical multilocus genotype (MLG) among colonies. This analysis was performed with GENCLONE v.2.0 (Arnaud-Haond and Belkhir 2007). The term clonal lineage is used for each

MLG encompassing multiple ramets (GMR). Each ‘multi-ramet genotype’ represents a lineage (originated from the same reproductive event) with all clones produced by fragmentation. MLGs with one single ramet (GSR) were considered to be produced sexually with no clone. The probability that identical MLGs arise from distinct random reproductive events was estimated as PSEX (Arnaud- Haond and Belkhir 2007). The genotypic dataset was screened for somatic mutations. Samples showing evidence of slight allelic differences among ramets of MLGs were re-amplified and screened at five additional microsatellite loci to eliminate errors in clone assignment: Mille_01, Mille_04, Mille_06, Mille_08 and Mille_09 (Heckenhauer et al. 2014). Multilocus lineages (MLLs) were defined as clustering ramets with the occurrence of somatic mutations belonging to the same clonal lineage.

Once MLLs were assigned, the proportion of clones was estimated for each transect in all habitats. A standard genotypic diversity index was estimated, the clonal richness: R = (G – 1)/(N – 1), where G is the number of MLLs and N the number of genotyped samples (Arnaud-Haond and Belkhir 5

2007). This index ranges from zero (all samples belong to the same lineage) to one (each sample

belongs to a unique lineage). The Simpson index D* (Simpson 1949), corrected for sample size, was estimated for each transect. The clonal equitability was also investigated using the Simpson’s evenness index: ED* = (D – Dmin)/(Dmax – Dmin), with Dmin and Dmax being the approximate minimum and maximum values of D*. This index also ranges from zero (population dominated by one lineage) to one (population composed of lineages reaching an equal number of ramets). The maximum number of ramets per lineage (MAX) was estimated. Colony size data (projected surface) were estimated from 2D photos using ImageJ 1.4f (Abràmoff et al. 2004). Size frequency distributions of both single and clonal ramets within each of the five surveyed habitats were generated. Multivariate permanova tests were used to quantify the variation in sexual and asexual reproduction among transects and habitats.

2.6. Distribution and morphology of clonal lineages clones coral Fire demonstrate phenotypic plasticity

The maximum geographic distance between two ramets belonging to the same clonal lineage is the clonal subrange (CR). CR was estimated within and among habitats using GENCLONE. Pairwise geographic distances between clones were computed in GENALEX v.6.4 (Peakall and Smouse 2006). Variation among transects and habitats were quantified with multivariate permanova tests. 97

Maps showing the distribution of all ramets within each clonal lineage across habitats were produced using R. Clonal lineages that were shared in at least two habitats were identified; these were used to assess whether morphologies varied among clones between habitats with contrasting levels of wave energy (i.e. phenotypic plasticity). Only clonal lineages with at least five clones in at least two habitats were retained to assess phenotypic plasticity.

3. Results

3.1. Sexual versus asexual reproduction

A total of 3651 colonies of Millepora platyphylla were counted over the five surveyed habitats. 77.7% of the colonies were observed on the fore reef habitats (i.e. 1761 colonies on the upper slope and 1075 on the mid slope), while only 5.2% on the patch reef (Table S3). Out of the 3651 samples analyzed, 1157 multilocus genotypes (MLGs) were detected with our 12 microsatellite loci. The probability of repeated MLG to arise from distinct sexual reproductive events (PSEX) was negligible (≤ 0.001). Based on this analysis, 93 MLGs showed evidence of somatic mutations and reduced the probability of distinguishing clone mates. By sequentially replacing the mismatched allele at one locus between MLGs, a total of 1064 multilocus lineages (MLLs) were retained for further analyses. Overall, 69% of the 1064 lineages were assigned to a single ramet belonging to a unique lineage (GSR), while the remaining 31% were identified as clonal lineages with multiple ramets

(GMR). The proportion of single ramets was higher on the mid slope (42.7%) and back reef (29.3%), while lower for other habitats (≤ 18.9%) (Fig. S2, left side). On the mid slope, the proportion of single ramets was highest in small size classes with 32.3% represented in sizes below 32 cm2, i.e. mostly juveniles (> 1–20 cm2, 27.2 ± 5.5%). Single ramets were distributed at 19.3% in medium size classes on the back reef, i.e. mostly young adults (> 20–128 cm2, 10.7 ± 3.8%). Sexual propagules were less abundant in other habitats. On the upper slope, single ramets (11.7%) were equally distributed among size classes (0.2 ± 0.0% ≤ frequency ≤ 2.7 ± 0.2%), while mostly distributed among large size classes (> 512 cm2) in the fringing (5.1%) and patch reefs (11.7%). The size frequency distribution of single ramets was significantly different among habitats (permanova; 999 permutations, P < 0.001), while similar for the clonal ramets (Fig. S2, right side).

Fig. 5.1 Spatial distribution of sexual versus asexual M. platyphylla colonies (left) and morphologies (right) across clones coral Fire demonstrate phenotypic plasticity all five surveyed habitats. Photo series shown is of clones of the same clonal lineage found on the mid slope, upper slope, and back reef, respectively (see Fig. S7 for location of these colonies). The inset photo for sheet tree shows the horizontal view of this morphology; the vertical blades make the morphology vulnerable to fragmentation in the high energy upper slope habitat. Data shown are for the transect with the greatest sample size (See Figs. S3 and S4 for all transect replicates).

3.2. Morphology of sexual and clonal ramets

In addition to assigning each georeferenced colony to a genetic lineage, the morphology of each single and clonal ramet was classified (Fig. 5.1). On the upper slope, 76.7% (± 5.1, SE) of the colonies (i.e. single and clonal ramets) displayed the sheet tree morphology, while the remaining colonies were encrusting (Fig. S4 and Table S4). Colonies on the mid slope and back reef were mostly encrusting (64.4 ± 3.1% and 71.9 ± 9.9%, respectively), while the massive morphology was dominant in the fringing and patch reefs (84.5 ± 8.4% and 74.4 ± 9.1%, respectively). There was no significant difference in morphology between the two reproductive strategies on the mid slope, upper slope and back reef (Table S5). Lastly, all single ramets were massive on the fringing and patch reefs, while significant lower proportions of massive colonies (≤ 83.3%) were observed for clonal ramets in both fringing (permanova; 999 permutations, P < 0.05) and patch reefs (P < 0.01).

3.3. Distribution and morphology of clonal lineages

The 328 distinct clonal lineages identified were distributed in lines perpendicular to the reef crest, aligned with wave energy (Fig. 5.2 and Fig. S5). Clone mates of each clonal lineage were close to one another with a mean distance of 17.98 m (± 35.40, SE) between clones. The back and patch reefs are the habitats where the wave energy disperses. These habitats had higher values of clonal subrange, with respectively 87.6 m (± 18.3, SE) and 142.7 m (± 64.5, SE) (Table S3). One clonal lineage was found in two different transects within the patch reef with a clonal subrange of 448.9 m (Fig. S6). Clonal dispersal is more limited within the mid slope (29.6 ± 3.2 m), upper slope (39.6 ± 13.1 m) and fringing reef (56.3 ± 47.7 m) where wave energy is lower (mid slope and fringing) and where waves break (upper slope) (Table S3). 57 lineages had clones shared in at least two of the mid slope, upper slope and back reef habitats (Fig. 5.2 and Fig. S7). Clone mates of each of these lineages were at a mean distance of 58.90 m (± 44.61, SE) with a maximum clonal subrange of 239.9 m.

Six of these clonal lineages had clones (5–33) shared in at least two habitats. 80% of these clones displayed the sheet tree morphology on the upper slope but five of these six lineages are 100% encrusting or massive on the mid slope and back reef (the other is 80% massive or encrusting) (Table 5.1). Fire corals within these lineages demonstrate phenotypic plasticity (see photo series in Fig. 5.1).

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4. Discussion 5

This study reports evidence of phenotypic plasticity among fire coral clones with clones expressing different morphologies (i.e. phenotypes) among reef habitats. Phenotypic plasticity among genetically identical individuals has been suggested in natural coral populations based on early genetic work (i.e. electrophoresis analyses, see Ayre and Willis 1988). Using contemporary genetic tools, we find that M. platyphylla clones have a vulnerable morphology that increases colony fragmentation. Corals typically have wave-tolerant growth forms in high-energy reef areas. This is almost certainly due to the costs of being injured outweighing the benefits of fragmenting (Highsmith 1982). The results presented here suggest that fire corals being susceptible to fragmentation on the upper slope has greater benefits than costs in the marginal reef habitat of Moorea Island.

4.1. Genetic diversity clones coral Fire demonstrate phenotypic plasticity

The genotype diversity (> 1000 genotypes) observed in this study is the highest ever documented for terrestrial or marine populations. Most studies assessing genetic variation in clonal organisms are not spatially explicit (Arnaud-Haond et al. 2008; Schwartz and McKelvey 2008; Gorospe et al. 2015), are based on sampling few individuals (~50) (Becheler et al. 2014; Adjeroud et al. 2014;

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Ardehed et al. 2015), or involve sampling of a single habitat (Gorospe and Karl 2013). Such studies may therefore underestimate genotype diversity in clonal populations. Gorospe and Karl (2013) identified ~80 genotypes from more than 2700 colonies of Pocillopora corals. These authors exhaustively sampled colonies in a single patch reef in Kaneohe Bay, where coral reef cover has declined greatly over recent decades due to human activities (e.g. Smith et al. 1981; Jokiel et al. 1993). Despite recent disturbances on Moorea’s reefs (Acanthaster outbreaks and cyclone), the M. platyphylla population is still characterized by a high genotype diversity. This suggests that some aspects of its life history (e.g. reproduction and growth) successfully increase its resilience under such environmental stress.

Table 5.1 Proportion of clones with encrusting, sheet tree and massive morphology for six clonal lineages shared among habitats.

Habitat N Morphology (%)

Encrusting Sheet tree Massive Mid < 5 ------Upper 32 12.50 87.50 ---- Back 5 100 ------Mid 10 70 ---- 30 Upper 5 ---- 100 ---- Back < 5 ------Mid < 5 ------Upper 33 24.24 75.76 ---- Back 5 100 ------Mid < 5 ------Upper 9 55.56 44.44 ---- Back 5 100 ------Mid 5 40 20 40 Upper 9 ---- 100 ---- Back < 5 ------Mid 6 100 ------Upper 11 54.55 45.45 ---- Back < 5 ------Proportions are not estimated for clonal lineages with less than 5 clones.

Fire corals on the exposed fore reefs had the highest genotype diversity. In fore reefs (mid and upper slopes), the survival of both sexual and clonal colonies can be greater. These areas have lower disturbance frequencies than the habitats closer to the coast where anchoring impacts are greater and water quality is poorer due to human interactions (Fichez et al. 2005; Fabricius 2005; Cooper et al. 2007). On the mid slope, the high investment in sexual reproduction maintains fire coral populations where wave energy is low and settlement success is high (Roth and Knowlton 2009). Consequently, genotype diversity is greater on the mid slope (see Appendix S1 for more details). On

102 the upper slope, the high number of genotypes is mostly due to the low but continuous supply of sexual larvae and the high level of clonal propagation of these well established recruits (i.e. the ‘memory-effect’ in Bengtsson 2003, see Appendix S1 for more details). In near coast habitats (fringing and patch reefs), genotype diversity is relatively low and, correspondingly, abundance and sexual reproduction are lowest. This confirms and extends earlier findings demonstrating that recruitment and disturbance histories can play an important role in maintaining genetic diversity in local populations (Bengtsson 2003; Schwartz et al. 2007).

In highly clonal populations, local adaptation (i.e. via genetic changes) in response to selection pressures is expected to be much slower due to these populations having lower genetic diversity (Halkett et al. 2005). We find high genotype diversity and a lack of population structure (Table S6) likely driven by larval and fragment dispersal among habitats, which creates a genetically homogenous population. This result emphasizes that genetic adaptation through the selection of a particular adapted genotype may not have taken place in M. platyphylla population at Moorea. With the exception of the fringing reef, the system is characterized by a mix of reproductive processes leading to high genotype diversity.

4.2. Clone distribution 5 M. platyphylla populations in Moorea are highly clonal with 80% of all individuals produced

through fragmentation. Here, the probability that sexually produced genotypes belong to a clonal

lineage outside the study area is low due to our exhaustive sampling design, extensive field surveys (45,000 m2 of reef) and the proximity between clone mates (average separation ~17 m). Variance in the proportion of clones among habitats strongly suggests wave energy and flow velocity as environmental drivers of clonal dynamics in the study population. The great majority of colonies are clones where wave energy is high (upper slope) and where waves and resultant coral fragments disperse (back and patch reefs). The proportion of clones is lower in deeper waters where wave energy is lower (mid slope). The fringing reef is characterized by the highest contribution from asexual reproduction through fragmentation. Very few sexual or clonal lineages are spread within the fringing reef, which reduces the effective population size and potential for mating (i.e. reproductive success is lowered). Wave energy is typically lower in the fringing reef, which is

sheltered. However, this habitat is exposed to large waves during the austral summer (Hench et al. clones coral Fire demonstrate phenotypic plasticity 2008), which likely drives asexual reproduction through fragmentation of the colonies there. This result highlights the importance of asexual reproduction at the margins (see also: Baums 2008; Silvertown 2008), even highly locally, of M. platyphylla range (Randall and Cheng 1984).

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Maps of colony locations reveal that clones are dispersed in line perpendicular to the reef crest. This distribution is in perfect alignment with wave energy attenuation after waves break on the upper slope and crest. Although there is previous evidence of water flow driving coral clone dispersal, to our knowledge, this is the first example of distribution patterns of clones being perfectly aligned with wave energy dispersal (Japaud et al. 2015). Clonal dispersal (i.e. maximum distance between two clones) is higher on the back and patch reefs, which may be due to the hydrodynamic regime there. These habitats are located at the limits of the lagoon where the waves break on the reef crest creating a turbulent kinetic energy (Hench et al. 2008). The distribution patterns also suggest water flow disperses clones of the same genetic lineage across adjacent habitats (i.e. mid slope, upper slope and back reef). Numerous studies have demonstrated that wave breaking drives water flow across the reef into the lagoon (Hearn 1999; Gourlay and Colleter 2005; Hench et al. 2008). Clone locations in Moorea indicate that water can disperse clones up to several hundred meters from the fore reef to the lagoon through multiple generations. This could occur via a ‘stepping stone’ process via different fragmentation events of the same clonal lineage and potentially within a single generation depending on flow velocities during fragmentation.

4.3. Phenotypic plasticity and future research

The three morphologies displayed by M. platyphylla (i.e. encrusting, sheet tree and massive) are unevenly distributed among the five reef habitats studied. The sheet tree morphology of M. platyphylla, the most vulnerable to wave-induced breakage, is nearly exclusive to colonies encountered in the upper slope. Waves can break the blades there, while the encrusting bases remain intact (Edmunds 1999). During the study, M. platyphylla colony fragments were observed that had clearly broken and were re-attaching to the reef framework. Among the genotypes represented, six clonal lineages with clones dispersed among habitats show distinct morphologies, demonstrating phenotypic plasticity in M. platyphylla. This is a unique example of highly local-scale developmental plasticity through morphological changes.

For long-lived sessile modular organisms, such as fire corals, morphological responses to local environmental conditions among clones can occur in the early development of the colony. For a fragmented colony, this is when many interconnected polyps are produced after the breakage of the colony (i.e. regeneration) (Todd 2008). These plastic responses may be due to stem-cell regulation, known to play an important role in asexual cloning in marine invertebrates (Rinkevich and Matranga 2009), and/or skeleton structures in corals (e.g. corallite shapes, skeletal mass, branch diameter and length) (Bruno and Edmunds 1997; Tambutté et al. 2015). Information on both structural modifications and signaling pathways in coral is scarce. More research is needed to

104 identify the mechanisms behind their developmental plasticity. Responses of sessile organisms to environmental stress are often discussed in terms of physiological plasticity since changes in physiological traits constitute the basis of homeostasis at the individual level (Piersma and Lindström 1997; Hoogenboom et al. 2008; Padilla-Gamiño et al. 2012). More information on physiological plasticity in fire coral clones is also needed to understand the relative importance of morphological and physiological traits in determining population maintenance in various environments.

4.4. Conclusions

M platyphylla is the only species of fire corals identified in French Polynesia to date. However, corals of the Millepora genus can be found in all tropical coral reef regions (Lewis 2006). Some previous studies on Millepora species have demonstrated intraspecific morphological variation, where compact and robust morphologies are found in high energy reef zones (Weerdt 1981; Kaandorp 1999). We find the opposite pattern in Moorea. The extensive sampling performed for this study showed that nearly all genets invest in the vulnerable sheet tree morphology in the upper reef slope and very rarely do so in the habitats with less energy. Reef environments are so dynamic that the percentage of fragmented colonies able to re-attach must be very low. Even so, enough are re-attaching to make asexual reproduction through fragmentation the primary means by which M. 5

platyphylla is colonizing reefs in Moorea. M. platyphylla morphologies clearly vary among the reef

habitats in Moorea and many of these reef-building coral clones demonstrate phenotypic plasticity.

Acknowledgements

We are grateful to A. Mercière for field support and help with statistical analyses. We also thank F. Lerouvreur and M. Besson who contributed to the fieldwork and V. Berteaux-Lecellier for valuable discussions. The figures were developed collaboratively with D. Tracey. C.E.D. is supported by a graduate scholarship from the Fonds Québécois de Recherche sur la Nature et les Technologies. E.B. and J.A.M. were supported by European Commission Marie Curie Actions fellowships

Fire coral clones coral Fire demonstrate phenotypic plasticity

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Supporting Information

Fig. S1 Aerial views of the locations of each transect in the five surveyed habitats in Moorea, French Polynesia. The names of these surveyed locations are: Tiahura (A), Papetoai (B), Cook’s Bay (C) and Temae (D). Map data © 2015 Google.

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Fig. S2 The size frequency distributions of single ramets (left) and clonal ramets (right) across the five clones coral Fire demonstrate phenotypic plasticity surveyed habitats (both sides add to 100%). Colony size (cm2) data distributed among 10 size classes. Frequencies (%) of single and clonal ramets for each size class were averaged by habitats with total population size (N in Table S3) and error bars show the standard error for transect replicates.

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Fig. S3 Spatial distribution of single and clonal ramets across the five surveyed habitats within three belt transects (300 x 10 m).

Fig. S4 Spatial distribution of colony morphologies across the five surveyed habitats within three belt transects (300 x10 m).

Fig. S5 Spatial distribution of clonal lineages across the five surveyed habitats along three 300 x 10 m belt transects. Each clonal lineage is represented by a unique color (N = 328).

Fig. S6 Spatial distribution of a single clonal lineage shared among two of the three transects within the patch reef.

Fig. S7 Spatial distribution of clonal lineages with clones shared in at least two habitats across the mid slope, upper slope and back reef. Each clonal lineage is represented by a unique colour (N = 57). Arrows in T3 depict the location of clones used in the photo series shown in Fig. 5.1.

Table S1 Locations of each transect within the five surveyed habitats in Moorea, French Polynesia.

Habitat Latitude Longitude Distance to Distance to Depth (°S) (°W) coast (m) crest (m) (m)

Mid 1 17.4816 149.8755 1155.73 122.36 13.17 Mid 2 17.4813 149.8785 1215.28 135.54 12.99 Mid 3 17.4819 149.8817 1034.70 118.32 12.59

Upper 1 17.4820 149.8755 1110.26 84.56 6.09 Upper 2 17.4818 149.8786 1176.29 93.45 5.95 Upper 2 17.4822 149.8816 995.20 76.98 5.65 5 Back 1 17.4838 149.8742 917.83 87.80 0.65

Back 2 17.4834 149.8773 1074.67 65.50 0.81

Back 3 17.4832 149.8805 927.40 37.72 0.76

Fringing 1 17.4881 149.8967 331.05 564.65 0.79 Fringing 2 17.4902 149.8676 323.32 561.96 0.84 Fringing 3 17.4836 149.8165 40.07 1198.13 0.80

Patch 1 17.4775 149.7673 35.40 66.47 0.97 Patch 2 17.4759 149.7699 20.28 52.78 0.90 Patch 3 17.4742 149.7726 26.91 58.98 0.59

Fire coral clones coral Fire demonstrate phenotypic plasticity

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Table S2 Newly developed polymorphic microsatellite loci for M. platyphylla.

Locus GenBank TA Size (bp) Na name Primer Sequence 5'-3' Motif accession (°C) range

Mill07 F: TAGTACATCGGGCATGAGCA (CA)16 KX670763 63 92–144 25 R: GTACTCTACGGCGTGTGCGT

Mill27 R: CTTTCGTTTCCGATCATTCC (TG)10 KX670764 55 136–148 7 R: TGCCAGAACTAAGTTATCACAGC

Mill30 F: AGTTGGCTCTGAGTGCGAGT (TG)11 KX670765 57 203–211 4 R: CCTCGGTTTATGGCTGAGAT

Mill47 F: AAGCGTGTAATGCACTCAAAGA (GA)8 KX670766 53 118–162 14 R: AACAGAAGTCGAACTGAGTCAAAA

Mill52 F: CCCTGAGGCATCGAAATATAA (AC)9 KX670767 57 94–98 2 R: TGCAATTGATGGTATTTGCATT

Mill61 F: AAATGAACTCGCCCAAAAGA (CAA)7 KX670769 57 163–166 2 R: ACACTGTCGATTGTGTTCCAA

Mill67 F: TTGCGAGTTTACTTACCAGGC (TAGA)6 KX670770 53 259–359 17 R: TGAAGCAAATGACAAGAGCAA

Mill93 F: TGAAATTTTCCAGTGACATCAAA (TGT)7 KX670773 57 91–100 4 R: GCTAATTATGAAATAGCAACTCCTAAA

Mill94 F: GCATAAAGAATAAAGCAGAGGCA (GAA)7 KX670774 55 131–140 5 R: CAATTGTGGGGAAGTTCGTT

Mill95 F: TCCATAGCTTCTGCCTCCTC (TTG)7 KX670775 53 123–138 5 R: GCTGATGATGCTGTCGAAGA

Mill101 F: AGTCCTTCAATTGGTGGGTG (CAA)6 KX670776 53 132–135 2 R: GAGATGATGACTGAGCAGCAG

Mill103 F: TTAAAGCCAGAGACAGAGAGACA (AG)7 KX670777 53 94–100 4 R: ATCAACAGTTTCCCCTGTGC

TA, Annealing temperature (°C); Na, Number of alleles per locus.

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Table S3 Index describing sexual and clonal diversity for M. platyphylla across the five surveyed habitats.

Habitat N GSR GMR Clone R D* ED* MAX CR (m) (% of N)

Mid 1 542 147 48 0.73 0.36 0.98 0.95 53 25.89 Mid 2 230 131 22 0.43 0.66 0.99 0.90 14 31.54 Mid 3 303 128 28 0.58 0.51 0.98 0.93 21 31.33 Tot / Mean 1075 406 98 0.58 ± 0.15 0.51 ± 0.15 0.98 ± 0.01 0.93 ± 0.03 29.59 ± 3.20

Upper 1 510 57 53 0.89 0.21 0.97 0.96 54 32.83 Upper 2 656 73 55 0.89 0.19 0.96 0.94 71 54.69 Upper 3 595 75 54 0.87 0.22 0.94 0.91 125 31.36 Tot / Mean 1761 205 162 0.88 ± 0.01 0.21 ± 0.02 0.96 ± 0.02 0.94 ± 0.03 39.63 ± 13.07

Back 1 101 26 28 0.74 0.53 0.97 0.89 12 78.20 5 Back 2 119 29 33 0.76 0.52 0.97 0.90 15 108.69

Back 3 104 34 25 0.67 0.56 0.98 0.94 7 75.91

Tot / Mean 324 89 86 0.72 ± 0.05 0.54 ± 0.02 0.97 ± 0.01 0.91 ± 0.03 87.60 ± 18.30

Fringing 1 78 3 7 0.96 0.12 0.76 0.78 34 28.61 Fringing 2 27 1 3 0.96 0.12 0.34 0.22 22 111.40 Fringing 3 197 2 12 0.99 0.07 0.79 0.83 81 28.98 Tot / Mean 302 6 22 0.97 ± 0.02 0.10 ± 0.03 0.63 ± 0.25 0.61 ± 0.04 56.33 ± 47.70

Patch 1 62 8 12 0.87 0.31 0.94 0.93 8 216.80 Patch 2 68 6 6 0.91 0.16 0.77 0.75 25 112.08 Patch 3 59 13 12 0.78 0.41 0.95 0.92 7 99.19 Tot / Mean 189 27 30 0.85 ± 0.07 0.29 ± 0.13 0.89 ± 0.10 0.87 ± 0.10 142.69 ± 64.50

N, number of genotyped samples; GSR, number of lineages with single ramet; GMR, number of lineages with multiple ramets; Clone, proportion of clones; PSEX, probability that clones arisen from sex; R, clonal richness; D*, Simpson’ diversity index; ED*, clonal evenness; MAX, maximum number of ramets per lineage; CR, clonal subrange (m). Bold values are average per habitat and ± SE for variation among transects clones coral Fire demonstrate phenotypic plasticity

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Table S4 Average numbers (N ± SE) and percentages (% ± SE) of colonies for M. platyphylla with encrusting, sheet tree and massive morphology within each surveyed habitat.

N Colonies of M. platyphylla

Habitat Encrusting Sheet tree Massive

Mid 82.67 ± 50.62 12.67 ± 15.14 33.33 ± 15.37 Upper 74.67 ± 10.97 249.67 ± 38.53 ---- Back 59.00 ± 8.54 7.67 ± 5.13 15.33 ± 2.89 Fringing 12.67 ± 14.57 ---- 49.67 ± 39.07 Patch 8.67 ± 1.53 1.00 ± 1.73 29.33 ± 8.74

% Colonies of M. platyphylla

Habitat Encrusting Sheet tree Massive

Mid 64.43 ± 3.13 7.55 ± 5.47 28.01 ± 6.09 Upper 23.28 ± 5.08 76.72 ± 5.08 ---- Back 71.91 ± 9.90 9.38 ± 6.39 18.71 ± 3.56 Fringing 15.54 ± 8.38 ---- 84.46 ± 8.38 Patch 23.08 ± 7.10 2.50 ± 4.33 74.42 ± 9.14

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Table S5 Average numbers (N ± SE) and percentages (% ± SE) of single and clonal ramets for M. platyphylla with each morphology within each surveyed habitat.

N Single ramet Clonal ramet

Habitat Encrusting Sheet-tree Massive Encrusting Sheet-tree Massive

Mid 18.00 ± 3.64 1.33 ± 1.52 5.33 ± 0.58 64.67 ± 48.21 11.33 ± 13.65 28.00 ± 15.87 Upper 8.00 ± 3.60 22.00 ± 3.60 ---- 66.67 ± 7.37 227.67 ± 36.23 ---- Back 18.33 ± 7.09 1.66 ± 2.89 3.00 ± 2.00 40.67 ± 1.53 6.00 ± 3.60 12.33 ± 1.53 Fringing ------2.00 ± 1.00 12.67 ± 14.57 ---- 47.67 ± 38.63 Patch ------6.67 ± 3.05 8.67 ± 1.53 1.00 ± 1.73 22.67 ± 6.51

% Single Ramet Single Ramet

Habitat Encrusting Sheet-tree Massive Encrusting Sheet-tree Massive

Mid 72.70 ± 6.76 4.90 ± 5.41 22.40 ± 9.52 61.99 ± 2.00 8.39 ± 5.03 29.61 ± 5.80 Upper 26.67 ± 12.02 73.33 ± 12.02 ---- 40.78 ± 7.44 54.93 ± 7.44 ---- Back 77.86 ± 18.15 8.33 ± 14.43 13.81 ± 9.57 69.15 ± 6.26 9.94 ± 5.64 20.90 ± 2.13 Fringing ------100 ± 0.00 16.17 ± 8.25 ---- 83.83 ± 28.23 Patch ------100 ± 0.00 27.74 ± 8.28 2.78 ± 4.81 69.48 ± 9.59

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Table S6 Genetic differentiation for M. platyphylla populations between the five surveyed habitats.

Patch 2 Patch 3 Frin 1 Frin 2 Frin 2 Back 1 Back 2 Back 3 Upper 1 Upper 2 Upper 3 Mid 1 Mid 2 Mid 3

Patch 1 0.010 0.010 0.000 0.022 0.015 0.004 0.000 0.003 0.015** 0.010* 0.010* 0.004 0.004 0.017*** Patch 2 0.000 0.006 0.029 0.010 0.005 0.014 0.001 0.012 0.004 0.001 0.006 0.000 0.020** Patch 3 0.008 0.030 0.019 0.008 0.019** 0.000 0.016** 0.009* 0.008 0.014** 0.009* 0.016*** Frin 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Frin 2 0.000 0.000 0.000 0.013 0.001 0.000 0.020 0.005 0.004 0.005 Frin 3 0.008 0.005 0.010 0.003 0.000 0.009 0.009 0.001 0.015* Back 1 0.000 0.001 0.000 0.000 0.001 0.000 0.000 0.004* Back 2 0.005 0.006* 0.002 0.007** 0.000 0.000 0.011*** Back 3 0.008* 0.002 0.002 0.003 0.001 0.005* Upper 1 0.003* 0.007*** 0.003* 0.004*** 0.010*** Upper 2 0.002* 0.003* 0.001 0.007*** Upper 3 0.004** 0.005** 0.008*** Mid 1 0.001 0.007*** Mid 2 0.009***

The estimator of Weir and Cockerham’ FST was estimated among transects of each surveyed habitat using GENETIX v.4.05.2 (Belkhir et al. 1996). Values were calculated on a data set where only one of each lineage was retained (i.e. colonies of sexual origin). * P < 0.05, ** P < 0.01, *** P < 0.001 and all other values are NS.

Appendix S1 Further details on size distribution of single and clonal ramets.

Our results indicate that wave energy forcing highly impacts the dynamics of sexual colonies in local populations (Fig. S2). In the mid slope, most sexual colonies are small recruits and juveniles (< 20 cm2, 63.7%, i.e. 27.2% out of the 42.7%) suggesting that low level of wave energy facilitates settlement success of recently produced propagules. The survival of these new settlers can increase the genotype diversity in the mid slope and their longevity will further influence the genetic variability within M. platyphylla population in Moorea. Contrastingly, the high level in wave energy on the upper slope seems to reduce recruitment success, although settlement of sexual larvae appears constant through times (frequencies among size classes, 0.2 to 2.7%). The survival of early established sexual propagules (i.e. recruitment history) can enhance the genotype diversity in the upper slope. This phenomenon is known as the ‘memory-effect’; even low investment in sexual recruitment is enough to retain high genotype diversity through time in highly clonal populations (Bengtsson 2003). Further, the hydrodynamic regime in the back reef has promoted the recruitment of sexual larvae in the past (> 20–512 cm2, 65.9%, i.e. 19.3% out of the 29.3%). Recent natural and/or anthropogenic disturbances may have recently impacted the back reef habitat, reducing settlement success and/or increasing post settlement mortality of newly established recruits. Contrastingly, there is no such evidence of disturbance effect on clonal dynamics. Clones may have higher survivorship compared to sexual recruits in all habitats regardless of the habitat specific 5

conditions, likely due to low survivorship of larval propagules during the settlement stage

Fire coral clones coral Fire demonstrate phenotypic plasticity

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CHAPTER 6 Dispersal limitations of early life stages and sibling aggregations in Millepora hydrocorals, as revealed by parentage analysis

To be submitted as: Dubé CE, Boissin E, Planes S. Dispersal limitations of early life stages and sibling aggregations in Millepora hydrocorals, as revealed by parentage analysis. Molecular Ecology

Dispersal limitations of early life stages and sibling aggregations in Millepora hydrocorals, as revealed by parentage analysis

Caroline E. Dubé, Emilie Boissin, Serge Planes

EPHE, PSL Research University, UPVD-CNRS, USR 3278 CRIOBE, F–66860 Perpignan, FRANCE Laboratoire d’excellence “CORAIL”, EPHE, PSL Research University, UPVD, CNRS, USR 3278 CRIOBE, BP 1013, 98729 Papetoai, Moorea

Keywords Dispersal · Self-recruitment · Sibling aggregations · Clones · Microsatellites · Millepora

Correspondence: Caroline E. Dubé, USR 3278 CRIOBE, Fax: +33-468-503-686; E-mail: [email protected]

Running Title: Dispersal patterns in Millepora hydrocorals

Abstract

Determining direct genetic estimates of dispersal and subsequent recruitment is crucial for understanding marine population dynamics and replenishment. In this study, we resolve dispersal patterns of sexual propagules of the partially clonal fire coral Millepora platyphylla in Moorea, French Polynesia. We conducted an extensive field survey of 3160 georeferenced colonies over 9000 m² of reef across three adjacent habitats. The parentage analysis based on twelve microsatellite markers revealed a high contribution of self-recruitment with 58% of the juveniles identified as self-recruits. Most of the offspring settled at less than 10 meters from their parents with a decrease in dispersal success over a distance of 300 meters. Limited connectivity among adjacent habitats via cross-reef transport was also detected. Sibship analyses showed that both full and half siblings recruit together on the reef resulting in sibling aggregations. Additionally, local families revealed that offspring are dispersed with currents that run along the reef and settled in alignment with the location of their parents. Even though most of the adults were clones, we found that parents with clonal replicates (asexual fragments) do not increase the number of self-recruits nor the dispersal potential of their offspring. Overall, this study is the first to provide direct estimates for local dispersal and self-seeding in Millepora hydrocorals and provides important information on their reproductive biology and early life ecology. Our work presents new evidence on the importance of self-recruitment in stabilizing population dynamics, as it enhances local sustainability and resilience to disturbance.

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1. Introduction

Understanding patterns of larval dispersal is a major goal in ecology and conservation biology (Warner and Cowen 2002; Cowen et al. 2007; Botsford et al. 2009). These patterns shape species’ distribution and abundance (Strathmann et al. 2002) and have major consequences for the persistence and adaptation of their populations (Garant et al. 2007; Underwood et al. 2009; Gilmour et al. 2013). For most marine species whose adults are sessile or relatively sedentary, the early life history includes a propagule stage and represents the first step for successful recruitment. Propagule

dispersal depends on many biological and physical processes, including the survival and

Millepora in in development rates of propagules (Figueiredo et al. 2013; Johnson et al. 2014; Doropoulos et al. 2016), larval behavior (Paris et al. 2007; Gerlach et al. 2007), and hydrodynamic regimes and seascapes (Cowen et al. 2006; Cowen and Sponaugle 2009; White et al. 2010). In coral reefs, many organisms, (e.g. fishes and scleractinian corals), rely on the dispersal of a larval stage for population replenishment and colonization of fragmented habitats.

Determining whether the maintenance of reef populations is more heavily influenced by local recruitment (i.e. most propagules settle close to their parents) or longer-distance dispersal is an issue

of much debate (Cowen et al. 2000; Strathmann et al. 2002). As larvae are relatively small and difficult to track in the pelagic environment, many studies investigating marine dispersal have relied

on virtual simulations of hydrodynamics rather than empirical estimates (Treml et al. 2008; Andutta Dispersal limitationsand sibling aggregations

hydrocorals et al. 2012; Wood et al. 2014). Parentage analysis is an efficient tool for determining self- recruitment and connectivity. Such a genetic approach in reef fishes uncovered high levels of 6 recruitment back to the parental source at some reefs (e.g. 30–60%, see Jones et al. 2005; Almany et al. 2007). This research reinforces the idea that reef populations are less open than previously thought.

In scleractinian corals, the extent of dispersal is largely governed by their reproductive biology and early life history ecology. Our ability to make inferences on what specific biological processes are driving dispersal and subsequent recruitment patterns in corals is limited due to their diverse dispersal strategies; gamete broadcasting, larval brooding, clonal propagation through fragmentation and polyp bailout (Harrison 2011). Nevertheless, field surveys and classical population genetic studies have suggested high levels of self-recruitment and limited dispersal in corals (Baums et al. 2005; Gilmour et al. 2009; Torda et al. 2013). Recently, the application of genetic parentage analysis in reef corals provided the first direct estimates of restricted larval dispersal in brooding species (Ledoux et al. 2010; Warner et al. 2016). Although broadcast spawning of gametes with planktonic development of larvae is the most common reproductive

123 strategy in coral reefs (Baird et al. 2009), dispersal patterns of their sexual propagules using parentage analyses have yet to be determined. Such information will provide us with the ability to disentangle whether or not this reproductive strategy optimizes larval dispersal, as commonly thought.

Millepora hydrocorals, also called fire corals, are an important component of reef communities where they, similar to scleractinian corals, contribute to the accretion of reefs (Nagelkerken and Nagelkerken 2004; Lewis 2006). Despite their importance in reef community dynamics, fire corals have been relatively understudied and not much is known with respect to their reproduction and dispersal patterns (reviewed in Lewis 2006). Millepora platyphylla has successfully colonized a wide range of reef environments in the Indo-Pacific region via both asexual and sexual reproduction (Lewis 2006; Dubé et al. unpublished data1). M. platyphylla is a gonochoric broadcast spawner that reproduces sexually by producing medusoids (modified medusa) and planula larvae. Medusoids are developed at the surface of the polyp coenosteum in cavities called ampullae and undergo sexual reproduction (Lewis 1991). The medusoids are shed freely in the water and release their gametes at the surface in one hour post-spawning (i.e. short-lived). After fertilization, the zooxanthellate planula larvae sink and move epibenthically (i.e. crawling not swimming) on the reef substratum and metamorphose into a new calcifying polyp in one day to several weeks after spawning (Bourmaud et al. 2013). Fire corals also rely on clonal propagation through fragmentation for local replenishment (Dubé et al. unpublished data1). The production of asexual larvae has never been documented within the Millepora genus. To date, there is no genetic study that has identified patterns of dispersal and recruitment in these reef-building species, although such information is crucial for understanding their population replenishment and recovery.

Here, we conducted an extensive field survey of 3160 georeferenced colonies of M. platyphylla over 9000 m² of reef based on replicated transects across three adjacent habitats (mid slope, upper slope and back reef) in Moorea, French Polynesia. Using parentage analysis, we attempted to resolve local patterns for the dispersal of sexual propagules and to establish the degree of self- replenishment and local sustainability of a population of fire corals. This study is the first to provide accurate estimations of local dispersal and self-seeding in Millepora hydrocorals from empirical data collected in situ.

1Dubé CE et al. Fire coral clones demonstrate phenotypic plasticity among reef habitats.

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2. Materials and Methods

2.1. Population sampling and microsatellite genotyping

Between April and December 2013, a series of surveys were conducted on the north shore of Moorea, French Polynesia, across three adjacent reef habitats at Papetoai: the mid slope (13 m depth) and upper slope (6 m depth), both fore reef habitats, and the back reef (Fig. 6.1). Within each habitat, three 300 m long by 10 m wide belt transects were laid over the reef parallel to shore, at least 30 m apart, for a total of 9000 m2 of reef area. All colonies of M. platyphylla that were at least

50% within the transect borders were georeferenced by determining their position along the Millepora

in in transect-line (0 to 300 m) and straight-line distance from both sides of the transect (0 to 10 m). From these measures, each colony was mapped with x and y coordinates. Map of the locations of each colony was produced using R (R Development Core Team 2013). The colony size (projected surface) of each colony was estimated (in cm2) from 2D photographs using ImageJ 1.4f (Abràmoff et al. 2004). To determine the gender in Millepora it requires the presence of medusoids at the surface of the colony as well as their release in the water column to observe the reproductive gametes, i.e. oocytes and sperm sacs. Such observations are difficult in the field and were thus made

only from specimens in aquariums (Weerdt 1984; Lewis 1991; Soong and Cho 1998; Bourmaud et al. 2013). Consequently, the sex of the colonies was not determined for this study. Small fragments 3

of tissue-covered skeleton (< 2 cm ) were sampled during field surveys and preserved in 80% Dispersal limitationsand sibling aggregations

hydrocorals ethanol and stored at –20°C until DNA extraction. 6

All samples were incubated at 55 ºC for 1 hr in 450 µL of digest buffer with proteinase K (QIAGEN, Hilden, Germany) and genomic DNA was extracted using a QIAxtractor automated

125 genomic DNA extraction instrument, according to manufacturer’s instructions. Each colony was amplified at twelve polymorphic microsatellite loci in four multiplex polymerase chain reactions (PCRs) using the Quiagen Multiplex PCR Kit (Table S1). Further details on these loci and the genotyping procedure are described in Dubé et al. (in revision). Samples were sent to GenoScreen platform (Lille, France) for fragment analysis on an Applied Biosystems 3730 Sequencer with the GeneScan 500 LIZ size standard. All alleles were scored and checked manually using GENEMAPPER v4.0 (Applied Biosystems, Foster City, CA).

2.2. Multilocus genotypes and population genetic analyses

To assess the discriminative power of the microsatellite markers, we estimated the genotype probability (GP) for each locus and a combination of all loci in GENALEX v.6.5 (Peakall and Smouse 2006). Repeated multilocus genotypes (MLGs) were identified in GENCLONE v2.0 (Arnaud-Haond and Belkir 2007) and were considered as clone mates at GP < 0.001. The probability of identity, P(ID), was also computed to evaluate the probability that two identical MLGs arise from distinct random reproductive events (Waits et al. 2001). Population genetic analyses were performed after the removal of all clonal replicates. Indices of genetic diversity, including the total number of alleles per locus (Na), observed (HO) and expected (He) heterozygosity (Weir and Cockerham 1984) were computed in GENALEX. Null allele frequencies were estimated with

MICROCHECKER 3.7 (van Oosterhout et al. 2004). Deviations from HWE (FIS) were assessed with a permutation procedure (N = 1000) implemented in GENETIX v4.02 (Belkhir et al. 1996).

The probability of exclusion (Pex) indicates the efficiency of a panel of microsatellite markers to exclude unrelated individuals when both parents are unknown (Jamieson and Taylor 1997). Pairwise relatedness (2x [Lynch and Ritland 1999], with relatedness varying from –1 to 1) and pairwise geographic distances between colonies were computed in GENALEX.

2.3. Parentage analysis

Kinship analyses were performed in COLONY v.2.0 (Jones and Wang 2010) to infer sibship and parentage relationships using individual MGLs. For the following analyses, only mature colonies (> 20 cm2) were considered as potential parents. Colonies smaller than 20 cm2 were considered as juveniles (used currently for scleractinian species, see Penin et al. 2010) and were assumed to be the pool of potential offspring. Parent-offspring relationships were assessed with all parental genotypes entered into the analysis as candidate fathers because the sex of colonies was unknown. COLONY was also used to identify siblings (i.e. full- and half-sibs) in the juvenile samples only. Parentage analyses were run with the assumption that 80% of potential parents were sampled due to the high number of adults and the large surveyed area. COLONY was launched with the following 126 parameters for each of the three medium length runs: both sexes are polygamous and the organism is dioecious, with inbreeding, full-likelihood method and a medium likelihood precision. Each run included explicit marker error rates, allele frequencies for the studied population computed with GENALEX and 80% sampled candidate fathers and unknown maternal sibs. Only inferred assignments with a probability of 0.95 or greater were considered for the results. Pairwise geographic distances were computed in GENALEX for all parentage relationships, i.e. parent- offspring, parent-parent, full and half siblings, and differences in dispersal patterns were assessed with a non-parametric statistical test (Kruskal-Wallis). Pearson’s correlation coefficient was used to

determine whether the number of offspring produced by each of the identified parents increased

Millepora in in with the number of ramets and colony size of parents.

3. Results

3.1. Population sampling and clones

A total of 3160 colonies of M. platyphylla were surveyed over the 9000 m2 of reef area (Fig. 6.2). The population density was approximately one colony per 10 m2 and the mean pairwise geographic

distance between all colonies within the entire study area was 347 m (± 228 SE; range: 0.01–979 m; median = 310 m). The size-frequency distribution of the population was skewed towards small 2

colonies (g1 = 0.395; Pnorm < 0.001) with 64% of all colonies below 125 cm (Fig. S1). Of all Dispersal limitationsand sibling aggregations

hydrocorals surveyed colonies, 1059 were considered as juveniles (< 20 cm ) and 2101 as adults (Table 6.1).

Table 6.1 Details of Millepora platyphylla population sampling based on colony size (ramet level) and parentage assignments across the three surveyed habitats at Moorea. Number of colonies surveyed (# col), 6 number of adults (# adu, > 20 cm2) and number of juveniles (# juv, < 20 cm2) are given. Percentages give the proportions of juveniles within that habitat that were i) offspring of parents sampled at the same habitat (SR = self-recruitment), ii) offspring of parents sampled at other habitats (HC = habitat connectivity), or iii) were not assigned to parents sampled within the entire area surveyed (UA = unassigned).

Habitats Ramet level Genet level

# col # adu # juv # col # adu # juv #assigned % SR % HC % UA

Back Reef 324 285 39 132 121 11 10 81.82 9.09 9.09

Upper Slope 1761 1253 508 357 268 89 41 43.82 2.25 53.93

Mid Slope 1075 563 512 489 214 275 165 54.55 5.45 40.00

Total 3160 2101 1059 978 603 375 216 57.60 --- 42.40

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A total of 282 multilocus genotypes (MLGs) were repeated in the entire population with GP values ranging from 3.1E-16 to 1.0E-06. Overall, 84% of adults were clones indicating that asexual reproduction prevails among this life stage. 65% of juveniles had at least one clone mate. Of these, only 4 clone pairs had no known genotype equivalent in adults, while 677 juveniles were genetically identical to one of the adult samples. Given the low P(ID) value estimated (4.5E-08), these 677 juveniles were removed from the pool of potential offspring as these repeated MLGs are

assumed to result from asexual reproduction through fragmentation. In order to perform the parentage analysis, only the biggest clone within each MLG (i.e. the colony from which

fragmentation most likely first occurred), was retained in our dataset. Following the removal of

Millepora in in replicated genotypes, 978 colonies with a unique MLG (i.e. genet level) remained to further assess sibship and parentage relationships among M. platyphylla colonies with a candidate pool of 603 parents and 375 offspring. Half of all sampled colonies were observed in the mid slope, where the proportion of total juvenile samples was the highest (i.e. 56% of potential offspring) compared to other surveyed habitats (i.e. 25% in the upper slope and only 8% in the back reef (Table 6.1).

3.2. Genetic diversity and microsatellite panel

All twelve loci were polymorphic over the 3610 colonies analyzed, with a mean observed and expected heterozygosity of 0.478 and 0.527, respectively, and 7.50 alleles per locus on average.

Seven loci showed significant deficiencies in heterozygotes compared to HWE (FIS: 0.040–1.000)

Dispersal limitationsand sibling aggregations

(Table S1). Null alleles occurred at low frequencies at six loci (< 0.006; Table S1), while a high frequency of null alleles was found only at Mill61 (> 0.1). The combined probability of exclusion, 6 P(EX), for the microsatellite marker panel was 0.94, revealing its high reliability for parentage assignments (Table S1), so all loci were retained to infer sibship and parentage relationships.

3.3. Parentage analyses and recruitment

Parentage analyses assigned 58% of all juvenile samples (216 of 375) to parents that were sampled within the study area (i.e. self-recruits, Table 6.1). 76% of these assigned juveniles (165 of 216) were found within the mid slope. Only 7% (25 of 375) had at least one parent located in one of the other habitats surveyed, suggesting more limited inter-habitat connectivity. Among the 603 parents sampled in the entire study area (genet level), only 96 of them were contributing to self-recruitment in M. platyphylla population (Fig. S2). 42 parents were unique genotypes (i.e. assumed to be the result of sexual reproduction with one single ramet), while the other 54 belonged to repeated MLGs (i.e. clonal lineages) with a mean number of 12 ramets (i.e. potential parents) per MLG (range: 2– 65). Of the 216 identified parent-offspring pairs, 203 were assigned to single parents and only 13 were to parent pairs. Although the sex of individuals was not identified in this study, distance 129 pairwise comparisons revealed that a mean distance of 314 m (± 281, SE) separated the 2 potential parents for the 13 parent-offspring pairs. On the contrary, some of these parent pairs were very far from each other (up to 892 m; median = 178 m) (Table S2). Furthermore, the mean pairwise genetic relatedness (2x [Lynch and Ritland 1999]) between parents contributing to self-recruitment (mean r = –0.011 ± 0.002 SE) was less than the average among all the potential parents surveyed in the study area (mean r = –0.002 ± 0.151 SE), indicating that biparental inbreeding was limited.

While most local parents produced less than 2 offspring each, 32% of them produced three or more offspring within the study area. We identified 4 parents with more than 5 assigned offspring. One parent produced 7 offspring and 3 other parents produced 5 offspring each within the study area (Fig. 6.3). Of these 4 families (i.e. one parent and several offspring), 2 were from clonal parents (Fig. 6.3C and D). Despite our expectations, clonal replicates and colony size of parents do not increase the number of offspring produced in the population (r = 0.067, P = 0.514 and r = 0.053, P = 0.605, respectively). Furthermore, the mapping of these families revealed that offspring seemed to settle parallel to the reef crest in alignment with the location of their parents (Fig. 6.3 and see Table S3 for details on each family). This result supports the assumption that limited connectivity exists among adjacent reef habitats due to dispersal along the reef and not from crossing the reef crest.

3.4. Dispersal distances and sibling distribution patterns

Observed dispersal distances between offspring and parents ranged from 0.05 to 921 m (Table 6.2). 50% of assigned offspring settled within 300 m of their parental sources with a gradual decrease in the proportions of offspring that settled at larger distances (Fig. 6.4A). At a smaller spatial scale (i.e. 100 m), 34% of offspring settled within the first 10 m, a distance very close to their parents (Fig. 6.4B). Parent-offspring distances revealed no difference in the dispersal abilities of unique genotype parents and clonal parents (Kruskal-Wallis test, P = 0.480, Table 6.2). This result could be related to the fact that clonal replicates for each of the 54 clonal parents were closely related in space with a mean distance of 15 m (± 28 SE; max = 226 m; median = 4 m).

Over the 375 offspring surveyed, 78 (21%) were involved in a full sibling relationship; 13 were assigned to local parent pairs, 40 to local single parents and 25 to unsampled parents. 132 offspring (35%) were also involved in a half sibling relationship from one local parent. Although dispersal distance distributions among full- and half-sibs were significantly different (Kruskal-Wallis test, P < 0.001), all siblings occurred within an aggregated pattern of distribution (Fig. 6.5).

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4. Discussion

In this study, the parentage analysis revealed a high contribution from self-recruitment (58%) in the population of M. platyphylla in Moorea. Offspring were dispersed with currents that run along the reef. While most of the new recruits settled within a few meters, adjacent habitats were also connected via cross-reef transport (7% of inter-habitat connectivity). Dispersal events were ranging up to approximately 1 km with half of the recruits settling within 300 m from the location of their parents. Still, 42% of the juveniles surveyed had parents located outside the study population and only 3% had both of their parents located within the surveys, which suggest a potential for longer- distance dispersal. Sibship analyses showed that siblings recruit together on the reef, a process that

132 results in the aggregation of siblings. Although most of the adults were clones, we found no difference between the contributions of parents with clonal replicates (i.e. asexual fragments) to local replenishment than those produced sexually (i.e. unique genotype). Clones do not increase the number of self-recruits nor do they increase the dispersal potential of their offspring.

assigned to an offspring within the surveyed area with their mean colony size (cm²), standard error (SE) and median; total number of assigned offspring and mean number of assigned offspring to one single parent with standard error (SE), maximum and median. All values are presented at the genet level (i.e. without clonal

replicates). Estimates of offspring dispersal within the study area are shown: mean distance between the Millepora

parent and their assigned offspring with standard error (SE), minimum, maximum and median. in

Parent Parent Parent total clonal genotype single genotype

# potential parents 603 279 324 # parents 96 54 42 Mean parent size (cm2) 1 002.58 982 .02 1 243.45 SE 2 980.19 2 950.73 3 336.22 Median 120.91 126.02 88.02 # assigned offspring 216 102 83 Mean # assigned offspring per parent 2.04 2.04 2.05 SE 1.30 1.30 1.45

Max 7 5 7 Dispersal limitationsand sibling aggregations Median 1.50 2.00 1.00 Mean dispersal distance parent-offspring (m) 334.48 353.16 316.18 SE 231.47 261.99 219.74 6 Min 0.05 0.05 0.05 Max 921.37 921.37 870.25 Median 304.51 307.28 296.86

4.1. High self-recruitment rates and limited connectivity among habitats

Parentage analyses revealed a self-recruitment rate of 58% in M. platyphylla population, which is much higher than previous studies that focused on brooding species of gorgonians and scleractinians (~25%, see Lasker et al. 2008; Warner et al. 2016). For M. platyphylla, we were expecting a lower contribution from self-recruitment to local population replenishment because of its larval development mode, i.e. broadcast spawning. This reproductive strategy was often associated with high dispersal ability in natural populations of countless reef-building organisms (reviewed in Harrison 2011). To our knowledge, our study is the first to provide direct estimations of self-recruitment in a population of a broadcast spawner. A high investment in self-seeding might well be an efficient process to sustain populations in an isolated and fragmented reef system such as 133

Moorea (as described in Gilmour et al. 2009). This high proportion of self-recruits in M. platyphylla can result from the interplay of its early life history ecology (e.g. pelagic larval duration and behavior) and/or local environmental conditions (e.g. water circulation and reef seascapes).

Our results reveal that M. platyphylla exhibits low dispersal ability, where most of the new recruits settle within only a few meters from their parents (less than 10 m). In addition, we found a limited connectivity among adjacent reef habitats. While very few studies have investigated the reproductive biology and early life stages of Millepora hydrocorals (reviewed in Lewis 2006), this

134 research has shown limited dispersal ability of their sexual propagules (i.e. medusoids and planula larvae). Only medusoids can swim by pulsation of their bell, while eggs are negatively buoyant and slowly sink after being released (Soong and Cho 1998) and larvae crawl once they reach the reef substratum (Bourmaud et al. 2013). Such early life history traits are most likely rising opportunities for self-recruitment in populations of fire corals, while the local dispersal among reef habitats must rely on the passive dispersal of their sexual propagules through water circulation patterns.

4.2. Dispersal of early life stages with reef currents

In Moorea, alongshore and cross-reef transports are known to affect recruitment of larvae and Millepora in in population connectivity among habitats within a single reef, both in corals (Edmunds et al. 2010; Leichter et al. 2013) and fishes (Beldade et al. 2012; Bernardi et al. 2012). The low connectivity among adjacent habitats indicates that cross-reef transport from the fore reef towards the lagoon (e.g. Hench et al. 2008; Monismith et al. 2013) is not the major factor determining the dispersal of offspring in M. platyphylla at Moorea. In contrast, for some scleractinian corals, this physical process seems to have a strong influence on their recruitment patterns on Moorea’s reefs (Edmunds et al. 2010). However, these conclusions were based only on field surveys, no population genetic approaches or parentage analyses were performed. The dispersal of offspring crossing the reef matrix is therefore a question warranting further investigation in scleractinian species. For fire

corals, cross-reef dispersal and subsequent recruitment patterns could be the result of a continuous Dispersal limitationsand sibling aggregations supply of asexual fragments (Fig. S2, see Dubé et al. unpublished data1). Considering that M. platyphylla heavily relies on clonal reproduction in Moorea, fragmentation process, although more important during period of big swells and storms, can provide a means to connect populations 6 among adjacent habitats rather than sexual reproduction.

In this study, dispersal patterns within local families revealed that currents that run along the reef help to disperse sexual propagules on the fore reef. Such water circulation results in the settlement of larvae parallel to the reef in alignment with the location of their parents. Our data also suggest that gamete and/or larval supply from unsampled colony within the study population (between our transects and habitats, Fig. 6.2) are potentially contributing to the local replenishment. These findings indicate a potential for dispersal at longer distances (> 1km), whereas most of the larvae settled near the parental source (i.e. 0 to 300 m, with high proportion between 0 to 10 m). As previously described in Caribbean reefs (Paris and Cohen 2004), water displacement decreases with increasing depth suggesting that larval behavior, such as swimming or crawling, may enhance local recruitment near the reef crest in deeper waters. For M. platyphylla in Moorea, high proportions of early life stages were reported on the mid slope (Dubé et al. unpublished data2), an exposed reef

135 where wave energy is reduced (Hearn 1999). Overall, our results indicate that the distribution of fire corals in Moorea is strongly influenced by the dispersal of sexual propagules with along-reef currents, a process accentuated in deeper waters, but also by the dispersal of asexual fragments with cross-reef currents.

4.3. Gamete dispersal and fertilization lead to sibling aggregations

In this study, sibship analyses suggested that siblings may complete their pelagic larval phase together. It is commonly assumed that the medusoid, the early life stage during which a fire coral releases its gametes, facilitates fertilization rates through synchronous spawning. This reproductive strategy enables gametes to aggregate at the water surface once they are released (Soong and Cho 1998; Bourmaud et al. 2013) and most likely contributes to the sibling aggregation observed in the study population. This suggests strong selection on early life history traits that minimizes the dilution of gametes. In many broadcast spawning species, the success of fertilization is proximity dependent (Carlon 1999). For fire corals, we observed important variations in the geographical distances between identified parent pairs (i.e. 4 to 900 m) indicating that fertilization can be successful for both nearby and distant parents. Many studies have focused on comparisons between sperm and egg dispersal in reef invertebrates to assess dispersal potential (Pennington 1985; Coma and Lasker 1997; Lasker et al. 2008; Warner et al. 2016). This research demonstrated that sperm dispersal often limits fertilization success, even at the scale of few meters. A previous study on M. platyphylla in southern Japan revealed that males released medusoids a few minutes earlier than females (Soong and Cho 1998). Such asynchrony within a species increases both the probability that sperm will encounter an unfertilized egg and that the eggs will be fertilized immediately after spawning, at which point they will sink to the bottom near the female. This reproductive strategy also contributes to sibling aggregations. Furthermore, successful mating and recruitment was found for parent pairs that were 900 m apart from one another suggesting that sperm dispersal may enhance fertilization success over large distances. Our results indicate that the eggs are most likely dispersed over small distances via reef currents parallel to the reef and are fertilized by sperm, which can disperse over great distances once they are released. Our estimates of offspring dispersal in M. platyphylla highlight their potential for long distance dispersal within a single reef (> 1 km), while we reported that several aspects of their early life history promote local dispersal and sibling

2 Dubé CE et al. Population structure of the hydrocoral M. platyphylla in habitats experiencing different flow regimes. aggregations. Based on a growing body of work on marine dispersal patterns, there is evidence that sexual propagules rarely reach their full dispersal potential (Jones et al. 1999; Swearer et al. 1999; Buston et al. 2012; Iacchei et al. 2013; Pusack et al. 2014). Sexual propagules of Millepora hydrocorals seem to be no exception. Overall, our study supports the current view that self- 136 recruitment may be more common than previously thought (Ayre and Hughes 2000; Gilmour et al. 2009; Saavedra-Sotelo et al. 2011).

4.4. Impact of clonal reproduction on self-recruitment and dispersal

Even though most of the adults were clones, we found that adults with a unique genotype (i.e. only one ramet) contributed equally to self-recruitment than those of clonal genotypes. Previous studies

have shown that colonies that have suffered from stress due to fragmentation may further invest in growth rather than reproduction (Okubo et al. 2005, 2007). Since half of the clonal parents were

smaller than 130 cm², it is reasonable to assume that these fragments may preserve their energy to Millepora in in reach a larger size and to increase their survival. Despite the fact that clonal reproduction only increases local replenishment via the production of new colonies through fragmentation, one could wonder if their propagation is increasing the area over which sexual propagules are dispersed. In plants, the dispersal of seeds increases through clonal propagation and further reduces competition among siblings in the next generation (van Drunen et al. 2015). Our estimates for the dispersal distances were not higher for clonal parents suggesting that Millepora fragments have no better ability for the dispersal of their offspring, as clones of each clonal lineage were in close proximity to one another.

Most of the juveniles sampled were genetically identical to parents. This result confirms that clonal

aggregation of large colonies (i.e. where clones are distributed in patches) can increase local Dispersal limitationsand sibling aggregations replenishment by supplying new recruits through their fragmentation (Highsmith 1982). Despite the fact that large fragments are assumed to have a higher chance of survival (Lirman 2000; Okubo et 6 al. 2007), the large proportion of small fragments (< 20 cm2) observed in this study suggests that they can survive and effectively contribute to local sustainability. Still, these aggregations of clones combined with sibling aggregations and limited dispersal can increase inbreeding in the population due to cross fertilization of genetically related neighbors. Despite all of these reproductive features, the mating between closely related adults is less likely to contribute to the observed population inbreeding, as revealed when the genetic relatedness of all parents sampled and those contributing to self-recruitment were compared. This result suggests that the dispersal of sexual propagules, although limited, is enough to restrict biparental inbreeding. Furthermore, half of local parents relied on multiple breeding, i.e. reproduce with more than two other adult colonies within or without the study area. As in numerous broadcast spawning marine invertebrates (Jonhson and Yund 2007; Lasker et al. 2008; Mokhtar-Jamai et al. 2013; Warner et al. 2016), multiple mating may limit inbreeding in populations (Foerster et al. 2003) and increase the performance and survival of offspring by increasing the genetic diversity in the brood (McLeod and Marshall 2009).

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5. Conclusions

Clonal propagation, self-recruitment and local dispersal of sexual propagules are all features known to reduce levels of genetic diversity. Nonetheless, high self-recruitment involving genetically unrelated parents and high clonal diversity seem to be enough to maintain relatively high levels of genetic diversity in M. platyphylla population. This study confirmed theoretical considerations claiming that self-recruitment is a key factor in stabilizing population dynamics of reef organisms, such as fishes and reef-building corals (Hastings and Botsford 2006). Despite major differences in reproductive strategies, e.g. clonal reproduction and planula larvae, reef fishes and fire corals have similar self-recruitment rates in Moorea with sibling aggregations (Beldade et al. 2012; Bernardi et al. 2012). This recruitment dynamics enables local sustainability and great opportunities to recover from major disturbances, which can occur frequently in coral reef ecosystems such as Moorea Island.

Acknowledgements

We are grateful to Alexandre Mercière for field support and help with statistical analyses. We also thank Franck Lerouvreur and Marc Besson who contributed to the fieldwork and Jeanine Almany for English improvements on the manuscript.

138

Supporting Information

Millepora

in in

Dispersal limitationsand sibling aggregations

Fig. S1 Size frequency distribution of the 3160 colonies sampled in the entire study area. The colony size (cm²) of each colony was estimated from 2D photographs and data were distributed among the size classes based on a logarithm scale.

139

Fig. S2 Spatial distribution and size of parents contributing to self-recruitment within the three belt transects (300 x 10 m) in each of the three surveyed habitats. Each clonal parent is represented by a unique color (N=54) and only the biggest clone was retained for parentage assignments. Each single genotype parent is represented in white (N = 42).

Table S1 Summary statistics for the twelve microsatellite loci analyzed in this study.

Mill07 Mill27 Mill30 Mill47 Mill52 Mill61 Mill67 Mill93 Mill94 Mill95 Mill101 Mill103

N 3148 3157 3154 3145 3159 3160 3132 3142 3159 3157 3157 3154

NA 25 6 4 14 2 2 17 4 5 5 2 4

HO 0.7951 0.710 0.668 0.625 0.000 0.321 0.376 0.362 0.444 0.314 0.468 0.650

HE 0.890 0.642 0.660 0.722 0.192 0.484 0.483 0.417 0.448 0.320 0.488 0.581

FIS 0.107** -0.105 -0.013 0.134** 1.000** 0.337** 0.220** 0.133** 0.008 0.019 0.040* -0.119 Null 0.032 ------0.092 0.079 0.135 0.093 0.087 ------LD 63.64 27.27 36.36 18.18 18.18 36.36 9.09 9.09 54.55 9.09 18.18 27.27

PID 3.8E-1 8.5E-2 1.0E-2 3.1E-3 1.5E-3 3.0E-4 6.5E-6 2.6E-6 4.4E-7 3.0E-7 1.1E- 4.5E-8

PEX 0.12 0.28 0.52 0.58 0.6 0.68 0.89 0.9 0.92 0.92 0.93 0.94

N: number of colonies successfully genotyped; NA: number of alleles; HO: observed heterozygosity; HE: expected heterozygosity; FIS: Weir and Cockerham’s (1984) inbreeding coefficient; Null: frequency of null alleles; LD: percentage of pair of loci showing significant linkage disequilibrium (P < 0.05); PID: Probability of idendity PEX: probability of exclusion given one missing parent genotype. Significant values of FIS are indicated by bold values with * P < 0.05 and ** P < 0.001 and the mean PID and PEX in red represents the additive estimate for all loci.

Table S2 Dispersal distance of offspring that were assigned to parent pairs within the study area and the geographic distance between the mother and father.

Offspring Distance Offspring Parents dispersal (m) parents (m)

MDT3-R4 UPT1-R304 387.63 601.32 MDT3-L143 215.32

MDT3-L118 MDT1-L96 768.65 98.06 MDT1-L185 670.61

MDT1-L229 MDT3-R16 465.14 165.75 UPT2-R267 310.00

UPT3-R168 UPT3-L226 33.90 3.94

UPT3-L209 32.52

MDT1-L95 MDT3-L162 836.40 45.53 MDT3-R81 791.02

MDT1-R153 MDT3-R79 687.50 429.00 UPT2-R153 266.46

UPT3-R253 UPT3-L226 5.21 3.94 UPT3-L209 1.30

BRT2-R34 UPT2-R327 188.28 177.78 BRT2-L48 63.75

UPT2-R99 UPT3-L101 433.31 178.41 MDT3-R7 268.54

MDT1-L113 MDT2-R35 285.53 255.15 MDT1-R102 30.38

UPT1-R99 UPT3-L38 645.35 603.45 BRT1-R41 179.91

MDT2-R38 BRT3-L35 536.17 891.74 MDT1-R30 376.60

MDT1-R81 MDT2-R35 304.51 255.21 MDT1-R102 49.30

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Table S3 Dispersal patterns of juvenile cohorts within four local families (P1, P2, P3 and P4). Several indices are indicated as follows: the number of potential parents (ramet level); the number of juveniles that were full siblings or half siblings; the mean dispersal distance of assigned offspring with standard error (SE), minimum, maximum and median values; and the mean dispersal distance between assigned offspring and their parent with standard error (SE), minimum, maximum and median values. Total dispersal distances were estimated at the genet level, i.e. the biggest parent in each of the local pedigree was retained for dispersal estimates. See Fig. 6.2 for location of parents and assigned offspring in the four local families.

P1 P2 P3 P4 Total

# potential parents 1 1 2 23 27 # full-sibs 2 ------2 # half-sibs 5 5 5 5 20 Mean dispersal distance of assigned offspring (m) 364.47 99.39 426.34 20.37 257.16 SE 326.66 62.96 253.07 12.81 285.84 Min 6.42 10.38 12.62 0.70 0.70 Max 768.25 221.21 881.11 33.18 881.11 Median 132.90 88.59 371.16 24.68 102.92 Mean dispersal distance parent-offspring (m) 333.34 362.61 402.54 29.14 309.00 SE 56.18 81.96 262.75 30.51 223.12 Min 234.76 267.00 110.40 0.07 0.07 Max 400.74 488.21 770.72 104.70 770.72 Median 361.30 341.23 262.48 25.05 309.85

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CHAPTER 7 Intracolonial genotypic variability in highly clonal populations of the hydrocoral M. platyphylla: a glimpse of hope for adaptation

To be submitted as: Dubé CE, Planes S, Zhou Y, Berteaux-Lecellier V, Boissin E. Intracolonial genotypic variability in highly clonal populations of the hydrocoral Millepora platyphylla: a glimpse of hope for adaptation. Scientific Reports

Intracolonial genotypic variability in highly clonal populations of the hydrocoral Millepora platyphylla: a glimpse of hope for adaptation

Caroline E. Dubé1,2,*, Serge Planes1,2, Yuxiang Zhou1, Véronique Berteaux-Lecellier2, Emilie Boissin1,2

Keywords Mosaicism · Chimerism · Microsatellites · Habitat · Reproductive strategies · Morphology

Abstract

In recent years, intracolonial genotypic variability has been described in many colonial marine organisms. This genetic variability can arise from mosaicism (somatic mutations) and/or chimerism (allogenic fusion of genetically distinct individuals). Both processes provide an important source of genetic variation and raise questions on their implications regarding the adaptive capacity of threatened species, such as corals. We investigated intracolonial genotypic variability using microsatellite markers in the fire coral Millepora platyphylla in five habitats in Moorea, French Polynesia. We aimed to determine whether chimerism and mosaicism are related to habitats, reproductive modes (asexual/sexual) and/or colony morphology. Our results show that intracolonial genetic variability is common (31.4%) in M. platyphylla with important variations in its frequency among habitats (0–60%). Mosaicism is responsible for most of the deviating genotypes (87.5%), while chimerism is rarer. Nearly all mosaic colonies were detected in individuals belonging to clonal lineages indicating that asexual reproduction increases the accumulation of somatic mutations, while there was no effect from their morphology. In addition to increasing genotypic diversity in highly clonal organisms, like M. platyphylla, intracolonial genetic variability results in more versatile phenotypic traits. Such variability presents what might well be a potential mechanism for adaptation under environmental changes.

146

1. Introduction

Understanding evolutionary strategies in species largely relies on the concept of individuality, where each individual represents the unit on which selection pressures occur (Williams 1966). An individual is intrinsically defined as reproductive, physiologically autonomous, genetically unique and homogeneous (Michod 1999; Santelices 1999), but there are many studies that question this definition (reviewed in Pineda-Krch and Lehtilä 2004). It has been recognized that for colonies of social insects, physiological unity is not respected because individuals cooperate with others to form a “superorganism”, acting as though the colony was one single individual (Hölldobler and Wilson 2008). Furthermore, asexual reproduction is common in natural populations of countless plants and animals, where individuals are not genetically unique (Avise 2008). The occurrence of genetic heterogeneity within a single individual has also been documented in populations of protists, fungi, plants and animals (Pineda-Krch and Lehtilä 2004) and is now considered a common phenomenon.

There are two main processes that can lead to intra-individual genetic variability: mosaicism and

chimerism. Mosaicism is the outcome of intrinsic genetic changes caused, among other processes, M.platyphylla by somatic mutations (Santelices 2004). In contrast, chimerism originates from allogenic fusion and requires specific environmental conditions and species’ life history traits (Rinkevich and Weissman 1987). Chimerism is much rarer in natural populations due to allorecognition systems. This process mostly occurs in seaweeds and colonial marine organisms with a dispersive pelagic phase, e.g. ypicvariability in sponges, hydroids, bryozoans, ascidians and corals (Sommerfeldt et al. 2003; Rinkevich 2004; Santelices 2004; Gonzalez-Bernat et al. 2013). Mosaicism, by contrast, is a widespread mechanism of many clonal plants and animals with long life-spans (Strassmann and Queller 2004; Reusch and

Boström 2011; van Oppen et al. 2011). Chimeras and mosaic organisms can lead to both Intracolonialgenot evolutionary benefits and disadvantages. Theoretically, intra-individual genetic variability promotes disruptive internal conflicts threatening an organism’s ability to function, e.g. developmental 7 instability (Stebbins 1986; Møller and Swaddle 1997) or intra-individual competition (Chadwick- Furman and Weissman 1995; Folse and Roughgarden 2012). However, the co-occurrence of many different genotypes within an individual also generates additional genotypic variation in populations, which can benefit the potential for adaptation (Frankham 2005; Bonin et al. 2007; Funk et al. 2012). This greater genotypic variability results in more versatile phenotypic traits (e.g. physiological pathways and morphology). Such variability can further increase individual fitness in response to environmental changes through intra-individual selection (e.g. growth rate, reproductive success and survivorship) (Otto and Hastings 1998; Pineda-Krch and Lehtilä 2004; Lakkis et al. 2008, van Oppen et al. 2011). As both chimerism and mosaicism generate intra-individual genetic

147 variation, evaluating the occurrence of these processes in threatened species such as reef-building corals carries important implications for conservation biology.

Coral reefs are increasingly threatened by chronic and acute anthropogenic stressors (Bellwood et al. 2004; Hoegh-Guldberg et al. 2007; Pandolfi et al. 2011; Kuffner et al. 2015). Reef-building corals (e.g. scleractinian. gorgonian and hydrozoan corals) provide much of the habitat framework in reefs. Therefore, their adaptive capacity to increasing sea temperature and ocean acidification in the context of climate change is an issue of much debate. As a consequence of their small populations, poor dispersal abilities, clonality and/or high levels of inbreeding, many coral species are predicted to have low genetic diversity (Kimura 1983; Willi et al. 2006; Frankham et al. 2010). Low genetic variability correlates with limited adaptive potential in the face of environmental change and increases the risk of extinction (Frankman 2005). However, many studies have shown the occurrence of intracolonial genetic variability in scleractinian corals, which provides an additional source of genotypic diversity in their populations (Amar et al. 2008; Puill-Stephan et al. 2009, 2012a; Maier et al. 2012; Schweinsberg et al. 2014, 2015). Due to the lack of germ line segregation in corals, the propagation of somatic mutations within a colony is highly likely (van Oppen et al. 2011), and these mutations are almost certainly passed on to the next generation of gametes (Schweinsberg et al. 2014). Evaluating intracolonial genetic variation (i.e. mosaicism and chimerism) in reef-building species can therefore reveal valuable insights on their adaptive potential under rapid and unpredictable climate change.

Our understanding of intracolonial genetic variability in colonial reef species (e.g. soft corals (Barki et al. 2002), sponges (Blanquer and Uriz 2011) and scleractinian corals (Amar et al. 2008; Schweinsberg et al. 2015; Rinkevich et al. 2016)) has improved over the last decade. However, such information remains unavailable for Millepora hydrocorals (also called fire corals) despite their major contribution to the reef framework in some reef ecosystems (Andréfouët et al. 2014). Millepora species can colonize a wide range of reef habitats through sexual reproduction and colony fragmentation (Lewis 2006). In Moorea, French Polynesia, populations of M. platyphylla displayed differences in sexual / asexual reproduction investment and morphology in response to habitat variability (Dubé et al. unpublished data1). Studies relating the occurrence of intracolonial genotypic variability to habitat specific environmental conditions and reproductive strategies (i.e. at both ramet and genet levels) remain largely unavailable (but see Reusch and Boström 2011; Rinkevich et al. 2016). Here, using microsatellite markers, we investigated the occurrence of chimeras and mosaic colonies within populations of the hydrocoral M. platyphylla in five reef habitats in Moorea, French Polynesia; the mid slope, upper slope, back reef, fringing reef and patch

1Dubé CE et al. Fire coral clones demonstrate phenotypic plasticity among reef habitats.

148 reef (Fig. 7.1). We specifically addressed the following questions: How common is intracolonial genotypic variability in the fire coral M. platyphylla? What is the major process, i.e. mosaicism or chimerism, leading to genetically heterogeneous colonies? Is the level of intracolonial genotypic variability related to a specific habitat, reproductive mode and/or colony morphology?

2. Results M.platyphylla

2.1. Colony reproduction and morphology

All fifteen tested microsatellites had between 2 and 18 alleles (Na in Table S1). Out of the 255 ypicvariability in samples collected from 51 colonies of the hydrocoral M. platyphylla, 65 multilocus genotypes were identified (Table 7.1). Clone mates were detected in almost all reef habitats: two individuals shared the same genotype in the patch reef, fringing reef and back reef and three individuals in the upper

slope (Table 7.1). In the mid slope, all sampled colonies are genetically distinct. However, the larger Intracolonialgenot survey of M. platyphylla colonies (N = 3651) revealed that only one of the 10 colonies sampled in the mid slope was produced through sexual reproduction, while all others belonged to clonal 7 lineages (Table 7.1). Sexually produced colonies were also detected in the patch reef (N = 2) and fringing reef (N = 3), but were absent in the back reef and upper slope (Table 7.1). The sheet tree morphology was dominant in the upper slope (85%) and back reef (75%), while all colonies were massive in nearshore habitats (fringing and patch reef). The growth form of fire coral colonies was highly variable in the mid slope, where the three morphologies were found in equal proportions. Colonies were smaller in the back reef compared to other habitats (Table 7.1).

2.2. Identification of intracolonial genetic variability

Among the 51 tested colonies of fire corals, 16 (31.4%) harboured more than one single genotype (Fig. 7.2). The percentage of genetically heterogeneous colonies was highest in the patch reef

149

(60.0%) and upper slope (46.2%), followed by the fringing reef and mid slope (20.0% each), and finally the back reef, where all colonies were homogeneous (Fig. 7.2 and Table 7.1). In the patch reef and upper slope, where heterogeneous colonies are more common, nearly 70% of the deviating genotypes were caused by a one-step and four- to twelve-step mutations. Two-step and four- to twelve-step mutations contributed equally in creating divergent genotypes in the fringing reef (Fig. 7.3). In the mid slope, deviating genotypes were mostly caused by one-step mutations.

Table 7.1 Sampling pattern among the five surveyed habitats. Number of colonies (# Col), number of replicates within a single colony (# Repl), total number of samples (# Sam), number of detected multilocus genotypes (# Gen), number of clones in sampled colonies (# Clon), percentage of genetically heterogeneous colonies (% Het), number of colonies displaying massive (M), encrusting (E) or sheet tree (ST) morphology and mean colony size are given for the 51 colonies sampled. The number of colonies sampled belonging to a clonal (asexual reproduction) or single genotypes (sexual reproduction) according to an exhaustive sampling and genotyping of M. platyphylla colonies (performed by Dubé et al. unpublished data1) are also shown.

Habitat # Col # Repl # Sam # Gen # Clon % Het Morphology (N) Colony # Clonal # Single M E ST size (cm²) lineages genotypes

Patch 10 5 50 17 1 60.0 10 ------11 272 8 2 Fringing 10 5 50 12 1 20.0 10 ------8 976 7 3 Back 8 5 40 7 1 --- 2 --- 6 4 289 8 --- Upper 13 5 65 17 1 46.2 --- 2 11 29 749 13 --- Mid 10 5 50 12 0 20.0 3 4 3 18 459 9 1

2.3. Clustering analyses

In total, 14 mosaic colonies and 2 chimeras were identified among the 51 tested colonies (Fig. 7.4). In the patch reef, M. platyphylla showed the highest proportion of heterogeneous colonies with 4 mosaics and 2 chimeras, all of which were detected in colonies belonging to clonal lineages. Mosaic colonies differed from the main genotype with a maximum of two loci and one of the mosaics harboured multiple genotypes, i.e. more than two genotypes (colony # 7). Chimeras were detected for two colonies with only one deviant genotype found within each colony. These chimeras had height (colony # 3) or nine (colony # 9) divergent alleles due to one- to twelve-step mutations. In the fringing reef, 2 mosaic colonies were identified; one belonged to a clonal lineage and displayed multiple genotypes (colony # 4), and the other was produced sexually and had only one divergent allele (colony # 9). In the upper slope, 3 of the 6 deviating genotypes were detected within the three colonies sharing the same genotype (clones) and one clone (colony # 13) displayed multiple genotypes. In this latter heterogeneous colony, one genotype was the most common within clones

150 and a second differed by only one allele from the main genotype (as for the three other mosaic colonies). A third genotype had four divergent loci (mostly from one- and two-step mutations) and was shared with one of its clone mates (colonies # 12). A one-step mutation in the highly divergent genotype (M5 in the upper slope bar plot, Fig. 7.4) resulted in another deviating genotype in the third clone (colonies # 11). In the mid slope, 2 mosaic colonies were identified and differed by four

to five loci from the main genotype mostly due to one-step mutations.

M.platyphylla

ypicvariability in

Intracolonialgenot

7 Fig. 7.2 Intracolonial genetic variability detected in M. platyphylla colonies in the five surveyed habitats. Frequency (%) of deviating genotypes caused by chimerism are shown in black; by mosaicism, i.e. somatic mutations, in grey and single genotypes, i.e. most common genotypes, are shown in light grey.

Overall, our results showed that intracolonial genetic variability occurred in all growth forms (Table 7.1). Among the twenty five massive colonies sampled, 9 were genetically heterogeneous (7 mosaics and 2 chimeras). Among the twenty sheet tree colonies and the six encrusting colonies, 6 and 1 mosaic colonies were identified, respectively.

151

This study demonstrates the occurrence of intracolonial genetic variability in M. platyphylla with important variations in its frequency among reef habitats. Genotypes that differed at only one single allele were observed in half of the heterogeneous colonies and most of the deviating genotypes were due to one-step and four- to twelve-step mutations (38.6% and 29.5%, respectively). Most of the deviating genotypes were caused by somatic mutations (87.5% mosaicism). Chimerism also contributed to increase genetic variability within individuals, although restricted to the patch reef habitat. Nearly all mosaic colonies were detected in individuals belonging to clonal lineages indicating that clonal propagation favors the accumulation of somatic mutations. Only one mosaic was identified within a sexually produced colony. Mosaicism was also identified in all of the three morphologies indicating that differences in growth forms do not affect the accumulation of mutations within a colony.

3.1. Pattern of intracolonial genetic variability among reef habitats

The occurrence of intra-individual genotypic diversity was traditionally assumed to be a phenomenon of rare exception (Santelices 2004; Folse and Roughgarden 2012). However, recent

152 investigations have demonstrated that genotypic heterogeneity is widespread in species of

scleractinian corals (Maier et al. 2012; Puill-Stephan et al. 2012a; Schweinsberg et al. 2014, 2015).

M.platyphylla

ypicvariability in

Intracolonialgenot

In this study, our results show that intracolonial genotypic diversity is also common in the fire coral M. platyphylla. Our genotypic data from 51 colonies, all subjected to multiple sampling (five replicates), revealed a high mean proportion of heterogeneous colonies (31.4%). Such occurrence of intracolonial genetic variability was similar to previous studies that focused on branching Acropora corals (38.7%, in Schweinsberg et al. 2015), but much higher when compared to another branching species, Seriatopora hystrix (17.4%, in Maier et al. 2012). In the shallow patch reef, 60.0% of the sampled colonies displayed intracolonial genetic variability, which is much higher than expected based on previous studies (Maier et al. 2012; Schweinsberg et al. 2015).

Fire corals were sampled in five different reef habitats, where colonies were exposed to different environmental conditions, which can potentially influence the rate of somatic mutational divergence within a species (Witte and Stöcklin 2010). Furthermore, colonies were collected at different depths with varying exposure to UV-induced DNA damage, which often derives in somatic mutation (Zvuloni et al. 2011). In coral reefs, this process occurs more frequently in shallow and clear waters, because UV radiation decreases with increasing depth (Lesser 2000). Variations in the proportions of heterogeneous colonies among the five surveyed habitats (0–60%) seemed unrelated to differences in their exposure to solar radiation. In Moorea, fire corals are exposed to high solar irradiance in the back reef and fringing reefs (Lesser and Farrell 2004). However, both of these shallow habitats (< 1 m depth) were characterized by low proportions of heterogeneous colonies (0% and 20%, respectively), similar to those of the mid slope at 13 m depth where irradiance is much lower (20%). Environmental heterogeneity was recognized as a key factor in determining important life history traits of M. platyphylla including the levels of clonality and morphological plasticity (Dubé et al. unpublished data1). These traits can influence the opportunity for mosaicism and chimerism to occur in natural populations of colonial reef organisms (van Oppen et al. 2011; Schweinsberg et al. 2014; Rinkevich et al. 2016). Therefore, determining how sexual / asexual reproduction and intraspecific morphological variation affect the prevalence of intracolonial genetic variability can reveal insights into species’ response to environmental changes.

3.2. Mosaicism

In this study, 14 adult colonies exhibited genotypic variability most likely caused by mosaicism indicating that the accumulation of somatic mutations is a common phenomenon in M. platyphylla in nearly all reef habitats, except in the back reef. The incidence of genetic mosaicism is expected to increase with longevity and size due to a higher number of dividing cells available for mutation (Orive 2001). Therefore, the absence of heterogeneous colonies in the back reef could be related to the higher mortality of ger colonies (Dubé et al. unpublished data2), hence limiting the colony

2 Dubé CE et al. Population structure of the hydrocoral M. platyphylla in habitats experiencing different flow regimes. 154 size (i.e. growth and age). This limitation in size can hamper the potential for the accumulation of mutations in adult corals. However, mosaicism was found in colonies of various sizes (> 800 as high as 63,500 cm2), while some of the largest colonies sampled were genetically homogeneous. In partially clonal organisms, such variability in the accumulation of mutations among size classes can be related to recently small fragmented ramets that might have accumulated mutations before their fragmentation. This highlights the importance of aging clonal lineage (as described in Devlin- Durante et al. 2016) rather than estimating colony size to better understand the mechanisms behind mosaicism in reef-building corals, such as fire corals.

M. platyphylla is also morphologically variable and can either have a massive, encrusting or sheet tree morphotype. In this study, mosaicism was identified in all M. platyphylla growth forms, where most of the mosaics were found in massive and sheet tree morphology. In the upper slope, most of

the colonies grew as isolated vertical blades on encrusting bases (i.e. sheet tree). All six mosaics identified in this habitat were exclusively detected in sheet tree colonies suggesting that this growth form can increase somatic mutations within a colony. In many colonial organisms, such as long-

lived trees and corals, branching growth forms exhibit more deviating genotypes throughout the M.platyphylla entire colony due to mutations that only occur within isolated branches (Whitham and Slobodchikoff 1981; van Oppen et al. 2011). When displaying the unusual sheet tree morphology, Millepora are potentially similar to branching growth forms due to their isolated vertical blades.

However, an additional five sheet tree colonies were identified as genetically homogeneous in the ypicvariability in upper slope and raise questions on whether colony morphology influence mosaicism processes. This uncertainty is strengthened by the high number of mosaics in massive colonies (6 out of 14). Somatic mutations are less likely to occur in such growth forms because polyps are in close contact

with one another and favor intracolonial competition. Competition within a colony is a driving force Intracolonialgenot in lowering genetic variability due to the elimination of alternative mutant cells. Schweinsberg et al. (2015) also demonstrated a conflicting pattern of mosaicism among coral growth forms, whereby 7 highest and lowest proportions of mosaic individuals were both detected in branching species. Whether more extensive studies could verify an increased accumulation of somatic mutations in branching corals (or tubular or sheet) compared to massive or encrusting growth forms remains to be determined. What is certain, however, is that further investigations on intracolonial competition during colony development in fire corals are needed to fully understand the complex interaction between morphological plasticity and intracolonial genetic variability.

In addition, we investigated whether genetic variation caused by mosaicism is associated with one specific reproductive mode, i.e. sexual or asexual reproduction. Thirteen of the 14 mosaic individuals were detected in colonies belonging to a clonal lineage indicating that colony

155 fragmentation can increase genotypic variation, although evolutionary theories predict otherwise. In this study, our sampling design targeted the larger colonies, from which fragmentation was most likely to occur over time. Further investigations on whether asexual reproduction can increase genetic diversity in populations due to mosaicism are needed. Such research requires an explicit experimental design with equal numbers of sexually and asexually produced colonies. Still, in M platyphylla population, all colonies with more than two genotypes (3 of 14 mosaic colonies) were detected in asexually produced colonies and despite our random sampling scheme, three clone mates were collected in the upper slope. These colonies represented five different genotypes, some shared between clones and others found only in one of the three clones. This result indicates that when fire corals spread via colony fragmentation, the fragments inherit somatic mutations from their mother colony, in addition to acquiring their own over time (Schweinsberg et al. 2014). Hence, clonal reproduction can often result in colonies with deviating genotypes of more than four divergent loci, although mosaicism is commonly thought to induce divergent genotypes at one or two loci (Orive 2001). Overall, this study reveals that mosaicism is a very promising strategy to increase genetic variability in M. platyphylla, a species that mostly relies on colony fragmentation for colonization and population persistence (Dubé et al. unpublished data1).

3.3. Chimerism

In this study, a low proportion of chimeras was identified in fire coral colonies (2 out of 51 colonies sampled, i.e. 3.9%), which is similar to earlier reports for scleractinian corals (from 1.3 to 4.5% depending on the coral species, e.g. Maier et al. 2012; Schweinsberg et al. 2015). This result further confirms that chimeric fusion between conspecific are rare events in dynamic environments such as coral reefs. Here, two chimeras were detected in adults that belong to two distinct clonal lineages in the patch reef, where M. platyphylla colonies primarily reproduce through fragmentation (Dubé et al. unpublished data1). Despite low investment in sexual reproduction, fire corals have limited dispersal abilities and are often aggregated due to the co-settlement of their larvae (Dubé et al. unpublished data3). In Moorea, fusion between siblings is likely to occur as recruits settle together and grow in proximity on the reef (Dubé et al. unpublished data3). The fusion of siblings could be related to a low conspecific acceptance threshold and/or a delay in allorecognition maturation for Millepora hydrocorals, as described in some hermatypic corals (Amar et al. 2008; Puill-Stephan et al. 2012a). Puill-Stephan et al. (2012b) demonstrated that high levels of relatedness between juvenile corals correlate with late maturation of allorecognition. Such delay in the recognition system can increase opportunities for chimeric fusion between adjacent recruits, which allows a rapid growth during early development (Pineda-Krch and Lehtila 2004; Santelices et al. 2010).

3 Dubé CE et al. Dispersal limitations and sibling aggregations in Millepora hydrocorals. 156

3.4. Evolutionary and ecological implications

Considering the common occurrence of mosaicism in M. platyphylla, this process might have important implications for adaptation as this species heavily relies on clonal reproduction in Moorea. Clonal genets can accumulate allelic mutations that become functionally variable under strong selection pressures and these mutations can be spread in the population via both sexual and asexual reproduction (Lashai et al. 2003; Pouchkina-Stantcheve et al. 2007). Such mutation dynamics can result into more versatile phenotypic traits and potentially compensate the reduced genotypic diversity usually associated with clonal reproduction (Sniegowski and Gerrish 2010). However, further investigations are needed to ensure that M. platyphylla have no clear separation of somatic and germ cells, and that mutations can be spread via the next sexual generation. Even if chimerism is less common is the study population, this process also contribute in creating novel

genotypic diversity required for adaptation. It is thus imperative to expand studies of intracolonial genetic variability based on neutral microsatellite markers to include functional genes that underpin coral physiology, which often correlates with adaptive advantages.

4. Methods M.platyphylla

4.1. Sampling

Between April and December 2013 field surveys were conducted on the north shore of Moorea, ypicvariability in French Polynesia, at three different locations (Tiahura, Papetoai and Temae) across five reef habitats; two in the fore reef: mid slope (13 m depth) and upper slope (6 m depth), and three in the lagoon (< 1 m depth): back reef, fringing reef and patch reef (Fig. 7.1). From these surveys a total

of 3651 colonies of M. platyphylla were collected, whereby 51 colonies were selected in the five Intracolonialgenot habitats to determine whether intracolonial genetic variability is a common phenomenon in fire corals (Table 7.1). All fire coral colonies were subjected to a multiple sampling, where five tissue 7 samples were taken from each colony with four samples taken from the edges of the colony and one additional from the middle. This sampling pattern was previously used to detect genetically heterogeneous individuals in some coral species (Schweinsberg et al. 2015). All colonies had a minimum size of 100 cm to ensure sexual maturity and showed no visual evidence of fusion between two or more individuals (i.e. various morphologies and colors within a single colony, and no interaction zone). To determine whether the colony morphology influences the prevalence of intracolonial genetic variability, we classified each colony as one of these three morphologies: 1) massive: solid colonies, roughly hemispherical in shape, 2) encrusting: thin colonies growing against the substratum or 3) sheet tree: encrusting bases with vertical bladelike outgrowths (see Jackson 1979). We also estimated mean colony size (cm²) from 2D photographs of each colony

157 sampled using ImageJ 1.4f software (Abràmoff et al. 2004). A total of 255 small fragments of tissue-covered skeleton (< 2 cm3) were sampled and preserved in 80% ethanol and stored at –20 °C until DNA extraction.

4.2. Microsatellite genotyping

Samples were incubated at 55 ºC for 1 hr in 450 µL of digest buffer with proteinase K (QIAGEN, Hilden, Germany). Genomic DNA was extracted using a QIAxtractor automated genomic DNA extraction instrument, according to manufacturer’s instructions. Samples were amplified and genotyped at 15 microsatellite loci shown to be coral-specific and polymorphic in M. platyphylla (Heckenhauer et al. 2014; Dubé et al. in revision) (Table S1). All loci were combined in three multiplex panels according to their size range and primer annealing temperature. PCRs were performed in a final volume of 10 µL including 5 µL Type-it Multiplex PCR Master Mix (1x) (QIAGEN, Hilden, Germany), 3 µL RNase-free water, 1 µL primers (2 µM of fluorescently labelled forward primer – G5 dye set including 6-FAM, VIC, NED and PET – and reverse primer diluted in TE buffer) and 1 µL of template (10 to 50 ng.µL-1). The PCR protocol included an initial denaturing step of 5 min at 95 ºC, followed by 40 cycles of 30 sec at 95 ºC, 90 sec at 57–63 ºC, and 30 sec at 72 ºC, and by a final 30 min elongation step at 60 ºC. Samples were analyzed on a 3730 sequencer and scored manually using GENEMAPPER (Applied Biosystems, Foster City, CA). Samples that were ambiguous in their scoring were re-amplified and re-scored, as for missing alleles. Alleles were individually re-scored by a second and third person to ensure accurate genotyping. All peak profiles that were faint or ambiguous (i.e. multiple peaks) were considered as missing data and only samples with no more than two missing loci were retained for further genetic analyses. Control for the presence of null alleles and large allele dropout were performed with MICRO-CHECKER (van Oosterhout et al. 2004).

4.3. Molecular analyses

Multilocus genotypes were produced for each sample and compared within each colony to detect the occurrence of intracolonial genetic diversity. Multilocus genotypes were also compared between colonies using GENALEX (Peakall and Smouse 2006) to identify clone mates among the sampled fire coral colonies (Table 7.1). Based on genotypic data acquired from 3651 colonies of M. platyphylla that were collected using an exhaustive sampling at the same locations within the five surveyed habitats, colonies that belonged to a clonal lineage (genet with multiple ramets) and those produced sexually (genet with single ramet) were identified (Table 1, Dubé et al. unpublished data1). For the 51 sampled colonies of M. platyphylla that were subjected to multiple samplings, the most common genotype was retained as the main genotype (i.e. single genotype). All additional 158 genotypes within the same colony could result either from mosaicism (somatic mutations) or chimerism (fusion of two or more individuals). In previous studies, mosaic individuals were identified based on the number of divergent loci from the main genotype, i.e. only one or two loci (as in Puill-Stephan et al. 2012a; Schweinsberg et al. 2014) since mutations are rare events (Orive 2001). In contrast, a greater number of locus and allelic differences was expected in chimeras, i.e. when two genetically distinct colonies merged. Based on the stepwise mutation model of microsatellite markers (Selkoe and Toonen 2006), we estimated the number of repeat units that were added or subtracted during a mutation event. Divergent alleles from the main genotype caused by multiple mutation step and large allele differences are most likely due to chimerism rather than somatic mutations. The size of the mutation step (in repeat units) were identified over all loci for each deviating genotype and averaged per habitat (percentage of mutational-step). Bayesian clustering analyses have been used to identify chimeras based on their cluster assignment probability, i.e. chimeras have to include genotypes that differ from the main genotype and are belonging to a different cluster (Maier et al. 2012; Schweinsberg et al. 2015).

Here, mosaic individuals and chimeras were identified based on a Bayesian clustering analysis M.platyphylla using STRUCTURE (Pritchard et al. 2000). Clustering analyses were performed to ensure non- biased detection of deviating genotypes following the protocol used in Schweinsberg et al. 2015. Initial STRUCTURE runs were used to determine the most likely number of clusters (K) in each population of M. platyphylla, i.e. within the five reef habitats: mid slope, upper slope, back reef, ypicvariability in fringing reef and patch reef. Runs were performed with the default setting, a burn-in period of 50 000, 50 000 MCMC repeats and 10 iterations per K. The results were uploaded to STRUCTURE HARVESTER (Earl and vonHoldt 2011) and the most likely K was retained for a second run in

STRUCTURE with a burn-in period of 500 000, 500 000 MCMC repeats, 10 iterations and uniform Intracolonialgenot prior setting. The results were once more uploaded to STRUCTURE HARVESTER and the resulting merge dataset was analyzed to estimate cluster assignment. Following the framework of 7 Schweinsberg et al. 2015, deviating genotypes that differed with more than 60% in their cluster assignment probability compared to the most common colony genotypes were identified as chimeras. All other deviating genotypes were considered as mosaic colonies.

Acknowledgements

We are grateful to Alexandre Mercière who contributed to sample collection and Jeanine Almany for English improvements on the manuscript. C.E.D. is supported by a graduate scholarship from the Fonds Québécois de Recherche sur la Nature et les Technologies. E.B. is supported by European Marie Curie Postdoctoral fellowship MC-CIG-618480.

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Supporting Information

Table S1 Summary of the fifteen microsatellite locus diversity in M. platyphylla. TA, Annealing temperature (°C); Na, Number of alleles per locus.

Locus TA Size (bp) Developed name Motif (°C) Na range by

Mill07 (CA)16 57 18 92–130 Dubé et al. in press

Mill27 (TG)10 57 5 140–148 Dubé et al. in press

Mill30 (TG)11 57 4 203–211 Dubé et al. in press

Mill47 (GA)8 57 4 114–124 Dubé et al. in press

Mill52 (AC)9 63 3 94–98 Dubé et al. in press

Mill67 (TAGA)6 63 6 275–345 Dubé et al. in press

Mill93 (TGT)7 57 2 94–100 Dubé et al. in press

Mill94 (GAA)7 57 4 134–143 Dubé et al. in press

Mill95 (TTG)7 63 4 123–138 Dubé et al. in press

Mill101 (CAA)6 57 2 132–135 Dubé et al. in press

Mill103 (AG)7 57 6 94–114 Dubé et al. in press

Mill_D01 (ACCG)9 (ACTG)3 57 4 169–197 Heckenhauer et al. 2014

Mill_D04 (AAAT)6 57 4 152–166 Heckenhauer et al. 2014

Mill_D06 (AAT)9 63 13 136–187 Heckenhauer et al. 2014

Mill_D08 (GAT)11 63 3 97–118 Heckenhauer et al. 2014

160

M.platyphylla

ypicvariability in

Intracolonialgenot

161

162

CHAPTER 8

Conclusions and New Directions

What can we learn from population genetic approaches on the adaptive potential of Millepora hydrocorals to future environmental changes? Are they ‘winners’ or ‘losers’?

General discussion

Deepening our understanding of genetic diversity patterns in species is crucial for ecological and evolutionary studies, and carries important implications for conservation biology. The capacity of reef organisms to survive is partially related to their degree of genetic variation, where low levels of diversity may limit adaptation to novel selective pressures (Frankham 2005; Barrett and Schluter 2008; Hoffmann and Sgrò 2011). The degree of genetic variation in populations is highly influenced by a number of factors that are associated with life history traits, e.g. gene flow, genetic drift and mutation (Gaggiotti et al. 2009). The worldwide degradation of coral reefs has prompted a surge in understanding species’ life history and population genetic structure in response to local and global changes. As coral reefs are heterogeneous ecosystems, different environmental and habitat conditions may impose divergent selection pressures, such that populations evolve differences in morphology, reproductive modes and dispersal abilities (Sanford and Kelly 2011; Darling et al. 2012). Evaluating such differences in life history traits under contrasting local environmental conditions offer a glimpse into how such populations may survive and adapt to expected environmental changes. In conservation management, there is a particular concern regarding the vulnerability of marginal reefs, where sexual reproduction might be impeded due to their isolation, often resulting in lowered genetic diversity and adaptation potential (Hennige et al. 2010; Goodkin et al. 2011). Studying life history of keystone species in environments subjected to natural (cyclones, Acanthaster outbreaks) and anthropogenic disturbances (run off, sewages), such as Moorea, provide an example from which to comprehend population persistence in response to environmental changes.

In this thesis, we have provided an improved understanding of the life history of Millepora hydrocorals, a conspicuous component of coral reef ecosystems worldwide (Lewis 1989, 2006). Based on an exhaustive sampling of more than 3600 colonies collected across various reef habitats at Moorea, we investigated reproductive modes (both sexual and clonal) and growth strategies (allogenic fusion, stolonal spreading and morphological plasticity) in M. platyphylla populations, as well as the occurrence of somatic mutations within a single colony. Using different population genetic approaches, new ecological and evolutionary perspectives have enabled insights into how the complex interaction between high clonal propagation, self-seeding and morphological plasticity, is making milleporids efficient competitors on coral reefs, but also into how these life history strategies maintain a relatively high level of genotypic diversity required for adaptation.

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1. Life history of Millepora hydrocorals: Are they ‘winners’?

In this thesis, we sought for possible differences in colony size distributions, morphologies and recruitment dynamics among various reef habitats to improve the knowledge and understanding of ecological and biological processes governing the population structure of M. platyphylla. We have demonstrated that fire corals colonized a wide range of habitats in Moorea reflecting its ability to adapt and survive in a large variety of environmental settings. Marked differences in population structure of fire corals in two common reef environments, the lagoon and fore reef, have illustrated the importance of environmental conditions in driving population dynamic processes. Such results underpin the urge of developing new molecular markers to evaluate several aspects of the M. platyphylla life history. Different population genetic approaches based on newly developed microsatellite markers were performed to determine how such populations can persist under rapid and unpredictable environmental changes.

1.1. High clonal propagation of locally adapted offspring

In the course of this thesis, we have demonstrated that M. platyphylla displays a wide range of strategies to ensure its survival by maximizing the acquisition of local resources. Our genetic data indicated that fragmentation is the dominant reproductive process generating the high abundance of fire corals on Moorea’s reefs (80% of colonies were clones). Even small recruits were having multilocus genotypes identical to adults and were often positioned below the reef substratum, i.e. frequently on branches of dead coral colonies or side of crevices. These observations suggest that the successful recruitment of clones may be the result of other clonal reproduction processes, e.g. asexual planula larvae, because asexual fragments are less likely to re-attach on such inclined substrate. The release of ameiotic planula larvae was reported in a great number of coral species (Harrison 2011), where larval behavior allows the settlement of a new individual characterized by its mother genotype (clone mates). However, such clonal reproductive strategy has never been described for the Millepora genus and requires further investigations. While we cannot be certain that M. platyphylla reproduces asexually only through fragmentation, determining the Conclusionsand Directions New environmental setting under which clonal reproduction is favored and maintained remains a difficult task. 8

A review of empirical studies in plants showed that clonality is often associated with rare taxa and prevails in populations of marginal environments, such as those located at the margin of species’ geographical distribution (Silvertown 2008). Clonal reproduction is also thought to hamper evolutionary potential because it prevents genetic recombination and leads to the selection of particularly well locally adapted clones, thus reducing genotypic diversity (Halkett et al. 2005).

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Furthermore, the overall population fitness is also predicted to be lowered in highly clonal populations due to the accumulation and spread of deleterious somatic mutations (Lynch and Gabriel 1990). Hence, clonal reproduction is often seen as an evolutionary dead-end and is regarded as a prolonged route to extinction for some marginal populations (Honnay and Bossuyt 2005; Silvertown 2008). Therefore, there was evidence that M. platyphylla in Moorea, at the edge of its distribution range (Randall and Cheng 1984), should undergo reduced levels of genetic diversity due to high clonal reproduction and reduced gene flow, both imperiling its ability for adaptation to environmental changes. Nonetheless, we have demonstrated that even a low investment in sexual reproduction is sufficient to maintain a relatively high level of genotypic diversity in M. platyphylla population in Moorea (He = 0.54, see Table S1), where a similar pattern was reported for the partially clonal scleractinian coral Pocillopora damicornis (0.50–0.53, see Adjeroud et al. 2014).

In Moorea, fire corals are sustained by a high degree of self-seeding suggesting that despite low gene flow, genetically diverse and locally adapted recruits can successfully establish high local population abundance via their subsequent growth, survival and fragmentation (as described in Bengtsson 2003). However, such populations are predicted to be vulnerable to severe disturbances owing to their isolation from potential source reefs and are often associated with increased extinction risks (Harrison and Wallace 1990; Harrison and Booth 2007). A high potential for gene flow and connectivity has been revealed among islands of the Society Archipelago in French Polynesia for some scleractinian species (i.e. Moorea, Raiatea, Taha’a and Tahiti) (Adjeroud et al. 2014). Our local sampling design cannot confirm such dispersal patterns of sexual propagules in milleporids on a regional scale. Nevertheless, preliminary results from samples of M. platyphylla collected in several islands in French Polynesia revealed significant genetic differentiation among some Archipelagos (Marquesas, Austral, Society and Tuamotu), highlighting the importance of self- recruitment processes in the population sustainability. Despite all of that, there is evidence that high clonal reproduction is an efficient means to expand populations locally in marginal reefs, but it remains unknown whether such populations retain sufficient functional genetic diversity (i.e. the degree to which clonal diversity translates into functional phenotypes) to adapt to changing environments. In the light of our results, it seems that the combination of high clonal propagation and early life history traits, which promote high self-recruitment, can generate sufficient clonal genotype diversity, such that populations can evolve through divergent selection pressures induced by environmental changes. Even though investment in clonal reproduction varied in response to habitat specific conditions, similar levels of genetic diversity were maintained between habitats (Table S1). Larval and asexual fragments dispersal among reef habitats lead to a genetically homogenous population.

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1.2. Fusion and mutation: Additional source of genetic diversity

There is evidence that populations reproducing primarily via asexual reproduction possess highly dynamic and adaptive genomes (Lashai et al. 2003) and maintain high levels of allelic diversity within individual (Balloux et al. 2003). In this study, we have demonstrated that M. platyphylla can accumulate somatic mutations while growing with a high potential of spreading these mutations in the population via colony fragmentation. Many cnidarians have no clear separation of somatic and germ cells, which ensure the passage of somatic mutations throughout the entire colony to the next generation via their gametes (Extavour and Akam 2003; Seipel et al. 2004; Watanabe et al. 2009). Such life history strategies enhance the genetic variability within colonies and their consecutive generations, but also have important implications for their adaptability (van Oppen et al. 2011). However, a recent study has shown conclusive evidence of germline segregation in the coral Orbicella faveolata (Barfield et al. 2016). The lack of segregated germline has been reported in hydrozoans (Seipel et al. 2004), while there is no evidence for this phenomenon in fire corals. In Millepora hydrocorals, sexual reproduction occurs via the development of medusoids (i.e. modified medusa) via asexual budding from the lateral wall of polyps in cavities called ampullae (Lewis 1991). More information is needed to better understand how the ampullae develop to confirm whether these cnidarians have the potential to transfer somatic mutations in their gametes, located in the medusoids. Nonetheless, such mutations result in genetically heterogeneous colonies and may have important ecological and evolutionary implications as they generate additional genotypic

variation required for adaptation. Based on the common occurrence of intracolonial genetic variability in M. platyphylla population in Moorea, it is reasonable to suspect that clonal genotypes may accumulate allelic mutations that become functionally variable under strong selection pressures (Lashai et al. 2003; Pouchkina-Stantcheve et al. 2007). Such mutation dynamics can result into more versatile phenotypic traits in populations and potentially compensate the reduced genotypic diversity usually associated with clonal reproduction (Sniegowski and Gerrish 2010). Although chimerism was less common in fire corals, sibling aggregations of early life stages facilitate fusion of two or more settling recruits and also contribute in generating novel genetic diversity. Because Conclusionsand Directions New M. platyphylla is a long-lived organism mostly relying on fragmentation for local replenishment with high self-seeding and sibling aggregations on Moorea’s reefs, intracolonial genetic variability 8 is most likely a key process in population persistence by supplying additional genotypic diversity (Fig. 8.1).

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Fig. 8.1 Summary of life history strategies in M. platyphylla in Moorea, French Polynesia. M. platyphylla heavily relies on asexual reproduction through fragmentation for local replenishment (80% of the colonies are clones), allowing population growth and the persistence of a genotype over time when sexual reproduction is impeded. Although only 20% of the colonies of M. platyphylla are produced through sexual reproduction, its population is sustained via a high contribution of self-recruitment (58% of juveniles are self-recruits). Mosaicism and chimerism also contribute in creating novel genotypic diversity in the population.

1.3. Morphological plasticity: A means to promote clonal reproduction

Although genetic diversity is often linked to ecological functioning and adaptive capacity, population can also evolve within a single generation due to plasticity or natural selection altering phenotypic traits, such as changes in behavior, physiology and morphology (Reed et al. 2011). Phenotypic plasticity provides another means for population persistence and understanding such phenotypic response to different selection pressures is a major challenge in evolutionary biology. Here, we have demonstrated the occurrence of phenotypic plasticity in M. platyphylla, where a single genotype can produce multiple morphologies in response to habitat specific conditions. Such phenotypic changes occurring during the development of the colony enable a rapid response to local environmental conditions compared to genetic changes (Auld et al. 2009). We found that M. platyphylla clones have a vulnerable morphology that increases colony fragmentation in the upper slope. Such phenotypic response can increase mortality of both the colony subjected to breakage

168 and coral fragments. This phenotype potentially reduces colony fitness and should be unsuited for highly dynamic environments. Even so, our results have shown that enough fragments are re- attaching to the reef substratum indicating that this high risk / reward morphological strategy promotes self-replenishment of a marginal population through clonal reproduction. In addition, colonies that have suffered from stress related to fragmentation can further invest their energy to reach larger size and increase their survival (Okubo et al. 2005, 2007), and further contribute to population growth via their own fragmentation and release of sexual propagules. This complex interaction between morphological changes and local replenishment highlights the importance of determining limits and trade-off to phenotypic plasticity and evolutionary potential in traits affecting survival, reproduction and dispersal. Nonetheless, more information on physiological plasticity associated to different morphologies and genotypes is needed to fully understand the limits of phenotypic plasticity in the adaptive response of fire corals to environmental changes. For instance, reciprocal transplant experiments of clonal genets can provide important information to determine whether these morphological changes are reversible in response to contrasting environments.

1.4. Millepora platyphylla: A competitive and resilient species

Overall, this work has demonstrated the importance of gathering genotypic and phenotypic data to produce a complete picture of ecological and evolutionary strategies involved in the population

persistence of Millepora hydrocorals. Self-seeding and intracolonial genetic variability successfully establish diverse genotypes within M. platyphylla population, while colony fragmentation contributes effectively to population growth, where a high number of clonal genotypes have the potential for phenotypic plasticity in response to environmental changes (Fig. 8.2). Our evaluation of the life history of M. platyphylla suggests a competitive strategy, based on the production of few locally produced sexual recruits and their ability of reaching large sizes (fusion and stolonal spreading), which allows them to preempt space on coral reefs, but also brought evidence of high

susceptibility to fragmentation. This life strategy is well suited for population persistence in the Conclusionsand Directions New absence of sexual recruitment, but can be risky in unstable environments (Courchamp et al. 1999). Yet, M. platyphylla populations in Moorea have withstood severe disturbances, e.g. Acanthaster outbreaks and cyclones. Their recovery is foremost sustained by the rapid growth of remnant 8 colonies, mostly those encrusting, and the subsequent local recruitment via both sexual and asexual reproduction. There is evidence that fire corals may ‘win’ under pressure from environmental changes, although more information on how they respond to bleaching events is needed, as Millepora species have been reported to be highly vulnerable to thermal stress in other reefs (Marshall and Baird 2000). Nevertheless, the life history of M. platyphylla is most likely

169

170 contributing to its colonization success in various reef environments in French Polynesia, where only this species of Millepora was reported in this geographic region. M. platyphylla is also characterized by one of the widest range of distribution in the entire Indo-Pacific region within the Millepora genus (Randall and Cheng 1984), although similar to the branching M. intricata. Evaluating the life history of other Millepora species with different growth forms will enable to determine whether these strategies are unique to M. platyphylla or spread within the Millepora genus.

1.5. Is Millepora a good model to predict adaptation of reef corals?

Using M. platyphylla as a model species, we have made great progress in understanding the life history of Millepora hydrocorals, an understudied genus of calcifying species. It has been argued at many occasions when discussing the results of this PhD thesis that Millepora is not a good model to evaluate ecological and evolutionary strategies that influence the ability of reef-building corals to adapt to expected climate change, as for predicting long-term consequences on reef community dynamics. Predicting how coral reef ecosystems will respond to the inevitable increase of human activities and environmental changes remains a difficult task. In recent decades, declines in scleractinian coral cover have challenged their role as key ecosystem engineers of coral reefs (Bellwood et al. 2004; Bruno and Selig 2007; De’ath et al. 2012). Assuming rising sea temperatures and increased ocean acidification, climate change can interfere with a range of key processes in the life history of corals, including growth, calcification, development, reproduction and behavior (Orr et al. 2005; Kroeker et al. 2010). Despite the acclimatization and genetic adaptation of reef corals (Hoegh-Guldberg et al. 2007), such persistent physical and chemical conditions can lead to shifts in reef community composition. This phenomenon has already been reported in many reefs, where alternative organisms are dominating reef assemblages (reviewed in Norström et al. 2009). Only few studies have considered hydrocorals in ecological monitoring of coral reefs (Marshall and Baird 2000; Glynn et al. 2001; Brown and Edmunds 2013). For instance, M. platyphylla can dominate some reefs in the Indo-Pacific region (Andréfoüet et al. 2014) and also contribute to the survival of corals during Acanthaster outbreaks as this corallivorous predator tends to avoid Millepora species Conclusionsand Directions New (Lewis 2006; Kayal and Kayal 2016). Therefore, it is crucial to gain insights into how populations of this keystone species can adapt and survive in the face of climate change and other natural and 8 anthropogenic disturbances. In this thesis, we have demonstrated that M. platyphylla possesses a great variety of life history strategies that favor a high degree of genetic diversity and plasticity enabling this species to persist throughout environmental variations. Consequently, this species may become one of the major components in some modern reefs and requires more considering in ecological monitoring.

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Because M. platyphylla is a long-lived species relaying heavily on fragmentation for local persistence, estimating the age of a clonal lineage (i.e. time since a clone’s sexual origin) rather than its size could provide important information to predict the resilience of this species. Although many genetic approaches were used for determining age of multicellular organisms, such as the incorporation of environmental signals into tissues (Prouty et al. 2011), telomere length (Barrett et al. 2013) and phenotypic changes (Caspari and Lee 2004), age determination remains challenging in clonal organisms. Devlin-Durante and colleagues (2016) have recently demonstrated that the accumulation of somatic mutations within a clone correlates with genet age. Such technique based on the genetic divergence of microsatellite markers could be used to estimate the age of the 328 clonal lineages identified in this thesis. Such data are important to relate investment in clonal reproduction to environmental disturbances, such as El Niño events and cyclones, and also provide further insights into the history of M. platyphylla spread on Moorea’s reefs.

New directions

In order to make further progress in evaluating adaptive potential to environmental changes it is necessary to study how local environmental conditions may shape the microbial community (e.g. bacteria and Symbiodinium algae) associated to fire corals as they ensure essential functions in maintaining host’ homeostasis. Additionally, further investigations on epigenetic regulation of phenotypic variation are crucial to predict adaptation to environmental changes as this process plays a key role in gene regulation and expression. Such pending questions require extending our work based on neutral microsatellite markers to functional genes underlying fire coral physiology in order to unravel adaptive advantages of both symbiotic microbial organisms and epigenetic regulation processes.

Predicting how populations of Millepora hydrocorals can survive and adapt under ongoing environmental changes requires to determine the scope of genetic, epigenetic and physiological adaptation processes (Brown and Cossins 2011; Collins et al. 2013). A major source of variation in coral physiology and tolerance to environmental changes result from their association with symbiotic photosynthetic algae (Symbiodinium spp., e.g. Berkelmans 2002; Howells et al. 2016) and other microbial organisms, such as bacteria (Rosenberg et al. 2007; Kelly et al. 2014; Roder et al. 2015). Symbiodinium algae derive inorganic compounds from the host for photosynthesis and provide phototrophic energy required for the metabolic requirements of the coral host (Muscatine 1990). In corals, there are hundreds of Symbiodinium species comprised in nine evolutionary lineages (‘clades’) with differences in their function and performance (Blackall et al. 2015). The assemblage of Symbiodinium clades can affect growth (Little et al. 2004), disease susceptibility

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(Correa et al. 2009; Littman et al. 2010) and thermal tolerance of coral hosts (Rowan 2004; Berkelmans and van Oppen 2006; Howells et al. 2012). Although not much is known with respect to Symbiodinium composition in hydrocorals, we performed preliminary tests in healthy and partially bleached colonies of M. platyphylla via PCRs amplification of the 28S gene for four clades (A, B, C and D). Clade A and D were present in both healthy and partially bleached colonies, while the clade C was present only in the healthy ones. In scleractinian corals, there is also evidence of temporal changes in the relative abundance of sensitive or more tolerant symbiont that correlate with distinct environmental settings, also referred to as ‘shuffling’ (reviewed in Baker 2003). Such variations in response to environmental changes or stress events are often accompanied by physiological changes of the coral host (Berkelmans and van Oppen 2006), a means for adaptive plasticity (Kitano and Oda 2006). Furthermore, microbes also provide critical functions within the host, including the passage and fixation of nitrogen and carbon, the production of secondary metabolites and antimicrobial compounds, mucus production and acquisition of nutrients (Knowlton and Rohwer 2003; Lesser et al. 2007; Wegley et al. 2007; Raina et al. 2009; Fiore et al. 2010). Considering that microbes confer immunity and support host metabolic demands it is crucial to gather more information into how coral-associated microbial communities are impacted by variation in environmental conditions, which can further benefit our understanding of acclimatization process in coral reefs.

Recent advancements in DNA sequencing technology have enabled a new understanding of the role

of symbiotic microorganisms (i.e. microbiome) in the adaptive response of corals to environmental changes (Pedrόs-Aliό 2006; Bik et al. 2012). Many studies have demonstrated that changes in the microbiome assembly contribute to phenotypic plasticity (Reshef et al. 2006; Jones et al. 2008; Lajeunesse et al. 2009). As reef-building corals must acclimatize and adapt to rapid and unpredictable environmental changes, such phenotypic plasticity facilitates a more rapid response to environmental change than possible through natural selection and likely a key process for the persistence of many species (Charmantier et al. 2008; Chevin et al. 2010). However, plasticity is

constrained by host-specific affinities for particular types of Symbiodinium and microbes and by the Conclusionsand Directions New environmental availability of microorganisms diversity (Manning and Gates 2008; Abrego et al. 2009). Furthermore, symbiotic partners can also influence the adaptive capacity of corals through 8 physiological and genetic adaptation to prevailing conditions (Robison and Warner 2006; Howells et al. 2012). To date, the flexibility of the association between corals and microorganisms has been demonstrated using transplant experiments and/or coral colonies exposed to contrasting environmental conditions (Bongaerts et al 2010; Correa and Baker 2011), while it has never been demonstrated among clones. In this thesis, we have identified 57 clonal lineages with clones exposed to distinct environmental conditions enabling in a future work to test for the first time

173 whether host genotype limits phenotypic plasticity through the selection of particular Symbiodinium types and other microorganisms such as microbes. Such a study will improve our understanding of co-evolution processes among the host and its symbiotic microbial community by testing the following hypotheses: 1) the microbiome composition varies among clones of a clonal lineage exposed to various environmental conditions (adaptive plasticity); 2) all clones of the same clonal lineage exposed to various environmental conditions are characterized by a unique microbiome composition (genetic adaptation) and 3) all clonal lineages exposed to the same environmental conditions are characterized by a unique microbiome composition (co-speciation, ecotype) (Fig. 8.2).

Furthermore, phenotypic changes often involve modifications in gene expression and require further investigations. Using transplant experiment, Barshis and colleagues (2010) have demonstrated that host genotype limits protein expression in the coral Porites lobata, thus limiting phenotypic response to environmental changes. Investigating gene regulation and expression in clonal genotypes in different reef habitats provides a unique opportunity to assess these questions in natural populations. At last, epigenetic mechanisms are largely recognized as one of the principal mediators of gene expression and adaptive plasticity (Duncan et al. 2014). Dimond and Roberts (2016) have demonstrated that genes are differentially expressed in coral species in response to thermal stress and ocean acidification due to lower levels of DNA methylation. Because this epigenetic process can be influenced by the environment, further investigations of DNA methylation are needed to get the whole picture on the ability of M. platyphylla to acclimatize and adapt to environmental change.

Conclusions

Much of our understanding about the response of coral reef organisms to environmental changes has focused on acclimatization via phenotypic plasticity and the scope for genetic adaptation. In highly clonal populations, genetic adaptation through selective pressures is expected to be much slower due to low genetic recombination rates. Using both genetic and phenotypic data, we have demonstrated variability in genotypic diversity and phenotypic traits within populations of M. platyphylla. As variability within populations is the source of adaptive changes, genetic and phenotypic adaptation in clonal organisms, such as fire corals, is likely to be greater than some have anticipated. We might also expect to see high variability in gene expression, even within hydrocoral genets in different habitats, and considerable phenotypic plasticity at the physiological level due to epigenetic regulation and associated microbial communities. Using knowledge of the life history of M. platyphylla, we can state that this species is heavily fit to ‘win’ under pressure from multiple

174 stressors and is a good model to predict resilience of reef species due to its wide range of effective

strategies involved in local population maintenance.

Conclusionsand Directions New

175

Table S1 Index of genetic diversity in Millepora platyphylla in Moorea, French Polunesia.

Habitats Transects Na Ramet level Genet level

Ho He FIS Ho He FIS Patch Reef T1 4.33 0.544 0.538 –0.011 0.518 0.549 0.058

T2 4.00 0.489 0.459 –0.065 0.467 0.534 0.132*

T3 4.17 0.483 0.548 0.120*** 0.481 0.544 0.118**

Fringing Reef T1 3.83 0.416 0.390 –0.066 0.425 0.527 0.202**

T2 2.75 0.472 0.332 –0.436 0.417 0.503 0.195

T3 4.17 0.602 0.543 –0.10 0.559 0.576 0.030

Back Reef T1 5.08 0.487 0.513 0.051** 0.498 0.533 0.067**

T2 4.92 0.479 0.513 0.066*** 0.507 0.530 0.045*

T3 5.17 0.481 0.542 0.113*** 0.495 0.547 0.096***

Upper Slope T1 5.33 0.522 0.536 0.026** 0.485 0.534 0.092***

T2 5.92 0.492 0.511 0.038*** 0.504 0.543 0.072***

T3 5.67 0.415 0.506 0.180*** 0.465 0.534 0.133***

Mid Slope T1 6.17 0.531 0.552 0.038*** 0.505 0.542 0.069***

T2 6.17 0.518 0.545 0.049*** 0.520 0.555 0.063***

T3 5.83 0.580 0.554 –0.048 0.584 0.563 –0.038*

Na, number of alleles; HO, observed heterozygosity; HE, expected heterozygosity; FIS, inbreeding coefficient. Significant values of FIS are indicated by bold values with * P < 0.05, ** P < 0.01 and *** P < 0.001.

176

Conclusionsand Directions New

177

178

CHAPTER 9

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RÉSUMÉ SUBSTANTIEL

Les récifs coralliens sont l'un des écosystèmes les plus productifs et les plus diversifiés sur Terre. Toutefois, 75% des récifs sont actuellement menacés par de nombreux stress locaux et globaux et entravent ainsi la capacité des récifs coralliens à fournir d'importantes sources de services écosystémiques à des millions de personnes. Dans ce contexte actuel de changement climatique, évaluer les stratégies d'histoire de vie des espèces récifales est essentiel afin de comprendre le fonctionnement de leurs populations et prédire les conséquences à long terme sur la dynamique des communautés face aux changements environnementaux.

Les hydrocoralliaires du genre Millepora (‘coraux de feu’) représentent une composante importante au sein des communautés récifales où ils contribuent à la formation des récifs. Malgré leur importance écosystémique, les coraux de feu ont été relativement peu étudiés et leurs traits d’histoire de vie demeurent toujours méconnus. Les coraux de feu sont des organismes coloniaux gonochoriques (colonies mâles et femelles séparées) qui se reproduisent à la fois par reproduction sexuée (stades médusoïdes et larves planula) et asexuée (fragmentation). Chaque mode de reproduction confère différents avantages évolutifs. La reproduction sexuée favorise les processus d'adaptation génétique (recombinaison génétique) et la colonisation de nouveaux habitats (potentiel de dispersion plus élevé) alors que la reproduction asexuée favorise la propagation locale de génotypes localement bien adaptés. Déterminer la balance entre ces deux modes de reproduction est donc cruciale pour comprendre le renouvellement et le maintien des populations au sein d’environnements changeants. Puisque les conditions environnementales peuvent imposer des pressions de sélection divergentes, un vaste échantillonnage a été réalisé à Moorea, Polynésie Française, au sein de cinq habitats récifaux aux conditions environnementales contrastées : deux habitats sur la pente externe, la pente moyenne (13 mètres de profondeur) et la pente supérieure (6 mètres de profondeur), et trois dans le lagon (< 1 mètre de profondeur), le récif arrière, le récif frangeant et le récif en ‘patch’. Dans le cadre de cette thèse, un total de 3651 colonies de coraux de feu ont été mesurées, géoréférencées et collectées dans ces habitats.

L’objectif principal de cette thèse consistait à évaluer le contexte biologique et écologique du maintien et du renouvellement des populations de Millepora platyphylla, la seule espèce de corail de feu recensée à ce jour en Polynésie Française. Pour ce faire, nous avons tout d’abord déterminé la structure démographique des populations au sein de chaque habitat. Ce travail a démontré que la structure des populations diverge entre le lagon et la pente externe. Ensuite, nous avons développé de nouveaux marqueurs microsatellites puisqu’aucun marqueur n'était disponible pour le genre

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Millepora. Ces quinze locus microsatellites nouvellement développés ont été nécessaires afin d’évaluer plusieurs aspects du cycle de vie de cette espèce.

A l’aide de ces marqueurs moléculaires, nous avons déterminé le niveau de clonalité au sein de chaque habitat et examiné l’influence de ce paramètre environnemental sur les variations morphologiques de M. platyphylla. Au niveau de la pente supérieure, où les vagues se brisent, la plupart des colonies se développent sous forme de feuillets verticaux (morphologie ‘arbre à feuilles’) alors que les colonies recensées dans les autres habitats se développent majoritairement sous forme encroûtantes et massives. Nos données génétiques ont démontré que M. platyphylla se reproduit principalement par la fragmentation (80% des colonies étaient des clones). La proportion de clones varie fortement entre les habitats (≥ 58–97%) et les fragments (clones appartenant à 328 lignées clonales) sont distribués perpendiculairement au récif, en parfait alignement avec la dispersion des vagues. De plus, les clones d’une même lignée clonale partagés entre habitats adjacents (i.e. la pente moyenne, la pente supérieure et le récif arrière) expriment différents phénotypes selon leur exposition aux vagues. 80% des colonies de ces lignées affichent une morphologie ‘d'arbre à feuilles’ sur la pente supérieure, une morphologie vulnérable à la fragmentation, tandis que 80 à 100% des colonies sont encroûtantes ou massives sur la pente moyenne et sur le récif arrière. Ce résultat est un exemple unique de plasticité phénotypique entre clones d’organismes constructeurs de récifs puisque les coraux scléractiniaires (principaux constructeurs) ont des morphologies typiquement tolérantes aux vagues dans les zones récifales à haute énergie.

Afin d'accroître notre connaissance sur la reproduction sexuée des coraux de feu, nous avons également établi la contribution relative entre l'autorecrutement et l’allorecrutement dans la population de Moorea. Une analyse de parenté a été effectuée à l’aide des 3160 colonies recensées au sein des trois habitats adjacents et a révélé une forte contribution de l'autorecrutement (58% des juvéniles échantillonnés étaient des auto-recrues). Cette analyse a également démontré une faible capacité de dispersion des propagules sexuées et une tendance à l’agrégation d’individus issus de mêmes parents. Ce travail présente de nouvelles évidences quant à l'importance de l'autorecrutement dans la stabilisation de la dynamique des populations, car elle améliore la durabilité locale et la résilience aux perturbations.

Finalement nous avons examiné la variabilité génétique intracoloniale chez les coraux de feu dû aux phénomènes de mosaïcisme (accumulation de mutations somatiques) et de chimérisme (fusion allogénique entre colonies) qui génèrent une source supplémentaire de diversité génétique au sein des populations. Nos résultats ont démontré que la variabilité génétique intracoloniale est un phénomène commun (31,4%) chez M. platyphylla avec des variations importantes de sa fréquence 210 entre les cinq habitats récifaux étudiés (0-60%). Le mosaïcisme est responsable de la plupart des génotypes déviants (87,5%), tandis que le chimérisme est plus rare. De plus, nous avons démontré que M. platyphylla peut accumuler des mutations somatiques pendant la croissance avec un fort potentiel de propagation de ces mutations par fragmentation, alors que les agrégations d’individus apparentés peuvent faciliter la fusion allogénique (chimérisme).

En conclusion, ce projet de thèse a démontré que l'évaluation des stratégies d’histoire de vie a des implications importantes afin de mieux comprendre le renouvellement et le maintien des populations au sein d’environnements changeants. Ce travail a démontré que l’autorecrutement et l’accumulation de mutations somatiques permettent d'établir avec succès des génotypes variés au sein de la population de M. platyphylla, tandis que la fragmentation des colonies contribue efficacement à la croissance démographique de la population. L'interaction de ces stratégies génère un niveau élevé de variabilité génétique favorable aux processus d'adaptation génétique. De plus, chaque génotype a la capacité d’exprimer différents phénotypes en réponse à des changements environnementaux. Toutes ces stratégies d'histoire de vie font de M. platyphylla une espèce compétitive et opportuniste pouvant s’adapter et proliférer autant dans des environnements productifs que récemment perturbés. Ces caractéristiques suggèrent que cette espèce de corail de feu sera résiliente face aux futurs changements environnementaux.

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Titre: Stratégies d’histoire de vie des coraux hydrozoaires Millepora

Résumé: Évaluer les stratégies d’histoire de vie d’espèces est indispensable à leur conservation. Un total de 3651 colonies de corail de feu, Millepora platyphylla, ont été mesurées, géoréférencées et collectées dans 5 habitats différents à Moorea afin d’évaluer le contexte biologique et écologique du maintien et du renouvellement des populations. Ce travail de thèse a démontré que la structure des populations diverge entre le lagon et la pente externe. À l’aide de marqueurs microsatellites nouvellement développés, nous avons démontré que cette espèce se reproduit principalement par fragmentation (80%) et que les fragments sont distribués en parfait alignement avec la dispersion des vagues. Les clones d’une même lignée clonale partagés entre habitats expriment différents phénotypes selon leur exposition aux vagues. Surprenamment, M. platyphylla affiche une morphologie vulnérable à la fragmentation dans les habitats exposés à la houle. L’analyse de parenté a révélé une forte contribution de l'autorecrutement (58%), une faible dispersion des propagules sexuées et une tendance à l’agrégation d’individus issus de mêmes parents. Enfin, nous avons démontré de la variabilité génétique intracoloniale, principalement due aux mutations somatiques (mosaïcisme), qui contribue ainsi à augmenter la diversité génétique dans la population. L’interaction de ces processus engendre une diversité génétique et phénotypique élevée dans la population et permet également le renouvellement local et la persistance de cette espèce à Moorea; habitat marginal. Ces stratégies d’histoire de vie augmentent ainsi le potentiel d’adaptation et la résilience de M. platyphylla face aux changements environnementaux.

Mots-clés: Millepora, Reproduction, Plasticité phénotypique, Dispersion, Diversité génétique, Potentiel d’adaptation

Title: Life history of Millepora hydrocorals

Abstract: Evaluating life history of species carries important implications for conservation biology. A total of 3651 colonies of the fire coral Millepora platyphylla was measured, georeferenced and collected in 5 different habitats in Moorea to evaluate the biological and ecological context of the population maintenance and renewal. This thesis has demonstrated that the population structure of this species varies greatly between lagoonal and fore reef habitats. Using newly developed microsatellite markers, we have shown that M. platyphylla relies heavily on clonal reproduction via fragmentation (80%) and that the fragments are distributed in perfect alignment with wave energy dispersal. Clonal lineages with clones shared among habitats revealed the ability of a single genotype to express different phenotypes depending on its exposure to swell wave energy. Surprisingly, M. platyphylla invests in a vulnerable morphology to wave-induced breakage in high energy reef habitats. Furthermore, parentage analysis revealed a high contribution from self-seeding (58%), limited dispersal of sexual propagules and sibling aggregations. At last, we have demonstrated intracolonial genotypic variability, mostly from somatic mutations (mosaicism), which creates novel genetic diversity within the population. The interaction of these processes generates a high level of genetic and phenotypic variation within the population and allows for local replenishment and the persistence of this fire coral species in Moorea, a marginal habitat. These life history strategies thus increase the adaptive potential and resilience of M. platyphylla in response to rapid and unpredictable environmental changes.

Keywords: Millepora, Reproduction, Phenotypic plasticity, Dispersion, Genetic diversity, Adaptive potential