Thesis

New insights into the diversity of deep-sea benthic foraminifera

LECROQ, Béatrice

Abstract

Les foraminifères benthiques sont une composante majeure des fonds océaniques. Leur importance dans le cycle du carbone est largement reconnue et ils sont couramment utilisés en paléocéanographie en tant que marqueurs des changements climatiques. Cependant, nos connaissances croissantes à leur sujet nous dévoilent peu à peu que ce vaste phylum retient encore quelques secrets, notamment quant à sa diversité et à la distribution géographique de ses espèces. Dans cette thèse sont décrits deux nouveaux genres de foraminifères agglutinés : Capsammina patelliformis et Shinkaiya lindsayi. Leur morphologies, spectaculairement différentes, illustrent parfaitement l'étendue de la richesse des foraminifères monothalames. Comme d'autres xenophyophores, S. lindsayi présente un réseau interne de conglomérats digestifs (stercomata) mais se distingue aussi par l'absence de cristaux de barite dans son cytoplasme. Des analyses élémentaires ont révélé que ce foraminifère géant (8 cm de diamètre) concentrait de grandes quantités de métaux, dont l'uranium, à l'intérieur de ses stercomata, contribuant ainsi [...]

Reference

LECROQ, Béatrice. New insights into the diversity of deep-sea benthic foraminifera. Thèse de doctorat : Univ. Genève, 2009, no. Sc. 4106

URN : urn:nbn:ch:unige-39568 DOI : 10.13097/archive-ouverte/unige:3956

Available at: http://archive-ouverte.unige.ch/unige:3956

Disclaimer: layout of this document may differ from the published version.

1 / 1 UNIVERSITÉ DE GENÈVE FACULTÉ DES SCIENCES

Département de Zoologie et Biologie Animale Professeur Jan PAWLOWSKI

New Insights Into The Diversity Of Deep-sea Benthic Foraminifera

THÈSE

présentée à la Faculté des Sciences de l’Université de Genève pour obtenir le grade de Docteur ès sciences, mention biologie

par Béatrice Lecroq de Roquebrune Cap Martin (France)

Thèse N °°° 4106 Lausanne Reprographie de l’ EPFL 2009

ii

Je dédie cette thèse à l’église de Ruminghem qui a prié une nuit entière pour moi lors de mes difficiles premiers jours… et surtout, à celui qui leur a répondu.

iii

First of all, I would like to thank all the members of my thesis jury:

Dr Tomas Cedhagen,

Dr Andrew John Gooday,

Dr Hiroshi Kitazato, and

Dr Purificación López-García.

iv Remerciements

J’ai le sentiment d’avoir été extrêmement privilégiée tout au long de ma vie, en ne faisant rien pour le mériter réellement. Sans que cela ne puisse jamais compenser tout ce qui m’a été donné, j’aimerais dire merci, plusieurs fois merci, aux personnes qui m’ont aidée ou encouragée… A Jan, pour m’avoir fait confiance.

A Jackie (chan), la meilleure de tout l’étage (pas sûre que tu me revoies près de la frontière alors n’oublies pas que tu restes quand même dans mon cœur). Aux gars de l’autre coté du couloir : Fabien, Loic et Thierry qui a pseudopodé ma life (on aurait quand même pu sortir plus souvent ensemble, désolée, c’est un peu ma faute…). A José, pour ses grandes qualités et pour tout ce qu’il m’a transmis. Aux petits nouveaux : Cyril, Michael (courage, merci pour votre gentillesse, et bonne chance, Cyril, pour le dessin). Aux anciens : Quique (futur éleveur de crabes phosphorescents des iles Tonga), Cédric, Ben, David, Xavier, Patrick, Délia, Yurika et mon dive body préféré : Fred (salut Fred ;) ). Au vénérable Juan (merci pour tes précieuses corrections et tes questions toujours pertinentes lors des lab meetings !), à Ilham (Shokran, passes à la maison quand tu viendras voir Rime), Slim (merci pour tes encouragements qui m’ont énormément touchée, j’espère que l’on se reverra), Raphael, Aurélia, Anouchka, et la douce Yamila. Au professeur Bény qui aime tant les petits poulpes à la niçoise, M. Wuest. A Jacqueline, Roland, Frank et André. A Wanda, Yvan, Anne, Lisbeth, Virginie (la furieuse pilote de rallye des champs) et Kevin. Au Dr Peck et à Benjamin (merci pour ton éternel sourire qui réchauffe le cœur). A Tomohiko qui fait glisser ses claquettes, à Patrick qui a tort (et que je vais humilier bientôt au Poker), à Julien, la belle Chen-Da et Luca (c’est bête que l’on ne soit devenus amis que maintenant !). A Wojciech. A Giovanni (spetacollo !).

A toutes les bonnes rencontres de missions ou de meetings. De ORI, Arctowski, Ferraz (spécialement à Janaina), Polarstern, Hakuho Maru, Tansei Maru, Håkon Mosby, Téthys II. A Pedro. Aux grands Thierry et Pierre (un jour je vivrai à Marseille et je mangerai des trucs bons, comme vous ...). A Juljiana, Edu, Asma, Raphaella, Ludwig (j’espère que tu es en train de chauffer les pistes à Thonon). A Antoine, Charly (le nain) et Blujita.

A toute l’équipe du Lausanne Water Polo (un de plus !!!).

A mes amis que je garderai toute ma vie ! Caro-ling-ling-Bambou ( !!! love you baby !!! ), Tao (le saaaage, le jazz man, le lionceau, mon ami…), Pop’eye (prête pour la course j’espère), la Cantunette des bois (ah, qu’est ce que je vais faire sans toi ?), A Carl (Bombyx des), Lanou et son petit Gabriel (merci de m’être restée fidèle), Alex Pardo (la manatee), Mu (la fée végétale, acidulée et pétillante), Scully (revival), Mulder, Pablo et Salvia (« you know my friends, if you have some neurones….. »), Daphné (mon inséparable sœur ennemie), Jose et Catherine, Chloé, Patricia, Sandra, Gwen, Manon-lolola (courage), Rudy et Mariana, Sarah, Maria et Montse. A Yuuka. A Miško et Nena. A Nina, reine des fleurs.

A ma famille: papa (j’espère que tu es fier de moi), ma petite maman chérie, ma sœur l’endive, Lilou, anounette (je t’aime). A Pépé et mémé (mon refuge), Jean Luc et maintenant aussi…………ZIGI, Gabibone et Gordana.

Au Baron de Münchausen, à Kuro et Shiro

A Davor (ti i ja) v

vi Résumé

Les foraminifères benthiques sont une composante majeure des fonds océaniques. Leur importance dans le cycle du carbone est largement reconnue et ils sont couramment utilisés en paléocéanographie en tant que marqueurs des changements climatiques. Cependant, nos connaissances croissantes à leur sujet nous dévoilent peu à peu que ce vaste phylum retient encore quelques secrets, notamment quant à sa diversité et à la distribution géographique de ses espèces.

Dans cette thèse sont décrits deux nouveaux genres de foraminifères agglutinés : Capsammina patelliformis et Shinkaiya lindsayi . Leur morphologies, spectaculairement différentes, illustrent parfaitement l’étendue de la richesse des foraminifères monothalames. Comme d’autres xenophyophores, S. lindsayi présente un réseau interne de conglomérats digestifs (stercomata) mais se distingue aussi par l’absence de cristaux de barite dans son cytoplasme. Des analyses élémentaires ont révélé que ce foraminifère géant (8 cm de diamètre) concentrait de grandes quantités de métaux, dont l’uranium, à l’intérieur de ses stercomata, contribuant ainsi à modifier la composition chimique du sédiment.

En recherchant l’origine moléculaire des komokiacés Septuma ocotillo et Normanina conferta , nous avons révélé involontairement une importante faune eucaryotique associée à leurs tests branchus. Cette étude a mis en évidence une richesse dissimulée à l’intérieur des tests de foraminifères ou dans le sédiment. Il semble plausible que des foraminifères nus ou de petite taille soient particulièrement difficile à observer au microscope, échappant ainsi aux études passées. Pour cette raison, afin d’améliorer notre connaissance de ce phylum, nous avons également appliqué les dernières techniques moléculaires de séquençage massif à des extractions globales d’ADN provenant d’échantillons environnementaux. Dans cette optique, nous avons parcouru les régions variables du « SSU rDNA » de différents foraminifères à la recherche du meilleur « code barre » potentiel. L’hélice 37 (région I), ayant présenté une excellente résolution aux plus bas niveaux taxonomiques, a été choisie pour tester cette approche. Nous avons donc séquencé massivement quatre échantillons de sédiment dont l’ADN global a été amplifié sélectivement pour les foraminières. Un fragment extrêmement court de cette région (36 pb) a été analysé par le séquenceur Solexa nous permettant d’identifier un grand nombre de phylotypes avec une résolution satisfaisante. Quelques séquences sont cependant restées sans attribution car trop éloignées de tous taxa connus. Nous suspectons que beaucoup de ces phylotypes sont en faite encore inconnus de la science, et que la diversité des foraminifères, en particulier celle des monothalames, est grandement sous estimée.

Finallement, nous nous sommes intéréssés à trois espèces communes de foraminifères calcaires ayant une distribution particulièrement étendue : Epistominella exigua , Oridorsalis umbonatus et Cibicides wuellerstorfi . Nos analyses phylogénétiques basées sur le SSU partiel et l’ITS de ces espèces révélèrent un flux de gènes entre les populations des deux régions polaires. Cette étude a été généralisée dans le dernier article de cette thèse en incluant des analyses de spécimens de E. exigua provenant de l’océan pacifique. L’analyse génétique des populations de cette espèce, basée sur les séquences de l’ITS montre effectivement une homogénéité globale, confirmant qu’au moins un foraminifère benthique d’océan profond pourrait avoir une dispersion mondiale. De plus, l’analyse phylogénétique d’espèces sœurs d’ E. exigua indique que la crypticité de ce genre décroîtrait avec la profondeur. vii

Abstract

Benthic foraminifera are major components of the deep-sea bottoms and especially of the abyssal plains. Because of their value as paleoceanographic proxies and their importance in the carbon cycle, they have been extensively studied. However, as our knowledge on foraminifera progresses, it becomes clear that this vast phylum still hides numerous secrets notably concerning its diversity and the geographic distribution of its species.

In the first part of this thesis we present two genera of agglutinated, monothalamous (single-chambered) deep-sea foraminifera new to science: Capsammina patelliformis and Shinkaiya lindsayi . Their respective morphologies are spectacularly different and reflect well the broad richness of monothalamous taxa. Like other xenophyophores, S. lindsayi presents internal strings full of digestive pellets (stercomata) but its cytoplasm displays the singularity to be deprived of barite crystals. Elemental analyses revealed that this giant foraminiferan (8 cm in diameter) concentrates high quantities of metals, including uranium, in its stercomata and thus contributes to modify the chemical composition of the sediment.

By searching the molecular origin of the komokiaceans Septuma ocotillo and Normanina conferta , we revealed an important eukaryotic fauna associated with their branching tests. This study emphasizes the significant species richness concealed in foraminiferal tests or simply “hidden” within the sediment. Some small and naked foraminifera might be out of reach with traditional microscopic observations. Therefore, in order to get an enhanced view of foraminiferal richness, we proposed to apply the recent molecular technique of massive sequencing using Solexa analyser and global DNA extractions of environmental samples. For this purpose we investigated variable regions of foraminiferal SSU rDNA and identified the helix 37 (region I) as the best potential “barcode” at lower taxonomic level. To confirm the relevance of this approach, we performed the massive sequencing of four sediments targeting foraminifera and using an extremely short rDNA fragment from region I (36 bp). We succeeded to identify quite a high number of phylotypes with a satisfying taxonomic resolution. However, some sequences remained indeterminate since they were considerably divergent from any of known taxa. We suspect therefore that several phylotypes are effectively unknown to science and that foraminiferal species richness has been largely underestimated.

Finally, we examined the distribution of three widely dispersed calcareous morphospecies: Epistominella exigua , Oridorsalis umbonatus and Cibicides wuellerstorfi . Phylogenetic analyses of their partial SSU and ITS rDNA sequences show that gene flow occurs between Arctic and Southern Ocean populations. This study was extended in the last paper of this thesis including analyses of E. exigua specimens from the Pacific Ocean. These ITS-based analyses show that E. exigua presents a global homogeneity confirming that at least one deep-sea species could have a world-wide dispersal. Moreover, investigations on partial SSU sequences of different Epistominella sister species indicated that the crypticity of this genus would decrease with depth.

ix Table of Contents

Résumé ...... vii Abstract...... ix Table of Contents ...... x List of Figures...... xii List of Tables...... xiii

CHAPTER 1: GENERAL INTRODUCTION ...... 1 1.1 Diversity: context and rational...... 1 1.1.1 The unnatural concept of “species”...... 1 1.1.2 Richness and diversity...... 6 1.1.3 Why study diversity?...... 10 1.2 Deep-sea ecosystems patterns...... 13 1.2.1 An odd and ordinary world ...... 13 1.2.2 Patchiness and transience of resources: ephemeral benthic oases...... 18 1.2.3 The deep-sea benthos continuum ...... 22 1.3 The foraminiferal model...... 30 1.3.1 General ...... 30 1.3.2 A wide benthic taxa for a wide range of niches...... 33 1.3.3 The typical deep-sea citizens...... 37 1.4 Objectives and impacts ...... 41

CHAPTER 2: THE VAST FORAMINIFERAL DIVERSITY IS INCOMPLETELY EXPLORED: MONOTHALAMOUS EXAMPLES ...... 43 2.1 Introduction ...... 43 2.2 The ‘mica sandwich’; a remarkable new genus of Foraminifera (Protista, Rhizaria) from the Nazare Canyon (Portuguese margin, NE Atlantic)...... 45 Abstract ...... 46 Introduction ...... 46 Methods ...... 47 Results ...... 49 Concluding remarks ...... 60 2.3 A new genus of xenophyophores (Foraminifera) from Japan Trench: morphological description, molecular phylogeny and elemental analysis...... 61 Abstract ...... 62 Introduction ...... 62 Material and Methods ...... 64 Results ...... 66 Discussion ...... 74

x CHAPTER 3: “HIDDEN” RICHNESS REVEALED BY MOLECULAR TOOLS...... 79 3.1 Introduction ...... 79 3.2 Molecular analyses reveal high levels of eukaryotic richness associated with enigmatic deep-sea protists (Komokiacea)...... 81 Abstract ...... 82 Introduction ...... 82 Material and Methods ...... 84 Results and Discussion ...... 86 Conclusions ...... 98 3.3 Assessment of the deep-sea foraminiferal richness by massive sequencing with Solexa analyser ...... 99 Abstract ...... 100 Introduction ...... 100 Material and Methods ...... 103 Results and discussion ...... 106 Conclusions ...... 124

CHAPTER 4: COSMOPOLITANISM ...... 125 4.1 Introduction ...... 125 4.2 Bipolar gene flow in deep-sea benthic foraminifera ...... 127 Abstract ...... 128 Introduction ...... 128 Material and Methods ...... 131 Discussion ...... 137 4.3 Global genetic homogeneity in the deep-sea foraminiferan Epistominella exigua (Rotaliida: Pseudoparrellidae)...... 141 Abstract ...... 142 Introduction ...... 142 Material and Methods ...... 143 Results ...... 144 Discussion ...... 149

CHAPTER 5: GENERAL DISCUSSION, CONCLUSIONS AND PERSPECTIVES153 5.1 General discussion...... 153 5.1.1 Benthic foraminiferal richness ...... 153 5.1.2 On the trail of biodiversification processes ...... 155 5.2 Conclusions ...... 161 5.3 Perspectives...... 163

REFERENCES ...... 165

APPENDIXES ...... 189 Appendix A: Monothalamous foraminifera from Admiralty Bay...... 191 Appendix B: Bowseria arctowskii gen. et sp. nov...... 215 Appendix C: Supplementary Material of section 2.2 ...... 227 Appendix D: Using 454 sequencing technology to explore eukaryotes diversity ...... 229 Appendix E: Supplementary Material of section 3.2 ...... 235 Appendix F: Supplementary Material of section 3.3 ...... 239 Appendix G: Supplementary Material of section 4.2 ...... 241 Appendix H: Supplementary Material of section 4.3 ...... 243 xi List of Figures and Plates

Fig. 1.1.1. Distribution of a morphological trait as a criterion for species distinction 5 Fig. 1.2.1. Models of populations dispersal and gene flow 25 Fig. 1.2.2. Diversity of microbes 28 Fig. 2.2.1. SSU phylogenetic tree of Capsammina patelliformis 58 Fig. 2.3.1. SSU rDNA of Shinkaiya lindsayi 66 Fig. 2.3.2. Shinkaiya lindsayi (binocular) 68 Fig. 2.3.3. Shinkaiya lindsayi (SEM and TEM) 71 Fig. 2.3.4. SSU phylogenetic tree of Shinkaiya lindsayi 73 Fig. 2.3.5. Elemental composition of Shinkaiya lindsayi 74 Fig. 3.2.1. SSU phylogenetic tree of Komokiacea (foraminifera) 87 Fig. 3.2.2. SSU phylogenetic tree of Komokiacea (eukaryotes: Metazoan, Fungi) 89 Fig. 3.2.3. SSU phylogenetic tree of Komokiacea (eukaryotes: Euglenozoa) 91 Fig. 3.2.4. SSU phylogenetic tree of Komokiacea (eukaryotes: stramenopiles) 92 Fig. 3.2.5. SSU phylogenetic tree of Komokiacea (eukaryotes: Cercozoa) 94 Fig. 3.2.6. Pie charts of eukaryotic richness from Komokiacea and sediment 97 Fig. 3.3.1. Map of sediment sampling, Solexa massive sequencing 104 Fig. 3.3.2. Secondary structure of SSU rDNA 107 Fig. 3.3.3. Secondary structure of foraminifera-specific expansion zone 37/f 108 Fig. 3.3.4. Taxonomic resolution of SSU rDNA variable region 117 Fig. 3.3.5. Simulated saturation curves 119 Fig. 3.3.6, Fig. 3.3.7. Phylotypes richness of SFA 2, SFA 3 122 Fig. 3.3.8, Fig. 3.3.9. Phylotypes richness of SFA 4, SFA 5 123 Fig. 3.3.10. Number of phylotypes for lageniids, rotaliids, textulariids ans monothalamous 124 Fig. 4.2.1. Sampling map (bipolar gene flow) 130 Fig. 4.2.2. SSU phylogenetic tree of E. exigua , C. wuellerstorfi and O. umbonatus 134 Fig. 4.2.3. Haplotype networks of E. exigua , C. wuellerstorfi and O. umbonatus 136 Fig. 4.3.1. SSU phylogenetic tree of Epistominella genus 145 Fig. 4.3.2. ITS divergences of E. exigua populations 147 Fig. 4.3.3. ITS sequences network (TCS) of E. exigua 148

Plate 1. Psammosphaera bowmanni 52 Plate 2. Capsammina patelliformis , (light micrographs and SEM) 53 Plate 3. Capsammina patelliformis, (SEM) 54 Plate 4. Capsammina patelliformis, (SEM) 55 Plate 5. Capsammina patelliformis, (SEM) 56 xii List of Tables

Table 3.3.1. Depths, coordinates and sampling method of sediment (Solexa) 104

Table 3.3.2. SSU variable regions in literature 106

Table 3.3.3. Sequences of the six variable regions 111

Table 3.3.4. Sequences divergence between and within 14 foraminiferal morphospecies 113

Table 3.3.5. Intraspecific polymorphism in variable regions 116

Table 3.3.6. Number of phylotypes recognized by phylogenetic analyses 116

Table 3.3.7. Statistics of reads and phylotypes obtained in Solexa analyses 118

Table 4.2.1. SSU and ITS rDNA sequence data for E. exigua , C. wuellerstorfi and O. umbonatus 133

xiii

Chapter 1 General Introduction

1.1 Diversity: context and rational

1.1.1 The unnatural concept of “species”

It would seem unwise to look into the diversity without introducing its most fundamental and universal unit: the species. Althought the “species” concept has been and is still widely used in science and numerous other fields, it appears impossible to define it in a way that applies to all organisms. And this to such an extent, that many biologists simply stopped believing in the existence of the species as a taxonomic level, i.e. category. Among them Darwin, who dedicated a great part of his work to this term but still considered it as indefinable.

« It is really laughable to see what different ideas are prominent in various naturalists' minds, when they speak of ‘species’; in some, resemblance is everything and descent of little weight — in some, resemblance seems to go for nothing, and Creation the reigning idea — in some, sterility an unfailing test, with others it is not worth a farthing. It all comes, I believe, from trying to define the indefinable. » (Darwin, 1887).

It may be useful to start with the prior definition of the word “species”, namely its etymologic root. From Latin “ speci ō” meaning “see” and “ speci ēs” meaning “appearance”, the term “species” contains intrinsically the idea of “showing some traits”. Thus, a first definition of “species” could be “a set of organisms showing common traits specific to them”. This definition fits to the essentialist point of view, prevailing from Aristotle to Linnaeus and describing species as “natural kinds with eternal essences”. Each and every member of a kind is sharing a common essence which is, at the same time, responsible for the traits typically associated with those members. However, this definition induces two problems. The first one is that biologists sometime failed to find traits occurring in all members of a species and the second one is that they often also failed to find traits occurring exclusively in the members of a species. 1 Natural environment does not produce exact replicates but rather displays phenotypic diversity. Actually, each of the traits which constitute a species according to the essentialist definition could eventually disappear in the offspring. To conserve this definition, only the traits which will pass to the next generations (genetically inherited) should thus be considered. Therefore, an improved definition for “species” could be “a set of organisms sharing traits which will all be transmitted to the offspring”. However, environmental parameters alone decide which traits will be, by the way of selection, transmitted. Since those parameters can not be totally predicted, one could define the species category but would fail to describe any of them.

The second problem related to the essentialist definition of species is also induced by the natural selection process. According to the definition, a trait defining a species should be unique to that species. There are numerous examples of extremely specific traits shared by asunder species. This phenomenon results from a convergent evolution creating similarities coming from independent origins (homoplasy). For instance, there are striking morphological likenesses between the shell of bivalves and that of brachiopods, however not closely related; between the spiny stems of Euphorbiaceae and Cactaceae; between river dolphins Iniidae and Platanistidae; or even, between cuttlefish and mammalian eyes. Convergent evolutions also occur at molecular level, like for the antifreeze glycoproteins in Antarctic notothenioid fish and Arctic cods (Chen et al., 1997) and the amino acid sequence convergence of the lysozyme from the stomach of cows and colobine monkeys (Stewart et al., 1987). In each case the same evolutionary answer is proposed to an ecological problem. At first sight, it should be a quite unlikely mechanism because phenotypic differences are supposed to be controlled by many genes. The probability that the entire set of genes implied in one phenotypic trait evolves to produce the same result than for a different and independent organism should be thus very low. However, some investigations show a totally different situation. Firstly, many quantitative traits would be actually controlled by few genes, increasing the probability of a convergent evolution (Tanksley, 1993). Secondly, recent studies tend to show that molecular homoplasies would be in fact prevalent since driven by natural selection. By compiling the homoplastic amino acid substitutions in eukaryotic proteins, Rokas and Carroll showed they were twice as frequent than expected under neutral models of protein evolution (Rokas and Carroll, 2008). At this point, it becomes obvious that no set of traits is able to include or exclude an organism in or from a species since species themselves have great similarities but

2 heterogeneous members. The essentialist definition of “species” should therefore be definitively rejected.

If a set of traits can not define a species by itself, the frequencies and the persistence of each trait over generations could. After Darwin introduced how species are changing over time (Darwin, 1859b), most of the scientists agreed that an organism belongs to a species because it is part of a lineage and not because it has a particular qualitative feature. Such a lineage could be compared to a continuous entity with a distribution of gene frequency over time and over all the members of the lineage. Considering a trait, a species would thus be “located” around the maximum of this distribution. This implies that two closely related species will share a common boundary in term of gene frequencies regarding one trait. In the same way, a species under speciation process will change progressively from unimodal to multimodal distribution of gene frequencies. A similar approach of the species concept is given in the “Population Structure Theory” (PST) (Ereshefsky and Matthen, 2005). A species is there defined only by the similarities (or variations) of its members, i.e. its traits distributions. This assumption seems correct and more universal than the essentialist definition which failed to catch the species heterogeneity over time and between specimens. Nevertheless it weakly defines the concept and rather only describes some of its intrinsic properties. A species is indeed constituted of organisms having, at a given time, a precise distribution of traits frequencies, but does it state on what is a species? In other words, the PST presents a species as a set of individuals having a certain distribution properties regarding a given trait. Thus, the common feature shared by all species and defining them as “species” should be “to have members non-randomly distributed regarding certain traits”. Yet, this feature is also shared with other entities than species, notably with other taxonomic levels. Therefore, the PST fails to offer any univocal definition of the species category or efficient method to separate closely related species.

A third definition for “species” is given by Ernst Mayr: "groups of actually or potentially interbreeding natural populations, which are reproductively isolated from other such groups" (Mayr, 1942). At first sight, this definition seems to offer a clear distinction between species and appears to be proper to this taxonomic level. Unfortunately, it also raises more questions than it gives answers. First of all, reproductive compatibility criterion does not take into account horizontal gene transfers, which also contribute to species diversification

3 and distinctness. There are increasing evidences that horizontal gene transfer occurs not only within bacteria and unicellular eukaryotes (Andersson, 2009) but also within plants (Woloszynska et al., 2004), mollusks (Rumpho et al., 2008) and crustaceans (Williamson, 2003). Many biologists assume that two populations with sufficiently different traits (acquired for instance during horizontal gene transfer) should be considered as two distinct species even if they still can interbreed. This remark is especially relevant in microbiology where the interspecies boundary is hazy and horizontal gene transfer common. To resolve such conflict some kind of arbitrary limits have been established depending on the taxonomic groups. For instance, populations of bacteria or archaea having more than 1.3 % differences in the 16S ribosomal RNA gene, are currently considered as distinct species (Stackebrandt and Ebers, 2006). The second objection to the Ernst Mayr’s definition comes from the fact that the interbreeding criterion is actually also a trait, having (like any other trait) a frequency distribution across the members of one single population. This implies that the ability of a specimen to interbreed with another specimen from another population will depend on its “position” in this distribution. This is illustrated in Fig. 1.1.1. Considering three populations A, B and C closely related and composed of respective subpopulations: A1, A2, A3; B1, B2, B3; C1, a value could be attributed to each subpopulation according to a morphological trait. For instance, populations of birds could be plotted according to their beak size. Specimen of population A present beaks of different size among subpopulations A1, A2 and A3, with a maximum of individuals in A1, i.e. having a beak of 3 cm length. The situation of population B is similar with three subpopulations B1, B2 and B3 presenting increasing beak sizes with a maximum of individuals in B2, i.e. having a beak of 5 cm length. Considering that the beak size is as a decisive criterion to choose mating partner. If birds of A1, A2 and A3 can potentially interbreed, as well as birds of B1, B2 and B3 without being able to interbreed between A and B, both populations should be considered as distinct species S1 and S2. If birds of C1 can interbreed with A3 and B1, those three populations should also, according to the definition, consist in a species S3. Yet it is impossible, according to the same definition, since S3 is not “reproductively isolated” from S1 and S2. This fictive example show how unclear is the interbreeding criterion in the Ernst Mayr’s definition. If it should be applied to all members of the same species, the definition becomes impractical. But if only few specimen of a population should be able to interbreed for that population to be a species, any population wide enough to include interbreeding members should be considered as species. Once again, the species concept seems to escape from its own definition. 4 Species distinction according to a morphological trait

Figure 1.1.1. Distribution of a morphological trait as a criterion for species distinction. A1, A2, A2, C1, B1, B2 and B3 represent birds populations and are plotted as a function of their beak size. S1, S2 and S3 represent hypothetical species according to Ernst Mayr’s definition (groups of potentially interbreeding natural populations). Barriers between S1, S2 and S3 can not be established. According to the definition, should A3 and B1 belong to the same species? In one hand, they are reproductively isolated but on the other hand, they are regrouped by C1, which can interbreed with both A3 and B1.

To conclude, it should be assumed that there is no universal definition of “species” simply because this category does not exist in the nature. Indeed, species vary in the way they regroup organisms, do not have a common definition but rather common characteristics like a non-random distribution in the traits frequency of their members. Darwin also wrote:

“I look at the term species as one arbitrarily given for the sake of convenience to a set of individuals closely resembling each other (...) It does not essentially differ from the word variety, which is given to less distinct and more fluctuating forms. The term variety, again, in comparison with mere individual differences, is also applied arbitrarily, and for convenience sake." (Darwin, 1859a).

Eventhough the existence of species category (i.e. taxonomic level) has to be rejected; there should be no doubt about the use of the species taxa (like for instance Raphus cucullatus or Epistominella exigua ) as the first and foremost convenient evolutionary units, which representatives have been arbitrarily chosen and which traits evolve over space throughout their representatives and over time from their appearance to their extinction.

5 1.1.2 Richness and diversity

The species richness is simply defined by the number of different species and can be established, for instance, inside a given area, at a certain time or within a community. The biological diversity or “biodiversity” is the "variation of life at all levels of biological organization" (Gaston K. J., 2004). It can refer to the species diversity, the genetic diversity, the ecosystem diversity, or to any other biological variety. For the moment, we will focus on the species diversity, which reflects both the species richness and the number of individuals from each species (Margurran, 1988).

Nowadays, the relevance of both richness and diversity seems obvious in any biological study linked to natural populations. However, these two concepts, as they are currently used in ecological context, are quite new. Indeed, taxonomy exists since thousands of years, whereas it is only in the second part of the 19 th century that biologists headed toward ecology, probably in the background of an already declining environment. Ecology, introduced by Ernst Hackel (Haeckel, 1866) and initially developed by Eugenius Warming (Warming, 1895), examines the interactions of living organisms with their environment. The development of this new field reflected thus a slide in biologists’ concerns, from a particular to a global and contextual point of view. Actually, during this period, a real and deep upheaval was occurring, in the scientific thought as well as in the experimental methods. Biology became less contemplative and was not restricted anymore to the description and study of natural examples. On the contrary, main issues were, from that moment, to understand the relationships between biotic units and abiotic factors with the inherent purpose of acting on the overall system and modifying it.

The first crucial step of the ecological approach, and also the one which will be mainly discussed in this thesis, consists in the assessment of the diversity. Since the work of Whittaker, tree levels are widely used to define the diversity: the Alpha, Beta and Gamma diversity. They are representing respectively the within-habitat, cross-habitat and regional diversity (Whittaker, 1972). Before assessing any richness or diversity level, an ecological purpose is required. For instance, studying the impacts of industrial activity on a natural swamp will imply investigations on alpha diversity, while comparing bacterial fauna from two different types of environment will involve the Beta diversity. There are several metric

6 ways to quantify the species richness and diversity of an ecosystem. The most common involve the calculation of the Simpson Index (Simpson, 1949), which represents the probability that two randomly selected individuals in the habitat belong to the same species, or that of the Shannon Index (Shannon, 1948), which accounts for both abundance and evenness of the species and which is maximum if each species represented is composed of the same number of individuals. Nevertheless, some ecologists consider that species number is a poor unit for evaluating biodiversity and highly depends on sampling. For that reason, Warwick and Clarke have introduced the taxonomic diversity index and the taxonomic distinctness, which both take into account the phylogenetic separation between individuals (Warwick and Clarke, 1995).

No matter what method is chosen for the diversity assessment, the work always includes the specimen counting and their identification. Once again, numerous different ways exist for counting and identifying organisms depending on the characteristics of the group studied, like its body size range or its occurrence. Identification criteria truly depend on taxa even if morphology remains, until today, widely used. However, morphological studies are sometimes insufficient or excessively time consuming as identification tool. Biochemical analyses, such as fatty acids composition, are often performed for the identity diagnosis of the smallest organisms (Cox et al., 2006; El Menyawi et al., 2000; Roberts et al., 2006). Quite rapidly after the rise of the molecular systematics in the late 1960s, the genetic information contained in the DNA and RNA also became a standard for the identification. The use of this powerful molecular tool is now more and more systematic in the identification process but the investigated regions differ depending on the group, the family or even the genus studied. For instance, DNA sequences of some nuclear genes enabled the distinction between the African elephant species Loxodonta africana and L. cyclotis (Roca et al., 2001); small subunit ribosomal DNA (SSU rDNA) has been used to identify apicomplexan parasites of tortoises (Traversa et al., 2008) and microbiologists refer either to SSU or to internal transcribed spacer (ITS) rDNA to dissociate strains of bacteria (Chen et al., 2001). In 2003, Paul Hebert proposed that partial sequences of the cytochrome c oxidase subunit I gene (COI) from the mitochondrial DNA (mtDNA) would be kinds of species specific barcodes and would provide “a new master key for identifying species” (Hebert et al., 2003). Unfortunately, there are now clear evidences that the COI gene does not suit to identify species in all taxonomic groups either because it may be represented by heterogenous copies (Song et al., 2008) or because it

7 is not diverging rapidly enough (Elias et al., 2007; Huang et al., 2008). However, continuous efforts to find reliable short DNA barcodes are still produced for each taxonomic group separately and give sometimes positive results (Huse et al., 2008). Thus, DNA barcoding (if not only based on COI) offers a competitive solution for the diversity assessment and its management, since it potentially provides a fast and relatively cheap way to identify species (Rubinoff, 2006).

As for the species identification, the specimens count is performed based on direct or indirect evidences that the species is or was indeed present in the studied area. For instance, diversity of insects is usually established by in situ trapping and direct counting (Abdullah et al., 2008). For terrestrial mammals like coyotes, number of individuals is often estimated by collecting feces (Kays et al., 2008) and for bacteria, richness can be found using clone libraries of rRNA genes (Polymenakou et al., 2009). All the methods to assess the species richness and the diversity are not equally relevant and indirect evidences can sometimes be misleading. Remains and metabolites can be dragged out of their original place by the wind, the current or another organism. The best way to be sure that a species is indeed in a given area is by observing it alive directly in its ecosystem, which is of course impossible for many taxa. Moreover, some studies suggest the presence, in marine sediments, of extracellular DNA, which could be preserved for a long time after the death of the organism it comes from (Dell'Anno and Danovaro, 2005a). These “dead” DNA molecules could potentially be amplified and included in clone libraries, inducing wrong conclusions about the species richness. Finally, a particular attention should be paid to the “active part” of the diversity. Since molecular tools are getting more and more efficient, they enable to reveal a great richness including numerous new taxa from the environmental samples. The ecological meaning of this diversity should be taken in account, since all the species recovered by molecular analysis may not be equally involved in metabolic processes of ecosystems.

After the assessment of the diversity for a given area, an ecological approach should lead to the factors that are associated with the species richness and the species occurrence in this area. Three kinds of events can modify the local species richness and thus, the diversity: speciation, extinction and migration in and out of the studied area from and toward a regional gene pool (Gage, 2004). Thus, to identify the factors shaping the richness, it is first required to find what could generate these three events.

8 An ecosystem with a set of populations from different species can only support a finite amount of biomass regarding its physicochemical characteristics like, for instance, light exposure, resources availability or nesting sites. There are two opposite ways to consider the populations occupying the ecosystem. The first one is based on the ecological niches concept (ENC) assuming that each species possesses its own characteristics, which make it suitable to occupy a particular space, so called “niche” (Grinnell, 1917). It implies that each species has a different fitness regarding the environment. After a certain time, a niche will be occupied by only one species: the one with the greatest fitness. Grinnell presents the niche as a property of the environment. According to him, the nature will supply to each new niche a new occupant, selected by evolutionary processes. However, it remains unclear whether new species are indeed produced by niches creation or whether competing species tend to use different resources to avoid competition and so, create niches. In the latter case, ecosystems should evolve by partitioning natural niches and would continuously increase their species number. Evidently, Grinnell’s concept could be criticized for being totally devoted of randomness, since it implies that new species could only be produced by competition.

The other way to consider populations occupying an ecosystem refers to the neutral theory of Kimura, which gives a predominant place to genetic random drifts in evolution (Kimura, 1979). This will lead Hubbell to later introduce the unified neutral theory of biodiversity (UNTB), setting that all species and individuals of the same trophic level are equivalent (Hubbell, 2001). In other words, all species have “neutral” differences and similar chance of success in a given ecosystem: they have thus similar fitness. Considering a closed ecosystem and according to the UNTB, genetic drift would induce speciation at the same global frequency for each population. At the beginning of this process, population’s size could be large and obey to the same deterministic models, for instance, prey-predator interactions. When preys population increases, predator population increases too, inducing a growing consumption of preys and so on, until an equilibrium state. Balances will be successively reached between populations of smaller and smaller size, while species are drifting and speciation is occurring. As a consequence, the number of species should continuously increase with a decreasing size of their respective populations, since those sympatric species are competing for similar resources. The UNTB predicts that this process will go on and on until the populations size becomes so small that species obey to stochastic models. Random events (like fire or disease) will eliminate species as fast as others will

9 appear, producing, this time, an equilibrium between species (Levinton, 1979). This vision meets somehow the theory of island biogeography, describing the colonization process of a virgin island. A steady-state of the species richness is reached when there is equilibrium between immigration and local extinction (MacArthur and Wilson, 1967). According to UNTB, any new ecosystem will evolve by continuously increasing its species richness and decreasing its species respective abundance until equilibrium, where the system is biotically saturated with individuals. Thus, at steady state and without any perturbation of the system, species richness would be predictable (maximized regarding the area size) and population densities constant. These conclusions, only valid for species competing at the same trophic level, induce that diversity per unit area would tend to be the same everywhere.

Both ENC and UNTB agree that the species richness of an undisturbed area will increase with time. Assuming that, it becomes clearer that there are no factors directly associated with the species richness and the species occurrence, but rather different evolution states from the moment when the system was disturbed. Area with low species richness would thus be young ecosystem resulting from new niches partitioning or having been recently disturbed and passed through a bottleneck. Other way round, hotspots of diversity would be old undisturbed system close to the steady state.

1.1.3 Why study diversity?

First and foremost, it has to be pointed out that very little is known about the biodiversity. Living organisms have been given names since ages, but till the end of the 17 th century, only species of the same range of size as that of humans were considered. Microbial diversity, which forms the greatest part of the global diversity, remained totally unknown until microscopic observations of Leeuwenhoek. Today, between 1.5 and 2 million eukaryote species have been formally described (including redundant descriptions and considering only the world-wide accepted literature) and would constitute, according to the latest estimations, between 10 and 20 % of the entire eukaryotic richness (Gonzalez-Oreja, 2008). Prokaryotic richness is represented by less than 5000 described species, while some scientists estimate the actual number close to 4 million (Curtis et al., 2002). Other authors doubt about the accuracy of any speculation since essential parameters required by models are still unavailable (Curtis

10 et al., 2006; Ward, 2002). Increasing our poor knowledge on global diversity will surely lead to a certain benefit.

A second argument to study diversity comes naturally from the value of the species themselves. Besides aestheticism and well-being that they provide to humans, species are the main actors of the global ecosystem humans belong to. Investigate the diversity pattern contributes to understand voucher systems involved in human requirements like food, air and water quality, or drugs availability. For instance, last pharmacology global report indicated that, only during 2005-2006, 183 chemicals from marine organisms have been shown to have one or several biological activities of medical interest (Mayer et al., 2009). Goods that humans need are likely to be found almost anywhere in the nature, on the condition that the global species richness remains sufficient. Since they are increasing evidences of redundancy among species metabolites (Wood et al., 2005) we should be able to find, anytime despite the species natural turnover, organisms producing a molecule of interest or fulfilling a desired function. However, it seems quite more difficult, or at least much longer, to invert a process of biodiversity loss. For that reason, it is probably more urgent to study mechanisms involved into the diversity maintaining rather than study the species themselves. This last remark might be true to such an extent that the diversity would consist in a real necessity for the human species, without which it could not perpetuate. Indeed, Homo sapiens is poorly extremophile and incredibly delicate species with extensive requirements to survive. The picturing of human as a “superior” species able to extract any kind of goods from its environment could be counterbalanced by the one of an “invalid” species, physiologically deficient, since dependant on numerous other species. A major reason why humans survived over two hundred thousand years with increasing abundance might be that they came across an environment with high diversity and, by chance or as an evolutionary issue, were able to use it extensively.

The last points concern the involvement of diversity into the productivity and the stability of ecosystems. The overall value of biodiversity may reside in how it affects ecosystem functions. Several investigations established a relationship between biodiversity loss and ecosystems functioning (Bunker and Naeem, 2006; Danovaro et al., 2008b; Fox, 2006; Loreau, 1998; Tilman, 2001). According to the functional insurance theory, diversity would protect ecosystems against declines in their functioning because high number of species will increase the chances that, at least, some of them maintain those functions if others

11 fail (Diaz and Cabido, 2001). It is still debated if adding species to an ecosystem will increase its functioning continuously (so called the “rivet hypothesis”) or only up to a certain point where some of the species will start to share same functions (known as the “redundancy hypothesis”). It is also pointed out that diversity alone might not be able to provide stability to ecosystems and is only one contribution in a complex and wider global process (Ives and Carpenter, 2007; Valone and Barber, 2008). However, diversity seems to largely contribute to the stability of ecosystems and thus, to their durability (Pfisterer and Schmid, 2002; Tylianakis et al., 2006). Numerous studies looked also for correlation between productivity and diversity since it was crucial issue from an economical point of view. Most of those researches converged to affirm that diversity, among other parameters, would not only buffer but also enhance ecosystems productivity (Witman et al., 2008; Yachi and Loreau, 1999).

To conclude, it is certain that human destiny is linked to the biodiversity of the planet. Diversity loss, like it seems to be occurring right now in most of environments (Ling, 2008), will certainly have direct impact on ecosystems functioning and productivity. Despite all, scientists are late to study processes involved in the species richness maintenance and even fail to give estimations of diversity for many taxa. Tremendous amounts of money are worldwide spent to balance losses induced by extinction or populations reduction of target species with commercial interest, instead of being used for the study and the protection of biodiversity. At the “World Conference on Marine Biodiversity” holding in Spain during November 2008, Rudolf de Groot presented some socio-economic costs of marine biodiversity protection:

“It is calculated that effective protection of 20-30% of the world’ seas and coastal systems would cost between 5 and 19 billion US$ per year but will generate benefits many times that amount. Current global expenditures on supporting (non-sustainable) marine fisheries are estimated between 15 and 30 billion US$ per year.”

12 1.2 Deep-sea ecosystems patterns

1.2.1 An odd and ordinary world

Seventy-one percent of the earth surface is covered by water accumulated by outgassing, over the past 4.6 billion years, or from extraterrestrial origin (brought with comets). Oceans represent 97.3% of this water and are, for 95%, considered as deep sea, i.e. deeper than 200 m below the sea level. Therefore, it is correct to affirm that the deep sea is the most common environment of the planet. However, it is still regarded by many scientists as one of the most unusual and fairyland-like biotope of the world. For a long time, deep sea was even not fully considered as a biotope and many have speculated that life would not occur very deep. In the early 19th century, how deep extended oceans and living organisms was still a complete mystery. After a dredging campaign on Aegean Sea in 1841, Edward Forbes proposed the “azoic theory” based on his observations of a fauna getting rarer with depth. According to his extrapolated curve of rarefaction, life should disappear around 550 m (Forbes, 1844). It is remarkable that this erroneous theory held for almost 25 years, despite contrary evidences (Anderson and Rice, 2006). The “recording telegraph” invention, two years later, was about to bring one of those evidences and change the history of marine biology. The installation of transatlantic telegraphic cable between Ireland and the Newfoundland revealed deep-sea bottoms of 5000 m and a living specimen of Caryophyllia borealis (a stony coral) attached to the cable at 1800 m. From that moment, marine biologists’ mind got carried away by this question alone: “How deep occurs life in the oceans?”. Still, they will have to wait more than a century to get the answer. Finally, in 1960, Jacques Piccard and Don Walsh on board submersible “Trieste II” reached the deepest known ocean point at 10’911 m disturbing, by the way, flounders and shrimps of the Mariana Trench. Today, almost fifty years later, this record is waiting to be repeated and less than 1% of the deep sea has been explored. One of the reasons why abysses were unstudied during such a long time and why they still remain more mysterious than the dark side of the moon, is probably that they drastically differ from the terrestrial environment scientists are living in. First, because this aquatic milieu has a density about 830 times that of air and a viscosity about 60 times greater, directly ruling the morphology, metabolism and behavior of its inhabitants. Then, considering an average depth of 3800 m, deep sea is largely deprived of natural light except that produced by the organisms themselves. As a major consequence, primary production can 13 not be processed through photosynthesis, which induces a very low average concentration in nutrients and thus also, low concentration of organisms. High pressures, low temperatures and oxygen concentrations also participate to increase differences between terrestrial and deep marine environments. Since the late 1970’s, exceptions to those general features are known. Vents and seeps, for instance, are forming real biological “hot-spots” at the opposite of other typical deep-sea ecosystems. They emphasize even more the singularity of this world.

Deep sea consists in a prodigious volume of water (1.3 billion km 3) over a floor shaped by plate accretion and particle sedimentation. Traditionally, deep-sea pelagic volume is divided into four vertical zones: the mesopelagic (from 200 to 1000 m), the bathypelagic (from 1000 to 4000 m), the abyssopelagic (from 4000 to 6000 m) and the hadopelagic (from 6000 m to the bottom). The mesopelagic, also called “twilight” is clearly different from the other three realms. Just below the surface water forming the photic epipelagic, reduced light still penetrates but not sufficiently for photosynthesis. Biomass is getting poorer and is almost deprived of phytoplankton. It is also the place of vertical migrations for zooplankton, fishes, crustaceans and mollusks which follow the phytoplankton up through the water every night. Physiological adaptations linked to the reduced light conditions, as tubular eyes or well- developed phototactic organs, can be observed in the species that do not participate in this migration. Bioluminescence is another feature widely spread among mesopelagic organisms and is known to be linked to varied function as communication (Rees et al., 1998), camouflage (Young and Mencher, 1980) or prey illumination (Douglas et al., 2000). Light is produced in photophores by specialized tissues or symbiotic bacteria (Shimomura et al., 1972). Temperature is getting down from over 20°C at the top of the mesopelagic zone (200 m) to around 4°C at its border with the bathyal zone (1000 m). Oxygen minimum zone (OMZ) also occurs in the same depths interval, depending on the atmospheric conditions and the local mixing of water masses. In the upper layers, close to the water-air interface, oxygen concentration is high (around 6 ml.L -1). Oxygen that is dissolved from atmosphere into the water and oxygen produced by photosynthesis exceed that consumed by respiration and by decomposition of sinking organic matter. Between 80 and 90% of these sinking particles are consumed by bacteria in the first 1000 meters. Going down from the surface to the OMZ, where oxygen concentration can reach less than 1 ml.L -1, contribution of atmosphere and photosynthesis is getting weaker. Deeper than the OMZ, organic matter degradation is weak, since there are only few particles left. There, oxygen concentration, also supported by cold

14 deep waters (oxygen-rich) supply, increases again but remains lower than near the surface (up to 3 ml.L -1). Organisms living in oxygen deprived environment present metabolic adaptations that enable them to consume less oxygen (some bacteria and foraminifera use rather nitrate) or to extract it from the water with high efficiency, as the vampire squid with its haemocyanin of enhanced oxygen affinity (Seibel et al., 1999). It is not the point here to describe each and every chemico-physical mechanism occurring in the deep sea but OMZ plays indeed an important role by regulating the productivity and the ecological community structure of pelagic systems (Deutsch et al., 2007), both affecting the benthos. While the mesopelagic zone is the place of strong gradients and temporal variability, the rest of the deep sea consists in a much more homogenous environment with relatively stable parameters. Bathypelagic, abyssopelagic and hadopelagic zones are globally cold, poor in nutrient and oxygen, and totally deprived of solar light. At 1000 m, less than 10 % of the sinking organic matter from the upper layers remains, making all the food chains energy-poor and poorer with depth. Organisms are therefore sparse and have to cope with nutrients limitation, cold temperature and hypoxic conditions. Numerous adaptations aim to increase their chance to eat and meet mating partners and to reduce energy consumption. Fishes, for instance, tend to be opportunist predator able to catch and swallow huge preys regarding their own size (Ebeling and Caillet, 1974; Hopkins and Baird, 1973). It has also been reported that copepods use extremely efficient mechano- and chemoreceptors to track female and food (Yen, 2000). Another striking example is angler fish male, which follows female’s pheromones, bits her and remains attached to her body for the rest of his life, saving energy and being exclusively devoted to the reproduction (Munk, 2000). In conclusion, the deeper part of the oceans is a diluted world where each source of energy is exploited to the uttermost and each opportunity is seized.

The benthic realm does not escape the poor energy and food resources constraints. Even if the deep-sea bottom presents various sorts of topological features, nutrients density seems to shape almost alone the spatial distribution of organisms. The deep-sea relief starts near the coast with the continental slopes, usually in the range of 300-2000 m, and meets up the abyssal plain at 4000 m in the mean and deep trenches at the deepest points. These three major environments are actually connected with those not only above but also beneath the ground. Oceans bottoms receive unevenly organic matter from the upper water layers depending not only on the surface production and consumption but also on the ability of their

15 form to retain the sediment. Upstream input consists first in marine snow accumulated especially in the bowl-shaped places (Alldredge and Silver, 1988; Lampitt, 1996), then in carcasses of larger organisms like whales or kelps (Graham et al., 2007; Lorion et al., 2009), and finally in terrestrial sediments dragged from the coast through submarine canyons (Canals et al., 2006). Consequently, the surface of most areas consists in mud and organic ooze, except for some rocky bathyal slopes and trenches. Matter input also comes from underneath the ocean floor due to geological activity of the tectonic plates. Under the mid-oceanic ridges, convection currents in the magma rise from the mantle core through the oceanic crust and emerge as lava. This induces a high volcanic activity with frequent earthquakes and faulting. Hydrothermal vents, discovered only 30 years ago (Corliss et al., 1979), are among the features created by these events. Seawater that has permeated into the ocean floor is heated by the hot magma (up to 350-400°C) and enriched in metals (mainly iron, copper and zinc) and hydrogen sulfide by dissolution from the surrounding crust. The hot and less dense hydrothermal fluids rise up through the ocean crust before exiting the chimney and mixing with the seawater. Because the seawater is cold and oxygen-rich, it induces the precipitation of metal sulfides and oxides resulting in a black smoke which led to the nomination of “black smokers”. When the water reaches only 250-300°C, hydrothermal fluids flow more slowly than in a black smoker and thus, can mix with closely permeated sea water (cold) already under the sea floor. In this case, metal sulfides and oxides precipitate into black minerals before exiting the chimney. When the fluids finally get out in the open ocean, only silica and calcium sulfate (white) are left to precipitate, leading to the white color of the “white smokers”. A huge biomass is associated with the smokers, starting with thermophile chemosynthetic bacteria, which insure the primary production without photosynthesis by oxidizing sulfite ions from the vents into sulfur (CO 2 + H 2S + O 2 → CH 2O + H 2SO 4) (Kaiser, 2005; Ruby et al., 1981). This primary production enables directly or indirectly the occurrence of many other life forms each of them deeply specialized and typically associated with most of hydrothermal vents ecosystems. Some organisms graze on bacteria, while others host them in their tissues or feed on primary and secondary consumers. A famous example of endosymbiosis with the chemosynthetic bacteria from the vents is the giant gutless tube worm Riftia pachyptila , consumed by the hydrothermal crab Bythograea thermydron , which is itself hunted by both octopus Vulcanoctopus hydrothermalis and eelpout fish Thermarces cerberus (Childress and Fischer, 1992).

16 Along continental margins occur other special features of the deep-sea bottom called “cold seeps” and consisting in seepage of hydrogen sulfide, methane (sometime methane- hydrate ice) or hydrocarbonated fluids (Dugan and Flemings, 2000). These fluids are released in the form of brine and settle along the bottom like lakes, because of their high density. Living communities associated with the cold seeps are similar in density and composition to those found near the hydrothermal vents and include, at the base of the food web, chemosynthetic bacteria metabolizing sulfides and methane (Knittel et al., 2005). Compared with the short lasting vents (a couple of years only) cold seeps are relatively stable systems sheltering among the longest living invertebrates, as the tube worm Lamellibrachia luymesi , which can live up to 250 years (Bergquist et al., 2000).

The third kind of special habitat induced by geothermal activity is also found near the continental margins and is composed of mud volcanoes and seamounts. Mud volcanoes are also considered as a kind of seep and consist in a mixture of mud, water and gases (mainly methane) forming characteristic domes at the surface of the sea floor. Immediate surroundings of mud volcanoes are found to be rich in micro-organisms and notably, there again, in chemosynthetic bacteria (Niemann et al., 2006). Seamounts consist in undersea mountains (typically extinct volcanoes progressively covered by sediment) higher than 1000 m. Because they are from volcanic rock, they offer a substrate much harder than the surrounding sedimentary floor and thus shelter different types of organisms including suspension feeders as sponges and corals. Moreover, their shapes disturb deep currents and induce upwelling, which bring nutrients to the euphotic zone. This locally enhances biological activity and increases concentration of living organisms. For that reason, seamounts are strategic stops for large migratory animals and also aggregate numerous visitors (Morato et al., 2008). Finally, the deep-sea bottom appears to be much less featureless than it has been supposed during the past. Local geological events create remarkable habitats for remarkable organisms.

17 1.2.2 Patchiness and transience of resources: ephemeral benthic oases

Considering deep-sea ecosystems in an overall view, it is obviously valuable to ask what could be the factors driving the richness and the diversity of the deep-sea benthos. More precisely, the distribution of energy resources over space and time should now be considered.

Ocean floor could be chiefly depicted as a wide place with extremely stable conditions (the abyssal plains) delimited by a remarkably heterogenous and disturbed zone (the continental margins). On the scale of the vast seabed, natural resources and populations of abyssal plains are extremely patchy and appear as minute and heterogeneous points. As it has been described previously, geological activity as well as sedimentation can induce this pattern of patchiness occurring at different scales. At large scale, it is quite clear that hydrothermal vents, cold seeps and whale falls provide occasionally great amount of food resources attracting and nurturing many organisms of wide size ranges. However, those spots remain rare considering the global surface of the oceanic bottoms and the effective patchiness of the deep sea has to be searched within smaller features. At medium scale, an important contribution of the floors heterogeneity consists in living organisms themselves. Biogenic structures have been found to enhance biological activity in their proximity by providing numerous goods and services like resources and advantageous structures. For instance, deep- sea corals have been recognised, in some area, to shelter large benthic communities (Krieger and Wing, 2002; Malakoff, 2003). Nematodes, polychaetes, crustaceans and bryozoans associated with large agglutinated foraminifera also illustrate, at smaller scale, the high epibiotic diversity found on the oceans floor (Gooday, 1984a, b). Habitat partitioning induced by such organisms seems to be of the most relevance in this global context of low biomass (Jumars and Eckman, 1983). Since there are few organisms, these advantageous biotic structures remain rare and thus intensively occupied. Passive deposition of larvae, depending on the sediment microtopography and hydrodynamic conditions, could also explain this patchy distribution (Butman, 1987). Finally, at small scale, fine particles and amorphous aggregates, which have reached the bottom, can attract microorganism communities and provoke patchiness. There are two different contributions to the particulate organic matter (POM): suspended particles and sinking particles (Karl et al., 1988). POM and flocculent material as gelatinous bodies forming the marine snow has been found to be hotspots of diversity for microplanktonic populations (Alldredge and Silver, 1984; Silver et al., 1978;

18 Simon et al., 2002). In the benthic meio- and microfaunal ecosystems, this organic input should have similar function, whenever particles are big enough to reach the bottom and if they are of nutritional interest compared to the surroundings. In the water column, aggregates of various sizes have been reported not only to concentrate individuals but also to differ in species composition from those of the ambient water (Crump et al., 1999; DeLong et al., 1993). It is sometimes difficult to detect, isolate and study such aggregates on the ocean floor but they should also be likely to present differences in species composition compared to the neighborhood. Spatial distribution of life in deep-sea bottoms consists thus in narrow hotspots of alternative diversity and huge concentration gradients. Gradients of biotic concentrations occurring on the seafloor are, by far, greater than those existing in terrestrial ecosystems. For instance, density of organisms in hydrothermal vent zones can be 10,000 to 100,000 times higher than in the surroundings (Juniper et al., 1998). Transition zones between deep-sea ecosystems seem highly reduced whereas, on land, environment has a quite continuous pattern considering specimens and species occurrence. This might be explained by a lower global food availability inducing a lower global biomass, which concentrates only where amounts of food are maximum (Grassle, 1991; Grassle and Maciolek, 1992). Moreover, there are evidences that geographically close areas could present large differences not only in abundance but also in species number and composition (Jumars, 1976; Jumars and Hessler, 1976). There are thus apparent barriers to genetic flows between ecosystems, which, in the deep sea, almost come down to barriers between resources hotspots. However, it remains unclear to what extent physical features (as topography or currents) and biological restrictions (as oxygen or food deprivation) consist in real enclosures separating populations. In some cases, the reason of a limited gene flow between populations have been clearly identified, as for the vent-endemic mussels of the genus Bathymodiolus separated by deep-sea currents (Won et al., 2003). It is also likely that the species richness of a given hotspot would be determined mainly by the occurrence of specimens (if they are close to the spot or not) and by the specific colonization ability of species. Therefore, it is absolutely necessary to investigate how those patchy ecosystems evolve with time.

Since food resources are major factors shaping the deep-sea ecosystems, the duration has to be taken into account. Large organic pieces settling to the floor and geological special features are typically spontaneous events, which often appear instantaneously where there was nothing just before. After reaching one of those new islands, an organism should still colonize

19 it, which implies staying and eventually reproducing. The future of a newly arrived population depends directly on the durability of the providential oasis. Typical duration of hydrothermal vents is a couple of years (Grassle, 1985), while that of cold seeps is over million years (Olu et al., 1996). Interesting correlations between organisms life span and their habitat duration time have been reported and could result from colonization strategies. For instance, the tube worm Lamellibrachia luymesi living in cold seeps has the life span record, for a deep-sea non colonial invertebrate, of 250 years during which it will slowly grow up to two meters (Bergquist et al., 2000). At the opposite, Riftia pachyptila is able to colonize a new hydrothermal vent, reach sexual maturity and a size of 1.5 m, in less than two years (Govenar et al., 2004). Deep-sea corals, which are suspension feeders and can maintain their colonies over 4000 years, represent another exception among the short living habitats of the bottoms. However, they seem to occur only in zones of constant particulate flux or on seamounts (Roark et al., 2009). Those deep reefs (which can cover enormous areas) as well as the cold seeps represent fundamentally atypical ecosystems of the oceans floor. Indeed, they should be the place of positive or negative natural selection, since they are long lasting and supposedly stable enough for competition to occur. Therefore, they may have a crucial function in the global diversification processes of the deep sea. Coral reefs, vents, seeps or carcasses are, by far, less numerous than microhotspots constituted by smallest biogenic structures, organic aggregates or particulate food. A special attention must thus be paid to the food supply of smallest size, which probably rules general patterns of deep-sea diversity. As for the larger inputs, the occurrence of these modest nutrient sources on the sediment floor is largely spontaneous and ephemeral. At regional scale, emergence of benthic microhotspots can nevertheless follow the seasonality of surface waters or land (Ittekkot et al., 1984). For instance, episodic blooms of phytoplankton can provoke regular episodes of faecal pellets and moults fall (Thiel et al., 1989). In the same way, downslope currents, associated with intense cascading events, bring nutritive particles to the bottom, depending on terrestrial climatic conditions, which can be cyclic (O'Connell et al., 1985). Evidences of seasonal response among deep-sea benthic species are also reported. Concerning the meiofauna, it is interesting to notice some clues of seasonal reproduction cycles (Kitazato et al., 2000; Tyler, 1988), as well as short response to the arrival of phytodetritus on the sea bottom (Bahls et al., 2004; Gooday, 2002a; Gooday and Turley, 1990). The seasonality brings the issue of the predictability for the food pulses with the question whether the deep-sea benthos can predict such events. However, the huge water column, which separates the benthos from the food 20 production zones and which is often disturbed by currents, scatters hotspots on the deep-sea floor and make their occurrence largely unpredictable over space and time. The duration of those minute but common spots is quite short: for most of them, it takes from weeks to months to be drained out their nutritive substance. It has even been shown that bodies of coccolithophorids and macroaggregates of phytodetritus are completely decomposed at the sediment surface within one year (Cole et al., 1987; Gardner et al., 1983). Most ecosystems of the oceans floor appear and disappear with an erratic cadence and have typically shorter life than organisms themselves. Those need thus to cope with fugitive food resources. During the rare opulent periods, energy input into their metabolism has to be maximized, either to be stocked in prevision of scarcity, or to be used immediately for vital processes as growth and reproduction. It is likely that a great part of the deep-sea benthos alternates vegetative periods and short moment of enhanced metabolism. To be able to use a great amount of resources in a short time, many sessile organisms have turn into opportunist feeding behavior by moving from microphagous suspension feeders to macrophagous predators (Gage and Tyler, 1991). The fast and episodic growth observed in xenophyophores (Gooday et al., 1993) could also indicate an evolutionary response to the transitory food pulses from the water column. Bioturbation is another reason why benthic microhabitats briefly evolve and disappear. On its uppermost layer, the deep-sea floor is disturbed by organisms which mix, dig or displace the sediment. Although fauna is sparser in the oceans bottom than in shallow areas, deep-sea bioturbation and its consequences on ecosystems should not be overlooked. Firstly, because deposit feeders must ingest greater quantities of sediment, since the bottom is poor in nutritious organic compounds (Deming and Colwell, 1982; Smith et al., 1986). Secondly, because any slight perturbation of the soil deeply affects the topology of meio- and microfaunal habitats (Meadows and Tufail, 1986). From the smallest organisms’ point of view, environment should be so often disturbed that competition between species should rarely have time to occur. A successful strategy to cope with the transience of resources could thus simply consist in arriving among the firsts at the hotspot and developing as fast as possible. Consequently, benthic communities flourishing on the oceans floor should count many “efficient colonizators”. In the megafauna, echinoderms represent a group particularly fit to rapidly colonize newly available niches or, as in the deep-sea, new hotspot of food resources. Aggregations of sea urchins Echinus affinis have been observed around short-lived patches of phytodetritus (Billett et al., 1983) and spectacular “herds” of holothurians Kolga hyalina have also been reported on phytodetrital hotspots (Billett and Hansen, 1982). In both 21 examples, many specimens from a single species are found to thrive on the ephemeral “open buffet service”. Most of the food resource will probably disappear before other species succeed to colonize the same hotspot, which induces a local low richness. If one of those providential islands would have sustained echinoderms life longer, other species would have had opportunity to colonize it. In the very next step, competition for colonization would have occurred and the local richness would have increased until being proportional to the richness of immigrants. Main part of the diversity found in deep-sea hotspots should thus result from immigration. Extend the durability of a hotspot should have similar consequences on local diversity as an increase in immigration rate. Depending on organisms and on their dispersal ability, a given hotspot should be considered as a young or an old ecosystem with low or high richness respectively. Microorganisms like viruses, bacteria and protists should also possess great skills for colonization, since they have high potential of dispersal, and since they reproduce faster than bigger organisms. Interestingly, microbes represent the greatest proportion of the deep-sea benthic biomass and process the main part of the carbon cycle (Danovaro et al., 2008a). Could the deep-sea taxonomic structure, where species of high dispersal potential prevail, reflect the instability of its ecosystems?

Following the resources availabilities, most of ecosystems from the ocean floor are patchy and transient. Intuitively, the benthic hotspots could be thought to offer a low local species richness. However, their distribution over space and time could also induce evolutionary responses drastically different between taxa.

1.2.3 The deep-sea benthos continuum

The minute, patchy, and ephemeral ecosystems, shaped on the oceans floor by food resources, contrast with the “common matrix” of the abyssal plains, which are vast, homogenous and relatively stable. How this uniform background contributes to the global diversity of the deep sea and how its benthic communities differ from those of the hotspots, will be discussed here.

Compared to terrestrial environments, oceans floor presents globally a great homogeneity over space and over time. The very little fluctuations of physico-chemical parameters such as salinity or temperature, as well as the general lack of light and photosynthesis production, make this habitat globally monotonous and static. Actually, and 22 contrary to what has been previously thought, deep-sea bottoms experience seasonality (Deuser and Ross, 1989) and spatial variability over large scale, such as those induced by deep currents and storms (Hollister and McCave, 1984). However, regarding the tremendous dimensions of deep sea, those disturbing events can be rightfully considered as isolated and reversible. At small scale, the situation is similar since physical heterogeneities, so numerous as they can be, will remain sparse and will cover a much smaller area than the homogenous part of the sediment. For instance, the surface of abyssal seabed covered by visible traces from bioturbation has been estimated at less than 4% (Laughton, 1963), which reflects not only a global homogeneity but also a relatively high stability, since those traces are known to be quite persistent in deep-sea sediment (Rowe, 1974). At longer term or at geological scale, the stability of the oceans floor is more questionable. Some variations over thousands of years in the deep-sea benthic diversity have been found to coincide with glaciations cycles (Cronin and Raymo, 1997). However, the huge buffering volume of water and the general oligotrophic conditions should reduce the amplitude of any climatic or biologic variation. Therefore, even at scales encompassing evolutionary processes, ocean floor is relatively stable compared to terrestrial ecosystems and should tend to fulfill the equilibrium hypothesis. Sanders attempted to explain the high diversity, which can be found in the deep sea, with the stability-time hypothesis (Sanders, 1969). According to this theory, deep-sea environment is sufficiently stable to enable species specialization with regards to the predictable resources, allowing them to coexist in complementary niches. This is in agreement with observations made on trilobite fossil records, which indicate a gradual evolution into highly specialized morphologies (Sheldon, 1996). Indeed, such situation would not be possible in a frequently disturbed environment, which should rather lead to less differentiation between species and to few similar generalists. Another view is that low productivity of the deep sea induces a high diversity by reducing rates of interactions (Van Valen, 1976). The negative correlation between primary production and diversity in coral reefs supports the idea that species interaction would reduce differentiation mechanisms and thus few interactions would lead to a high species richness (Fraser and Currie, 1996). Finally, what could also predict or explain the cases of high diversity found in the deep sea is its wide area. Broadly distributed species should be less incline to extinction after a disturbing event, since there is higher chance that refugia exist somewhere in their distribution area (Abele and Walters, 1979). Unfortunately, none of those theories can be experimentally tested. Because the sampling efforts are too poor and the oceans floor is too vast, there is no experimental access to the global pattern of the 23 deep-sea benthic diversity. Indeed, there are extremely few chances that the set of species found in a sample recovered from the deep-sea would actually be representative from an overall regional richness for instance. For that reason, it is impossible, only from observations of local diversity, to conclude about global diversity patterns of the oceans floor. Numerous studies have reported high species richness in the deep-sea sediment (Grassle and Morse- Porteous, 1987; Gray, 2002; Rowe et al., 1982; Sanders, 1968) or increasing richness with depths (Levin et al., 2001; Rex, 1983) but also many others have presented opposite results, such as low richness in the abysses (Rex, 1973), decreasing diversity with depth (Etter et al., 2005), or even a maximum diversity at intermediate depth (Boucher and Lambshead, 1995; Etter and Grassle, 1992). This confusion may be induced by an extremely high Beta diversity between benthic samples (Danovaro et al., 2008c), but also by the complexity of the mechanisms regulating deep-sea diversity. Why should one single driving force prevail on other diversification processes? Finally, even if biologists disagree on how the lack of perturbation could regulate diversity in the oceans floor, they generally recognise that the relative stability of the deep-sea bottoms should somehow increase its global richness or should be, at least, a contributing factor.

Having presented the patchy hotspots of the deep sea with their predicted low local richness and their common and stable background, which should theoretically lead to high diversity, it is now the right time to discuss how these two basically different kinds of environment are connected, and how their connections are modeling the diversity. Until recently, these questions remained difficult to address, not only because the deep-sea sampling was too poor and inappropriate, but also because scientific interest was focused on local causes of diversity rather than on regional processes. However, latest studies showed that local species richness depends largely on regional diversity (Tsurumi, 2003; Witman et al., 2004). In the young (disturbed) ecosystems of the oceans floor communities are supposedly not saturated. The regional pool of migrants should thus play a major role in the construction of their composition and abundance. Therefore, local deep-sea diversity should not be regarded as only resulting from small scale biotic and abiotic processes but also, and perhaps above all, as permanent ongoing colonization from regional species. To colonize any hotspot of food resource, organisms must, firstly, reach this island and then, establish a community in it. There are basically two ways to access the spot: by chance or by means resulting from selection. Some organisms have improved strategies to search such oases. The

24 deep-sea shrimps Rimicaris exoculata , for instance , developed infrared receptors probably to detect heat emissions from vents (Van Dover, 2000). An organism can also find itself close to a new hotspot by accident. A second important issue, involving selection mechanisms, consists in the dispersal potential of species. Organisms with planktonic stages or with larvae of extended lifespan will increase their chance to passively meet special features of the bottom. The lifespan for a larva of tubeworm R. pachyptila has been estimated to average 38 days, which allow, in the East Pacific Rise region, a maximal dispersal of 100 km according to the local hydrodynamic conditions (Adam et al., 2001). Two models of dispersal have been proposed to explain the gene flow pattern within species: the “island model” and the “stepping-stone model” (Vrijenhoek, 1997). In the island model (Fig. 1.2.1B) individuals disperse from a well-mixed pool of migrants, so the gene flow between colonies should not vary with geographical distance (Slatkin, 1993; Wright, 1931).

A Stepping-stone model

B Island model

Figure 1.2.1. Models of populations dispersal and gene flow. (A) The Stepping-stone model is appropriate for species with limited dispersal ability, the rate of gene flow between colonies declines with increasing geographical distance. (B) The Island model is appropriate for species with long-distance dispersal ability, the rate of gene flow between colonies is independent of geographical distance. From Vrijenhoek, 1997.

According to the stepping-stone model (Fig. 1.2.1A), dispersal occurs predominantly between neighboring colonies and gene frequencies should decline with the number of steps

25 between colonies (Kimura and Weiss, 1964). This situation is similar to the “isolation by distance” model in the case of continuously distributed species (Wright, 1943). Organisms with limited dispersal potential should thus follow the stepping-stone model and present a gene flow declining with the distance. In contrast, species with high dispersal potential (for instance with long-lived planktonic larvae) should follow the island model and should not show any gene flow variation with distance (Slatkin, 1993). Both island and stepping-stone models have been frequently used to describe dispersal between hydrothermal vents but they should basically fit to colonization patterns of any kind of hotspots such as biogenic structures, phytodetritus or organic particles that have sunk to the bottom.

Since most of the deep-sea microhabitats are patchy and ephemeral, they should favor species with great colonization skill and thus, with high dispersal potential. Moreover, the multiple extinction/colonization steps associated with the transient hotspots should affect the genetic structure of metapopulations (groups of populations spatially separated but still interacting at some level). Low or high dispersal potential should respectively increase or decrease genetic diversity between populations. Vrijenhoek has introduced the term of “occupancy” as a proportion of sampled sites, where a particular species can be found (Vrijenhoek, 1997). He predicted that species with high occupancy should have high probability of colonization and low probability of local extinction. Therefore, according to him, high-occupancy species should retain more genetic diversity (within a single population) than low-occupancy species. Vrijenhoek’s observations on hydrothermal vent communities indicate indeed that high-occupancy species have higher level of genetic diversity (between specimens from the same population) and tend to occur earlier in a new vent, while reverse is true for low-occupancy species (i.e. lower genetic diversity and late occurrence during succession). The oligotrophic deep-sea benthos continuum should be thus regarded as a transition space between two hotspots or as a way followed by organisms to reach a place of interest. Thanks to the great research work made on the very limited samples available, diversity patterns in the deep-sea can be regarded, with indulgence, as slightly less obscure. However, diversification processes remain a complete mystery. Even in deep-sea ecosystems extensively studied, the causes of present species richness still cannot be determined, neither their future evolution can be predicted. Dispersal potential seems to be a key factor for the success of some deep-sea species. The core questions asked by the deep-sea biologists are:

26 “How many species are widely distributed?” and “How far a species can be dispersed?”. Actually, it is not the point to decide whether taxa tend to be ubiquitous in the deep sea. Examples of deep-sea species with clear biogeographic pattern (Brandt et al., 2007), as well as examples of globally distributed species (Lara et al., 2009) can be found in literature. The real issue is rather to determine which species tend to be ubiquitous and which evolutionary mechanisms are increasing the number of highly dispersed species. Recently, another point that has been heavily discussed concerns the possible reduction of species number by ubiquity. If some species are not restricted by geographical barriers, they should also not experience diversification. This hypothesis has been rejected by many of the “everything is everywhere” supporters (Whitfield, 2005). In that sense, the small Prasinophyceae Micromonas pusilla has been shown to present high genetic diversity revealing separate lineages, among which some are clearly ubiquitous (Slapeta et al., 2006). This study supports the idea that a globally dispersed species can experience speciation without geographical isolation, possibly by adaptation to different ecological niches. Many elements converge to show that the most ubiquitous species are also those with the most numerous representatives. However, it is unclear if specimens abundance lead to ubiquity or if ubiquity allows success in the deep sea and thus, induces high abundance. This non trivial question should find a hint to an answer by investigating fluctuations over time of local species richness, occupancy and abundance. Obviously, the best candidates for such a monitoring of the diversity are to be found among microbes, since they have great dispersal ability, and since they reproduce quite fast. In 2006, Pedros-Alio pointed out that even the right order of magnitude for the microbial diversity is unknown. He also proposed that this diversity can be separated into “dominant” and “rare” species (Pedros-Alio, 2006) (Fig 1.2.2). The dominant species, also called “core species” would consist in the most abundant taxa and would be responsible, in a given ecosystem, for the main carbon and energy flows (Magurran and Henderson, 2003). The remaining species, called “rare species”, have a low abundance and weak contribution to those flows. Locally, it has been shown that there are extremely few dominant microbial species compared to the huge number of rare species (Sogin et al., 2006). Pedros-Alio proposed that the dominant species are in active growth mode, because they are well adapted to the ecosystem. However, they also suffer predation and viral lyses, since they are numerous. The rare taxa are recruited through immigration, because they are not growing actively. Moreover, the long tail of those “occasional taxa” would not be subject to such 27 losses. Indeed, viruses randomly prey on organisms they encounter having thus very low probability to prey on rare taxa (Thingstad, 2000) and predators prefer to feed on actively growing populations (Pernthaler, 2005).

C Global Extinction dispersal

Active growth Death Immigration Predation, viral lysis Individuals (N)

Abundant Taxon rank Rare

Figure 1.2.2. Diversity of microbes. Plot of individuals number versus taxa, ranked according to their respective abundance. The total curve represents biodiversity and is postulated to be composed of two sections: diversity of abundant taxa or “core taxa”(in red) and diversity or rare taxa or “seed bank” (in blue). From Pedro´s-Alio, 2006.

This would explain why the rare taxa are so numerous. The crucial point of this theory is that a species can be promoted from the “rare” zone of the curve into the core taxa if the conditions become suitable for that species. Therefore, rare taxa could be considered as a “seed bank” containing potential future dominant species. These assumptions are particularly interesting for the deep sea issue, not only because microbes are a major component of the benthos, but also because recruitment through immigration is a key mechanism shaping the diversity of patchy and ephemeral hotspots (as we have seen before). A widely dispersed species should have higher chance to be found in many samples, at least within the rare taxa. Taking this logic to extremes, if all of the bottoms species would tend to be ubiquitous, each sample would contain the total species richness of the deep-sea benthos. The oceans floor could be thus regarded as a global ecosystem comprising, in one hand, a set of “active subunits” (the patchy hotspots) with high nutrients availability, high abundance, and large flows of carbon and energy; and, on the other hand, a background matrix with low activity and low abundance (the benthos continuum). The benthos continuum could be represented as 28 a kind of highways network that each species would take, waiting to find a nice hotel to sleep few nights. It is likely that competition should not occur in the continuum, i.e. among rare species. The matrix, which by definition remains undisturbed, may rather be the place of a slow genetic drift, which would increase theoretically the global species richness in a continuous way. Competition could possibly occur in the hotspots between dominant species. However, most of the hotspots are probably too ephemeral for the competition to occur in situ, during the short period of resources availability. It might be that selection actually occurs between dominant species of different hotspots in the global system. That is why, once more, the continuum and the hotspots should be considered as a whole. Finally, it has been asked whether those rare species are ecologically relevant. This point remains unsolved but some evidences, notably based on RNA sequencing, seem to indicate that the rare biosphere can play an important role, not only as active gene pool but also as mediator in elemental cycles (Hamasaki and Taniguchi, 2009; Moeseneder et al., 2009).

Oligotrophy allows the patchiness of ecosystems on the sea floor. Organisms may not have the same chance to reach one of the benthic ephemeral oases. However, because hotspots occur unpredictably, most species should find the sustenance that will guarantee the survival of, at least, some of their representatives. If high dispersal is common on the oceans bottoms, deep-sea should be regarded as a global ecosystem with a patchy activity over space and time, inducing selection for dominant species. It also might be that, out of the active spots in the stable matrix, extremely numerous species are preserved from extinction and experience a slow genetic drift increasing the global species richness of the deep-sea.

29 1.3 The foraminiferal model

1.3.1 General

From Antiquity, and probably even before, foraminifera have attracted attention by their lenticular tests fossilized in the sediment. Herodote (V century before J. C.), Strabon and Pline the Older (both around J. C.) have reported numerous of those small eerie stones (tests of Nummulites) in the limestone of the Giza pyramids. Actually, they did not recognize their organic origin, which was established much later by Leonardo da Vinci (in the XV century) or by Agricola (in the XVI century). At the beginning of the XIX century, Alcide d’Orbigny proposed the first classification of Foraminifera, literally “hole bearer” (from Latin “ foramen ” meaning hole and “ferre ” meaning bearing) and included them among mollusks (d 'Orbigny, 1826). Nine years later, Dujardin (1835) showed that foraminifera were in fact single-cell organisms and placed them among amoeboid protozoa (Sarcodina). Several different classifications of foraminifera were established based on morphological characteristics (Cushman, 1928; Loeblich and Tappan, 1988; Neyumayr, 1887; Schubert, 1921; Schultze, 1854). One of the most recent ones distinguished 12 sub-orders and 2446 genera according to the composition and the structure of the test (Loeblich and Tappan, 1988). Several molecular phylogenetic studies demonstrate the inaccuracy of this taxonomy, but no new updated higher-level classification was published yet (Pawlowski 2009). Currently, foraminifera are placed in the supergroup of Rhizaria (Adl et al., 2005) based on phylogenomic data (Burki and Pawlowski 2006), but their relationships with other representatives of this supergroup remains controversial (Pawlowski and Burki 2009).

First fossilizable foraminifera, including multilocular agglutinated species, appeared around 520 Myr ago during Cambrian (Culver, 1991). However, the divergence of the foraminifera from their rhizarian ancestors have been estimated, based on local molecular clocks, to have occurred between 690 and 1’150 Myr (Pawlowski et al., 2003). Early non- fossilizable foraminifera (Monothalimida) were naked or presented organic or agglutinated test. The multilocular calcareous orders (Rotaliida and Miliolida) evolved about 350 Myr ago (Pawlowski et al., 2003).

30 Modern foraminifera are mainly marine although there are examples of fresh water (Holzmann and Pawlowski, 2002) and terrestrial (from damp rain forest soil) species (Meisterfeld et al., 2001). Around 40 planktonic morphospecies are described, but they may represent a much higher number of molecularly distinct entities (Kucera and Darling, 2002). Benthic species are morphologically far more diverse (more than 4’900 described) but their richness is also largely underestimated, particularly that of monothalamous organic-walled species (Pawlowski et al., 2005).

Foraminifera are basically single-celled organisms characterized by a network of granuloreticulopodia. Some of the biological functions of the cell, as well as its interactions with the environment, are conducted by those anastomosing pseudopodia. They enable fixation to the substrate or locomotion; they are used for the feeding process allowing resources input and metabolic wastes output; they participate in particles transport for building the test; and finally, they are involved in reproduction, predation or simply interactions with other organisms. A dynamic system of microtubules ensures bidirectional movement of reticulopodia. The granules are moving inside and on the surface of the podia and mostly consist in mitochondria and various vesicles required for aerobic respiration and metabolic transportation (Sen Gupta, 1983). Benthic species living within the photic zone are mainly grazing on diatoms and other algae, while those below the photic zone feed on phytodetritus and bacteria. The food is captured by invagination of the pseudopodial membrane forming large digestive vacuoles. Those vacuoles are then transported through the pseudopodia to the intra test cytoplasm where the digestion occurred. Most foraminifera possess an outer protective layer which can be organic (mainly proteinaceous), agglutinated (with mineral particles embedded into an organic matrix or a calcareous cement), calcareous (composed of secreted calcite or aragonite crystals) or finally siliceous (a minority). Although the foraminiferal test has been extensively studied, its precise chemical composition and its detailed construction process remain poorly known. Depending on species and its environment, foraminiferal test can be extremely diverse. It is basically composed of single or interconnected multiple chambers and possesses generally one or several apertures. Naked foraminifera have simply developed a particularly thick layer of glycoproteins and polysaccharides to protect their cytoplasm. Foraminiferal growth and reproduction are not always well understood, especially for the deep-sea species. Some foraminifera possess a single and large nucleus (up to 100 m in diameter) while others have hundreds or thousands

31 of small nuclei (less than 10 m in diameter) distributed in the whole cytoplasm. The foraminiferal life-cycle is quite complex and consists schematically in an alternation of sexual and asexual generations. During sexual reproduction, uninucleate gamont produce amoeboid or flagellated gametes, which fuse to form zygotes, and become then diploid agamonts. Nuclei of each mature agamont undergo two meiotic divisions, before its cytoplasm fissures and produces embryonic haploid gamonts. Foraminifera can follow three types of sexual reproduction: gametogamy, which takes place outside the test in the sea water; gamontogamy, which occurs by a direct contact between gamonts; and autogamy, which is a kind of autofertilization inside the test. Finally, this classical cycle can be sometimes modified. Agamonts can undergo mitotic divisions instead of meiosis, and the asexual cycle can be repeated several times. Such complex life cycle can have consequences on the local gene flow, but nothing is known about this aspect.

Compared to other free-living protists, the phylum of Foraminifera has been extensively studied regarding morphology, ecology and evolution of its representatives. Regrettably, scientists have not been attracted by foraminifera only because of the poetic shapes of their test or because their amazing diversity was offering multitude of opportunities to describe new species. Actually, foraminifera stir up interest in highly diverse fields of biogeosciences. First of all, the abundance, the diversity, and the continuity of foraminiferal fossils record, which counts about 50’000 species described (Debenay and Pawlowski, 1996), make them the most important proxies for paleoceanographic studies. Isotopic and chemical composition of their tests as well as their species assemblage can reflect the age of sedimentary strata and bring precious information on past environmental parameters such as temperature, oxygen concentration or primary productivity. Those inferences are based on observations of living foraminifera at different spatial scales: from microhabitats to regional patterns (Gooday, 2003). Concerning benthic species, special efforts have been devoted to relate organic carbon fluxes to the composition of foraminiferal assemblages (Wefer et al., 1999; Weinelt et al., 2001). Total foraminiferal standing stocks are considered as good indicators of food availability (Douglas, 1981; Phelger, 1976), while particular species would tend to be associated with certain levels of carbon flux (Altenbach et al., 1999; Fontanier et al., 2002). Then, foraminifera are also recognized for their economic importance in the petroleum industry, which largely rely on microfossils to find potential oil deposits (Broadman et al., 1987).

32 Benthic foraminiferal assemblages are also of great interest for marine ecology. Because they are ubiquitous, small and numerous enough to be statistically analysed, they represent excellent bioindicators (Kramer and Botterweg, 1991). For instance, larger symbionts-bearing species can attest of coral reefs health (Hallock, 2000). Shallow water foraminifera have been extensively studied for pollution assessment (Scott et al., 2001; Yanko et al., 1999). Numerous investigations showed they were extremely sensitive to a wide range of pollutants as domestic and agricultural wastes, trace metals or oil spill (Alve, 1995; Armynot du Châtelet et al., 2004; Buckley et al., 1974; Ellison et al., 1986; Frontalini and Coccioni, 2008). Scientists recommend their general use for environmental monitoring (Debenay et al., 2000).

1.3.2 A wide benthic taxa for a wide range of niches

"The case of the three species of protozoan (I forget the names) which apparently select differently sized grains of sand, etc., is almost the most wonderful fact I ever heard of. One cannot believe that they have mental power enough to do so, and how any structure or kind of viscidity can lead to this result passes all understanding." Charles Darwin, letter to W.B. Carpenter, 1872 (Darwin and Seward, 1903).

The first and the most obvious characteristic of benthic foraminifera is their high species richness. Estimations of modern species number range from 1’000 to 10’000 (Boltovskoy and Wright, 1976; Jones, 1994; Minelli, 1993; Murray, 2007; Vickerman, 1992). Benthic foraminifera are not only rich in term of species number, but also amazingly diverse considering their morphology and ecology. Foraminifera are one of a few groups of protists with a size ranging from micrometers to centimeters and species scattered between microfauna and macrofauna. Micro- and nanoforaminifera have been reported in the smallest fraction of the sediment with some mature specimens smaller than 30 m (Gooday, 1995; Pawlowski et al., 1993). In contrast, some giant agglutinated species, like xenophyophores, can reach 25 cm in diameter (Tendal, 1990). The shape, the structure and the composition of the test also present huge variations. The acquisition of granuloreticulopodia in the early history of foraminifera must have largely participated in their diversification. Indeed, this new type of pseudopodia is likely to have enhanced their ability to manipulate particles and thus, to construct various types of tests (Travis and Bowser, 1991), providing efficient protection against predators and environmental conditions, as well as a compartment to store food and to protect juveniles (Lipps, 1983). The large radiation of early unilocular foraminifera revealed 33 by molecular study (Pawlowski et al., 2003), could directly result from the successful evolutionary pathway of the tested species. Each morphology has therefore to be regarded as an evolutionary response to an ecological niche and thus as a clue for biotic and abiotic pressures. In this perspective, some authors showed obvious relationships between foraminiferal morphologies and their way of life, their microhabitats or the nature of substrate they were living on (Corliss and Chen, 1988; Kitazato, 1988a, b). Since trophic pressures are obvious diversification driving forces, morphological richness could be overviewed through the different food resources exploited by each morphospecies. The wide variety of feeding behaviors well reflects the amazing richness of the phylum (Goldstein, 1999). Some of the large species occurring in the shallow reefs shelter photosynthetic symbionts within their hyaline test, which lets the light through. In some cases, symbionts only provide a small fraction of the energy input, as for Archaias angulatus and Sorites marginalis , which still get their main resource by feeding on unicellular algae (Lee and Bock, 1976). In other cases, symbionts provide their hosts with most of the organic carbon they require, as for Heterostegina genus (Röttger et al., 1980).

A clear relationship between the trophic behavior and the morphology of agglutinated foraminifera has been established by Jones and Charnock (1985), who distinguished four morphological groups corresponding to different feeding strategies: 1) the suspension feeders, fixed and standing up on the soil with branched or tubular shape; 2) the surface feeders, which can be grazers, detritivorous or omnivorous and which have globular or coiling shape; 3) the diggers, which are infaunal detritivorous or herbivorous, typically elongated or ribbed; 4) the herbivorous epiphytes, with biserial and trochospirally coiled shapes. Osmotrophy (assimilation of dissolved organic matter through cell surface) is a quite common feeding strategy among deep-sea foraminifera (DeLaca et al., 1981) and could reflect one of their ways to cope with oligotrophic environment (Lipps, 1982). Parasitism should also be mentioned as a possible trophic adaptation of benthic foraminifera. For instance, Hyrrokkin sarcophaga is a well known ectoparasite of bivalve and sponges (Cedhagen, 1994), while Fissurina marginata has been described as an ectoparasite of Discorbis vilardeboanus (Le Calvez, 1947) and Planorbulinopsis parasita was observed to live as an endoparasite inside the test of Alveolinella quoyi (Banner, 1971). Development of morphological features driven by trophic reasons is thus perfectly illustrated by the wide morphospecies richness of benthic

34 foraminifera, especially for the deep-sea species exposed to low or transient concentrations of nutrients.

In the same way, oxygen concentration in the water and in the sediment, which is closely linked to organic matter availability, may have impact on evolution of foraminifera. The correlations between foraminiferal morphology and different oxygen supply, as well as species occurrence in particular oxycity, have been studied (Kaiho, 1994; Schönfeld, 2001). Some calcareous species, notably within genus Bolivina , present thinner and less ornamented walls, enhancing oxygen penetration where the bottom-water oxygen is low (Douglas, 1979, 1981). In general, an increasing proportion of hyaline calcareous species compared to agglutinated taxa are observed at poorly oxygenated bottoms (Gooday et al., 2000; Levin et al., 2002).

Finally, this short and incomplete overview of relations between benthic foraminiferal morphologies and environmental conditions should also include investigations on hydrographic parameters. Correlation has been shown between composition and shape of agglutinated foraminiferal tests on the one hand and bottom currents and physical disturbances on the other hand. Tranquil environments would be dominated by finely agglutinated forms with delicate and branching tests, while disturbed areas with strong currents are inhabited by robust, coarse-grained and often infaunal species (Kaminski and Schröder, 1987). However, it is not clear if some of those morphological features result from the hydrographic conditions or rather from nutrients distribution patterns induced by hydrography.

The plasticity of benthic foraminiferal tests is a good reason to be extremely careful with species identification based only on morphology. It is not always possible to find a trait, which can be relevant regarding the origin of a species, and which does not result from homoplasy. Moreover, the ecophenotypic variations are so important in some taxa that it is difficult to define species boundaries. For that reason, alternative methods are required to complete the morphological approach of the diversity. Molecular tools can bring another piece of information likely to enhance the accuracy of an evolutionary scenario. The application of molecular analysis to assess the foraminiferal diversity is quite recent (Pawlowski et al., 1994) and based, until now, exclusively on nuclear ribosomal RNA genes (Pawlowski, 2000). Mitochondrial genes are not yet available for foraminifera (Pawlowski, 35 2009) and the only other coding genes so far investigated (actin, tubulin and ubiquitin) are too conserved for the species richness assessment (Flakowski et al., 2005). The rDNA has been chosen as a molecular marker of forams, as well as many other organisms for two main reasons. The first one is the high number of copies of rRNA genes, which facilitates amplifications by polymerase chain reaction (PCR) from a single cell. The second one is the different levels of variability offered by various regions of ribosomal genes. For instance, SSU alternates conserved and variable regions, while ITS is usually more variable. Most of molecular foraminiferal studies focus on the 3’ fragment of the SSU rDNA (Pawlowski, 2009). Indeed, this fragment provides on the one hand some regions, which are stable enough to design foraminifera-specific primers; and on the other hand variable regions, which enable distinction between species or even between populations. Since foraminiferal SSU provides both regions of high stability and variability, it offers a relevant set of molecular clues to investigate species history and their identification. In this respect, benthic foraminifera differ from many other eukaryotes with much slowly evolving SSU. However, it has to be noticed that foraminifera present sometimes high intraindividual polymorphism within their ribosomal genes copies. One single specimen can display a sequence divergence higher than 1% (Pawlowski, 2009), which complicates the determination of species-specific sequences (Holzmann and Pawlowski, 1996), and which seriously compromises population genetics studies applied to foraminifera. Nevertheless, rDNA-based phylogenetic analyses have shown, on several occasions, their efficiency to resolve cryptic species issue or, on the contrary, cases of overestimated diversity (Hayward et al., 2004; Holzmann and Pawlowski, 1997; Pawlowski et al., 1995; Tsuchiya et al., 2003). So far, molecular investigations converge to show that the species richness of benthic foraminifera, partially reflected by an already amazing wide set of morphologies, is still underestimated.

36 1.3.3 The typical deep-sea citizens

As we have seen before, foraminifera form a large phylum and can be found in all marine habitats that have been studied, no matter the depth (Todo et al., 2005) or the latitude (Bergsten, 1994; Brandt et al., 2007). Benthic species seem to be especially successful in the deep-sea where they can reach, in some areas, more than 50% of biomass (Gooday et al., 1992; Snider et al., 1984). Abundance of calcareous taxa appears to decrease with depth beyond the shelf break (Hughes et al., 2000; Kurbjeweit et al., 2000). Below the carbonate compensation depth (CCD), organic walled and agglutinated species dominate the benthic foraminiferal assemblage. They play a main role in the carbon cycle (Kitazato et al., 2000; Moodley et al., 2000) and occupy a central position in the deep-sea bottom ecosystems (Sen Gupta, 1999). Finally, with their wide variety of ecological niches, benthic foraminifera encompass all the different “deep-sea ways of life” and appear to be particularly suitable for studying the dispersal ability and subsistence under food restrictions.

Feeding strategies of deep-sea foraminifera can be considered as different ways to cope with patchy and ephemeral resources. There are two general and basically opposite trends in their feeding behaviour: specialization and opportunism. Particular species tend to be associated with either higher or lower levels of organic fluxes (Altenbach et al., 1999; Fontanier et al., 2002; Gooday, 2003). This could suggest that, under strong food limitation or stable conditions, competition occur and specialized species dominate. Some cases of such highly specialized foraminifera; as those shaped to perform suspension feeding or osmotrophy; have already been evocated in the previous section. Many of those specialized species are monothalamous agglutinated forms that present fragile tests of sometimes unusual shapes. They have been preferentially observed in places of constant and limited organic fluxes where environmental conditions were stable (Gooday, 2003). On the contrary, other foraminiferal species seem to dominate when food become suddenly abundant, possibly because they are extremely fast to exploit the resources and develop rapidly on the eutrophic spots. This hypothesis would be congruent with the observations of species dominance shift during seasonal nutrient inputs (Bahls et al., 2004; Gooday, 2002a; Gooday and Lambshead, 1989), sometimes coupled with reproduction events (Kitazato et al., 2000; Ohga and Kitazato, 2003). Generally, occurrence of hyaline calcareous rotaliid foraminifera can be more strongly correlated with the organic matter than that of agglutinated taxa (Gooday et al., 2008; 37 Gooday, 2003). Moreover, Betram and Cowen reported, during artificial substrates colonization experiments, that the settlement rate of agglutinated species was uniform over time, whereas calcareous ones presented higher rates during periods of enhanced particles flux (Bertram and Cowen, 1999). Since some opportunist species show a greater response to food input, it could be thought that their selection would have occurred mainly through food type rather than through habitats. Some authors emphasized the important issue of different food preferences for deep-sea benthic foraminifera (Kitazato et al., 2003; Nomaki et al., 2005a; Nomaki et al., 2005b). It would actually concern the decomposition state of nutrients that have sunk to the sea floor rather than their precise nature or composition. Indeed, among calcareous taxa, some species seem to prefer degraded and labile phytodetritus, while others appear associated with more refractory material (Caralp, 1989; Fontanier et al., 2002). If these observations would reflect a general trend of opportunist species, it would have radical consequences on their dispersion. According to some studies in Eastern Pacific Ocean, calcareous species distribution patterns are dominated by a response to surface ocean productivity (Loubere, 1996; Loubere and Fariduddin, 1999). Since degradation level of nutrients depends largely on the depth rather than on the geographic position, those opportunist species could be rightfully expected to have bathymetrically restricted broad geographic ranges.

Still in order to hunt for possible clues of benthic foraminiferal adaptation to the deep- sea environment, their dispersal ability should be considered. Using once more the simplistic distinction between opportunist and specialized species, it could be proposed that the two kinds have different trends in dispersal ability. Since opportunist species have greater skills for colonization of newly formed food sources, they should also be particularly efficient to reach those spots and thus, should tend to be highly dispersed. One active and three passive ways of dispersal have been recognized in foraminifera (Alve, 1999; Murray, 2006). The active dispersal, occurring via self-locomotion, is unlikely to have much impact at largest scales. By contrast, benthic foraminifera can be passively dispersed by getting into suspension in the water column and being transported, potentially over long distances. This dispersal mode can apply to the first stages of development (gametes, zygotes, propagules or juveniles), to species having temporary planktonic phase, or even to the small-size adult forms. Passive dispersal of benthic foraminifera can occur by water masses displacement (with currents for instance), by sediment displacement (with canyons avalanches), or with biotic activities (as

38 for parasitic or epibotic species). Because reproduction and development cycles of deep-sea foraminifera are still largely unknown, their respective contribution to dispersal potential remain purely speculative. Nevertheless, even if gametes and zygotes may not survive over a long periods of transport (Murray, 2006), propagules could tolerate greater distances (Alve and Goldstein, 2002, 2003). Those hypotheses are extremely difficult to test in the deep sea by in situ experiences. It is thus essential to seek an accurate way to assess somehow the general trends of foraminiferal dispersal ability. The most obvious way to enquire this feature could consist in observing their distribution at large scale.

A significant part of the research on foraminiferal biogeography was done by John W. Murray, who recognized four main factors, which could be correlated with the distribution of modern benthic foraminifera: food availability, oxygen concentration, depths and currents (Murray, 1991). After a large revue of species occurrences in the different oceans of the world, it appeared that more than a half of the 938 common morphospecies studied was restricted to one of ten biogeographic regions. Seven species were found in eight regions or more, and three of them (Epistominella exigua , Cibicides wuellerstorfi and Globocassidulina subglobosa ) occurred in nine of the ten investigated areas. According to Murray’s data, most of the benthic foraminifera would thus have restricted biogeography, which would conflict with the idea of great dispersal ability. However, the three species having the wider distribution are characteristic of bathyal and abyssal environment. This might reflect a stronger trend to ubiquity in the deep sea.

Moreover, sampling efforts, especially in the deep sea, probably do not reflect accurately the presence/absence of species. At regional scale, the surface of the collected sediment represents such a small proportion of regional total surface that numerous rare species could easily be missed by erratic sampling. Additionally, the foraminiferal diversity is highly variable at micro and mesoscale (Semeniuk, 2000) and could create considerable bias in a poor sampling (Soetaert and Heip, 1990). Even in the ideal case, where a sampling would perfectly reflect the distribution at the particular time of collecting, it would not mean that the lacking species do not have the ability to occur there. Indeed, ecologists conceptually separate the “fundamental” niche, where a species could potentially exist, from the “realized” niche, where the species really does exist (Hutchinson, 1957). It can be, for instance, that a particular species temporally disappears from a location which however suites it, because it is excluded

39 by other species through competition for food. During days, months or years, no representatives of this species would physically occupy the region until competitive pressure would disappear. For that reason, species occurrence remains poorly informative considering their dispersal potential. It has been suggested that ubiquitous morphospecies may not consist in a single entity but would rather represent a cluster of distinct species sharing the same morphology (Haynes, 1992). Molecular studies confirm this suggestion, identifying large number of cryptic species in shallow water foraminifera (Pawlowski and Holzmann, 2008), but nothing was known about the genetics of deep-sea species before this work started.

Searching for dispersal clues among benthic foraminifera appears finally as a quite risky investigation based mainly or only on distribution studies. Unfortunately, distribution assessment depends highly on sampling, which is obviously too poor to be relevant for deep- sea foraminifera. It is virtually impossible to demonstrate that a particular species does not occur in a particular region. However, if widely dispersed or ubiquitous species actually exist, it should not be a task out of reach to find one of them. Therefore, searching for cosmopolite species rather than for biogeography pattern could be a more relevant strategy to begin with.

Benthic foraminifera offer not only an amazing species richness to explore but also taxa of fundamentally different evolutionary paths. If there are some specific patterns of speciation in the oceans floor, they should be found among foraminiferal species. For that reason, biologists should pay a very special attention to those typical deep-sea citizens. Indeed, identify the foraminiferal evolutionary response to the patchiness and transience of food could highly contribute to understand general biodiversification processes in the deep sea.

40 1.4 Objectives and impacts

This thesis aims to consider the patterns of the deep sea biodiversity through the benthic foraminiferal model.

The global objective of this work is to improve the general knowledge on the species richness of the deep-sea bentic foraminifera by two different approaches. The first one consists in separately investigating particular species or group of species in order to reveal their respective contribution and impact toward species richness of the deep sea. The second approach is broader and aims to test some hypotheses on the general patterns of foraminiferal diversity, based on environmental samples.

The topics addressed in this thesis will be separated into three distinct chapters:

• Chapter 2 aims to highlight the stupendous and overlooked species richness of monothalamous foraminifera, focusing on two remarkable examples. The first study presents the morphology and the phylogenetic position of a new genus from the Nazare Canyon (off Portugal): Capsammina patelliformis . The next paper describes the new genus Shinkaiya lindsayi , bringing the second molecular evidence that xenophyophores belong to Foraminifera. It also includes the analysis of its elemental composition

• Chapter 3 approaches the “hidden” diversity related to benthic foraminifera. The first study was attempting to find, by molecular tools, the origin of komokiaceans but reveals instead the huge eukaryotic richness associated with these organisms. The second part of the chapter is dedicated to the hidden foraminiferal diversity and presents the preliminary results of the first attempt to use massive sequencing to assess the richness of deep-sea foraminifera.

• Chapter 4 concerns the highly debated issue of cosmopolitanism in the deep sea. The first study points out a gene flow occuring between Arctic and Southern Ocean populations of three calcareous common morphospecies. The second paper will show that one of them, at least, could be actually globally dispersed.

Finally, the global results of this research as well as their interpretations and implications will be discussed in Chapter 5, leading to the general conclusions of this thesis and to the perspectives for future investigations.

41 42 Chapter 2 The vast foraminiferal diversity is incompletely explored: monothalamous examples

2.1 Introduction

Monothalamous foraminifera regroup all the single-chambered (unilocular) species having organic test or agglutinated wall. Previous studies emphasized their high abundance in the deep-sea sediment as well as in the soft bottoms of the Polar regions (Gooday, 2002b). Our knowledge of monothalamous foraminiferal diversity remains extremely poor and unsatisfactory considering their obvious ecological importance. This situation reflects both the geographic scarcity of samples and a general lack of interest for those fragile, often hardly recognizable and usually non-fossilizable forms (Habura et al., 2008; Sabbatini et al., 2007). Recent efforts to fill this gap led to the description of several new species (Cedhagen et al., 2009; Cedhagen and Pawlowski, 2002; De Laca et al., 2002; Gooday and Pawlowski, 2004; Sabbatini et al., 2004; Wilding, 2002), provided the first molecular insights into the phylogeny of this group (Pawlowski et al. 2002) and revealed its hidden richness (Pawlowski et al., 2002a; Pawlowski et al., 2002b). Our interest in monothalamous foraminifera was motivated by their long evolutionary history and high diversity meaning this group is likely to provide particularly relevant information about general patterns of diversification in the entire Foraminifera phylum.

Two new genera of monothalamous agglutinated species, Capsammina and Shinkaiya , are presented here with their morphological description and molecular characterization.

The first species, C. patelliformis , was found in the Nazare Canyon of the North East Atlantic Ocean, at bathyal depths, and consists basically in an allogromiid-like cell enclose

43 between transparent plates of mica. This remarkable morphology was never encounter before and is clearly distinct from that of its molecularly closest relatives (crithioninids).

The second species, S. lindsayi , was collected in abyssal North West Pacific Ocean. It belongs to the enigmatic group of xenophyophores, which are sometime extremely abundant at the deep-sea bottom and can display spectacularly large agglutinated test. The description and molecular analysis of S. lindsayi contribute to clarify the phylogenetic position of these multinucleated protists, providing new evidence of their wide richness. Mass spectrometry analyses performed on S. lindsayi revealed high concentrations of metal inside the fecal pellets stored inside its test.

Two additional papers related to monothalamous foraminiferal diversity are presented in Appendixes. The first one concerns the distribution pattern of monothalamous foraminifera from Admiralty Bay, King George Island (Appendix A). Some of them represented a new organic-walled species: Bowseria arctowskii , which is described in the second paper (Appendix B). Both papers also contribute to enhance general knowledge of monothalamous foraminiferal diversity but have not been integrated to the main part of this thesis, since they concern shallow waters species.

44 2.2 The ‘mica sandwich’; a remarkable new genus of Foraminifera (Protista, Rhizaria) from the Nazare Canyon (Portuguese margin, NE Atlantic)

1 2,3 4 5 Andrew John Gooday , Ana Aranda da Silva , Karoliina A. Koho , Béatrice Lecroq ,

Richard B. Pearce 1

1National Oceanographic Centre, European Way, Southampton SO14 3ZH, UK.

2CESAM, Departamento de Biologia, Universidade de Aveiro, Campus universitário de Santiago, 3810-193 Aveiro.

3INETI, Departamento de Geologia Marinha, Estrada da Portela, Zambujal 2721-866 Alfragide, Portugal.

4Utrecht University, Faculty of Geosciences, Budapestlaan 4, 3584 CD Utrecht, The Netherlands.

5Department of Zoology and Animal Biology, University of Geneva, Switzerland.

Submited in: Zoological Journal of the Linnean Society

45 Abstract

Based on morphological and molecular characteristics, we describe a new genus and species of monothalamous agglutinated foraminifera, Capsammina patelliformis, from bathyal (1000- 3400 m, rarely at 344 m) water depths in the Nazare Canyon. The test is typically strongly flattened, up to 500 µm or more in maximum dimension, and 30-80 µm thick. It lacks obvious apertures, and is typically composed of 2-3 large, plate-like grains of mica that form the upper and lower surface of the test and are separated by fine-grained, white agglutinated material (‘mortar’) that forms a ring around the cell body. The cytoplasm, visible through the mica plates, is whitish in colour with few obvious inclusions. Analysis of a fragment of the SSU rDNA gene indicates that C .patelliformis belongs in a clade branching with Crithionina delacai, C. granum and an undetermined crithioninid species. However, the divergences between the new species and these Crithionina species range from 19% to 21%, and are therefore too high to classify it in the same genus. Other monothalamous agglutinated foraminifera, including Psammosphera spp., are phylogenetically distant from Capsammina . The new species occupies a shallow infaunal microhabitat, living mainly in the top 0.5-cm of sediment.

Introduction

HERMES (Hotspot ecosystem research on the margins of European seas), an Integrated Project funded by the European Union, aims among other things to investigate the biodiversity of ‘hotspot’ ecosystems around the European margins (Weaver et al., 2004). One main focus of HERMES is on submarine canyons, and particularly on the large canyons that traverse the continental slope on the southern part of the Portuguese margin. These canyons have been studied during a series of HERMES cruises. The most intensively studied is the Nazare canyon, which extends from close to the shoreline to 5000 m depth on the Iberian Abyssal Plain. Arzola et al. describe sedimentary features and processes in the Nazare canyon (Arzola et al., 2008). De Stigter et al. describe modern sediment transport and deposition (De Stigter et al., 2007). A general account of the morphology, sedimentology, physical oceanography and biology of the Nazare canyon is given by Tyler et al. (Tyler et al., in press).

46 Koho et al. (2007) provide an overview of the abundance, species composition, and vertical distribution within the sediment of foraminifera at sites in the axis and on the adjoining terraces of the Nazare canyon at depths from 146 to 4976 m. Among the species they recognise is a peculiar agglutinated form, which they termed the ‘mica sandwich’ because the test is formed from two mica plates. Koho et al. (2007) assign this species to the genus Crithionina. However, our molecular data suggest that it is sufficiently distant from typical Crithionina to warrant the establishment of a new genus . The purpose of this paper is to describe the ‘mica sandwich’ based on HERMES and other material from the Nazare canyon. The description combines morphological features, mainly test characteristics with phylogenetic molecular data.

Methods

Study site Most of our material originated from a 3500-m site located on a terrace in middle part of the Nazare Canyon. This area is characterised by very high sedimentation rates (up to 32.6 g m −2 d −1 , De Stigter et al., 2007). Piston cores recovered from 40–60 m high terraces at ∼ 3500 m water depth reveal thick sequences of dark greenish-brown, bioturbated silt-mud turbidites, rich in black carbonaceous fragments and mica flakes (Azola et al., 2008). Macrofaunal densities at this site are the highest observed anywhere in the canyon (Tyler et al., 2008). The new species was also collected ~1000-m water depth on the terraces of the upper Nazaré canyon. The upper canyon is also influenced by relatively high sedimentation rates; 14.1 g m −2 d −1 at 927-m water depth (de Stigter et al. 2007). The sediments here are generally medium-fine-grained silt with a modal grain size of ~14 µm (de Stigter et al. 2007) and relatively enriched in labile organic matter with a high phytopigment content (García et al. 2007; García and Thomsen 2008). The high organic matter content is reflected in a shallow (generally < 1 cm depth in sediment) oxygen penetration depth in the sediments of the upper Nazare Canyon (Epping et al, 2002).

47 Sample collection and treatment Samples were collected during R.R.S Discovery cruise 297 (July 27 to August 16; Weaver, 2005), R.R.S. Charles Darwin 179 (April 14 to May 17; Billett, 2006) and legs 2 and 3 of the R.R.S James Cook cruise 10 (June 3 to July 7, 2007; Weaver and Masson, 2007) using either pushcores deployed by the Isis ROV or a megacorer equipped with core tubes of 10-cm diameter. As soon as possible after collection, the surficial sediment (usually upper 2 cm) was sliced off, sieved on a 125 m in chilled water and selected foraminifera, including specimens of the new species, extracted under a binocular microscope. Specimens for morphological study were fixed in buffered 10% formalin and stored in 2 ml cryovials. Specimens for molecular analyses were transferred to microtubes containing 60 ml of guanidine DNA extraction buffer. Additional material for morphological study was collected during R.V Pelagia cruises 64PE138 (May 1999) and 64PE236 (May 2005) using an 8+4 multiple corer developed by Oktupus GmbH. Cores (6-cm diameter) used for foraminiferal analyses were immediately sliced on board down to 10 cm depth in sediment; the top 2 cm were cut into 0.5 thick slices and the rest of the core into 1 cm slices. The samples were stored in a solution of rose Bengal in 96% ethanol (1g/L) until washed and sieved (63-150 µm, >150 µm) in the laboratory several months later. The well-stained specimens were picked from the top 5 cm of sediment (>150 µm fraction only). Details on sampling sites are presented in Appendix C, Table C1.

Morphological methods Light photographs of the new species were taken in water using a SLR digital camera (Canon EOS 350D) attached to either a Leica binocular microscope or an Olympus BH-2 compound photomicroscope. Test measurements were made to the nearest 10 mm using an eyepiece graticule fitted to a Wild M50 dissecting microscope. Selected specimens were examined by scanning electron microscopy (SEM) using either a LEO 1450VP SEM in Southampton or an XL30FEG SEM in Utrecht. The Leo 1450VP SEM is a tungsten filament SEM from which both secondary electron and backscattered electron images were acquired. EHT settings of 15kV and 30kV were used with nominal probe current settings of 750pA and 31pA respectively and a working distance ranging from between 12–19 mm. Elemental microanalysis was undertaken using a PGT light element detector.

48

Molecular methods DNA of six specimens from three different stations was extracted using guanidine buffer: two from station 91 (DNA 10068), two from station 101 (DNA 10069) and two from station 127 (DNA 10070). A fragment of the SSU rDNA gene was amplified by PCR with the primer pair s14F3 (5’ACG CA(AC) GTG TGA AAC TTG) and sB (5’ TGA TCC TTC TGC AGG TTC ACC TAC), and re-amplified using nested primer s14F1 (5' AAG GGC ACC ACA AGA ACG C). The amplified PCR products were purified using High Pure PCR Purification Kit (Roche Diagnostics) and then cloned using ultracompetent cells XL2-Blue MRF’ (Stratagene) after ligation in the Topo Cloning vector (Invitro Gene). Sequencing reactions were prepared using an ABI-PRISM Big Dye Terminator Cycle Sequencing Kit and analysed with an ABI-377 DNA sequencer or an ABI-PRISM 3100 (Applied Biosystems), all according to the manufacturer's instructions.

Sequences were compared to 40 other foraminiferal sequences and manually aligned using the Seaview software (Galtier et al. 1996). The maximum likelihood tree was constructed with GTR + I + G model, using Phy_ML program (Guindon and Gascuel 2003).

Results

Systematic description

Rhizaria Cavalier-Smith, 2002

Foraminifera D’Orbigny, 1826

Capsammina gen. nov.

Derivation of name: Latin ‘capsa’ a box

Type specie: Capsammina patelliformis gen. & sp. nov.

Diagnosis: Monothalamous test composed of a few large, plate-like grains of mica separated by fine-grained, white agglutinated material (‘mortar’). Obvious aperture absent. Remarks: Capsammina is distinguished by the structure and composition of its test from other monothalamous foraminifera which lack an obvious aperture. Morphology-based 49 classifications group these forms in the Families Psammosphaeridae and Hemisphaeramminidae (Loeblich and Tappan, 1988). Psammosphaera is much larger and has a test composed of quartz grains. Crithionina has a more rounded shape and the test does not incorporate mica plates. Molecular evidence (see below) indicates that the type species of Capsammina belongs in a different phylogenetic clade from both Psammosphaera and Crithionina , although it is most closely related to the latter. In addition to the type species, described below, we include Psammosphaera bowmanni Heron-Allen and Earland, 1912 in the new genus (Pl. 1). The test of this species was originally described as ‘consisting of a more or less irregularly polyhedral chamber, constructed of small flakes of mica cemented around the edges by a light grey mud-like cement’ (Heron-Allen and Earland, 1912)

Capsammina patelliformis gen. & sp. nov.

Plates 2-5

Crithionina sp. (mica sandwich). Koho et al., 2007, Pl. 3, Fig. 3 Derivation of name. Patella (L), a plate, referring to the typically plate-like morphology of the test. Diagnosis: Species of Capsammina characterised by strongly flattened test dominated by 2-3 flat, parallel mica plates. Plates separated by more or less oval ring of white mortar composed of fine mineral grains and enclosing cell body. Both mortar and cell body visible though transparent plates. Type material: The type specimens, from Isis Dive 57 ( James Cook Station 127; 39°29.756’, 9°56.041’, 3536 m water depth) are deposited in the Natural History Museum, London under registration numbers ZF5210 (holotype; Pl. 2D), ZF5211 (1 paratype; Pl. 2E) and ZF5210- 5229 (18 paratypes; Pl. 2C). Other material examined: 17 specimens from the type locality and 153 specimens from other sites (Table 1) Morphological description: The test is usually strongly compressed with flat upper and lower surfaces formed from single plate-like mineral grains, presumed to be mica (Pls. 2,3). Most of the plates are colourless and yield main peaks for Si, Al and K when examined using elemental X-ray microanalysis under SEM. These are presumably muscovite. Others are 50 brownish in colour and yield peaks for Fe and Ti, in addition to Si, Al and K. These plates are presumably biotite. The mica plates are separated by a mass of small, more equidimensional mineral grains that form a ring around the cell body and appear pure white in colour when viewed in reflected light (Pl. 2). X-ray microanalyses indicate that some larger grains are rich in Si and are presumably quartz. Other smaller grains yield peaks for Si, Al, K, Ca and Fe and are probably represent different kinds of clay mineral, possibly chlorite and smectite. This ring-like formation of ‘mortar’ and the cell body that it encloses, are clearly visible through the transluscent plates. In flat specimens, the length and width of the test vary from 200 to 640 µm and 150 to 500 µm respectively. However, these dimensions are usually those of the mica plates. The size of the test is more accurately reflected by the size of the mortar ring. This ranges from 200 to 260 µm long and 160 to 200 µm wide. The inner lumen generally occupies over a half (50-70%, usually 53-62%) of the diameter of the mortar ring. In side view, the test is very thin (Pl. 4A). Many specimens are only 30-50 µm thick but a few are thicker, up to 80 µm. A minority of specimens incorporate three or more mica plates. Sometimes, there are two overlapping plate-like grains on one side of the test with a double ring of white mortar developed between the grains. In a few cases, 3-4 plates are arranged to form a more three- dimensional, triangular test (Pl. 2A); occasionally, more plates are present, forming a polygonal test (Pl. 2B; Pl. 5A). The cell body almost completely fills the space within the mortar ring. In unfixed specimens it is pale cream in colour in reflected light, translucent in transmitted light. The cytoplasm is relatively featureless, except for a single nucleus (Pl. 2D) and, in some specimens, various inclusions, including brown, spherical, cyst-like structures, that are presumably ingested particles (Pl. 2F).

51

Plate 1. Psammosphaera bowmanni Heron-Allen and Earland, 1912; scale bars = 100 µm. Specimens from Goldseeker Haul 73, Burghead Bay, Firth of Forth, Scotland, housed in the Natural History Museum, London. A) registration number. 1957.11.14.93. B) registration number 1957.11.14.87-92. Photographs courtesy of Prof. John Murray. 52

Plate 2. Capsammina patelliformis gen. et sp. nov.; JC station 127; light micrographs except for B; scale bars = 100 µm, unless indicated otherwise A.Four specimens with multifaceted tests; JC station 101. B. SEM photograph of bottom right-hand specimen in A. C. Holotype and paratypes (reg. nos ZF5210-5229). D. Holotype, reg. no ZF5210. E. Paratype, reg. no. ZF5211. F. Transmitted light photograph showing cell body with inclusions.

53

Plate 3. Capsammina patelliformis gen. et sp. nov.; JC station 127; scale bars = 100 µm A-F. Transmitted light and SEM micrographs of the same three specimens, viewed lying flat. G-I. G is an oblique view and I an edge view of the specimens shown in G. 54

Plate 4. Capsammina patelliformis gen. et sp. nov.; JC station 127; scanning electron micrographs; scale bars = 100 µm except where indicated otherwise A-C. Edge view of specimen at progressively higher magnifications. D-E. General view and detail of agglutinated ‘mortar’. F-G. General view and detail of mortar of second specimen. 55

Plate 5. Capsammina patelliformis gen. et sp. nov; scanning electron micrographs; scale bars = 100 µm except where indicated otherwise. A. Specimen with a multifaceted test; station 64PE236-13 (0.0-0.5cm depth in sediment) B. Specimen displaying the ‘mortar’ wall and the interior of the test; station 64PE236-07 (0.0-0.5 cm depth in sediment). C. General view; station 64PE236-13 (0.0-0.5cm depth in sediment) D. General view; station 64PE236-07 (0.5-1.0 cm depth in sediment) E-F. Edge view and a detail of ‘mortar’; station 64PE236-13 (0.0-0.5 cm depth in sediment). 56 Molecular characterization: For each extraction, two clones were sequenced and a total of six sequences were deposited in the EMBL/GenBank under accession numbers FJ646885- FJ646885. No particular structural features (introns, insertions) were observed. The sequenced fragments were 1120 nucleotides and the GC content ranged from 44.5 to 44.8%. The observed divergences between the six sequences of Capsammina patelliformis, including variable regions, range from 0% to 2.7% which is quite low but also not surprising since the analysed samples were from the same 3400-m locality. The maximum likelihood phylogenetic tree (Fig. 2.2.1) showed that these six sequences are monophyletic (with a bootstrap support of 100 %) and comprise a clad branching with three crithioninids: C. delacai, C. granum and an undescribed specimen of crithioninid morphology. Because the genetic database for crithioninids and for the monothalamous species in general is still poor, it is difficult to evaluate the closeness of the relationship between C. patelliformis and species of the genus Crithionina . However, the observed divergences between the new species and its closest relatives are 19% (23% including variable regions) for the “Unident. crithioninid k55”, 20% (26% including variable regions) for C. granum and 21% (27% including variable regions) for C. delacai . The variation between C. granum and C. delacai is only 6% (13% including variable regions) and so these percentages are far too high to include the new species in the genus Crithionina , assuming that the C. granum and C. delacai are representative of this genus. Unfortunately, there are currently no sequence data for the type species, C. mamilla (the species with this name in Pawlowski et al., 2003, Fig. 2.2.1 therein was another species). The phylogenetic tree also shows that another monothalamous species, Psammosphera sp., is very distant from C. patelliformis based on the partial sequences of SSU.

57 99 Reophax sp. 1 Reophax spiculifer 96 88 Psammosphaera sp. Undet. allogromiid 1195 73 72 Undet. allogromiid 1212 100 Undet. allogromiid 1018 Silver saccamminid A26 91 Marsipella elongata 63 Gloiogullmia eurystoma 84 Syringammina corbicula 66 63 Rhizammina sp. 87 72 Hippocrepinella alba 62 Toxisarcon synsuicidica Bathyallogromia weddellensis 81 Cylindrogullmia alba 100 Bathysiphon flexilis Bathysiphon argenteus 78 Micrometula sp. Vellaria zucchellii 100 Psammophaga sp. Psammophaga cf. P. simplora Allogromia crystallifera 96 Nemogullmia sp. A330 71 Tinogullmia sp. 100 Notodendrodes hyalinosphaira 100 Notodendrodes antarctikos Hemisphaerammina bradyi 100 Astrammina rara 87 Astrammina triangularis 85 Armorella sphaerica Saccodendron limosum 10069-21 (FJ646885) 10070-32 (FJ646887) 10068-12 (FJ646883) Capsammina 10068-13 (FJ646884) patelliformis 100 10070-34 (FJ646888) 93 10069-22 (FJ646886) 100 Crithionina granum 100 Crithionina delacai Undet. crithioninid k55 Undet. crithioninid 2008 100 Undet. crithioninid 1037 Hyperammina sp. 96 Cribrothalammina alba Ovammina opaca Reticulomyxa filosa

Figure 2.2.1. Phylogenetic tree based on SSU rDNA partial sequences showing the position of Capsammina patelliformis gen. et sp. nov. among the Foraminifera. The tree was obtained using maximum likelihood method with GTR + I + G model of evolution. Only bootstrap values higher than 60 % are indicated.

58 Relative abundance and vertical distribution in the sediment: At CD179 station 56848, close to the type locality, 52 specimens of Capsammina patelliformis represented 7.9% of all stained foraminifera in the 0-2 cm layer (>150 µm fraction) . All except one of these specimens were extracted from the 0-0.5 cm layer, where they accounted for 43% of the 119 stained foraminifera in the >150 µm fraction. At station 56851, 37 specimens represented 67% of the 55 stained foraminifera in the same sieve fraction. The vertical distribution of C. patelliformis was also investigated at the two shallow sites, 64PE236-13 and 64PE236-07 (927-m and 1160-m water depth, respectively). At 64PE236-13 a total of 18 well-stained specimens were found, of which 12 were located in the top 0.5-cm of sediment; followed by 3, 2 and 1 in the following three 0.5-cm slices of sediment. Only the top 2 cm of the core were examined at 64PE236-07. Here, 9 specimens were found in the first 0.5-cm of sediment and 3 specimens between 0.5-1.0 cm depth. These observations indicate that C. patelliformis is a sediment surface dwelling species and has a shallow microhabitat distribution.

Remarks

The white, finely granular ‘mortar’ that separates the mica plates in Capsammina patelliformis resembles the material that constitutes the test in Crithionina granum Goës, 1894 and C. delacai Gooday, Bernhard and Bowser 1995 . A phylogenetic relationship between these three species is indicated by the fact that they belong to the same clade (Fig. 2.2.1). However, the high genetic divergence (34-35%) between M. patelliformis and the two Crithionina species suggests that they are not closely related.

As far as we are aware, Psammosphaera bowmanni is the only species that resembles C. patelliformis. We illustrate some specimens from the type locality in the Moray Firth, Scotland, for comparison with our new species (Pl. 1). They also have a faceted test composed of mica plates separated by fine-grained white agglutinated material. However, the test has an elongate, rounded, pellet or droplet-shaped morphology rather than the strongly flattened form of the new species. Occasional specimens of C. patelliformis are more three- dimensional, but they do not approach the shape of the test in P. bowmanni. Another difference is that the protoplasm of P. bowmanni is described as ‘very dark and opaque’ in contrast to the light-coloured protoplasm in C. patelliformis. The two species also come from different water depths; P. bowmanni from 55-64 m and C. patelliformis from 344 to 3400 m. 59 Concluding remarks

The recognition of Capsammina patelliformis adds to our knowledge of the diversity of monothalamous agglutinated foraminifera. These ‘primitive’ taxa form part of the bush- like radiation of foraminifera revealed by recent molecular studies (Pawlowski et al., 2003). Modern agglutinated taxa which lack apertures and have spherical or dome-like tests are generally assigned to the genera Crithionina and Psammosphaera. Although these genera contain relatively few formally described species, they are represented by a variety of different forms, which are often attached to hard substrates such as stones and shells. These forms tend to grade into each other and are difficult to distinguish clearly based on morphological features (Heron-Allen and Earland, 1913). Molecular evidence suggests that they represent several different clades (Pawlowski et al., 2002, 2003). The new genus, in contrast, possesses some characteristic features that distinguish it from other monothalamous agglutinated taxa that lack apertures. The most distinctive feature is the use of mica plates as the dominant test component. Many agglutinated foraminifera construct their tests from particular kinds of particles. Those selected include sponge spicules, globigerina tests, coccoliths and quartz grains. However, as Heron-Allen and Earland (1912) remark, mica flakes are a rarely used, probably because they are difficult to cement together and easily detached. The selection of these particles by Capsammina patelliformis may reflect their availability in the Nazare Canyon. Mica flakes are particularly common at the type locality at 3400-m depth , where they are associated with a turbidite deposit that underlies a veneer of hemipelagic sediment (Arzola et al., 2008).

Acknowledgements This research was supported by the HERMES project (EU contract GOCE-CT-2005-511234 and funded by the European Commission's Sixth Framework Programme under the priority ‘Sustainable Development, Global Change and Ecosystems’). We thank Prof. John Murray for generously making available his images of Psammosphaers bowmanni, reproduced in Plate 1 .

60 2.3 A new genus of xenophyophores (Foraminifera) from Japan Trench: morphological description, molecular phylogeny and elemental analysis

1 2 3 1 Béatrice Lecroq , Andrew John Gooday , Masashi Tsuchiya and Jan Pawlowski

1Department of Zoology and Animal Biology, University of Geneva, Switzerland.

2National Oceanographic Centre, European Way, Southampton SO14 3ZH, UK.

3Institute for Research on Earth Evolution, Japan Agency for Marine-Earth Science and Technology, Yokosuka, Kanagawa 237-0061, Japan.

Published in: Zoological Journal of the Linnean Society (2009) 156 : 455-464

61 Abstract

The deep-sea floor is inhabited by a number of unusual and enigmatic taxa unknown in shallow waters. These include the xenophyophores, a group of giant protists that construct fragile agglutinated tests. Here, we describe Shinkaiya lindsayi gen. et sp. nov. , a new xenophyophore collected by the submersible Shinkai 6500 at a depth of 5435 m near the Japan Trench. The phylogenetic analysis performed with its complete small-subunit ribosomal DNA (SSU rDNA) sequence confirms that S. lindsayi sp. nov. is a foraminiferan that is closely related to another xenophyophore Syringammina corbicula Richardson, 2001, and to a monothalamous (single-chambered) foraminiferan Rhizammina algaeformis Brady, 1879. In terms of morphology, the new genus resembles Syringammina but its test wall is thicker, softer and more weakly cemented. Moreover, the SSU rDNA sequences of the two genera are highly divergent. Mass spectra analyses reveal unusually high concentrations of some elements like lead, uranium and mercury. The granellare system (the cytoplasm and the organic sheath that encloses it) is apparently devoid of barite crystals, which are usually abundant as intracellular inclusions in xenophyophores, but is rich in mercury (with 12 times the concentration of mercury found in the surrounding sediment). Fecal pellets retained within a tubular system (stercomare) concentrate heavy metals including lead and uranium (respectively 2 and 6 times more than in the sediment). Based on a comparison of the compositions of the agglutinated test wall, the granellare, the stercomare and the surrounding sediment, we discuss the impact of xenophyophores on their habitat.

Introduction

Despite many years of study, the deep-sea fauna remains poorly known. The xenophyophores are one particularly enigmatic group. These spectacularly large protists are extremely abundant in productive parts of the deep ocean. They are benthic deposit feeders that build an agglutinated test, often greater than 10 cm in diameter, consisting mainly of foreign particles (xenophyae) and having a wide variety of morphologies. Xenophyophores are often very fragile, easily fragmented, and have no proven fossil record (Levin 1994). This may be one of the reasons why they were poorly studied until recently, despite their wide occurrence in the deep sea and their importance for bioturbation. Indeed, the enhanced

62 particules deposition in their vicinity would provide food and refuge to their associate fauna, which increase the biological mixing of the sediment (Levin et al., 1986). Syringammina fragilissima Brady 1883, the first species to be described was classified as a foraminiferan. Later, however, xenophyophores were considered successively as sponges (Haeckel, 1889), members of an independent class of Rhizopoda (Schultze, 1907) or a new eukaryotic phylum (Lee et al., 2000). Recently, molecular studies showed that S. corbicula is indeed related to monothalamous foraminifera (Pawlowski et al., 2003). Nevertheless, the monophyly of the group remains unproven.

Fourteen genera and almost 60 species of xenophyophores are now described (Gooday and Tendal, 2000). Large species are epifaunal, but a few smaller, infaunal species are also known. Most resemble agglutinated foraminifera in having a test composed of foreign particles. The internal organisation of xenophyophores is distinctive. The multinucleate cytoplasm and the organic tube which encloses it comprise together the granellare system. Faecal pellets (stercomata) enclosed within an organic sheath form the stercomare system. Another distinctive feature of the xenophyophores is the presence of barium sulphate crystals (granellae) throughout the cytoplasm, and sometimes within the stercomare. The crystallography of these crystals has been investigated (Hopwood et al., 1997) but their function, if any, is still a matter of debate.

Xenophyophores are often abundant beneath productive waters where the flux of organic matter to the seafloor is high (Tendal, 1972). Their diets probably comprise detrital particles obtained by suspension feeding (Tendal, 1972), surface-deposit feeding (Lemche et al., 1976) or by being trapped within the folds and spaces of the often morphologically complex test (Levin and Thomas, 1988). It is possible that organic material concentrated in this way is digested within invaginations of the cell wall, and that the indigestible remnants are accumulated into stercomata (Tendal, 1979; Hopwood et al., 1997). It has also been suggested that stercomares are used to cultivate bacteria as an additional food source (Tendal, 1979). Some support for this idea is provided by studies of lipid biomarkers which suggest a diet rich in bacteria (Laureillard et al., 2004). Large, epifaunal xenophyophores may constitute important habitat structures on the seafloor, providing refuges and possibly sustenance for numerous small metazoans (Levin and Thomas, 1988; Levin and Gooday, 1992) and foraminifera (Hughes & Gooday, 2004).

63 In this paper, we describe a new species and genus of xenophyophore from the North- West Pacific, and discuss its phylogenetic position according to the complete small-subunit ribosomal DNA (SSU rDNA) sequence. We also performed a chemical analysis of different parts of the organism and compared them with the surrounding sediment.

Material and Methods

Sample collection

The single specimen was collected by MBARI-type push core during the RV Yokosuka cruise YK07/15 to Japan Trench off Sanriku using the submersible Shinkai 6500 (dive 1037; 38°14.8175’N, 147°00.1885’E; 5435 m; October 2007). After recovery, the specimen was split into two main pieces, one to be deposited in National Museum of Nature and Science, Tokyo, and the other used for analyses. Fragments of the specimen were either fixed in formalin (for morphology investigations) or guanidine buffer (for DNA analyses); the rest was immediately frozen at -20°C.

Microscopy

Fragments of Shinkaiya lindsayi were broken open and examined with a light microscope. Nuclei were observed under a UV microscope after the granellare strands had been stained for 3 min in a 50% solution of 4’,6-diaminido-2-phenylindole (DAPI). Other fragments were critical-point dried before being coated with platinium and examined in a scanning electron microscope (SEM) operating at 1.5 kV (Jeol 6300F, field emission). For transmission electronic microscopy observations (TEM; Phillips CM12, tungsten filament), fragments of the specimen were dehydrated in a series of graded alcohols and propylene oxide before embedding in EPON® resin. Semi-thin sections (0.6-0.7 µm) were stained with a mixture of methylene blue and Azur II. Thin sections (60-70 nm) were contrasted with lead citrate and uranyl acetate and viewed on coated 200 µm nickel grids in a graphite holder. Energy dispersive X-ray spectrographic microanalysis (EDAX) was performed in conjunction with TEM.

64 Mass Spectrometry

Fragments were analysed by inductively coupled plasma mass spectrometry (ICPMS Agilent 7500). Pieces of the test, stercomare and granellare were separately dissolved in a mixture of Nitric and Hydrofluoric Acid prior to being analysed. Two additional sediment samples were prepared in the same way: one from the same site as Shinkaiya (1037) , the other from another site (1036; 39˚24.1602’N, 144˚26.1275’E; 6406m; October 2007) approximately 145 nautical miles away.

Molecular and phylogenetic analyses

The complete SSU rDNA of S. lindsayi was obtained by PCR amplifications and cloning according to the protocol described in Schweizer et al. (2008). Several overlapping fragments of SSU rDNA were separately amplified using foraminiferal specific primers A10: 5’CTC AAA GAT TAA GCC ATG CAA GTG G 3’, s4F: 5’TCT AAG GAA CGC AGC AGG 3’, s13: 5’ GCA ACA ATG ATT GTA TAG GC 3’, s8F: 5’ TCG ATG GGG ATA GTT GG 3’, s12r: 5’ GAT YAG ATA CCG TCG TAG TC 3’, s14f: 5’ACT TGA AGG AAT TGA CGG 3’, s17: 5’ CGG TCA CGT TCG TTG C 3’ or eukaryotic universal primer sb: 5’ TGA TCC TTC TGC AGG TTC ACC TAC 3’ (Fig. 2.3.1). Five DNA extractions from five different fragments of the specimen were used for molecular work. For each PCR product, 3-4 clones were sequenced. We also sequenced the complete SSU of Rhizammina algaeformis Brady,1879 (from specimen collected during ANDEEP 2002 cruise in the Weddell Sea; 64°00.9’S, 39°06.3’W; water depth, 4730 m), which appeared as sister group of S. corbicula in previous study (Pawlowski et al, 2003). Sequences were compared with 30 other foraminiferal sequences and manually aligned using the SEAVIEW software (Galtier et al. 1996). The GC content, number of informative sites and sequence divergence were determined with PHYLO_WIN (Galtier et al., 1996). The tree was built using the maximum- likelihood method with Treefinder program (Jobb, von Haeseler & Strimmer, 2004), using the general time-reversible (GTR + G + I) model with four rates categories and with 1000 replicates for bootstrap analysis.

65

Figure 2.3.1. Schematic representation of the small-subunit ribosomal DNA (SSU rDNA) sequence of Shinkaiya lindsayi gen. et sp. nov., showing the conserved regions, as well as the largest insertion and primers used for DNA amplifications.

Results

Systematic description

Rhizaria Cavalier-Smith, 2002

Foraminifera D’Orbigny, 1826

Xenophyophorea Schulze, 1904

Psamminidae Haeckel, 1889

Shinkaiya gen. nov.

Type species: Shinkaiya lindsayi gen. et sp. nov.

Generic diagnosis: Large xenophyophore, at least 8 cm diameter and 5 cm high. Test fragile, approximately cylindrical in shape and forming tightly-meshed, reticulated structure composed of bar-shaped elements (~0.5 cm diameter) separated by open spaces. Test with smooth outer surface; wall relatively thick, soft, weakly cemented and composed of fine sediment particles. Scattered internal xenophyae (agglutinated particles), mainly radiolarian tests, present.

Derivation of name: The name of the new genus is derived from the Japanese submersible Shinkai 6500, operated by JAMSTEC, which was used to collect the specimen.

66 Remarks: The new genus resembles species of the genus Syringammina, in particular the type species S. fragilissima Brady 1883. The genera are similar in the general shape and construction of the test, which consists of a framework of bar-like elements, forming a tightly- meshed, often reticulated structure. Another species, Syringammina reticulata Gooday 1996, has a similar arrangement of test elements, although the body form is flattened rather than domed. The main morphological difference between the new genus and Syringammina is the nature of the test wall. In Syringammina, the wall is brittle with a smooth inner surface and consists of ‘tightly cemented xenophyae’ (Tendal, 1972). These comprise mainly fine sand grains and small foraminiferal tests in S. fragilissima . Shinkaiya, on the other hand, is characterised by a relatively thick wall which is soft rather than brittle and consists mainly of clay-sized sediment particles. Unlike Syringammina, in which the particles are confined to the test wall, the lumen of the test in Shinkaiya includes scattered internal xenophyae. Our distinction of these two genera is supported by molecular data showing an important genetic distance between S. lindsayi and S. corbicula . Unfortunately, DNA sequences are not yet available for S. fragilissima.

Shinkaiya lindsayi gen. et sp. nov.

Diagnosis: As for genus

Derivation of name: The species is named for the biologist Dhugal Lindsay who collected the specimen.

Type specimen: The single specimen (and therefore the holotype) was recovered in a push core by the Shinkai 6500 submersible from North Pacific, East of the Japan Trench (38°14.8175’N, 147°00.1885’E; water depth 5435 m). The major fragment is deposited in the National Museum of Nature and Science of Tokyo (registration number: NSMT-Pr 241).

Morphological description.

Test form and structure: The test forms a short, approximately cylindrical structure with a fairly flat upper surface. It measures at least 8 cm in diameter with ~5 cm of test exposed above the sediment surface. At the base of the test, root-like structures 1-2 cm long, extend into the sediment. The test comprises a system of anastomosing branches, typically 0.5 cm diameter, forming a meshwork with open spaces ranging from 1 to 3 cm (Fig. 2.3.2A, B).

67

Figure 2.3.2. Shinkaiya lindsayi gen. et sp. nov. A, holotype specimen in its push core, just after collecting (the authors assume that this is a whole specimen, almost unbroken by the corer tube). B, holotype specimen out of its core. C, D, microscopic views of fragments, revealing the internal organisation (G, granellare; S, stercomare). C, transversal view showing the dark stercomare strings. D, the fragment is open along a longitudinal axis, displaying the obvious whitish granellare and the stercomare. E, F, fragments of granellare stained with diaminidophenylindol (DAPI), revealing thousands of nuclei in the cytoplasm. Scale bars = 15 mm (A), 15 mm (B), 250 µm (C), 500 µm (D), 250 µm (E), 30 µm (F). 68

On the upper surface of the test, these branches tend to form an approximately reticulated pattern. The test wall is delicate, soft and 300 m thick. It is light brown in colour and composed mainly of fine-grain sediment particles with scattered darker particles and occasional larger radiolarian tests (up to 200 m in diameter) and quartz grains (Fig. 2.3.3D).

Test interior : The test branches are usually basically hollow, but there are some internal xenophyae, mainly isolated radiolarian tests but also quartz grains and sponge spicules (Plate 2A). Occasionally, the two sides of the test adjoin, leaving almost no lumen.

Cytology: The interior contains prominently developed granellare and stercomare strands, which are intimately intertwined inside the test branches but without any obvious connections between them (Fig. 2.3.2D). The stercomare and granellare are not equally distributed within the specimen. Some test branches contain stercomare but no granellare, although the reverse has not been observed.

The granellare strands are pale yellowish (straw-coloured) and branch in an irregular manner (Fig. 2.3.2D). The diameter is highly variable (50-200 m). Sometimes, a thick granellare section gives rise to a cluster of 4-5 much narrower branches. Where the granellare runs along the length of a test section, the branches may merge; however, these anastomose are not common in the test fragments examined. The organic sheath is very thin, delicate and has a non-reflective surface (Fig. 2.3.3C). No granellae (barite crystals) are visible within the cytoplasm when squashed preparations of granellare fragments are viewed under a high powered microscope. DAPI staining of the cytoplasm revealed numerous nuclei (roughly 15.10 5 mm -3) between 2 and 4 m in diameter (Fig. 2.3.2E, F). Although the cytoplasmic ultrastructure had been largely destroyed by freezing, nuclei and a Golgi apparatus were recognisable in TEM sections and at least one stercome was present within the cytoplasm. Barite crystals were not observed in any of the sections examined.

The stercomare system occupies a greater volume of the test interior than the granellare (Fig. 2.3.2C). The strands are usually attached loosely to the inner surface of the wall but in places they project into the test lumen (Fig. 2.3.3A). They are dark grey, almost black and the thin organic sheath that encloses the stercomata masses has a distinctly reflective, slightly iridescent surface. The strands range from 30 to 200 m in diameter, and 69 their width is often uneven; lobate sections separated by constrictions sometimes develop. Some branches end blindly with rounded terminations. Anastomoses have not been observed, although branches sometimes adjoin without merging. Branching, which is usually dichotomous, may be very frequent. The branches often run in different directions. However, in the more tubular sections of the test, the stercomare strands extend for 100 m without branching, and run more or less parallel to the granellare strands.

The stercomata are between 10 and 15 m diameter (Fig. 2.3.3B). TEM observations reveal that the organic envelope enclosing the stercomare is of even thickness: 1 m (Fig. 2.3.3E). The envelope appears rather homogeneous and featureless except for an outer layer that in places separates from the underlying part to form a loop-like structure (Fig. 2.3.3F). A peak for iron is evident in EDAX spectra. TEM sections of stercomare revealed the presence of cytoplasm associated with stercomata (Fig. 2.3.3E, F). The cytoplasm is present around the margins of the stercomare mass but inside the organic envelope. Stercomata are composed mainly of flake-like mineral particles. EDAX microanalysis revealed peaks for silica, aluminium, magnesium, iron, suggesting that these particles are composed of clay minerals. Barium was also detected within the stercomata. In one case, this element was associated with a crystal. The barite composition of this crystal, however, remains uncertain because it also yielded a peak for calcium. A sharp peak for titanium was associated with another crystal, presumably rutile.

Life position

The specimen was epibenthic. It projected from the seafloor with the root-like lower part buried in the sediment. It was found among numerous other unidentified xenophyophores of different sizes.

Molecular characterisation

The total length of the SSU was 4054 bp and all the clones sequenced were identical. The sequence alternates between conserved regions and variable regions among foraminifera, with a long insertion of 624 bp starting in the variable region E23 at position 1744 (Fig. 2.3.1). The GC content of S. lindsay (32.2%) is similar to that of S. corbicula (34.1%). The sequence divergence between the two xenophyophores is 23.6% while is 30.2% between S. lindsayi and R. algaeformis . 70

Figure 2.3.3. Shinkaiya lindsayi gen. et sp. nov. A, scanning electron micrograph (SEM) of an open tube, showing its inner surface with many radiolarian tests, a granellare string (right arrow) and a stercomare string (left arrow). B, SEM image of an open stercomare string containing stercomata (spherical pellets). C, SEM image of the organic sheath of the granellare. D, SEM image showing details of the external surface of the test, with agglutinated material. E,F, transmission electronic microscopy images of stercomare section, showing its wall (W), stercomata (S), and cytoplasm (C). Scale bars = 100 µm (A), 10 µm (B-D), 2 µm (E), 1 µm (F). 71

In the phylogenetic tree obtained by ML method (Fig. 2.3.4), S. lindsayi clusters with S. corbicula and the two xenophyophores form a sister group of R. algaeformis . This topology is supported by high bootstrap values (respectively 94% and 100%). The clade consisting of S. lindsayi , S. corbicula and R. algaeformis branches at the base of polythalamous (multichambered) foraminifera including rotaliids, textulariids and robertinids.

Remarks

As discussed above, the new species is similar to some species of Syringammina in the construction of the test from reticulated bar-like elements. There is a particular resemblance between S. lindsayi and S. reticulata in the constant diameter, dimensions and arrangement of the tubes (compare Fig. 2.3.2A of the present paper with Gooday, 1996: pl. 7). However, in addition to the differences in wall structure noted above, the overall morphology of the test is distinctly flattened in S. reticulata but more or less equidimensional in S. lindsayi.

Elemental composition

Mass spectrometry analyses were performed separately on pieces of the stercomare, granellare and on intact fragments of the specimen, as well as on environmental samples from the area where the specimen was collected (site 1037) (Fig. 2.3.5). Aluminium, barium and magnesium were present inside the stercomare, where concentrations were >30% higher than in the sediment. These elements were less abundant in the granellare than in the surrounding sediment (site 1037). They occur in roughly the same concentration in the intact fragment (mainly test) and in the environment. Consistent with microscopic observations of barite crystals, barium occurs in the stercomata but not in the cytoplasm. Lead, mercury and uranium concentrations are also higher (respectively 2, 4 and 6 times) inside the stercomare than in the sediment. The concentration of mercury in the granellare is 12 times that in the sediment.

72

Figure 2.3.4. Phylogenetic position of Shinkaiya lindsayi gen. et sp. nov. among Foraminifera, based on complete small-subunit ribosomal DNA (SSU rDNA) gene sequences. The tree was obtained using the maximum-likelihood method with the general time-reversible (GTR) + G + I model, with four rates categories, and 1000 replicates for bootstrap analysis. Only bootstrap support values higher than 70% are indicated. 73

Figure 2.3.5. Inductively Coupled Plasma Mass Spectrometry (ICPMS) values for the composition of the total fragment of Shinkaiya lindsayi gen. et sp. nov., of its different structural parts, and of environmental sediment. The mass of elemental aluminium (Al), lead (Pb), magnesium (Mg), uranium (U) barium (Ba), strontium (Sr), and mercury (Hg), per gram of dry material, is shown. A semiquantitative method has been used for Pb, U and Hg.

Discussion

Phylogenetic position

Several authors have regarded xenophyophores as a distinct higher taxon at the level of subclass (Tendal, 1972), class (Tendal, 1996; Gooday and Tendal, 2000) or even phylum (Tendal 1990). Pawlowski et al. (2003), however, showed that Syringammina corbicula is a foraminiferan, based on a complete analysis of the SSU rDNA gene. Here we present evidence that a second xenophyophore species is also a foraminiferan, thus strengthening the case that this enigmatic group does not represent a distinct eukaryotic taxon.

The phylogenetic position of Shinkaiya as sister group to Syringammina supports the monophyly of the xenophyophores. However, the two species for which DNA sequences are available are both classified within Psamminidae. It is possible that members of Stannomidae, the other xenophyophore family, characterized by the presence of proteinaceous fibres (linellae) within the test, will branch outside the clade. Moreover there are still too few 74 complete SSU sequences of monothalamous foraminifera and missing data could artefactually bring Shinkaiya and Syringammina together.

The sequence divergence between S. lindsayi and S. corbicula is remarkably high (23.6% compared to 13.9% between Astrammina rara Rhumbler, 1931 and Astrammina Triangularis Earland, 1993 ; which are placed in the same genus) and supports their separation into distinct genera. Both xenophyophore sequences also seem to be closely related to that of R. algaeformis , another monothalamous foraminiferan of uncertain taxonomic origin . Like Shinkaiya and Syringammina , Rhizammina contains stercomata and cytoplasmic strands within its tubular test. It has been proposed that R. algaeformis should be placed in the superfamily Komokiacea, based on the overall test morphology and the presence of stercomata (Gooday and Cartwright, 1987; Cartwright et al. 1989). Our study suggests that Rhizammina is related to xenophyophores. Whether komokiaceans also group with the xenophyophores is unknown. Komokiacean sequences are needed to answer this question.

Elemental composition

Elemental analyses of Shinkaia lindsayi revealed that the granellare are surprisingly poor in barite. Our TEM observations, together with microanalysis, identified a few barite crystals in the stercomare but failed to find any in the cytoplasm. This surprising result could be a temporary state or a specific feature of the new species. Tendal (1972) also reports an absence of granellae in few species of xenophyophores, including several stannomid species and Reticulammina labyrinthica Tendal, 1972. However, mass spectra analyses confirmed a weak concentration of barium inside the granellare of S. lindsayi . We therefore can not exclude the possibility that the observed granellare sections were poor in crystals and not representative of the granellare as a whole.

Another striking result of the mass spectra analysis is the extremely high concentration of mercury inside the granellare system. This result is astonishing considering the toxicity of mercury. It is highly improbable that only the granellare sample was contaminated. Mercury is lipophilic and thus could be retained inside lipid droplets within the cytoplasm. Moreover, mercury resistance is widespread among microorganisms and some marine bacteria are known to convert water-soluble inorganic mercury and methylmercury to the volatile elemental form

75 (Poulain et al., 2007). It is possible that some xenophyophores also perform this detoxification process.

Other heavy metals, for example, lead, seem to be concentrated in the stercomare, as previously proposed by Tendal, Swinbanks & Shirayama (1982) when they described Occultammina profunda . The inorganic remnants of digested particles taken up from the environment accumulate in the stercomata, which as a result may become enriched in non- nutritive substances like heavy metals. Because xenophyophores do not release these digestive wastes, they probably modify the chemical composition of the sediment, at least locally. Indeed, Swinbanks and Shirayama (1986b) showed that xenophyophores may drastically change the distribution of some elements in deep-sea sediment profiles. They also demonstrate that high levels of natural radiation occur in xenophyophores, as a result of the presence of 226 Ra in the intracellular barite crystals, and suggested that this radiation would induce numerous genetic mutations (Swinbanks and Shirayama, 1986a). As noted above, there are no obvious barite crystals in the cytoplasm of S. lindsayi. However, radiation could arise from the high concentrations of uranium in the stercomata of this species. It is interesting to note that the excessively long branch of S. lindsayi in our phylogenetic tree could suggest an accelerated evolution rate of its ribosomal genes. Measurement of the radiation emanating from xenophyophores may enhance our knowledge of the respective contributions of natural and artificial radioelements, thereby improving assessments of deep- sea pollution.

As they seem to concentrate many elements from the environment, xenophyophores may affect directly the composition of deep-sea sediments, especially because they can be extremely numerous on the abyssal seafloor. For example, densities reach almost 1000 xenophyophores per 100 m 2 at a depth of 4000 m off North-West Africa (Tendal and Gooday, 1981). Information about this group, its diversity, biology and ecology, is still scarce. The elemental analysis must be extended to other species and genera of xenophyophores to confirm that they concentrate high amounts of heavy metals and radioactive elements compared to the sediment, and in this way modify the chemistry of their environment. This could reveal how far they are involved in global biogeochemical cycles, as well as improving our knowledge of their role in deep-sea ecosystems.

76 Acknowledgements

We would like to thank captain, crew members and scientists of Yokosuka YK07-15 cruise and especially Dhugal Lindsay and Frédéric Sinniger; José Fahrni (University of Geneva) for the DAPI staining; Francine Voinesco, Antonio Mucciolo and Michel Bonin for the microscopy (Université de Lausanne); Dominique Robin and Ricardo Stouvenel (Ecole d’ingénieur de Genève) for the ICPMS analyses and finally Ana Aranda Da Silva for great discussions. The project is supported by a grant from the Swiss National Science Foundation (3100A0-100415).

77 78 Chapter 3 “Hidden” richness revealed by molecular tools

3.1 Introduction

In marine benthic ecosystems, it is quite common that a single organism represents a niche for numerous other species. A meaningful example is the ascidian Microcosmus sabatieri , which has been reported to shelter many benthic organisms, including not less than 38 different peracarid species (Voultsiadou et al., 2007). In the oligotrophic bottom of the deep sea, association between organisms is likely to be even more common, since it potentially enhances resources exploitation and provide the associated species with numerous ecological benefits such as the protection from predators or hard substratum for attached deposit or suspension feeders. Similar situation may occur with shells and tests of dead specimens or with any structures of biogenic origin. Large agglutinated foraminiferal tests have been shown to be sometimes associated with metazoan meiofauna and macrofauna (Gooday, 1984a, b; Hughes and Gooday, 2004; Levin, 1991). It is quite likely for instance that xenophyophores test; providing three dimensional elevated structure, which disturbes the laminar currents near the benthic boundary layer; would directly enhances biological activities by creating physico-chemical hotspots for other organisms. Because it is often impossible to separate foraminifera from their acolytes, this can induce misinterpretations of molecular analyses. Indeed, during DNA extraction step, material from any organisms associated with target specimens is likely to be dissolved into the extraction buffer and then amplified by PCR.

In this chapter we define the “hidden” richness as the part of the species richness, which do not appear obviously by traditional investigations such as microscopic observations. For instance, foraminiferal specimens and their dead tests can presumably shelter and hide other organisms, which could go unnoticed during preliminary observations and despite

79 would contribute to the richness of ecosystems. In a similar way, foraminiferal specimens can themselves be included in the “hidden” diversity of a given sample, because of their small size, unusual shape or even because they are dissimulated inside another eukaryote. Molecular tools offer a vison of the species richness, which differs from that revealed by direct observations or culturing. Species can be revealed almost regardless of their size and shape, depending only on the presence of their DNA, its conservation state and recognition by amplification primers. For these reasons, molecular tools have a potential descriptive power much greater than that of microscopy regarding the “hidden diversity”. Recent studies involving phylogenetic approaches unveiled unexpectedly high diversity of microbial eukaryotes in marine environments, which had never been noticed until then (Lovejoy et al., 2006; Moreira and López-Garcia, 2002; Takishita et al., 2007).

Our interest for the “hidden” richness was first totally fortuitous and appeared with an attempt to determine phylogenetic position of Komokiacea, a group of agglutinated protists morphologically related to foraminifera. SSU rDNA sequences obtained from the extraction of representative komokiacean specimens revealed such a high eukaryotic diversity (including different foraminiferal taxa) that it was obvious they were reflecting a whole community of eukaryotes living inside or on the surface of the tests. The first paper of this chapter presents this “hidden” richness associated with komokiaceans analysed using traditional PCR-based cloning approach.

The second part of this chapter focuses on the foraminiferal richness assessment in environmental samples. Global DNA extractions of deep-sea sediments from Arctic and Southern Oceans have been amplified by PCR targeting foraminifera. To avoid bias and limitations induced by cloning of PCR products, we performed those analyses by massive sequencing approach, using Solexa technology. In this part, we present what could be the most efficient and less time-consuming method to access the foraminiferal richness including “hidden” taxa, which were difficult or impossible to detect before.

An additional short paper related to the massive sequencing of environmental samples is included in Appendix D. This preliminary study investigated the entire eukaryotic richness (including foraminifera) in 6 polar deep-sea sediments using 454 technology.

80 3.2 Molecular analyses reveal high levels of eukaryotic richness associated with enigmatic deep-sea protists (Komokiacea)

1 2 3 4 Béatrice Lecroq , Andrew John Gooday , Tomas Cedhagen , Anna Sabbatini and Jan Pawlowski 1

1Department of Zoology and Animal Biology, University of Geneva, Switzerland.

2National Oceanographic Centre, European Way, Southampton SO14 3ZH, UK.

3Department of Marine Ecology, University of Aarhus, 8200 Aarhus N, Denmark.

4Department of Marine Sciences, Polytechnic University of Marche, 60131 Ancona, Italy

Published in: Marine Biodiversity (2009) 39 : 45-55 doi: 10.1007/s12526-009-0006-7

81 Abstract

Komokiaceans are testate agglutinated protists extremely diverse and abundant in the deep sea. About 40 species are described and share the same main morphological feature: a test consisting of narrow branching tubules forming a complex system. In some species, the interstices between the tubules are filled by sediment creating a mudball structure. Because of their unusual and sometimes featureless appearance, komokiaceans were frequently ignored or overlooked until they formal description in 1977. The most recent taxonomy places the Komokiacea within the Foraminifera based on general morphological features. To examine their taxonomic position at the molecular level we analysed the SSU rDNA sequences of two species, Normanina conferta and Septuma ocotillo, obtained either with specific foraminiferal or universal eukaryotic primers. Many different sequences resulted from this investigation but none of them could clearly be attributed to komokiaceans. Although our study failed to confirm univocally that Komokiacea are foraminifera, it revealed a huge eukaryotic richness associated with these organisms, comparable to the richness in the overall surrounding sediment. These observations suggest strongly that komokiaceans, and probably many other large testate protists, provide a habitat structure for a large spectrum of eukaryotes, significantly contributing to maintaining the biodiversity of micro- and meiofaunal communities in the deep sea.

Introduction

The ocean floor is a remote environment, characterised by the absence of solar light, high pressures and food limitation, in which the microbial fauna and small eukaryotes play an important role in food webs and carbon cycling (Vickerman 1992; Moodley et al. 2002). Within the meiofaunal size fraction (small eukaryotes), most of the biomass is made up by nematodes and foraminifera. At abyssal depths, the latter group is dominated by agglutinated species, which are very diverse and include many undescribed taxa. The superfamily Komokiacea (Tendal and Hessler 1977) is one of the most widely distributed deep-sea foraminiferal groups and also the most controversial one. Prior to their classification as Foraminifera, placements within the sponges and xenophyophores were proposed (Hessler and Jumars 1974). Komokiaceans (informally termed ‘komoki’) are particularly common in

82 oligotrophic, abyssal regions, but sometimes have broad bathymetric ranges (Schröder et al. 1989). They have a delicate, flexible test consisting of a complex system of fine branching tubules, sometimes subdivided by septae with foramina. In some forms, the interstices between the tubules are filled with mud to create a mudball structure (Shires et al. 1994). The tubules contain stercomata (waste pellets) and diffuse cytoplasm that does not stain readily with rose Bengal, making the recognition of individuals that were alive at the time of collection difficult. In at least some species, the cytoplasm appears to be multinucleate (Tendal and Hessler 1977). The fragility of komokiacean tests impedes their preservation as fossils; indeed, the existence of fossil komokiaceans has never been confirmed (Gooday et al. 2007a). Moreover, because of their peculiar structure and wide variety of tests morphologies, komoki are difficult to recognise as living organisms and in the past have often been overlooked (Tendal and Hessler 1977).

Although they possess some typical attributes of agglutinated Foraminifera, including a test wall comprising an organic layer overlain by a veneer of attached particles, the classification of komokiaceans within the Foraminifera is controversial. In particular, some typical foraminiferal features, such as granuloreticulate pseudopodia, have not yet been observed. This has led some authors to conclude that they represent a separate taxon, close to the foraminifera (Kamenskaya 2000). In order to explore the taxonomic position of komokiaceans, we analysed partial SSU rDNA sequences obtained from several specimens of two species from the Weddell Sea and North Atlantic: Septuma ocotillo Tendal and Hessler, 1977 and Normanina conferta (Norman 1878) (Gooday et al. 2007b). Our study failed to identify sequences that were derived univocally from komokiaceans. On the other hand, it revealed a spectacular eukaryotic richness associated with these overlooked organisms. This richness, as well as the possible reasons that impede the identification of genuine komokiacean rDNA sequences, are discussed.

83 Material and Methods

Sediment sampling and DNA extraction

Samples were collected during tree consecutive expeditions: “ANDEEP II”, (RV Polarstern cruise ANT XXII/3, Weddell Sea, Antarctica, 2002), RRS Charles Darwin cruise 158 (North Atlantic, 2003) and “ANDEEP III” (RV Polarstern cruise ANT XIX/4, Weddell Sea, Antarctica, 2005). One hundred thirteen komokiacean specimens (or fragments) of two species: Septuma ocotillo (71) and Normanina conferta (42) were analysed during this study. Samples were collected with boxcorer, multicorer, Epibenthos sledge and Agassiz trawl at the depths and coordinates indicated in Appendix E, Table E1. In the case of corers, first top 1 cm layer of sediment was sliced off and sieved on 500 m, 300 m and 125 m meshes. Some specimens were collected by elutriation (Sanders, Hessler and Hampson 1965); others were sorted by hand under a binocular microscope (mostly from the 300-500 m fraction). Isolated specimens were either fixed directly in guanidine DNA extraction buffer (Pawlowski 2000) or stored frozen at -80°C. Some of them were cut into 2 or 3 pieces in order to compare sequences derived from different parts from the same individual. At stations where komoki were found and successfully extracted, 14 frozen sediment samples of about 1 ml were extracted with the FastDNA SPIN Kit for Soil (QBIOgene).

DNA amplification, cloning and sequencing

Partial SSU rDNA were amplified by PCR with a set of foraminiferal specific primers: s14F3 (5’-ACGCA(AC)GTGTGAAACTTG-3’); s14F1 (5’-AAGGGCACCACAAGACGC- 3’); s17 (5’-CGGTCACGTTCGTTGC-3’) and a set of universal eukaryotic primers s12.2 (5’- GAT(CT)AGATACCGTCGTAGTC-3’) and sB (5’-GTAGGTGAACCTGCAGAAGG ATCA-3’). In the case of amplification with foraminiferal primers, the first PCR obtained with primers pair s14F3/s17 was reamplified using nested primer s14F1. Other foraminiferal and eukaryotic primers were also tried but did not provide successful amplifications. Amplified products were purified using the High Pure PCR Purification kit (Roche) and cloned into the sequencing vector “pGEM ®-T Easy (Promega)” and replicated in DH5 α Competent Cells . After purification, 2 to 5 clones for each sample were sequenced from both directions for cross-checking. Finally, a total of 191 clones (46 for S. ocotillo , 77 for N.

84 conferta and 68 for the sediment samples) were sequenced. GenBank accession numbers are indicated in Appendix E, Table E2.

Phylogenetic analysis

Sequences were aligned manually using Seaview software (Galtier et al. 1996). Our database of 871 foraminiferal sequences was used to align the sequences obtained with foraminiferal specific primers. The 60 foraminiferal sequences most closely related to those obtained from komoki were retained in final analysis. A database of 505 eukaryotic sequences was used to analyse the sequences obtained with universal s12.2 – sB primers. Poorly aligned positions and divergent regions were eliminated and the alignments of foraminiferal and eukaryotic sequences were analyses separately. To increase the resolution of the eukaryotic phylogenetic analyses, sequences were analysed in four different sets, corresponding to the supergroups of eukaryotes recently defined (Keeling et al. 2005). The first set corresponds to “unikonts” (Cavalier-Smith 2002) and includes Amoebozoa, Metazoa, Fungi and other Opisthokonta. The second set consists of various “bikonts”: Apusozoa, Euglenozoa, Plantae, Glaucophyta, Haptophyta and Cryptophyta. The third set is composed of Alveolates and Stramenopiles. Finally the fourth set represents the Rhizaria. The phylogenetic affiliation of each obtained rDNA sequence was initially investigated by NCBI BLAST search (Altschul et al. 1990) in order to include their closest relative sequence from GenBank (Bilofsky 1986). Trees were built according to the Maximum Likelihood (ML) method using PhyML program (Guindon and Gascuel 2003) with the GTR + I + G model suggested by Mr Modeltest (Posada and Crandall 2001) with 10,000 replicates for bootstrap analysis. Additionally, bayesian phylogenetic analyses were performed on the same dataset with the same model using MrBayes program (Huelsenbeck and Ronquist 2001). All analyses were performed on the freely available Bioportal ( http://www.bioportal.uio.no , accessed 2008). In order to sum up all information from this phylogenetic analysis, we built pie charts of richness for S. ocotillo , N. conferta and sediment samples respectively. The total number of Operational Taxonomic Units (OTU) found in each of the 12 major eukaryotic groups appearing in the phylogenetic trees was counted and reported in a pie chart.

85 Results and Discussion

Foraminifera

In order to identify a “characteristic” komokiacean SSU rDNA sequences, extractions of Normanina conferta and Septuma ocotillo were amplified first with foraminiferal specific primers. Several combinations of these primers were tested in nested PCR with different annealing temperatures and different numbers of cycles for the first and second amplification. Most of these combinations did not give any PCR product, suggesting that komoki do not have a “typical” foraminiferal sequence (if any komokiacean DNA has indeed been extract from those samples). Only the set of primers s14F3-s17 reamplified with s14F1-s17 led to a successful amplification in the case of 25% and 50% of S. ocotillo and N. conferta samples, respectively.

In total, 23 foraminiferal sequences were obtained for both species (15 for S. ocotillo and 8 for N. conferta ). Their phylogenetic analysis shows that they do not group together but are widely spread between different foraminiferal taxa (Fig. 3.2.1). Some of them, such as S5930-82, which is identical to the sequence of Marginopora vertebralis from tropical shallow waters, are certainly a contamination by foreign foraminiferal DNA. Others are similar to the sequences of foraminifera that could be present in the area where the komoki were sampled, but which belong to different well-defined taxonomic groups. For instance, the sequences S5132-12 and N5976-102 are close to the calcareous rotaliid Oridorsalis umbonatus , while the sequence S5928-11 is close to calcareous miliolid Cornuspira antarctica . As these species are morphologically very different from the komokiaceans, the only explanations for their presence in our DNA extractions are that they represent foraminiferal inhabitants of the komokiacean tests, or the species living in their vicinity.

Most of foraminiferal sequences obtained here can be convincingly attributed to inhabitants of komokiaceans. However, for some sequences, a real komokiacean origin cannot be completely eliminated. In theory, we should obtain a separate clade consisting of two distinct subclades, one grouping sequences from S. ocotillo and the other grouping sequences from N. conferta . In our tree (Fig. 3.2.1) the best candidates (which are supposed to be distinct lineages) are the clade formed by N3502-52 plus N3474-52 and the isolated sequence N3509-32.

86

Figure 3.2.1. SSU rDNA maximum likelihood phylogenetic tree of foraminifera showing the position of the sequences obtained from N. conferta (in red) and S. ocotillo (in blue) in amplification using foraminiferal specific primers. Only support values higher than 60% are indicated. 87

However, the sequences N3502-52 and N3502-A originate from the same specimen but do not branch together, which suggests that one or other (if not both) represents an unknown foraminiferal lineage associated with komoki rather than the komoki themselves. There is only one case where sequences from S. ocotillo and N. conferta branch together. S5008-62 and N3502-A form a separate clade of two genetically extremely close sequences. However, sequences that are so similar are unlikely to originate from two morphologically very distinct genera.

Other eukaryotes

One hundred and ninety-one sequences were obtained with the “universal” eukaryotic primers: 46 from S. ocotillo, 77 from N. conferta and 68 from sediment samples. The analysis of these sequences was performed separately for four large groups that correspond roughly to the eukaryotic supergroups as defined by Keeling et al. (2005). Five groups of sequences and one clone were not related to any well defined taxonomic group present in the GenBank database and therefore have been labelled “undetermined lineage” or “undeterminated clone” with the name of the group to which they refer in literature when it was available.

Fig. 3.2.2 presents a partial SSU rDNA tree of Unikonta, including 38 new sequences. Most of these sequences are found among Fungi. Many of them could result from contamination from different sources, including fungal spores in deep-sea sediments (Damare et al. 2006) and because almost all of them have a sister group among known fungal taxa, it is unlikely that they represent komokiaceans. On the other hand none of those fungal sequences was found in the sediment samples which might suggest that some fungi could somehow benefit from komokiacean structures or from komokiacean metabolites. Two sequences of N. conferta and one of S. ocotillo branching within Metazoa could be some small annelids or other invertebrates living inside komokiacean tubes, but the examined fragment is too short to identify them safely.

88

Figure 3.2.2. Phylogenetic position of partial SSU rDNA sequences obtained from komokiacean and sediment samples grouping within Unikonta. The sequences from N. conferta are in pink, those from S. ocotillo are in blue and those from sediment samples are in green. Environmental sequences from GenBank are indicated with the original name of the clone and information on the sampling location. Except for outgroups, the eukaryotic sequences which did not branch with any new sequences were discarded from the trees. The black circles reflect the support of the nodes for both ML and Bayesian trees: 100% for the big circles and more than 50% for the small ones. 89 Fig. 3.2.3 presents various groups of Bikonta including Apusozoa, Euglenozoa, Plantae, Glaucophyta, Centrohelida, Haptophyta and Cryptophyta. Many of new sequences branch among Euglenozoa. Some of them form a very important clade distantly related to Euglena . It is composed of 7 N. conferta and 10 S. ocotillo sequences but without segregation between the two genera. For this reason it seems unlikely that this clade represents authentic komokiaceans. Except for this clade, we did not find other Euglenozoa among sequences derived from komoki, although many of them were present in the sediment samples. A few new sequences branch among Plantae and Haptophyta. As these are photosynthetic groups, our sequences certainly originated from organisms living in the surface waters. Presumably, these were conveyed rapidly to the seafloor on sinking particles (Thiel et al. 1989). Some of the sequences form two distinctive clades: “undetermined lineage 2” related in the literature to the clade “OLI11011” (Edgcomb et al. 2002) and “undetermined lineage 3” related to the clade “DH148-5-EKD18” (Takishita et al. 2007). One of these clades (“undetermined lineage 2”) branches as sister group to Apusozoa, but with no bootstrap support. The other (“undetermined lineage 3”) form a distinctive lineage separated from other groups by a very long stem branch. In this clade, we found 9 sequences from N. conferta and 1 from S. ocotillo branching together with six environmental sequences. As those “environmental” sequences also originated from the deep-sea samples, this clade could potentially represent komokiaceans, yet the strong divergence between N. conferta sequences and the presence of only one S. ocotillo sequence does not strongly support this hypothesis.

Fig. 3.3.4 shows a tree of Alveolates and Stramenopiles with very diverse new sequences. Most of them branch within the diatoms and probably represents organisms that have settled from the water column. Several other sequences were derived from ciliates or dinoflagellates. Interestingly, very few komokiacean sequences branch together with sequences from the sediment suggesting that different eukaryotes inhabit the komokiacean tests and the sediment. One lineage, “undetermined lineage 4”, was found to be related in the literature to the clade “NAI.2” (Not et al. 2007) and contains one S. ocotillo sequence. However, its position within the dinoflagellates is rather well supported excluding the possibility that represents new komokiacean lineage.

90

Figure 3.2.3. Phylogenetic position of partial SSU rDNA sequences obtained from komokiacean and sediment samples grouping within Bikonta, except Alveolates, Stramenopiles and Rhizaria (see legend Fig. 3.2.2 for details).

91

Figure 3.2.4. Phylogenetic position of partial SSU rDNA sequences obtained from komokiacean and sediment samples grouping within Alveolates and Stramenopiles (see legend Fig. 3.2.2 for details).

92

Finally, Fig. 3.2.5 presents a tree of Rhizaria that also reveals a striking diversity of the new komokiacean sequences. Many of these sequences, including 19 from sediment samples, 13 from S. ocotillo and 3 from N. conferta, are located among the core Cercozoa. Haplosporidia mainly include sequences from komoki and probably correspond to parasites living inside their tests. One sequence from the sediment (SED833) also represented a sister group of Foraminifera without any relatives and was therefore labelled “undetermined rhizarian clone”. New sequences were not found within Foraminifera because the eukaryotic primers that we used do not match the foraminiferal rDNA. A very distinct clade (“undetermined lineage 5”), composed of 10 sequences from the sediment, 1 from N. conferta and 1 from S. ocotillo, branched as a sister group to the polycystine radiolarians represented by Collozoum inerme. Other four sequences from the sediment appeared as sister group of the taxopodid Stycholonche zanclea .

Why it is so difficult to identify the true komokiacean rDNA sequences?

In previous studies, we have recovered DNA from foraminifera obtained at abyssal depths down to >6000 m (Gooday et al. 2004). However, in the present study, we were unable to determine which, if any, of the numerous sequences obtained from two komokiacean species represented the actual komokiaceans. There are several possible explanations for this lack of success.

First, the majority of examined specimens could be dead and their “well preserved” agglutinated tests difficult to distinguish from living specimens. Although many individuals were filled with stercomata, these waste pellets probably persist intact for a considerable time after death. As is typical for abyssal foraminifera, we did not observe any signs of cellular activity, such as the pseudopodial movement or the cytoplasmic flux. Indeed, the cytoplasm of komokiaceans is diffuse and difficult to observe. Therefore, we cannot be sure that the DNA was actually extracted from the living komokiacean specimens.

Second, our specific foraminiferal primers may not fit to the komokiacean rDNA sequences. These primers were designed based on the specific region in the foraminiferal SSU rDNA containing unique 3-nucleotides insertion found exclusively in this group (Pawlowski 2000). 93

Figure 3.2.5. Phylogenetic position of partial SSU rDNA sequences obtained from komokiacean and sediment samples grouping within Rhizaria (see legend Fig. 3.2.2 for details).

94 Using our specific foraminiferal primers, we have successfully amplified the majority of foraminiferal taxa (Bowser et al. 2005). It would be very surprising if the komokiaceans are Foraminifera but do not recognise the specific foraminiferal SSU rDNA insertion, and at the same time do not amplify with universal eukaryotic primers.

Third, the komokiacean rRNA genes could be represented by a very low number of copies. In this case, the rDNA of other organisms coexisting in the sample could be amplified much more easily than the authentic komokiacean genes. The lack of clear evidence for authentic komokiacean rDNA sequence might result from a bias of amplification promoting majority copies of komoki inhabitants.

Komokiaceans as hot spots of eukaryotic diversity

The taxonomic composition of eukaryotes found in S. ocotillo , N. conferta and in the sediment samples is presented in Fig. 3.2.6. Twelve major eukaryotic groups identified in this study are represented in very different proportions. Each slice of pie chart reflects the number of OTU found in one of those major groups.

Both komokiacean and sediment samples yield an amazing diversity of major taxonomic groups and constituent OTUs. Another study based on sediment from a deep-sea methane cold seep reported similar results described by the authors as “an unexpected high diversity of microbial eukaryotes at various taxonomic levels” (Takishita et al. 2007). It is remarkable to find this level of diversity in 14 ml of sediment (resulting from the 14 extractions) and even more surprising to obtain a similar richness from a few (17 S. ocotillo and 23 N. conferta ) millimeter-sized organisms, in some cases only fragments of specimens, with a total volume smaller than 1 ml. From this observation we can postulate that komoki concentrate the diversity inside or outside their branching tests. Fungi represent most of the eukaryotic richness in samples from N. conferta, with 28 different OTU recognised. The Euglenozoa (10 OTU) was the most diverse group in S. ocotillo , while the Cercozoa was by far the richest group (19 OTU) in the sediment samples.

Most of the new komokiacean or sediment sequences consisted of clearly distinct OTUs; in only a very few cases did two sequences represent the same phylotype. By sequencing more clones it is likely that the number of OTUs, and thus the richness, will increase even more. Massive sequencing technologies should hugely increasing the number of sequences and 95 provide a powerful way to reveal the full extent of species richness associated with komokiaceans. However, even with the limited number of sequences reported in this study, it is clear that some eukaryotic groups are not represented, either in the sediment or in one of the two komokiacean species. For instance, Fungi are completely missing in the sediment samples while they are extremely diverse in N. conferta. The later species also yields ciliates and non-diatoms stramenopiles, which seem to be missing in S. ocotillo. On the other hand, the sediment samples contain some radiozoans and haptophytes, which are not present in komoki, but lack Apusozoa, stramenopiles and Metazoa. It is remarkable that almost one quarter of the richness found in the sediment consists of OTUs not related to any known group. This observation is in general agreement with several recent environmental surveys (Dawson and Pace 2002, Lopez-Garcia et al. 2001, reviewing in Epstein and Lopez-Garcia 2008) revealing a huge number of new lineages from environmental DNA extractions and emphasizing the general lack of knowledge of eukaryotic richness. However, as far as we are aware, no previous studies have investigated the eukaryotic diversity in abyssal plains. Thus, our environmental DNA survey of komokiaceans and the surrounding sediment is the first attempt to assess the eukaryotic richness in this vast deep-sea biotope.

The xenophyophores, a group of giant agglutinated foraminifera that are an order of magnitude larger than komokiaceans, provide habitat structure for a wide range of meiofaunal and macrofaunal metazoans (Levin and Thomas 1988; Levin 1991), as well as smaller foraminifera (Hughes and Gooday 2004). Relatively large ctenostome bryozoans (genus Nolella ) are commonly associated with the komokiacean genera Lana and Edgertonia (Gooday et al. 1984). Our results suggest that komoki are also inhabitated by much smaller (microscopic) organisms. The complex, branching tests of genera such as Septuma and Normanina may offer a stable and elevated microhabitat on the deep seafloor, allowing better access to suspended particles (Jumars et al. 1982), or they may provide a refuge against predators and physical disturbances (Tendal 1979; Levin 1991). We predict that the ‘mudball’ komoki (Shires et al. 1994; Gooday et al. 2007a) and large tubular agglutinated foraminifera Gooday et al. 1992), which are often very abundant in the bathyal and abyssal deep sea, likewise represent ‘hotspots’ of biological diversity and activity.

96

Figure 3.2.6. Pie chart representing the proportion of 12 major eukaryotic groups found in N. conferta (a), S. ocotillo (b), and sediment (c) samples. Each slice of pie chart reflects the number of taxonomic units found in one particular group. 97 Conclusions

The molecular analyses of S. ocotillo and N. conferta do not confirm that Komokiacea belong to Foraminifera. The main difficulty in this study was to identify authentic komokiacean DNA in our extractions. This problem could have arisen because specimens were either dead or contained very few copies of rDNA. Although we failed to establish the phylogenetic position of komoki, we discovered an extraordinary richness of eukaryotes associated with these organisms. Therefore, rather than addressing the phylogenetic position of komokiaceans, this study focussed on the question of their role in maintaining the diversity of microfaunal communities. A comparison of this richness with that derived from the surrounding sediment strongly suggests that eukaryotic diversity increases in the vicinity of komokiacean tests. The xenophyophores, which are usually much larger than komokiaceans, are already known to be “hot spots” of deep-sea meiofaunal and macrofaunal diversity. Our molecular study provides a first glimpse of the high diversity of much smaller eukaryotes, belonging to many different phyla, associated with komoki. It is unclear whether their complex test architecture is the only reason for their attractiveness as microhabitats, or whether they present other metabolic advantages for associated organisms. The presence of a considerable eukaryotic richness, including many new lineages, in abyssal sediment samples suggests that future molecular studies should focus on deep-sea sediments, in addition to the hydrothermal vents and cold seeps that have attracted the attention of earlier investigators.

Acknowledgements

We thank A. Brandt, B. Hilbig, D. Fütterer, E. Fahrbach, and the Captain, officers and crew of the Polarstern for their assistance during the ANDEEP II and III expeditions. We also thank J. Blake for collecting komoki using elutriation technique during “ANDEEP II” expedition. This study was supported by the Swiss National Science Foundation (grant no. 3100A0- 112645 to JP), the Danish Research Agency (Grant no. 95091435 to TC), and the UK Natural Environment Research Council (Grant no. NER/B/S/2001/00336 to AJG). This is ANDEEP publication no 119. This publication also contributes to the CoML field project CeDAMar.

98

3.3 Assessment of the deep-sea foraminiferal richness by massive sequencing with Solexa analyser

1 2 2 2 1 Béatrice Lecroq , Loïc Baerlocher , Laurent Farinelli , Magne Osteras , José Fahrni and Jan Pawlowski 1

1Department of Zoology and Animal Biology, University of Geneva, Switzerland.

2FASTERIS SA, 1228 Plan-les-Ouates, Switzerland.

Manuscript in preparation 99 Abstract

Development of massive sequencing methods has opened new perspectives for the assessment of species richness in environmental samples. This approach is based on the principle that species can be identified by very short DNA fragments. In this preliminary study, (1) we investigated the variable regions of SSU rDNA in search for the most efficient barcode for identification of foraminiferal species; and (2) we used the chosen barcode to assess diversity of foraminifera in four sediment samples from Arctic Ocean. Based on our large database of the partial SSU rDNA sequences, we choose a foraminifera-specific expansion segment of the helix 37 (region I), as having the highest barcoding potential. This region was amplified by PCR targeting foraminifera and the 36 bp long fragment situated at the 5’ end was massively sequenced by Solexa analyzer. Some of the phylotypes resulting from these analyses have been identified to the species level confirming the efficiency of that fragment. It also appeared that the greatest part of obtained sequence data correspond to the undetermined monothalamous taxa. We argue that most of them could be unknown rather than unidentifiable and would reflect a bias in our database artificially enriched in large, well studied species.

Introduction

It became obvious during last decades and mainly through the example of prokaryotes (Wintzingerode et al., 1997) that the cultured organisms do not reflect accurately natural diversity. A new field of microbial molecular ecology has risen up to investigate environmental diversity. Environmental extractions have rapidly revealed numerous undescribed taxa, not only within Bacteria and Archea but also among small eukaryotes (Dawson and Pace, 2002; Edgcomb et al., 2002; Epstein and López-García, 2008; López- García and Moreira, 2008; Lopez-Garcia et al., 2001; Moon-van der Staay et al., 2001). Although this kind of analyses resolved the problem of selective laboratory culturing bias, they remained hedged by different steps of the molecular process itself (mainly PCR amplification and cloning). Recently, new methods of massive sequencing reducing cloning limitations were applied to environmental samples focusing on microbial diversity (Huber et al., 2007; Miller et al., in Press; Sogin et al., 2006). The uncovered genetic diversity of

100 microbes was far beyond all previous predictions leading to the discovery that the majority of phylotypes are represented by only few sequences (rare biosphere). In order to determine the uttermost part of the environmental richness (including rare taxa), technologies shifted toward increasing number of short sequences rather than analysis of fewer sequences of longer size. Therefore, to develop massive sequencing approach for environmental survey it is crucial to find a relevant and short genetic marker sufficiently universal and informative regarding the taxonomic group of interest. For foraminifera, ribosomal DNA appears as a good region to start this investigation.

The ribosomal RNA genes are widely used in molecular systematics of foraminifera. They are commonly applied to resolve the phylogenetic relationships between and within major taxonomic groups (de Vargas et al. 1997, Pawlowski et al. 2002, 2003, reviewed in Pawlowski 2009), to place the new foraminiferal species (Pawlowski et al. 2002, Cedhagen et al. 2009) and to examine the intraspecific variations in particular morphospecies or genera, in relation to their geographic distribution and morphology (de Vargas et al. 1999, Tsuchiya et al. 2000, Holzmann and Pawlowski 2000, Hayward et al. 2004, Darling et al. 2004, Pawlowski et al. 2008). There are almost 3000 sequences of ribosomal RNA genes of foraminifera deposited in the Genbank (2917 in April 2009). Most of these sequences correspond to a 3’ fragment of the SSU rDNA, which is most commonly used in molecular phylogenetic studies of foraminifera. The other sequences correspond to the ITS region, which is used to examine the intraspecific variations (de Vargas et al. 2001, Pawlowski et al. 2007, Tsuchiya et al. 2009) and to a 5’ fragment of the LSU gene (covering the variable regions D1 and D2), which was specifically used to analyse the genetic variations in the genus Ammonia (Holzmann et al. 1996, Holzmann and Pawlowski 2000, Hayward et al. 2004).

Foraminiferal ribosomal genes are highly divergent compared to other eukaryotes. They possess numerous substitutions in the most conserved regions of the SSU, resulting in a strong acceleration of their stem lineage (Pawlowski and Berney 2003). They are also much longer than the typical eukaryotic genes. The length of foraminiferal SSU rRNA genes ranges from 2300 to over 4000 bp, while in other eukaryotes the length of these genes averages 2000 bp. Most of the additional length is due to a series of expansion zones and insertions (Pawlowski 2000), which are especially prominent in the SSU rDNA but are also found in the LSU rDNA. Some of these variable regions are specific to foraminifera, the other are

101 expansion of typical eukaryotic variable domains. They are present in the RNA as suggested by reverse transcriptase (RT) sequencing of the rRNA (Pawlowski et al. 1994, 1996) and RT PCR experiments (Habura et al. 2004). The position of variable regions in the 3’ fragment of the SSU was established based on the predicted secondary structure in the case of rotaliid foraminifera (Ertan et al. 2004). Their variations in different taxonomic groups were analysed by Habura et al. (2004) and Grimm et al. (2007).

The rates of substitution in variable regions of foraminiferal rRNA genes are unusually high. They vary between the taxonomic groups (Pawlowski et al. 1997), with the most rapid evolutionary rates observed in some planktonic species (de Vargas and Pawlowski 1998). Changes in variable regions of the SSU rDNA were used to distinguish geographically separated populations of subpolar planktonic morphospecies and to define their genotypes (Darling et al. 2000). Analysis of these regions also revealed an unexpectedly high diversity of monothalamous foraminifera (Pawlowski et al. 2002). The variable regions D1 of the LSU rDNA were used to revise the taxonomy of the genus Ammonia (Holzmann and Pawlowski 2000).

All these studies show that the variable regions of the SSU and LSU rDNA in foraminifera have potential to become good barcodes for species identification in this group. However, in most of the cited studies, the analysed rDNA fragment contained several variable regions and the taxonomic resolution of each of them is unknown. Nothing is known about the minimum length of rDNA fragment necessary for species distinction in foraminifera and other groups of eukaryotes. Examining this issue is crucial for application of massive sequencing technologies for species identification and interpretation of the short sequences produced by these methods. Therefore, before starting our massive sequencing experiments, at first we have examined six variable regions of the SSU one by one and evaluated the level of their taxonomic resolution for selected species and genera. Once we selected the most promising barcoding region, we applied it to examine the foraminiferal richness in four sediment samples from Arctic Ocean. The global environmental DNA was extracted and selectively amplified to target only foraminiferal species. An extremely short fragment of the PCR product (designated as a relevant barcode) was then massively sequenced with Solexa analyser to assess the foraminiferal richness in our samples.

102 Material and Methods

Identification of barcode for foraminiferal taxa

An alignment of the SSU rDNA 3’ fragment, including about 1000 sequences representing all major taxonomic groups of foraminifera and large databases for selected genera and species, was analysed. The alignment has been carefully checked using Seaview (Galtier et al. 1996), with special attention paid to the variable regions. The sequences of each region were cut off the global alignment and analysed separately. The foraminiferal specific regions were identified based on an alignment of 300 eukaryotes (Berney and Pawlowski 2006). For each region the secondary structure model was predicted using MFold program as implemented in http://mfold.bioinfo.rpi.edu/ . The limits of each region were refined based on secondary structure models previously published for foraminifera (Ertan et al., 2004; Grimm et al., 2007; Habura et al., 2004) and other eukaryotes (Wyust et al. 2002). The divergence between sequences was calculated using the DNA distance matrix program implemented in BioEdit 7.0.5.2.

Sediment sampling and DNA extraction

Four surface sediment samples (SFA2-5), of which depth and coordinates are presented in Table 3.3.1 and Fig. 3.3.1, were collected during RV Polarstern cruise ARK XXII/2 (Arctic Ocean, 2007). For each sample, 5 mL of the first centimetre layer have been collected and immediately frozen. PowerMax TM Soil kit (Mo Bio) was used to extract DNA from each 5 mL sample of sediment according to the protocol (except for step 4, where vortexing time has been extended to 40 minutes). Extraction products were then stored at - 20°C for further analyses. Additionally, DNA of cultured foraminiferan Reticulomyxa filosa was extracted and processed as other environmental samples. Reticulomyxa filosa DNA was used as a reference (SFA6) to be compared with other samples and to improve our interpretation of the sequencing results.

103 Table 3.3.1. Depth, coordinates and sampling method (BC: box corer, MC: multicorer)

SFA 2 SFA 3 SFA 4 SFA 5 Depth 3538 m 3519 m 221 m 4443 m

83°42'58N 83°41'54N 80°59'40N 87°4'14N Coordinates 60°38'27E 60°40'55E 34°0'13E 104°39'57E

Collected with BC MC MC BC

Figure 3.3.1. Map of the sampling

DNA amplification and massive sequencing

In the first step, partial SSU rDNA (about 400 bp) was amplified by PCR (15 cycles, 50°C for annealing temperature) with a set of foraminiferal specific primers containing Solexa adaptators at each end. In the second step, PCR products were reamplified (for additional 10 cycles) and attached to the surface of the Solexa flow cell channels by adaptators. The last step consisted in solid-phase bridge amplification and sequencing by incorporation of labelled reversible terminators (for detailed method see Appendix F, Fig. F1).

Reads analysis and phylotypes identification

The millions of 36 bp sequences or “reads” obtained for each samples have been analysed by grouping the reads into phylotypes and then identifying the phylotypes. 104 Grouping the reads into phylotypes : All datasets were screened to select only sequences meeting required quality. This has reduced the number of sequences for all samples but has provided datasets with a lower error rate. A certain minimum base average quality value was required over the whole read and a maximum of one base of lower quality was allowed. Reads with more than 30 identical bases were discarded as well as reads containing more than one “N”.

The datasets have been profiled for the copy number of each sequence leading to a list of unique sequences and a number of reads for each of them. Sequences displaying less than two reads were discarded before the grouping step as well as those with one “N” or with 30 or more identical bases. The profiled files containing the filtered unique sequences have been screened from the most abundant sequences to the least abundant ones. Sequences with 1 to 3 mismatches were clustered into groups represented by “reference sequences”. Sequences were considered one by one (from that with the higher copy number to that with the lower one) and compared with the reference sequence of each group. Each sequence was attributes to the group, of which reference sequence had the highest copy number and not more than 3 mismatches with the sequence considered. If no such group existed, a new group was created with the current sequence as reference for this group. If a sequence could be attributed to one group with 3 mismatches and to a second group of lower total reads with only one or two mismatches, it was nevertheless attributed to the second group.

When two sequences are compared during the grouping step, indels can artificially increase the number of mismatches, since all the bases can be shifted. In such a case, sequences are wrongly attributed to two distinct groups even if they are closely related. For that reason, after the grouping step, all the reference sequences were aligned with ClustalX program (Larkin et al. 2007) to detect misalignment. Phylotypes were finally formed, based on this alignment, by referring to sequence divergence values. The threshold value for phylotypes distinction was fixed at 0.0834 (i.e. three mismatches for 36 bp).

Identification of phylotypes : Phylotypes were identified according to our foraminiferal database, which contains a total of 1248 partial SSU rDNA sequences and includes described and undescribed species as well as undetermined species from environmental samples or those squatting the test of other foraminifera. This database was used to blast the phylotypes of each sample, except SFA6 ( R. 105 filosa ). The relevance of the 10 best matches resulting from this local blast has been evaluated using the following criteria: a sequence matching with any of our 36 bp phylotypes should have a similar region longer than 14 bp and start at one of the 3 first bases of the phylotype. In the case of conflict between several satisfying results at species level, the sequences were compared at generic level. In the case of a second conflict, the following groups have been considered: monothalamous, textulariids, rotaliids, lageniids and miliolids. In the case of a third conflict between the results, the phylotype was defined as “undetermined”. By this way, phylotypes have been assigned to the uttermost precise taxon.

Results and discussion

Identification of barcode for foraminiferal taxa

1) Characterization of variable regions

The 3’ fragment of the SSU rDNA analysed in the majority of foraminiferal studies comprises six variable regions (Fig. 3.3.2). Three of these regions are specific to foraminifera, while three others correspond to the typical eukaryotic variable segments. The nomenclature of these regions changes from author to author (Table 3.3.2).

Table 3.3.2. Names given to different regions in literature Reference I II III IV V VI Ertan et al. 2004 F1 F2 V5 V6 F3 V7 Habura et al. 2004 I II na na na na Grimm et al. 2007 37/e1 41/e1 V7 45/e1 46/e1 Tp49 Schweizer et al. 2008 F4 F5 V7 V8 F6 V9 This study 37/f 41/f 43/e 45/e 45/f 49/e

106

Figure 3.3.2. Schematized secondary structure of the SSU rRNA gene showing the analysed fragment (in red) and the position of the six variable regions (modified after Schweizer et al. 2008)

107 A A C C G C G A 70 U A A U G U U A UU A A A A U 30 60 U A U C A U 40 A U C G G G A U C U 30 G C U U U U A A U A U A U U A U G U U U A U 20 U A A G A 80 A A U G C U U U U U A U A G 50 50 C A 20 A U U U A U C U A U A A U A A 40 G A A U A A U A U A C U U G G U U A U G A G A U A U 10 C G 10 C G A C 90 A C G U G U U A U A U G U G 60 A U A U G C G C G C G C A U A U 5' G U 3' 5' G U 3'

Reticulomyxa filosa Epistominella exigua

UU U U U U U U A 30 C G A U 40 C 30 U A U A A U U A U U U A U A A U 30 U A U G A U A U G C 40 U A U A A U U A A U U A U U U A U C G U A A U A C A U 20 U G U A 40 A U 50 20 A U G C A U A A G U U U 20 U A A G U U A U 50 A A A G A U U A G A A C A A C A A A A C G A A G A C A G U A U G U G A G A A U 10 C G A U 10 C G 10 C G 60 A A A C A C G U 50 G G G U U A U A 60 U A U G U G U G A U A U A U G C G C G C G C G C G C A U A U A U 70 5' G U 3' 5' G U 3' 5' G U 3'

Marginopora vertebralis Textularia sp. Micrometula hyalostriata

Figure 3.3.3. The predicted secondary structure of the foraminifera-specific expansion zone 37/f of the SSU rRNA for representatives of the major groups of foraminifera: monothalamids ( R. filosa , M. hyalostriata ), rotaliids ( E. exigua ), textulariids ( Textularia sp.) and miliolids (Marginopora vertebralis ).

108 Here, we called the variable regions according to the number of concerned helix and the letter “f” or “e” designating whether the region is found exclusively in foraminifera or it is present also in other eukaryotes, respectively. The position of each region, its length and primary and secondary structure are presented below.

Helix 37/f (region I): This expansion zone is situated in prolongation of the helix 37 (Fig. 3.3.2). It started as a large loop followed by a long helix, interrupted by a small loop in some species (Fig. 3.3.3). At the 5’ end, it is delimited by GG, which remain unchanged in almost all sequences, except the Spirillinids and Ammodiscus , which possess GA or GT, respectively. Moreover, the first nucleotides remain relatively unchanged across the taxonomic groups. At the 3’ end, the region ends usually by T(C)AAATA, but it is much more variable and may also ends by TAAAATA ( Micrometula ), TAAATTA (Cylindrogullmia ), CAAAGA ( Capsammina ). The region can be extremely short (13 nt) in some freshwater environmental sequences (EnvLeman27) but exceptionally can reach up to 123 nt, in a monothalamiid “Notrhabdammina”.

Helix 41/f (region II) : This region is an expansion of the loop that connects helixes 39, 40 and 41. According to the predicted secondary structure, it is composed of several more or less long helixes separated by small loops. This region was extensively discussed by Ertan et al. (2004) and Habura et al. (2004), who presented secondary structure models for several species. However, the borders of this region are not well defined. Based on rotaliid sequence database, Ertan et al. (2004) proposed that the region starts with TCTATA at 5’ end and terminates with GAAAGC at 3’ end. Our alignment shows certain variability in the preceding bases (TTT which change to TCT in Crithionina and TAT in Carterina ) and therefore we include these bases into this region. At 3’ end the 41/f terminates with GAAA in most of forams, although this sequence can be strongly modified in some species ( Hipocrepinella hirudinea ). The 41/f is much longer than the 37/f, with its length varying from 87 nt in Vellaria to 360 nt in Crithionina granum , with average length of 150-200 nt in most of the species.

Helix 43/e (V7) (region III) : This region corresponds to the helix 43 and its extension - helices 43/e1-43/e4 in the secondary model of Wuyst et al. (2002). At the 5’ end, the region is delimited by a relatively stable motif CTTGTT, which change in miliolids into TTTATT, and 109 is followed usually by a motif GCC (GCT in miliolids), which form the beginning of the helix 43. At the 3’ end, the variable region include the motif GGC at the end of helix 43, followed by few variable bases, which form a loop preceding the helix 43 and terminates with conserved motif AACTAGAG. In most of foraminifera the helix 43 is followed by a loop and a short helix. The region is relatively short in most of species, counting only 26 nt in Psammosphaera -like 3918 and 28 nt in Cribrothalammina alba , but can exceptionally reach up to 279 nt in Notodendrodes hyalinosphaira and 278 nt in Astrammina rara .

Helix 45/e (V8) (region IV) : This region is situated between helices 45 and 46. It corresponds to the region 45/e1 in Wuyst et al. (2002) and is considered as a part of eukaryotic variable region V8 (Grimm et al. 2007). In many eukaryotes, the region comprises two loops separated by a short stem GAG/CTT. In foraminifera, the expansion region 45/e1 starts after GAG, with a large loop followed by more or less long stem. The region begins with a motif CATCTC and ends with a motif GGTAAAG. Its length varies from 30 nt in Androsina to 215 nt in Notodendrodes (1931) and 202 nt in Hemisphaerammina bradyi .

Helix 45/f (region V) : This region is situated just after the helix 45’ and is also considered as a part of the region V8 (Grimm et al. 2007). In most of eukaryotes the helix 45 is followed by a large loop starting with a characteristic more or less modified motif GTGATGGGG. In foraminifera, the helix 45 differs from other eukaryotes and is followed by a relatively short expansion zone specific to this group. At the 5’end, the flanking conserved sequence ATGATT corresponds to the complementary branch of helix 45 (45’). The region ends with the sequence GTCAATT, followed by a conserved motif CATGGTGGGG. The length of 45/f varies between 19 nt in Cyclorbiculina to 266 nt in an undetermined allogromid 1847 and 248 nt in Leptammina spp.

Helix 49 (V9) (region VI) : This region corresponds to the helix 49 present in all eukaryotes and is designated as variable region V9 (Neefs et al. 1990). This is a very long stem situated at the 3’ end of the SSU rRNA, followed by a short helix 50 (Wyust et al. 2002). In the majority of the foraminifera, the helix 49 starts with the sequence CTCTTA and terminates with complementary sequence AAAGAG. The first 30 bases of the helix are conserved in most of foraminiferal species. For this reason and because some of our

110 sequences lack the terminal part of the SSU, we analysed here only the most variable part of the helix 49, starting at TTTGAG and ending at CTTAAA.

Table 3.3.3. Sequences of the six variable regions and the flanking conserved zones. # helix Conserved region Variable region Conserved region

I 37/f 5’ GG ATT GACA GG C ………...…. TAAA TA TGCTAGTCC 3’

II 41/f 5’ TT AA TT GCG TTT ………….…….G AAA GCAA CGAA 3’

III 43/e 5’ CTT GTT GCC ..……...... GG CTNNN AA CTAGAGGG 3’

IV 45/e1 5’ CAGTGAG CATCTC ..……GG TAAA G CC TGCTT CGAA 3’

V 45’/f 5’ TAA TGATT TCC T...……………... AA TT CAA GG TGG 3’

VI 49 5’ G TGAG TTT GAG ………. CTT AAA CGAA CAG 3’

2) Taxonomic resolution of variable regions

In order to evaluate the possibility to distinguish foraminiferal species using different variable regions, we analysed for each region the divergence between and within sister morphospecies, the intraspecific polymorphism, and the ability for phylotypes recognition.

Sister species divergence :

We calculated the sequence divergence between sister morphospecies and within those complex morphospecies that show evidence of cryptic speciation usually related to geographic distribution (Table 3.3.4). We selected seven pairs of morphospecies among monothalamids and rotaliids, which belong to the same genus and are morphologically well defined. For comparison of cryptic species, we selected seven monothalamid morphospecies, for which representatives of different populations usually from geographically distant regions were sequenced. The most closely related populations were analysed. Our comparison shows that the sequence divergence values strongly vary between the regions and the examined pairs of species. In general, the species or populations can be distinguished by almost every region independently. The highest values have been found for the three pairs of monothalamids belonging to the genera Astrammina , Notodendrodes , and Leptammina . This can be due to a particularly high rate of evolution in these species, or to their more ancient divergence than suggested by morphological similarity. The sequence 111 divergence is much lower between pairs of rotaliid morphospecies and isolates of monothalamids. In the latter case, the isolates of some species ( B. weddellensis , Psammophaga sp.) can be distinguished only in two or three variable regions. The sequence divergence varies strongly between the regions. For example, Notodendrodes hyalinosphaira differs from N. antarctikos by more than 30 % in the regions I and IV but the two species are identical in the region VI. Opposite situation is observed in the genus Cassidulinoides , in which two examined species differ by more than 16% in the region VI, while their divergence ranges from 0.9 to 1.9 in the regions I, II and V. The region I is the only expansion segment allowing the distinction of all species or isolates. The lowest values of sequence divergence are found in regions IV, V and VI, suggesting that this part of the SSU rRNA gene, close to the 3’ end, is more conserved in foraminifera than the central part.

Intraspecific polymorphism:

In addition to the sequence divergence between morphospecies or their geographically distant populations, we analysed the intraspecific polymorphism within 15 genetically homogenous morphospecies. We selected for this study the species, for which more than 10 sequences were available and which divergence does not exceed 2% in the entire 3’ SSU fragment. In addition to these species, we also included here Oridorsalis umbonatus , with slightly higher sequence divergence (3.6%), as an example of a strong intra-individual polymorphism (Pawlowski et al., 2007). In all these cases, the sequences of clones from the same and different isolates were analysed together. As shown by our results (Table 3.3.4) the intraspecific divergence rarely exceeds 5%, which corresponds to 1-2 substitutions in a given region. The only exception is O. umbonatus , in which the cloned sequences from the same isolate differ by more than 30% in the region III, and are relatively highly divergent in the regions II and IV. In the other species, the high values of divergence (for example 7.1 % in Micrometula , region I) are often due to the presence of one or two unusually divergent sequences. Whether these sequences are fast evolving or their divergence is due to technical errors during PCR amplification or sequencing is unclear.

112 Table 3.3.4. Sequence divergence (%) between and within the 14 foraminiferal morphospecies calculated for each variable region and for the entire fragment of the SSU rDNA. The number of compared sequences for each morphospecies or population is in brackets.

Species pairs I II III IV V VI Total Morphospecies: Astrammina rara 38.0- Astrammina triangularis (2-1) 41.2 29.8-33.9 63.2 44.7-63.3 8.4-12.4 26.4-46.9 17.5-22-7 Notodendrodes hyalinosphaira 32.0- Notodendrodes antarctikos (3-1) 34.2 13.7 95 31.5-56.7 15.7-37.6 0 18.9-22.0 Leptammina grisea Leptammina flavofusca (7-5) 39.9 71.5-74.0 31.3-34.8 22.1-26.5 34.7-37.2 24.2 15.9-16.6 Cassidulinoides parkerianus Cassidulionoides porrectus (11-4) 1.4 1.9 26.3 8.1-10.8 0.9 16.6 5.7-5.9 Epistominella exigua Epistominella vitrea (17-14) 10.2 5.7 9.7 1.2-2.4 1 5.8-7.4 1.9-2.6 Cibicides ungerianus Cibicides wuellerstorfii (3-16) 2.4-4.7 0.9 15.4-19.4 1.2 1.0-3.1 3.8 1.2-3.7 Chilostomella ovoidea Chilostomella oolina (3-2) 6.6-8.9 1 1.8 1.2 0 4.2 1.1 Cryptic species Bathysiphon argenteus : Ross Sea - Oslofjord (2-2) 21.2 1 5.2-8.1 10.9-11.8 6.4 0 3.6-3.7 Bathyallogromia weddellensis : Weddell Sea - Arctic (4-1) 3.7 2.5 0 0 0 0 0.6-0.8 Cylindrogullmia alba : Oslofjord - Svalbard (5-5) 17.8 3.6 6.5 1.3-5.7 4.9-6.8 17.9 3.4-4.2 Gloiogullmia sp.: Ross Sea - Weddell Sea (6-4) 2.2 3.4-4.1 11.0-14.6 0 0 4.3-6.8 1.5-2.7 Hippocrepinella hirudinea : Oslofjord - Admiralty Bay (2-9) 2.2-4.6 17.1-18.6 4.3-6.7 12.2-15.4 6.3-12.9 48.4-87.8 6.8-18.1 Micrometula sp.: Norwegian Sea - Arctic Ocean (4-4) 2.4-4.5 1.0-2.0 16.1-17.7 2.0-3.0 6.2-7.4 2.6-8.2 2.8-3.2 Psammophaga sp. : Svalbard - Ross Sea (2-2) 3.7-7.6 0 12.9 0 0 2.2 1.3-2.3

113

There are species, like C. wuellerstorfii , which SSU rDNA sequences are extremely homogenous and differ only by a single substitution in the region I and few indels in other parts of the gene. High genetic homogeneity was observed in some other rotaliids, for example G. biora and C. parkerianus . On the other hand, the two examined monothalamiid species, M. hyalostriata and Psammophaga sp., show substitutions in all regions. This may be related to generally higher evolutionary rates often observed in this group, but the example of highly polymorphic rotaliid O. umbonatus , suggests that the level of polymorphism in rRNA genes is not necessarily taxonomically meaningful.

Phylotypes recognition:

To test the capability of each variable region to distinguish among different taxa, we compared the number of phylotypes inferred by phylogenetic analysis of the entire 3’ fragment of the SSU with number of phylotypes distinguished in each variable region. We selected three genera with the largest database available and published phylogenies: a monothalamid Micrometula (Pawlowski et al. 2008) and rotaliids Epistominella (Lecroq et al. 2009) and Cibicides (Schweizer et al. in press). Moreover, we performed the same test on the family Nummulitidae, for which all recent species have been sequenced (Holzmann et al. 2004, in prep.). As indicated in Table 3.3.5, the number of recognized phylotypes varies from region to region. The best results were obtained in the case of Micrometula , which phylotypes could be distinguished by almost all regions, with exception of the region I, which performed surprisingly poor compared to the others. The recognition of phylotypes was much more erratic in the three other taxa. The six species of Cibicides ( lobatulus, wuellerstorfii, ungerianus, kullenbergi , refulgens 1 and refulgens 2) differ in almost all regions by single substitutions or indels, but often these differences were not important enough to be taken in account by distance calculations. The same situation occurred in the genus Epistominella . In both cases, particularly low sequence divergence was observed in the regions IV and V, in which only half of the species or phylotypes were recognized in the best case.

114

The family Nummulitidae represented a particular case because of high sequence divergence in some species. To overcome this problem, we have chosen representative isolates for each species. Interestingly, none of these species could be distinguished by more than a single substitution in regions II and IV, which seems to evolve at very slow rate in this family, compared to the region I, in which all nummulitid species were identifiable. When we combine the number of phylotypes identified by each region (Fig. 3.3.4), it appears clearly that the regions I and III provide the best taxonomic resolution for examined foraminiferal taxa. The analysis of each of these regions allows identification of more than 80% of phylotypes. In other regions, the proportion of distinct phylotypes ranges from 35 to 57%. Interestingly, the foraminifera-specific regions (I, II, V) do not perform better than those typical for all eukaryotes. The choice between the six variable regions we analysed was certainly not easy. As indicated by our results, each region possesses its particular characteristics and evolves at different rates in different taxonomic groups. The sequence divergence values vary between the regions and the examined pairs of species or populations. None of the regions seems particularly affected by intraspecific polymorphism, which is clearly related to species-specific evolution of ribosomal genes (see for example high intra- individual polymorphism in O. umbonatus ). At least two regions (I and III) have similarly high potential to recognize the phylotypes of examined taxa. In view of our data, the region I appears as the best candidate for barcoding foraminifera at this moment. Certainly, not all foraminiferal species could be recognized by this region, as illustrated by the case of Micrometula . It is also clear that some general characteristics of ribosomal genes, such as polymorphism of rDNA copies, could lead to overestimation of the diversity in some particularly rapidly evolving species. However, our choice is limited by general lack of foraminiferal sequence data for other genes. Sequencing of the foraminiferal mitochondrial protein coding genes, such as cytochrome oxidase (COI) commonly used as animal barcodes (Hebert et al. 2003, Meusnier et al. 2008), could potentially change this situation. Recent attempts to use this gene for some groups of protists, such as ciliates (Barth et al. 2006), diatoms (Evans et al. 2007) or amoebae (Nassonova et al. 2009) gave positive results. However, our first efforts to amplify foraminiferal COI gene were unsuccessful, suggesting that this gene was possibly strongly modified in foraminifera compared to other eukaryotes.

115

Table 3.3.5. Intraspecific polymorphism in the variable regions and the entire 3’ fragment of the SSU. The maximum values of sequences divergence are reported. A star indicates when this value is due to changes in a single sequence. Number of analysed sequences for each species is in brackets.

Species I II III IV V VI Total Micrometula hyalostriata (16) 7.1 1.9 5.4 4.3 1.7 5.5 1.6 Psammophaga sp. (13) 5.7 2.1 5.8 2.6* 4.5 4.2 1.4 Globocassidulina biora (11) 0.0 1.9 0.0 1.1* 1.6 0.0 0.8 Cassidulinoides parkerianus (10) 0.0 0.9* 0.0 2.2 0.9* 0.0 0.2 Trifarina earlandii (17) 4.9 1.9 1.5 2.0 0.9 3.5 1.9 Uvigerina peregrina (15) 3.0 1.8 5.0 2.2 1.9* 1.8 1.0 Epistominella exigua (17) 0.0 4.9 3.6 1.2* 2.0 1.9* 0.9 Epistominella vitrea (15) 0.0 0.9 0.0 2.4 1.0* 1.7 0.6 Oridorsalis umbonatus (11) 2.5* 8.9 35.9 6.4 1.1 0.0 3.2 Cibicides wuellerstorfii (16) 2.4* 0.9* 0.0 0.0 0.0 0.0 0.5 Cibicides lobatulus (19) 4.6 1.8 1.5 5.0 4.1* 0.0 1.2 Pullenia subcarinata (20) 5.0 3.2 3.3 0.0 3.1 4.1* 0.9

Table 3.3.6. Number of phylotypes recognized by phylogenetic analyses of the 3’ SSU rDNA fragment (2 nd column) and estimated for each of its variable regions. The number of phylotypes recognized by variable regions was calculated using 5% threshold value for sequence divergence. The number of phylotypes distinguished by single substitutions or indels is given in brackets.

Taxon Phylotypes I II III IV V VI Micrometula 6 3 (5) 5 (6) 6 (6) 6 (6) 6 (6) 5 (6) Cibicides 6 5 (6) 4 (6) 6 (6) 2 (5) 3 (6) 3 (5) Epistominella 6 6 (6) 5 (6) 5 (6) 1 (5) 2 (5) 4 (6) Nummulitidae 10 10 (10) 1 (7) 6 (9) 1 (7) 3 (4) 4 (7)

116

30

25

20

Nummulitidae 15 Epistominella

Phylotypes Cibicides 10 Micrometula

5

0 Total I II III IV V VI Variable regions

Fig. 3.3.4. Taxonomic resolution of variable regions of the 3’ fragment of the SSU rDNA. The number of phylotypes identified by analysis of entire 3’ fragment is indicated in the first column.

Our final decision to choose the region I (helix 37f) for our further study was motivated by several reasons. First, this region was highly divergent in the majority of taxa. It was the only one, which shows divergence between all examined pairs of species and populations (Table 3.3.4). It was also the one that allows distinction of the highest number of phylotypes, although its capacity was sometimes limited. The second reason was the relatively short length of this region (averaging 60 nt) allowing to sequence it in a single run of 454 or new Solexa technologies. The third reason was the facility of its amplification using foraminiferal-specific primers. Indeed, there exists already a large database of short rDNA sequences covering regions I and II, which are much easier to amplify than the whole fragment.

117 Assessment of the foraminiferal richness

For each sample, the total number of reads sequenced as well as the statistics of those, which were discarded before the grouping step, are presented in Table 3.3.7. The differences in the total number of reads can be explained by an optimisation more or less successful of initial DNA concentration in Solexa analyser. For SFA 4 and 6, the reads yield is not optimum and probably comes from a poor estimation of DNA concentration. The quantity of reads discarded because of low quality or poly“N” is proportional to the total number of reads and is directly linked to the analyser performances.

Table 3.3.7. Statistics of reads and phylotypes obtained in Solexa analyses.

SFA 6 SFA 2 SFA 3 SFA 4 SFA 5 (R. filosa) total number of reads 4'875'252 4'237'150 2'032'210 3'936'158 2'416'756 total number of reads discarded: 1794852 910931 53305 696095 39657 low quality 1705116 810674 20345 600799 26857 with more than one "N" 564 1373 3377 1392 4253 represented only once 89172 98884 29583 93904 8547 (% of tot reads) (1.8%) (2.3%) (1.5%) (2.4%) (0.3%) % of total reads used for analyses 63% 78% 97% 82% 98% Number of phylotypes 76 304 302 239 4 Number of taxa with 100% match 1 4 14 8 1 Number of unidentified phylotypes 41 193 175 130 1

The quantity of reads represented only once (the “singletons”) is low but still not insignificant. Singletons were removed from analyses before clustering step in order to avoid a maximum of artificial variation due to sequencing errors. According to technical references of Solexa analyser, the base calling during sequencing induces in average one mistake every 200 nucleotides. Therefore, only a small fraction of singletons appearing in analyses could be attributed to machine errors. There should be many extremely rare rDNA copies in our PCR products, resulting either from amplification errors or from an initially low number of copies in the samples.

Simulated saturation curves are presented in Fig. 3.3.5. They should reflect, for each sample, how the number of phylotypes increases with adding new sequences. In theory, if all the species present in a given sample has been sequenced, new reads should just accumulate 118 within the phylotypes already existing and the curve should reach a plateau. As expected, saturation is clearly reached for SFA 6 (the reference sample R. filosa ). The flattening of the curve corresponding to SFA 2 occurs later but still shows that almost all phylotypes have been sequenced. Concerning SFA 4, the plateau is hardly reached and additionally reads could theoretically reveal more phylotypes. Finally for SFA 3 and 5, all phylotypes present in the samples have clearly not been sequenced, which is remarkable considering the total number of reads approaching 4 000 000.

Simulated saturation curves

350

300

250

SFA2 200 SFA3 SFA4 150 SFA5

Phylotypes SFA6 100

50

0 0 0.1 0.2 0.3 0.4 0.5 0.6 % total reads

Figure 3.3.5. Simulated saturation curves. A plateau indicates that most of the phylotypes present in the sample would be sequenced.

The case of SFA 6 is particularly interesting since this sample, containing the extract of a single species (R. filosa ). Yet, our analyses revealed four different phylotypes including the expected sequence of R. filosa . The three other phylotypes are represented by less than 10 reads and consist in a “C”-rich sequence (probably erratic), in an undetermined taxon, and in a 119 sequence matching at 100% a Polymorphinidae lageniid present in our database. The last sequence was also found in SFA 4 and 5, suggesting that the three samples were probably contaminated with PCR product of that species.

The pie charts (Fig. 3.3.6 to 3.3.9) represent the reads number of each phylotypes. Because of the PCR potential bias, there is no guaranty that this number reflects the amount of rDNA copies or number of specimens. To assess somehow the diversity of the samples (including the number of specimens), quantitative PCR using specific primers designed for each species coupled with Solexa sequencing would be necessary.

The most striking point in the four pie charts (Fig. 3.3.6 to 3.3.9) as well as in Fig. 3.3.9, is the great proportion of undetermined phylotypes, which exceed 40 % of reads in SFA 5 and half of the phylotypes richness for SFA 3 and SFA 4. Those phylotypes are likely to be foraminifera but could not be surely assigned to any known groups from the database. It is possible that at least some of them represent the “hidden” foraminiferal richness present in the sediment. They could correspond to the small or/and naked foraminiferal species that have been overlooked or simply out of reach in routine microscopic observations.

A constant trait of the four samples is the great proportion of monothalamous taxa, which reach about 60% of reads in SFA 4 (Fig. 3.3.8) and consist in the richest phylotypes for all samples (Fig. 3.3.10). Most of them are not defined at genus or family level, which highlights the need of further taxonomic study of this poorly known but highly diversified group.

There is no direct correlation between the total number of reads and the number of phylotypes. For that reason, it could be proposed that the number of phylotypes is proportional to the species richness of the sample. However, this idea is arguable, since we have used the same criteria to distinguish phylotypes for all taxonomic groups. Yet, as we have seen before, the level of genetic variation differs between taxonomic groups and the same sequence divergence values can have different taxonomic meaning in different taxa. If highly variable taxa constitute the greatest part of the richness, the number of phylotypes will exceed the real number of species. On the contrary, if the sample richness consists mainly of taxa with low genetic divergence, the actual number of species will be underestimated by the

120 phylotypes. Therefore, we propose that SFA 3 and SFA 4 are the richest samples provided that they are similar regarding the average genetic divergence of their taxa.

It is interesting to notice that there seems to be a correlation between the number of phylotypes and the number of identified taxa with 100% match. In a certain way, this is not surprising since chances to find something known in a given sample increase statistically with the richness of that sample. However, the number of high matches could be largely bias by our database, which may not reflect the global foraminiferal richness. Indeed, according to sampling efforts, some well studied groups such as rotaliids are likely to be overrepresented in our database.

Another striking point is the great difference between SFA 2 and SFA 3 regarding their phylotype richness and composition. Both samples are coming from the same station (extremely close coordinates and depths) and should be physically distant by few meters. If we believe that the sampling methods (box corer for SFA 2 and multicorer for SFA 3) are not causing that difference, this could highlight the surprisingly high small scale variation of foraminiferal richness.

Surprising is also the presence of typically shallow water genera, such as Jadammina and Ammotium in our samples. This can be explained by the presence in the deep-sea of species closely related to these two genera. Generally slow rates of textulariids and relatively poor database for this group can make the distinction of these species difficult at generic level.

Finally, some studies suggested the presence of extracellular DNA (Dell'Anno and Danovaro, 2005b; Naviaux et al., 2005; Not et al., in Press; Vlassov et al., 2007), prone to be amplified by PCR and to appear in environmental richness assessment (see also Appendix D). For that reason, we cannot exclude that some of the phylotypes revealed by Solexa analyses could come from dead specimens, which DNA is preserved in the sediment or cells debris transported by the water column.

121

Silversaccam (ARKXXI 5414.26) Unknown allogromiid (Lagena McM 2178) SFA 2 Unknown allogromiid (XenoFlatnew 230 12) - 4 phylotypes Bathyallogromia Silversaccam (RIS 3894) Unknown allogromiid (Normanina WED 5177.92) - 4 phylotypes MON - 5 phylotypes Reophax Jadammina - 5 phylotypes Ammotium - 2 phylotypes TEX - 3 phylotypes ROT - 7 phylotypes UNDETERMINED - 41 phylotypes

Figure 3.3.6. Phylotypes richness of SFA 2 (3538m). Parts of the pie chart are proportional to the number of reads. Identifications with 100% match are indicated with plain colors in chart and with arrows in legend. Undetermined phylotypes are represented in black. “MON” stand for “monothalamous undetermined taxa”(bold hatched in red), “TEX” for “textulariid undetermined taxa” (bold hatched in green), “ROT” for “rotaliid undetermined taxa” (bold hatchet in blue) and “LAG” for “lageniid undetermined taxa” (bold hatched in purple).

Silversaccam (ARKXXI 5414.26) Unknown allogromiid (XenoFlatnew 229 2) SFA 3 Unknown allogromiid (k49) Unknown allogromiid (XenoFlatnew 230 12) - 24 phylotypes Environmental sample (Cha2A1) - 2 phylotypes Unknown allogromiid (Gromia-like RIS 3891) Unknown allogromiid (Lagena McM 2178) - 2 phylotypes Rhabdammina Bathysiphon sp.(ARKXXI 5428.1) Unknown allogromiid (XenoGal 246 33) Unknown allogromiid (Normanina WED 5177.92) - 8 phylotypes Psammosphaera Pelosina Saccammina Unknown allogromiid (NH 1212) Silversaccam (ARKXXI 5414.26) - 2 phylotypes MON - 26 phylotypes Ammotium - 4 phylotypes Jadammina - 8 phylotypes Reophax - 2 phylotypes TEX - 3 phylotypes Epistominella arctica (ARKXXI 5572.47) Nonionella ROT - 16 phylotypes UNDETERMINED - 193 phylotypes

Figure 3.3.7. Phylotypes richness of SFA 3 (3519 m). For details see Fig. 3.3.5.

122

Unknown allogromiid (k49) Pelosina variabilis (SV 2852) SFA 4 Micrometula sp. (USH 7632.1) Unknown allogromiid (Septuma WED 5967.122) Unknown allogromiid (Septuma WED 5125.5) Silversaccam (ARKXXI 5414.26) Capsammina - 11 phylotypes Psammophaga - 2 phylotypes Crithionina - 2 phylotypes Leptammina Unknown allogromiid (Lagena McM 2178) Rhabdammina - 4 phylotypes MON - 52 phylotypes Reophax curtus (Korsun 9713.16) Reophax sp. (SV 4676.1) Carterina - 5 phylotypes Jadammina - 4 phylotypes Reophax - 6 phylotypes Spiroplectammina TEX - 5 phylotypes Epistominella arctica (ARKXXI 5572.47) Stainforthia fusiformis (SV 2641) Melonis affinis (M474-8) Astrononion gallowayi (Korsun 9692.6) Bolivina ROT - 18 phylotypes Polymorphinidae (Chupa 9800.1) Lagenammina arenulata (ADM 8207) UNDETERMINED - 175 phylotypes

Figure 3.3.8. Phylotypes richness of SFA 4 (221 m). For details see Fig. 3.3.5.

Unknown allogromiid (Septuma WED 5967.122) Unknown allogromiid (k49) SFA 5 Bathysiphon sp. (ARKXXI 5428.1) Bathyallogromia weddellensis (WED 3363) Unknown allogromiid (WED 3415a) Silversaccam (ARKXXI 5414.26) Tinogullmia (NH 1199) Unknown allogromiid (XenoFlatnew 230 12) - 33 phylotypes Silversaccam (DML 4016) Unknown allogromiid (Lagena McM 2178) Bathyallogromia - 2 phylotypes Psammosphaera-like (RIS 3918) Micrometula - 2 phylotypes MON - 56 phylotypes Reophax ROT - 3 phylotypes Polymorphinidae (Chupa 9800.1) UNDETERMINED - 130 phylotypes

Figure 3.3.9. Phylotypes richness of SFA 5 (4443 m). For details see Fig. 3.3.5.

123 350

300 LAGENIIDS 250 ROTALIIDS 200 TEXTULARIIDS MONOTHALAMOUS 150 UNDETERMINED 100

number of phylotypes 50

0 SFA 2 SFA 3 SFA 4 SFA 5

Figure 3.3.10. Number of phylotypes for each group (lageniids, rotaliids, textulariids and monothalamous) and for each sample.

Conclusions

Our analyses confirm that the variable regions of the SSU rDNA can be used for identification of foraminiferal species. Among them the region I (helix 37f) was chosen as the most promising candidate for richness assessment by massive sequencing methods. As we have seen, an extremely short fragment (36 bp) of this region offered a quite high taxonomic resolution allowing identification of many new phylotypes. Our preliminary study revealed that a great part of samples richness consists in monothalamous and undetermined phylotypes. This suggests that our vision of foraminiferal diversity might be largely bias by microscopic observations, in which several small or naked taxa do not appear obviously.

Acknowledgements

We thank U. Schauer and the Captain, officers and crew of the Polarstern for their assistance during ARK XXII-2. We also thank D. Trumbi ć for his help during analyses and M. Schweizer for the schema of the SSU rRNA secondary structure.

124 Chapter 4 Cosmopolitanism

4.1 Introduction

As it has been proposed in the general introduction, the dispersal ability of species should directly affect their diversity. Molecular analyses represent an efficient tool to investigate biogeography. Until recently, molecular phylogenetic studies have tended in most cases to divide morphospecies into several distinct genetic entities or cryptic species, reducing in this way the geographic range of each of them (Erwin and Thacker, 2008; Fontaneto et al., in Press; Zakšek et al., 2009). Planktonic foraminiferal taxa have been shown to display high crypticity sometimes related to geographical narrow niches (Aurahs et al., 2009). Intuitively, benthic foraminifera could be thought to have even more restricted distribution. The hypothesis that diversification and dispersal processes differ between the deep sea and the shallow waters could be ideally tested with benthic foraminiferal taxa.

In this chapter, we present two papers on the distribution of some common calcareous benthic foraminifera. The first study involves three morphospecies ( Epistominella exigua , Cibicides wuellerstorfi and Oridorsalis umbonatus ) widely dispersed in the deep sea, and which are investigated here by analysing the SSU and ITS rDNA sequences to reveal potential gene flows between populations from the two Polar regions. The second paper extends this analysis to the Pacific Ocean to test the ubiquity of E. exigua at global scale. It also provides phylogeny of sister species of E. exigua (including E. vitrea and E. arctica ) from shallower depth in order to compare their respective genetic variability, crypticity and thus also, their geographic distribution.

125 126 4.2 Bipolar gene flow in deep-sea benthic foraminifera

Jan Pawlowski 1, José Fahrni 1, Béatrice Lecroq 1, David Longet 1, Nils Cornelius 2, Laurent Excoffier 3, Tomas Cedhagen 4 and Andrew John Gooday 5

1Department of Zoology and Animal Biology, University of Geneva, Switzerland.

2Natural History Museum, London, UK

3Zoological Institute, University of Bern, Switzerland

4Department of Marine Ecology, University of Aarhus, 8200 Aarhus N, Denmark.

5National Oceanographic Centre, European Way, Southampton SO14 3ZH, UK.

Published in: Molecular Ecology (2007) 16 : 4089-4096 doi: 10.1111/j.1365-294X.2007.03465.x

127 Abstract

Despite its often featureless appearance, the deep ocean floor includes some of the most diverse habitats on Earth. However, the accurate assessment of global deep-sea diversity is impeded by paucity of data on the geographical ranges of bottom-dwelling species, particularly at the genetic level. Here, we present molecular evidence for exceptionally wide distribution of benthic foraminifera, which constitute the major part of deep-sea meiofauna. Our analyses of nuclear ribosomal RNA genes revealed high genetic similarity between Arctic and Antarctic populations of three common deep-sea foraminiferal species (Epistominella exigua , Cibicides wuellerstorfi and Oridorsalis umbonatus ), separated by distances of up to 17,000 km. Our results contrast with the substantial level of cryptic diversity usually revealed by molecular studies of shallow-water benthic and planktonic marine organisms. The very broad ranges of the deep-sea foraminifera that we examined support the hypothesis of global distribution of small-sized eukaryotes and suggest that deep- sea biodiversity may be more modest at global scales than present estimates suggest.

Introduction

Recent molecular phylogenetic studies unveiled an extraordinarily rich hidden diversity of marine single-cell eukaryotes (Moreira and Lopez-Garcia 2002). However, most of these studies focused on shallow-water and pelagic environments, while relatively little is known on diversity of eukaryotes living at the bottom of the deep ocean (Edgcomb et al. 2002, Lopez-Garcia et al. 2003). It has been proposed that the deep-sea diversity is astronomically large based on local scale studies of bathyal macrofauna (Grassle and Maciolek 1992). However, the extent to which high local biodiversity can be extrapolated to larger spatial scales is hotly disputed (Lambshead and Boucher 2003). There is a general lack of genetic data on geographical ranges of bottom-dwelling deep-sea species (Etter et al. 1999). A few genetic studies of deep-sea hydrothermal vent animals provided evidence for dispersal barriers and isolation of deep-sea populations related to deep-oceanic currents and topographic features (Won et al. 2003, Hurtado et al. 2004). Whether such genetic differentiation can also be observed in deep-sea micro- and meiofauna is unknown.

128 Benthic foraminifera constitute the major component of deep-sea meiofauna and include several cosmopolitan species that occur in almost all regions of the global ocean (Murray 1991, Gooday et al. 2004). Some have an excellent Cenozoic and Quaternary fossil record and are widely used as paleoceanographic and paleoclimatic proxies (Thomas 1992, Zachos et al. 2001). Their identification is based entirely on test morphology. Recently, however, the accuracy of such identifications has been challenged by molecular studies revealing extraordinarily rich cryptic diversity among many groups of foraminifera (Holzmann 2000, Darling et al. 1999, Pawlowski et al. 2002). Most of these studies used the SSU and LSU rRNA genes that evolve at different rates in different taxonomic groups (Pawlowski et al. 1997). The fast evolving SSU rDNA sequences have been used to show that some planktonic morphospecies comprise a number of cryptic species, usually with different geographic distributions and ecological preferences (de Vargas et al. 1999, Darling et al. 1999). The SSU rDNA sequences were also used for study the diversity of benthic monothalamous foraminifera (Pawlowski et al. 2002), while the diversity of shallow water rotaliid genus Ammonia was inferred from partial LSU rDNA sequences (Holzmann and Pawlowski 2000). The most rapidly evolving ITS region was used rather exceptionally in the case of some planktonic (de Vargas et al. 2001) and benthic (Tsuchyia et al. 2003, Schweizer et al. 2005, Grimm et al. 2007) species. The foraminiferal mitochondrial genes are not available yet (work in progress).

Most of molecular studies were focused on planktonic and shallow-water foraminifera. Until now, there have been few genetic analyses of deep-sea benthic foraminifera (Gooday and Pawlowski 2004, Gooday et al. 2004). One of these studies revealed cryptic diversity in a foraminiferal genus Chilostomella collected at depth between 600 and 1500 meters (Grimm et al. 2007). Bearing in mind the growing evidence for genetic differentiation among metazoan populations on bathyal continental margins (Etter et al. 1999), we expected that cryptic diversity would be prevalent among benthic foraminiferal species in the deep-sea.

To test this hypothesis we analysed 223 sequences of the SSU and ITS ribosomal genes from three well-known calcareous, foraminiferal morphospecies ( Epistominella exigua, Cibicides wuellerstorfi, Oridorsalis umbonatus ), all of which are widely distributed on the ocean floor (Murray 1991). Our results show that Arctic and Antarctic populations of these species are very similar genetically suggesting that molecular diversity of deep-sea meiofauna may be lower than expected.

129

Figure 4.2.1. Map indicating sampling localities of deep-sea foraminifera from Arctic, Antarctic and North Atlantic.

130 Material and Methods

Sampling The samples were taken from 30 sites in the Arctic Ocean and the Southern Ocean with distances between sampling sites ranging from 15,487 to 16,981 km, and water depths ranging from 572 to 4975 m (Fig. 4.2.1). Coordinates and depths of sampling sites are given in Appendix G, Table G1-G3. In total, we examined 37 samples from Arctic Ocean, 24 samples from Weddell Sea, 2 samples from Norwegian Sea, and 2 samples from NE Atlantic. Foraminifera were collected during RV Polarstern cruises ANT-XIV/4 (ANDEEP project cruise II), ANT-XXII/3 (ANDEEP project cruise III) and ARK XXI-1b. Additional specimens (2) from NE Atlantic were collected during RRS Charles Darwin cruise 158 and Eurostrataform mission 64PE218. Foraminifera were picked individually on board from sediment samples sieved through serial 1-mm, 0.5-mm, and 0.125-mm meshes. Some specimens were immediately transferred to microtubes containing 60 µl of guanidine buffer while others were frozen. Most of the extractions have been done with a single specimen, except eight extractions of E. exigua and four extractions of O. umbonatus , in which up to six specimens were extracted together. Because some extractions contained more than one specimen, we used a term “isolate” rather than “specimen”. DNA extraction, PCR, cloning and sequencing DNA was isolated from single cells following the guanidine DNA extraction protocol (Pawlowski 2000). A fragment of the SSU rRNA gene was amplified by PCR with the foraminiferal specific primer s14F3 (5’ACG CA(AC) GTG TGA AAC TTG), starting at position 1807 in Ammonia beccarii sequence X86094 and universal eukaryotic primer sB (5’ TGA TCC TTC TGC AGG TTC ACC TAC), starting at position 2853 in A. beccarii sequence X86094. It has been re-amplified using nested foraminiferal specific primer s14F1 (5' AAG GGC ACC ACA AGA ACG C) starting at position 1838 in A. beccarii sequence X86094, and universal primer sB. The complete ITS rDNA region was amplified using universal eukaryotic primer sBr (5’ GTA GGT GAA CCT GCA GAA GG) situated at the 3’ end of the SSU rDNA (position 2853 in A. beccarii sequence X86094) and the foraminiferal specific primer 2TAIC (5’ CTC ACT CGA GCT GAT GTG) situated at the 5’ end of the LSU rDNA. PCR products were purified using High Pure PCR Purification Kit (Roche Diagnostics), ligated into pCR2.1 TOPO TA vector (Invitrogen) and cloned in XL-2 Blue 131 Ultracompetent Cells (Stratagene). Clones were screened by amplification with the OriMaster kit (Eppendorf). Products were sequenced without previous purification using the ABI- PRISM Big Dye Terminator Cycle Sequencing Kit (Applied Biosystems), and analysed with an ABI-3130xl DNA sequencer (Applied Biosystems), all according to the manufacturer’s instructions. The new sequences were deposited in the EMBL/GenBank Nucleotide Sequence Database (accession numbers EF 653455-EF 653572). Phylogenetic analyses Twenty-one SSU and 202 ITS rDNA sequences were obtained from 29 isolates of E. exigua , 21 isolates of C. wuellerstorfi , and 16 isolates of O. umbonatus . For the majority of specimens, 3-5 clones were sequenced. The sequences were aligned using Seaview software (Galtier et al. 1996) and sequence divergence was calculated using PhyloWin (Galtier et al. 1996). Phylogenetic analysis of SSU rDNA sequences, including 23 sequences of other rotaliid foraminifera were performed using PhyML v2.4 (Guidon and Gascuel 2003), with GTR + Γ model (6 categories, α = 0.107). The ITS rDNA sequences were aligned and analysed separately for each species. Consensus ITS sequences for each individual specimen were obtained using Seaview (Galtier et al. 1996). Haplotype ITS networks were established using TCS software, with gaps considered as 5th state (Clement et al. 2000). The TCS program implements a statistical parsimony approach for estimating genealogical relationships among sequences using the method of Templeton et al. (1992). The program collapses identical sequences into haplotypes, calculates the frequencies of the haplotypes in the sample and connects them into a network. By taking into account the presence of ancestral haplotypes, low level of variation and possibility of recombination, the TCS method provides more accurate estimates of gene genealogy at the population level than traditional phylogenetic methods. Statistical analyses The extent of differentiation between populations was assessed by performing an Analysis of Molecular Variance (AMOVA, Excoffier et al. 1992), taking the genetic diversity between clones within individuals into account. For this analysis, sites with indels were discarded. For E. exigua, individuals sampled below 4650 m were assigned to a “deep” Antarctic population, which was contrasted to the other samples of the south population and individuals from the north population. All significance levels were obtained by 10,000 permutations. 132

Results

SSU and ITS rDNA phylogeny At first, we analysed a fragment of the SSU rDNA that is commonly used to study the genetic diversity in foraminifera (Pawlowski 2000). The total length of this fragment varies between 961 and 1023 nucleotides (Table 1). We found no differences in the SSU sequences of all examined C. wuellerstorfi and only a single transition in two Antarctic E. exigua belonging to a “deep” abyssal population. The SSU sequences of O. umbonatus were much more variable. This species shows an unusually high level of intra-individual polymorphism, with some copies of SSU rDNA diverging by up to 2.3% within the same individual (Table 1), however, most of these variations are present in a single variable region of the SSU. As shown in Fig. 4.2.1, the three examined species belong to the same clade of rotaliid foraminifera. This clade includes also species from different localities in Northern hemisphere (Stainforthia fusiformis , Bulimina marginata , Cibicides lobatulus ) but none of them are as genetically homogenous as the Arctic and Antarctic populations of E. exigua and C. wuellerstorfi .

Table 4.2.1. SSU and ITS rDNA sequence data for E. exigua , C. wuellerstorfi and O. umbonatus.

E. exigua C. wuellerstorfi O. umbonatus SSU ITS SSU ITS SSU ITS Number of analysed sequences 14 92 10 53 23 54 Total length of sequence alignment 1 961 977 1023 1136 989 865 Percentage of variable sites 0.9% 12.1% 0.0% 9.2% 4.4% 5.1% Percentage of informative sites 0.2% 1.9% 0.0% 1.8% 3.6% 0.9% Maximum sequence divergence 2 0.4% 1.4% 0.0% 1.1% 2.9% 1.1% Maximum intra-individual sequence divergence 2 0.4% 1.2% 0.0% 1.0% 2.3% 0.9% 1 Without gaps and ambigous characters (estimated by PhyloWin, Galtier et al. 1996) 2 Excluding the ITS of C. wuellerstorfi (5247) and O. umbonatus (5156,5832), which sequences differed by 2.15% and 3.97%, respectively.

133

Figure 4.2.2. Relationships between Arctic, Antarctic and North Atlantic deep-sea foraminifera (E. exigua , C. wuellerstorfi , O. umbonatus ) illustrated by the SSU rDNA- based maximum likelihood tree. Each sequence in the ML tree is marked with DNA isolate number referred to the table 1. The numbers at internal nodes represent the bootstrap support values based on 100 replicates.

134 To ensure that our first results were not due to an artifact caused by exceptionally slow evolutionary rates of the SSU rDNA of examined species, we analysed the ITS rDNA which is the most rapidly evolving region of a nuclear genome available for foraminifera. The total length of the ITS alignment ranges from 865 nucleotides in O. umbonatus to 1136 in C. wuellerstorfi , with most of the length variations observed in the ITS1 region. The number of variable sites was relatively elevated, however, only few of these sites were phylogenetically informative (Table 1). For each of the three species, the majority of ITS sequences were almost identical, with mean sequence divergence less than 1%, and the maximum values of intra-individual polymorphism as high as the variability between individuals (Table 1). We found only three specimens ( Cibicides isolate 5247 and Oridorsalis isolates 5156, 5832) that were significantly different from all other representatives of their respective species. Excluding these three isolates, the specimens of each species, represented by ITS consensus sequences, formed a network in statistical parsimony analysis (Fig. 4.2.2). Genetic differentiation between Arctic and Antarctic populations was visible only in O. umbonatus , in which two populations differed by one transition and four indels. However, since the Southern Ocean population of this species was represented by two specimens only, it is highly probable that more diverse ITS copies will be found later. No phylogenetic signal clearly distinguishes the Arctic and Antarctic populations in the other two species. Population genetics A population genetics approach was used to study the historical relationship between the polar populations of the three foraminiferal species. The analysis of the genetic structure was performed by considering three populations of E. exigua : deep abyssal Antarctic E. exigua (4650-4975m, n=28 sequences); abyssal Antarctic E. exigua (2600-4600 m; n=13) , and bathyal northern E. exigua (1352-2784 m; n=40). The AMOVA analysis revealed that E. exigua was significantly differentiated since 28% of the genetic diversity (p<0.001; 90% CI: 5.0-45.0) was due to differences between populations. The analysis of pairwise distances, however, showed that this large differentiation was mainly due the divergence of the deep abyssal Antarctic population. Indeed FCT values between the deep abyssal population and the remaining southern and northern populations were equal to 0.28 and 0.17, respectively, while the abyssal Antarctic population differed much less from the northern bathyal population only

(FCT =0.12, p=0.002).

135

Figure 4.2.3. Haplotype networks of E. exigua , C. wuellerstorfi and O. umbonatus based on the ITS rDNA and obtained by TCS software. Networks within each clade were delineated with 95% certainty, the gaps being treated as a fifth state. Haplotype are marked with DNA isolate number referred to the table 1. The representative specimens of each species from Arctic and Antarctic are illustrated. Scale bar = 0.1 mm.

136 For O. umbonatus , the north and south populations were significantly differentiated

(p=0.04) with an FCT value of 0.33 (90% CI: 0.24-0.43), while the northern and souther populations of C. wuellerstorfi were interestingly not statistically differentiated, with a very low FCT value of 0.03 (p=0.078, 90% CI: 0.02-0.04).

Discussion

In contrast to the high degree of molecular diversity exhibited by some coastal benthic (Pawlowski et al. 2002) and oceanic planktonic (Darling et al. 2004) polar foraminifera, we found very limited genetic differentiation among two out of three deep-sea species that we examined. Each probably represents a huge metapopulation extending from pole to pole, living wherever a suitable habitat exists. A few sequences of E. exigua and C. wuellerstorfi obtained from the Porcupine Abyssal Plain, Setubal Canyon and Norwegian Sea (in red in Fig. 4.2.2) indicate that genetically similar individuals are present in the North Atlantic Ocean. Long-distance dispersal capabilities and high levels of gene flow have been observed in deep-sea hydrothermal vent macroinvertebrates with planktonic larval stages (Van Dover et al. 2002). Although planktotrophic larvae can disperse widely, various geographic and hydrological barriers seem to limit their distribution at larger spatial scales (Won et al. 2003, Hurtado et al. 2004). Among microbial eukaryotes, global dispersal has been suggested for hydrothermal vents flagellates (Atkins et al. 2000), marine picoeukaryotic algae (Slapeta et al. 2006), and some planktonic foraminifera (Darling et al. 2000). However, only bacteria and archaebacteria are so far reported to have genetically similar species in Arctic and Antarctic oceans (Hollibaugh et al. 2002, Brinkmeyer et al. 2003, Bano et al. 2004). Our study provides the first evidence for bipolar and possibly global distributions among benthic organisms of meiofaunal size.

How do we explain the high degree of genetic similarity of deep-sea populations? Size may be a critical factor. Some macrofaunal (animal) morphospecies appear to be confined to particular regions of the deep ocean (Grassle & Maciolek, 1992; Allen & Sanders, 1996). For microbial eukaryotes and small metazoans (< 1 mm), on the other hand, it has been proposed that the huge population sizes ensure ubiquitous distributions (Finlay 2002, Finlay et al. 2004). Genetic analyses of freshwater and marine picoeukaryotes, averaging 1-2 microns in size (Atkins et al. 2000, Richards et al. 2005, Slapeta et al. 2006) have confirmed this

137 observation for the very small organisms. The tests of the foraminiferal species that we examined are one to two orders of magnitude larger, in the size range 100-500 microns. Nevertheless, the survival of microbe-sized foraminiferal propagules in habitats that are unfavorable to adults (Alve and Goldstein, 2003) implies an ability to disperse widely in marine environments and even small adult tests can be entrained by currents (Alve 1999). Thus, gene flow between Antarctic and Arctic populations via the Atlantic Ocean may be facilitated by the transport of juvenile or possibly small adult foraminifera by thermohaline circulation. The Weddell Sea is the source of Antarctic Bottom Water (AABW) which provides much of the deep water of the World Ocean. AABW flows into the SW Atlantic, penetrates into the NW Atlantic through the Vema Channel and finally into the NE Atlantic via the Romanche Fracture Zone. The influence of AABW persists in a diluted form at least as far north as 56°N in the Rockall Through (New and Smythe-Wright, 2001). The bathymetric ranges of the species that we examined ( C. wuellerstofi 1106-3485 m; E. exigua 1351-4975 m; O. umbonatus 573-4407 m) are wide enough to enable them to cross most bathymetric obstacles.

The extremely slow rates of evolution in some deep-sea foraminiferal species could be another factor explaining our results. The substitution rates in foraminiferal ribosomal genes can vary between taxonomic groups and it has been shown that some planktonic species evolve more than 50 times faster than the benthic ones (Pawlowski et al. 1997, de Vargas and Pawlowski 1998). Similarly, it cannot be excluded that the deep bottom species evolve much slower than the shallow water ones. This sounds particularly plausible in view of exceptional geological longevity of deep-sea foraminiferal species compared to coastal ones. Modern deep-sea assemblages emerged 15 million years in the Middle Miocene and many species have fossil records extending back to that period (Miller et al., 1992). One of our bipolar species, E. exigua, first appeared in the Oligocene, 35 million years ago (Thomas and Gooday, 1996), yet the recent specimens of E. exigua are morphologically undistinguishable from their fossil ancestors. Is this morphological stasis related to lower level of genetic variations in this species? If further molecular studies confirm this hypothesis, than we could suggest that the observed homogeneity of Antarctic and Arctic populations reflects a combination of dispersal by thermohaline circulation and genetic slowdown.

Establishing the geographical ranges of deep-sea benthic species is a crucial step in extrapolating from local species diversity on the ocean floor to regional and global diversity.

138 Yet even at the morphospecies level, ranges are poorly known for many taxa (Thistle, 2003). Existing estimates assume a relatively high rate of species turnover leading to a very diverse ocean (Grassle & Maciolek, 1992). However, if wide species ranges are common (i.e. species turnover rates are low), and cryptic species uncommon, then the global benthic diversity may be much more modest than these estimates suggest. Our study clearly shows that genetic diversity in some important, typically abyssal foraminiferal species is minimal on a global scale. We predict that other deep-sea foraminifera with cosmopolitan distributions (Murray 1991; Gooday et al., 2004) will also prove to be genetically homogeneous. This prediction implies slow rates of species turnover which would place constraints on the magnitude of regional and global foraminiferal diversity. Recent evidence suggests that even nematodes, a group which lacks dispersive larval stages, have wide morphospecies ranges in the abyssal deep sea (Lambshead and Boucher, 2003), and so these results may apply to other meiofaunal taxa as well.

Our study has further important implications in palaeoceanography. The demonstration of gene flow across large distances among well-known, deep-sea calcareous foraminifera suggests that test morphology provides a sound basis for discriminating species. This conclusion reinforces the widespread use of the fossil shells of these protists to reconstruct the productivity and circulation of ancient oceans (Gooday 2003).

Acknowledgements

We thank A. Brandt, B. Hilbig, I. Schewe, E. Fahrbach, P. Lemke, organizers and scientific leaders of ANDEEP II, ANDEEP III and ARK XXI/1b cruises and captains and crew of R/V Polarstern for help in collecting samples. M. Schweizer and A. Aranda da Silva are acknowledged for collecting and isolating DNA from North Atlantic foraminifera. S. Palumbi and two anonymous referees provided valuable comments to improve the manuscript. The work was supported by the Swiss National Science Foundation (grant 3100A0-112645 to J.P.), the U.K. Natural Environment Research Council (N.C., A.J.G.) and the National Science Research Foundation, Denmark (T.C.)

139 140 4.3 Global genetic homogeneity in the deep-sea foraminiferan Epistominella exigua (Rotaliida: Pseudoparrellidae)

Béatrice Lecroq 1, Andrew John Gooday 2 and Jan Pawlowski 1

1Department of Zoology and Animal Biology, University of Geneva, Switzerland.

2National Oceanographic Centre, European Way, Southampton SO14 3ZH, UK.

Published in: Zootaxa (2009) 2096 : 23-32

141 Abstract

Epistominella exigua is one of the most common deep-sea foraminiferal morphospecies and has a world-wide distribution. A recent molecular study revealed high genetic similarity between Arctic, Atlantic and Antarctic populations of this species. Here, we show that the small-subunit (SSU) and internal transcribed spacer (ITS) rDNA sequences of an E. exigua population from Pacific are almost identical to those reported previously from the other three oceans. This result confirms the genetic homogeneity of E. exigua , which contrasts with the prevalence of highly differentiated populations in planktonic and shallow-water benthic foraminifera. We discuss special features of diversifications mechanisms in the deep sea that may be responsible for the lack of genetic differentiation and global distribution of some meiofauna species.

Introduction

At a local scale, deep-ocean sediments contain some of the most species rich communities on Earth (Grassle & Maciolek 1992). Recently, there has been an increasing emphasis on the relationship between local diversity and diversity at larger (regional to global) scales (Levin et al., 2001). However, there is still little information available about how widely species are distributed or about biodiversity at the genetic level (Etter et al., 1999, 2005). There is a particular need to increase the genetic database on small size deep-sea benthic organisms in order to learn whether the biodiversification mechanisms operating there are different from those in shallow-water.

Deep-sea benthic foraminifera provide particularly good models to tackle these questions. They occur in all marine environments and their rich fossil record reveals their morphological evolution over geological time. Molecular studies, focused mainly on planktonic and shallow-water foraminiferal species, have demonstrated considerable cryptic diversity (reviewed in Pawlowski and Holzmann 2008, Darling et al. 2008). In striking contrast, three deep-sea species showed very low levels of genetic differentiation between populations in the Arctic and Antarctic sectors of the Atlantic, separated by a distance of up to 17,000 km (Pawlowski et al., 2007).

142 To explore whether this surprising degree of genetic homogeneity along a north-south axis was indicative of a global distribution for some deep-sea benthic meiofauna, we examined molecular diversity in Epistominella exigua from the Pacific Ocean and compared it to the earlier data on Arctic, Atlantic and Southern Oceans populations of this well-known and widely-distributed foraminiferal morphospecies (Pawlowski et al., 2007). Our analyses were based on sequences of the ITS rDNA, which have already revealed cryptic species of benthic foraminifera (Tsuchiya et al., 2003). We found that the Pacific population is genetically similar to those from the other three oceans. This represents strong evidence that E. exigua is globally distributed and points to some major differences between biodiversification mechanisms occurring in deep-sea and shallow-water environments .

Material and Methods

Sampling

Pacific Epistominella exigua were collected off Japan during RV Hakuho-Maru cruise KH06- 03. Our study includes also new sequences of E. vitrea and two unidentified species of genus Epistominella (morphologically close to E. vitrea ) collected in Admiralty Bay (King George Island, Antarctica) (Majewski et al. 2007) and off Ushuaia (Argentina), one unidentified specimen collected off Japan, as well as two specimens of E. arctica collected during ANDEEP III cruise to Weddell Sea and during ARKXXI1b cruise to Arctic Ocean. Detailed on sampling sites for each specimen are compiled in Appendix H, Table H1 and H2.

Samples were collected using a multiple corer equipped with tubes of 8.2 cm diameter. The upper 2 cm layer of selected cores was sliced off, sieved on a 63-micron mesh screen, and foraminifera picked out individually by hand under a binocular microscope. Epistominella specimens were either directly fixed in guanidine DNA extraction buffer or stored frozen at - 80°C.

Sequencing, phylogenetic and statistical analyses

The partial SSUrDNA and complete ITS rDNA region were amplified and sequenced as described in Pawlowski et al. (2007). Thirty-three new DNA sequences were obtained for partial SSU and 22 for ITS (1 to 6 clones were sequenced for each amplified product). They

143 were deposited in the EMBL/GenBank under accession numbers listed in Appendix H, Table H1 and H2. The sequences were aligned using Seaview software and sequence divergence was calculated using PhyloWin (Galtier et al., 1996) with Kimura 2 parameters and pair wise comparison. SSU rDNA tree was built according to the Maximum Likelihood (ML) method using PhyML program (Guindon and Gascuel, 2003), with the GTR + I + G model (suggested by Mr Modeltest, Posada and Crandall 1998) with 6 categories of substitution rates and 1000 replicates for bootstrap analysis. Bayesian phylogenetic analyses were also performed on the same dataset with the same model using MrBayes program via Bioportal (http://www.bioportal.uio.no , accessed 2008).

Haplotype ITS network was established with E. exigua sequences using TCS software, with gaps considered as 5 th state (Clement et al., 2000). Population genetic analysis was performed with Analysis of Molecular Variance (AMOVA, Excoffier et al., 1992). We defined four hypothetic groups of different geographic origin (Arctic, Antarctic, Atlantic and

Pacific) and tested their relevance by computing Fixation Indices FSC and FCT with Arlequin ver 3.01 (Excoffier et al., 2005). Significance tests were performed with 10,100 permutations.

Results

SSU rDNA

New SSU rDNA sequences were obtained for 5 specimens of Epistominella exigua , 2 specimens of E. vitrea, 2 specimens of E. arctica, 3 specimens of Epistominella sp. 1, 2 specimens of Epistominella sp. 2 and 1 specimen of Epistominella sp. 3. The sequences were compared to 11 specimens of E. exigua from the Arctic Ocean, Weddell Sea and North Atlantic and to 7 specimens of E. vitrea from Weddell Sea and McMurdo Sound. Because we were interested in comparing specimens from extremely distant locations, our study focused on E. exigua . There were almost no differences between partial SSU rDNA sequences derived from this species, The only exceptions were four specimens from Weddell Sea (WED5127, WED5191, WED5222, WED3623), all from sites deeper than 4650 m, which differed from all other, including the Pacific ones, by a single substitution (C – T). The total length of the sequenced SSU fragment was 1021 nucleotides (nt).

144 WED 5127 (AM 491306) WED 5191 (AM491307) 60/63 WED 5222 WED 3623 (DQ195557) 0.02 92/76 ARK 5448 P6928-11 * 58/- ATL 4941 P7180-11 * P7180-12 * ARK 5406 ARK 5459 P6928-15 * Epistominella exigua P7565-22 * P7566-31 * WED 5153 WED 5233-15 ARK 5461 P6929-21 * 63/97 P7565-21 * P6929-22 * P7566-33 * 52/- WED 3614-5 (AM491311) McM 7341-2 (AM491313) 66/- McM 1220-2 (AM491308) McM 1220-5 (AM491310) KG 8250-26 * KG 8250-27 * 63/- KG 8250-24 * Epistominella vitrea 51/- McM 7253-3 (AM491312) McM 7395-1 (AM491314) McM 2060 (DQ45269) 100/94 McM 1220-4 (AM491309) KG 8043-22 * WED 3615-2 (AM491315) WED 3615-1 (AM491316) KG 7890-3* 100/100 KG 7994-7* 68/51 KG 7994-8* Epistominella sp. 1 59/- KG 7994-10 * 74/- KG 8042-18 * 92/- KG 7994-9* WED 5232-12 * 77/67 WED 5232-11 * Epistominella arctica WED 5232-18 * 58/- ARK 5521-34 * 70/99 KG 8042-15 * 72/94 KG 8042-16 * 99/100 KG 8042-12 * USH 7639-2* Epistominella sp. 2 65/94 USH 7639-1* USH 7639-5* 66/96 USH 7639-4* 100/100 P6937-52 * P6937-55 * Epistominella sp. 3 100/100 S. fusiformis (AY934743) S. fusiformis (DQ452714) 100/100 B. marginata (AY359143) B. marginata (AY934747) O. umbonatus O. umbonatus 81/100 O. umbonatus 89/100 O. umbonatus 55/66 O. umbonatus 100/100 O. umbonatus (AM491317) O. umbonatus (AM491318) 100/100 P. subcarinata (AY934754) P. subcarinata (AY934755) 100/100 C. wuellerstorfi 94/100 C. wuellerstorfi C. lobatulus (DQ408649) 100/99 C. lobatulus (DQ408650) 53/- N. venosus P. operculinoides O. ammonoides

Figure 4.3.1. Phylogenetic tree inferred from SSU rDNA sequences showing the position of E. exigua among other Epistominella species and the lack of differentiation between populations of E, exigua from different regions. This tree has been obtained using the ML method with 1000 bootstrap replicates. The support values at internal nodes correspond to ML (left) and Bayesian (right) analyses. Only values over 50% were indicated. Within the genus Epistominella , first letters of the Epistominella sequence names indicate their geographical origin (ARK: Arctic, WED: Weddell Sea, ATL: North Atlantic, P: Pacific, McM: Mc Murdo Sound, USH: Ushuaia, KG: King George Island) and colour indicates a range of depths (purple: 0-200 m; green: 200- 1200 m; dark blue: >1200 m). New sequences are indicated by a star (*). 145 Phylogenetic analyses (Fig. 4.3.1) show E. exigua branching as sister group to E. vitrea, a species found at depths down to 1000 m in the Southern Ocean (Pawlowski et al. 2007). Four other clades of Epistominella can be distinguished, including E. arctica (depth ~ 2600 m), Epistominella sp. 1 (depth ~ 100 m), Epistominella sp. 2 (depth 20-100 m), and Epistominella sp. 3 (depth 1110 m). All of these species (except E. arctica ) form well supported monophyletic clades, but the relationships between these clades are not well resolved.

ITS rDNA

To evaluate the genetic diversity within E. exigua, we analysed the complete ITS rDNA. We compared our 26 new Pacific sequences to 92 previously published sequences of E. exigua from the other three oceans (Pawlowski et al., 2007). The total length of sequenced fragment varied between 992 and 1009 nucleotides. There was a quite high number of variable sites (141) but most of them differed by single nucleotide polymorphisms (SNP) or insertion/deletion events. The maximum percentage of intra-individual polymorphism (1.2%) was almost as high as the variability between individuals (1.5%).

We then performed a population genetics analysis to better understand the internal structure of the E. exigua “global” population. The TCS network (Supplementary Material, Fig. 4.3.3) includes 104 haplotypes for a total of 118 sequences. Every haplotype is connected with one to nine others, which means that they are all extremely close. The lack of any biogeographic pattern in this network indicates that there is no cryptic speciation among the collected specimens. Sequences originating from different geographic regions are often closer to each other than to sequences from the same region.

Finally we performed an AMOVA analysis to quantify the different components of the genetic variations. By computing the Fixation Indices, we evaluated the part of the variation due to the differences inside each specimen, those due to differences between specimens and finally those due to the differences between the “hypothetic” geographic populations: Arctic, Antarctic, Atlantic and Pacific. We found an F CT value of 0.11 (p=

0.0023) and an F SC value of 0.38 (p= 0.0000). This means that a significantly greater part of the genetic variation is due to differences between specimens within each population rather than differences between populations.

146

FSC > F CT indicates that the subdivision of the four geographic populations are not relevant and thus E. exigua specimens form one big genetically homogenous population. This lack of geographic pattern is also obvious in Fig. 4.3.2, which shows sequence divergences within different clones from the same specimen (intraspecimen divergence “DiS”), within each region (intrapopulation divergence “DiP”), and between regions (interpopulations divergence “DIP”). In each case, the minimum value found for DIP is smaller than the maximum value found for DiP and DiS. This means that some sequences from the same site are more different from each other than they are from sequences obtained at other sites. Moreover, for each site some intraspecimen divergences exceed some divergences between sequences from different locations.

0

DiS MAX = 0.011

1 1 0 0< . DI 0 P< < 0 P .0 I 12 D < 0

0.001

DiS MAX =0.006 5

5 0

1 1 1 0

0 0

. .

0 0 2

2 DiS MAX = 0.009

< <

1 1

P P

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0 0

D D

< <

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< 15 0 0 0 0. P< DI 1< 00 0.

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50 µm

Figure 4.3.2. In Background. Map with position of Epistominella exigua sampling sites (red anchors for Antarctic, green for Atlantic, blue for Arctic and yellow for Pacific). In Foreground . E. exigua ITS rDNA sequence divergences. Minimum and maximum values of divergences within each geographic population (DiP) as well as maximum values of intraspecimen divergences (DiS) are indicated in color according the sampling sites. Minimum and maximum values of divergences between each geographic population (DIP) are indicated above black arrows. Inset. Epistominella exigua specimen collected off Japan. 147 N5406 -05 N5406 -37

N5459 -64 S5153 -29 N5466 -56 N5448 -56 S5233 -69 N5459 -13 N5459 -12 N5459 -67 A4941 -46 N5725 -49 N5459 -11 N5536 -13 S5233 -61 N5719 -29 N5459 -61 N5406 -11 S3606 -06 S3634 -51 A5702 -74 S3634 -49 A5702 -76 A5702 -73 S3631 -44 P7180 -41 S5153 -24 S5153 -22 N5406 -39 A4941 -48 S5153 -25 P7180 -45 S3629 -43 A5702 -75 N5406 -38 N5725 -43 N5406 -03 N5726 -50 N5459 -66 A4941 -47 P6928 -19 N5486 -68 P6928 -17 N5448 -53 N5726 -53 N5448 -55 N5719 -30 N5724 -38 P6928 -28 P7566 -73 N5461 -43 P6928 -14 P7566 -72 S5142 -12 N5 486 -69 P6928 -12 P7566 -71 N5718 -24 S5142 -13 P7156 -34 N5461 -41 P7156 -31 S5225 -24 S5142 -11 N5461 -42 P7566 -75 P7156 -35 S5127 -17 N5718_23 S5222 -52 S3625 -32 P6929 -23 S5218 -49 P7565 -63 S3623 -25 S3623 -28 P6929 -30 P6929 -24 S3623 -24 S5127 -11 S5218 -46 S3623 -25a S5218 -45 S5191 -37 S5218 -48 S5191 -36 S5225 -26 S3623 -30 P7565 -61 P6929 -22 P6929 -29 S5222 -53 N5448 -54 N5448 -57 S5222 -54 A4941 -45 S5225 -25 S3623 -27 P6928 -16 S5191 -38 A5701 -61 S512 7-13 S5127 -12 A5701 -63

Figure 4.3.3. ITS sequences network performed by TCS software: schema of genetic relationships between each haplotype (1 node represents a difference of 1 nucleotide or indel). Geographic origin of haplotypes is indicated by the color of the boxes: yellow for Pacific, red for Antarctic, blue for Arctic and green for North Atlantic.

148 Discussion

The present study confirms our previous analyses showing a lack of genetic differentiation between populations of E. exigua from the Arctic, Atlantic and Southern Oceans, with the exception of an abyssal subpopulation from Weddell Sea that may be undergoing speciation (Pawlowski et al. 2007). The SSU phylogenetic tree shows that the diversity within the deep-sea clade of E. exigua from different oceans is as high as the diversity within the shallow-water clades of Epistominella vitrea , Epistominella sp. 1, and Epistominella sp. 2 from the same region (Southern Ocean). We also observe very low diversity between populations of E. arctica from Arctic and Antarctic, but this species is represented in our material by only two specimens. Although the SSU rDNA is known to be quite conservative, our analyses show clearly that this gene is able to distinguish different species of Epistominella. Therefore the lack of divergence between populations of E. exigua is not an artifact caused by slow evolutionary rates. Although the samples from distant localities are not yet available for the shallow water Epistominella species, we predict that their diversity will be much higher than in E. exigua .

The genetic homogeneity of E. exigua in the SSU and especially in the ITS supports morphological evidence for a global distribution of some small (meiofauna-sized), abyssal foraminifera and clearly contrasts with the high genetic diversification usually observed in shallow-water benthic species (Pawlowski and Holzmann 2008, Pawlowski et al. 2008). We therefore advance the hypothesis that global genetic homogeneity is more common in the abyssal deep sea than in shallow water. This could be explained by differences in dispersal opportunities and/or in biodiversification mechanisms.

Compared to shallow-water habitats where strong environmental gradients and seafloor topography create ecological barriers, the deep-sea floor provides a more uniform environment with a greater potential for global gene flow, particularly across abyssal plains. Epistominella exigua is a predominantly abyssal species (Murray, 1991). It has an opportunistic life style, exploits ephemeral patches of phytodetritus derived from surface production (Gooday, 1988, 1993), and tends to be abundant where primary production is strongly seasonal (Sun et al., 2006). Thus, metapopulations of E. exigua could comprise spatially separated, relatively dense, temporally fluctuating populations of different sizes, living wherever a suitable habitat exists, and with some degree of gene flow occurring 149 between them. Epistominella exigua also occurs over a much wider range of organic flux rates (spanning three orders of magnitude) than other deep-sea foraminifera (Altenbach et al., 1999). Dispersal and gene flow therefore may be mediated by the sparse populations living in more oligotrophic regions (Gooday, 1996) where phytodetrital deposits are likely to be confined to occasional small patches, as well as by the ability of foraminifera to survive long periods of starvation.

The small size of foraminifera such as E. exigua (typically 100-200 m) may also help to ensure their wide dispersal. Because body size is inversely correlated to population size, microbial eukaryotes and small metazoans (< 1 mm) occur in sufficient numbers to ensure ubiquitous distributions (Finlay et al., 2002). Many other deep-sea benthic foraminifera, particularly those living at abyssal depths, have very wide distributions (Murray, 1991; Pawlowski and Holzmann, 2008) and may be dispersed globally. A similar conclusion has been suggested in the case of hydrothermal vent flagellates (Atkins et al., 2000) and small eukaryotes from the water column (Slapeta et al., 2006). Although many marine species (benthic or planktonic) may be dispersed worldwide it seems nevertheless that deep-sea species are more likely to be cosmopolitan.

A greater prevalence of global genetic homogeneity in the deep sea than in shallow waters could also result from different speciation mechanisms. Abyssal species may evolve more slowly than shallow-water species. The high intra-individual divergence and the important single nucleotide polymorphism (SNP) of E. exigua suggest that it has preserved old mutations. Indeed, big metapopulations will be more likely to conserve selectively neutral genetic polymorphisms because they present higher initial diversity. One could ask whether the ITS rDNA homogeneity accurately reflects evolutionary rates. We cannot totally discount the possibility that the ITS of E. exigua has an atypically slow substitution rate, but we consider this unlikely and expect that the analysis of other parts of the genome will confirm its genetic homogeneity.

Our evidence for the ubiquity of E. exigua could be interpreted as an argument that global benthic diversity in the deep ocean has been overestimated (Lambshead and Boucher, 2003). However, E. exigua most likely constitutes an exceptional case. The other two deep- sea species, Cibicides wuellerstorfi and Oridorsalis umbonatus , included in our preceding study (Pawlowski et al. 2007) have not been found during the sampling off Japan and seem to 150 be absent or rare in Pacific Ocean. A very large database on the distribution of modern deep- sea benthic foraminifera lists a relatively limited number of ubiquitous deep-sea morphospecies (Murray 2006). Therefore, it is possible that globally-dispersed species do not constitute the majority of those living at the abyssal depths, even if they are more common here than in shallow water.

Acknowledgements

We thank Junichiro Ashi, Minoru Ikehara and captain and crew of R/V Hakuho-Maru KH06- 03; and Angelika Brandt, Brigitte Hilbig, Ingo Schewe, Eberhard Fahrbach and captains and crew of R/V Polarstern for help in collecting foraminifera; José Fahrni, Jackie Guiard, Estella Poloni and Frederic Sinniger for technical assistance and help with analyses. The work was supported by the Swiss National Science Foundation (3100A0-112645) and the U.K. Natural Environment Research Council (NER/B/S/2001/00336).

151 152 Chapter 5 General discussion, conclusions and perspectives

5.1 General discussion

This work provides several new insights into the richness and the distribution of foraminiferal species that will be discussed here.

5.1.1 Benthic foraminiferal richness

Massive sequencing experience presented in the second chapter points out to our lack of knowledge on foraminiferal richness. This preliminary study shows a considerable number of different new phylotypes detected in each sample. Whether those phylotypes reflect populations, species, genera or even families of foraminifera remains disputable. However, our analyses have been particularly restrictive concerning the grouping steps and the number of phylotypes is likely to have been underestimated. This would indicate that the foraminiferal local richness is higher that previously thought and several phylotypes identified by massive sequencing approach are effectively new to science.

The results of massive sequencing approach, however, should be interpreted extremely cautiously because of the problematic issue of extracellular DNA. As shown by our very first results of 454 analyses about 30% of sequences obtained from deep sediment samples originated from surface dwelling organisms. In the case of benthic foraminifera, the numerous sequences can potentially originate from dead specimens, which were living in situ a certain time ago or, which were brought (for instance by currents or by turbidity) from a distant locality. It would be possible to overcome this problem by analysing larger fragment of rDNA (less likely to be conserved long after organisms death) or by studying the rRNA, which is known to be rapidly degraded and more accurately reflect the assemblage of metabolically active specimens. The advantage of using benthic foraminifera compared to other eukaryotes 153 is that they are usually not present in the column water, and therefore the environmental diversity survey gives better view on their local richness, even if it includes a certain proportion of species that were not alive at the moment of sampling.

Massive sequencing does not only reveal that the number of foraminiferal species is unknown and still hard to estimated, but also highlights an often overlooked issue: the intraspecific and intraindividual variability. Some species, such as S. lindsayi or R. filosa , seems to have homogenous copies of SSU rDNA. On the contrary, the calcareous polythalamous taxa, such as E. exigua and O. umbonatus , present high intraspecimen polymorphism. This might indicate different diversification processes as we will propose in the next section (5.1.2).

Considering results of massive sequencing, it becomes clear that the level of genetic variations within lower taxonomic categories (species and genera) may differ between higher taxonomic groups. This situation could be considered in two different ways. The first one would be to recognize that the current taxonomy is not correct (admitting that the SSU rDNA would accurately reflect the evolutionary history of taxa) and therefore to propose a rearrangement of the species classification with the purpose of homogenizing their respective variability based on genetic data. Yet, as presented in the general introduction, the species concept is not applicable in the same way to each taxonomic group and therefore the option of rewriting the foraminiferal taxonomy using equal genetic distinction for all taxa should be given up. The second possibility would be to accept different criteria of distinction for different taxonomic groups. A criterion should remain constant within the same group. For instance, the threshold value used as genetic boundary between species should be the same for all the species included in a given genus; that used as a genetic boundary between genera should be the same for all the genera included in a given family; and so on. We recommend that congruent maximum genetic divergence be established for each taxon before interpreting massive sequencing results. For that reason, it is urgent that the sequence data for as many described morphospecies as possible become available.

It is interesting to notice that, among phylotypes obtained by SOLEXA analyses, numerous undetermined monothalamous clades appeared. This could indicate that this group of early single-chambered foraminifera forms a great proportion of the “hidden” richness. Some of them may have escaped the traditional microscopic observations because of their 154 small size or inconspicuous shape. The two agglutinated species presented in the first chapter show very well the wide range of morphologies, which can be found within monothalamous foraminifera. C. patelliformis and S. lindsayi are extremely different by their size (the first one is 160 times smaller in length than the second), by their test morphology and by their cytology (C. patelliformis has a single or few nuclei, whereas S. lindsayi have millions of them). Actually, the only morphological feature indubitably shared by both species is their agglutinated test. They probably also possess granuloreticulopodia but this could not have been observed as it is often the case for deep-sea foraminifera. Monothalamous clades can thus present high level of distinctness in their morphology, which is related to their long evolutionary history. This is also reflected by higher genetic divergence between monothalamous lineages compared to evolutionary younger groups such as rotaliids and textulariids. We speculate that this long history and high genetic divergence would result in increased diversity of monothalamous taxa, which are forming today the greatest part of the global foraminiferal richness.

5.1.2 On the trail of biodiversification processes

In this section, we will discuss the general patterns of foraminiferal diversity based on the previous discussion. We will speculate here on the general biodiversification processes, which could explain those patterns.

The global genetic homogeneity of E. exigua shown in chapter 4 has considerable consequences on our interpretation of foraminiferal species distribution. By providing evidence for lack of genetic differences between widely distributed populations of this species, we show that benthic foraminifera have the potential ability to disperse globally.

First of all, the role of microhabitat segregations at sediment-water interface could be put forward to explain differences between calcareous species concerning their geographic distribution. E. exigua and C. wullerstorfi are known to have epifaunal life habits and both display rather less biogeographic pattern in their gene structures than O. umbonatus , which is infaunal. It can thus be proposed that juveniles or gametes of epifaunal species may be dispersed in an easier way than infaunal ones, which reproduce in sediment interstices far from currents.

155 The depth parameter seems to be somehow involved in the separation between species displaying clear biogeography patterns and the others (if E. exigua is not a genuine case). This idea is supported by the important crypticity in shallow water species of Epistominella . Indeed, five cryptic species ( E. arctica , E. vitrea , Epistominella sp.1, Epistominella sp.2, Epistominella sp.3) have been found shallower than 1200 m, while apparently only one ( E. exigua ) occurs deeper. We suspect that the crypticity and the richness of others calcareous species would also tend to decrease with depth. However, we do not exclude the possibility that other species of the genus Epistominella could occur in the deep- sea neither that some of them could present limited geographic distribution. We propose that this feature of ubiquity increasing with depth would be rather a tendency than a common trend or general law. Moreover, we do not believe that the depth could act as a physical constraint restricting the dispersal and we even doubt that it could be directly correlated with species richness. We rather suspect that the dispersal and crypticity patterns would be linked to other parameters such nutrient concentration, which often depend on depth.

If we consider, once again, the different trophic strategies between species of benthic foraminifera, we could schematically distinguish the highly specialized taxa from the opportunist ones. As we proposed in the introduction, monothalamous species present many specialized traits in their highly adapted morphologies. They are also the most ancient group of foraminifera and probably the richest one in the deep-sea environment. In contrast, the polythalamous calcareous rotaliids include typical opportunist species, such as E. exigua , which are able to bloom rapidly where nutrients become abundant. The rotaliids are much younger in the evolutionary history of benthic foraminifera. They also display less genetic diversity than that found within monothalamous species, at least considering our database of the SSU rDNA sequences. All these observations converge to the following evolutionary scenario:

Hypothetically, deep-sea monothalamous foraminifera would have diversified by adaptation to different environments as well as by niches partitioning at the same location. The deep sea offer many oligotrophic places of relative stability, where a niche partitioning is especially likely to occur. Monothalamids specialization might have been enhanced by the facility to acquire or to lose an agglutinated test, occurring independently in different lineages. Indeed the extremely wide range of morphologies found in this group, offers numerous

156 possibilities of adaptation to a great variety of ecological niches. This remark would be even more relevant for those agglutinated monothalamids, which selectively pick up different particles from local environment and enhance in this way their diversification potential. It is thus plausible that a strong positive selection occurred in deep-sea monothalamous foraminifera regarding the features of their test that could explain the high evolution rates and the high richness of this group.

In the case of deep-sea rotaliids, a hypothesis would be that some of them, like E. exigua , changed their trophic strategy toward opportunism. In the deep sea, the opportunist taxa with generalist trophic behaviour should logically be favoured. Indeed, large food inputs are ephemeral and often unpredictable. It should therefore be convenient for a species to be able to feed on a wide range of resources and take benefit from a maximum of food opportunities. The generalist behaviour could also diminish the impact of food niche partitioning as diversification factor. Hotspots of resources in the deep-sea are thought to last not long enough for local populations to reach a steady state and start to compete between each others. Without competition, niches partitioning seems quite unlikely. This could provide explanation of the relatively slow diversification of opportunist taxa. Nevertheless, evolution rates highly depend on species dispersal and the geographic distribution should be taken into account.

We believe that deep-sea benthic foraminifera have globally considerable physiological ability for dispersal. For instance, most of them are small enough to be carried by currents on long distances. There are also evidences that they can construct cysts and adopt a dormant state (Heinz et al., 2005), which could potentially allow them to survive during long transportation despite food deprivation and changing physico-chemical conditions. The causes of their geographic occurrence at regional scale should thus be searched according to their ecological “interest” rather than to their ability to disperse. The point is probably not to know whether they could reach a given area but rather to predict whether that area is sufficiently attractive for them to settle there. Considering the opportunist trophic strategy, we could expect that deep-sea multi-chambered calcareous species, such as E. exigua , would have considerable interest to be widely dispersed, since they need to follow the resources hotspots where they appear. The patchier these hotspots are, the more widely dispersed opportunist species should be. Yet, the patchiness of resources is supposed to increase with

157 the oligotrophic character of environment and thus with the depth. For that reason, it would not be surprising that the dispersal potential of opportunist taxa would increase with depth. The distribution of Epistominella species, which seems to get wider with depth, would thus reflect a way to cope with an increasing patchiness of food resource. A wide dispersal should increase the gene flow and contribute to reduce diversification rates.

Additionally, it could be proposed that the diversification of opportunist species by food niches partitioning would also affect their distribution. Differences between resource types are obviously greater in shallow water than in the deep sea. Most of the food available for opportunist deep-sea foraminifera consists in decomposed organic matter (such as phytodetritus) coming from upper layers. In the deep sea, it is likely that this kind of resource would differ globally with depth rather than with geographic location inducing a vertical speciation rather than a horizontal one. Opportunist species living sufficiently deep should generally face similar type of nutrients and would have therefore fewer possibilities to speciate by “food partitioning”. This could possibly contribute to increase their geographic ubiquity with depth.

The gene flow of E. exigua prevails on its diversification rate but its populations display a relatively high variability, as indicated by multiple single point mutations present in their SSU and ITS rDNA. This could reflect a fast evolution of the ribosomal genes in this species. However, we may also think that this is related to the fact that the wide dispersion and the global gene flow of E. exigua are actually recent. A hypothesis would be that this species has improved its dispersal potential and shifted toward a more opportunistic trophic strategy. Genetically distinct populations of E. exigua would thus have been propagated quite recently and mixed between each others. The high genetic variability would thus be the trail of a previous biogeographic isolation.

The cosmopolitanism of E. exigua remains remarkable even if it would constitute an exception. We suspect, however, that other deep sea benthic species could also display a global genetic distribution although they should not be numerous since opportunistic way of life does not promote biodiversification. The number of ubiquitous foraminiferal species could be thought, at first glance, to be somehow correlated with the total amount of available providential nutrient such as phytodetritus. Indeed, even without a strong niche partitioning by food, opportunist species sharing the global resources should slowly separate until their 158 populations become small and follow stochastic model where there is equilibrium between species (see section 1.1.2). At evolutionary scale, a higher amount of global resources should thus result in a higher richness of ubiquitous species. In a certain way, diversification processes in opportunist taxa, such as E. exigua , could be compared to those described by Pedros-Alio for microorganisms (see Fig. 1.2.2). As microbes, they tend to be globally dispersed and could also be separated into dominant and rare species respectively. At a certain time and locality, the dominant opportunist species would be flourishing on providential hotspots, while rare opportunist species would “wait” the environmental change, which would favor them and allow their population to increase. It is for instance possible that E. exigua was some time ago a rare species, which became once and is until now successful. As for microbes, opportunist species should not get easily extinct since they can supposedly feed on a wide range of food and should have high dispersal ability: at least few representatives of a rare species should find enough food to survive. For all these reasons, we expect relatively few deep-sea benthic foraminifera with a current global distribution but a high number of species, which could potentially become ubiquitous. The richness of those opportunist taxa should be increasing with time.

Finally, foraminifera would encompass two different kinds of deep-sea “specialists". The first one would comprise mostly monothalamous taxa, highly adapted to oligotrophic local environments. They would be older, diversify relatively fast thanks primarly to their wide range of tests and should consist in the main part of foraminiferal richness. The second kind would include the opportunist and generalist taxa, especially adapted to the patchiness of deep-sea food resources. Some of the dominant species may have a global dispersal, while the other rare ones wait for better times. This kind of “opportunist deep-sea specialists” would slowly diversify thanks to a trophic strategy preventing them from extinction. This foraminiferal model could possibly fit to other eukaryotes including big metazoans. Indeed, these two schematic biodiversification pathways could evoke the differences existing between other deep-sea ecosystems. For instance, pelagic organism highly adapted to oligotrophy versus hydrothermal vents fauna coping with patchy and abundant resources of short availability.

159 160 5.2 Conclusions

Despite the fact that the deep-sea foraminifera have been extensively studied, there are still a lot of open questions concerning their diversity and evolution. Some of these questions have been targeted here using molecular tools. Although some data are still largely preliminary, there are two main conclusions that result from this work.

Firstly, the already great richness of benthic foraminifera seems to have been largely underestimated, especially as far as the monothalamous taxa are concerned. These single- chambered species present an impressive range of morphologies encompassing widely different sizes, test shapes and wall compositions. Their importance in the deep-sea ecosystems as a major component of the meiofauna was already known. However, as shown in our study, they would also be involved in other ecological functions by modifying sediment chemistry (like xenophyophores) or maintaining the microbial diversity (like komokiaceans). Most of the monothalamous lineages have probably diversified during early stages of foraminiferal history and seem particularly well adapted to their environment. As suggested by high divergence of their ribosomal genes, they seem to evolve relatively fast compared to other groups. We predict that they constitute the greatest part of the foraminiferal richness, which still remains to be uncovered.

Secondly, this work shows that some calcareous common morphospecies present a broad geographic range in the deep sea and at least one of them ( E. exigua ) could be truly ubiquitous. This lack of apparent barriers for the gene flow might be a common trend of deep- sea calcareous species with an opportunist feeding strategy. Their high dispersal ability linked to this strategy is probably a way to cope with the patchiness and the transience of food resources. Those species would slowly diversify regarding the food type (especially its decomposition state) rather than the environment. Their cosmopolitan character should thus intensify with the depth, since resources tend to get more patchy, ephemeral and similar further from the surface.

161 Our general conclusion is that benthic foraminifera represent an ideal model to investigate deep-sea diversification processes because of their great diversity and variety of evolutionary pathways. Moreover, they represent particularly good candidates to study the diversity of deep-sea benthic meiofauna by the newly developed massive sequencing technologies. We are convinced that this remarkable phylum still reserves a lot of surprises, which will be progressively uncovered by further molecular studies.

162 5.3 Perspectives

There is a considerable work left to be done concerning deep-sea benthic foraminifera. Many issues remain unsolved and new molecular methods have just opened a door on a tremendous world never seen before.

It is really important that our knowledge on “early foraminifera” improves in the near future. Each new description of monothalamous species adds an important piece of information regarding this largely overlooked group, which is, however, the core richness of the entire phylum. This kind of investigations should include molecular data for a much larger set of species, which is the only possible way to establish a solid phylogenetic classification of this group.

We wish to expand physico-chemical analyses on xenophyophores. We propose notably to further investigate radioactive elements contained in their stercomata and their possible origins. Additionally, it could be worthwhile to get the RNA of some specimens and obtain sequences of functional genes. This might give us some clues to understand biological functions linked to the particular feature of fecal pellets sequestration, which drastically modify the concentrations of metallic compounds within the deep-sea sediment.

We should acknowledge that it was particularly frustrating failing to establish komokiaceans origin by molecular tools. This project should be continued by collecting fresh specimens, and enlarged to other described species of Komokiacea.

Concerning the chapter on “hidden” foraminiferal richness (including numerous cosmopolite unidentified taxa and squatters) we should design specific fluorescent probes and apply them to sediment samples to reveal targeted undescribed species.

The applications of massive sequencing methods are countless. Our preliminary analyses probably still retain a lot of information we are not able to unscramble yet. For that reason and because the costs of analyses are not so high (at least in the case of Solexa), we should multiply basic tests to settle properly those new methods. However, it will be hard to

163 wait for starting a new project and screening the deep-sea sediment on a large scale. We believe that massive sequencing could be a way to circumnavigate the problematic issue of deep-sea sampling and its lack of representativeness. It is now possible to perform far more replicates, which should increase the accuracy of any environmental analysis.

Among numerous analyses, which could be performed using massive sequencing approach, three in particular, have retained our attention: 1) testing possible correlations between foraminiferal richness and some environmental parameters such as depth, latitude and the species richness of other meiofaunal group (for instance nematodes); 2) testing the ubiquity or wide dispersal of target species; and finally 3) monitoring foraminiferal populations in a reduced area over time by massive sequencing of DNA and RNA extracts.

Last but not least, the extracellular DNA obviously amplified during our 454 project should be investigated. It might be possible to estimate its concentration by real time PCR and determine its profile in the sediment.

164 REFERENCES

Abdullah, F., Sina, I., and Fauzee, F. (2008). The ground beetle fauna (Coleoptera: Carabidae) of Kenyir water catchment, Terengganu, Peninsular Malaysia. Pak J Biol Sci 11 , 2478-2483. Abele, L.G., and Walters, K. (1979). Marine benthic diversity: a critique and alternative explanation. Journal of Biogeography 6, 115-126. Adam, G., Marsh, A.G., Mullineaux, L.S., Young, G.M., and Manahan, D.T. (2001). Larval dispersal potential of the tubeworm Riftiapachyptila at deep-sea hydrothermal vents. Nature 411 , 77-80. Adl, S.M., Simpson, A.G.B., Farmer, M.A., Andersen, R.A., Anderson, O.R., Barta, J.R., Bowser, S.S., Brugerolle, G., Fensome, R.A., and Fredericq, S.(2005). The new higher level classification of eukaryotes with emphasis on the taxonomy of protists. J Eukaryot Microbiol 52 , 399-451. Alldredge, A.L., and Silver, M.J. (1988). Characteristics, dynamics and significance of marine snow. Progress in Oceanography 20 , 41-82. Allen, J.A. and Sanders, H.L. (1996). The zoogeography, diversity and origin of deep-sea protobranch bivalves of the Atlantic: the epilogue. Progress in Oceanography 38 , 95- 153. Altenbach, A.V., Pflaumann, U., Schiebel, R., Thies, A., Timm, S., and Trauth, M. (1999). Scaling percentages and distributional patterns of benthic foraminifera with flux rates of organic carbon. J ournal of Foraminiferal Research 29 , 173-185. Altschul, S.F., Gish, W., Miller, W., Myers, E.W., and Lipman, D.J. (1990). Basic local alignment search tool. J Mol Biol 215, 403-410. Alve, E. (1995). Benthic foraminiferal responses to estuarine pollution: a review. Journal of Foraminiferal Research 25 , 190-203. Alve, E. (1999). Colonization of new habitats by benthic foraminifera: a review. Earth-Sci Rev 46 , 167-185. Alve, E., and Goldstein, S.T. (2002). Resting stage in benthic foraminiferal propagules: a key feature for dispersal? Evidence from two shallow water species. Journal of Micropalaeontology 21 , 95-96. Alve, E., and Goldstein, S.T. (2003). Propagule transport as a key method of dispersal in benthic Foraminifera (Protista). Limnology and Oceanography 48 , 2163-2170. Anderson, T.R., and Rice, T. (2006). Deserts on the sea floor: Edward Forbes and his azoic hypothesis for a lifeless deep ocean. Endeavour 30 , 131-137. Andersson, J.O. (2009). Horizontal gene transfer between microbial eukaryotes. Methods Mol Biol 532 , 473-487. Armynot du Châtelet, E., Debenay, J.P., and Soulard, R. (2004). Foraminiferal proxies for pollution monitoring in moderately polluted harbours. Environmental Pollution 127 , 27-40. Arzola, R.G., Wynn, R.B., Lastras, G., Masson, D.G., and Weaver, P.P.E. (2008). Sedimentary features and processes in the Nazaré and Setúbal submarine canyons, west Iberian margin. Marine Geology 250 , 64-88. 165 Atkins, M.S., Teske, A.P., and Anderson, D.R. (2000) A survey of flagellate diversity at four deep-sea hydrothermal vents in Eastern Pacific ocean using structural and molecular approaches. J. Eukaryot. Microbiol . 47 , 400-411. Aurahs, R., Grimm, G.W., Hemleben, V., Hemleben, C., and Kucera, M. (2009). Geographical distribution of cryptic genetic types in the planktonic foraminifer Globigerinoides ruber. Mol Ecol 18 , 1692-1706. Bahls, A.S., Rathburn, A.E., and Perez, M.E. (2004). Responses of deep-sea benthic foraminifera to seasonal fluctuations in productivity of the Southern California margin. Paper presented at: Geological Society of America North-Central Section - 38th Annual Meeting (St. Louis, Missouri, USA ) . Bano, N., Ruffin, S., Ransom, B., and Hollibaugh, J.T. (2004) Phylogenetic composition of Arctic Ocean Archaeal assemblages and comparison with Antarctic assemblages. Applied Environmental Microbiology 70 , 781-789. Banner, F.T. (1971). A new genus of Planorbulinidae an endoparasite of another foraminifer. Revista Española de Micropaleontología 3, 113-128. Barth, D., Krener. S., Fokin, S.I., and Berendonk, T.U. (2006) Intraspecific genetic variation in Paramecium revealed by mitochondrial cytochrome c oxidase I sequences. J. Eukaryot. Microbiol. 53 ,20-25. Bergquist, D.C., Williams, F.M., and Fisher, C.R. (2000). Longevity record for deep-sea invertebrate. Nature 403 , 499-500. Bergsten, H. (1994). Recent benthic foraminifera of a transect from the North Pole to the Yermak Plateau, estern central Arctic Ocean. Marine Geology 119 , 251-267. Bertram, M.A., and Cowen, J.P. (1999). Temporal variations in the deep-water colonization rates of small benthic foraminifera: the results of an experiment on Cross Seamount. Deep-Sea Research I 46 , 1021-1049. Billett, D.S., and Hansen, B. (1982). Abyssal aggregations of Kolga hyalina Danielssen and Koren (Echinodermata: Holothuroidea) in the northeast Atlantic Ocean. Deep-Sea Research 29A , 799-818. Billett, D.S.M., Lampitt, R.S., Rice, A.L., and Mantoura, R.F.C. (1983). Seasonal sedimentation of phytoplankton to the deep-sea benthos. Nature 302 , 520-522. Bilofsky, H.S., Burks, C., Fickett, J.W., Goad, W.B., Lewitter, F.I., Rindone, W.P., Swindell, C.D., and Tung, C.S. (1986) The GenBank genetic sequence databank. Nucleic Acids Res 14 ,1-4. Boltovskoy, E., and Wright, R. (1976). Recent Foraminifera (The Hague, W. Junk). Boucher, G., and Lambshead, P.J.D. (1995). Ecological biodiversity of marine nematodes in samples from temperate, tropical, and deep-sea regions. Conserv Biol 9, 1594-1604. Bowser, S.S., Habura, A., Pawlowski, J. (2006). Molecular Evolution of Foraminifera. Genomics and Evolution of Microbial Eukaryotes. Katz, L. and Bhattacharya, D. (Eds) Oxford University Press, 78-93. Brandt, A., Gooday, A.J., Brandao, S.N., Brix, S., Brokeland, W., Cedhagen, T., Choudhury, M., Cornelius, N., Danis, B., De Mesel, I., et al. (2007). First insights into the biodiversity and biogeography of the Southern Ocean deep sea. Nature 447 , 307-311. Brinckmeyer, R., Knittel, K., Jürgens, J., Weyland, H., Amann, R., and Helmke, E. (2003) Diversity and structure of bacterial communities in Arctic versus Antarctic pack ice. Applied Environmental Microbiology 69 , 6610-6619. Broadman, R.S., Cheetham, A.H., and Rowell, A.J. (1987). Fossil Invertebrates (Cambridge, MA, Blackwell Science).

166 Buckley, D.E., Owens, E.H., Schafer, C.T., Vilks, G., Cranston, R.E., Rashid, M.A., Wagner, F.J.E., and Walker, D.A. (1974). Canso strait and Chedaucto bay: a multidisciplinary study of the impact of man on the marine environment. Geological Survey of Canada 1, 133-160. Bunker, D.E., and Naeem, S. (2006). Species diversity and ecosystem functioning. Science 312 , 846-848; author reply 846-848. Butman, C.A. (1987). Larval settlement of soft-sediment invertebrates: the spatial scales of pattern explained by active habitat selection and the emerging role of hydrodynamical processes. Oceanography and Marine Biology - an Annual Review 25 , 113-165. Canals, M., Puig, P., de Madron, X.D., Heussner, S., Palanques, A., and Fabres, J. (2006). Flushing submarine canyons. Nature 444 , 354-357. Caralp, M. (1989). Relationship to the quality of marine organic matter. Geo-Marine Letters 9, 37-43. Cartwright, N.G., Gooday, A.J., and Jones, A.R. 1989. The morphology, internal organization and taxonomic position of Rhizammina algaeformis Brady, a large, agglutinated, deep-sea foraminifer. Journal of Foraminiferal Research 19 : 115-125. Cavalier-Smith, T. (2002). The phagotrophic origin of eukaryotes and phylogenetic classification of Protozoa. Int J Syst Evol Microbiol 52 :297-354. Cedhagen, T. (1994). Taxonomy and Biology of Hyrrokkin-Sarcophaga Gen Et Sp-N, a Parasitic Foramiferan (Rosalinidae). Sarsia 79 , 65-82. Cedhagen, T., Gooday, A.J., and Pawlowski, J. (2009). A new genus and two new species of saccamminid foraminiferans (Protista, Rhizaria) from the deep Southern Ocean. Zootaxa 2096 , 9-22. Cedhagen, T., and Pawlowski, J. (2002). Toxisarcon synsuicidica n. gen., N. sp., a large monothalamous foraminiferan from the west coast of Sweden. Journal of Foraminiferal Research 32 , 351-357. Chen, L., DeVries, A.L., and Cheng, C.H. (1997). Convergent evolution of antifreeze glycoproteins in Antarctic notothenioid fish and Arctic cod. Proc Natl Acad Sci U S A 94 , 3817-3822. Chen, Y.C., Eisner, J.D., Kattar, M.M., Rassoulian-Barrett, S.L., Lafe, K., Bui, U., Limaye, A.P., and Cookson, B.T. (2001). Polymorphic internal transcribed spacer region 1 DNA sequences identify medically important yeasts. J Clin Microbiol 39 , 4042-4051. Childress, J.J., and Fischer, C.R. (1992). The biology of hydrothermal vent animals: physiology, biochemistry and autotrophic symbioses. Oceanography and Marine Biology - an Annual Review 30 , 337-441. Clement, M., Posada, D., and Crandall, K.A. (2000). TCS: a computer program to estimate gene genealogies. Mol. Ecol. 9, 1657-1659. Cole, J.J., Honjo, S., and Erez, J. (1987). Benthic decomposition of organic matter at deep- water site in the Panama Basin. Nature 327 , 703-704. Corliss, B.H., and Chen, C. (1988). Morphotype patterns of Norwegian Sea deep-sea benthic foraminifera and ecological implications. Geology 16 , 716-719. Corliss, J.B., Dymond, J., Gordon, L.I., Edmond, J.M., von Herzen, R.P., Ballard, R.D., Green, K., Williams, D., Bainbridge, and A., Crane, K. (1979). Submarine Thermal Sprirngs on the Galapagos Rift. Science 203 , 1073-1083. Cox, K.D., Scherm, H., and Riley, M.B. (2006). Characterization of Armillaria spp. from peach orchards in the southeastern United States using fatty acid methyl ester profiling. Mycol Res 110 , 414-422. Cronin, T.M., and Raymo, M.E. (1997). Orbital forcing of deep-sea benthic species diversity. Nature 385 , 624-627. 167 Crump, B.C., Armbrust, E.V., and Baross, J.A. (1999). Phylogenetic analysis of particle- attached and free-living bacterial communities in the Colubia river, its estuary, and the adjacent ocean. Appl Environ Microbiol 65 , 3192-3204. Culver, S.J. (1991). Early Cambrian Foraminifera from West Africa. Science 254 , 689-691. Curtis, T.P., Head, I.M., Lunn, M., Woodcock, S., Schloss, P.D., and Sloan, W.T. (2006). What is the extent of prokaryotic diversity? Philos Trans R Soc Lond B Biol Sci 361 , 2023-2037. Curtis, T.P., Sloan, W.T., and Scannell, J.W. (2002). Estimating prokaryotic diversity and its limits. Proc Natl Acad Sci U S A 99 , 10494-10499. Cushman, J.A. (1928). Foraminifera, their classification and economic use, 4 edn (Harvard University Press). d 'Orbigny, A. (1826). Tableau méthodique de la classe des Céphalopodes. 3 ème ordre Foraminifères. Ann Sci Nat, Paris (Zool) 7 , 245-374. Damare, S., Raghukumar, C., and Raghukumar, S. (2006). Spore germination of fungi belonging to Aspergillus species under deep-sea conditions. Deep Sea Research I 55 :670-678 Danovaro, R., Dell'Anno, A., Corinaldesi, C., Magagnini, M., Noble, R., Tamburini, C., and Weinbauer, M. (2008a). Major viral impact on the functioning of benthic deep-sea ecosystems. Nature 454 , 1084-1087. Danovaro, R., Gambi, C., Dell'Anno, A., Corinaldesi, C., Fraschetti, S., Vanreusel, A., Vincx, M., and Gooday, A.J. (2008b). Exponential decline of deep-sea ecosystem functioning linked to benthic biodiversity loss. Curr Biol 18 , 1-8. Danovaro, R., Gambi, C., Lampadariou, N., and Tselepides, A. (2008c). Deep-sea nematode biodiversity in the Mediterranean basin: testing for longitudinal, bathymetric and energetic gradients. Ecography 31 , 231-244. Darling, K.F., Kucera, M., Pudsey, C.J., and Wade, C.M. (2004). Molecular evidence links cryptic diversification in polar planktonic protists to Quaternary climate dynamics. Proc Natl Acad Sci U S A 101 , 7657-7662. Darling, K. F., and Wade, C. M. (2008). The genetic diversity of planktic foraminifera and the global distribution of ribosomal RNA genotypes. Marine Micropaleontology 67 , 216- 238. Darling, K.F., Wade, C.M., Kroon, D., Leigh Brown, A.J., and Bijma, J. (1999). The diversity and distribution of modern planktic foraminiferal small subunit ribosomal RNA genotypes and their potential as tracers of present and past ocean circulations. Paleoceanography 14 , 3-12. Darling, K.F., Wade, C.M., Stewart, I.A., Kroon, D., Dingle, R., and Leigh Brown, A.J. (2000). Molecular evidence for genetic mixing of Arctic and Antarctic subpolar populations of planktonic foraminifers. Nature 405 , 43-47. Darwin, C. (1859). On the origin of species by means of natural selection . In, Murray, ed. (London), p. 52. Darwin, F. (1887). The life and letters of Charles Darwin, including an autobiographical chapter , Vol 2, London: John Murray, Albemarle street ed. Darwin, F., and Seward, A.C. (1903). Charles Darwin, letter to W.B. Carpenter, 1872. In, F.a.A.C.S. Darwin , ed. (New York). Dawson, S.C., and Pace, N.R. (2002). Novel kingdom-level eukaryotic diversity in anoxic environments. Proc Natl Acad Sci U S A 99 , 8324-8329. De Laca, T.E., Bernhard, J.M., Reilly, A., and Bowser, S.S. (2002). Notodendrodes hyalinosphaira (sp. nov.): structure and autoecology of an allogromiid-like agglutinated foraminifer. Journal of Foraminiferal Research 32 , 177-187. 168 De Stigter, H.C., Boer, W., De Jesús Mendes, P.A., Jesus, C.C., Thomsen, L., Van den Berg, G.D., and Van Weering, T.C.E. (2007). Recent sediment transport and deposition in Nazaré Canyon, Portuguese continental margin. Marine Geology 246 , 144-164. de Vargas, C., Norris, R., Zaninetti, L., Gibb, S.W., and Pawlowski, J. (1999). Molecular evidence of cryptic speciation in planktonic foraminifers and their relation to oceanic provinces. Proc Natl Acad Sci U S A 96 (101), 2864-2868. de Vargas, C., and Pawlowski, J. (1998). Molecular versus taxonomic rates of evolution in planktonic foraminifera. Molecular Phylogenetics and Evolution 9, 463-469. de Vargas, C., Renaud, S., Hilbrecht, H., and Pawlowski, J. (2001). Pleistocene adaptive radiation in Globorotalia truncatulinoides: genetic, morphologic, and environmental evidence. Paleobiology 27 , 104-125. de Vargas, C., Zaninetti, L., Hilbrecht, H., and Pawlowski, J. (1997) Phylogeny and rates of molecular evolution of planktonic foraminifera: SSU rDNA sequences compared to the fossil record. Journal of Molecular Evolution 45 :285-294. Debenay, J.P., Guillou, J.J., Redois, F., and Geslin, E. (2000). Distribution trends of foraminiferal assemblages in paralic environments. A base for using foraminifera as bioindicators. In Enviromental Micropaleontology , E.R.a.M. Kluver, ed. (New York, Geobiology), pp. 39-67. Debenay, J.P., and Pawlowski, J. (1996). Les foraminifers actuels (Paris). DeLaca, T.E., Karl, D.M., and Lipps, J.H. (1981). Direct use of dissolved organic carbon by agglutinated benthic foraminifera. Nature 289 , 287-289. Dell'Anno, A., and Danovaro, R. (2005). Extracellular DNA plays a key role in deep-sea ecosystem functioning. Science 309 , 2179-2179. DeLong, E.F., Franks, D.G., and Alldredge, A.L. (1993). Phylogenetic diversity of aggregate- attached and free-living marine bacterial assemblages. Limnology and Oceanography 38 , 924-934. Deming, J.W., and Colwell, R.R. (1982). Barophilic bacteria associated with the digestive tract of abyssal holothurians. Appl Environ Microbiol 44 , 1222-1230. Deuser, W.G., and Ross, E.H. (1989). Seasonally abundant planktonic foraminifera of Sargasso Sea: Succession, deep-water fluxes, isotopic composition, and paleoceanographic implications. Journal of Foraminiferal Research 19 , 168-193. Deutsch, C., Sarmiento, J.L., Sigman, D.M., Gruber, N., and Dunne, J.P. (2007). Spatial coupling of nitrogen inputs and losses in the ocean. Nature 445 , 163-167. Diaz, S., and Cabido, M. (2001). Vive la différence: plant functional diversity matters to ecosystem processes. Trends Ecol Evol 16 , 646-655. Douglas, R.G. (1979). Foraminiferal Ecology and Paleoecology. In SEPM Short Course No 6 , W.H.B. J. H. Lipps, M. A. Buzas, R. G. Douglas, C. A. Ross, ed. (Society of Economic Paleontologists and Mineralogists), pp. 21-53. Douglas, R.G. (1981). Paleoecology of continental margin basins: a modern case history from the borderland of Southern California. In Depositional Systems of Active Continental Margin Basins , R.G.D.e. al., ed. (Bakersfield, California, Society of Economic Paleontologists and Mineralogists, Pacific Section), pp. 121-156. Douglas, R.H., Mullineaux, C.W., and Partridge, J.C. (2000). Long-wave sensitivity in deep- sea stomiid dragonfish with far-red bioluminescence: evidence for a dietary origin of the chlorophyll-derived retinal photosensitizer of Malacosteus niger. Philos Trans R Soc Lond B Biol Sci 355 , 1269-1272. Dugan, B., and Flemings, P.B. (2000). Overpressure and fluid flow in the new jersey continental slope: implications for slope failure and cold seeps. Science 289 , 288-291.

169 Ebeling, A.W., and Caillet, G.M. (1974). Mouth size and predator strategy of midwater fishes. Deep-Sea Research 21 , 959-968. Edgcomb, V.P., Kysela, D.T., Teske, A., de Vera Gomez, A., and Sogin, M.L. (2002). Benthic eukaryotic diversity in the Guaymas Basin hydrothermal vent environment. Proc Natl Acad Sci U S A 99 , 7658-7662. El Menyawi, I., Wogerbauer, M., Sigmund, H., Burgmann, H., and Graninger, W. (2000). Identification of yeast species by fatty acid profiling as measured by gas-liquid chromatography. J Chromatogr B Biomed Sci Appl 742 , 13-24. Elias, M., Hill, R.I., Willmott, K.R., Dasmahapatra, K.K., Brower, A.V., Mallet, J., and Jiggins, C.D. (2007). Limited performance of DNA barcoding in a diverse community of tropical butterflies. Proc Biol Sci 274 , 2881-2889. Ellison, R.L., Broome, R., and Oglivie, R. (1986). Foraminiferal response to trace metal contamination in the Patapsco river and Baltimore harbour, Maryland. Marine Pollution Bulletin 17 , 419-423. Epping, E., Van Der Zee, C., Soetaert, K., and Helder, W. (2002). On the oxidation and burial of organic carbon in sediments of the Iberian margin and Nazaré Canyon (NE Atlantic). Progress in Oceanography 52 : 399–431. Epstein, S., and López-García, P. (2008). Missing protists: a molecular prospective. Biodiversity and Conservation 17 , 261-276. Ereshefsky, M., and Matthen, M. (2005). Taxonomy, polymorphism, and history: An introduction to population structure theory. Philosophy of Science 72 , 1-21. Ertan, K.T., Hemleben, V., and Hemleben, C. (2004). Molecular evolution of some selected benthic foraminifera as inferred from sequences of the small subunit ribosomal DNA. Marine Micropaleontology 53 , 367-388. Erwin, P.M., and Thacker, R.W. (2008). Cryptic diversity of the symbiotic cyanobacterium Synechococcus spongiarum among sponge hosts. Mol Ecol 17 , 2937-2947. Etter, R.J., and Grassle, J.F. (1992). Patterns of species diversity in the deep sea as a function of sediment particle size diversity. Nature 369 , 576-578. Etter, R.J., Rex, M.A., Chase, M.C., and Quattro, J.M. (1999). A genetic dimension to deep- sea biodiversity. Deep-Sea Res. I 46 , 1095-1099. Etter, R.J., Rex, M.A., Chase, M.R., and Quattro, J.M. (2005). Population differentiation decreases with depth in deep-sea bivalves. Evolution 59 , 1479-1491. Evans, K.M., Wortley, A.H., and Mann, D.G. (2007). An assessment of potential diatom “barcode” genes (cox1, rbcL, 18S and ITS rDNA) and their effectiveness in determining relationships in Sellaphora (Bacillariophyta). Protist 158 ,349-364. Excoffier, L., Laval, G., and Schneider, S. (2005). Arlequin (version 3.0): An integrated software package for population genetics data analysis. Evol. Bioinformatics Online 1, 47-50. Excoffier, L., Smouse, P., and Quattro, J. (1992). Analysis of molecular variance inferred from metric distances among DNA haplotypes: Application to human mitochondrial DNA restriction data. Genetics 131 , 479-491. Finlay, B.J. (2002). Global Dispersal of Free-Living Microbial Eukaryote Species. Science 296 , 1061-1063. Finlay, B.J., Esteban, G.F., and Fenchel, T. (2004). Protist Diversity is different? Protist 155 , 15-22. Finlay, B.J., and Fenchel, T. (2004). Cosmopolitan metapopulations of free-living microbial eukaryotes. Protist 155 , 237-244. Flakowski, J., Bolivar, I., and Fahrni, J. (2005). Actin phylogeny of foraminifera. Journal of Foraminiferal Research 35 , 93-102. 170 Fontaneto, D., Kaya, M., Herniou, E.A., and Barraclough, T.G. (in Press). Extreme levels of hidden diversity in microscopic animals (Rotifera) revealed by DNA taxonomy. Mol Phylogenet Evol . Fontanier, C., Jorissen, F.J., Licari, L., Alexandre, A., Anschutz, P., and Garbonel, P. (2002). Live benthic foraminiferal faunas from the Bay of Biscay: faunal density, composition, and microhabitats. Deep-Sea Research I 49 , 751–785. Forbes, E. (1844). Report on the Mollusca and Radiata of the Aegean Sea, and on their distribution, considered as bearing on geology. In Report of the British Association for the Advancement of Science for 1843 , pp. 129-193. Fox, J.W. (2006). Using the Price Equation to partition the effects of biodiversity loss on ecosystem function. Ecology 87 , 2687-2696. Fraser, R.H., and Currie, D.J. (1996). The species richness-energy hypothesis in a system where historical factors are thought to prevail: coral reefs. American Naturalist 148 , 138-159. Frontalini, F., and Coccioni, R. (2008). Benthic foraminifera for heavy metal pollution monitoring: A case study from the central Adriatic Sea coast of Italy. Estuarine, Coastal and Shelf Science 76 , 404-417. Gage, J.D. (2004). Diversity in deep-sea benthic macrofauna: the importance of local ecology, the larger scale, history and the Antarctic. Deep-Sea Research II 51 , 1689–1708. Gage, J.D., and Tyler, P.A. (1991). Deep-sea biology: a natural history of organisms at the deep-sea floor (Cambridge, Cambridge University Press). Galtier, N., Gouy, M., and Gautier, C. (1996). SEAVIEW and PHYLO_WIN, two graphic tools for sequence alignment and molecular phylogeny. Comput. Applic. Biosci. 12 , 543-548. Garcia, R., Koho, K.A., De Stigter, H.C., Epping, E., Koning, E., and Thomsen, L. (2007). Distribution of meiobenthos in the Nazaré Canyon and adjacent slope (western Iberian Margin) in relation to sedimentary composition. Marine Ecology Progress Series 240 , 207–220. Garcia, R., and Thomsen, L. (2008). Bioavailable organic matter in surface sediments of the Nazaré canyon and adjacent slope (Western Iberian Margin). Journal of Marine Systems 74 : 44–59 Gardner, W.D., Hinga, K.R., and Marra, J. (1983). Observation on the degradation of biogenic material in the deep ocean with implications on accuracy of sediment trap fluxes. Journal of Marine Research 41 , 195-214. Gaston K. J., S.J.I. (2004). Biodiversity: an introduction , second edt. (Blackwell Publishing). Goldstein, S. (1999). In Modern Foraminifera , B.K. Sen Gupta, ed. (Dordrecht, Kluwer), pp. 37-55. Gonzalez-Oreja, J.A. (2008). The Encyclopedia of Life vs. the Brochure of Life: Exploring the relationships between the extinction of species and the inventory of life on Earth. Zootaxa 1965 , 61-68. Gooday, A.J. (1984a). Komokiacean foraminifers (Protozoa) and paludicelline ctenostomes (Bryozoa) from the abyssal northeast Atlantic. Journal of Natural History 18 , 765- 784. Gooday, A.J. (1984b). Records of deep-sea rhizopod tests inhabited by metazoans in the north east Atlantic. Sarsia 69 , 45-53. Gooday, A.J. (1988). A response by benthic foraminifera to phytodetritus deposition in the deep sea. Nature 332 , 70-73. Gooday, A.J. (1993). Deep-sea benthic foraminiferal species which exploit phytodetritus: characteristic features and controls on distribution. Mar. Micropaleontol. 22 , 187-205. 171 Gooday, A.J. (1995). Micro- and nanoforaminifera from abyssal northeast Atlantic sediments: a preliminary report. Int Rev Gesamten Hydrobiol 80 , 361-383. Gooday, A.J. (2002a). Biological responses to seasonally varying fluxes of organic matter to the ocean floor: A review. Journal of Oceanography 58 , 305-332. Gooday, A.J. (2002b). Organic-walled allogromiids: Aspects of their occurrence, diversity and ecology in marine habitats. Journal of Foraminiferal Research 32 , 384-399. Gooday, A.J. (2003). Benthic foraminifera (Protista) as tools in deep-water palaeoceanography: environmental influences on faunal characteristics. Adv Mar Biol 46 , 1-90. Gooday, A.J., Bernhard, J.M., Levin, L.A., and Suhr, S.B. (2000). Foraminifera in the Arabian Sea oxygen minimum zone and other oxygen-deficient settings: taxonomic composition, diversity, and relation to metazoan faunas. Deep-Sea Res Part II-Top Stud Oceanogr 47 , 25-54. Gooday, A.J., Bett, B.J., and Pratt, D.N. (1993). Direct Observation of Episodic Growth in an Abyssal Xenophyophore (Protista). Deep-Sea Research I-Oceanographic Research Papers 40 , 2131-2143. Gooday, A.J., and Cartwright, N. (1987). Rhizammina algaeformis: a giant komokiacean foraminifer?. Deep Sea Newsletter 13 , 13-15. Gooday, A.J., Cedhagen, T., Kamenskaya, O.E., and Cornelius, N. (2007b). The biodiversity and biogeography of komokiaceans and other enigmatic foraminifera-like protists in the deep Southern Ocean. Deep-Sea Res II 54 ,1691-1719. Gooday, A.J., Cook, P.L. (1984). An association between komokiacean foraminifera (Protozoa) and paludicelline ctenostomes (Bryozoa) from the abyssal northeast Atlantic. J Nat. Hist 18 :765–784. Gooday, A.J., Holzmann, M., Guiard, J., Cornelius, N., Pawlowski, J. (2004). A new monothalamous foraminifera from 100-6300 m water depth in the Weddell Sea: morphological and molecular characterization. Deep-Sea Res. II 51 , 1603-1616. Gooday, A.J., Hori, S., Todo, T., Okamoto, T., Kitazato, H., and Sabbatini, A. (2004). Soft- walled, monothalamous benthic foraminifera in the Pacific, Indian and Atlantic Oceans: aspects of biodiversity and biogeography. Deep-Sea Research I 51 , 33–53. Gooday, A.J., Kamenskaya, O.E., Cedhagen, T. (2007a). New and little-known Komokiacea (Foraminifera) from the bathyal and abyssal Weddell Sea and adjacent areas. Zool J Linnean Soc 151 ,219-251. Gooday, A.J., and Lambshead, P.J.D. (1989). Influence of Seasonally Deposited Phytodetritus on Benthic Foraminiferal Populations in the Bathyal Northeast Atlantic - the Species Response. Marine Ecology-Progress Series 58 , 53-67. Gooday, A.J., Levin, L.A., Linke, P., and Heeger, T. (1992). The role of benthic foraminifera in deep-sea food webs and carbon cycling. In Deep-Sea Food Chains and the Global Carbon , G.T. Rowe, and V. Pariente, eds. (Dorcrecht, Kluwer Academic Publishers), pp. 237-243. Gooday, A.J., Levin, L.A., Thomas, and C.L., Hecker, B. (1992). The taxonomy, distribution and ecology of Bathysiphon filiformis and B. major (Protista, Foraminiferida) on the continental slope off North Carolina. J Foraminiferal Res 22 ,129-146. Gooday, A.J., Nomaki, H., and Kitazato, H. (2008). Modern deep-sea benthic foraminifera: a brief review of their morphology-based biodiversity and trophic diversity. Geological Society London Special Publications 303 , 97-119. Gooday, A.J., and Pawlowski, J. (2004). Conqueria laevis gen. and sp. nov., a new soft- walled, monothalamous foraminifera genus from the deep Weddell Sea. Journal of the Marine Biological Association of the United Kingdom 84 , 919-924. 172 Gooday, A.J., and Tendal, O.S. (2000). Class Xenophyophorea Schulze 1904. In: Lee JJ, Leedale GF, Bradbury P, eds. The illustrated Guide to the Protozoa , 2 nd ed. Lawrence, Kansas: Allen Press, 1086-1097. Gooday, A.J., and Turley, C.M. (1990). Responses by benthic organisms to inputs of organic material to the ocean-floor - a review. Philos Trans R Soc Lond Ser A-Math Phys Eng Sci 331 , 119-138. Govenar, B., Freeman, M., Bergquist, D.C., Johnson, G.A., and Fisher, C.R. (2004). Composition of a one-year-old Riftia pachyptila community following a clearance experiment: insight to succession patterns at deep-sea hydrothermal vents. Biol Bull 207 , 177-182. Graham, M.H., Kinlan, B.P., Druehl, L.D., Garske, L.E., and Banks, S. (2007). Deep-water kelp refugia as potential hotspots of tropical marine diversity and productivity. Proc Natl Acad Sci U S A 104 , 16576-16580. Grassle, J.F. (1985). Hydrothermal Vent Animals: Distribution and Biology. Science 229 , 713 - 717. Grassle, J.F. (1991). Deep sea benthic diversity. Bioscience 41 , 464-469. Grassle, J.F., and Maciolek, N.J. (1992). Deep-sea species richness: regional and local diversity estimates from quantitative bottom samples. American Naturalist 139 , 313- 341. Grassle, J.F., and Morse-Porteous, L.S. (1987). Macrofauna colonization of disturbed deep- sea environments and the structure of deep-sea benthic communities. Deep-Sea Research 34 , 1911-1950. Gray, J.S. (2002). Species richness of marine soft sediments. Marine Ecology Progress Series 244 , 285-297. Grimm, G.W., Stögerer, K., Ertan, K.T., Kitazato, H., Kucera, M., Hemleben, and V., Hemleben, C. (2007). Diversity of rDNA in Chilostomella: Molecular differentiation patterns and putative hermit types. Marine Micropaleontology 62 , 75-90. Grinnell, J. (1917). The niche-relationships of the California Thrasher. Auk 34 , 427-433. Guindon, S. & Gascuel, O. (2003) A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood. Systematic Biology 52, 696-704. Habura, A., Goldstein, S.T., Broderick, S., and Bowser, S.S. (2008). A bush, not a tree: The extraordinary diversity of cold-water basal foraminiferans extends to warm-water environments. Limnol. Oceanogr. 53 (4), 1339–1351. Habura, A., Pawlowski, J., Hanes, S.D., and Bowser, S.S. (2004). Unexpected foraminiferal diversity revealed by small-subunit rDNA analysis of Antarctic sediment. J Eukaryot Microbiol 51 , 173-179. Habura, A., Rosen, D.R., and Bowser, S.S. (2004). Predicted secondary stricture of the foraminiferal SSU 3’ major domain reveals a molecular synapomorphy for granuloreticulosean protists. J. Eukaryot. Microbiol . 51 ,464-471. Haeckel, E. (1866). General Morphology of Organisms; General Outlines of the Science of Organic Forms based on Mechanical Principles through the Theory of Descent as reformed by Charles Darwin (Berlin). Haeckel, E., (1889). Report on the Deep-Sea Keratosa. Report on the Scientific Results of the Voyage of H. M. S. Challenger during the years 1873-76. Zoology 32 (82), 1-92. Hallock, P. (2000). Larger foraminifera as indicators of coral-reef vitality. Environmental Micropaleontology 15 , 121-150.

173 Hamasaki, K., and Taniguchi, A. (2009). Diversity of active microbial communities in the surface seawaters along a north-south transect in the South Pacific ocean. Paper presented at: International Census of Marine Microbes 454 Users Spring Meeting (Woods Hole, MA USA) . Haynes, J.R. (1992). Supposed pronounced ecophenotypy in foraminifera. Journal of Micropalaeontology 11 , 59-63. Hayward, B.W., Holzmann, M., Grenfell, H.R., Pawlowski, J., and Triggs, C.M. (2004). Morphological distinction of molecular types in Ammonia - towards a taxonomic revision of the world's most commonly misidentified foraminifera. Marine Micropaleontology 50 , 237-271. Hebert, P.D., Ratnasingham, S., and deWaard, J.R. (2003). Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species. Proc Biol Sci 270 (Suppl 1), 96-99. Heinz, P., Geslin, E., and Hemleben, C. (2005). Laboratory observations of benthic foraminiferal cysts. Marine Biology Research 1, 149-159. Heron-Allen, E., and Earland, A. (1912). On some Foraminifera from the North Sea, etc, dredged by the Fisheries cruiser ‘Goldseeker’ (International North Sea Investigations – Scotland). Journal of the Royal Microscopical Society 1912 , 382-389. Heron-Allen, E., and Earland, A. (1913). On some Foraminifera from the North Sea, etc, dredged by the Fisheries cruiser ‘Goldseeker’ (International North Sea Investigations – Scotland). II On the distribution of Saccammina sphaerica (M. Sars) and Psammosphaera fusca (Schultz) in the North Sea. Journal of the Royal Microscopical Society 1913 , 1-26. Hessler, R.R., and Jumars, P.A. (1974). Abyssal community analysis from replicate box cores in the central North Pacific. Deep Sea Res 21 ,185-209. Hollibaugh, J.T., Bano, N., and Ducklow, H.W. (2002). Widespread distribution in polar oceans of a 16S rRNA gene sequence with affinity to Nitrosospira-like ammonia- oxidizing bacteria. Applied Environmental Microbiology 68 , 1478-1484. Hollister, J.C., and McCave, I.N. (1984). Sedimentation under deep-sea storms. Nature 309 , 220-225. Holzmann, M. (2000). Species concept in foraminifera: Ammonia as a case study. Micropaleontology 46 , 21-37. Holzmann, M., and Pawlowski, J. (1996). Preservation of foraminifera for DNA extraction and PCR amplification. Journal of Foraminiferal Research 26 , 264-267. Holzmann, M., and Pawlowski, J. (1997). Molecular, morphological and ecological evidence for species recognition in Ammonia (Foraminifera). Journal of Foraminiferal Research 27 , 311-318. Holzmann, M., and Pawlowski, J. (2000). Taxonomic relationships in the genus Ammonia (Foraminifera) based on ribosomal DNA sequences. Journal of Micropaleontology 19 , 85-95. Holzmann, M., and Pawlowski, J. (2002). Freshwater foraminiferans from Lake geneva: past and present. Journal of Foraminiferal Research 32 , 344-350. Holzmann, M., Piller, W., and Pawlowski, J. (1996) Sequence variations in large-subunit ribosomal RNA gene of Ammonia (Foraminifera, Protozoa) and their evolutionary implications. Journal of Molecular Evolution 43 , 145-151. Hopkins, T.L., and Baird, R.C. (1973). Diet of the hatchetfish Sternoptyx diaphana. Marine Biology 21 , 34-46.

174 Hopwood, J.D., Mann, S., and Gooday, A.J. (1997). The crystallography and possible origin of barium sulphate in deep-sea rhizopod protists (Xenophyophorea). Journal of the Marine Biological Association of the United Kingdom 77 , 969-987. Huang, D., Meier, R., Todd, P.A., and Chou, L.M. (2008). Slow mitochondrial COI sequence evolution at the base of the metazoan tree and its implications for DNA barcoding. J Mol Evol 66 , 167-174. Hubbell, S.P. (2001). The unified neutral theory of biodiversity and biogeography (Princeton, Princeton University Press). Huber, J.A., Mark Welch, D.B., Morrison, H.G., Huse, S.M., Neal, P.R., Butterfield, D.A., and Sogin, M.L. (2007). Microbial population structures in the deep marine biosphere. Science 318 , 97-100. Huelsenbeck, J.P., and Ronquist, F. (2001). MRBAYES: Bayesian inference of phylogeny. Bioinformatics 17 ,754-755. Hughes, J.A., and Gooday, A.J. (2004). Associations between living benthic foraminifera and dead tests of Syringammina fragilissima (Xenophyophorea) in the Darwin Mounds region (NE Atlantic). Deep-Sea Research I 51 , 1741-1758. Hughes, J.A., Gooday, A.J., and Murray, J.W. (2000). Distribution of live benthic Foraminifera at three oceanographically dissimilar sites in the northeast Atlantic: preliminary results. Hydrobiologia 440 , 227-238. Hurtado, L.A., Lutz, R.A., and Vrijenhoek, R.C. (2004). Distinct patterns of genetic differentiation among annelids of eastern Pacific hydrothermal vents. Molecular Ecology 13 , 2603-2615. Huse, S.M., Dethlefsen, L., Huber, J.A., Welch, D.M., Relman, D.A., and Sogin, M.L. (2008). Exploring microbial diversity and taxonomy using SSU rRNA hypervariable tag sequencing. PLOS Genet 4, e1000255. Hutchinson, G.E (1957) Concluding remarks in Cold Spring Harbor Symposia on Quantitative Biology 22 (2), 415-427 Ittekkot, V., Deuser, W.G., and Degens, D.G. (1984). Seasonality in the flux sugars, amino acids and amino sugars to the deep ocean: Sargasso Sea. Deep-Sea Research 31A , 1057-1069. Ives, A.R., and Carpenter, S.R. (2007). Stability and diversity of ecosystems. Science 317 , 58- 62. Jobb, G., von Haeseler, A., and Strimmer, K. (2004). TREEFINDER: a powerful graphical analysis environment for molecular phylogenetics. BMC Evolutionary Biology 4, 18. Jones, R.W. (1994). The Challenger Foraminifera (New York, Oxford University Press Inc.). Jumars, P.A. (1976). Deep-sea species diversity: does it have a caracteristic scale? Journal of Marine Research 34 , 217-246. Jumars, P.A., and Eckman, J. (1983). Spatial structure within the deep-sea benthic communities , Vol 8 (New York, Wiley-Interscience). Jumars, P.A., and Gallagher, E.D. (1982). Deep-sea community structure: tree plays on the benthic proscenium. In: WG Ernst and JG Morin (eds). The Environment of the Deep Sea , Prentice-Hall Inc. Englewood Cliffs, N J, 217-255 Jumars, P.A., and Hessler, R.R. (1976). Hadal community structure: implications from the Aleutian Trench. Journal of Marine Research 34 , 547-560. Juniper, S.K., Sarrazin, J., and Grehan, A. (1998). Remote sensing of organism density and biomass at hydrothermal vents. In Proceedings of the first international symposium on deep-sea hydrothermal vent biology , R. Ed. de la station biologique, FRANCE (1960) (Revue), ed. (Funchal, Madeira, Portugal), 245-247.

175 Kaiho, K. (1994). Benthic foraminiferal dissolved-oxygen levels in the modern ocean. Geology 22 , 719-722. Kaiser, M. (2005). Marine ecology: Processes, systems and impacts (Oxford, Oxford University Press). Kamenskaya OE (2000) Order Komokiida. Protista. Manual on Zoology . Part 1. St. Petersburg, “Science”, 524-527 Kaminski, M.A., and Schröder, C.J. (1987). Environmental analysis of deep-sea agglutinated foraminifera: can we distinguish tranquil from disturbed environments? In Gulf Coast Section SEPM Foundation Eighth Annual Research Conference , 90-93. Karl, D.M., McMurtry, G.M., Malahoff, A., and Garcia, M.O. (1988). Loihi Seamount, Hawaii: a mid-plate volcano with a distinct hydrothermal system. Nature 335, 532- 535. Kays, R.W., Gompper, M.E., and Ray, J.C. (2008). Landscape ecology of eastern coyotes based on large-scale estimates of abundance. Ecol Appl 18 , 1014-1027. Keeling, P.J., Burger, G., Durnford, D.G., Lang, B.F., Lee, R.W., Pearlman, R.E., Roger, A.J., and Gray, M.W. (2005). The tree of eukaryotes. TREE 20 :670-676 Kimura, M. (1979). The neutral theory of molecular evolution. Sci Am 241 , 98-100. Kimura, M., and Weiss, W.H. (1964). The stepping stone model of genetic structure and the decrease of genetic correlation with distance. Genetics 49 , 561-576. Kitazato, H. (1988a). Ecology of benthic foraminifera in the tidal zone of a rocky shore. Revue de Paleobiologie special 2, 815-825. Kitazato, H. (1988b). Locomotion of some benthic foraminifera in an on sediments. Journal of Foraminiferal Research 18 , 344-349. Kitazato, H., Nomaki, H., Heinz, P., and Nakatsuka, T. (2003). The role of benthic foraminifera in deep-sea food webs at the sediment-water interface: Results from in situ feeding experiments in Sagami Bay. Front Res Earth Evol 1, 227-232. Kitazato, H., Shirayama, Y., Nakatsuka, T., Fujiwara, S., Shimanaga, M., Kato, Y., Okada, Y., Kanda, J., Yamaoka, A., Masuzawa, T., et al. (2000). Seasonal phytodetritus deposition and responses of bathyal benthic foraminiferal populations in Sagami Bay, Japan: preliminary results from ‘‘Project Sagami’’ 1996-1999. Marine Micropaleontology 40 , 135-149. Knittel, K., Losekann, T., Boetius, A., Kort, R., and Amann, R. (2005). Diversity and distribution of methanotrophic archaea at cold seeps. Appl Environ Microbiol 71 , 467- 479. Koho, K.A., Kouwenhoven, T.J., De Stigter, H.C., and Van Der Zwaan, G.J. (2007). Benthic foraminifera in the Nazaré canyon, Portuguese continental margin: sedimentary environments and disturbance. Marine Micropaleontology 66 , 27-51. Kramer, K.J.M., and Botterweg, J. (1991). Aquatic biological early warning systems: an overview (London, Academic Press). Krieger, K.L., and Wing, B. (2002). Megafauna associations with deepwater corals (Primnoa spp.) in the Gulf of Alaska. Hydrobiologia 471 , 83-90. Kucera, M., and Darling, K.F. (2002). Genetic diversity among modern planktonic foraminifer species: its effect on paleoceanographic reconstructions. Philos Trans R Soc Lond B Biol Sci A 360 , 695-718. Kurbjeweit, F., Schmiedl, G., Schiebel, R., Hemleben, C., Pfannkuche, O., Wallmann, K., and Schafer, P. (2000). Distribution, biomass and diversity of benthic foraminifera in relation to sediment geochemistry in the Arabian Sea. Deep-Sea Research II 47 , 2913- 2955.

176 Lambshead, J. D. P., and Boucher, G. (2003). Marine nematode deep-sea biodiversity – hyperdiverse or hype? J. Biogeography 30 , 475-485. Lampitt, R.S. (1996). Snow falls in the open ocean (London, Manson Publishing). Lara, E., Moreira, D., Vereshchaka, A., and Lopez-Garcia, P. (2009). Pan-oceanic distribution of new highly diverse clades of deep-sea diplonemids. Environ Microbiol 11 , 47-55. Larkin, M.A., Blackshields, G., Brown, N.P., Chenna, R., McGettigan, P.A., McWilliam, H., Valentin, F., Wallace, I.M., Wilm, A., Lopez, R., Thompson, J.D., Gibson, T.J., and Higgins, D.G. (2007). Clustal W and Clustal X version 2.0. Bioinformatics 23 , 2947- 2948. Laughton, A.S. (1963). Microtopography, Vol 3 (New York, Wiley-Intersience). Laureillard, J., Méjanelle, L., Sibuet, M. (2004). Use of lipids to study the trophic ecology of deep-sea xenophyophores. Marine Ecology Progress Series 270, 129-140. Le Calvez, J. (1947). Entosolenia marginata, foraminifere apogamique ectoparasite d'un autre foraminifere Discorbis mediterranensis. C R Acad Sci 224 , 1448-1450. Lee, J.J., and Bock, W.D. (1976). The importance of feeding in two species of soritid foraminifera with algal symbionts. Bull Mar Sci 26 , 530-537. Lee, J.J., Leedale, G.F., and Bradbury, P. (2000). The Illustrated Guide to the Protozoa , 2 nd ed., Society of Protozoologists. Lawrence, Kansas: Allen Press. Lemche, H., Hansen, B., Madsen, F.J., Tendal, O.S., and Wolff, T. (1976). Hadal life as analysed from photographs. Videnskabelige meddelelser fra Dansk naturhistorisk forening 139 , 263-336. Levin, L.A. (1991). Interactions between metazoans and large, agglutinated protozoans: Implications for the community structure of deep-sea benthos. Am Zool 31 :886-900. Levin, L.A. (1994). Paleoecology and ecology of xenophyophores. Palaios 5, 32-41. Levin, L.A., DeMaster, D.J., McCann, L.D., and Thomas, C.L. (1986). Effects of giant protozoans (Class: Xenophyophorea) on deep-sea-mount benthos. Marine Ecology Progress Series 29 , 99-104. Levin, L.A., Etter, R.J., Rex, M.A., Gooday, A.J., Smith, C.R., Pineda, J., Stuart, C.T., Hessler, R.R., and Pawson, D. (2001). Environmental influences on regional deep-sea species diversity. Annu Rev Ecol Syst 32 , 51-93. Levin, L.A., and Gooday, A.J. (1992). Possible roles for xenophyophores in deep-sea carbon cycling. In: Rowe GT, Pariente V, eds. Deep-Sea Food Chains and the Global Carbon Cycle . The Netherlands: Kluwer Academic Publishers, 93-104. Levin, L., Gutierrez, D., Rathburn, A., Neira, C., Sellanes, J., Munoz, P., Gallardo, V., and Salamanca, M. (2002). Benthic processes on the Peru margin: a transect across the oxygen minimum zone during the 1997-98 El Nino. Progress in Oceanography 53 , 1- 27. Levin, L.A., and Thomas, C.L. (1988). The ecology of xenophyophores (Protista) on eastern Pacific seamounts. Deep-Sea Research 35 , 2003-2027. Levinton, J.S. (1979). A Theory of Diversity Equilibrium and Morphological Evolution. Science 204 , 335-336. Ling, S.D. (2008). Range expansion of a habitat-modifying species leads to loss of taxonomic diversity: a new and impoverished reef state. Oecologia 156 , 883-894. Lipps, J.H. (1982). Biology / Paleobiology of Foraminifera. In Foraminifera: notes for a short course Studies in Geology , T.W. Broadhead, ed. (University of Tenessy), pp. 1-22. Loeblich, A.R., and Tappan, H. (1988). Foraminiferal Genera and their classification , Vol 1 (New York, Van Nostrand Reinhold). López-García, P., and Moreira, D. (2008). Tracking microbial biodiversity through molecular and genomic ecology. Res Microbiol 159 , 67-73. 177 López-García P, Philippe H, Gail F, Moreira D (2003) Autochthonus eukaryotic diversity in hydrothermal sediment and experimental microcolonizers at the Mid-Atlantic ridge. Proc Natl Acad Sci U S A 100 , 697-702. Lopez-Garcia, P., Rodriguez-Valera, F., Pedros-Alio, C., and Moreira, D. (2001). Unexpected diversity of small eukaryotes in deep-sea Antarctic plankton. Nature 409 , 603-607. Loreau, M. (1998). Biodiversity and ecosystem functioning: a mechanistic model. Proc Natl Acad Sci U S A 95 , 5632-5636. Lorion, J., Duperron, S., Gros, O., Cruaud, C., and Samadi, S. (2009). Several deep-sea mussels and their associated symbionts are able to live both on wood and on whale falls. Proc Biol Sci 276 , 177-185. Loubere, P. (1996). The surface ocean productivity and bottom water oxygen signals in deep water benthic foraminiferal assemblages. Marine Micropaleontology 28 , 247-261. Loubere, P., and Fariduddin, M. (1999). Benthic foraminifera and the flux of organic carbon to the seabed. In Modern Foraminifera , B.K.S. Gupta, ed. (Dordrecht, Kluwer Academic Publishers), pp. 181-199. Lovejoy, C., Massana, R., and Pedros-Alio, C. (2006). Diversity and Distribution of Marine Microbial Eukaryotes in the Arctic Ocean and Adjacent Seas. Appl Environ Microbiol 72 , 3085-3095. MacArthur, R.H., and Wilson, E.O. (1967). The Theory of Island Biogeography . (Princeton, N.J., Princeton University Press.). Magurran, A.E., and Henderson, P.A. (2003). Explaining the excess of rare species in natural species abundance distributions. Nature 422 , 714-716. Majewski, W., Lecroq, B., Sinniger, F., and Pawlowski J. (2007). Monothalamous foraminifera from Admiralty Bay, King George Island, West Antarctica. Polish Polar Research 28, 187-210. Malakoff, D. (2003). Deep-sea science. Cool corals become hot topic. Science 299 , 195. Margurran, A.E. (1988). Ecological diversity and its measurement (Princeton, Princeton University Press). Mayer, A.M., Rodriguez, A.D., Berlinck, R.G., and Hamann, M.T. (2009). Marine pharmacology in 2005-6: Marine compounds with anthelmintic, antibacterial, anticoagulant, antifungal, anti-inflammatory, antimalarial, antiprotozoal, antituberculosis, and antiviral activities; affecting the cardiovascular, immune and nervous systems, and other miscellaneous mechanisms of action. Biochim Biophys Acta. Mayr, E. (1942). Systematics and the origin of species, from the viewpoint of a zoologist (Cambridge, Harvard University Press.). Meadows, P.S., and Tufail, A. (1986). Bioturbation, microbial activity and sediment properties in an estuarine ecosystem. P roceedings of the Royal Society of Edinburgh 90B , 129-142. Meisterfeld, R., Holzmann, M., and Pawlowski, J. (2001). Morphological and molecular characterization of a new terrestrial allogromiid species: Edaphoallogromia australica gen. et spec. nov. (Foraminifera) from Northern Queensland (Australia). Protist 152 , 185-192. Miller, K.G., Katz, M.E., and Berggren, W.A. (1992). Cenzoic deep-sea benthic foraminifera; a tale of three turnovers. In: BENTHOS 90 , Sendai, Tokai University Press, p. 67-75. Miller, S.R., Strong, A.L., Jones, K.L., and Ungerer, M.C. (in Press). Barcoded Pyrosequencing Reveals Shared Bacterial Community Properties along Two Alkaline Hot Spring Temperature Gradients in Yellowstone National Park. Appl Environ Microbiol . 178 Minelli, A. (1993). Biological Systematics (London). Moeseneder, M.M., Witte, U., Smith, K., and Prosser, J.I. (2009). Response of bacterial communities to in situ carbon pulse label experiments at the abyssal seafloor. Paper presented at: International Census of Marine Microbes 454 Users Spring Meeting (Woods Hole, MA USA). Moodley, L., Boschker, H.T.S., Middelburg, J.J., Pel, R., Herman, P.M.J., De Deckere, E., and Heip, C.H.R. (2000). Ecological significance of benthic foraminifera : 13C labelling experiments. Marine Ecology Progress Series 202 , 289-295. Moodley, L., Middelburg, J.J., Boschker, H.T.S., Duineveld, G.C.A., Pel, R., Herman, P.M.J., and Heip, C.H.R. (2002) Bacteria and Foraminifera: key players in a short-term deep- sea benthic response to phytodetritus. Mar Ecol Progr Series 236 , 23–29 Moon-van der Staay, S.Y., De Wachter, R., and Vaulot, D. (2001). Oceanic 18S rDNA sequences from picoplankton reveal unsuspected eukaryotic diversity. Nature 409 , 607-610. Morato, T., Varkey, D.A., Damaso, C., Machete, M., Santos, M., Prieto, R., Santos, R.S., and Pitcher, T.J. (2008). Evidence of a seamount effect on aggregating visitors. Marine Ecology Progress Series 357 , 23-32. Moreira, D., and López-Garcia, P. (2002). The molecular ecology of microbial eukaryotes unveils a hidden world. Trends Microbiol 10 , 31-38. Munk, O. (2000). Histology of the fusion area between the parasitic male and the female in the deep-sea anglerfish Neoceratias spinifer Pappenheim, 1914 (Teleostei, Ceratioidei). Acta Zoologica Stockholm 81 , 315-324. Murray, J.W. (1991). Ecology and distribution of benthic foraminifera. In Biology of Foraminifera , J.J. Lee, and O.R. Anderson, eds. (London, Academic Press), pp. 221- 253. Murray, J.W. (1991). T he Ecology and Palaeoecology of Benthic Foraminifera . Longman, Harlow, 397 pp. Murray, J.W., (2006). Ecology and Applications of Benthic Foraminifera . Cambridge University Press, the Edinburgh Building, Cambridge CB2 2RU, UK, 438 pp. Murray, J.W. (2007). Biodiversity of living benthic foraminifera: How many species are there? Marine Micropaleontology 64 , 163-176. Nassonova, E., Smirnov, A., Fahrni, J., and Pawlowski, J. (2009). Barcoding amoebae: Comparison of SSU, ITS and COI as tools for molecular identification of naked lobose amoebae. Protist (in press). Naviaux, R.K., Good, B., McPherson, J.D., Steffen, D.L., Markusic, D., Ransom, B., and Corbeil, J. (2005). Sand DNA - a genetic library of life at the water's edge. Marine Ecology Progress Series 301 , 9-22. New, A.L., Smythe-Wright, D. (2001). Aspects of the circulation in the Rockall Through. Continental Shelf Research 21 , 777-810. Neyumayr, M. (1887). Die naturlichen Verwandschaftsverhaltnisse des Schalentragenden Foraminiferen. Sitzungsber Akad Wiss Wien 95 , 156-186. Niemann, H., Losekann, T., de Beer, D., Elvert, M., Nadalig, T., Knittel, K., Amann, R., Sauter, E.J., Schluter, M., and Klages, M. (2006). Novel microbial communities of the Haakon Mosby mud volcano and their role as a methane sink. Nature 443 , 854-858. Nomaki, H., Heinz, P., Hemleben, C., and Kitazato, H. (2005a). Behavior and response of deep-sea benthic foraminifera to freshly supplied organic matter: a laboratory feeding experiment in microcosm environments. J ournal of Foraminiferal Research 35 , 103- 113.

179 Nomaki, H., Heinz, P., Nakatsuka, T., Shimanaga, M., and Kitazato, H. (2005b). Species- specific ingestion of organic carbon by deep-sea benthic foraminifera and meiobenthos: In situ tracer experiments. Limnology and Oceanography 50 , 134-146. Norman, A.M. (1978). On the genus Haliphysema, with the description of several forms apparently allied to it. Annals and Magazine of Natural History series 5 (1), 264-284 Not, F., de CAmpo, J., Balagué, V., de Vargas, C., and Massana, R. (in Press). New insights into the diversity of marine picoeukaryotes. PLOS ONE . Not, F., Gausling, R., Azam, F., Heidelberg, J.F., and Worden, A.Z. (2007). Vertical distribution of picoeukaryotic diversity in the Sargasso Sea. Environmental Microbiology 9: 1233-1252. O'Connell, S., Alonso, B., Kastens, K.A., Maldonado, A., Malinverno, A., Nelson, C.H., Palanques, A., and Ryan, W.B.F. (1985). Morphology and downslope sediment displacement in a deep-sea valley, the Valencia Valley (Northwestern Mediterranean). Geo-Marine Letters 5, 149-156. Ohga, T., and Kitazato, H. (2003). Seasonal changes in bathyal foraminiferal populations in response to the flux of organic matter (Sagami Bay, Japan). Terr Nova 9 , 33-37. Olu, K., Duperret, A., Sibuet, M., Foucher, J.-P., and Fiala-Medioni, A. (1996). Structure and distribution of cold seep communities along the Peruvian active margin: relationship to geological and fluid patterns. Marine Ecology Progress Series 132 , 109-125. Pawlowski, J. (2000). Introduction to the molecular systematics of foraminifera. Micropaleontology 46 (Suppl 1), 1-12. Pawlowski, J. (2009). Foraminifera. In Encyclopedia of Microbiology , M. Schaechter, ed. (Oxford, Elsevier), pp. 646-662. Pawlowski, J., and Berney, C. (2003). Episodic evolution of nuclear small subunit ribosomal RNA gene in the stem lineage of Foraminifera. In: Donoghue, P.C. and Smith, M.P. (eds.) Telling the evolutionary time: molecular clocks and the fossil record . Systematics Association Special Volume No. 66. London: Taylor & Francis. pp. 107- 118. Pawlowski, J., Bolivar, I., Fahrni, J., Cavalier-Smith, T. and Gouy, M. (1996). Early origin of foraminifera suggested by SSU rRNA gene sequences. Molecular Biology and Evolution 13 ,445-450. Pawlowski, J., Bolivar, I., Fahrni, J.F., de Vargas, C., and Gouy, M. (1997). Extreme differences in rates of molecular evolution of foraminifera revealed by comparison of ribosomal DNA sequences and the fossil record. Molecular Biology and Evolution 14 , 498-505. Pawlowski, J., Bolivar, I., Farhni, J., and Zaninetti, L. (1995). DNA analysis of ''Ammonia beccarii'' morphotypes: One or more species? Marine Micropaleontology 26 , 171-178. Pawlowski, J., Bolivar, I., Guiard-Maffia, J., and Gouy, M. (1994). Phylogenetic position of foraminifera inferred from LSU rRNA gene sequences. Mol Biol Evol 11 , 929-938. Pawlowski, J., Bowser, S.S., Gooday, A.J. (2007). A note on the genetic similarity between shallow- and deep-water Epistominella vitrea (Foraminifera) in the Antarctic. Deep- Sea Research II 54 , 1720-1726. Pawlowski, J., Fahrni, J., and Bowser, S.S. (2002a). Phylogenetic analysis and genetic diversity of Notodendrodes hyalinosphaira. Journal of Foraminiferal Research 32 , 173-176. Pawlowski, J., Fahrni, J.F., Brykczynska, U., Habura, A., and Bowser, S.S. (2002). Molecular data reveal high taxonomic diversity of allogromiid Foraminifera in Explorers Cove (McMurdo Sound, Antarctica). Polar Biology 25 , 96-105.

180 Pawlowski, J., Fahrni, J.F., Guiard, J., Konlan, K., Hardecker, J., Habura, A., and Bowser, S.S. (2005). Allogromiid foraminifera and gromiids from under the Ross Ice Shelf: morphological and molecular diversity. Polar Biology 28 , 514-522. Pawlowski, J., Fahrni J., Lecroq B., Longet D., Cornelius N., Excoffier L., Cedhagen T. & Gooday A., J. (2007) Bipolar gene flow in deep-sea benthic foraminifera. Molecular Ecology 16 , 4089-4096. Pawlowski, J., and Holzmann, M. (2008). Diversity and geographic distribution of benthic foraminifera: a molecular perspective. Biodiversity and Conservation 20 , 317-328. Pawlowski, J., Holzmann, M., Berney, C., Fahrni, J., Cedhagen, T., and Bowser, S.S. (2002b). Phylogeny of allogromiid foraminifera inferred from SSU rRNA gene sequences. Journal of Foraminiferal Research 32 , 334-343. Pawlowski, J., Holzmann, M., Berney, C., Fahrni, J., Gooday, A.J., Cedhagen, T., Habura, A., and Bowser, S.S. (2003). The evolution of early Foraminifera. Proc Natl Acad Sci U S A 100 , 11494-11498. Pawlowski, J., Holzmann, M., Fahrni, J., and Richardson, S.L. (2003). Small subunit ribosomal DNA suggests that the xenophyophorean Syringamma corbicula is a foraminifera. Journal of Eukaryotic Microbiology 50 (6), 483-487. Pawlowski, J., Lee, J.J., and Gooday, A.J. (1993). Microforaminifera—perspective on a neglected group of foraminifera. Arch Protistenkd 143 , 271-284. Pawlowski, J., Majewski, W., Longet, D. Guiard, J., Cedhagen, T., Gooday, A.J., Korsun, S., Habura, A.A., and Bowser, S.S. (2008). Genetic differentiation between Arctic and Antarctic monothalamous foraminifera. Polar Biology 31 , 1205-1216. Pedros-Alio, C. (2006). Marine microbial diversity: can it be determined? Trends Microbiol 14 , 257-263. Pernthaler, J. (2005). Predation on prokaryotes in the water column and its ecological implications. Nat Rev Microbiol 3, 537-546. Pfisterer, A.B., and Schmid, B. (2002). Diversity-dependent production can decrease the stability of ecosystem functioning. Nature 416 , 84-86. Phelger, F.B. (1976). Benthic foraminiferids as indicators of organic production in marginal marine areas. Maritime Sediments Special Publication 1, 107-117. Polymenakou, P.N., Lampadariou, N., Mandalakis, M., and Tselepides, A. (2009). Phylogenetic diversity of sediment bacteria from the southern Cretan margin, Eastern Mediterranean Sea. Syst Appl Microbiol 32 , 17-26. Posada, D., and Crandall, K.A. (1998). MODELTEST: testing the model of DNA substitution. Bioinformatics 14 , 817-818. Posada, D., Crandall, K.A. (2001). Evaluation of methods for detecting recombination from DNA sequences using computer simulations. Proc. Nat. Acad. Sci. USA 98 , 13757- 13762 Poulain, A.J., Ní Chadhain, S.M., Ariya, P.A., Edenise Garcia, M.A., Campbell, P.G.C., Zylstra, G.J., and Barkay, T. (2007). Potential for Mercury Reduction by Microbes in the High Arctic. Applied and Environmental Microbiology 7 (73), 2230-2238. Rees, J.F., de Wergifosse, B., Noiset, O., Dubuisson, M., Janssens, B., and Thompson, E.M. (1998). The origins of marine bioluminescence: turning oxygen defence mechanisms into deep-sea communication tools. J Exp Biol 201 , 1211-1221. Rex, M.A. (1973). Deep-sea species diversity: decreased gastropod diversity at abyssal depths. Science 181 , 1051–1053. Rex, M.A. (1983). Geographic patterns of species diversity in deep-sea benthos (New York, John Wiley & Sons).

181 Richards, T.A., Vepritskiy, A.A., Gouliamova, D.E., Nierzwicki-Bauer, S.A. (2005). The molecular diversity of freshwater picoeukaryotes from an oligotrophic lake reveals diverse, distinctive and globally dispersed lineages. Environmental Microbiology , 1- 13. Roark, E.B., Guilderson, T.P., Dunbar, R.B., Fallon, S.J., and Mucciarone, D.A. (2009). Extreme longevity in proteinaceous deep-sea corals. Proc Natl Acad Sci U S A . Roberts, C.A., Ren, C., Beuselinck, P.R., Benedict, H.R., and Bilyeu, K. (2006). Fatty acid profiling of soybean cotyledons by near-infrared spectroscopy. Appl Spectrosc 60 , 1328-1333. Roca, A.L., Georgiadis, N., Pecon-Slattery, J., and O'Brien, S.J. (2001). Genetic evidence for two species of elephant in Africa. Science 293 , 1473-1477. Rokas, A., and Carroll, S.B. (2008). Frequent and widespread parallel evolution of protein sequences. Mol Biol Evol 25 , 1943-1953. Röttger, R., Irwan, A., Schmaljohann, R., and Franzisket, L. (1980). Growth of the symbiont- bearing foraminifera Amphistegina lessonii d'Orbigny and Heterostegina depressa d'Orbigny (Protozoa). In Endocytobiology and Cell Biology, S.W.e.S. H.E.A., ed. (Berlin, Walter de Gruyter). Rowe, G.T. (1974). The effects of the benthic fauna on the physical properties of deep-sea sediments (New York, Plenum Press). Rowe, G.T., Polloni, P.T., and Haedrich, R.L. (1982). The deep-sea macrobenthos on the continental margin of the North-west Atlantic Ocean. Deep-Sea Research 29 , 257-278. Rubinoff, D. (2006). Utility of mitochondrial DNA barcodes in species conservation. Conserv Biol 20 , 1026-1033. Ruby, E.G., Wirsen, C.O., and Jannasch, H.W. (1981). Chemolithotrophic Sulfur-Oxidizing Bacteria from the Galapagos Rift Hydrothermal Vents. Appl Environ Microbiol 42 , 317-324. Rumpho, M.E., Worful, J.M., Lee, J., Kannan, K., Tyler, M.S., Bhattacharya, D., Moustafa, A., and Manhart, J.R. (2008). Horizontal gene transfer of the algal nuclear gene psbO to the photosynthetic sea slug Elysia chlorotica. Proc Natl Acad Sci U S A 105 , 17867- 17871. Sabbatini, A., Morigi, C., Negri, A., and Gooday, A. (2007). Distribution and diversity of stained monothalamous foraminifera from Tempelfjord, Svalbard. Journal of Foraminiferal Research 37 , 93-106. Sabbatini, A., Pawlowski, J., Gooday, A.J., Piraino, S., Bowser, S.S., Morigi, C., and Negri, A. (2004). Vellaria antarctica n.sp., a new small monothalamous foraminifer from Terra Nova Bay, Antarctica. Antarctic Science 16 , 307-312. Sanders, H.L. (1968). Marine benthic diveristy: a comparative study. The American Naturalist 102 , 243-282. Sanders, H.L. (1969). Benthic marine diversity and the stability-time hypothesis. Brookhaven Symp Biol 22 , 71-81. Sanders, H.L., Hessler, R.R., and Hampson, G.R. (1965). An introduction to the study of the deep-sea benthic faunal assemblages along the Gay Head, Bermuda transect. Deep Sea Res 12 , 845-867 Schires, R., Gooday, A.J., and Jones, A.R. (1994). The morphology and ecology of an abundant new komokiacean mudball (Komokiacea, Foraminiferida) from the bathyal and abyssal NE Atlantic. Journal of Foraminiferal Research 24 (4) , 214-225. Schönfeld, J. (2001). Benthic foraminifera and pore-water oxygen profiles: A re- assessment of species boundary conditions at the western Iberian Margin. Journal of Foraminiferal Research 31 , 86-107. 182 Schroeder, C.J., Medioli, F.S., and Scott, D.B. (1989). Fragile abyssal foraminifera (including new Komokiacea) from the Nares abyssal plain. Micropaleontology 35 ,10-48 Schubert, R.J. (1921). Paleontologische Daten zur Stammesgeschichte der Protozoen. Paläont Zeitschr 3 , 129-188. Schultze, M.S. (1854). Uber den Organismus der Polythalamien (Foraminiferen) nebst Bemerkungen über die Rhizopoden im Allgemeinen (Leipzig). Schulze, F.E. (1904). Über den Bau und die Entwicklung gewisser Tiefsee-Organismen. Sitzungsberichte der Königlich-preussischen Akademie der Wissenschaften zu Berlin 53 : 1387. Schulze, F.E. (1907). Die Xenophyophoren, eine besondere Gruppe der Rhizopoden. Wissenschaftliche Ergebnisse der Deutschen Tiefsee-Expedition auf dem Dampfer “Validivia” 1898-1899 11 , 1-55. Schweizer, M., Pawlowski, J., Duijnstee, I.A.P., Kouwenhoven, T.J., and van der Zwaan, G.J. (2005). Molecular phylogeny of the foraminifera genus Uvigerina based on ribosomal DNA sequences. Marine Micropalentology 57 , 51-67. Schweizer, M., Pawlowski, J., Kouwenhoven, T.J., Guiard, J., van der Zwaan, B. (2008). Molecular phylogeny of Rotaliida (Foraminifera) based on complete small subunit rDNA sequences. Marine Paleontology 66 , 233-246. Scott, D.B., Medioli, F.S., and Schafer, C.T. (2001). Monitoring in coastal environments using foraminifera and thecamoebian indicators (Cambridge University Press). Seibel, B.A., Chausson, F., Lallier, F.H., Zal, F., and Childress, J.J. (1999). Vampire blood: respiratory physiology of the vampire squid (Cephalopoda: Vampyromorpha) in relation to the oxygen minimum layer. Experimental Biology Online 4, 1-10. Semeniuk, T.A. (2000). Spatial variability in epiphytic foraminifera from micro- to regional scale. Journal of Foraminiferal Research 30 , 99-109. Sen Gupta, B. (1999). In Modern Foraminifera , B. Sen Gupta, ed. (Dordrecht, The Netherlands, Kluwer), pp. 7-36. Shannon, C.E. (1948). A mathematical theory of communication. Bell System Technical Journal 27 , 379-423. Sheldon, P.R. (1996). Plus ca change-a model for stasis and evolution in different environments. Palaeogeography Palaeoclimatology Palaeoecology 127 , 209-227. Shimomura, O., Johnson, F.H., and Kohama, Y. (1972). Reactions involved in bioluminescence systems of limpet (Latia neritoides) and luminous bacteria. Proc Natl Acad Sci U S A 69 , 2086-2089. Shires, R., Gooday, A.J., and Jones, A.R. (1994). A new large agglutinated foraminifer (Arboramminidae n. fam.) from a oligotrophic site in the abyssal northeast Atlantic. J Foraminiferal Res 24 ,149-157 Silver, M.W., Shanks, A.L., and Trent, J.D. (1978). Marine Snow: Microplankton Habitat and Source of Small-Scale Patchiness in Pelagic Populations. Science 201 , 371-373. Simon, M., Grossart, H.-P., Schweitzer, B., and Ploug, H. (2002). Microbial ecology of organic aggregates in aquatic ecosystems. Aquat Microb Ecol 28 . Simpson, E.H. (1949). Measurement of diversity. Nature 163 , 688. Sinniger, F., Reimer, J.D., and Pawlowski, J. (2008). Potential of DNA sequences to identify zoanthids (Cnidaria: Zoantharia). Zoolog. Sci. 25 ,1253-60. Slapeta, J., Lopez-Garcia, P., and Moreira, D. (2006). Global dispersal and ancient cryptic species in the smallest marine eukaryotes. Molecular Biology and Evolution 23 , 23-29. Slatkin, M. (1993). Isolation by distance in equilibrium and non-equilibrium populations. Evolution 47 , 264-279.

183 Smith, C.R., Jumars, P.A., and deMaster, D.J. (1986). In situ studies of megafaunal mounds indicate rapid sediment turnover and community response at the deep-sea floor. Nature 323 , 251-253. Snider, L.J., Burnet, B.R., and Hessler, R.R. (1984). The composition and distribution of meiofauna and nanobiota in a central North Pacific deep-sea area. Deep-Sea Research I 31 , 1225-1249. Soetaert, K., and Heip, C. (1990). Sample-size dependence of diversity indices and the determination of sufficient sample size in a high-diversity deep-sea environment Marine Ecology Progress Series 59, 305-307. Sogin, M.L., Morrison, H.G., Huber, J.A., Mark Welch, D., Huse, S.M., Neal, P.R., Arrieta, J.M., and Herndl, G.J. (2006). Microbial diversity in the deep sea and the underexplored "rare biosphere". Proc Natl Acad Sci U S A 103 , 12115-12120. Song, H., Buhay, J.E., Whiting, M.F., and Crandall, K.A. (2008). Many species in one: DNA barcoding overestimates the number of species when nuclear mitochondrial pseudogenes are coamplified. Proc Natl Acad Sci U S A 105, 13486-13491. Stackebrandt, E., and Ebers, J. (2006). Taxonomic parameters revisited: tarnished gold standards. Microbiol Today 33 , 152-155. Stewart, C.B., Schilling, J.W., and Wilson, A.C. (1987). Adaptive evolution in the stomach lysozymes of foregut fermenters. Nature 330 , 401-404. Sun, X., Corliss, B.C., Brown, C.W., and Showers, W.J., (2006). The effect of primary production and seasonality on the distribution of deep-sea benthic foraminifera in the North Atlantic. Deep-Sea Res. I 53 , 28-47. Swinbanks, D.D., and Shirayama, Y. (1986a). High levels of natural radionuclides in a deep- sea infaunal xenophyophore. Nature 320 , 354-357. Swinbanks, D.D., and Shirayama, Y. (1986b). A model of the effect of an infaunal xenophyophore on 210Pb distribution in deep-sea sediment. La mer 24, 69-74. Takishita, K., Yubuki, N., Kakizoe, N., Inagaki, Y., and Maruyama, T. (2007). Diversity of microbial eukaryotes in sediment at a deep-sea methane cold seep: surveys of ribosomal DNA libraries from raw sediment samples and two enrichment cultures. Extremophiles 11 , 563-576. Tanksley, S.D. (1993). Mapping polygenes. Annu Rev Genet 27 , 205-233. Templeton, A.R., Crandall, K.A., and Sing, C.F. (1992). A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data. III. Cladogram estimation. Genetics 132 , 619-633. Tendal, O.S. (1972). A monograph of the Xenophyophora (Rhizopodea, Protozoa). Galathea Report 12 , 7-103. Tendal, O.S. (1979). Aspects of the biology of Komokiacea and Xenophyophoria. Sarsia 64 , 13-17. Tendal, O.S. (1990). Phylum Xenophyophora. In Handbook of Protoctista , L. Margulis, Corliss, J. O., Melkonian, M. Chapman, D. J. , ed. (Boston , MA, Jones & Bartlett Publishers), pp. 135-138. Tendal, O.S. (1996). Synoptic checklist and bibliography of the Xenophyophorea (Protista), with a zoogeographic survey of the group. Galathea Report 17 , 79-101. Tendal, O.S., and Gooday, A.J. (1981). Xenophyophoria (Rhizopoda, Protozoa) in bottom photographs from the bathyal and abyssal NE Atlantic, Oceanologica Acta 4, 415-422. Tendal, O.S., Swinbanks, D.D., and Shirayama, Y. (1982). A new infaunal xenophyophore (Xenophyophorea, Protozoa) with notes on its ecology and possible trace fossil analogues. Oceanologica Acta 5, 325-329.

184 Tendal, O.S., and Hessler, R.R. (1977). An introduction to the biology and systematics of Komokiacea (Textulariina, Foraminiferida). Galathea Report 14 , 165-194 Thiel, H., Pfannkuche, O., Schriever, G., Lochte, K., Gooday, A.J., Hemleben, Ch., Mantoura, R.F.C., Turley, C.M., Patching, J.W., and Riemann, F. (1989). Phytodetritus on the deep-sea floor in a central oceanic region of the northeast Atlantic. Biol Oceanography 6, 203-239 Thingstad, T.F. (2000). Elements of a theory for the mechanisms controlling abundance, diversity, and biogeochemical role of lytic viruses in aquatic systems. Limnology and Oceanography 45 , 1320-1328. Thistle, D. (2003). In: The Deep Seafloor. Ecosystems of the World (ed. Tyler PA), pp. 3-37. Elsevier, Amsterdam. Thomas, E. (1992). Cenozoic deep-sea circulation: evidence from deep-sea benthic foraminifera. Antarctic Research Series 56 , 141-165. Thomas, E., and Gooday, A.J. (1996). Cenozoic deep-sea benthic foraminifera: tracers for changes in oceanic productivity. Geology 24 , 355-358. Tilman, D. (2001). An evolutionary approach to ecosystem functioning. Proc Natl Acad Sci U S A 98 , 10979-10980. Todo, Y., Kitazato, H., Hashimoto, J., and Gooday, A.J. (2005). Simple foraminifera flourish at the ocean's deepest point. Science 307 , 689. Traversa, D., Iorio, R., Otranto, D., Modry, D., and Slapeta, J. (2008). Cryptosporidium from tortoises: Genetic characterisation, phylogeny and zoonotic implications. Mol Cell Probes 22 , 122-128. Travis, J.L., and Bowser, S.S. (1991). The motility of foraminifera. In Biology of foraminifera , J.J. Lee, and G.C. Anderson, eds. (London, Academic Press), pp. 91- 155. Tsuchiya, M., Kitazato, H., and Pawlowski, J. (2003). Analysis of internal transcribed spacer of ribosomal DNA reveals cryptic speciation in Planoglabratella opercularis. Journal of Foraminiferal Research 33 , 285-293. Tsurumi, M. (2003). Diversity at hydrothermal vents. Global Ecology and Biogeography 12 , 181-190. Tyler, P.A. (1988). Seasonality in the deep sea. Oceanography and Marine Biology - an Annual Review 26, 227-258. Tyler, P., Amaro, T., Arzola, R., Cunha, R.H., De Stigter, H., Gooday, A., Huvenne, V., Ingels, I., Kiriakoulakis, K., Lastras, G., et al. (in press). Europe’s Nazaré Submarine Canyon. Oceanography Magazine . Tylianakis, J.M., Tscharntke, T., and Klein, A.M. (2006). Diversity, ecosystem function, and stability of parasitoid-host interactions across a tropical habitat gradient. Ecology 87 , 3047-3057. Valone, T.J., and Barber, N.A. (2008). An empirical evaluation of the insurance hypothesis in diversity-stability models. Ecology 89 , 522-531. Van Dover, C.L. (2000). The Ecology of Deep-Sea Hydrothermal Vents (Princeton University Press). Van Dover, C.L., German, C.R., Speer, K.G., Parson, L.M., and Vrijenhoek, R.C. (2002). Evolution and biogeography of deep-sea vent and seep invertebrates. Science 295 , 1253-1257. Van Valen, L.M. (1976). Domains, deduction, the predictive method, and Darwin. Evolutionary Theory 1, 231-245. Vickerman, K. (1992). The diversity and ecological significance of Protozoa. Biodiversity and Conservation 1, 334-341. 185 Vlassov, V.V., Laktionov, P.P., and Rykova, E.Y. (2007). Extracellular nucleic acids. Bioessays 29 , 654-667. Voultsiadou, E., Pyrounaki, M.M., and Chintiroglou, C. (2007). The habitat engineering tunicate Microcosmus sabatieri Roule, 1885 and its associated peracarid epifauna. Estuar Coast Shelf Sci 74 , 197-204. Vrijenhoek, R.C. (1997). Gene flow and genetic diversity in naturally fragmented metapopulations of deep-sea hydrothermal vent animals. J Hered 88 , 285-293. Ward, B.B. (2002). How many species of prokaryotes are there? Proc Natl Acad Sci USA 99 , 10234-10236. Warming, E. (1895). Plantesamfund - Grundtræk af den økologiske Plantegeografi (Kjøbenhavn). Warwick, R.M., and Clarke, K.R. (1995). New 'biodiversity' measures reveal a decrease in taxonomic distinctness with increasing stress. Marine Ecology Progress Series 129 , 301-305. Weaver, P.P.E., (2005). The geobiology of the Nazare and Setubal Canyons, Portuguese Continental Margin. Cruise report No. 1 RRS Discovery cruise D297 27 Jul - 16 Aug 2005 . National Oceanography Centre, Southampton, 41 pp. Weaver, P.P.E., Billett, D.S.M., Boetius, A., Danovaro, R., Freiwald, A., and Sibuet, M. (2004). Hotspot Ecosystem Research on Europe's Deep-Ocean Margins. Oceanography 17 , 132-143. Weaver, P.P.E., and Masson, D.G. (2007). RRS James Cook Cruise 10, 13 May – 07 Jul. 2007 . National Oceanography Centre, Southampton, Cruise Report No. 22, 93 pp. Wefer, G., Berger, W.H., Bijma, J., and Fischer, G. (1999). Clues to ocean history: a brief overview of proxies. In Use of Proxies in Paleoceanography , G.F.a.G. Wefer, ed. (Berlin, Springer), pp. 1-68. Weinelt, M., Kuhnt, W., Sarnthein, M., Altenbach, A., Costello, O., Erlenkeuser, H., Plaumann, U., Simstich, J., Thies, A., Trauth, M.H., et al. (2001). Paleoceanographic proxies in the northern North Atlantic. In The Northern North Atlantic: A Changing Environment , W.R. P. Schäffer, M. Schlüter and J. Thiede, ed. (Berlin, Springer), pp. 319-352. Whitfield, J. (2005). Biogeography: is everything everywhere? Science 310 , 960-961. Whittaker, R.H. (1972). Evolution and measurement of species diversity. Taxon 21 , 213-251. Wilding, T. (2002). Taxonomy and ecology of Toxisarcon alba sp.nov. from Loch Linnhe, west coast of Scotland, UK. Journal of Foraminiferal Research 32 , 358-363. Williamson, D.I. (2003). The Origins of Larvae (Dordrecht, Kluwer Academic Publishers). Wintzingerode, F.V., Goëbel, U.B., and Stackebrandt, E. (1997). Determination of microbial diversity in environmental samples: pitfalls of PCR-based rRNA analysis. FEMS Microbiol Rev 21 , 213-229. Witman, J.D., Cusson, M., Archambault, P., Pershing, A.J., and Mieszkowska, N. (2008). The relation between productivity and species diversity in temperate-Arctic marine ecosystems. Ecology 89 , S66-80. Witman, J.D., Etter, R.J., and Smith, F. (2004). The relation between regional and local species diversity in marine benthic communities: a global perspective. Proc Natl Acad Sci U S A 101 , 15664-15669. Woloszynska, M., Bocer, T., Mackiewicz, P., and Janska, H. (2004). A fragment of chloroplast DNA was transferred horizontally, probably from non-eudicots, to mitochondrial genome of Phaseolus. Plant Mol Biol 56 , 811-820.

186 Won, Y., Young, C.R., Lutz, R.A., and Vrijenhoek, R.C. (2003). Dispersal barriers and isolation among deep-sea mussel populations (Mytilidae: Bathymodiolus) from eastern Pacific hydrothermal vents. Mol Ecol 12 , 169-184. Wood, T.E., Burke, J.M., and Rieseberg, L.H. (2005). Parallel genotypic adaptation: when evolution repeats itself. Genetica 123 , 157-170. Wright, S. (1931). Evolution in Mendelian populations. Genetics 16 , 97-159. Wright, S. (1943). Isolation by distance. Genetics 28 . Yachi, S., and Loreau, M. (1999). Biodiversity and ecosystem productivity in a fluctuating environment: the insurance hypothesis. Proc Natl Acad Sci U S A 96 , 1463-1468. Yanko, V., Arnold, A., and Parker, W. (1999). Effect of marine pollution on benthic foraminifera (Dordecht, Kuwer Academic). Yen, J. (2000). Life in transition: balancing inertial and viscous forces by planktonic copepods. Biol Bull 198 , 213-224. Young, R.E., and Mencher, F.M. (1980). Bioluminescence in Mesopelagic Squid: Diel Color Change During Counterillumination. Science 208 , 1286-1288. Zachos, J., Pagani, M., Sloan, L., Thomas, E., Billups, K. (2001). Trends, rhythms and aberrations in global climate 65 Ma to present. Science 292 , 686-693. Zakšek, V., Sket, B., Gottstein, S., Franjevi ć, D., and Trontelj, P. (2009). The limits of cryptic diversity in groundwater: phylogeography of the cave shrimp Troglocaris anophthalmus (Crustacea: Decapoda: Atyidae). Mol Ecol 18 , 931-946.

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188 Appendixes

Appendix A: Monothalamous foraminifera from Admiralty Bay...... 191

Appendix B: Bowseria arctowskii gen. et sp. nov...... 215

Appendix C: Supplementary Material of section 2.2 ...... 227

Appendix D: Using 454 sequencing technology to explore eukaryotes diversity ...... 229

Appendix E: Supplementary Material of section 3.2 ...... 235

Appendix F: Supplementary Material of section 3.3 ...... 239

Appendix G: Supplementary Material of section 4.2 ...... 241

Appendix H: Supplementary Material of section 4.3 ...... 243

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Appendix C

Supplementary Material of: The ‘mica sandwich’; a remarkable new genus of Foraminifera (Protista, Rhizaria) from the Nazare Canyon (Portuguese margin, NE Atlantic)

Table C1. Station data and number of specimens of Capsammina patelliformis recovered from each core. CD = R.R.S Charles Darwin, JC = R.R.S. James Cook, PE = RV Pelagia

Cruise Station Gear/Dive °N °W Depth (m) Specimens CD179 56851#1 Megacorer 39°.49.98´ 09°.93.28´ 3518 37

CD179 56848#1 Megacorer 39°.50.00´ 09°.93.35´ 3517 52

JC10 91 Isis Dive 46 39°29.822’ 9°55.995’ 3536 27

JC10 101 Megacorer 39°30.05’ 9°55.88’ 3466 24

JC10 122 Megacorer 39°30.05’ 9°55.88’ 3461 7

JC10 127 Isis Dive 57 39°29.756’ 9°56.041’ 3536 37

64PE138 12 Multicorer 39°38.87’ 9°14.72’ 344 2

64PE138 14 Multicorer 39°30.76’ 9°51.05’ 2847 1

64PE236 7 Multicorer 39°35.99’ 9°24.26’ 1160 12

64PE236 13 Multicorer 39°35.87’ 9°24.26’ 927 18

227 228 Appendix D

Using 454 sequencing technology to explore eukaryotes diversity in the polar deep-sea sediments (presented as a poster during the International Census of Marine Microbes “454 User Spring Meeting”, Woods Hole USA, April 6-9th , 2009)

J. Pawlowski 1, B. Lecroq 1, & L. Guillou 2

1 Department of Zoology and Animal Biology, University of Geneva, Switzerland 2 Station Biologique de Roscoff, France

INTRODUCTION

Deep sea floor is considered as one of the most diverse ecosystem on Earth, however, the origin of this huge diversity remains poorly understood. The research on deep-sea floor diversity is mainly focused on invertebrates. Very little is known about protists diversity despite that they often form a major part of deep-sea benthic meio- and microfauna. To get a better insight into the taxonomic structure of deep-sea bottom eukaryotes community, we investigate six surface sediment samples from the Arctic and Southern Oceans, collected at depth ranging from 686 to 6326 m. We used the 454-based sequencing technology to identify deep-sea eukaryotic phylotypes and to estimate their richness.

MATERIAL & METHODS

Variable region V9 of the SSU rDNA was sequenced. In total, 104’137 reads were obtained and combined into 29’627 unique eukaryotic sequence tags of the length of 120-130 nucleotides. Taxonomic analysis of these short rDNA tags show that all major groups of eukaryotes are represented at the deep-sea floor. The dinoflagellates, ciliates, cercozoans and euglenozoans predominate, making up 38% of all sequences. The diatoms, metazoans, and plants are also abundant. On the other hand, the amoebozoan and fungi are the least common 229 among the major eukaryotic groups. However, the relative abundance of different groups varies considerably from sample to sample. For example the dinoflagellates form 32% of sequences in DSE3 sample but only 5% in the adjacent but much shallower sample DSE2. The sequence tags were combined into OTUs (at 99% similarity level) for samples DSE2 and DSE4. The number of obtained OTUs corresponded to 59% and 62% of the total number of sequence tags, respectively. The proportion of different taxonomic groups remained similar. However, because the definition of OTUs in the V9 region is ambigous for some groups, the sequence tags rather than OTUs were analysed here.

Figure 1. Sampling locations and depths.

230 RESULTATS

Amoebozoa Fungi Metazoa other Opisthokonta Plantae Cercozoa Haplosporidia Foraminifera Radiolaria Ciliophora Dinophyceae Apicomplexa Bacilliariophyta Labyrinthulida Chryso- + Synurophycea Pinguiophyceae MAST other Stramenopiles Euglenozoa other Excavata Apusozoa Cryptophyta Haptophyta Telonemida Other lineages Non determined

Figure 2. Diagram representing the proportion of major eukaryotic groups identified using KeysDNA approach (see below).

Taxonomic identification

The accurate identification of V9 sequence tags is probably the most challenging problem. To evaluate the relative efficiency of different methods we compared identifications obtained with Blast, GAST and KeysDNA ( KeyDNAtools.com ) for the DSE2 sample.

Blast provides very good resolution and determines almost all sequences. However, the reliability of Blast results is relatively low: more than 25% of identifications are uncertain (score < 100) in DSE2.

GAST identifications are certainly more reliable, but several taxonomic groups, such as Haplosporidia, Radiolaria, etc. were not recognized. Moreover, some very good Blast identifications were misidentified by GAST. KeysDNA method identifies sequences by using short 15mers oligonucleotides (Guillou et al. 2008). Their specificity is deduced from a manually annotated referenced sequences and the reliability of the result can be evaluated from the number of keys providing converging annotation. In our data, the Keys recognize all major eukaryotic groups. However, many sequences could not be annotated, leaving much larger proportion of non determined sequences (25%) than the other two methods. Both Keys and GAST require optimization for V9 region and eukaryotic database to be more efficient.

Surface and extracellular DNA

Taxonomic analysis of our environmental DNA samples shows clearly that many sequences belong to the surface dwelling organisms. According to our estimations for the DSE2 sample, about 13% of sequences originated from the photosynthetic taxa (dinoflagellates not included), less than 3% belong to planktonic heterotrophic protists (radiolarians, planktonic forams, MAST), and 18% are very similar (best Blast) to the sequences reported in various picoplankton surveys. Thus, about one third of all sequences in this sample originated from the specimens that possibly are not living at the ocean floor. This proportion may be even higher if we include the metazoans and various protists living in the water column close to the bottom. On the other hand, in all samples we found high diversity of metazoans, including some macrofaunal taxa (ophiuroids, echinoids, etc.). It is highly improbable that all these species could be found in our very small sediment samples (0.35g or 0.7g), even in form of larvae or eggs. Some of these sequences originate probably from the extracellular DNA present in deep-sea sediments.

232 Non determined Other lineages * Breviatea 100% Planomonadida Centroheliozoa 90% Picobiliphyta Katablepharidales Telonemida 80% Haptophyta Cryptophyta Apusozoa 70% other Excavata Euglenozoa 60% other Stramenopiles MAST Pinguiophyceae 50% Chryso- + Synurophycea Labyrinthulida 40% Bacilliariophyta other Alveolates Apicomplexa 30% Dinophyceae Ciliophora Radiolaria 20% Foraminifera Haplosporidia 10% Cercozoa Plantae other Opisthokonta 0% Choanozoa Metazoa Blast GAST Keys Fungi Amoebozoa Figure 3. Diagram representing relative abundances of eukaryotic taxonomic groups identified with Blast, GAST and KeysDNA methods for the sample DSE2.

Phytoplankton Plantae Bacilliariophyta Chryso- + Synurophycea Pinguiophyceae other Stramenopiles Cryptophyta Undetermined Picoplankton Haptophyta Picobiliphyta Benthos? Foraminifera Radiolaria MAST ND picoplankton Others

Figure 4. Pie chart representing the proportion of sequences from photosynthetic and putative planktonic species in DSE2 sample. 233

Acknowledgements We thank Andrew Gooday, Angelika Brandt, Brigitte Hilbig, Eberhard Fahrbach and captains, officers and crew of R/V Polarstern for their assistance during ANDEEP II and ARK XXIV expeditions; Linda Amaral-Zettler, Hilary Morrison, Mitch Sogin and other members of the ICoMM and MBL Laboratory for 454 sequencing; Swiss National Science Foundation, and ANR Aquaparadox for support .

Deep -sea deer

Curiosity ! Deep-sea deer are timid creatures living in abyssal depths. No living one has been seen yet but their DNA has been just found in our sediment samples. The one identified in DSE3 sample seems closely related (100% similarity in V9) to the white tailed deer Odocoileus virginianus .

234 Appendix E

Supplementary Material of: The Molecular analyses reveal high levels of eukaryotic richness associated with enigmatic deep-sea protists (Komokiacea.)

Table E1 (continuation). Sampling stations. N: North, S: South, W: West, E: East, BC: Boxcore, MC: Multicore.

Station Water General area Location Gear DNA samples number depths (m)

Lower Continental 65°19.35’S AII 131 BC/MC 3055 SED9 Slope NW Weddell 51°32.26’W

Middle Continental 65°20.23’ S SED1335, SED1331, AII 133 BC/MC 1166 Slope, N W Weddell 54°12.65’ W SEDk82, SEDk42, SED7 Weddell Abyssal 62°45.36' S AII 134 BC/MC 2514 S3455 Plain 52°48.61' W N Weddell Abyssal 64°01.67’ S AII 136 Plain, S Endurance BC/MC 4760 SED12, S3410 39°07.68’ W Ridge N Weddell Abyssal 63°45.00’ S N3474, N3475, SED8, AII 137 Plain, near fracture BC/MC 4975 33°47.81’ W SED817 zone S Sandwich Trench, 58°14.71’S AII 139 E of Montague BC/MC 3936 N3502, SED1397 24°20.48’W Island S Sandwich Trench, 58° 16.14’ S AII 140 E of Montague BC/MC 2964 SED5, SED140, SED14045 24°53.74’ W Island N5977, N5124, S5929, 67°30.37' S AIII 59 N Weddell MC 4648 S5132, S5125, S5928, 0°03.74' W S5930 N7578, N7576, N7580, 70°39.22' S AIII 80 N Weddell BC/MC 3102 S5936, S5933, S5947, 14°43.39' W S5935 N5177, N5982, N5981, N5986, N5978, N5980, 68°03.65' S AIII 88 N Weddell BC/MC 4932 N5983, N5984, S5954, 20°27.77' W S5176, S7587, S5967, S5962, S5970 N6012, N6013, N5976, 66°37.43' S AIII 94 N Weddell BC/MC 4894 N6016, N7569, S5183, 27°09.77' W SED945 AIII 65°34.32' S N5214, S5213, S7592, N Weddell BC/MC 4805 102 36°31.32' W S7589, S7588, S7591 CD158 Porcupine Abyssal 48°51.00’ N MC 4800 S4995 56519 Plain 16°29.90’W CD158 Porcupine Abyssal 48°51.00’ N MC 4800 S5008 56527 Plain 16°29.80’W 235

Table E2. GenBank accession numbers.

GenBank GenBank Sequence name Sequence name accession number accession number Foraminifera S5132-12 FJ646666 Eukaryotes N5984-94 FJ646716 Foraminifera N5976-102 FJ646667 Eukaryotes S5929-45 FJ646717 Foraminifera S3496-A FJ646668 Eukaryotes N7580-33 FJ646718 Foraminifera N3397-A FJ646669 Eukaryotes N7580-52 FJ646719 Foraminifera S3455-A FJ646670 Eukaryotes SED12-51 FJ646720 Foraminifera S3410-71 FJ646671 Eukaryotes N6012-33 FJ646721 Foraminifera S3465-13 FJ646672 Eukaryotes S5132-12 FJ646722 Foraminifera N3475-51 FJ646673 Eukaryotes N5177-103 FJ646723 Foraminifera S5213-21 FJ646674 Eukaryotes N5980-54 FJ646724 Foraminifera N5177-92 FJ646675 Eukaryotes SED7-22 FJ646725 Foraminifera S5947-63 FJ646676 Eukaryotes S7592-102 FJ646726 Foraminifera S5967-122 FJ646677 Eukaryotes N6013-48 FJ646727 Foraminifera S5970-112 FJ646678 Eukaryotes S7587-52 FJ646728 Foraminifera N5177-93 FJ646679 Eukaryotes S7587-53 FJ646729 Foraminifera S4995-25 FJ646680 Eukaryotes S7587-55 FJ646730 Foraminifera S5125-5c FJ646681 Eukaryotes S7587-63 FJ646731 Foraminifera N3502-52 FJ646682 Eukaryotes N6016-57 FJ646732 Foraminifera N3474-52 FJ646683 Eukaryotes N6013-45 FJ646733 Foraminifera S5213-111 FJ646684 Eukaryotes N6013-47 FJ646734 Foraminifera N3502-A FJ646685 Eukaryotes N6016-53 FJ646735 Foraminifera S5008-62 FJ646686 Eukaryotes N3502-73 FJ646736 Foraminifera S5928-11 FJ646687 Eukaryotes N3502-75 FJ646737 Foraminifera S5962-41 FJ646688 Eukaryotes S5954-24 FJ646738 Eukaryotes N5986-104 FJ646689 Eukaryotes S5967-44 FJ646739 Eukaryotes N5984-92 FJ646690 Eukaryotes S5967-43 FJ646740 Eukaryotes N5132-14 FJ646691 Eukaryotes S5954-22 FJ646741 Eukaryotes S5132-31p FJ646692 Eukaryotes S5954-23 FJ646742 Eukaryotes N3475-65 FJ646693 Eukaryotes S596742 FJ646743 Eukaryotes N5978-41 FJ646694 Eukaryotes SED139-742 FJ646744 Eukaryotes N5978-45 FJ646695 Eukaryotes SE139-749b FJ646745 Eukaryotes N5980-55 FJ646696 Eukaryotes SED139-740 FJ646746

236

Table E1 (continuation). GenBank accession numbers.

Sequence GenBank Sequence GenBank name accession number name accession number Eukaryotes N5984-95 FJ646699 Eukaryotes SED140-459 FJ646749 Eukaryotes N5983-85 FJ646700 Eukaryotes S5176-43p FJ646750 Eukaryotes N5978-42 FJ646701 Eukaryotes N7580-35 FJ646751 Eukaryotes N5978-44 FJ646702 Eukaryotes S5936-83 FJ646752 Eukaryotes N5978-43 FJ646703 Eukaryotes SED140-452 FJ646753 Eukaryotes N3475-63 FJ646704 Eukaryotes N5982-74 FJ646754 Eukaryotes S5132-13 FJ646705 Eukaryotes SED8-32 FJ646755 Eukaryotes N5984-91 FJ646706 Eukaryotes S5933-52 FJ646756 Eukaryotes N7569-14 FJ646707 Eukaryotes S5933-51 FJ646757 Eukaryotes N7569-13 FJ646708 Eukaryotes SE1397-49a FJ646758 Eukaryotes N7569-15 FJ646709 Eukaryotes SED140-454 FJ646759 Eukaryotes N7569-12 FJ646710 Eukaryotes SED140-21 FJ646760 Eukaryotes N5984-93 FJ646711 Eukaryotes N5981-61 FJ646761 Eukaryotes N3474-51 FJ646712 Eukaryotes N5981-62 FJ646762 Eukaryotes N3474-54 FJ646713 Eukaryotes S7587-62 FJ646763 Eukaryotes N5986-105 FJ646714 Eukaryotes N6012-32 FJ646764 Eukaryotes N6012-38 FJ646765 Eukaryotes SED5-15 FJ646818 Eukaryotes N6012-39 FJ646767 Eukaryotes S5947-104 FJ646819 Eukaryotes N5976-21 FJ646768 Eukaryotes N5124-91 FJ646820 Eukaryotes N5977-31 FJ646769 Eukaryotes SED8-1721 FJ646821 Eukaryotes N5977-35 FJ646770 Eukaryotes SED8-1727 FJ646822 Eukaryotes N5976-25 FJ646771 Eukaryotes SED8-1724 FJ646823 Eukaryotes N6012-37 FJ646772 Eukaryotes SED8-1723 FJ646824 Eukaryotes SED133-532 FJ646773 Eukaryotes SED8-1720 FJ646825 Eukaryotes SEDk42-33 FJ646774 Eukaryotes SED8-1722 FJ646826 Eukaryotes SED133-14 FJ646775 Eukaryotes SED8-1725 FJ646827 Eukaryotes N5983-83 FJ646776 Eukaryotes SED8-1726 FJ646828 Eukaryotes SED133-15 FJ646777 Eukaryotes SED8-1729 FJ646829 Eukaryotes SED12-54 FJ646778 Eukaryotes SED8-35 FJ646830 Eukaryotes SED12-52 FJ646779 Eukaryotes S5213-61p FJ646831 Eukaryotes SED133-539 FJ646780 Eukaryotes SED9-45 FJ646832 Eukaryotes SED133-13 FJ646781 Eukaryotes N5214-15 FJ646833 Eukaryotes S7591-91 FJ646782 Eukaryotes SED945-11 FJ646834 Eukaryotes S5176-25 FJ646783 Eukaryotes SED945-14 FJ646835 Eukaryotes SED133-533 FJ646784 Eukaryotes SED945-18 FJ646836 Eukaryotes SED133-53 FJ646785 Eukaryotes SED945-16 FJ646837 Eukaryotes SED133-537 FJ646786 Eukaryotes SED945-13 FJ646838 Eukaryotes SED140-450 FJ646787 Eukaryotes N5124-94 FJ646839 Eukaryotes N5983-53 FJ646788 Eukaryotes S7589-81 FJ646840

237

Table E1 (continuation). GenBank accession numbers.

Sequence GenBank Sequence GenBank name accession number name accession number Eukaryotes SED945-17 FJ646870 Eukaryotes S5935-72 FJ646791 Eukaryotes S7588-74 FJ646871 Eukaryotes S5935-71 FJ646792 Eukaryotes S5954-25 FJ646872 Eukaryotes S5933-53 FJ646793 Eukaryotes N5976-22 FJ646873 Eukaryotes S5935-73 FJ646794 Eukaryotes N6012-36 FJ646874 Eukaryotes S5935-75 FJ646795 Eukaryotes N6013-41 FJ646875 Eukaryotes S5935-74 FJ646796 Eukaryotes N5177-102 FJ646876 Eukaryotes SED140-23 FJ646797 Eukaryotes S5176-23 FJ646877 Eukaryotes SED140-24 FJ646798 Eukaryotes N3502-72 FJ646878 Eukaryotes SED140-25 FJ646799 Eukaryotes SED140-22 FJ646879 Eukaryotes SEDk42-31 FJ646800 Eukaryotes SED139-743 FJ646880 Eukaryotes N7578-41 FJ646843 Eukaryotes S5213-65p FJ646881 Eukaryotes N5124-93 FJ646844 Eukaryotes N5177-101 FJ646882 Eukaryotes SED8-34 FJ646845 Eukaryotes SEDk42-35 FJ646802 Eukaryotes SED133-535 FJ646846 Eukaryotes SEDk82-41 FJ646803 Eukaryotes SED133-536 FJ646847 Eukaryotes SED8-33 FJ646804 Eukaryotes SED945-10 FJ646848 Eukaryotes S5213-63p FJ646805 Eukaryotes SED945-12 FJ646849 Eukaryotes S7588-71 FJ646806 Eukaryotes N5177-105 FJ646850 Eukaryotes SED139-741 FJ646807 Eukaryotes N5977-32 FJ646851 Eukaryotes N6016-52 FJ646808 Eukaryotes S7589-82 FJ646852 Eukaryotes S5183-31 FJ646809 Eukaryotes N7576-35 FJ646857 Eukaryotes N6016-55 FJ646810 Eukaryotes SED133-531 FJ646858 Eukaryotes S5967-45 FJ646811 Eukaryotes SED133-538 FJ646859 Eukaryotes S5183-51p FJ646812 Eukaryotes SED139-746 FJ646860 Eukaryotes S5125-23p FJ646813 Eukaryotes SED133-534 FJ646861 Eukaryotes S5125-22p FJ646814 Eukaryotes N5214-11 FJ646862 Eukaryotes SED5-12 FJ646815 Eukaryotes SED139-748 FJ646863 Eukaryotes SED5-14 FJ646816 Eukaryotes SED12-55 FJ646864 Eukaryotes SEDk42-32 FJ646801 Eukaryotes N5214-14 FJ646865 Eukaryotes S5929-41 FJ646854 Eukaryotes SED7-21 FJ646866 Eukaryotes N5977-33 FJ646855 Eukaryotes N3474-52 FJ646867 Eukaryotes S7592-101 FJ646856 Eukaryotes N3474-55 FJ646869 Eukaryotes S5176-22 FJ646853 Eukaryotes N7578-42 FJ646842 Eukaryotes N5981-63 FJ646697 Eukaryotes SED140-458 FJ646747 Eukaryotes N5983-84 FJ646698 Eukaryotes SED140-451 FJ646748 Eukaryotes N5980-51 FJ646789 Eukaryotes N5124-92 FJ646841 Eukaryotes S5933-55 FJ646790

238 Appendix F

Supplementary Material of: Assessment of the deep-sea foraminiferal richness by massive sequencing with Solexa analyser (from www.illumina.com/downloads/SS_DNAsequencing.pdf )

Figure F1. Massive sequencing method with Solexa analyser.

239

Figure F1 (continuation). Massive sequencing method with Solexa analyser.

240 Appendix G

Supplementary Material of: Bipolar gene flow in deep-sea benthic foraminifera

Table G1. Isolates of Epistiminella exigua with description of sampling sites

DNA Depth area locality cruise date station latitude longitude # (m) 3606 Antarctic Weddell Sea ANT-XIV/4 avr.02 131 65°18,69' S 51°31,36'W 3066 3623 Antarctic Weddell Sea ANT-XIV/4 avr.02 136 64°1,56' S 39°6,94' W 4749 3625 Antarctic Weddell Sea ANT-XIV/4 avr.02 137 63°45,5' S 33°47,63' W 4975 3629 Antarctic Weddell Sea ANT-XIV/4 avr.02 138 62°57,86' S 27°54,1'W 4541 3631 Antarctic Weddell Sea ANT-XIV/4 avr.02 139 58°14,4' S 24°20,26' W 3934 3634 Antarctic Weddell Sea ANT-XIV/4 avr.02 139 58°14,4' S 24°20,26' W 3934 NE Porcupine Darwin 158 48°85,34' N 16°49,53' E 4941 Atlantic Abyssal Plain juin.04 56502/6 4815 5127 Antarctic Weddell Sea ANT-XXII/3 févr.05 59/7 67°31,05' S 0°0,27' E 4654 5142 Antarctic Weddell Sea ANT-XXII/3 févr.05 59/14 67°31,01' S 0°0,00' W 4650 5153 Antarctic Weddell Sea ANT-XXII/3 févr.05 80/5 70°39,40' S 14°43,47' W 3086 5191 Antarctic Weddell Sea ANT-XXII/3 févr.05 102/8 65°34,37' S 36°30,93' W 4803 5218 Antarctic Weddell Sea ANT-XXII/3 févr.05 110/4 64°59.95' S 43°1.97' W 4700 5222 Antarctic Weddell Sea ANT-XXII/3 févr.05 110/6 64°59.98' S 43°2.00' W 4700 5225 Antarctic Weddell Sea ANT-XXII/3 févr.05 110/6 64°59.98' S 43°2.00' W 4700 5233 Antarctic Weddell Sea ANT-XXII/3 févr.05 121/4 63°40.99' S 50°44.29' W 2609 5406 Arctic AWI Hausgarten ARKXXI/1b août.05 238 79°3,91' N 4°10,81' E 2462 5448 Arctic AWI Hausgarten ARKXXI/1b août.05 248 79°4,01' N 4°10,22' E 2465 5459 Arctic AWI Hausgarten ARKXXI/1b août.05 248 79°4,01' N 4°10,22' E 2465 5461 Arctic AWI Hausgarten ARKXXI/1b août.05 251 79°17,01' N 4°19,81' E 2402 5466 Arctic AWI Hausgarten ARKXXI/1b août.05 250 79°36,23' N 5°10,32' E 2784 5486 Arctic AWI Hausgarten ARKXXI/1b août.05 276 79°7,81' N 4°54,13' E 1548 5536 Arctic AWI Hausgarten ARKXXI/1b août.05 273 78° 55,05' N 5°0,13' E 2633 Norwegian Hakon Mosby ARKXXI/1b 71° 57,63' N 14°39,79' E 5701 Sea sept.05 371 1351

Norwegian Hakon Mosby ARKXXI/1b 71° 57,63' N 14°39,79' E 5702 Sea sept.05 371 1351 5718 Arctic AWI Hausgarten ARKXXI/1b sept.05 274 78° 46,83' N 5°19,95' E 2467 5719 Arctic AWI Hausgarten ARKXXI/1b sept.05 274 78° 46,83' N 5°19,95' E 2467 5724 Arctic AWI Hausgarten ARKXXI/1b sept.05 276 79° 7,81' N 4°54,13' E 1548 5725 Arctic AWI Hausgarten ARKXXI/1b sept.05 276 79° 7,81' N 4°54,13' E 1548 5726 Arctic AWI Hausgarten ARKXXI/1b sept.05 276 79° 7,81' N 4°54,13' E 1548

241 Table G2. Isolates of Cibicides wuellerstorfi with description of sampling sites

DNA Depth area locality cruise date station latitude longitude # (m) 5247 Antarctic Weddell Sea ANT-XXII/3 févr.05 133/2 62°6.34' S 53°4.14' W 1581 5400 Arctic AWI Hausgarten ARKXXI/1b août.05 238 79°3,91' N 4°10,81' E 2462 5402 Arctic AWI Hausgarten ARKXXI/1b août.05 238 79°3,91' N 4°10,81' E 2462 5437 Arctic AWI Hausgarten ARKXXI/1b août.05 252 79°3,60' N 3°34,89' E 3485 5438 Arctic AWI Hausgarten ARKXXI/1b août.05 252 79°3,60' N 3°34,89' E 3485 5439 Arctic AWI Hausgarten ARKXXI/1b août.05 252 79°3,60' N 3°34,89' E 3485 5441 Arctic AWI Hausgarten ARKXXI/1b août.05 252 79°3,60' N 3°34,89' E 3485 5660 Antarctic Weddell Sea ANT-XXII/3 févr.05 150/7 61°48.32' S 47°28.45' W 1970 5661 Antarctic Weddell Sea ANT-XXII/3 févr.05 150/7 61°48.32' S 47°28.45' W 1970 5662 Antarctic Weddell Sea ANT-XXII/3 févr.05 150/7 61°48.32' S 47°28.45' W 1970 5709 Arctic Yermak Plateau ARKXXI/1b août.05 317 81°6,00' N 8°22,09' E 1149 5713 Antarctic Weddell Sea ANT-XXII/3 févr.05 150/7 61°48.32' S 47°28.45' W 1970 5715 Arctic AWI Hausgarten ARKXXI/1b août.05 274 78°46,83' N 5°19,95' E 2467 5716 Arctic AWI Hausgarten ARKXXI/1b août.05 274 78°46,83' N 5°19,95' E 2467 5717 Arctic AWI Hausgarten ARKXXI/1b août.05 274 78°46,83' N 5°19,95' E 2467 5727 Arctic AWI Hausgarten ARKXXI/1b août.05 276 79°7,81' N 4°54,13' E 1548 5729 Arctic AWI Hausgarten ARKXXI/1b août.05 276 79°7,81' N 4°54,13' E 1548 5730 Arctic Yermak Plateau ARKXXI/1b août.05 320 81°5,99' N 8°8,53' E 1106 5834 Antarctic Weddell Sea ANT-XXII/3 févr.05 150/7 61°48.32' S 47°28.45' W 1970 C184 Atlantic Setubal Canyon 64PE218 oct.03 20 38°12.02' N 9°31.71' W 2774

Table G3. Isolates of Oridorsalis umbonatus with description of sampling sites

DNA Depth area locality cruise date station latitude longitude # (m) 5149 Antarctic Weddell Sea ANT-XXII/3 févr.05 78/8 71°9,48' S 14° 0,12' W 2167 5156 Antarctic Weddell Sea ANT-XXII/3 févr.05 80/5 70°39,40' S 14° 43,47' W 3086 5164 Antarctic Weddell Sea ANT-XXII/3 févr.05 81/4 70°31,49' S 14° 34,95' W 4407 5404 Arctic AWI Hausgarten ARKXXI/1b août.05 238 79°3,91' N 4° 10,81' E 2462 5410 Arctic AWI Hausgarten ARKXXI/1b août.05 238 79°3,91' N 4° 10,81' E 2462 5454 Arctic AWI Hausgarten ARKXXI/1b août.05 261 79°3,80' N 3° 39,48' E 3127 5462 Arctic AWI Hausgarten ARKXXI/1b août.05 251 79°16,98' N 4° 19,65' E 2400 5485 Arctic AWI Hausgarten ARKXXI/1b août.05 276 79°7,81' N 4° 54,13' E 1548 5612 Arctic Greenland Sea ARKXXI/1b août.05 367 78°49,96' N 17° 28,83' W 572 5705 Arctic Greenland Sea ARKXXI/1b août.05 367 78°49,96' N 17° 28,83' W 572 5707 Arctic Greenland Sea ARKXXI/1b août.05 367 78°49,96' N 17° 28,83' W 572 5708 Arctic Greenland Sea ARKXXI/1b août.05 367 78°49,96' N 17° 28,83' W 572 5721 Arctic AWI Hausgarten ARKXXI/1b août.05 276 79°7,81' N 4° 54,13' E 1548 5722 Arctic AWI Hausgarten ARKXXI/1b août.05 276 79°7,81' N 4° 54,13' E 1548 5723 Arctic AWI Hausgarten ARKXXI/1b août.05 276 79°7,81' N 4° 54,13' E 1548 5832 Antarctic Weddell Sea ANT-XXII/3 févr.05 80/8 70°39,40' S 14° 43,47' W 3086

242 Appendix H

Supplementary Material of: Global genetic homogeneity in the deep-sea foraminifera Epistominella exigua (Rotaliida: Pseudoparrellidae).

Table H1. List of ITS DNA extractions indicating clones sequenced and their accession number in GenBank, sampling station, depth and location.

Clones (GenBank DNA Depth Coordinates Station access number)

-12 (EF653496) -14 (EF653497) P6928 N33°51’26 -16 (EF653498) 1905 m PC12 E. exigua -17 (EF653499) E136°29’96 -19 (EF653500) -28 (EF653501) -22 (EF653503) -23 (EF653504) P6929 N33°51’26 PC12 -24 (EF653505) 1905 m E. exigua E136°29’96 -29 (EF653506) -30 (EF653507) -31 (EF653508) P7156 N33°49’00 PC10 -34 (EF653509) 1990 m E. exigua E137°08’70 -35 (EF653510)

P7180 N33°51’26 -41 (EF653511) 1905 m PC12 E. exigua -45 (EF653514) E136°29’96

P7165 N33°49’00 -61 (EF653515) 1990 m PC10 E. exigua -63 (EF653516) E137°08’70

-71 (EF653518) P7166 N33°51’26 -72 (EF653519) 1905 m PC12 E. exigua -73 (EF653520) E136°29’96 -75 (EF653521)

243

Table H2. List of SSU rDNA extractions indicating clones sequenced and their accession number in GenBank, sampling station, depth and location.

Clones (GenBank DNA Depth Coordinates Station access number)

P6928 -11 (FJ185806) 1905 m N33°51’26 PC12 E. exigua -15 (FJ185804) E136°29’96

P6929 -21 (FJ185805) 1905 m N33°51’26 PC12 E. exigua -22 (FJ185803) E136°29’96

P7180 -11 (FJ185798) 1905 m N33°51’26 PC12 E. exigua -12 (FJ185797) E136°29’96

P7565 -21 (FJ185801) 1990 m N33°49’00 PC10 E. exigua -22 (FJ185802) E137°08’70

P7566 -31 (FJ185800) 1905 m N33°51’26 PC12 E. exigua -33 (FJ185799) E136°29’96 KG8043 S62°09’29 -22 (FJ185825) 100 m KG14 E. vitrea W58°29’43 -24 (FJ185822) KG8250 40 m S62°11’05 KG19 -26 (FJ185824) E. vitrea W58°23’00 -27 (FJ185823) -11 (FJ185793) WED5232 2609 m S63°40’99 121/4 -12 (FJ185794) E. arctica W50°44’29 -18 (FJ185795) ARK5521 N78°55’05 -34 (FJ185796) 2633 m 273 E. arctica E5°0’13 KG7890 S62°09’58 -3 (FJ185807) 107 m KG10 E. sp1 W58°34’28

-7 (FJ185808) KG7994 -8 (FJ185809) 108 m S 62°09’46 KG13 E. sp1 -9 (FJ185811) W58°29’73 -10 (FJ185810) KG8042 S62°09’29 -18 (FJ185812) 100 m KG14 E. sp1 W58°29’43 -12 (FJ185813) KG8042 100 m S62°09’29 KG14 -15 (FJ185815) E. sp2 W58°29’43 -16 (FJ185814) -1 (FJ185817) USH7639 -2 (FJ185816) 20 m S54°51’50 4 E. sp2 -5 (FJ185818) W68°27’00 -4 (FJ185819) -52 (FJ185820) P6937 1110 m N34°11’97 MC16 E. sp3 -55 (FJ185821) E137°45’73

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