Patrice L'

Invitation au voyage Mon enfant, ma soeur, Songe à la douceur D'aller là-bas vivre ensemble ! Aimer à loisir, Aimer et mourir Au pays qui te ressemble ! Les soleils mouillés De ces ciels brouillés Pour mon esprit ont les charmes Si mystérieux De tes traîtres yeux,

RESUME

Les récifs artificiels sont des structures immergées posées délibérément sur le fond marin pour imiter certaines caractéristiques d'un habitat naturel, ils sont utilisés depuis des milliers d'années par les hommes dans le but d'améliorer leurs pratiques de pêches et depuis peu ils sont également employés pour la protection voire la restauration de certains habitats marins. Malgré ces divers objectifs, il réside encore un manque de fondements scientifiques pour déterminer la qualité de ces structures mises à l'eau afin d'en évaluer leur efficacité. Les présent travaux, focalisés sur l'étude de leurs caractéristiques intrinsèques, à savoir leurs matériaux et leurs structures Un suivi conjugué du biofilm et du macrofouling sur différents matériaux, complété par une analyse de leur contenu en métaux lourds a permis de mettre en évidence la qualité de certains matériaux utilisé pour la construction de récifs artificiel. Le suivi simple du biofilm s'est révélé être un bon indicateur pour mettre en valeur ces différences de façon simple et rapide pour valider l'utilisation de tel ou tel matériau.

Par ailleurs, la mise au point d'une méthode destinée à évaluer la complexité et l'hétérogénéité des récifs artificiels a permis de donner une classification pertinente des différentes structures existantes. Cette méthode standardisée permettra d'évaluer in situ l'influence des paramètres structuraux des récifs artificiels sur le recrutement, l'abondance, la distribution et/ou la diversité. Une première étude à l'échelle microscopique a permis de révéler l'influence de la structure du matériau à la fois sur l'abondance du biofilm et sur l'activité photosynthétique de ces communautés.

L'ensemble de ces résultats permet d'offrir un cadre scientifique plus précis pour aborder la construction des récifs artificiels sur le choix de leurs matériaux et de leurs designs.

De futures lignes directrices pourraient être émises afin d'optimiser l'efficacité de tout projet d'immersion de récifs artificiels.

Mots-clés : Récif artificiels, colonisation des récifs artificiels, matériaux des récifs artificiels, structure des récifs artificiels, biofilm, macrofouling, substances polymériques extracellulaires, métagénomique, chromatographie en phase liquide, contamination en métaux lourds, Imaging Pam, modèle numérique 3D CAD, Complexité, hétérogénéité ABSTRACT Artificial reefs are submerged structures deliberately placed on the seabed to mimic some characteristics of a natural habitat, they have been used for thousands of years by fishermen to improve their fishing practices and recently they are also used for the protection or even the restoration of certain marine habitats. Despite these various objectives, there is still a lack of scientific fundaments for determining the quality of these submerged structures in order to assess their effectiveness. The present works, focused on the study of their intrinsic characteristics, namely their materials and their structures.

A combined monitoring of the biofilm and the macrofouling on different substrates, supplemented by an analysis of their heavy metal content allowed to highlight the quality of certain substrates used for the construction of artificial reefs. Simple monitoring of the biofilm has proven to be an efficient indicator for highlighting these differences to validate the use of a particular substrate.

In addition, the development of a method to assess the complexity and heterogeneity of artificial reefs has enabled us to give a relevant classification of the various existing structures. This standardized method will allow to assess in situ the influence of structural parameters of artificial reefs on recruitment, abundance, distribution and/or diversity. A first study at the microscopic scale revealed the influence of substrate structure on both the abundance of biofilm and the photosynthetic activity of these communities.

A more precise scientific framework is now available to guide the construction of artificial reefs on the choice of materials and the design of artificial reef structures in order to optimize the effectiveness of artificial reef immersion project. Keywords: Artificial reefs, colonisation of artificial reefs, artificial reef substrates, biofouling, , artificial reef structure, biofilm, macrofouling, extracellular polymeric substances, metagenomic, Hight performance liquid chromatography, heavy metals contamination, Imaging Pam, 3D CAD model, complexity, Heterogeneity.

AVANT-PROPOS

En 2010, la Société Boskalis, société néerlandaise d'assistance maritime aux travaux offshore spécialisée dans les travaux de dragage, travaille sur un projet d'implantation de récifs coralliens en Jamaïque. Madame Astrid KRAMER, ingénieur environnement, lance une étude sur les récifs artificiels et découvre un article présentant un inventeur italien, Monsieur Enrico DINI, Président de la Société Dini Engineering et concepteur d'une imprimante 3D qu'il utilise pour créer des récifs artificiels avec du sable. L'idée lui vient de réaliser des récifs avec du sable de dragage, un produit naturel plus adapté que le béton habituellement utilisé. Son projet remporte en 2014 le « Challenge de l'innovation » qui permet aux collaborateurs de la Société Boskalis de présenter des idées innovantes.

CLAUDE LORRAIN : MATIN DANS LE PORT (II) -1640S -CONSERVE AU MUSEE DE L'HERMITAGE A SAINT PETERSBOURG

REMERCIEMENTS

L'aventure de cette thèse est une conjugaison de belles rencontres, d'émotions fortes et d'une solidarité sans relâche avec l'ensemble des personnes qui ont parcouru ce chemin à mes côtés de loin ou de près. J'ai eu la chance de pouvoir changer d'atmosphère dans les deux coins les plus extrêmes de la France : Nice-Concarneau = 875 km à vol d'oiseau. Malgré la variété des modes de transport en commun et d'escales que j'ai pu tester, je n'ai toujours pas trouvé le moyen de traverser la France en moins de 8h. Mais le voyage en valait la peine. J'ai pu apprécier la sympathie des bretons, la danse gracieuse des phoques dans les laminaires, les paysages lunaires des fonds granitiques, l'eau glaciale et vivifiante de l'Atlantique (ton astuce des cailloux réchauffés avant la marée montante, je n'y crois pas Cédric !), le caramel au beurre salé, les crêpes de chez Masson et les maisons aux atmosphère étranges… Merci à Franck et Marie de m'avoir sauvée des griffes de la sorcière de Concarneau ! Comme il est de coutume, je m'essaie à l'exercice des remerciements en sachant qu'il est inévitable que j'oublie certain(e)s d'entre vous. Au-delà de la coutume, ces remerciements sont des plus sincères car sans votre soutien à tous je ne serais pas en train d'écrire ces dernières lignes qui clôturent l'écriture de mon manuscrit.

Je voudrais tout d'abord remercier Patrice Francour qui de son vivant et après son départ m'a portée pour devenir la chercheuse que je suis aujourd'hui. Depuis les années de licence, c'est à travers ses cours que mon parcours jusqu'à la thèse s'est dessiné. Son aura, qui se passe de parole, a toujours suscité en moi un profond respect à son égard. Ses encouragements m'ont poussée à partir à Paris pour poursuivre mes études au MNHN où j'ai rencontré Cédric Hubas, mon co-directeur. Durant ces trois années passées aux côtés de Patrice, j'ai pu développer mon esprit scientifique, engager des collaborations, construire des projets. En l'observant sous l'eau, j'ai appris à être plus économe, plus observatrice, à gagner en confiance tout en restant vigilante, à trouver des solutions méthodologiques dans ce milieu particulier qui restreint bien souvent les possibilités. Ses gestes calmes et précis m'ont toujours apaisée, la mer était son milieu. J'aime l'idée d'imaginer Patrice dans le grand bleu, entouré d'un cortège de mérous près de la Gabinière, savourant paisiblement son souffle éternel. Il reste près de moi à travers ce travail. Je sais que notre amour commun pour la Méditerranée me liera à lui pour toujours.

Mes pensées se tournent évidemment vers Jacqueline Gautier-Debernardi, sa compagne et mon amie. J'admire ta force de caractère et ta détermination pour continuer.

Sans toi, toute cette aventure n'existerait pas, sans toi il n'y aurait pas ce brin de folie pour décoincer nos esprits un peu trop rigides de scientifiques. Malgré la tempête, tu continues à être enthousiaste et curieuse, tu gardes ton beau sourire et ton sens de l'humour. C'est cette belle étincelle qui ne faiblit jamais qui a sûrement séduit ta saupe. Je suis si heureuse de pouvoir continuer à travailler à tes côtés pour poursuivre tout ce que nous avons mis en place ensemble avec Patrice. Je te remercie également pour ton aide dans cette dernière ligne droite, sans toi la qualité de ce manuscrit serait largement réduite. Je t'embrasse avec mes milliers de ventouses de Poulpinette.

Malgré la distance de 875 km à vol d'oiseau qui nous sépare, le soutien de mon codirecteur, a été sans relâche. Cédric, je te remercie pour ton écoute et pour tes mots qui ont toujours su me ramener à l'essentiel tout en considérant mes difficultés. Je te remercie pour ta confiance lorsque je t'ai proposé le sujet du stage de Master 2. Merci d'avoir cédé à mon obsession de la microtopographie du matériau en trouvant des moyens de tester cette hypothèse à travers le projet LIMIT. Merci pour ton accueil à Concarneau et pour ce jogging sur le sentier des douaniers que j'ai pris comme une épreuve symbolisant le chemin vers la soumission du manuscrit. Le parcours a été rude, mais j'ai enfin réussi toutes les étapes tel un padawan à tes côtés ! J'espère que notre collaboration se poursuivra au-delà de la thèse, car j'aime beaucoup travailler avec toi. J'admire la rigueur et l'intégrité de ta démarche scientifique, teintée d'un désir de créer des liens avec diverses disciplines. Avec toi, le champ des possibles semble toujours pouvoir s'élargir.

Merci à tous mes collègues d'ECOSEAS, votre bienveillance dans le contexte particulier de ma fin de thèse m'a apporté beaucoup de courage et de joie. Merci à Paolo pour ton soutien à la fin de mon parcours, tes mots envers Patrice m'ont tant touchée. Merci à ceux qui m'ont prêté main forte lors de mes périodes de terrain (je pense à Virginie, Marie-Jeanne, Jean-Michel en particulier). Merci à Natacha qui a rendu toutes mes tâches administratives plus fluides, merci pour ton écoute et ta gentillesse. Merci à Martina pour tes fous rires et tes pièces de théâtre improvisées, tu vas nous manquer ! Merci à Benoît pour toutes tes initiatives ''écoterroristes'', ton dynamisme est un vrai moteur dans le labo. Merci également pour le 38 rue André Theuriet, un vrai petit nid douillet ! Merci à Francesca pour ta confiance pour poursuivre ensemble le projet de recherche sur les récifs artificiels initié avec Patrice. Merci à Claudia, Emna, Sylvaine, Patricia, Elena, Margalida, Alexis, Eugenio, Alexandre, Antonio & Antonio, votre présence a rendu cette expérience bien plus amusante. Mes poulettes et ma cocotte, sans vous au labo, c'est un peu moins rigolo, (heureusement le copain marseillais est encore là, Marseille en force !!!!), mais je sais qu'au-delà des distances notre amitié reste forte.

Merci pour votre douceur, votre écoute et vos rires.

Special Thanks to Elena, the thesis gave me the gift to meet you. Together in the same storm we encourage each other to accomplish all the baby steps that lead us to the creation of our fantastic little lizard. You have been the closest to me even if you were so far away.

Merci à mes collègues de BOREA avec qui j'ai partagé de beaux moments au labo et sur Paris. Votre accueil a toujours été des plus chaleureux. Je pense plus particulièrement à Dominique qui a beaucoup participé à l'élaboration de mon projet de thèse depuis le Master 2. Merci pour ta douceur et ta compréhension. Merci à Tarik pour tes dattes, tes jujubes et tes paroles ensoleillées lorsque je venais vous rendre visite. Merci à Najet pour ton accueil, ton franc-parler, heureusement que tu étais là pour veiller sur moi lorsque j'étais all by myself dans le labo. Merci à Guillaume, Sylvia et Franck pour les échanges toujours intéressants que nous avons eus lorsque nous nous sommes retrouvés.

Merci à mes stagiaires.

À Thomas Gutierrez qui n'était pas loin de ressembler à un lapin atteint de myxomatose à la suite des séances d'identification. J'admire ton abnégation à vouloir identifier le turf, ton travail a été de qualité, je te remercie mille fois. À Axel Munerol, pour avoir réalisé mon rêve de l'étude de la microtopographie et de son influence sur les communautés de biofilm. Merci pour tout ce travail de fourmi sur le repositionnement des patchs. À Emma Faveau, qui a amorcé les premières digestions et analyses des contenus en métaux lourds dans les pièges à sédiments.

Merci à l'équipe de Thierry Virolle, de l'IBV, sans qui je n'aurais pas pu conserver mes centaines d'échantillons, et qui a mis à ma disposition tout le matériel nécessaire afin que je puisse appliquer certains de mes protocoles sur le biofilm.

Merci à Stéphane Jamme et Jérôme Espla d'avoir immortalisé des scènes insolites de ma vie subaquatique en compagnie de mes collègues et de Patrice.

Maman, je pense que lorsque tu m'apprenais à dessiner des maisons selon la perspective, tu m'as inoculé une vision tridimensionnelle qui a sûrement eu une influence majeure sur ma façon d'aborder la complexité de la structure des habitats. Ta voix d'architecte devait me parlait tout bas pour orienter ma manière d'aborder mon sujet de thèse. Merci pour ton écoute quand ça n'allait pas, merci d'avoir toujours été là pour m'aider dans les étapes charnières de ma vie.

Papa, quand tu m'as mis pour la première fois un masque et un tuba sur la tête et des petites palmes aux pieds, tu ne te doutais pas que ce premier baptême dans les eaux claires de la lagune de Gaou allait déterminer la passion qui m'a menée jusqu'à ce projet de thèse. C'est en vous suivant, toi et Frédéric, à l'Estagnol, à Hyères, à Sète, dans tous les coins que tu connaissais, que mon amour pour la Méditerranée a grandi. Merci de m'avoir appris à lire et à comprendre la nature à tes côtés.

Merci à vous deux d'avoir cru en moi et de m'avoir donné la possibilité de m'engager même tardivement dans cette voie scientifique.

Mon frère, ton influence sur mon parcours est incontestable, je ne serais jamais allée si loin sans toi. Tu m'as entraînée dans ta soif de connaissance et ton besoin de comprendre le vivant, l'humain, les étoiles, la terre. Tout sujet que tu abordes est pour toi une source inépuisable de questions et un terrain de jeu pour ton esprit analytique et créatif. J'admire l'intelligence et la sensibilité de ton esprit. Ton soutien dans mes phases de doute a toujours su me ramener à celle que je suis, car tu me connais mieux que personne. Merci Piquick.

Merci au plus méchant des méchants qui depuis des années me supporte et me pousse à persévérer dans cette voie malgré les sacrifices que cela engage sur notre couple. Je t'ai rencontré sous l'eau, il n'y a pas de signe plus clair pour décrire l'évidence de notre union. La réussite de ce projet te revient aussi. Tu as constamment veillé à ce que je ne "mange pas des pierres", dans mes rêves ton corps a été le cobaye de mes calculs de la dimension fractale et ton brin de folie a su apaiser mes angoisses. Sans toi, je me serais probablement transformée en méchant Gremlins. Ta patience est sans limite. Merci ce Chat.

Alain, tu serais très fier de celle que je suis devenue. Merci d'avoir éveillé en moi le besoin d'aller toujours chercher de nouvelles perspectives.

Merci à Toutoune, tu as toujours cru en moi. Ton attention et ta bienveillance m'ont poussée à poursuivre mes rêves.

Papi Lili et Mamie Odile, de là où vous êtes je vous envoie toute ma reconnaissance et je vous remercie pour les belles valeurs que vous nous avez inculquées.

Merci à Antoine, tu m'as appris le sens de l'abnégation et de la rigueur. Je n'en serais pas là sans ton aide.

Merci à mes caillettes de Marseille, vous avez toujours cru en mes projets, votre soutien m'a toujours été extrêmement précieux. Même si la vie rend nos retrouvailles de plus en plus rares, je vous sens toujours près de moi.

Merci à l'association de Plongée IEMANJA et à Serge Vermillac, mon formateur en plongée loisir. Merci pour ta bienveillance et ta formation de qualité, tu m'as donné la confiance et la vigilance essentielles pour aborder la plongée dans le monde professionnel.

Thanks to the Plan Blue team for the nice moments spent underwater with the hyperspectral camera, and the others to come. <°)))>< <°)))>< <°))))>< <°))>< <°)))>< J'en viens maintenant à adresser des remerciements plus formels à toutes les parties prenantes ainsi qu'à tous ceux qui ont collaboré à ce projet :

Les gestionnaires des aires marines protégées de Roquebrune Cap Martin et de Monaco qui ont facilité mes expérimentations in situ.

Le Conseil d'Administration de l'AMPN sans qui ce projet n'aurait pu voir le jour. Merci pour votre confiance et votre bienveillance à mon égard. Merci d'avoir mis à ma disposition vos moyens à la mer et vos locaux pour conduire mes travaux sur le terrain. Je remercie également les adhérents qui m'ont régulièrement prêté main forte.

La Société Boskalis dont l'implication depuis le début du projet et la générosité ont permis de développer la base de mes travaux de recherche sur le suivi du biofouling en mettant notamment à disposition les multiples échantillons de matériaux nécessaires aux diverses analyses.

Monsieur Enrico Dini, Président de la Société Dini Engineering et concepteur de l'imprimante 3D utilisée pour les récifs immergés en Principauté de Monaco, dont la maîtrise de la technologie de l'impression 3D à grande échelle et la conscience de son intérêt pour créer des récifs artificiels innovants, le conduit aujourd'hui à poursuivre notre collaboration dans le cadre d'un prochain programme de recherche.

Les Sociétés Créocéan et Geolab dont le savoir-faire et la méthodologie en matière de modélisation par photogrammétrie sous-marine m'ont permis de tester ma méthode d'évaluation de la structure de l'habitat sur le milieu naturel, et dont les résultats ont été présentés lors de la 5ème conférence européenne sur la plongée scientifique en avril 2019 à l'Institut d'Océanologie de l'Université des Sciences de Sopot (Pologne).

L'équipe de THALASSA Marine research & Environmental awareness pour leur professionnalisme, leur disponibilité, leur soutien et leur bonne humeur durant tous les suivis mis en place sur le terrain.

Le Gouvernement Princier de Monaco pour avoir permis la réalisation du projet d'immersion des récifs et avoir facilité la mise en oeuvre de mes travaux de recherche.

Les mécènes privés qui, par le soutien apporté aux projets mis en place par l'AMPN depuis la création des aires marines protégées de Monaco, ont permis de mener à bien les différents axes de recherche sur les récifs artificiels.

La Fondation Prince Albert II de Monaco qui est à l'origine du projet d'immersion à Monaco de récifs artificiels réalisés avec une imprimante 3D et s'est engagée dans un programme de financement visant à valoriser les travaux de recherche qui en découlent.

TABLE DES MATIERES TABLE DES TABLES

Table II-1:Composition of the solutions used in the modified LOWRY assay protocol . 57

Table II-2

TABLE DES ILLUSTRATIONS

Historique et définition des récifs artificiels

Les récifs artificiels sont à ce titre utilisés depuis des milliers d'années par les hommes pour améliorer leurs pratiques de pêches. En immergeant des structures, les pêcheurs attirent des espèces présentant un fort intérêt et améliorent ainsi leurs prises. Aux Etats Unis, les premières installations référencées remontent aux années 1830 ; des assemblages de bûches et de pierres avaient été placés dans des bras de mer au sud de la Californie pour remplacer des arbres morts et favoriser la pêche de sparidés [START_REF] Stone | HISTORY OF ARTIFICIAL REEF USE IN THE UNITED STATES[END_REF]. Au Japon, les premières pratiques remontent au XVIIème siècle ; des pêcheurs de l'île d'Awaji, près de Köbe, dans la mer de Seto eurent l'idée de remplacer une vielle épave très productive ̶ délabrée par un typhon ̶ par un assemblage de gabions composé de paniers en bambou remplis de pierres A partir des années 1960, l'immersion de structures artificielles s'est multipliée partout dans le monde selon des initiatives locales, sans suivi ni cadre scientifique. L'usage de matériaux de recyclage (ex : vieux pneus, carcasses de voitures, épaves de bateaux) a progressé sans se soucier des impacts sur l'environnement en termes de pollution [START_REF] Pickering | Artificial Reefs as a Tool to aid Rehabilitation of Coastal Ecosystemes: Investigating the Potential[END_REF][START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF] [START_REF] Jensen | Introduction and Background to artificial Reefs in European Seas[END_REF]. [START_REF] Pickering | Artificial Reefs as a Tool to aid Rehabilitation of Coastal Ecosystemes: Investigating the Potential[END_REF] en dépit des études qui commençaient à montrer leur potentiel impact sur l'environnement [START_REF] Collins | A Review of Waste Tyre Utilisation in the Marine Environment[END_REF]. En effet, les pneus s'avèrent être des vecteurs de bioaccumulation de métaux lourds dans les tissus de certains bivalves (Risso-de Faverney et al. 2010) et une source de pollution des sédiments [START_REF] Taneez | Capping of marine sediments with valuable industrial by-products: Evaluation of inorganic pollutants immobilization[END_REF]. De nos jours, la plupart des structures sont construites en béton, dont la base en ciment est souvent chargée de métaux lourds en raison de l'utilisation de déchets industriels pour la cuisson du clinker [START_REF] Achternbosch | Heavy Metals in Cement and Concrete Resulting from the Co-incineration of Wastes in Cement Kilns with Regard to the Legitimacy of Waste Utilisation[END_REF]. Bien que le béton soit considéré comme un matériau très inerte et conservant bien ses composants face à la lixiviation, sa résistance à la bio-érosion a déjà été remise en cause [START_REF] Javaherdashti | On the impact of algae on accelerating the biodeterioration/biocorrosion of reinforced concrete: A mechanistic review[END_REF]. Par ailleurs, le pH très alcalin (proche de pH 13) de ces matériaux peut également avoir un impact non négligeable sur la physiologie des espèces colonisant ces structures. De la même manière que l'utilisation des pneus, le béton pourrait se révéler être un matériau polluant. Il existe cependant des moyens permettant de limiter la présence de métaux lourds dans la confection des ciments mais aussi de diminuer le pH du béton.

Par ailleurs, l'efficacité des récifs artificiels se focalise principalement sur les assemblages de poissons et de la faune mobile qui représentent les espèces d'intérêt pour la pêche et leur efficience dépend directement du design. Les structures sont conçues selon le jugement d'expert sans méthode standardisée pour évaluer leur design [START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF].

De nombreuses approches de post-complexification de certaines structures sélectionnées selon des dires d'expert ont d'ailleurs été mises en place pour améliorer leur efficacité de production et attirer une plus grande diversité d'espèces [START_REF] Charbonnel | Effet de la complexification de l'architecture des récifs artificiels du Parc national de Port-Cros (Méditerranée, France) sur les peuplements ichtyologiques[END_REF][START_REF] Bodilis | Monitoring of the artificial reef fish assemblages of golfe juan marine protected area (France, North-Western Mediterranean)[END_REF] Actuellement, l'étude de la colonisation des récifs artificiels se focalise principalement sur la faune mobile et rarement sur le biofouling. Au sein de ce dernier compartiment, le biofilm constitue la base du processus de colonisation, mais il est pourtant très rarement étudié dans le cadre des récifs artificiels [START_REF] Salamone | Fungal diversity of marine biofilms on artificial reefs in the northcentral Gulf of Mexico[END_REF][START_REF] Liu | Succession and seasonal variation in epilithic biofilms on artificial reefs in culture waters of the sea cucumber Apostichopus japonicus[END_REF][START_REF] Riera | Biofilm monitoring as a tool to assess the efficiency of artificial reefs as substrates: Toward 3D printed reefs[END_REF]. Il définit pourtant la première forme de vie entrant en interaction avec le récif artificiel une fois immergé, et peut donner des informations sur la structure des communautés et leur physiologie en peu de temps.

Les biofilms sont définis comme des assemblages microbiens adhérant les uns aux autres et se liant à une surface immergée [START_REF] Costerton | Microbial biofilms[END_REF][START_REF] Hall-Stoodley | Bacterial Biofilms: From the Natural Environment to Infectious Diseases[END_REF]). En milieu marin, le biofilm est composé de microbes tels que bactéries, archées, microalgues, champignons microscopiques, flagellés hétérotrophes et ciliés. L'abondance relative de ces taxons varie en fonction des conditions environnementales, mais les diatomées et les cyanobactéries sont les taxons majoritairement représentés [START_REF] Wahl | Marine epibiosis. I. Fouling and antifouling: some basic aspects[END_REF][START_REF] Callow | Biofilms[END_REF][START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF][START_REF] Dang | Microbial Surface Colonization and Biofilm Development in Marine Environments[END_REF] La colonisation ultérieure par le macrofouling est globalement déterminée par l'environnement biologique local, sous l'influence de l'établissement du biofilm [START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF][START_REF] Hamer | The development and settlement of certain marine tubeworm (serpulidae and spirorbidae) larvae in response to biofilms[END_REF][START_REF] Lam | Induction of larval settlement in the polychaete Hydroides elegans by surfaceassociated settlement cues of marine benthic diatoms[END_REF][START_REF] Patel | Specificity in the settlement -modifying response of bacterial biofilms towards zoospores of the marine alga Enteromorpha[END_REF][START_REF] Dahms | The effect of bacterial and diatom biofilms on the settlement of the bryozoan Bugula neritina[END_REF][START_REF] Dobretsov | Facilitation and inhibition of larval attachment of the bryozoan Bugula neritina in association with mono-species and-multi-species biofilms[END_REF][START_REF] Qian | Marine biofilms as mediators of colonization by marine macroorganisms: Implications for antifouling and aquaculture[END_REF][START_REF] Zardus | Microbial Biofilms Facilitate Adhesion in Biofouling Invertebrates[END_REF][START_REF] Bixler | Biofouling: lessons from nature[END_REF][START_REF] Wahl | The second skin : ecological role of epibiotic biofilms on marine organisms[END_REF]. Les algues sont les premières recrutées, s'ensuit une association plus diverse au bout de 6 à 8 semaines composée d'hydroïdes, de polychètes serpulides, de balanes et de mollusques [START_REF] Ardizzone | Prediction of Benthic and Fish Colonization on the Fregene and other Mediterranean Artificial Reefs[END_REF]. L'équilibre de la communauté suit un processus interactif et dynamique régi par les conditions environnementales et la compétition interspécifique de l'assemblage [START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF]) (Figure I-7).

Influence des caractéristiques intrinsèques des récifs artificiels sur la colonisation

De nombreuses études ont mis en avant le rôle du substrat sur le recrutement du biofilm [START_REF] Dang | Bacterial Primary Colonization and Early Succession on Surfaces in Marine Waters as Determined by Amplified rRNA Gene Restriction Analysis and Sequence Analysis of 16S rRNA Genes[END_REF][START_REF] Miller | Using ecological processes to advance artificial reef goals[END_REF][START_REF] Huang | Composition and density of bacterial biofilms determine larval settlement of the polychaete Hydroides elegans[END_REF][START_REF] Jones | Bacterial Community Structure of Biofilms on Artificial Surfaces in an Estuary[END_REF][START_REF] Dang | Cross-Ocean Distribution of Rhodobacterales Bacteria as Primary Surface Colonizers in Temperate Coastal Marine Waters[END_REF][START_REF] Chung | Bacterial community succession and chemical profiles of subtidal biofilms in relation to larval settlement of the polychaete Hydroides elegans[END_REF]) puis du macrofouling [START_REF] Brown | Epifaunal colonization of the Loch Linnhe Artificial Reef : Influence of substratum on epifaunal assemblage structure[END_REF][START_REF] Lakshmi | Influence of surface characteristics on biofouling formed on polymers exposed to coastal sea waters of India[END_REF][START_REF] Myan | The interaction of marine fouling organisms with topography of varied scale and geometry: A review[END_REF][START_REF] Xiao | Cost and time-effective method for multiscale measures of rugosity, fractal dimension, and vector dispersion from coral reef 3D models[END_REF], ainsi que l'influence combinée du biofilm et du substrat sur le recrutement de ces derniers colonisateurs [START_REF] Faimali | The interplay of substrate nature and biofilm formation in regulating Balanus amphitrite Darwin , 1854 larval settlement[END_REF][START_REF] Huggett | Effects of initial surface wettability on biofilm formation and subsequent settlement of Hydroides elegans[END_REF][START_REF] Dobretsov | The effect of surface colour on the formation of marine micro-and macro-fouling communities[END_REF][START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF] Outre les implications que peut avoir la qualité chimique du substrat sur la faune mobile, la structure tridimensionnelle de la texture du substrat jusqu'à la forme globale joue quant à elle un rôle essentiel sur le recrutement de ces espèces [START_REF] Bohnsack | Habitat structure and the design of artificial reefs[END_REF]. En effet, la topographie du substrat peut influencer la diversité et l'abondance du biofouling et indirectement de la faune mobile s'en nourrissant [START_REF] Bohnsack | Artificial reef research: a review with recommendations for the future prorities[END_REF][START_REF] Bohnsack | Are high densities of fishes at artificial reefs the results of habitat limitation or behavioural preference?[END_REF], 1991[START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF][START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF] [START_REF] Macarthur | On Bird Species Diversity[END_REF][START_REF] Macarthur | On Bird Species Diversity II. Prediction of Bird Census from Habitat Measurements[END_REF], McCoy et al. 1991[START_REF] Kovalenko | Habitat complexity: approaches and future directions[END_REF]. En se basant sur la définition proposée par McCoy & Bell (1991), la structure de l'habitat se définit selon trois dimensions :

• La complexité, définie par la forme mesurée selon divers paramètres (quelques exemples des plus utilisés : rugosité, dimension fractale, porosité).

• L'hétérogénéité, définie par l'abondance relative des différentes formes (quelques exemples : indice de Shannon, écart type)

• L'échelle à laquelle les deux précédents paramètres sont étudiés.

Selon ces trois dimensions, il est possible de poser les bases d'une méthode d'évaluation des récifs artificiels depuis l'aspect de leur surface jusqu'à leur arrangement global qui suit un modèle identique de par le monde [START_REF] Bohnsack | Are high densities of fishes at artificial reefs the results of habitat limitation or behavioural preference?[END_REF], Cépralmar 2015[START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF], Charbonnel et al. 2011, Figure 5-1)

• Les modules sont assemblés en agrégat ou récif unitaire ("set" pour les anglophones). La distance entre chaque module peut varier d'une dizaine de centimètres à quelques mètres.

• Un ensemble de récifs unitaires forme un village ("group") dont la distance varie d'une dizaine de mètres à 500 mètres selon la taille des agrégats.

• Enfin, un ensemble de villages forme un champ ("complex") sous-entendu l'étendue globale du projet de déploiement des récifs. La distance entre les villages peut atteindre 3 km.

Ainsi, la complexité peut être évaluée au niveau du module unitaire, l'hétérogénéité au niveau des différents arrangements (agrégat, village, champ) et ces paramètres peuvent faire l'objet d'études à l'échelle globale de la structure ainsi qu'à l'échelle de la surface afin de donner une base d'évaluation à toutes les échelles possibles.

Abstract

Habitat destruction is one of the main causes of the decline of biodiversity and of fishery resources in the marine environment. An artificial reef (AR) could be a tool for protecting or restoring these habitats and their declining biodiversity, and also help to enhance sustainable fisheries. The goal is to design non-polluting structures that best mimic the complexity of natural habitats in order to improve their service to the community. To date, the assessment of reef performance has been mostly focused on fish assemblages and species of ecological and/or socio-economic interest, and has disregarded the biofilm communities that determine the first level of an AR's trophic network. In this work, we used biofilm formation to compare the quality of substrates used as building parts for an AR, in order to optimize an eco-friendly material that will be used to design a new generation of ARs produced by giant 3D printers. The structure of the photosynthetic communities has been identified using pigment biomarkers and their production of exudates has been analysed. These polymeric substances were quantified in terms of total sugar and protein concentrations. They were further analysed in terms of amino acid content. We found no significant differences between the micro-algae communities developed on different substrates. These photosynthetic communities were mainly composed of diatoms, prasinophytes, haptophytes, and dinoflagellates. However, we showed that the material for ARs is crucial for biofilm development, especially with regard to its secretions of sugar. The choice of an appropriate substrate for AR construction is thus of particular importance since biofilm secretions determine the organic substrate on which sessile macroorganisms will settle.

Keywords: biofilm, bio-indicator, photosynthetic pigments, extracellular polymeric substances, artificial reef substrates.

Introduction

Artificial reefs (ARs) have been defined as "submerged structures placed on the seabed deliberately to mimic some characteristics of natural reefs" (Pickering et al. 1999). The main goal is to protect, regenerate and increase marine resource production, to help measure conservation in the protection and restoration of habitat and to enhance fisheries (UNEP 2009).

The first ARs were made with recycled waste materials, then since the mid-1970s, innovative trends shifted towards purpose-designed reef structures [START_REF] Pickering | Artificial Reefs as a Tool to aid Rehabilitation of Coastal Ecosystemes: Investigating the Potential[END_REF][START_REF] Barnabé | Artificial reef in France : analysis , assessments and prospects[END_REF][START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF]. In the USA, various depolluted waste materials were used, such as wrecks of oil and gas production platforms or charter vessels [START_REF] Pickering | Artificial Reefs as a Tool to aid Rehabilitation of Coastal Ecosystemes: Investigating the Potential[END_REF], while in Europe and Japan since the 1980s, concrete blocks have been virtually exclusively used [START_REF] Pickering | Artificial Reefs as a Tool to aid Rehabilitation of Coastal Ecosystemes: Investigating the Potential[END_REF][START_REF] Barnabé | Artificial reef in France : analysis , assessments and prospects[END_REF][START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF]. In comparison to wrecks, AR design using concrete blocks limits the spatial heterogeneity and cannot mimic the high threedimensional complexity of natural rocky habitats.

To date, the assessment of reef performance has focused mostly on fish assemblages and species of commercial value, and has underestimated the development of epibiosis (or biofouling) [START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF][START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF]. Moreover, material characteristics that affect larval settlement and recruitment have seldom been taken into account [START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF]. ARs are colonized as a consequence of the immersion of vacant hard substratum [START_REF] Wahl | Marine epibiosis. I. Fouling and antifouling: some basic aspects[END_REF][START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF][START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]; holes and structures provide shelter for motile organisms and the surface is colonized ultimately by epibionts. The establishment of epibiosis is a complex process. It follows the same basic pattern of an initial biochemical conditioning film formed by the ambient water chemistry, followed by early colonisers such as bacteria and unicellular eukaryotes which form a matrix biofilm that composes the living substratum necessary for the successive colonisation by multicellular eukaryotes [START_REF] Wahl | Marine epibiosis. I. Fouling and antifouling: some basic aspects[END_REF][START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF][START_REF] Callow | Biofilms[END_REF][START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]). The biofilm is, therefore, a key element in the subsequent colonisation of ARs and the development of their trophic network.

The biofilm is described as a matrix of microbial assemblages bonding with a biological or non-biological immersed surface [START_REF] Costerton | MINIREVIEW Biofilms, the Customized Microniche[END_REF][START_REF] Hall-Stoodley | Bacterial Biofilms: From the Natural Environment to Infectious Diseases[END_REF]). In the marine environment, biofilm is composed of microbes such as bacteria, archaea, microalgae; microscopic fungus, heterotrophic flagellates, and ciliates that previously lived as plankton. The relative abundance of these taxa varies according to environmental conditions, but diatoms and cyanobacteria are those mainly represented [START_REF] Wahl | Marine epibiosis. I. Fouling and antifouling: some basic aspects[END_REF][START_REF] Callow | Biofilms[END_REF][START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]. Absorption and adherence of bacteria to the surface involves physical and chemical interactions and secretion that form the primary film, then unicellular eukaryote settles several days later, dominated by diatoms that are attached to the surface by mucus secretion [START_REF] Wahl | Marine epibiosis. I. Fouling and antifouling: some basic aspects[END_REF]). The unicellular eukaryote and bacterial secretions, called extracellular polymeric substances (EPS), are composed of macromolecules such as polysaccharides, proteins, nucleic acids, lipids and other polymeric substances [START_REF] Flemming | The biofilm matrix[END_REF]. Those EPS constitute a matrix giving a tri-dimensional structure to the biofilm and express a particular phenotype of the microorganisms, giving them better access to nutrients, stronger colonisation capability and greater resistance to the environmental pressure [START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]. The EPS are heterogeneous and vary spatially, chemically and physically within the matrix according to environmental gradients (pH, temperature, oxygen, light, etc.;[START_REF] Costerton | Microbial biofilms[END_REF]. To date, only two studies have focused on characterizing the biofilm community of the ARs [START_REF] Salamone | Fungal diversity of marine biofilms on artificial reefs in the northcentral Gulf of Mexico[END_REF][START_REF] Liu | Succession and seasonal variation in epilithic biofilms on artificial reefs in culture waters of the sea cucumber Apostichopus japonicus[END_REF]), but no investigation dealing with the biochemical characterisation of the biofilm has been undertaken to evaluate the nutritional quality of biofilm exudates that may have a function in ARs' trophic network.

Recently, D-shape (3D giant inkjet printing company for building construction) and Royal Boskalis Westminster N.V (Netherlands-based Company that provides services relating to the construction and maintenance of maritime infrastructure on an international basis) proposed a new way to build ARs using a giant 3D printer and an eco-friendly material, dolomite Sorel cement (84% dolomite sand and 16% magnesium oxide). 3D printing enables the building of more complex artificial structures, closer to the complexity of natural rocky habitat. As part of the evaluation of the quality of this new generation of ARs, and to assess the quality of various kinds of substrate used for ARs, we developed a method to monitor the first stage of biofilm colonisation that constitutes the living substrate for epibiont settlement. A comparative study has been performed on different substrate types: grey concrete (which is commonly immersed in Europe), white concrete (that contains less metallic oxide than grey concrete, [START_REF] Telford | Portland cement : Composition, production and properties, 2nd editio[END_REF][START_REF] Betocib | Les Bétons à base de Ciment Blanc[END_REF], and dolomite Sorel cement (used to build the 3D printed ARs). Samples of these substrates were immersed in the Larvotto marine reserve (Principality of Monaco) over a 35-day period in order to determine the colonisation of biofilm from the early phase to maturation and to identify potential biological and biochemical variations of biofilm composition between the substrates. We hypothesised that the substrate type is likely to induce differences (i) in microbial diversity during the colonisation process and (ii) in the composition of biofilm secretion.

Materials & methods

Sampling and site of monitoring

Biofilm communities were monitored on different substrates for 35 days in the coastal waters of the Larvotto reserve (Monaco: 43.743950°N, 7.434700°E). The reserve is a protected marine area managed by the AMPN (Association Monaco pour la Protection de la Nature).

Samples were retrieved one day after immersion to analyse the initiation phase, and then every week (during 4 weeks) to follow the maturation of communities. However, a storm occurred the third week of monitoring which delayed the sampling by one week. The five sampling dates are thus unevenly distributed, and sampling finally took place 1, 7, 14, 28 and 35 days after immersion. The samples were immersed at 18 m depth, 2 meters above a sandy bottom. They were fixed on 5 different 1m² plastic frames (1 frame for each sampling date), suspended from a 10 liters buoy and anchored by concrete blocks. The depth was selected in order to facilitate monitoring by scuba divers and corresponds to the depth at which ARs are commonly immersed in the French Mediterranean Sea [START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF].

Cobblestones of 5*2*2 cm were cut within large slabs of dolomite Sorel cement (Ds), standard grey concrete (Cg) and white concrete (Cw). Three replicates of each substrate were dedicated for 3 different analyses (Pigment, EPS, and 16S ribosomal DNA analyses) at each sampling time (i.e. 3 replicates x 3 substrates x 3 analyses x 5 times = 135 samples).

Unfortunately, after extraction, the quantity of DNA compared to the PCR inhibitory products was not sufficient to follow the analysis by amplicon sequencing.

Immersion, installation and sampling were done by scuba divers. The retrieval of the plastic frames with the attached cobblestone samples lasts for ca. 2 min from the bottom to the boat. We therefore consider that new irreversible settlement of planktonic microorganisms during the retrieval was very unlikely. Samples were then packed in falcon tubes and immediately frozen with liquid nitrogen. Samples were stored at -80°C before analysis.

Pigment analysis

The photosynthetic communities have been analysed by the quantification of pigments by High Performance Liquid Chromatography (HPLC) according to [START_REF] Brotas | The use of HPLC pigment analysis to study microphytobenthos communities[END_REF].

Pigments were extracted by scraping the biofilm from the substrate using a scalpel and fiber glass filter (GF/F) with 6 mL of 95 % cold buffered MeOH (2 % ammonium acetate) for 4 hours at 4°C, in the dark. Extracts were then filtered (0.2 µm) immediately before HPLC analysis.

Pigment extracts were analysed using an Agilent 1260 Infinity HPLC composed of a quaternary pump (VL 400 bar), a UV-VIS photodiode array detector (DAD 1260 VL, 190 to 950 nm), and a 100 µL sample manual injection loop (overfilled with 250 µL). Chromatographic separation was carried out using a C18 column for reverse phase chromatography (Supelcosil, 25 cm long, 4.6 mm inner diameter). The solvents used were A: 0.5 M ammonium acetate in methanol and water (85:15, v:v), B: acetonitrile and water (90:10, v:v), and C: 100 % ethyl acetate. The solvent gradient followed the Brotas & Plante-Cuny method ( 2003), with a flow rate of 0.5 mL.min -1 .

Identification and calibration of the HPLC peaks were performed with chlorophyll a, ββcarotene, chlorophyll c2, diatoxanthin, diadinoxanthin and fucoxanthin standards. All peaks detected were identified by their absorption spectra and relative retention times using the Open Lab CDS software (ChemStation Edition for LC/MS Systems, Agilent Technologies).

Quantification was performed by repeated injections of standards over a range of dilutions to establish a standard curve of concentrations. The relative abundance of each pigment (%) was calculated from their respective concentrations (µg.cm -2 ).

Extraction of Polymeric substances

Since our samples were frozen before extraction, this could have broken the cell wall, and some cell content would have been released and mixed with extracellular polymeric substances (EPS). Thus, although this input of intracellular material is probably negligible, our chemical analyses may reflect the total polymeric substances (PS).

All samples (i.e. Ds, Cg and Cw cobblestones) were mixed with 2 mL of artificial seawater and 2 g of cation exchange resin (Dowex® Marathon™ C sodium form previously activated in PBS) for 1.5 h with a tube roller (Denley Instruments). Samples were then centrifuged (6030 × g, 10 min) and the supernatants containing the polymers (exo-and intra-) were retrieved (PS fraction: intracellular material with colloid and bond substances from extracellular material).

Previous studies showed that the cation exchange resin method is more efficient than other extraction methods (e.g. with EDTA or NaOH), leading to high PS yields with no apparent cell lysis and no impact on subsequent biochemical analysis (Jachlewski et al. 2015)

Quantification of carbohydrate concentration by colorimetric assay

Carbohydrate analyses were performed following the phenol assay protocol [START_REF] Dubois | Colorimetric method for determination of sugars and related substances[END_REF]). Briefly, 200 µl of the PS fraction were mixed with 200 μl phenol (5 %) and 1 mL sulphuric acid (98 %). Mixtures were then incubated for 35 min at 30 °C and the carbohydrate concentration was measured with a spectrophotometer at 488 nm (Milton Roy Spectronic Genesys 2). A calibration curve was prepared using glucose as standard.

Protein analyses were performed following the modified LOWRY assay protocol [START_REF] Raunkjaer | Measurement of pools of protein, carbohydrate and lipid in domestic wastewater[END_REF][START_REF] Frølund | Extraction of extracellular polymers from activated sludge using a cation exchange resin[END_REF], using five reagents as described in Table II-1.

Table II- 5 Folin with distilled water 5 : 6 (v : v)

Amino acid composition of polymers by HPLC

Amino acids of the PS fraction were identified and quantified by HPLC. PS fractions were dialysed against distilled water (cut-off 12-14 kDa) and freeze-dried. 10 mg were then mixed with 200 µl of HCl (6N). The acid mixture was carefully degassed to reduce the level of oxidative destruction and proteins were then hydrolysed (24 h at 110°C) in vacuum using a sealed glass ampule. Ampules were then dried using a speedvac after hydrolysis. The resulting amino acids were then reconditioned in Pickering diluent prior to injection in the HPLC system. Amino acids were separated by ion-exchange HPLC using a high-efficiency sodium column (4 × 150 mm;

Pickering Lab, LCTech, Dorfen, Germany) with a Waters 2695 separation module (Waters). The elution buffers and gradient conditions were those recommended by the manufacturer (Table II-2).

Table II-2: HPLC solvents for amino acid detection

Separating amino acids were first subjected to post-column derivatization with Ninhydrin (Pickering Lab.) by using a PCX 5200 derivatizer (Pickering Lab.) and later detected on a Waters 2996 Photodiode as a UV module detector at 570 nm for all the amino acids containing a primary amine, and at 440 nm for the Proline which holds a secondary amine.

Quantification was performed by repeated injections of standards over a range of dilutions to determine the relationship between peak area and standard concentrations. The relative abundance of each amino acid (%) was calculated from their respective concentration (µg.cm - 2 ), and protein concentration was calculated from the total amino acid concentration. to identify significant differences between modalities of factors [START_REF] Anderson | A new method for non-parametric multivariate analysis of variance[END_REF]. A Principal Component Analysis (PCA) was applied on pigment concentrations and supplementary variables (sugar and protein concentrations). Pigment concentrations varied between 0.006 µg•cm -2 and 6.647 µg•cm -2 , taking all substrates and times together (Figure II-1). On all substrate samples, it increased drastically after two weeks of immersion . At this time, maximum average concentration was measured on grey concrete (Cg: 6.503 ± 0.054 µg•cm -2 ; Cw: 5.494 ± 0.181 µg.cm -2 ;

Results

Pigment analysis

Ds: 4.630 ± 0.465 µg.cm -2 ). It then remained stable until the end of monitoring for white concrete despite a slight decrease after the storm. However, it decreased dramatically on grey concrete and dolomite Sorel cement after the storm event. In addition, dolomite Sorel cement had a lower concentration than grey and white concrete after the storm event (day 28: Cg:

17.801 ± 1.672 µg.mm-², Ds: 6.333 ± 0.190 µg.mm-², Cw: 15.537 ± 1.479 µg.mm-²). At the end of the monitoring period, concentrations remained constant on grey and white concrete and increased again on dolomite Sorel cement up to a level comparable to the two other substrates.

On average, chlorophyll a, fucoxanthin and chlorophyll c were the major pigments detected (Table II-3). The results of the PERMANOVA revealed significant differences for each factor (time and substrate) and their interaction (2-way PERMANOVA: time: p = 0.001, substrate: p = 0.035, interaction: p = 0.001; Permutation test for homogeneity of multivariate dispersions: p = 0.067). However, pairwise post-hoc test revealed significant differences only between sampling times except between d01 and d07 (Post-hoc pairwise PERMANOVA between sampling time with Bonferroni correction: d01-d07: p = 1, d07-d14, d14-d28: p = 0.01, d28-d35: p = 0.02). During the first week, we only detected fucoxanthin and chlorophyll a on all substrates (Table II-3). After two weeks of immersion, the proportion of chlorophyll a and fucoxanthin decreased due to the detection of chlorophyll c, pheopigments, prasinoxanthin, diadinoxanthin, and a small proportion (<1%) of carotene, hex-fucoxanthin, diatoxanthin, antheraxanthin, zeaxanthin and chlorophyll b. After the storm event (between day 14 and day 28), carotene and chlorophyll b could not be detected anymore, whereas chlorophyll c and prasinoxanthin increased. During the last week of monitoring, chlorophyll b and carotenes were detected anew and chlorophyll c and prasinoxanthin decreased (Table II-3). The ratio of sugar to protein was equivalent between substrates for the two first sampling times (mean of the ratio for the 3 substrates at d01: 4.84 ± 0.13, at d07: 4.68 ± 0.29).

It remained the same on dolomite Sorel cement till the end of the monitoring, while it increased drastically on the two other substrates from the second week of monitoring and then remained stable at high values till the end of the monitoring (Table II-4). Overall, it showed significant differences between dolomite Sorel cement and other substrates (Van-der-Waerden: p = 0.0042, post hoc test: Cg-Ds: p = 0.0022; Cg-Cw: p = 0.9472; Ds-Cw: p = 0.0026)

Amino acid composition

Proportions of amino acids showed significant differences over time but not between substrates (2-way PERMANOVA: time: p = 0.001, substrate: p = 0.078, interaction: p = 0.918;

Permutation test for homogeneity of multivariate dispersions: p = 0.716). Post hoc analyses revealed significant differences before and after the storm event (between d14 and d28, Posthoc pairwise PERMANOVA, Bonferroni correction: p = 0.01). On average, the PS fraction contained amino acids mainly composed of glutamic acid (20.83 ± 0.14 %), aspartic acid (10.25 ± 0.08 %), glycine (11.80 ± 0.09 %), alanine (8.23 ± 0.4 %), proline (7.70 ± 0.21 %) and serine (9.31 ± 0.12 %), 26.18 ± 1.12 % were essential amino acids (Table II Supplementary variables did not show significant correlations with the first two dimensions.

Discussion

The assessment of the quality of total polymeric substances (PS) in conjunction with photosynthetic communities of biofilm on different types of substrates enabled a better understanding of the first step of colonisation of AR, and established the first basis for a protocol to assess the ecological quality of different AR materials. We hypothesised that the substrate type is likely to induce differences (i) in microbial diversity during the colonisation process, and (ii) in the composition of biofilm secretions. The influence of substrate on biofilm attachment and diversity has been extensively investigated and most of the studies revealed significant differences [START_REF] Dexter | Influence of Substrate Wettability on the Attachment of Marine Bacteria to Various Surfaces[END_REF][START_REF] Dexter | Influence of Substratum Critical Surface Tension on Bacterial Adhesion--in[END_REF][START_REF] Fletchert | Influence of Substratum Characteristics on the Attachment of a Marine Pseudomonad to Solid Surfaces[END_REF][START_REF] Fletcher | The Effect of Surface Free Energy and Medium Surface Tension on Bacterial Attachment to Solid Surfaces[END_REF][START_REF] Pringle | Adsorption of Bacterial Surface Polymers to Attachment Substrata[END_REF][START_REF] Fletcher | The settlement , attachment and establishment of marine algal spores[END_REF][START_REF] Cooksey | Adhesion of bacteria and diatoms to surfaces in the sea : a review[END_REF][START_REF] Finlay | The Influence of Surface Wettability on the Adhesion Strength of Settled Spores of the Green Alga Enteromorpha and the Diatom Amphora[END_REF][START_REF] Souza | Seasonal variation in the chemical composition and carbohydrate signature compounds of biofilm[END_REF][START_REF] Patil | Biofilm diatom community structure : Influence of temporal and substratum variability[END_REF][START_REF] Jones | Bacterial Community Structure of Biofilms on Artificial Surfaces in an Estuary[END_REF][START_REF] Sweet | Development of Bacterial Biofilms on Artificial Corals in Comparison to Surface-Associated Microbes of Hard Corals[END_REF][START_REF] Lakshmi | Influence of surface characteristics on biofouling formed on polymers exposed to coastal sea waters of India[END_REF][START_REF] Ozkan | Biointerfaces Cell to substratum and cell to cell interactions of microalgae[END_REF][START_REF] Tan | Differences in Intertidal Microbial Assemblages on Urban Structures and Natural Rocky Reef[END_REF]. In this study, diversity, abundance and secretion were significantly different according to sampling time, but only sugar secretion showed significant differences between substrates.

The biofilm on each substrate became mature after two weeks of monitoring, as shown by the high concentration and diversity of pigments, and the sugar to protein ratio that reached a stable value. Previous studies showed that the maturity of biofilm influences the settlement of various larvae of Mytillus galloprovencialis [START_REF] Bao | Larval settlement and metamorphosis of the mussel Mytilus galloprovincialis in response to biofilms[END_REF], Hydroides elegans [START_REF] Huang | Composition and density of bacterial biofilms determine larval settlement of the polychaete Hydroides elegans[END_REF][START_REF] Chung | Bacterial community succession and chemical profiles of subtidal biofilms in relation to larval settlement of the polychaete Hydroides elegans[END_REF]), Enteromorpha sp. [START_REF] Dillon | Adhesion of Enteromorpha Swarmers to Microbial Films[END_REF]), Balanus amphirite [START_REF] Faimali | The interplay of substrate nature and biofilm formation in regulating Balanus amphitrite Darwin , 1854 larval settlement[END_REF]) and Bugula neritina [START_REF] Dahms | The effect of bacterial and diatom biofilms on the settlement of the bryozoan Bugula neritina[END_REF]) according to diversity, density and secretion of PS.

The overall pattern of changes of the communities is well illustrated by the two first axes of the PCA performed on pigment variables. The first axis represented the diversity of these biofilm communities over time, where communities of the first week (d01 and d07) were related to chlorophyll a and fucoxanthin, and the other sampling times to chlorophyll c and all the minor pigments and supplementary variables (sugar and protein concentrations). The second axis represented the split due to the storm event that eroded the biofilm, with samples at d14 characterised by the presence of the less abundant pigments (chlorophyll b, diatoxanthin, zeaxanthin and carotene), contrasting with samples at d28 characterised by the loss of rare pigments and the increase of prasinoxanthin, antheraxanthin, chlorophyll c, hexfucoxanthin and diadinoxanthin. At the end of monitoring, the communities are more scattered and recovered slowly to reach the initial state (d14). The loss of zeaxanthin, carotene and chlorophyll b might be due to the limitations of HPLC detection. The concentrations of these pigments were very low before the storm and could be undetectable after it. Thus, this loss is not to be considered as a variation in terms of diversity of the pigment composition of communities, but rather as a variation in terms of proportion of the different pigments.

Consistent with the presence of the three types of chlorophyll (a, b and c), the communities were composed of green and brown algae, and perhaps of photosynthetic bacteria (cyanobacteria including prochlorophytes, [START_REF] Jeffrey | Microalgal classes and their signature pigments[END_REF]. According to the proportions of fucoxanthin, chlorophyll c, diadinoxanthin and diatoxanthin, brown algae were dominant. Diatoms should be the main taxon represented, since fucoxanthin can represent up to 60% of their pigment content [START_REF] Strain | Xanthophylls and Carotenes of Diatoms, Brown Algae, Dinoflagellates, and Sea-Anemones[END_REF]. It is known that Raphids diatoms generally represent the main taxa of marine biofilm (78%; [START_REF] Wahl | Marine epibiosis. I. Fouling and antifouling: some basic aspects[END_REF][START_REF] Callow | Biofilms[END_REF][START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]. The presence of hex-fucoxanthin may reveal the specific presence of benthic haptophytes of the Coccolithophyceae class [START_REF] Jeffrey | Microalgal classes and their signature pigments[END_REF], although this was not documented in the biofilm community. The association of antheraxanthin and prasinoxanthin may reveal the presence of prasinophytes among the green algae [START_REF] Egeland | Carotenoids from Further Prasinophytes[END_REF][START_REF] Jeffrey | Microalgal classes and their signature pigments[END_REF]. Finally, endosymbiotic dinoflagellates with pigments of haptophyte, diatoms and prasinophytes origin, can also occur [START_REF] Jeffrey | Microalgal classes and their signature pigments[END_REF]. Dinoflagellates and green flagellates (like prasinophytes) are known to each represent 1% of the biofilm communities [START_REF] Wahl | Marine epibiosis. I. Fouling and antifouling: some basic aspects[END_REF][START_REF] Callow | Biofilms[END_REF][START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]. The increase of diadinoxanthin, hex-fucoxanthin and prasinoxanthin after the storm might reveal a shift in the community toward the increase of flagellate organisms (dinoflagellates, coccolithophores and prasinophytes), perhaps coming from the water column after the storm, since those flagellate organisms are planktonic [START_REF] Jeffrey | Microalgal classes and their signature pigments[END_REF]. Besides, the increase of sugar concentrations on grey concrete and white concrete might also reveal the increasing activity of diatoms. Diatoms, previously identified as the main taxa of the community, secrete a mucilage rich in polysaccharides to adhere to substrates [START_REF] Hamer | The development and settlement of certain marine tubeworm (serpulidae and spirorbidae) larvae in response to biofilms[END_REF][START_REF] Myklestad | Rate of release of extracellular amino acids and carbohydrates from the marine diatom Chaetoceros affinis[END_REF][START_REF] Hoaglang | Diatom Extracellular Polymeric Substances: Function, Fine structure, Chemistry, and Physiology[END_REF][START_REF] Underwood | The Importance of Extracellular Carbohydrate Production by Marine Epipelic Diatoms[END_REF][START_REF] Stal | Structure and Dynamics of Exopolymers in an Intertidal Diatom Biofilm[END_REF][START_REF] Bruckner | Bacteria associated with benthic diatoms from Lake Constance: Phylogeny and influences on diatom growth and secretion of extracellular polymeric substances[END_REF]. Pigment concentrations, mainly related to fucoxanthin produced by diatoms, strongly increased on all substrates from d14, thus the dynamic of sugar secretions appeared not to be synchronous with their settlement on these different substrates. Previous culture studies have shown that benthic diatom cells produce higher concentrations and greater proportions of extracellular carbohydrates when cells enter the transition from exponential growth to stationary phase [START_REF] Sutherland | The effect of carbohydrate production by the diatom Nitzschia curvilineata on the erodibility of sediment[END_REF][START_REF] Underwood | Predicting Epipelic Diatom Exopolymer Concentrations in Intertidal Sediments from Sediment Chlorophyll[END_REF][START_REF] Staats | Isolation and characterization of extracellular polysaccharides from the epipelic diatoms Cylindrotheca closterium and Navicula salinarum[END_REF][START_REF] Underwood | The Importance of Extracellular Carbohydrate Production by Marine Epipelic Diatoms[END_REF]. It might be possible that diatoms settled on grey concrete and white concrete start their stationary phase after the 14 th day of monitoring, whereas they continue to grow on dolomite Sorel cement. These differences in secretion of PS between substrates might also be due to differences in diatom species composition. Culture studies showed that species composition can affect the amount of PS secreted, some species having significantly higher rates of PS production than others under the same conditions [START_REF] Smith | The production of extracellular carbohydrates by estaurine benthic diatoms: The effects of growth phase and light and dark treatment[END_REF][START_REF] Brouwer | Physical characterization and diel dynamics of different fractions of extracellular polysaccharides in an axenic culture of a benthic diatom[END_REF][START_REF] Underwood | The Importance of Extracellular Carbohydrate Production by Marine Epipelic Diatoms[END_REF]. Although HPLC detection of pigments could not identify differences in terms of diatoms diversity, our results are consistent with previous studies that showed that substratum type can influence the diversity of the diatom community and of their PS secretion [START_REF] Cooksey | Adhesion of bacteria and diatoms to surfaces in the sea : a review[END_REF][START_REF] Finlay | The Influence of Surface Wettability on the Adhesion Strength of Settled Spores of the Green Alga Enteromorpha and the Diatom Amphora[END_REF][START_REF] Patil | Biofilm diatom community structure : Influence of temporal and substratum variability[END_REF][START_REF] Chung | Bacterial community succession and chemical profiles of subtidal biofilms in relation to larval settlement of the polychaete Hydroides elegans[END_REF][START_REF] Ozkan | Biointerfaces Cell to substratum and cell to cell interactions of microalgae[END_REF]. Diatoms represent a large part of the feeding resources and they are often associated with the post-larval dietary requirement for suspension feeders [START_REF] Lam | Induction of larval settlement in the polychaete Hydroides elegans by surfaceassociated settlement cues of marine benthic diatoms[END_REF] or grazing juvenile invertebrates, such as gastropods [START_REF] Slattery | Larval settlement and juvenile survival in the red abalone (Haliotis rufescens), an examination of inductive cues and substrate selection[END_REF][START_REF] Bryan | Induction of larval attachment and metamorphosis in the abalone Haliotis diversicolor (Reeve)[END_REF][START_REF] Siqueiros-Beltrones D A | Grazing Selectivity of Red Abalone Haliotis rufescens Postlarvae on Benthic Diatom Films under Culture Conditions[END_REF][START_REF] Dahms | The effect of bacterial and diatom biofilms on the settlement of the bryozoan Bugula neritina[END_REF][START_REF] Beltrones | Benthic Diatom Assemblages in an Abalone (Haliotis spp.) Habitat in the Baja California Peninsula[END_REF], sea urchins [START_REF] Rahim | Larval metamorphosis of the sea urchins, Pseudocentrotus depressus and Anthocidaris crassispina in response to microbial films[END_REF]) and sea cucumbers [START_REF] Ito | Induction of larval metamorphosis in the sea cucumber Stichopus japonicus by periphitic diatoms[END_REF]. Thereby, the significant differences in sugar concentration on dolomite Sorel Cement compared to the other substrates might have a negative impact on the feeding resources of suspension feeders and grazing invertebrates.

To the best of our knowledge, analyses of global amino acids in in situ biofilm development are rare. [START_REF] Bhosle | Amino acids in biofilm material on aluminium panels immersed in marine waters[END_REF][START_REF] Brown | Epifaunal colonization of the Loch Linnhe Artificial Reef : Influence of substratum on epifaunal assemblage structure[END_REF] monitored the amino acid composition of biofilms on aluminium panels in an Indian tropical bay, focusing on the contribution of the major sources of organic matter in the biofilm chemical composition. They observed that the distribution of individual amino acids did not vary in time, and was very similar to that observed in the two main sources of organic matter, and was dominated by aspartic acid, glycine, alanine, serine, leucine, lysine and glutamic acid. In our study, the amino acid composition of the biofilms was dominated by glutamic acid, glycine, aspartic acid, proline, alanine and serine. This composition could stem from the sinking organic matter of marine snow and/or from the microbial community itself that produces protein. But it is generally difficult to distinguish differences between proteins produced by different taxa on the basis of their amino acid composition. The amino acid composition of the proteins is highly conserved among different species, even those performing specific functions. For instance, it has been shown that 16 microalgae species exhibited minor differences in the amino acid composition of their hydrolysates [START_REF] Brown | The amino-acid and sugar composition of 16 species of microalgae used in mariculture[END_REF]. Aspartic acid and glutamic acid are generally found at the highest concentrations, while cysteine, methionine, tryptophan, histidine and proline are found at the lowest concentrations. Therefore, it would be spurious to estimate biofilm diversity on the basis of their amino acid composition. However, the high degree of conservation in amino acid composition among species exudates makes it an interesting biomarker to monitor changes in biofilm functioning. Amino acids can indeed play a key role in the settlement of the macrofouling, [START_REF] Trapido-Rosenthal | L-α, ω-Diamino acids facilitate GABA induction of larval metamorphosis in a gastropod mollusc (Haliotis rufescens)[END_REF] showed that the presence of lysine at a micromolar concentration facilitates the induction of larval settlement and the metamorphosis of Haliotis rufescens. In addition, the proportion of essential amino acids in the biofilm is a useful proxy of biofilm nutritional quality for higher trophic levels. The slight differences detected between the dolomite Sorel cement and the other substrates at d14 and d35 could potentially imply a lower nutritional quality on the dolomite Sorel cement.

Taken together, these results suggest that the use of different substrates for ARs may lead to differences in the biofilm composition and secretions, and thus biofilm characterization in this context proves to be a good tool. Through the characterization of the PS composition secreted by the biofilm communities, we have been able to highlight significant differences in sugar concentration of the biofilm between the dolomite Sorel cement and the two types of concrete. This could potentially have an impact on organisms that settle and/or feed on this biofilm. Thus, it is essential to understand these mechanisms in the context of ARs, in order to enhance the colonisation. Otherwise, the two concrete substrates did not show significant differences in the parameters surveyed in this study, while white concrete contains less metallic oxide than grey concrete [START_REF] Telford | Portland cement : Composition, production and properties, 2nd editio[END_REF][START_REF] Betocib | Les Bétons à base de Ciment Blanc[END_REF]. Further analyses are thus needed to determine whether or not those two substrates present equivalent substrate quality for AR communities. Further research is also needed to understand the mechanisms involved in the adaptation of communities to substrates and to determine whether those differences might imply differences in the settlement of sessile macro-organism larvae and propagules at higher trophic levels. We need to determine whether the physical or chemical properties or both are involved in these mechanisms.

Conclusions

We identified a photosynthetic biofilm community mainly composed of diatoms, prasinophytes, coccolithophores and dinoflagellates on each substrate. We also identified differences between communities on the dolomite Sorel cement and those of white and grey concrete. The lower sugar to protein ratio on the dolomite Sorel cement community might be the result of differences in biofilm community composition and activity and is potentially determinant in the recruitment of various larvae and with regard to the diet of grazing invertebrates. We showed that biofilms are useful bio-indicators in that they develop quickly and give a rapid estimation of the quality of AR substrates.

Introduction

Since ages, in the marine environment, Man has immersed artificial structures in order to create dedicated habitats to attract species of interest. These structures have been immersed, these last decades, only according to judgment expert and rarely based on scientific criteria. Once the artificial reef has been immersed, the material used to build it constitutes the first element in contact with the marine environment. Its colonization follows a well-known basic pattern named "fouling sequence model". Firstly, the surface is covered by a conditioning film formed by the surrounding water, this film can sometimes mask the physicochemical characteristics of the material. Following this film, the first microorganisms colonize the reef allowing the formation of a biofilm at the surface. The matrix extracellular substances produced by this biofilm can in turn positively or negatively influence the colonization of larvae of multicellular organisms constituting the reef macrofouling [START_REF] Wahl | Marine epibiosis. I. Fouling and antifouling: some basic aspects[END_REF][START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF].

The term biofilm refers to a microbial community that binds to a biological or nonbiological submerged surface as well as the diversity of molecules produced by the microbes outside the cells membrane [START_REF] Costerton | MINIREVIEW Biofilms, the Customized Microniche[END_REF][START_REF] Hall-Stoodley | Bacterial Biofilms: From the Natural Environment to Infectious Diseases[END_REF]). In the photic marine environment, it is mainly composed of diatoms and cyanobacteria [START_REF] Wahl | Marine epibiosis. I. Fouling and antifouling: some basic aspects[END_REF][START_REF] Callow | Biofilms[END_REF][START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]. The adhesion of these microorganisms is mediated by the secretion of these external compounds named extracellular polymeric substances (EPS)

composed of macromolecules such as polysaccharides, proteins, nucleic acids, lipids and other polymeric substances [START_REF] Flemming | The biofilm matrix[END_REF]. The composition of these EPS can vary according to the environmental conditions to which the microorganisms are subjected. The expression of particular phenotypes confers them a better access to nutrients, a better colonization capacity and a better resistance to environmental pressures [START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]). The subsequent colonisation by macrofouling is determined by the local biological environment, but the substrate can also have a preponderant influence on it [START_REF] Bohnsack | Artificial reef research: a review with recommendations for the future prorities[END_REF][START_REF] Bohnsack | Habitat structure and the design of artificial reefs[END_REF][START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF]. In Mediterranean Sea, [START_REF] Ardizzone | Prediction of Benthic and Fish Colonization on the Fregene and other Mediterranean Artificial Reefs[END_REF] determined a global model of colonisation with early benthic colonization by diatoms, hydroids, serpulid polychaetes, barnacles and molluscs. Then, the equilibrium of the community is an interactive and dynamic process driven by environmental conditions and interspecific competition of the assemblage [START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF]. The success of artificial reefs according to the use of different material used has been rarely investigated [START_REF] Brown | Epifaunal colonization of the Loch Linnhe Artificial Reef : Influence of substratum on epifaunal assemblage structure[END_REF][START_REF] Riera | Biofilm monitoring as a tool to assess the efficiency of artificial reefs as substrates: Toward 3D printed reefs[END_REF], and these studies focus mainly on biofilm and macrofouling community structure and EPS secretion of biofilm. However, it is important to determine if the material itself is a source of pollution to the marine environment and/or the reef food web.. Biofilm and biofouling are known to highly bioaccumulate heavy metals, and could be the first step in the contamination of the entire food web [START_REF] Kratochvil | Advances in the biosorption of heavy metals[END_REF][START_REF] Bhaskar | Bacterial extracellular polymeric substance (EPS): A carrier of heavy metals in the marine food-chain[END_REF][START_REF] Romera | Comparative study of biosorption of heavy metals using different types of algae[END_REF][START_REF] Das | Biosorption of heavy metals -An overview[END_REF][START_REF] Pal | Microbial extracellular polymeric substances: Central elements in heavy metal bioremediation[END_REF][START_REF] Dash | Marine bacteria: Potential candidates for enhanced bioremediation[END_REF][START_REF] Decho | Microbial Extracellular Polymeric Substances (EPSs) in Ocean Systems[END_REF] This study aims to study the evolution of epibenthic communities developing on different substrates used for the construction of artificial reefs. In addition, this study makes it possible to determine whether certain substrates promote the phenomena of bioaccumulation of heavy metals. This monitoring has been carried out from the first stages of colonization of the biofilm until the establishment of macrofouling communities. We hypothesized (i) that the nature of the substrate used to build artificial reefs could affect the structure of the biofilm microbial community and its EPS secretion, and (ii) that substrates and biofilm could influence the colonisation by macrofouling. Finally, we hypothesized that these differences between substrates could affect the sequestration by biofilms and/or macrofouling of heavy metals present in the environment and/or in the substrates used for this monitoring. To test these hypotheses, we first monitored the colonisation of biofilm microbial communities on different artificial reef substrates by metagenomic sequencing on prokaryotic 16S rDNA genes (bacteria and archaea) and by HPLC to identify photosynthetic communities. Colorimetric analyses on sugar and proteins were performed to characterize the content of the EPS of the biofilm matrix.

Secondly, we monitored macrofouling communities over a period of one year by taxonomic identification. Both monitorings were completed by an analysis of heavy metals content in biofilm and macrofouling, compared to the heavy metals contained in the virgin substrates and in sinking and suspended particulate organic matter (POM) collected by sediment traps.

Materials & methods

Substrates

Three different substrates used for artificial reefs have been tested: the rock, mainly used for dikes and rockfills, the concrete, mainly used to build classical module of artificial reefs nowadays, and a substrate based on dolomite sand and white cement made by the Boskalis industry and used to build artificial reef using giant 3D printers (D-Shape). This substrate will be named thereafter "dolomite". The samples were cut in different shapes according to the monitoring type. For the biofilm monitoring, each cobblestone sized 1.5x2x5 cm in order to fit in a 50 ml Falcon tube. For the macrofouling monitoring, each plate sized 25*25*5 cm, and mimics a quadrat used for the determination of benthos on the rocky reefs. In total 330 samples for the biofilm monitoring and 96 samples for the macrofouling monitoring have been immersed.

Monitoring and sampling

The Before the retrieval of each plate, it was wrapped in plastic film and placed in a plastic bag in order to prevent any detachment of the organisms. It was then placed in a solid plastic box and elevated to the surface by diving parachute of 50 litters.

We immersed replicates of the 3 substrates for each sampling period at each site and for every kind of analysis, our replicates are then not paired between analyses. In total 330 samples for the biofilm monitoring and 96 samples for macrofouling monitoring have been immersed. In addition, two sediment traps have been placed in both selected sites with three temperature loggers. They were retrieved and replaced at the end of the biofilm monitoring

Macrofouling identification

The plates were unwrapped and gently placed in a plastic tray. With the help of a guillotine blade, all the organisms were detached from the substrate and gathered in the plastic tray. Each sample was then passed under a 100 μm sieve to get rid of the fine sediments, then placed in a container with artificial seawater (30 g. L -1 of salt, equivalent to the salinity of the study site), and stored at 4 °C before sorting organisms at the lab. No preservatives were added because all samples were pre-sorted within two days after the sampling. Sorting was carried out using different sieves inferior to 400 µm as recommended in Ganbi and Dappiano (2004) for macrofouling identification. A pre-identification step was done with a binocular Nikon SMZ -10. The different species (higher taxa) were then kept in adequately sized containers and frozen until final identification using a Stereomicroscopes LEICA M80, connected to a

Qimaging RoHS camera and a lamp LEICA CLS 150 XE. Pictures of samples were done for postverification, using the Image Pro plus 7.0 software. Depending on the individual development and their state after being detached from the plates, some of them could be identified up to the species. The identification has been done with the help of referenced manuals [START_REF] Giulia | Guida alle conchiglie mediterranee[END_REF][START_REF] Riedl | Fauna e flora del Mediterraneo. Dalle alghe ai mammiferi: una guida sistematica alle specie che vivono nel mar Mediterraneo[END_REF][START_REF] Pansini | Fauna d'Italia. Vol. XLVI, Porifera. I, Calcarea, Demospongiae (partim), Hexactinellida, Homoscleromorpha[END_REF][START_REF] Rodriguez-Prieto | Alghe e fanerogame del Mediterraneo, italiana a[END_REF]. The database Worms (http://www.marinespecies.org/) and Algae Base (http://www.algaebase.org/) were used to verify the species terminologies according to their phylogeny. After the last identification, samples have been dried in an oven at 70°C and weighed to the nearest milligram with a balance (Denver instrument company TR-64) to obtain the total macrofouling dry weight (expressed in mg cm -2 ).

Heavy metals analyses

The heavy metals concentration (As, Cd, Cr, Cu, Ni, Pb, Zn) was measured in the biofilm, the macrofouling, the 3 substrates and in the sinking and suspended marine particulate organic matter (POM) collected in the sediment trap to assess the contamination level in all the compartments of this study.

Samples preparation -To gently detach the biofilm from the substrate, 5 ml of ultrapure water was added to the sample before agitation with optoelectronic speed control (VXR basic Vibrax ®) at 2.2 rpm for 30 seconds. The substrate was then removed and the biofilm retrieved in the tube was frozen and lyophilized. The macrofouling was retrieved with a plastic ruler previously cleaned with alcohol and ultra-pure water, placed in petri glasses and dried in an oven at 110 °C. Three virgin samples of the different substrates that were not immersed were crushed with a plastic harmer. The sediment was recovered from the two sediment traps after 24h of sedimentation after sampling and dried in an oven at 110 °C. After being weighted separately to assess the sedimentation rate (in g m -2 day -1 ), the marine POM coming from two different sediment traps was pooled. All the different sample types (biofilm, macrofouling, marine POM and substrate) have been then reduced in powder with a ceramic pestle.

Heavy metals quantification -3 aliquots of each sample type were weighed in an

Erlenmeyer flask before the addition of 5 ml ofpure HNO3 (> 65%; puriss. p.a.) was added for the first digestion step. The sample was then heated on a hotplate at 90° C and 3. 30ml of aqua regia (1/3 HNO3 + 2/3 HCl (37%, Fisher Chemical) . was progressively added. Once this second digestion step was complete, 5ml of H2O2 (30% (v/v) EPR) was added to end the sample digestion, and the sample was reduced to the maximum, without however drying it. After this last digestion step, in order to reduce the acidity, the digestion products were diluted and reduced three times with 100 ml of ultra-pure water. The rinsed and diluted sample was resuspended in ultrapure water up to 40 ml. After centrifugation at 4 000 rpm for 10 min, the supernatant containing the heavy metals in suspension was recovered in a beaker and reduced again on a hotplate at 90 °C. The pellet, containing the sediment was resuspended in ultrapure water up to 15 ml and centrifuged again at 4000 rpm for 10 min. The supernatant was then added to the previous one, and reduced again on a hotplate at 90 °C. Then, the sample was 1/10 or 1/2 diluted with Ultra-pure water, depending on the concentration of the sample. The pellet was dried in an oven at 110 °C and weighted in order to determine the quantity of undigested material to be deduced from the mass of the studied samples. The quantities of heavy metals were then expressed in ppm (mg.kg -1 ) of samples.

Univariate data:

-Colorimetry analyses: concentration of sugar and proteins within biofilm EPS -Macrofouling identification: the total dry weight of macrofouling; -Heavy metals analyses: total concentration of heavy metals contained in biofilm, macrofouling, sediment trap and virgin substrates

We used the univariate non-parametric Van-der-Warden test to determine differences in time, sites and between substrates on the different univariate data. The illustration related to these results have been proceeded with the ggplot2 package, we used the non-parametric LOcally weighted Scatterplot Smoother (LOESS) regression method to calculate the best fit (average +-confidence interval) .

Multivariate data:

-Metagenomic analyses: relative abundance of bacteria identification at classes level for each sample -HPLC analyses: percentage of pigments for each sample macrofouling identification: percentage of the total dry weight of macrofouling identification at the highest taxonomical level for each sample To test differences between sites, sampling and substrates, we used the non-parametric statistical test of the analysis of similarities (ANOSIM) using a Bray-Curtis dissimilarity index.

To illustrate the dissimilarities between samples, we followed the different step described below:

1. A Bray-Curtis dissimilarity matrix has been calculated on each set of multivariate data (vegan package) 2. A hierarchical classification has been processed on the Bray-Curtis matrix using the Ward agglomeration method [START_REF] Murtagh | Ward's Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward's Criterion?[END_REF] to identify the distance between each cluster (R base) 3. The best partition of the dataset was performed by k-means partitioning using a range of values of k clusters. Function cascadeKM (package vegan) creates several partitions forming a cascade from a small to a large number of clusters (i.e. from 2 to 24 in the present sutdy). The "Calinski-Harabasz" criterion has been used to select the best partition (Calinski-Harabasz 1974).

A Principal Coordinates Analysis (PCoA), has been performed on the Bray-Curtis dissimilarity matrix of the data using ade4 package.On the ordination plot, scores were then grouped according to the hierarchical classification and the best partition previously evidenced (steps 2 and 3)

Heavy metals analyses

The percentage of the heavy metals has been processed for each sample of biofilm at D28 and for each sample of macrofouling at Apr. 2018, and where compared to the mean percentage of the marine POM in sediment traps for each biofilm and macrofouling monitoring, and to the mean percentage of each virgin substrates.

Two Principal Component Analysis (PCA) were applied to the percentage of heavy metals results, one for each monitoring. Total heavy metals concentration for both monitorings was added as supplementary variable to identify potential correlation, but did not influence the ordination of the PCA: The samples were collected according to partition determined by Hierarchical Clustering On Principle Components (HCPC) function corresponding to the higher relative loss of inertia.

Results

Temperature and sedimentation rates during the monitoring

The temperature was similar between sites during the biofilm monitoring (16.9 ± 0.

Photosynthetic community

The main pigments secreted by the photosynthetic communities of the biofilm growing on the different substrates were chlorophyll a (56.89 ± 0.45%), fucoxanthin (28.71 ± 0.40%), chlorophyll c (7.01 ± 0.23%), and pheopigments (3.98 ± 0.23%). The other minor pigments secreted were diatoxanthin (0.55 ± 0.03%), diadinoxanthin (1.72 ± 0.06%), zeaxanthin (0.43 ± 0.04%), chlorophyll b (0.17 ± 0.03%) and β carotene (0.54 ± 0.06%). As for prokaryotic communities, differences between photosynthetic communities were due to sampling times and sites (ANOSIM Bray Curtis dissimilarity: Sampling: 0.4729, p=0.001; Site: R: 0.1982, p=0.001), and not to the different substrates (Substrate: R: 0.008118, p = 0.201).

A PCoA has been performed on all the different pigments (

Macrofouling communities

For the first two sampling dates, both sites showed the same seasonal dynamic of colonisation, with increasing macrofouling dry weight from summer (Aug. 2017) to autumn (Oct. 2017). Then, during winter season (Feb. 2018), the community at Monaco diminished 10 times more than at Roquebrune (Monaco: 1.88 ± 0.26 mg.cm -2 ; Roquebrune 10.23 ± 1.67 mg.cm -2 ) and the recovering of the community in spring (Apr. 2018) was slighter at Monaco than at Roquebrune (Monaco: 7.81 ± 1.30 mg.cm -2 ; Roquebrune: 50.82 ± 7.59 mg.cm -2 ) (Figure III-7). On average, Roquebrune supported a higher amount of macrofouling than Monaco (Monaco: 16.42 ± 3.88 mg.cm -2 ; Roquebrune: 32.43 ± 4.38 mg.cm -2 , Van der Waerden test: p=0.0007). The dolomite and rock supported higher colonisation than concrete during autumn at Monaco (test). At the end of the monitoring, the macrofouling colonisation was similar on the different substrates at Monaco but was significantly higher on the rock at Roquebrune A large part of the macrofouling was composed of algal turf (56.90 ± 3.74 %). A total of 58 different taxa have been identified along the monitoring period of the macrofouling.

Dictyota sp. (13.53 ± 2.34 %) and Bitium reticulatum (10.70 ± 2.20 %) were the most abundant species. The number of taxa identified was higher at Roquebrune than at Monaco. Indeed, 24 taxa were found only at Roquebrune while 14 were found only at Monaco, and 33 taxa were common to both sites. Regarding the sampling periods, 8 taxa were specific to the summer

Macrofouling

A PCA was performed on the percentage of heavy metals contained in the macrofouling after one year of monitoring (Apr. 2018), in the virgin substrates and in the marine POM (Figure . The first two dimensions explained more than 60 % of the inertia, it showed a good projection of the data, as variables were close to the correlation circle, except arsenic and nickel that were better represented on the third dimension. The first dimension was mainly built by chrome and zinc, whereas the second dimension was equally built by the other heavy metals except for arsenic and nickel. The first dimension opposed the first to the sixth clusters, whereas the second dimension opposed the second and fourth clusters with the fifth. The third cluster is distributed close to origin of the 1:2 plan. The first cluster grouped the samples of macrofouling growing on dolomite at Monaco. It is positively described by its percentage of cadmium and lead and negatively by its content of total heavy metals. The second cluster gathered the samples of macrofouling growing on Rock at Monaco, positively described by their percentage of copper. The third cluster grouped all the samples of macrofouling growing on all substrates at Roquebrune, described positively by its percentage of nickel and negatively by its percentage of arsenic. The fourth cluster grouped the samples from the sediment traps at both sites and the samples of macrofouling growing on concrete, described positively by its content of total heavy metals, its percentage of zinc, and negatively by its percentage of lead. The last two clusters corresponded to the virgin concrete and dolomite (cluster 5) and the virgin rock (cluster 6) samples, and their heavy metals composition was previously described (see previous paragraph, p.103).

Figure III-12: Principal component analysis on the percentage of heavy metals within the macrofouling, the marine POMl and the virgin substrates in April 2018 on both sites (Monaco and Roquebrune): A) Correlation circle of the variables, B) and ordination of the samples on the first two dimensions

Discussion

Cyanobacterial growth potentially influences biofilm development and explains differences between sites:

In a previous study on biofilm monitoring on Sorel cement (made with dolomite sand for artificial reefs 3D print design) and different types of concrete (white and grey), we already highlighted significant differences between materials in biofilm secretion of sugars, but this study did not show difference in photosynthetic communities [START_REF] Riera | Biofilm monitoring as a tool to assess the efficiency of artificial reefs as substrates: Toward 3D printed reefs[END_REF]). In the present study, the analyses of the biofilm microbial communities (total prokaryotes and photosynthetic prokaryotes and eukaryotes) did not highlight significant differences between substrates either. According to metagenomic identification, the prokaryotic community was composed of few archaea, mainly represented by species of Nitrosopumilus spp. and Candidatus nitrosoarchaeum from the oxidize ammonia aerobicall phylum Thaumarchaeota, that prove to be highly represented in a wide variety of ecosystems [START_REF] Pester | The Thaumarchaeota: An emerging view of their phylogeny and ecophysiology[END_REF][START_REF] Brochier-Armanet | Spotlight on the Thaumarchaeota[END_REF], including marine environments [START_REF] Parada | Every base matters : assessing small subunit rRNA primers for marine microbiomes with mock communities , time series and global field samples[END_REF]. To the best of our knowledge, no previous study investigates archaea community within a marine biofilm, our results suggest that the archaea do not structure the prokaryote community within time, sites or substrates.

The prokaryotic communities were mainly dominated by Alphaproteobacteria and Flavobacteria all along the monitoring. These results are consistent with various studies of biofilm in Mediterranean costal seas [START_REF] Ortalo-Magné | Identification of Bacterial Strains Isolated from the Mediterranean Sea Exhibiting Different Abilities of Biofilm Formation[END_REF][START_REF] Briand | Spatio-Temporal Variations of Marine Biofilm Communities Colonizing Artificial Substrata Including Antifouling Coatings in Contrasted French Coastal Environments[END_REF][START_REF] Pollet | Prokaryotic community successions and interactions in marine biofilms : the key role of Flavobacteriia To cite this version : HAL Id : hal-02024255 Prokaryotic community successions and interactions in marine biofilms : the key role of Flavobacteriia HAL[END_REF]). These bacterial classes seem ubiquitous in marine biofilm growing on hard substrates, as they are often the most abundant in most case studies [START_REF] Chung | Bacterial community succession and chemical profiles of subtidal biofilms in relation to larval settlement of the polychaete Hydroides elegans[END_REF][START_REF] Dang | Cross-Ocean Distribution of Rhodobacterales Bacteria as Primary Surface Colonizers in Temperate Coastal Marine Waters[END_REF]Dang andLovell, 2002, 2000;[START_REF] Huang | Composition and density of bacterial biofilms determine larval settlement of the polychaete Hydroides elegans[END_REF][START_REF] Huggett | Effects of initial surface wettability on biofilm formation and subsequent settlement of Hydroides elegans[END_REF][START_REF] Jones | Bacterial Community Structure of Biofilms on Artificial Surfaces in an Estuary[END_REF]Webster and Negri, 2006). The dynamic of the other taxa may change according to environmental condition and depth of the study, in shallow water cyanobacteria prove to increase with time in Mediterranean sea [START_REF] Briand | Spatio-Temporal Variations of Marine Biofilm Communities Colonizing Artificial Substrata Including Antifouling Coatings in Contrasted French Coastal Environments[END_REF], in Baltic sea [START_REF] Sanli | Metagenomic sequencing of marine periphyton: Taxonomic and functional insights into biofilm communities[END_REF] and or even in Oman sea [START_REF] Musard | Long-term microfouling on commercial biocidal fouling control coatings[END_REF][START_REF] Abed | Short-term succession of marine microbial fouling communities and the identification of primary and secondary colonizers[END_REF] whereas in our study it decreased with time, suggesting they represent primary colonizers at 30 meters depth, followed by secondary colonizers, such as Gammaproteobacteria, Sphingobacteriia, Cytophagia, Verrucomicrobiae and Clostridia in the present study. According to pigments analyses, the presence of fucoxanthin, chlorophyll c, diadinoxanthin, and diatoxanthin might reveal the presence of brown algae from Bacillariophyceae class (i.e. diatoms). The presence of β carotene and chlorophyll b might reveal the presence of green algae, and the zeaxanthin might reveal more precisely the presence of Cyanophyceae which is coherent with the metagenomic identification and with the literature. Indeed, in microphytobenthos biofilms growing on hard substrates, diatoms and cyanobacteria are often the most abundant phylum [START_REF] Cooksey | Adhesion of bacteria and diatoms to surfaces in the sea : a review[END_REF][START_REF] Lam | Induction of larval settlement in the polychaete Hydroides elegans by surfaceassociated settlement cues of marine benthic diatoms[END_REF][START_REF] Briand | Pioneer marine biofilms on artificial surfaces including antifouling coatings immersed in two contrasting French Mediterranean coast sites antifouling coatings immersed in two contrasting[END_REF][START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF].

Globally the photosynthetic communities became mature rapidly, from the first week on the dolomite samples, and from the second week on the other substrates with the presence of all pigments represented by cluster 4. These results are consistent with our previous study, where biofilm became mature after two weeks [START_REF] Riera | Biofilm monitoring as a tool to assess the efficiency of artificial reefs as substrates: Toward 3D printed reefs[END_REF]. At the end of the monitoring, photosynthetic communities were significantly different between sites, Roquebrune showed a community with more diverse photosynthetic communities with the settlement of green algae related to the presence of chlorophyll b, whereas Monaco was still dominated by brown algae according to fucoxanthin and chlorophyll c percentage. The presence of green algae at Roquebrune could be linked to the recruitment of sporophytes of green macroalgae. Indeed, a previous study showed that the rate of settlement of the green algae Enteromorpha intestinalis (Ulva intestinalis) prove to be more effective when surface was colonized by mixed bacterial biofilm close to the one of our case study without cyanobacteria [START_REF] Dillon | Adhesion of Enteromorpha Swarmers to Microbial Films[END_REF][START_REF] Patel | Specificity in the settlement -modifying response of bacterial biofilms towards zoospores of the marine alga Enteromorpha[END_REF]). In the present study, we did not identify green algae of this family, indeed the depth at which the samples were placed does not match the distribution of Ulva spp. that lives in the supralittoral. However, the Roquebrune site was characterised by a higher diversity of seaweed than at Monaco. The only difference that could explain this better settlement of green algae at Roquebrune is the decline of cyanobacteria demonstrated by the decrease of zeaxanthin, and Cyanophyceae sequences in the bacterial community.

The material does not influence the diversity and composition of microbial communities:

No significant differences in microbial communities between substrates have been detected, which is in contradiction with many studies (e.g: [START_REF] Cooksey | Adhesion of bacteria and diatoms to surfaces in the sea : a review[END_REF][START_REF] Dexter | Influence of Substratum Critical Surface Tension on Bacterial Adhesion--in[END_REF][START_REF] Fletchert | Influence of Substratum Characteristics on the Attachment of a Marine Pseudomonad to Solid Surfaces[END_REF][START_REF] Jones | Bacterial Community Structure of Biofilms on Artificial Surfaces in an Estuary[END_REF][START_REF] Ozkan | Biointerfaces Cell to substratum and cell to cell interactions of microalgae[END_REF][START_REF] Patil | Biofilm diatom community structure : Influence of temporal and substratum variability[END_REF][START_REF] Pringle | Adsorption of Bacterial Surface Polymers to Attachment Substrata[END_REF]) However, [START_REF] Dang | Microbial Surface Colonization and Biofilm Development in Marine Environments[END_REF], highlighted that the nutritional conditions and physicochemical properties of primary film can have a "mask effect" by wiping off the hydrophobicity or roughness of a given surface. [START_REF] Tan | Differences in Intertidal Microbial Assemblages on Urban Structures and Natural Rocky Reef[END_REF] also suggested that changes in bacterial communities might be related to habitat characteristics such as orientation or complexity of the substrate. Nevertheless, the biofilm matrix revealed differences over time, between sites and substrates. On the concrete the higher amount of EPS secretion could be explained by the pH of the substrate that is known to be alkaline (close to 13 pH). Dogsa and colleagues (2005) showed that low pH favour larger EPS structures dense and homogeneous. At both sites, the proteins and sugars contained in EPS increased at D21 and globally decreased at the end of the monitoring except on rock in Monaco where their concentration slightly increased. This trend was also observed by [START_REF] Riera | Biofilm monitoring as a tool to assess the efficiency of artificial reefs as substrates: Toward 3D printed reefs[END_REF] in the winter season, and has been associated with a disturbance in biofilm growth due to a storm. In the present study, the biofilm followed the same pattern yet in spring, without any apparent influence of the weather conditions. The shift of the global structure of the community, from second to third sampling dates, could explain the decrease of the EPS production. Indeed, Cyanobacteria are known to produce high amount of EPS during biofilm growth [START_REF] Rossi | Role of Cyanobacterial Exopolysaccharides in Phototrophic Biofilms and in Complex Microbial Mats[END_REF].

EPS production does affect heavy metals sequestration in artificial reefs biofilms

Differences between sites have also been revealed in terms of EPS secretion, as the EPS were more abundant at Monaco than at Roquebrune. Location have been proved to influence the EPS secretion rate and, alternatively the same structure of communities is also known to show differences in secretion under specific environmental conditions [START_REF] Ortega-Morales | Valuable processes and products from marine intertidal microbial communities[END_REF][START_REF] Underwood | Exopolymers (Extracellular Polymeric Substances) in Diatom: Dominated Marine Sediment Biofilms[END_REF], Underwood et al. 2010[START_REF] Fang | Characteristics of extracellular polymeric substances of phototrophic biofilms at different aquatic habitats[END_REF][START_REF] Decho | Microbial Extracellular Polymeric Substances (EPSs) in Ocean Systems[END_REF], or substrate type [START_REF] Chung | Bacterial community succession and chemical profiles of subtidal biofilms in relation to larval settlement of the polychaete Hydroides elegans[END_REF][START_REF] Riera | Biofilm monitoring as a tool to assess the efficiency of artificial reefs as substrates: Toward 3D printed reefs[END_REF]. Over all the monitoring, on both sites, biofilms growing on concrete and rock showed higher heavy metals concentrations than on dolomite and rock. The higher amount of EPS within biofilm growing on concrete and rock might explain the higher amount of heavy metals on these two substrates. Indeed, EPS are known to contribute to trophic-transfer of environmental contaminants [START_REF] Bhaskar | Bacterial extracellular polymeric substance (EPS): A carrier of heavy metals in the marine food-chain[END_REF][START_REF] Leguay | Using biofilm for monitoring metal contamination in lotic ecosystemes: the protective effects of hardness an pH on metal bioaccumulation[END_REF][START_REF] Decho | Microbial Extracellular Polymeric Substances (EPSs) in Ocean Systems[END_REF] and are even used in bioremediation [START_REF] Pal | Microbial extracellular polymeric substances: Central elements in heavy metal bioremediation[END_REF][START_REF] Dash | Marine bacteria: Potential candidates for enhanced bioremediation[END_REF], the dead biomass of biofilm and their EPS constitute a biosorption site for heavy metals [START_REF] Kratochvil | Advances in the biosorption of heavy metals[END_REF][START_REF] Romera | Comparative study of biosorption of heavy metals using different types of algae[END_REF][START_REF] Das | Biosorption of heavy metals -An overview[END_REF]. The main heavy metals contained in the biofilm were copper and zinc. The high amount of zinc could be explained by the high abundance of this metal within the marine particulate organic matter (POM) , but the presence of copper can't be explained neither by marine POM nor by virgin substrates used for the monitoring because it was not present it these two compartments or at a concentrations below the detection limit. Copper is however present in the water column of the western Mediterranean Sea at very low concentration of 90 ng.l -1 on average (Laumond et al., 1984;Seritti et al., 1990). It is therefore very likely that the bioaccumulation of copper in the biofilm is related to the presence of this element dissolved in the marine POM. In a previous study [START_REF] Muhamed | Bioaccumulation of Trace Metals in Biofilms Formed on Aluminium and Steel in Aquatic Environment[END_REF], monitored biofilm during different seasons in Cochin estuary, South India, during 24 hours and 72 hours. They showed that zinc was the most abundant heavy metals sequestered by the biofilm, copper was also very high even if it was expected to be at a minimum. Even if copper is an essential trace element for different biological reactions, it is toxic to microorganisms even at very low concentrations [START_REF] Gadd | Microorganisms and heavy metal toxicity[END_REF][START_REF] Ochoa-Herrera | Toxicity of copper(II) ions to microorganisms in biological wastewater treatment systems[END_REF].

EPS sequestration determines the fate of heavy metals in artificial reefs food web

The macrofouling analyses, following the analyses of biofilm, allowed to identify seasonal changes. The macrofouling dry weight increased between summer and autumn, then diminished during the winter season and increased anew in spring. Roquebrune supported a higher amount of macrofouling than Monaco, mainly due to a very slight recovering of the community after winter at Monaco, which could be explained by the important sedimentation rate that might have impacted the global evolution of the assemblage. Slight differences between substrates have been highlighted and were site dependant, the dolomite and rock supported higher colonization than concrete during autumn at Monaco, and the community was significantly more abundant on the rock at Roquebrune.. The global colonization observed on the plates was close to the artificial reefs colonization model in Mediterranean sea determined by [START_REF] Ardizzone | Prediction of Benthic and Fish Colonization on the Fregene and other Mediterranean Artificial Reefs[END_REF], with an early benthic colonization by diatoms, hydroids (Obelia dichotoma, Bouganvillia ramosa), serpulid polychaetes (Pomatoceros triqueter, Pomatoceros lamarckii, Hydroides pseudouncinata), barnacles (Balanus eburneus, Balanus peiforatus), and molluscs (Anomia ephippium, Mytilus galloprovincialis). To the best of our knowledge, no study in the Mediterranean Sea conducts comparative analyses on different substrates and their epibiotic colonization. In Loch Linnhe artificial reef, the choice of construction material had little effect on the long-term epifaunal community structure [START_REF] Brown | Epifaunal colonization of the Loch Linnhe Artificial Reef : Influence of substratum on epifaunal assemblage structure[END_REF]; equivalent results were found in Dubai, United Arab Emirates, in the south-eastern basin of the Persian Gulf, where differences in recruitment patterns were more site dependant than substrate material dependant in determining early benthic community structure and coral recruitment [START_REF] Burt | Coral recruitment and early benthic community development on several materials used in the construction of arti fi cial reefs and breakwaters[END_REF]. It is known that EPS plays a key role in the settlement and stabilization of macrfouling larvae [START_REF] Huang | Composition and density of bacterial biofilms determine larval settlement of the polychaete Hydroides elegans[END_REF][START_REF] Sherrard | Temporal variation of an initial marine biofilm community and its effects on larval settlement and metamorphosis of the tubeworm Hydroides elegans[END_REF].

However, in our study this parameter did not significantly influence the colonization of the substrates, as the lesser amount of EPS on the dolomite did not impact the biofilm and macrofouling settlement. [START_REF] Chung | Bacterial community succession and chemical profiles of subtidal biofilms in relation to larval settlement of the polychaete Hydroides elegans[END_REF] showed that finally, the chemical composition of the substrate had no effect on the recruitment of Hydroides spp., [START_REF] Huggett | Effects of initial surface wettability on biofilm formation and subsequent settlement of Hydroides elegans[END_REF], assumed that after 10 days, the same species is recruited whatever the substrate used.

Conclusively, the colonization would depend principally on the neighbouring natural habitat and on the larvae and spores that the current can bring to the structure [START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF].

Nevertheless, the analyses of heavy metals content in biofilm and macrofouling brought interesting results. Like biofouling (biofilms & macrofouling) communities growing on dolomite accumulate fewer heavy metals than those growing on the other substrates. furthermore, macrofouling growing on concrete at Monaco showed the same signature as the marine POM whit a high amount of zinc. Thus, the substrate seems to play a preponderant role in the fate of heavy metals in the food web of an artificial reef. This role is rather indirect and the present study demonstrated that the type of material (especially concrete) used to build artificial reef influences biofilm EPS production which in turn favour the sequestration of heavy metals from marine POM and their fate in the food web. The presence of heavy metals, from the first stage of colonization, are likely transferred to the macrofouling and to the mobile fauna feeding on the reefs which may cause bioaccumulation in the food web [START_REF] Bhaskar | Bacterial extracellular polymeric substance (EPS): A carrier of heavy metals in the marine food-chain[END_REF]. Given that many artificial reefs are designed in concrete and that their main role is to help artisanal fisheries, it is of utmost importance to better understand the relationships between EPS quantity and quality and heavy metals (or other organic and inorganic pollutants) sequestration and bioaccumulation in the food web of artificial reefs according to the type of substrate.

Conclusion

This study revealed for the first time that the monitoring of the structure and diversity of the communities is probably not the best way to infer about the quality of a given material to build an artificial reef. Most of the time, microbial and macrofouling assemblages are similar whatever the material used. However, we highlighted that substrates influence significantly the amount (and very likely also the quality) of EPS secretion in the biofilm matrix, which has strong incidence in terms of heavy metals sequestration and bioaccumulation in biofouling (biofilm & macrofouling). These differences between substrates were stronger at Monaco, a site highly impacted by its artificial coast and permanent building work occurring there.

IV. CHAPTER 3: STUDY THE COMPLEXITY OF ARTIFICIAL REEFS FROM THE MICRO TO THE MACRO SCALE

Introduction

The artificial reefs (AR) are "submerged structures placed on the seabed deliberately to mimic some characteristics of natural habitats" [START_REF] Pickering | Artificial Reefs as a Tool to aid Rehabilitation of Coastal Ecosystemes: Investigating the Potential[END_REF]. In France, it represents a volume of nearly 90 000 m 3 mainly to promote fisheries [START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF]. Facing the artificialization of coastal areas, that can reach up to 90% of the coast line, the artificial reefs must be considered as a true ecological engineering solution for the restoration and conservation issues (UNEP 2009).

These objectives imply to improve their efficiency by focusing on the intrinsic characteristics of an AR which are linked to the material used to design it and its threedimensional structure. Some studies already investigate the effect of different substrates on the primary communities that settle on the artificial reefs [START_REF] Salamone | Fungal diversity of marine biofilms on artificial reefs in the northcentral Gulf of Mexico[END_REF][START_REF] Liu | Succession and seasonal variation in epilithic biofilms on artificial reefs in culture waters of the sea cucumber Apostichopus japonicus[END_REF][START_REF] Riera | Biofilm monitoring as a tool to assess the efficiency of artificial reefs as substrates: Toward 3D printed reefs[END_REF]). But regarding their three-dimensional structure, artificial reefs are currently mainly designed empirically according to expert judgment, but never according to scientific criteria [START_REF] Turner | Man-Made Reef Ecology[END_REF][START_REF] Bohnsack | Artificial reef research: a review with recommendations for the future prorities[END_REF][START_REF] Pickering | Artificial reefs and fisheries exploitation: A review of the 'attraction versus production' debate, the influence of design and its significance for policy[END_REF][START_REF] Barnabé | Artificial reef in France : analysis , assessments and prospects[END_REF][START_REF] Jeansen | Artificial Reefs in European Seas[END_REF][START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF][START_REF] Williams | Sinking Poor Decision Making With Best Practicices -A Case Study of Artificial Reef Decision-Making in the Florida Keys[END_REF][START_REF] Shokry | Coral Reef Restoration and Artificial Reef Management , Future and Economic[END_REF][START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF]. Few studies have used numerical methods to determine structure complexity of artificial reefs. Most of them focused on surface rugosity (or roughness) (Ferreira, Gonçalves and Coutinho, 2001;Wilding, Rose and Downie, 2007), or the fractal dimension [START_REF] Caddy | Mapping Growth and Mortality Rates of Organisms onto a Perforated Surface: The Relevance of 'Cover' to the Carrying Capacity of Natural and Artificial Habitats[END_REF]. More recently Loke andcolleagues (2014, 2015;[START_REF] Mohammed | Applications of 3D printing technologies in oceanography[END_REF] proposed a way to improve surface structure by increasing heterogeneity, in order to increase epibiotic settlement. Lan and colleagues (2008), proposed a method for the arrangement in space of the artificial reefs based on fractal design, but it did not concern the design of the structure itself. One study followed the recommendation of [START_REF] Bohnsack | Habitat structure and the design of artificial reefs[END_REF] by counting the number of space, voids and crevices to determine the preference of fish according to shelter types [START_REF] Hackradt | Influence of habitat structure on fish assemblage of an artificial reef in southern Brazil[END_REF]). However, no universal method exists to evaluate their structure complexity, in order to know whether they can mimic the spatial heterogeneity and high threedimensional complexity of natural habitat. For now, only comparative studies between communities of artificial and natural habitats could give us a first answer (e.i. [START_REF] Bohnsack | Are high densities of fishes at artificial reefs the results of habitat limitation or behavioural preference?[END_REF][START_REF] Caddy | Mapping Growth and Mortality Rates of Organisms onto a Perforated Surface: The Relevance of 'Cover' to the Carrying Capacity of Natural and Artificial Habitats[END_REF][START_REF] Pickering | Artificial reefs and fisheries exploitation: A review of the 'attraction versus production' debate, the influence of design and its significance for policy[END_REF][START_REF] Barnabé | Artificial reef in France : analysis , assessments and prospects[END_REF][START_REF] Jeansen | Artificial Reefs in European Seas[END_REF][START_REF] Hunter | The comparative effects of habitat complexity on faunal assemblages of northern temperate artificial and natural reefs[END_REF][START_REF] Aguilera | Spatial variability in community composition on a granite breakwater versus natural rocky shores: Lack of microhabitats suppresses intertidal biodiversity[END_REF][START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF]. Since the early '90s most of the structure modules used are simple shapes and are gathered in aggregates without offering a high heterogeneity. It has been quite common to practice post complexification of ARs to enhance their efficiency [START_REF] Charbonnel | Effet de la complexification de l'architecture des récifs artificiels du Parc national de Port-Cros (Méditerranée, France) sur les peuplements ichtyologiques[END_REF][START_REF] Charbonnel | Effects of increased habitat complexity on fish assemblages associated with large artificial reef units (French Mediterranean coast)[END_REF][START_REF] Bodilis | Suivi des peuplements ichtyologiques des récifs artificiels des zones marimes protégées des Alpes-Maritimes[END_REF][START_REF] Bodilis | Monitoring of the artificial reef fish assemblages of golfe juan marine protected area (France, North-Western Mediterranean)[END_REF]Cépralmar, 2015;[START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF]. Recently, giant three dimensional (3D) print gives rise to a new generation of artificial reefs [START_REF] Rageh | Effect of high power ultrasound on aqueous solution of DNA[END_REF][START_REF] Alessandro | Emergent Reefs[END_REF][START_REF] Frau | Effects of Ultra-Porous 3D Printed Reefs on Wave Kinematics[END_REF][START_REF] Mohammed | Applications of 3D printing technologies in oceanography[END_REF][START_REF] Riera | Biofilm monitoring as a tool to assess the efficiency of artificial reefs as substrates: Toward 3D printed reefs[END_REF]. For now, 3D printing remains expensive, but increasing the use of printed artificial reefs could reduce their price, making possible to build artificial structures whose properties are closer to the more complex structure of natural habitats, at a cost-efficient price.

In the natural environment, complexity and heterogeneity of the habitat strongly influence the diversity and abundance of species that settle [START_REF] Macarthur | On Bird Species Diversity[END_REF][START_REF] Macarthur | On Bird Species Diversity II. Prediction of Bird Census from Habitat Measurements[END_REF], McCoy & Bell 1991[START_REF] Beck | Separating the elements of habitat structure: independent effects of habitat complexity and structural components on rocky intertidal gastropods[END_REF][START_REF] Tews | Animal species diversity driven by habitat heterogeneity/diversity: the importance of keystone structures[END_REF][START_REF] Tagliapietra | Biological diversity and habitat diversity: a matter of Science and perception[END_REF][START_REF] Kovalenko | Habitat complexity: approaches and future directions[END_REF][START_REF] Tokeshi | Habitat complexity in aquatic systems : fractals and beyond[END_REF][START_REF] Musard | Long-term microfouling on commercial biocidal fouling control coatings[END_REF][START_REF] Loke | Creating complex habitats for restoration and reconciliation[END_REF]. The term complexity is closely related to the shape of the structures which is itself linked to the variation of its physical features in space, whereas heterogeneity defines the abundance and diversity of the elements that compose the habitat (McCoy and Bell, 1991;[START_REF] Tews | Animal species diversity driven by habitat heterogeneity/diversity: the importance of keystone structures[END_REF]² Tews et al., , beck 1998² Tews et al., , 2000)). Different variables are used to determine the complexity of habitat, the most common in marine environment is the roughness assessed by the chain and tape method (e.i.: [START_REF] Luckhurst | Analysis of the Influence of Substrate Variables on Coral Reef Fish Communities[END_REF][START_REF] Beck | Comparison of the measurement and effects of habitat structure on gastropods in rocky intertidal and mangrove habitats[END_REF][START_REF] Beck | Separating the elements of habitat structure: independent effects of habitat complexity and structural components on rocky intertidal gastropods[END_REF][START_REF] Friedlander | Habitat characteristics affecting fish assemblages on a Hawaiian coral reef[END_REF][START_REF] Willis | Habitat structural complexity and morphological diversity of fish assemblages in a Neotropical floodplain river[END_REF][START_REF] Pais | Improving the 'chain and tape' method: A combined topography index for marine fish ecology studies[END_REF][START_REF] Sánchez-Caballero | Links between fish community structure and habitat complexity of a rocky reef in the Gulf of California threatened by development: Implications for mitigation measures[END_REF]Young et al., 2017); but the roughness can be defined with more accurate variables such as area ratio [START_REF] Jenness | Calculating landscape surface area from digital elevation models[END_REF][START_REF] Friedman | Multi-Scale Measures of Rugosity, Slope and Aspect from Benthic Stereo Image Reconstructions[END_REF][START_REF] Bryson | Characterization of measurement errors using structure-from-motion and photogrammetry to measure marine habitat structural complexity[END_REF], vector dispersion (orientation), standard deviation of the elevation Z value [START_REF] Carleton | Effects of substratum irregularity on success of coral settlement: quantification by comparative geomorphological techniques[END_REF][START_REF] Beck | Comparison of the measurement and effects of habitat structure on gastropods in rocky intertidal and mangrove habitats[END_REF], 2000[START_REF] Grohmann | Surface Roughness of Topography : A Multi-Scale Analysis of Landform Elements in Midland Valley, Scotland[END_REF][START_REF] Kovalenko | Habitat complexity: approaches and future directions[END_REF], Young et al. 2017). All these variables are coming from the study of the surface topography, some of them can be adapted to the artificial reef structure to determine the variability of their surface orientation and the roughness aspect of their structure. The fractal dimension (D) is also often used. It translates the way an object fills the space, at all scales (e.g.: [START_REF] Mace | Scale-Dependent Fractal Dimensions of Topographic Surfaces : An Empirical Investigation , with Applications in Geomorphology and Computer Mapping[END_REF][START_REF] Frontier | Applications of fractal theory to ecology[END_REF][START_REF] Beck | Comparison of the measurement and effects of habitat structure on gastropods in rocky intertidal and mangrove habitats[END_REF][START_REF] Beck | Separating the elements of habitat structure: independent effects of habitat complexity and structural components on rocky intertidal gastropods[END_REF][START_REF] Schmid | Fractal Properties of Habitat and Patch Structure in Benthic Ecosystems[END_REF][START_REF] Johnson | The area-independent effects of habitat complexity on biodiversity vary between regions[END_REF][START_REF] Halley | Uses and abuses of fractal methodology in ecology[END_REF][START_REF] Frost | Measuring surface complexity in ecological studies[END_REF][START_REF] Kostylev | The relative importance of habitat complexity and surface area in assessing biodiversity: Fractal application on rocky shores[END_REF][START_REF] Warfe | Quantifying habitat structure : surface convolution and living space for species in complex environments[END_REF][START_REF] Wilding | Comparison of three methods for quantifying topographic complexity on rocky shores[END_REF][START_REF] Tokeshi | Habitat complexity in aquatic systems : fractals and beyond[END_REF]Young et al., 2017). [START_REF] Tews | Animal species diversity driven by habitat heterogeneity/diversity: the importance of keystone structures[END_REF] summarise four methods to assess heterogeneity ; two are based on discrete variables: the structural richness based on species richness and the structural diversity based on Shannon index ; the two others are based on continuous variable: the structural extent based on structural qualities such as percentage coverage, and structural gradient based on gradient length of Euclidian distance measured on differences between the structural elements. The most common variable used is the Shannon index computed on the different elements that compose the habitat (e.g.: [START_REF] Macarthur | On Bird Species Diversity[END_REF][START_REF] Macarthur | On Bird Species Diversity II. Prediction of Bird Census from Habitat Measurements[END_REF][START_REF] Roberts | Habitat complexity and coral reef fish diversity and abundance on Red Sea fringing reefs[END_REF][START_REF] García-Charton | Multi-scale spatial heterogeneity, habitat structure, and the effect of marine reserves on Western Mediterranean rocky reef fish assemblages[END_REF][START_REF] Tews | Animal species diversity driven by habitat heterogeneity/diversity: the importance of keystone structures[END_REF][START_REF] Gratwicke | The relationship between fish species richness, abundance and habitat complexity in a range of shallow tropical marine habitats[END_REF][START_REF] Pittman | Multi-scale approach for predicting fish species distributions across coral reef seascapes[END_REF][START_REF] Kovalenko | Habitat complexity: approaches and future directions[END_REF]. Regarding ARs, it is important to consider the different scales of their combination. Indeed, artificial reefs are first designed as a unitary module. These unit modules can be immersed in aggregate, and several aggregates can form a village [START_REF] Charbonnel | Artificial Reefs in Marseille : From Complex Natural Habitats to Concepts of Efficient Artificial Reef Design[END_REF]Cépralmar, 2015;[START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF]. When combined together, modules offer a heterogeneity of structure of different complexity.

Based on the specific combinations of the artificial reefs and inspired by different indexes of complexity used on the natural environment, we propose a method to evaluate the theoretical structure of artificial reefs from the modules to any kind of combination of modules.

We hypothesised that (i) the index of complexity proposed will increase according to the different variables chosen, (ii) and could help to categorise and classify the reefs with a standardized numerical method.

Material & method 2.1. The numerical object of artificial reefs and fictive objects

To test the influence of the structural parameters on the indexes, we created 7 different fictive 3D computer aided design (CAD) models. From one simple cube of 1 m 3 , we increased the surface complexity using a three steps iterative process. Then, we added successively circular cavities of different size three times (Figure IV-1). Those fictive 3D CAD models have been created on the online free access software Tinkercad for 3D computer aided design (CAD).

An STL file, that describes the surface geometry of a 3-dimensional object, was generated and exported. In order to evaluate the structural parameters on ARs modules, we also sampled 16 different artificial reefs used in France. The dimensions and shapes have been collected in the literature [START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF]. Most of the 3D CAD models have been produced thanks to the online free access software Tinkercad. More complex structures such as the one developed by Boskalis © were directly provided by the company (Figure IV-2). Dimensions, shapes, origin, and references are available in supplementary materials (Annexe 4).

Point clouds and normals

The mesh 3D CAD models have been exported to Cloud Compare in order to get similar points resolutions for each 3D CAD models. Cloud Compare is a 3D points cloud (and triangular mesh) processing software, including many advanced algorithms (registration, resampling, colour/normal/scalar fields handling, statistics computation, sensor management, interactive or automatic segmentation, display enhancement, etc.). The surface meshes have been transformed in points cloud with coordinates X Y Z. Three different densities of points by square unit have been exported for the fictive 3D CAD models (density per square unit: 1, 5 and 10) to determine the variability of the indexes according to the density. For each point (or vertex), a normal has also been exported (Figure IV-4). The normals are the directional cosines (cosx, cosy, cosz) of the normal vector of each point with respect to the orthogonal plane of the 3D CAD models, each directional cosines varies between -1 and 1. In three dimensions, a normal vector to a surface at point P is a vector perpendicular to the tangent plane of the surface at P, it gives the orientation of each vertex that composed the 3D CAD model.

Combination of modules

As an example, we evaluated known existing combinations of artificial reef modules.

One village of the Larvotto Marine Protected Area (MPA) at Monaco, is composed of BOSK modules. One village at the MPA of Roquebrune Cap Martin, is composed of CR14 modules.

Finally, one village at the MPA of Cap d'Agde, is composed of PIPE and STBS.

Evaluation of the structure 2.5.1. Module scale

Porosity, "Poro"

We proposed an Index called "Poro" that varies between 0 and 1. It is defined by the empty volume ratio (defining cavities) relative to the occupied volume (defined by the volume of the bounding box, computed on MeshLab, in which the 3D CAD model fits). It is determined by the following equation: Based on the area ratio. We proposed a normalized Index called "Topo" that varies between 0 and 1. It is determined by the following equation:

EQUATION 2: 𝑇𝑜𝑝𝑜 = 1 -(𝑆𝑜 𝑆𝑡 ⁄ )
With:

𝑆𝑜: surface occupied by the 3D CAD model, determined by the length and width of the bounding box on MeshLab.

𝑆𝑡: the total surface of the 3D CAD model

Fractal dimension, "Dn"

The fractal dimension has been computed thanks to the function "est.boxcount" of the package "Rdimtools" available on the open-source software R (3.4.2), the script used to determine it is available in the supplementary material (Annexe 3). The amount of r (radius) to be tested was set to 100 and the vector of ratios for computing estimated dimension in (0,1) was set to (0.1, 0.9).

Box-counting dimension, also known as the Minkowski-Bouligand dimension, is a popular way of figuring out the fractal dimension of a set in a Euclidean space. Its idea is to measure the number of boxes required to cover the set repeatedly by decreasing the length of each side of a box. It is defined as:

EQUATION 3: 𝐷 = 𝑙𝑖𝑚 𝑟→∞ ( 𝑙𝑜𝑔𝑁(𝑟) 𝑙𝑜𝑔( 1 𝑟 )
)

With: 𝑁(𝑟): the number of boxes with radius r needed to cover a given set.

𝑟: radius of boxes

The fractal dimension of an object in a 3D space ranges between 2 and 3: 2 is an object with a smooth shape and 3 an object highly folded. We normalized the results between 0 and 1 with the following equation:

EQUATION 4: 𝐷 𝑛 = 1 -(3 -𝐷)
The standard deviation of the normal "SDnz" Various variables derived from normals were used in benthic surface irregularity analyzes [START_REF] Carleton | Effects of substratum irregularity on success of coral settlement: quantification by comparative geomorphological techniques[END_REF][START_REF] Beck | Comparison of the measurement and effects of habitat structure on gastropods in rocky intertidal and mangrove habitats[END_REF][START_REF] Beck | Separating the elements of habitat structure: independent effects of habitat complexity and structural components on rocky intertidal gastropods[END_REF][START_REF] Grohmann | Surface Roughness of Topography : A Multi-Scale Analysis of Landform Elements in Midland Valley, Scotland[END_REF][START_REF] Kovalenko | Habitat complexity: approaches and future directions[END_REF]Young et al., 2017). These studies have their source in the method proposed by [START_REF] Hobson | Surface Roughness in Topography: A Quantitative Approach[END_REF] offering diverse values to identify surface topography: strength vector, vector dispersion, several standard deviations to the plane. In our case, vector strength and vector dispersion are not relevant to highlight complexity. This is explained by the fact that we study volume objects, not only surface. The orientation of the surface of a volume, even for a single cube, will always be higher than a surface, except if it is refolded and create a volume. This index remains interesting for surface studies at finer scales.

We therefore used the standard deviation of the normal with respect to the Z axis. The script used on R to determine it, is available in the supplementary material (Annexe 3). It gives the variation of the orientation of the normals on the vertical plane. If the object is flat SDnz is equal to zero, and increase each time there is an elevation or a depression of the surface. This SDnz index gives a more adequate value for determining the variability of the orientation of 3D CAD models that we are studying. It varies between 0 and 1. It is calculated with the following equation:

EQUATION 5: 𝑆𝐷 𝑛𝑧 = √ 1 𝑛 ∑ (𝑐𝑜𝑠 𝑛𝑧 𝑖 -𝑐𝑜𝑠 𝑛𝑧 ) 𝑖 1 ² With :
𝑖: each vertex 𝑛: number of vertices that composed the 3D CAD models 𝑐𝑜𝑠 𝑛𝑧𝑖 : directional cosines of the normal of each vertex with respect to the Z axis.

𝑐𝑜𝑠 𝑛𝑧 : mean of the directional cosines of the normal of the vertex that composed the 3D CAD models with respect to the Z axis

Global index of complexity at the module scale, "C"

The score for the module is determined by the sum of the different indexes. It varies between 0 and 4, with the following equation: EQUATION 6: 𝐶 = 𝑃𝑜𝑟𝑜 + 𝑇𝑜𝑝𝑜 + 𝐷𝑛 + 𝑆𝐷𝑛𝑧

Combination of modules at different scales

The difference between scales is defined by the area occupied on the ground. If the space between unitary modules does not exceed the ground area occupied by a unitary module, it constitutes an aggregate. A village is therefore composed of several modules or aggregates whose surface which separates them is greater than the surface occupied on the ground by the modules or aggregates which compose it [START_REF] Charbonnel | Artificial Reefs in Marseille : From Complex Natural Habitats to Concepts of Efficient Artificial Reef Design[END_REF]Cépralmar, 2015;[START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF].

We identified 2 different types of combinations: 2 types of aggregation and 2 types of the village. AG_COMN is a complex of 14 COMN modules assembled 3 by 3 in length and 2 by 2 in height & width, occupying 146 m 3 [START_REF] Blouet | Suivi scientifique des récifs artificiels au large de la commune d'Agde[END_REF]. This kind of aggregate can be found at the MPA of Cap d'Agde. AG_CR14 is composed of 35 CR14 modules assembled in chaos and occupying 270 m 3 , this aggregation is part of one village settled in the MPA of Roquebrune Cap Martin [START_REF] Bodilis | Monitoring of the artificial reef fish assemblages of golfe juan marine protected area (France, North-Western Mediterranean)[END_REF]. VL_BOSK is composed of 6 modules BOSK that occupy 780 m 3 ; 2 BOSK modules are positioned at each corner of an equilateral triangular shape plane, this village is settled in the Larvotto MPA of Monaco (Monaco: 43.74582°N 7.440709°E). Finally, VL_Z3AD is composed of 2 modules of PIPE and five modules of STBS and occupies 585 200 m 3 , it is settled in the MPA of Cap d'Agde called "Zone 3" [START_REF] Blouet | Suivi scientifique des récifs artificiels au large de la commune d'Agde[END_REF].

Weight for the different scale, "W"

We added a supplementary weight called "W" depending on the combination scale: 1 for the aggregation and 2 for the village.

Weighted mean Complexity, Cw

In order to determine the complexity at the higher scales (aggregation, village, fields), we calculated the mean complexity weighted by the volume of each module. The following equation was used:

Heterogeneity: Structural diversity, "H'"

We used structural diversity in order to determine the diversity of the microhabitat that composed the global habitat of the artificial reef. We computed the Shannon diversity (H') index on the volume of the different modules that compose the aggregate of the village. The Shannon index was calculated with the following equation:

Volume occupied, "V"

To discriminate between aggregates or villages that would have the same volume occupied but with a different number of modules, we used the ratio of the total volume of modules that compose the aggregate on the volume occupied by the aggregate.

EQUATION 9: 𝑉 = (𝑉𝑟 𝑉𝑜 ⁄ )

𝑉𝑟: volume of all the modules of the combination.

𝑉𝑜: volume occupied by the combination, computed as follows: 𝑉𝑜 = 𝑆. 𝑚𝑎𝑥(ℎ)

With:

𝑆: surface at the ground 𝑚𝑎𝑥(ℎ): maximum height reached by the artificial reefs of the village.

Combination score, "S"

The score for aggregation is determined by the sum of the different indexes of complexity with the following equation: using the "Hmisc" package. We used the Pearson test to determine if all the variables were correlated with the increasing complexity of the fictive object. The PCA performed on the complexity variables, have been processed with the package "FactoMineR". The hierarchical clustering was done on principal components with the HCPC function of "FactoMineR". The best cut of the dendrogram has been determined by K-means cascading with the cascadeKM function of the package "vegan". It creates several partitions forming a cascade from a small to a large number of groups (2 to 8 in our case).

The Calinski-Harabasz (CH) criterion has been used to select the best partition (Calinski-Harabasz (1974). The maximum value of CH usually indicates the correct number of groups.

The FunctionCatdes of the package FactoMineR was then used on the Euclidean distance matrix of the scaled complexity variables to describes the clusters.

3. Results

3D fictive 3D CAD models

The density of the points cloud has few incidences on the computation of the variable SDnz (Figure IV-5.A). However, for the computation of the fractal dimension the density was determinant, the more the object was getting complex and the more the computation of the ). For each variable, the higher gap was between MF05 and MF06, corresponding to the second step of cavities integration. The index of complexity ranges between 2.12 for the module CR02 and 2.75 for the module STBS. According to the different variables, the modules do not show the same classification (Table IV -2). Dn ranges between 0.04 (CR01) and 0.30 (BOSK and STBS). SDnz ranges between 0.31 (CR02) and 0.80 (SEAR). Topo ranges between 0.67 (SEAR) and 0.94 The first dimension, which represented 51% of total inertia, mainly structured the factor map. The second dimension also explained a large part of the total inertia (33.6%), while the third and fourth dimensions explained less than the mean threshold determined by the numbers of variables (Dim3:13.15%, Dim4:2.30%, <mean threshold 1/4 = 25%), and were not retained for the analysis. The first two dimensions showed a good projection of the data, as all variables were close to the correlation circle, and individuals had cumulative squared cosines above 0.6 on these two dimensions, except the modules KHEO (cumulative squared cosines=0.19), that was better explained by the third and fourth axis (cumulative squared The mean of the complexity index weighted by the volume stays the same for the two aggregations and the village VL_BOSK, since they are composed of one type of modules only.

Evaluation of the structure of the AR modules

Combination of modules

For the same reason, these three combinations don't show any structural diversity.

Discussion

The development of different fictive 3D CAD models enabled us to test the best resolution to compute Dn and SDnz values. The density of 10 points per square unit was determined as a good threshold between time and efficiency of the computation. The increasing complexity of these fictive 3D CAD models was strongly correlated with all the variables (Dn, SDnz, Topo, and Poro). The fractal dimension has long been used as a variable to determine the complexity of habitats. In our case study, this is the variable that had the strongest correlation with the developed complexity index (C) for the evaluation of the artificial reefs' modules. However, it is not to be considered alone, because fractal dimension is difficult to interpret without other parameters to describe the structure [START_REF] Tokeshi | Habitat complexity in aquatic systems : fractals and beyond[END_REF]. The other variables gave us more informative values to describe complexity. The SDnz was particularly sensitive to circular shapes. In fact, the refolding aspect of the surface on the fictive 3D CAD models has a stair-like aspect, and the stair orientation is the same from the cube to the highest level of refolding. This explains why SDnz increased only when cavities are added, because their circular shapes add new orientations. The same remark can be made with the variable Topo. Indeed, the two first 3D fictive 3D CAD models have the same deployed surface but with a different arrangement. However, these refolding implied differences, it brings shaded surfaces that could imply differences in settlement of epibiont and attraction for mobile species [START_REF] Bohnsack | Habitat structure and the design of artificial reefs[END_REF][START_REF] Pickering | Artificial reefs and fisheries exploitation: A review of the 'attraction versus production' debate, the influence of design and its significance for policy[END_REF][START_REF] Underwood | Predicting Epipelic Diatom Exopolymer Concentrations in Intertidal Sediments from Sediment Chlorophyll[END_REF][START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF][START_REF] Lam | Induction of larval settlement in the polychaete Hydroides elegans by surfaceassociated settlement cues of marine benthic diatoms[END_REF]. Another variable highlighting the shaded faces should be implemented to improve the characterisation of the surface. These results again support the importance of considering several variables in order to define the complexity of an object and that none prevails to another. Indeed most of the studies used several variables to identify the complexity of the surface (e.g. [START_REF] Beck | Comparison of the measurement and effects of habitat structure on gastropods in rocky intertidal and mangrove habitats[END_REF][START_REF] Beck | Separating the elements of habitat structure: independent effects of habitat complexity and structural components on rocky intertidal gastropods[END_REF][START_REF] Frost | Measuring surface complexity in ecological studies[END_REF][START_REF] Gratwicke | The relationship between fish species richness, abundance and habitat complexity in a range of shallow tropical marine habitats[END_REF][START_REF] Matias | Independent effects of patch size and structural complexity on diversity of benthic macroinvertebrates[END_REF][START_REF] Pittman | Multi-scale approach for predicting fish species distributions across coral reef seascapes[END_REF][START_REF] Bryson | Characterization of measurement errors using structure-from-motion and photogrammetry to measure marine habitat structural complexity[END_REF]C.A. Sánchez-Caballero et al., 2017;Young et al., 2017). Finally, the variable Poro, as the normalised fractal dimension was the only variable that varies at each step of complexification. To the best of our knowledge variables related to porosity are rarely used in complexity studies. It is certainly due to the difficulty to evaluate it in natural environment. The index of porosity we proposed is based on the volume occupied by the bounding box. For the artificial reef modules, the modules that had a low complexity value were those with the highest porosity values. It would then be interesting to determine a threshold of porosity according to the desired objectives. Such a threshold is difficult to determine [START_REF] Sherrard | Temporal variation of an initial marine biofilm community and its effects on larval settlement and metamorphosis of the tubeworm Hydroides elegans[END_REF]. Moreover, this variable did not give us information about the quality of this porosity. Is this porosity a result of several cavities or of a single cavity.

Improvements are needed to complement this information.

For now, this numerical method gave us the first opportunity to evaluate the complexity of the structure of ARs modules and to distinguish different types of artificial reefs. The principal component analysis and its clustering on the different variables computed on the 3D CAD models of ARs, gave us a good representation of the different aspects of their complexity. In fact, we distinguished 6 principal clusters. Among them we can highlight 4 principal types of artificial reefs with clusters 1, 2, 3 and 6. Cluster 1 (COMN, CR01, BONN, and TIPY) shows the highest porosity (Poro> 85%), and lowest fractal dimension (Dn<0.10). Indeed, it represents geometrically hollowed-out modules, that looks like "cage" shapes. The low value of Dn highlighted the simple geometry of their structure, basically composed of lines. This type of module is inspired by Japanese modules, preferentially used to attract pelagic fish. The BONN and TIPY can be effective as one module, but the modules COMN and CR01 need to be installed in aggregates on several floors to be effective [START_REF] Bodilis | Suivi des peuplements ichtyologiques des récifs artificiels des zones marimes protégées des Alpes-Maritimes[END_REF], Cépralmar 2015[START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF]. However, this type of ARs cannot reconstitute a rocky habitat, their "cage" structure does not offer shelters for demersal species and surfaces to favour colonization of sessile species. Indeed, in this purpose, BONN modules have been often post-complexified in several MPA in order to increasing species richness, abundance and biomass of fish assemblages [START_REF] Charbonnel | Effects of increased habitat complexity on fish assemblages associated with large artificial reef units (French Mediterranean coast)[END_REF][START_REF] Bodilis | Suivi des peuplements ichtyologiques des récifs artificiels des zones marimes protégées des Alpes-Maritimes[END_REF], 2011). Cluster 2 (SALB, CR14, CR02), could be defined as the "Box" type, it shows the lowest SDnz. Indeed, it represents simple geometric shapes that look like "box" widely opened on the top and down, and showing smaller opening on the side. It has basically four different orientations of the surface. However, it presents enough surface deployed to begets settlement of sessile species, and to provide wide shelter for demersal species. As the modules BONN and CR01, these latter are most of the time installed in aggregation to increase their efficiency, and can attract pelagic species if it reached a certain height [START_REF] Bodilis | Suivi des peuplements ichtyologiques des récifs artificiels des zones marimes protégées des Alpes-Maritimes[END_REF], Cépralmar 2015[START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF]. The Cluster 3 (SEAR, NEGR, FAKR), mainly defined by their low topography, could be defined as the "bock" type.

NEGR and FAKR are composed of a plateau on which is erected large circular or rectangular arises, whereas NEGR holds rather triangular shapes with oblique faces. All of them has no cavities, their solid shapes can explain their low topography. These modules are used for protection against trawling (Cépralmar 2015[START_REF] Tessier | Assessment of French artificial reefs: due to limitations of research, trends may be misleading[END_REF]. In this context, the importance of surface deployment is not of great interest and their best asset is to be a strong enough structure to prevent trawling. Finally, cluster 6 (BOSK, PIPE, STBS) could be defined as the "nested" type, it shows the highest fractal dimension (Dn) and topography (Topo). The reefs PIPE and STBS are composed of several units nested. PIPE is composed of two single pipes, one smaller in a bigger one. STBS is composed of various other modules: a steel rectangular basket that collects 2 single pipes, 4 SALB, and 32 block works arranged on two floors. Finally, the BOSK module is the first artificial reef designed by 3D printing, it has a unique shape and much more complex than most of the modules of artificial reefs designed in a classical way, this technic allows to bring up in one single module the same complexity as the one nested. these modules give a wide surface to be colonized by benthic sessile species and nice shadow shelters and diverse surface orientation. Regarding the modules of the remaining clusters 4 and 5, BONP could be integrated with the box type. This module was immersed in aggregation like the ones of the cluster 2, however its cylinder shapes increased its surface orientation explaining why it was not gathered with the cluster 2 that shows low SDnz. The KHEO is an anti-trawling module, however its shape is not solid as the other modules that composed the cluster 3 (block type), indeed it shows a higher porosity. Finally, DALO is composed of one big cubic unit with 2 CR01 nested inside, and could be gathered in the cluster 6, but it shows a very low fractal dimension (Dn) compared to the module of this cluster that show the highest value of fractal dimension.

This method seems effective in identifying different types of reefs and sufficiently sensitive to highlight the inherent variability of each module.

Conclusion

This first evaluation of modules of artificial reefs and module composition, proves to be promising. Indeed, we have been able to develop a method distinguishing the artificial reefs according to 4 numerical variables and to classify them according to their structure from the module until the different possible module combinations. Some improvements could be done in order to better characterize the porosity and the surface appearance according to its exposure to light and/or waves. However, this first evaluation of ARs could be expanded and used in the future to evaluate designs of ARs before their production and immersion. The collection of monitoring data on different type of artificial reefs would make it possible to assess the efficiency of this method. It would be possible to determine type of profile according their structural parameter that could favour the recruitment of juveniles or adults, or maybe species of economical or ecological interest. Some perspectives for the evaluation of natural habitat structures are also feasible. Indeed, with photogrammetry technology, it is now possible to reproduce the structure of natural habitats in marine environment [START_REF] Bryson | Characterization of measurement errors using structure-from-motion and photogrammetry to measure marine habitat structural complexity[END_REF][START_REF] Riera | An easy method to assess 3D underwater habitat complexity Riera[END_REF], our method could be used on 3D CAD models created by photogrammetry. The comparison of AR with the natural environment and the value of their different complexity parameters could help to design structures that best mimic natural habitat for restoration purposes and for targeting species of interest according to their natural habitat.

Introduction

The biofilm formation is linked to the chemical parameters of the substrate and the surrounding environment (Callow & Callow 2002[START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]. Motile bacteria are known to sense the surface and to be able to choose to adhere or not to a substrate [START_REF] Wahl | Marine epibiosis. I. Fouling and antifouling: some basic aspects[END_REF][START_REF] Cooksey | Adhesion of bacteria and diatoms to surfaces in the sea : a review[END_REF][START_REF] Callow | Biofilms[END_REF]; whereas diatoms sink on it by change and adhere to substrate by secreting large amount of EPS [START_REF] Cooksey | Adhesion of bacteria and diatoms to surfaces in the sea : a review[END_REF][START_REF] Wetherbee | The first kiss: Establishment and control of initial adhesion by raphid diatoms[END_REF]. The attachment of these microorganisms depends directly on the physical aspect of the substrate [START_REF] Hunt | The effect of substrattum roughness and river flow rate on the developpement of a freshwater biofilm community[END_REF][START_REF] Patil | Biofilm diatom community structure : Influence of temporal and substratum variability[END_REF][START_REF] Teughels | Effect of material characteristics and/or surface topography on biofilm development[END_REF][START_REF] Truong | The influence of nano-scale surface roughness on bacterial adhesion to ultrafine-grained titanium[END_REF][START_REF] Cui | Effects of Carrier Material and Design on Microalgae Attachment for Biofuel Manufacturing: A Literature Review[END_REF]. Indeed, a flat surface gives fewer anchoring points than a rough surface [START_REF] Huang | Enhancing microalgae biofilm formation and growth by fabricating microgrooves onto the substrate surface[END_REF]). However, the increase of surface roughness on a very small scale (50 to 300 nm) enhance the surface wettability of hydrophilic surface [START_REF] Singh | Quantitative characterization of the influence of the nanoscale morphology of nanostructured surfaces on bacterial adhesion and biofilm formation[END_REF]) that prove to decrease cell bacteria attachment [START_REF] Cooksey | Adhesion of bacteria and diatoms to surfaces in the sea : a review[END_REF][START_REF] Cerca | Quantitative analysis of adhesion and biofilm formation on hydrophilic and hydrophobic surfaces of clinical isolates of Staphylococcus epidermidis[END_REF]. The aspect of the surface can influence also the diversity of microorganisms and their physiology; the more the surface area of contact will be diverse, the more organisms with different body size would settle [START_REF] Battin | Microbial landscapes: New paths to biofilm research[END_REF][START_REF] Myan | The interaction of marine fouling organisms with topography of varied scale and geometry: A review[END_REF][START_REF] Huang | Enhancing microalgae biofilm formation and growth by fabricating microgrooves onto the substrate surface[END_REF].

The objective of this study is to determine if the physiology of photosynthetic microorganisms is linked or not with microtopography of the associated substrate. According to the topography of the substrate, we hypothesized that (i) the photosynthetic organisms will aggregate on the surface and (ii) might have different physiological responses. File Format or Stanford Triangle Format) but also a cloud of points with, for each point, its coordinates x, y, z. The software MeshLab ©, [START_REF] Cignoni | MeshLab : an Open-Source Mesh Processing Tool[END_REF]) is used to manipulate the different PLY and CloudCompare © software, is used to sample meshes in scatter plots at a very fine resolution (1000 point per unit squared) to defines more precisely the surface for indexes that are sensible to resolution (fractal dimension (D) and roughness (R)). Each mesh has been processed so that the different surfaces can be compared to one another by making a mean plane: the orientation of the 3D objects in the space has been standardized, the area of interest has been extracted from each brick and then used to define the origin of the z axis (altitude) of each 3D model.

Index of complexity to define microtopography

As far as possible, we used the same complexity indices developed in the previous part (chapter XX section XX). Some adaptations were necessary for the Topo index, and the poro index was not calculated in this study as it requires a volume and cannot be computed on surfaces.

irregular orientation. As SDnz, this index is based on the directional cosines of each triangle's normal vector (cosx, cosy, and cosz). it is determined by the following equations:

EQUATION 13: 𝑅1 = √ (∑ 𝑐𝑜𝑠 𝑥 𝑖 1 ) 2 + (∑ 𝑐𝑜𝑠 𝑦 𝑖 1 ) 2 + (∑ 𝑐𝑜𝑠 𝑧 𝑖 1 ) 2 EQUATION 14: 1 𝑘 ⁄ = (𝑖 -𝑅1)(𝑖 -1) -1
𝑖: is the number of points.

𝑐𝑜𝑠 𝑥 : is the directional cosine of a point's normal vector in the X direction.

𝑐𝑜𝑠 𝑦 : is the directional cosine of a point's normal vector in the Y direction.

𝑐𝑜𝑠 𝑧 : is the directional cosine of a point's normal vector in the Z direction.

Analyse of biofilm activity by Imaging PAM

After the preliminary test, only the samples retrieved after one week has been retained

for the analyses because the others showed a high abundance of organic matter that saturate Each index is therefore a proportion of use of total light energy. Indeed, the cumulation of these three parameters is always equal to 1, and is calculated by the following equation:

EQUATION 18: 𝑌(𝐼𝐼) + 𝑌(𝑁𝑂) + 𝑌(𝑁𝑃𝑄) = 1

Relative electron transporting rate "Ek" & maximal saturation brightness values ETRmax

The rETR (relative Electron Transport Rate) is calculated by the following formula:

EQUATION 19: 𝑟𝐸𝑇𝑅 = 𝑌(𝐼𝐼) × 𝑃𝐴𝑅 × 0.84 × 0.5

This formula takes into account the quantum yield as well at a given light intensity (PAR in µl quantat.m-2.s-1). 0.84 is the average ratio of light absorbed by a leaf and does probably not reflect that of our biofilm. It is necessary to divide by two to obtain the rETR because there are two photosystems and we make the assumption that the two photosystems have the same

scale

Even if in the previous study we identified no significant differences in biofilm communities between substrates (Chap. 1 & Chap. 2). We showed however that the use of chemically different substrates has an impact on biofilm formation according to their chemical and physical characteristics which is coherent with results from [START_REF] Teughels | Effect of material characteristics and/or surface topography on biofilm development[END_REF].

In the present study, several patches were selected within the same substrate at different scales. This allowed determining if the change of topography within the same substrate (which imply same chemical characteristics) influences the distribution and the physiology of the communities. The different scale selected and the number of patches is described below: 4. Medium scale (0.55 cm) : 10 patches per samples (total of 30 patches per substrate) 5. Small scale (0.25 cm): 20 patches per samples (total of 60 patches per samples) 3. Results

Characterisation of the surface of substrates at the global scale

Table IV-4: Mean of the complexity indices on the three substrates (concrete, dolomite, rock) on the total surface

Overall the set of indexes shows coherent value to characterize the surface of the substrate (Table IV -4). Indeed, dolomite and concrete that show complex surface compared to the smooth surface of the natural rock, showed the highest value for all the parameters (Table IV . Concrete and dolomite showed equivalent roughness (R) and variation of the orientation of the surface according the Z axis (SDnz). However, the two surfaces are very different, dolomite shows a homogeneous roughness due to the grain size of the dolomite sand, whereas concrete shows a heterogeneous roughness linked to a smooth surface punctuated by relatively deep holes due to the various air bubbles present during its manufacture. These differences are well described by the vector dispersion (ik) and the normalized fractal dimension (Dn). Indeed, higher value of ik expresses a more diverse orientation of the faces; and higher fractal dimension expresses a self-repeated aspect or a more refolded surface. These two indexes highlight these aspects of dolomite due to the grain size.

Characterisation of the biofilm activity with Imaging PAM and correlation with complexity indexes

The activity of the organisms resulting from the Imaging Pam showed that the absorbance was significantly stronger on the natural rock than on the other two substrates

Y ( i i ) Y ( N P Q ) Y ( N O ) A b s . E T R m a x E k Y ( i i ) Y ( N P Q ) Y ( N O ) A b s . E T R m a x E k R 0 0.
Y ( i i ) Y ( N P Q ) Y ( N O ) A b s . E T R m a x E k Y ( i i ) Y ( N P Q ) Y ( N O ) A b s . E T R m a x E k R 0.
Y ( i i ) Y ( N P Q ) Y ( N O ) A b s . E T R m a x E k Y ( i i ) Y ( N P Q ) Y ( N O ) A b s . E T R m a x E k R -0.

Discussion

In the present study, the use of Imaging Pam to characterize the physiological parameters of the photosynthetic biofilm communities, allowed to determine if the change of structure complexity of the surface within the same substrate influences the distribution and the physiology of the communities. At first sight, the three substrates have very different topographies. The vector dispersion (ik) and fractal dimension (D) where the index that revealed differences between each substrate, while the variation of normal to the z axis (SDnz)

and roughness (R) separates the rock from the other two substrates. However, the use of different indexes helps to define the broad spectrum of surface profile, giving information about the surface orientation, its roughness aspect, how the surface is self-repeated and refolded in the space and highlight different correlations with imaging pam indexes. The indexes related to normals (ik and SDnz) proved to be redundant as they show similar correlation on concrete and dolomite with photosynthetic activity. In the previous section, SDnz was used because it was more adapted to 3D volume object (Chap.3, Part I). However, [START_REF] Carleton | Effects of substratum irregularity on success of coral settlement: quantification by comparative geomorphological techniques[END_REF], had shown that ik was the best indexes to describes link between coral settlement and substratum irregularity compared to SDnz. Young et al., (2017), used it also with success on coral reef 3D photogrammetric models. Then according to the type of object study (3D surface, 3D volume object) ik or SDnz could be used and could give equivalent information related to the orientation of the surface. On the other hand, the fractal dimension (D) and the roughness index (R) has to be used with caution, because their computation is very sensible to the chosen resolution. Indeed, the number of points to define a surface must be at the highest possible resolution to truly mimic the surface, otherwise the spaces between the points may induce computational errors at very small scales. However, increasing the resolution will highly impact the computation time process. These two indices should therefore be used with caution and indicate precisely the resolutions used and the calculation methods to be able to compare the results with future studies.

Depending on the substrates, we observed that the activity of the biofilm did not respond to the same complexity parameters and that these relationships could also change from one scale to another. At first glance, smooth surface hosts more abundant communities, but when looking at small scale, within rock and concrete that present smoother area compare to dolomite, this relation is shifted. These results imply that even on a very smooth surface, when focusing on the smallest scale, the micro topography influence positively the abundance of individuals. This is in accordance with modern ecological concepts which state that ecological niches of microorganisms are influenced by the landscape that corresponds to their body size [START_REF] Battin | Microbial landscapes: New paths to biofilm research[END_REF]. Indeed, at the µm scale, grooved surface instead of flat surface increase biomass by giving anchor point and shelter from disturbance [START_REF] Huang | Enhancing microalgae biofilm formation and growth by fabricating microgrooves onto the substrate surface[END_REF], and between different topographies, some with high isotropy, provide less surface of contact and decline attachment of cells [START_REF] Myan | The interaction of marine fouling organisms with topography of varied scale and geometry: A review[END_REF].

Regarding photosynthetic activity and light saturation, whatever the substrates type or scale, when correlation was significant, they were positive. Organisms show a higher yield of photosynthetic activity and adaptation to high irradiance (i.e. hight Ek and low NPQ) when the surface orientation is more irregular. It can be explained by the fact that organisms may not receive the same light dose during their lifetime as they are not always oriented in the direct axis of light (Iluz & Dubinsky 2013). It is likely that they adapt their photosynthetic apparatus to the highest light conditions they are potentially exposed to in order to avoid photoinhibition.

In the microphytobenthos, biofilm diatoms are known to do vertical migration and to use physiological mechanisms as xanthophyll cycle and modulation of rETR to prevent damage from high irradiance [START_REF] Cartaxana | Physiological versus behavioral photoprotection in intertidal epipelic and epipsammic benthic diatom communities[END_REF][START_REF] Serôdio | Efficiency of photoprotection in microphytobenthos: Role of vertical migration and the xanthophyll cycle against photoinhibition[END_REF]. It is, therefore, possible for diatoms to migrate similarly within the protected valleys conferred by topography or to simply adapt their physiology to the light intensity according to their niche provides.

Conclusion

Taking together, these results suggest that with some adaptations indexes used at macroscale can characterized the microscale and revealed some differences according these different parameters. Indeed, micro-complexity have positive influence on the abundance of species, but this relation has to be studied at the appropriate scale. Moreover, the surface orientation plays a key role the physiology and perhaps in the behaviour of the biofilm that show preservative adaptation to light. The micro-complexity of the substrate constitutes various niches for microorganisms, that induce the distribution and activity of the different microbial communities within the biofilm.

V. DISCUSSION GENERALE Outre ces considérations appliquées au domaine des récifs artificiels, ces résultats nous ont permis de suivre l'évolution temporelle des communautés de biofouling sur une période d'un an. Afin de discuter plus amplement de la stabilité des communautés du macrofouling, un suivi sur plusieurs années aurait été souhaitable. Néanmoins, nous avons pu étudier les premières étapes de colonisation d'un habitat, ce que seule l'immersion de nouvelles structures telles que les récifs artificiels peut permettre. Alors que les populations de poissons semblent se stabiliser rapidement (2-3 mois), il est difficile d'observer une stabilité des assemblages de macrofouling après deux ans d'immersion. Ceci serait lié à des perturbations physiques fréquentes auxquelles les assemblages de macrofouling seraient plus sensibles [START_REF] Cummings | Colonization of a nearshore artificial reef at Boca Raton (Palm Beach County), Florida[END_REF]. En effet, un certain équilibre au sein des communautés serait atteint au bout de 4 ans [START_REF] Ardizzone | Prediction of Benthic and Fish Colonization on the Fregene and other Mediterranean Artificial Reefs[END_REF][START_REF] Falace | Periphyton' Colonization: Principles, Criteria and Study Methods[END_REF]. Il semble malgré tout difficile de prédire précisément les mécanismes qui définissent l'établissement des communautés. Nous avons pu observer des successions d'assemblages avec le biofilm comme premier maillon, suivi par des communautés algales monospécifiques, et enfin des communautés plus diverses composées de brouteurs, filtreurs et suspensivores. Ce schéma suit la « fouling sequence » expliquée par [START_REF] Wahl | Marine epibiosis. I. Fouling and antifouling: some basic aspects[END_REF]) et est conforme aux successions écologiques relatives à la théorie du climax [START_REF] Clements | Nature and Structure of the Climax[END_REF]. Cependant, la dynamique temporelle des différentes étapes de succession concernant le macrofouling semble très variable selon les sites d'immersion (Chap. 2). Il est donc très probable que la diversité des communautés soit avant tout déterminée par les conditions environnementales locales qui influent majoritairement sur le recrutement des larves et des spores [START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF]. Les diverses étapes de succession des communautés seront fonction des perturbations physiques du milieu, des événements aléatoires météorologiques voire anthropiques, ou encore des interactions liées à la compétition interspécifique [START_REF] Cummings | Colonization of a nearshore artificial reef at Boca Raton (Palm Beach County), Florida[END_REF][START_REF] Svane | On the Problems of Epibioses, Fouling and Artificial Reefs, a Review[END_REF]. L'ensemble de ces perturbations imprévisibles nous éloigne de l'établissement d'une communauté selon le schéma d'une succession atteignant un climax, et nous rapproche d'une théorie plus moderne prenant en compte la dynamique de ces événements stochastiques [START_REF] Meiners | Is successional research nearing its climax? New approaches for understanding dynamic communities[END_REF]. Si l'on se focalise sur la dynamique des communautés de biofilm, on observe un schéma similaire quels que soient les sites et les matériaux utilisés. Cela implique que malgré l'aspect stochastique de l'implantation des microorganismes révélé par notre étude, certains cycles sont conservés dans l'évolution d'un biofilm (i.e. adhésion, production d'EPS, ...). Par ailleurs, il est possible que la temporalité sur laquelle nous nous sommes focalisés soit trop longue pour observer des préférences de matériau. En effet, ces interactions se jouent au cours des premières heures d'immersion de la structure pour les microorganismes du biofilm [START_REF] Wahl | Marine epibiosis. I. Fouling and antifouling: some basic aspects[END_REF][START_REF] Callow | Biofilms[END_REF][START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]. Après une semaine, il est possible que la colonisation des espèces pionnières ait déjà modifié largement les propriétés de surface des matériaux et que les seules différences observables soient liées à l'adaptation des communautés par la mise en place de leur matrice extracellulaire [START_REF] Wahl | The second skin : ecological role of epibiotic biofilms on marine organisms[END_REF][START_REF] Dang | Microbial Surface Colonization and Biofilm Development in Marine Environments[END_REF]. Cependant, une identification plus précise des diatomées, par microscopie ou par métagénomique, aurait pu révéler des différences au sein des communautés du biofilm. En effet, les diatomées représentent près de 80% de la biomasse des biofilms marins photosynthétiques et sont responsables de la majorité des sécrétions d'EPS [START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]. Des différences au sein de leur structure auraient pu expliquer cette dynamique temporelle et ces différences entre les sites et les matériaux. (ii) Une étude comparative des communautés épibenthiques et mobiles de différents designs de récifs RA permettrait de déterminer l'influence de la structure des RA sur les communautés à l'aide de la méthode d'évaluation de la structure des RA.

(iii) Sur la base de la structure des habitats naturels qui peuvent être reproduits par photogrammétrie, des mesures de restauration et /ou compensation pourraient voir le jour.

L'utilisation de la méthode d'évaluation de la structure sur ces habitats naturels, permettrait d'imiter leur complexité et leur hétérogénéité et de produire des récifs biomimétiques.

(iv) L'impact des RA sur les milieux naturels qu'ils recouvrent est très peu étudié. L'étude de la sédimentation, de la production de matière organique et de l'activité de la méiofaune à leurs abords permettrait de disposer de nouveaux éléments relatifs à l'influence des RA.

Les résultats de ces différentes recherches permettraient d'améliorer les directives de ### create a loop to process all the indexes in a row for each table ### for (i in 1:length(list)) { cat(paste0("---",Sys.time(),"processing_",list[i]," ---/n")) # to monitor the processing time for each table. M=read.table(paste0(initial.wd,"/",list[i]), h=T, sep=" ") # read each table of the list P=M[,1:3] # extraction of the points from the table N=M[,4:6] # extraction of the normal from the table # computation of Dn outputD=est.boxcount(P, nlevel=100, cut = c(0.1,0.9)) # the result of the function est.boxcount Dn=1-(3-outputD$estdim) # compile the fractal dimension normalized between 0 and 1 # computation of SDnz SDn=as.matrix(apply(N,2,sd)) # processing of the standard deviation on the director cosines SDnz=SD [3] # SD [3] must correspond to the director cosines on the Z axe.

UNEP
# computation of ik cos=as.matrix(apply(N,2, sum)) # sum of the director cosines on each axis i=length(N$Nx) # number of normal R1= sqrt((cos[1,]^2)+(cos[2,]^2)+(cos[3,]^2)) # equation of R1 ik=(i-R1)*(i-1)^-1 # equation of ik # compuation of R P$X2=as.factor(round(P[,1], 1)) # round the points on the X axis vecx=aggregate(M$Z,by=list(P$X2),roughness) # the derivative second of Z curve on the X axis meanVecx=mean(vecx$x) # mean of the derivative second of Z curve on the X axis P$Y2=as.factor(round(P[,2], 1)) # round the points on the Y axis vecy=aggregate(M$Z,by=list(P$Y2),roughness) # the derivative second of Z curve on the y axis meanVecy=mean(vecy$x) # mean of the derivative second of Z curve on the Y axis R=(meanVecx+meanVecy)/2 # computation of R # compilation des indices dans ''output '' output=rbind(output,c(ik,Dn, SDnz, R)) } # sauvegarde du tableau au format csv row.names(output)=list # noms des lignes du tableau correspondant aux modèles numériques colnames(output)=c("ik","Dn","SDnz","R") # rename the columns with the names of the index write.csv2(output,"Complexity_Surface.csv") 190 Annexe 4: Descriptif des récifs artificiels étudiés dans le chapitre 3, partie 1

Ce tableau regroupe : les noms des récifs artificiels étudiés (''Module names''), leurs noms de code (''Code names''), les références utilisées (''References''), le volume (''Total volume (m3)''), la surface (''Total area deployed (m2)'') et le volume occupé (''Bounding box'') récupérés sur Meshlab.

Code names

  : HPLC solvents for amino acid detection....................................................... 58 Table II-3: Mean proportion of pigments over time on each substrate (Cg: grey concrete, Ds: dolomite Sorel cement, Cw: white concrete) ..................................................................... 62 Table II-4: Means of sugar to protein ratio over time on each substrate (Cg: grey concrete, Ds: dolomite Sorel cement, Cw: white concrete) ..................................................... 64 Table II-5: Mean proportion of amino acids over time on each substrate (Cg: grey concrete, Ds: dolomite Sorel cement, Cw: white concrete) ..................................................... 65 Table IV-1:Indexes computed on the 3D fictive 3D CAD models and evaluation of the global complexity (C) .............................................................................................................. 129 Table IV-2: Indexes computed on the artificial reef's modules and evaluation of average values for all the modules ....................................................................................................... 130 Table IV-3: Index and score of the different combinations of artificial reefs .............. 135 Table IV-4: Mean of the complexity indices on the three substrates (concrete, dolomite, rock) on the total surface ....................................................................................................... 149

Figure I- 1 :Figure II- 2 :Figure III- 1 :Figure III- 2 :Figure IV- 2 :Figure IV- 4 :

 121224 Figure I-1 :Illustration japonaise représentant l'utilisation de gabions en bambou ('jakagos') remplis de pierres utilisés pour lutter contre l'érosion des rivières au VIIIe siècle et comme récifs artificiels au XVIIe siècle (source : http://kmcenter.rid.go.th/kcdesign/dblog/wpcontent/uploads/2009/10/history-and-method-of-Gabion1TCNPF-o-Compatibility-Mode.pdf) .................................................................................................................................................. 34

(

  Thierry 1988, Figure 2-1). En Europe, et plus particulièrement dans la partie méridionale du bassin central de la Méditerranée, l'utilisation de dispositifs de concentration de poissons (DCP) remonte à la Rome antique. Ces DCP appelés "Kannizzati" à Malte ou "Incannizati" en Sicile sont encore utilisés aujourd'hui(Bombace 1989, Figure 2-2).

Figure I- 1 :

 1 Figure I-1 :Illustration japonaise représentant l'utilisation de gabions en bambou ('jakagos') remplis de pierres utilisés pour lutter contre l'érosion des rivières au VIIIe siècle et comme récifs artificiels au XVIIe siècle (source : http://kmcenter.rid.go.th/kcdesign/dblog/wp-content/uploads/2009/10/history-andmethod-of-Gabion1TCNPF-o-Compatibility-Mode.pdf)

Figure I- 3 :

 3 Figure I-3 : Illustration de diverses structures artificielles déployées dans les mers européennes : a) Languedoc-Roussillon, France; b), c) Nienhagen, Allemagne (bouches d'égout, d'après NICKELS et al., 2006); d), e) Grèce; f) Sicile, Italie; g) Réserve du Larvotto, Monaco (www.gouv.mc), h) Nordfjorden,Norvège (d'après HARTVIG, 2007); i), j) Algarve, Portugal; k) Odessa, Ukraine(de COLLINS, www.soes.soton.ac.uk), l) Pool Bay, Royaume-Uni (de COLLINS, www.soes.soton.ac.uk) (source :[START_REF] Fabi | Overview on artificial reefs in Europe[END_REF]

Figure I- 5 :

 5 Figure I-5 : Illustration des étapes du projet d'immersion de récifs artificiels conçus par impression 3D (Boskalis/D-Shape) en Principauté de Monaco : a) impression du récif, b) état du module après impression et excavation du matériau excédent, c) immersion d'un module en Principauté de Monaco, d) état d'un module après quelques jours d'immersion, e) f) état d'un module après 2 ans d'immersion (crédit photos : Boskalis, Patrice Francour, Jean-Michel Mille-AMPN, Stéphane Jamme-Les Aquanautes).

Figure I- 6 :

 6 Figure I-6 :Illustration de récifs artificiels réalisés à partir de pneus : a) projet Tire Artificiel Reefs (TAR) immergés en 1997 à Hong Kong (source : https://www.maoandpartners.com/tyre-artifical-reefs/), b) pneus immergés dans les années 1970 à Fort Lauderdale (Floride) dans le but de créer un récif artificiel (source : http://www.geologyin.com/2015/10/floridas-tire-reef-has-turned-into.html)

Figure I- 7 :

 7 Figure I-7 : Illustration du biofouling : a) schéma illustrant le processus de colonisation du biofilm en cinq étapes: 1) phase d'attachement réversible, 2) phase d'attachement irréversible avec production de la matrice extracellulaire, 3) croissance verticale du biofilm 4) biofilm mature, 5) dispersion du biofilm (source : Bixler & Bhushan 2012), b) paysage d'un biofilm microbien colonisant un environnement sédimentaire, la structure des colonies est fonction des flux (en agrégat au niveau des flux lents, en filament au niveau des flux rapides) créant des micro-perturbations qui induisent une dispersion des organismes (source : Battin et al. 2007), c) topographie 3D d'un biofilm composé principalement de diatomées (Amphora sp. Et Navicula sp.) sur des panneaux immergés pendant 3 semaines à Southampton (Royaume-Uni). Le trait pointillé blanc indique la section illustrée en d) représentant la topographie de la surface du biofilm (source :[START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]), e) surface en bois immergée à Southampton (Royaume-Uni) pendant 20 mois avec une communauté complexe de macrofouling comprenant des algues corallines, des vers turbicoles, des éponges et des algues. (source :[START_REF] Salta | Marine biofilms on artificial surfaces : structure and dynamics[END_REF]

Figure I- 8 :

 8 Figure I-8 : Illustration de l'arrangement des récifs artificiels selon l'échelle du module (source : Cépralmar 2015)

1 :

 1 Composition of the solutions used in the modified LOWRY assay protocol 250 µl of the PS fraction were mixed with 250 µl of SDS (2 %) and 700 µl of solution 4, and mixtures were then incubated for 15 min at 30°C. 100µl of solution 5 were added to each tube and vortexed immediately. Mixtures were then incubated for 30 min at 30 °C. The protein concentration was measured with a spectrophotometer at 750 nm (Milton Roy Spectronic Genesys 2). A calibration curve was prepared using bovine serum albumine (BSA) as standard. 1, 2 and 3 solutions with fraction 100 : 1 : 1 (v : v : v).

Figure II- 1 :

 1 Figure II-1: Variation of pigment concentration over time on the different substrates (dashed line: grey concrete Cg, solid line: dolomite Sorel cement Ds, dotted line: white concrete Cw). (Van-der-Waerden test on substrates: p= 0.867)

- 2 (

 2  and were significantly different between dolomite Sorel cement and the two types of concrete (Van-der-Waerden: p = 0.0315, post hoc test: Cg-Ds: p = 0.049; Cg-Cw: p = 0.537; Ds-Cw: p = 0.0104).They increased gradually over the monitoring period on grey and white concretes samples to reach on average 7.904 ± 2.472 µg•cm -2 and 10.546 ± 1.295 µg•cm -2 , respectively, at the end of monitoring. The concentration of sugars in dolomite Sorel cement samples increased slightly, with a maximum mean concentration of 2.733 ± 0.240 µg•cm -2 at the end of monitoring. Protein concentrations ranged between 0.208 and 1.552 µg•cm -2 (Figure II-2) and followed approximately the same pattern as the sugar concentration over time. However, the concentrations did not differ between substrates (Van-der-Waerden: p = 0.322).

Figure II- 2 :

 2 Figure II-2: Variation of (A) sugar concentration (equivalent glucose) and of (B) protein concentration (equivalent BSA) over time on the different substrates (dashed line: grey concrete Cg, solid line: dolomite Sorel cement Ds, dotted line: white concrete Cw). (Van-der-Waerden test on substrates: sugar: p = 0.0315; proteins: p = 0.322)

Figure II- 3 :

 3 Figure II-3: Principal component analysis: A) Ordination of the samples according to sampling time (d01: first day, d07: 1 week, d14: 2 weeks, d28: 4 weeks, d35: 5 weeks) and substrates (red star: grey concrete, green triangle: dolomite Sorel cement, brown circle: white concrete). B) Correlation circle of the pigments variables (Carotens: Carot., Chl.a: Chlorophyll a, Chl.b: Chlorophyll b, Chl.c: Chlorophyll c, Pheo.: Pheopigments, Anth.: Antheraxanthin, Diadino.: Diadinoxanthin, Diato.: Diatoxanthin, Fuc.: Fucoxanthin, Hex.fuc.: Hex-fucoxanthin, Pras.: Prasinophyte, Zea.: Zeaxanthin) and supplementary variables (sugar and protein concentrations).The PCA was performed on pigment variables (12 pigments) and supplementary variables (sugar and protein concentrations) have been computed to verify potential correlations. The samples were collected according to substrates (Ds, Cg and Cw for dolomite Sorel cement, grey concrete and white concrete, respectively) and sampling dates (from d01 to d35; FigureII-3). The first axis, which represented 67.03 % of total inertia, mainly structured the samples. The second axis also explained a large part of the total inertia (19.23 %), while the third axis (5.4 % of the total inertia, <mean threshold 1/12 = 8.33 %) was not retained in the analysis. The first two dimensions showed a good projection of the data, as all variables were close to the correlation circle, except the supplementary variables, and individuals had cumulative squared cosinus above 0.7 on these two dimensions (except the first and third replicates from Cw at d35). Chlorophyll a, fucoxanthin, pheopigments, diadinoxanthin, antheraxanthin, hex-fucoxanthin and chlorophyll c concentrations from d01 and d7 samples, and the Ds and Cw samples from d35 mainly contributed to the construction of the first dimension. Chlorophyll b, diatoxanthin, zeaxanthin, and prasinoxanthin concentrations

  monitoring took place during one year on two different sites: in the coastal waters of the Marine Protected Area (MPA) of Larvotto (Monaco) (7.440066°E, 43.74633°N), managed by the AMPN (Association Monaco pour la Protection de la Nature); and in the MPA of Roquebrune Cap Martin (7.449783°E, 43.75158°N) managed by "le Service de l'eau, des déchets et des énergies de la Direction de l'Environnement et de la Gestion des Risques du Département des Alpes Maritimes". These two MPA have been chosen to see whether highly artificial coast in the Monaco Larvotto reserve would show differences with the protected and natural coast of the MPA of Roquebrune (Figure III-1).

Figure III- 1 :

 1 Figure III-1: Map of the two Marine Protected Areas (MPA) selected for the sampling design: The Larvotto reserve (Monaco) with a highly artificialized coast and Roquebrune Cap Martin (France) with a natural coastThe biofilm monitoring was done within a month in May 2017, in order to get a mature biofilm. The samples were retrieved every week to follow this maturation of the biofilm communities. The sampling took place 7, 14, 21, and 28 days after immersion. The samples were immersed at 25 m depth, 2 meters above artificial reefs of the two different MPAs. They were fixed on 5 different 1m² plastic frames (1 frame for each sampling date), suspended from a 10 litres buoy and anchored to the artificial reefs. The immersion, the installation and the sampling follow the same methods asRiera et al. 2018 (Chap. 1, p.55).

(

  Figure III-2: Sampling design for the monitoring of the biofilm and macrofouling on 3 different substrates (Concrete, Dolomite, Rock) in two different Marine Protected Area (Larvotto MPA of Monaco, and MPA of Roquebrune Cap Martin), and analyses related to both monitoring

4 C°at

 4 Monaco and 16.8 ± 0.4 C° at Roquebrune. During the macrofouling monitoring, the temperature was higher at Monaco than at Roquebrune in summer (2017_08) and autumn (2017_10) season (Student test p<0.01). Then, the temperature was similar between sites for winter (2018_02) and spring (2018_04) season (Figure III-3: A) Average temperature of the sea, B) average sedimentation rate during biofilm and macrofouling monitoring at Monaco and Roquebrune.. During the monitoring of macrofouling, the sedimentation rate was greater in Monaco than in Roquebrune (Figure III-3: A) Average temperature of the sea, B) average sedimentation rate during biofilm and macrofouling monitoring at Monaco and Roquebrune.). On both sites, the sedimentation rate increased drastically after six months of monitoring, especially at Monaco (Monaco: from 8.02 ± 0.06xxx g.m-².day-1 to 52.34 ± 1.02 g.m-².day -1 , Roquebrune: from 4.84 ± 0.25 g.m-².day-1 to 15.14 ± 2.07 g.m-².day -1 ), peaked during the winter season (Monaco: 161.73 ± 0.04 g.m-².day-1, Roquebrune: 98.33 ± 6.94 g.m-².day-1) and then decreased at the end of the monitoring (Monaco: 91.55 ± 0.86 g.m-².day-1, Roquebrune: 54.22 ±0.12 g.m-².day-1) (Figure III-3: A) Average temperature of the sea, B) average sedimentation rate during biofilm and macrofouling monitoring at Monaco and Roquebrune.).

Figure

  Figure III-3: A) Average temperature of the sea, B) average sedimentation rate during biofilm and macrofouling monitoring at Monaco and Roquebrune.

Figure III- 4 :

 4 Figure III-4: A) PcoA computed on the Bray Curtis dissimilarity matrix of the relative abundance of the bacterial classes ≥ 1 % sequencing in the biofilm over the monitoring period (D07, D14, D21, D28), at both sites (Monaco and Roquebrune), and on each substrate (concrete, dolomite, rock). Samples are ordinated according to clusters determined by cascade Kmean (5 clusters: Calinski Criterion 84.20, SSE: 4.23). B) The relative abundance of bacterial classes ≥ 1% of each cluster and its hierarchical classification

  Figure III-5). The first two axes explain 30.07 % of the total inertia of the data (Figure III-5) and have been retained to illustrate the dissimilarity between samples. Our clusters have been determined by the best Calinski-Harabasz criterion (CH Criterion 89.1, see: 6.09) (Figure III-5). The pigments that explained the main differences between clusters were chlorophyll a and c, fucoxanthin and pheopigments (Figure III-5.B). The first cluster gathered the rock and concrete samples at D07from both sites and one dolomite sample at D07 from Roquebrune, and was characterised by the highest percentage of chlorophyll a (63.09 ± 0.55%), chlorophyll c (8.60 ± 0.39%), and the lowest percentage of all the other pigments (fucoxanthin (23.10 ± 0.32%), diadinoxanthin (0.97 ± 0.04%), diatoxanthin (0.28 ± 0.04%), zeaxanthin (0.15 ± 0.06%), chlorophyll b (0.01 ± 0.01%), and absence of β carotene). The second cluster grouped all the Roquebrune samples at D28, except one rock sample. It was characterised by the highest percentages of pheopigments (8.51 ± 0.47%), diadinoxanthin (2.10 ± 0.09%), zeaxanthin (1.07 ± 0.12%), Chlorophyll b (0.92 ± 0.15%), and β carotene (0.87 ± 0.10%), and the lowest percentage of chlorophyll c (3.04 ± 0.15%). The third cluster grouped all the Monaco samples at D21 and D28, except one dolomite sample at D21, that showed the highest percentages of fucoxanthin (35. ± 0.44%), and diatoxanthin (0.89 ± 0.08%), and the lowest percentage of chlorophyll a (50.79 ± 0.52%), pheopigments (2.93 ± 0.32%), and β carotene (0.15 ± 0.02%), and the absence of chlorophyll b. The fourth cluster gathers all the D14 samples from both sites, the D21 samples from Roquebrune and one dolomite sample at T21 from Monaco, and all the samples of dolomite at D07 except one sample from Roquebrune. This cluster showed percentage of pigments very closed to the global average, determined by 57.86% (± 0.21%) of chlorophyll a, 28.08 % (± 0.33%) of fucoxanthin, 6.98 % (± 0.30%) of chlorophyll c and 3.75 % (± 0.26%) of pheopigments.

Figure

  Figure III-5: A) PcoA computed on the Bray Curtis dissimilarity matrix of the relative abundance of pigments detected by HPLC in the biofilm over the monitoring period (D07, D14, D21, D28), at both sites (Monaco & Roquebrune), and on each substrate (concrete, dolomite, rock). Samples were ordinated according to clusters determined by cascade Kmean (4 clusters: Calinski Criterion 89.1, SEE: 6.09), B) Relative abundance of the type of pigments of each cluster and its hierarchical classification

Figure III- 6 :

 6 Figure Mean concentration of sugars (glucose equivalence) and proteins (BSA equivalence) detected by colorimetry at each sampling period (T07, T14, T21, T28), at both sites (Monaco and Roquebrune) and on each substrate(concrete, dolomite, rock). Grey zone corresponds to the confidence interval

  (Van der Waerden test: p= 1.102759e-10; post-hoc test: C -D: p= 0.2517, C -R: p < 0.0001, D -R: p<0.0001) (Figure III-7).

Figure III- 7 :

 7 Figure III-7: Mean total macrofouling dry weight (mg.cm -2 ) over time, on both sites and on the three different substrates. Grey zone corresponds to smoothed conditional means

season, 5

 5 to autumn season, 5 to winter season, and 8 to spring. Regarding the substrates, 29 taxa were common to all of them, 7 taxa were found only on the concrete (Aphrodita sp., Cerastoderma sp., Limaria hians, Patella pellucida, Alvania sp., Setia ambigua, Jujubinus sp.), 8 only on the dolomite (Arca tetragona, Dentaliidae, Tritia reticulata, Oncaea sp., Clanculus corallinus, Flabellia sp.) and 4 only on the rock (Chama asperalla, Cythara sp., Womersleyella sp., Rissoa sp.). The macrofouling growing on the dolomite samples shared 8 taxa with the one growing on concrete and ten others with the one growing on the rock (D-C: Crisia sp., Dexamine sp., Fusinus pulchellus, Galathea nexa, Veneridae, Watersipora subtorquata; D-R: Calliostoma sp., Clathrina sp., Fasciolariidae, Lichenoporidae, Muricidae, Peyssonnelia sp., Nereis sp., Folinella excavata, Sycettidae). Finally, the macrofouling growing on the concrete and the rock shared 5 different taxa(Amphipoda, Peltidium purpureum, Triphora sp., Truncatella hamersmithi, Valonia sp.). Overall, over the entire monitoring period and at both sites, the macrofouling growing on the dolomite showed the highest gamma diversity, while the macrofouling growing on the concrete showed the lowest gamma diversity.

Figure

  Figure III-8: A) Venn diagrams representing the taxa for each season: B) substrates, C) and sites. Gamma diversity computed with specific richness, Shannon index and Pielou index of equitability for each season, site, and substrate Dissimilarities between communities at the family rank were mainly explained by the seasonal sampling and the sites (ANOSIM : Season:Site:Substrate: R: 0.74, p=0.001; Season: R: 0.52 p=0.001; Site: R: 0.23, p=0.001; Substrate: R: -0.02, p=0.83). A PCoA has been performed for each site on the percentage of the family rank of the dry weight of macrofouling growing on the different substrates over the monitoring period (Figure III-9). At Monaco, the two first axes explained 36.35 % of the total inertia of the data. Only two clusters have been determined by the best Calinski-Harabasz (CH) criterion (CH Criterion: 30.60, see: 29.52) (Figure III-9). The first cluster gathered the samples of Summer and Autumn seasons 2017 and was characterised by the presence of Dyctyoceae (54,05 ± 6.39%), Rhodomelaceae (7.87.09 ± 2.60%)

Figure III- 9 :

 9 Figure III-9: PcoA computed on the Bray Curtis dissimilarity matrix of the relative abundance of the dry weight of macrofouling taxa family from Aug. 2017 to Apr. 2018, on each substrate (concrete, dolomite, rock): A) Monaco community, B) Roquebrune community. Samples are ordinated according to clusters determined by cascade Kmean (Monaco: 2 clusters: Calinski Criterion: 30.60, SEE: 29.52; Roquebrune: Calinski Criterion 84.20, SSE: 4.23), C) Relative abundance of Families of each cluster

Figure III- 10 :

 10 Figure III-10: Heavy metals concentration (ppm) in the biofilm, the macrofouling, the 3 virgin substrates and suspended material in sinking during biofilm and macrofouling monitoring

Figure

  Figure III-11: Principal component analysis on the percentage of heavy metals within the biofilm, the sinking material and the virgin substrates used for the biofilm monitoring at D28 on both sites (Monaco and Roquebrune): A) Correlation circle of the variables, B) and ordination of the samples on the first two dimensions

PART 1 :

 1 TOWARD A PURPOSEFUL DESIGN OF ARTIFICIAL REEFS: A FIRST METHOD TO ASSESS THEIR STRUCTURAL COMPLEXITY AND HETEROGENEITY To be submitted in Ecological Engineering Authors: Riera E., Mauroy B., Barthélémy J., Hubas C. & Francour P. Résumé Les récifs artificiels (RA) sont souvent considérés comme des outils d'ingénierie écologique favorisant la mise en place de mesures de restauration et de conservation. Outre la qualité et l'innocuité des matériaux utilisés pour leur construction, notions discutées dans les deux premiers chapitres, l'agencement tridimensionnel des récifs artificiels est déterminant pour l'établissement de communautés riches et fonctionnelles. A l'heure actuelle les structures des RA sont conçues et arrangées selon des dires d'expert, aucune méthode quantitative ne permet d'en évaluer la complexité et l'hétérogénéité. Nous supposons que l'élaboration d'une méthode permettant d'évaluer la complexité et l'hétérogénéité permettrait d'offrir une classification des différents types de récifs artificiels. Dans cette étude, la complexité de modules de RA a été déterminée à l'aide de modèles numériques 3D à partir de quatre variables normalisées entre 0 et 1: la rugosité (Topo), la porosité (Poro), la dimension fractale (Dn) et la déviation standard des normales sur le plan vertical (SDnz). Par la suite, l'hétérogénéité des différentes combinaisons possibles de modules (agrégat, village, champs) a été déterminée selon l'indice de Shannon (H') pondéré par le volume des modules déployés.Cette étude démontre que notre méthode est fiable pour évaluer la structure de tous types de récifs artificiels, d'un module donné à des combinaisons plus complexes. La classification proposée par la méthode regroupe des typologies de récifs selon leurs usages et les communautés qu'ils recrutent.Cette première étude de la structure des récifs artificiels est prometteuse et permettra d'offrir un outil efficace pour jouer sur les paramètres de complexité et d'hétérogénéité lors de l'élaboration de nouveaux designs de récifs artificiels. Il est cependant nécessaire d'effectuer une vérification sur le terrain de l'influence de ces paramètres sur les communautés afin de mieux définir des designs spécifiques selon des espèces cibles.

Figure IV- 1 :

 1 Figure IV-1: Fictive 3D CAD models generated on Tinkercad. The surface of a simple cube has been refolded three times, and tree different cavities have been added

Figure IV- 2 :

 2 Figure IV-2: Samples of Artificial reef modules from Tessier et al.2015 generated on Tinkercad and model from Boskalis (scales are not respected)

Figure IV- 3 :

 3 Figure IV-3: representation on MeshLab of the 3D CAD model of the module designed by Boskalis. The box surrounding it it the its bounding box that correspond to the volume occupied by the module. The dimension of the bounding box is used to compute the parameters Topo and Poro.

Figure IV- 4 :

 4 Figure IV-4: representation on MeshLab of the 3D CAD model of the module designed by Boskalis. on the left: the 3D CAD model with vertices (points) highlighted in yellow, on right: the 3D CAD model with the normal computed in blue. The points and normals are used to compute the parameters SDnz and Dn.

EQUATION 1 :

 1 𝑃𝑜𝑟𝑜 = (𝑉𝑜 -𝑉𝑡) 𝑉𝑜 ⁄ With: 𝑉𝑡: the total volume of the 3D CAD model 𝑉𝑜: volume occupied by the 3D CAD model determined by the length, width and hight of the bounding box on MeshLab Topography, "Topo"

  of modules 𝑖: a given module 𝐶 𝑖 : complexity score of a given module 𝑉𝑡 𝑖 : volume of the module 𝑉𝑡: volume of all the modules of the combination.

EQUATION 8 :

 8 𝐻′ = -∑ 𝑝 𝑖 . 𝑙𝑜𝑔 (𝑝 𝑖 ) Shannon diversity index 𝑀𝐷: number of modules 𝑖: volume of a given module 𝑝 𝑖 : the proportion of the volume 𝑛 𝑖 of a given module i relatively to the total volume of modules (N) of the structure, computed as follows: 𝑝 𝑖 = 𝑛 𝑖 𝑁 ⁄

EQUATION 10 :

 10 𝑆 = 𝐶 𝑤 + 𝐻' WITH: 𝑊: supplementary weight according to the scale 𝐶 𝑤 : mean complexity weighted 𝐻': heterogeneity of the combination 𝑉: volume ratio of the combination 2.6. Data analysis Statistical correlation tests have been done with the open-source software R (3.4.2)

  fractal dimension was different according to the density (Figure IV-5.B). We choose the density 10, that represents a good compromise between time processing and accuracy of the computation. The difference between the value of Dn of the most complex model, calculated with the maximum density and the density of 10 points per unit squared, is slight (FM07 density 20: Dn = 0.30, FM07 density 10: Dn = 0.32).

Figure IV- 5 :

 5 Figure IV-5: Values of SDnz (A) and Dn (B) computed on the fictive model with different density of point clouds (points per unit squared: 1, 5, 10, 15 and 20) Table IV-1:Indexes computed on the 3D fictive 3D CAD models and evaluation of the global complexity (C)

(

  STBS). Finally, Poro ranges between 0.63 (DALO) and 0.95 (COMN). Dn shows the highest correlation with the index C (Pearson correlation : Dn~C: R: 0.8237215, p = 8.777e-05; SDnz~C: R: 0.6156684, p = 0.01112, Topo~C: R: 0.5071884, p = 0.04494, Poro~C: R: -0.1669613, p = 0.5366) A PCA was performed on the 4 different variables that compose the index of complexity (Dn, SDnz, Topo, and Poro) of the artificial reef modules, the index of complexity C was added as a supplementary variable. The samples were collected according to optimal clustering computed with the Calinski criterion computed by cascade Kmeans (Figure IV-6).

Figure

  Figure IV-6: K-means cascade on the AR modules according to computed with Euclidean distance on the scaled value of the complexity variables (Dn, SDnz, Topo, and Poro), and Calinski criterion, groups ranging between 2 and 8: A)Comparison of the k-means repartitions of the AR modules according to the number of groups in each partition, B) and their value of the Calinski criterion

  cosines=0.81). Each individual contributes to less than 30% to the construction of both two first dimensions. COMN, BOSK, STBS, PIPE, DALO, CR01 and BONN mainly contributed to the construction of the first dimension. Whereas SEAR, CR02, NEGR, CR14 and FAKR mainly contributed to building the second dimension. The third and fourth dimension where mainly build by the DALO module (50%). The contribution of each variable to build the two first dimensions is well balanced (mean contribution for Dim.1 and 2: Dn: 22% SDnz: 30% Topo: 28% Poro: 20%). Dn contributes 42% to the construction of the first dimension, and SDnz contributes to 53% to the construction of the second one. Topo and Poro contributed equally to build both dimension (Topo: Dim.1: 28%, Dim.2: 30%; Poro: Dim.1: 23%, Dim.2: 15%). On one hand, all the variables were positively correlated to the first dimension, except "Poro". On the other hand, all the variables were positively correlated with the second dimension, except SDnz (FigureIV-7). The index of complexity as a supplementary variable shows a high correlation with the first dimension (71%).

Figure IV- 7 :

 7 Figure IV-7:Principal component analysis: A) correlation circle of the variable of complexity (Dn, SDnz, Topo, and Poro) and supplementary quantitative variable the index of complexity "C", B) and the factor map of the artificial reef's modules, C) coloured ordination according to the optimal clustering computed by K-means cascades with Calinski criterion. The optimal cut of the dendrogram by casacade K-means gave 6 different clusters (Figure IV-6, Figure IV-7). The first cluster (C1: BONN, COMN, CR01, and TIPY) and sixth cluster

PART 2 :

 2 PHOTOSYNTHETIC BIOFILM PHYSIOLOGY AT DIFFERENT SCALES

the

  photosystems II (PS II) centers open (F0), the maximal fluorescence yield of dark-adapted sample with all PS II centers closed (Fm), the maximal fluorescence yield of illuminated sample with all PS II centers closed (Fm') . The photochemical conversion quantum yield (Y (II)) is expressed by the following relationship.

EQUATION 15 :

 15 photosynthesis of organisms and their relation to light(Klughammer and Schreiber, 2008).

  photosynthetic activity (rETR) as a function of light intensity also called light curves. A model[START_REF] Eilers | A model for the relationship between light intensity and the rate of photosynthesis in phytoplankton[END_REF]) is applied to the data to retrieve different photosynthetic parameters such as maximum rETR and the light saturation parameter (Ek). Light saturation values (Ek) determine the light intensity, for which photosynthesis efficiency (rETR) reach a plateau. This parameter makes it possible to determine if the biofilms are adapted to strong or low luminosity. A high Ek value defines individuals acclimated to a strong irradiance.

Figure

  Figure IV-8: Example of a light curve (A) fited with the model of Eilers and Peeters (B) used to find the values of Ek and ETRmax

Figure

  Figure IV-9: Surface scan image of the different substrates (from left to right: dolomite, concrete, rock)

(

  Waerden Van der test: p < 0.05; post hoc test: C-D: > 0.05, C-R: < 0.05, R-D: < 0.05) (Figure IV-10).

Figure

  Figure IV-10: Absorbance of the biofilm by imaging PAM on the different substrates (concrete, dolomite & rock) We also noticed a high heterogeneity of the measured parameters at the surface of concrete samples. The photographs of the PAM imaging (Figure IV-11) show a nonhomogeneous distribution of individuals according to the different indices. The absorbance related to the abundance of communities shows that the entire surface is colonized. However, the cavities welcome fewer abundance compare to smooth surfaces. This differences of abundance in the cavities are related to high rETR, low photochemical efficiency Y(II), and high Y(NO) and Y(NPQ)

Figure IV- 12 :

 12 Figure Correlogram of the microtopography complexity indices and the Imaging Pam indices on the three substrates (concrete, dolomite, rock) according to the three scale scales studied (Small, medium, big), the gradient scale corresponds to the correlations, from the red to blue from negative to positive, framed values show significant correlations at p <0.05

  Un suivi du biofilm sur 3 semaines (correspondant à la maturité du biofilm dans nos deux études Chap.1 & 2), et une analyse de son contenu en métaux lourds ̶ complétée par la détection d'autres composés, tels que les polluants organiques persistants (POP) comprenant en particulier les dioxines, les polychlorobiphényles (PCB), les hydrocarbures aromatiques polycycliques (HAP) et les pesticides ̶ permettrait d'identifier rapidement si le matériau utilisé est susceptible de favoriser ou non la séquestration des diverses pollutions anthropiques du milieu marin. Sachant que ces résultats peuvent être fluctuants en fonction du site d'exposition, il serait intéressant de répliquer l'expérience dans différents sites présentant un gradient de pollution afin de voir si la séquestration dans le biofilm dépasse les normes environnementales.Si l'étude n'a pas pu mettre en évidence des différences structurelles au sein des communautés de biofouling entre les matériaux, il est possible que la séquestration des polluants, plus importante au sein des communautés se développant sur béton, ait avec le temps un impact sur leur évolution ainsi que sur l'ensemble du réseau trophique des récifs artificiels par des phénomènes de bioaccumulation. La vérification de cette hypothèse pourrait s'effectuer en suivant des espèces cibles du macrofouling correspondant au régime alimentaire de certaines espèces mobiles inféodées aux récifs artificiels telles que des blennies, des serrans ou encore des sparidés.La variété des méthodes expérimentales et des terminologies utilisées pour l'étude de la structure de l'habitat révèle l'aspect très complexe de son analyse(McCoy & Bell 1991). En se focalisant sur trois dimensions (complexité, hétérogénéité, échelle) comme le suggèrent Bell & McCoy, il semble plus facile d'aborder son étude. Nous avons ainsi pu mettre au point la première méthode standardisée pour évaluer la structure des récifs (Chap. 3). Une étude in situ sur le suivi de différents récifs artificiels et/ou la collection de données de recensement sur les communautés mobiles permettrait de vérifier la validité de cette méthode pour évaluer l'efficacité de la colonisation des récifs artificiels selon leur macrostructure. Cette méthode nécessite cependant encore des vérifications terrain. L'immersion en 2017, dans la réserve du Larvotto (Monaco), des nouveaux récifs artificiels conçus par impression 3D, ne permet pas d'avoir suffisamment de recul sur les suivis mis en place pour déterminer un lien entre leurs structures et les espèces recrutées sur ces nouveaux habitats. Au terme des 4 premières années de suivi de ces récifs, ces données ainsi que le regroupement de données de recensement sur d'autres récifs artificiels, permettraient de définir un cadre scientifique pour lier les différents paramètres de complexité proposés à des mesures de gestion des ressources marines inféodées aux récifs artificiels. Outre les améliorations à apporter à la méthode qui ont déjà été discutées dans le chapitre 3, il serait intéressant d'ajouter une évaluation de leur connectivité qui influence la dynamique de recrutement des communautés[START_REF] Koeck | Evaluation of Artificial Reefs Impact on Artisanal Fisheries: Necessity of Complementary Approaches[END_REF][START_REF] De Bie | Body size and dispersal mode as key traits determining metacommunity structure of aquatic organisms[END_REF]. A l'échelle globale du champ de récifs, le programme des récifs du Prado avait positionné des modules intermédiaires pour assurer des corridors entre les villages ainsi qu'avec les habitats naturels (roche et posidonie)[START_REF] Charbonnel | Artificial Reefs in Marseille : From Complex Natural Habitats to Concepts of Efficient Artificial Reef Design[END_REF]. Dans la partie 1 du chapitre 3, le paramètre "V" correspondant au volume occupé sur la totalité du champ d'occupation peut être un moyen d'évaluer cette connectivité. Plus le ratio est faible, plus la distance entre les éléments est faible, impliquant potentiellement une plus forte connectivité structurelle sur l'ensemble du site. Par ailleurs, les premiers essais à l'échelle du matériau sur les communautés de biofilm ont donné quelques résultats encourageants. Nous avons pu observer que différentes variables de complexité ont des relations positives avec l'abondance du biofilm, son activité photosynthétique ou encore des mécanismes de photo-adaptation. Il serait intéressant de poursuivre des tests similaires sur un matériau de même nature en faisant varier les différents paramètres étudiés à différentes échelles afin d'analyser plus finement les réponses du biofilm à ces variations et à ces niveaux d'échelles qui semblent déterminants pour étudier ce type de relations.

L

  'ensemble de ces résultats suggère que l'angle de vue et les méthodes que nous adoptons pour observer ces communautés détermine largement les conclusions que nous pouvons émettre sur les différences potentielles en fonction de certaines conditions. L'échelle temporelle et spatiale choisie ne correspond pas toujours idéalement à celle que nous devrions adopter pour identifier les mécanismes fins qui impliquent le recrutement des espèces puis leur établissement dans le temps (Chap 3. Part. 2). Les relations changeantes observées entre les échelles ouvrent une question fondamentale sur la façon dont nous étudions le lien entre les organismes et leur paysage. L'importance de l'échelle pour déterminer ces relations a déjà été soulignée parMcCoy & Bell (1991).[START_REF] Tokeshi | Habitat complexity in aquatic systems : fractals and beyond[END_REF] ont également souligné que l'échelle géographique implique des relations différentes selon que notre question se focalise sur l'échelle globale, régionale, locale ou sur celle des micro-habitats. In fine, il semble primordial de définir l'échelle en fonction du niveau d'organisation correspondant à la taille de l'organisme étudié(Farjalla et al. 2012), Chap. 3 Part. 2). Cependant l'étude de la structure de l'habitat selon les échelles ne nous permet pas d'identifier si les relations observées à une échelle peuvent avoir un impact sur les échelles supérieures. Y a-t-il une continuité ou une rupture dans les relations ? Y a-t-il des émergences de mécanismes nouveaux en fonction du niveau d'organisation ? Ou bien comme le présente[START_REF] Kupiec | A probabilist theory for cell differentiation, embryonic mortality and DNA C-value paradox[END_REF] dans ses travaux sur l'application de la théorie de l'évolution à l'échelle cellulaire, le vivant "bricole-t-il" toujours afin d'améliorer sa fitness en fonction des lois physiques dont l'influence peut changer selon l'échelle ? Il est bien connu que des espèces dites ingénieurs comme les castors, les fourmis, ou encore les termites modifient considérablement leur environnement à leur profit, impliquant des conséquences sur les écosystèmes et les organismes qu'ils côtoient(Jones et al. 1994). Par ailleurs, nous connaissons bien les effets top down des prédateurs et bottom up des producteurs primaires qui régulent les populations des niveaux trophiques intermédiaires. A ces égards, le biofilm peut être considéré comme une communauté ingénieure qui construit son écosystème grâce à ses sécrétions extracellulaires et qui par ce biais influence le recrutement des larves et des spores des espèces de macrofouling[START_REF] Flemming | The biofilm matrix[END_REF]. Il est également le producteur primaire des communautés benthiques offrant une source d'éléments nutritifs aux communautés de macrophytes et aux micro-brouteurs. Il influe ainsi sur tout l'écosystème benthique et son réseau trophique. Au regard de ces mécanismes observés au niveau du biofilm et des échelles supérieures ainsi que des autres exemples cités, il est donc justifié de se demander si ces relations inter-échelles sont susceptibles d'être récurrentes dans les écosystèmes. Conclusion Les caractéristiques extrinsèques des récifs artificiels (RA), liées au site d'immersion, constituent le facteur de réussite le plus déterminant car elles conditionnent la diversité des espèces et les conditions environnementales. Mais les caractéristiques intrinsèques des RA jouent également un rôle important. L'étude des matériaux, à travers le suivi du biofouling et plus particulièrement du biofilm, permet de tester rapidement la qualité d'un matériau et son influence sur les communautés. Les résultats révélés sur le béton nous conduisent à nous interroger sur l'impact écologique de toutes les structures artificielles immergées le long des côtes. Il est fort probable que dans des environnements particulièrement pollués, le béton favorise une bioaccumulation de métaux lourds ou d'autres polluants. Si, comme nous le supposons, la séquestration est favorisée par le pH du matériau, il est envisageable de produire des matériaux en béton ayant un pH plus proche de l'environnement marin. L'étude de la structure des RA par le biais de la méthode mise en place permettrait de construire des RA de façon plus rigoureuse, si tant est qu'il soit possible de relier ces paramètres structuraux au recrutement de certaines espèces. Malgré tout, la mise au point de cette méthode d'évaluation semble efficace pour proposer une classification intéressante des différents modules existants. Elle permet en effet de distinguer les structures selon leurs objectifs d'immersion. Pour la première fois, il est possible d'utiliser une méthode standardisée qui permettra d'évaluer in situ l'influence des paramètres structuraux des RA sur le recrutement, l'abondance, la distribution et/ou la diversité. Enfin, les récifs immergés dans la réserve du Larvotto (Monaco), représentent l'une des structures les plus complexes et le matériau à base de sable de dolomite utilisé pour les concevoir ne favorise pas la séquestration de polluants au sein du biofouling et semble accueillir des communautés tout aussi diverses que les autres matériaux. Cette évaluation positive de ces caractéristiques intrinsèques laisse envisager un avenir prometteur pour ce type de structure afin de concevoir des RA répondant aux directives actuelles de l'UNEP. Pour compléter les travaux initiés au cours de cette thèse et donner des réponses aux questions encore en suspens, nous pouvons envisager différentes perspectives : (i) Un suivi comparatif de différents types de béton (en faisant varier leur pH et leur microtopographie), des sécrétions du biofilm et de divers polluants séquestrés par le biofilm, permettrait d'isoler les paramètres les plus influents sur les sécrétions d'EPS et la séquestration de polluants.

  1. Contexte globalLes activités anthropiques des cinquante dernières années conduisent à un déclin sans précédent de la nature et de la biodiversité à toutes les échelles[START_REF] Mace | Scale-Dependent Fractal Dimensions of Topographic Surfaces : An Empirical Investigation , with Applications in Geomorphology and Computer Mapping[END_REF]. Les derniers rapports de la plateforme intergouvernementale sur la biodiversité et les services écosystémiques (IBPES) sont alarmants et nous révèlent les conséquences de ce déclin sur l'ensemble des services écosystémiques dont nous dépendons. En Méditerranée, de nombreuses espèces marines sont menacées en raison de la surpêche, de la réduction de leurs aires de répartition liée à la pollution et la destruction de leurs habitats, des impacts du changement climatique, ou encore de la progression des espèces exotiques envahissantes.Aujourd'hui, 74% des habitats benthiques méditerranéens sont menacés[START_REF] Clemens | The regional assessment report on Biodiversity and Ecosystem Services for Europe and Central Asia[END_REF]).

	De

plus, l'ensemble des pratiques traditionnelles autour de la mer, telles que la pêche artisanale, sont menacées par les nouvelles technologies permettant d'obtenir des rendements de pêche plus élevés. Malgré ces sombres constats, des « changements transformateurs » économiques, sociétaux, politiques et technologiques peuvent nous permettre de conserver et de restaurer la nature. Il est donc de première nécessité de mettre au service de cette transformation l'ensemble des connaissances scientifiques disponibles pour orienter notre système socioécosystème mondial vers une utilisation durable des services écosystémiques que la nature nous offre. Outre la protection des zones côtières/marines qui passe par la mise en place d'aires marines protégées, des solutions de restauration ou d'aménagement visant à valoriser et soutenir les pratiques d'exploitation durable de la mer sont aussi à envisager. Il est important d'identifier les usages autour de ces territoires menacés et d'apporter des améliorations à leur mise en place et à leur suivi afin de concilier protection de la nature et services rendus aux populations.

3 .

 3 Etat de l'art des caractéristiques intrinsèques des récifs artificielsCes directives ont permis d'établir un cadre plus précis définissant 3 critères principaux à considérer lors d'un programme de déploiement de récifs artificiels. Il s'agit de

	l'emplacement, déterminant les caractères extrinsèques des récifs artificiels ainsi que des
	matériaux et de la structure tridimensionnelle, déterminant les caractères intrinsèques des
	récifs artificiels. Concernant ces dernières caractéristiques, la construction de récifs artificiels
	doit être faite à partir de matériaux inertes n'engendrant pas de pollution des écosystèmes par
	lessivage, altération physique ou chimique, et/ou activité biologique, afin de ne pas entraîner
	une exposition accrue des contaminants nuisibles aux organismes. Ces matériaux peuvent être
	naturels, recyclés ou préfabriqués. Les principaux matériaux recommandés pour la
	construction de récifs artificiels sont la roche naturelle, le béton ou l'acier, excluant tous
	matériaux constituant des déchets. Par ailleurs, les structures utilisées doivent tout d'abord
	offrir un design correspondant à leurs objectifs et avoir des dimensions et des formes pouvant
	favoriser le recrutement de la vie marine à sa surface et aux alentours. Tout en remplissant ces
	fonctions premières, les structures doivent avoir une résistance mécanique suffisante afin
	qu'elles ne soient pas déplacées ou renversées par des engins de dragage, et qu'elles puissent
	résister aux conditions marines (vagues, courant ou processus d'érosion). De plus, toute
	structure mise à l'eau doit remplir ses objectifs avec une occupation minimale de l'espace et
	doit pouvoir être retirée si nécessaire (UNEP MAP 2005, UNEP 2009).
	Malgré la mise en place de ces lignes directrices, il existe à l'heure actuelle un manque
	de fondements scientifiques pour l'ensemble des initiatives. Les matériaux utilisés sont choisis
	principalement pour leur faible coup et leur robustesse. Cependant, leur résistance à la bio-
	érosion ne fait pas l'objet d'études à ce jour. Le cas le plus inquiétant a été l'utilisation de pneus
	encouragée lors de la première conférence du CARAH en 1974 et leur usage a même été
	sponsorisé aux USA par le géant Goodyear (Lizarraga-Partida 1974, Figure 3-1). Suite à ces
	encouragements, leur immersion s'est répandue dans le monde entier

Table II -

 II

	3.2. Sugar and protein concentration dynamics on the different
		substrates
	Cg Sugar concentrations ranged between 0.674 and 14.628 µg•cm Ds Cw Cg Ds Cw Cg Ds Cw Cg Ds Cw Day 28 Day 01 Day 07 Day 14	Cg	Ds Cw Day 35	Global Mean
	Chlorophyll a
	me an	62.34 71.78 59.71	63.1 68.63 61.28	51.48 52.74 49.8	40.43 45.3 40.42	45.3 42.17 45.01	53.09
	se	0.98 0.62 0.86	0.46 0.61 0.73	0.18 0.4 0.23	0.37 1.1 0.29	0.29 1.58 1.18	0.24
	Chlorophyll b
	me an	0	0	0	0	0	0	0.09 0.08 0.08	0	0	0	0.12 0.06 0.07	0.03
	se	0	0	0	0	0	0	0	0.01 0.01	0	0	0	0.01	0	0	0.00
	Chlorophyll c
	me an	0	0	0	0	0	0	16.17 14.52 16.18	22.65 19.49 24.88	17.74 15.48 15.08	11.06
	se	0	0	0	0	0	0	0.18 0.89 0.18	0.6 1.35 0.49	0.73 0.84 0.16	0.21
	Pheopigments
	me an	0	0	0	0	0	0	4.63 6.11 5.08	6.31 7.45 4.45	7.68 6.75 10.35	4.01
	se	0	0	0	0	0	0	0.19 0.32 0.41	0.85 0.58 0.39	0.32 0.47 1.13	0.08
	Caroten
	me an	0	0	0	0	0	0	0.85 0.85 0.79	0	0	0	0.74 0.57 0.55	0.30
	se	0	0	0	0	0	0	0.02 0.01 0.04	0	0	0	0.02 0.07 0.16	0.01
	Antheraxanthin
	me an	0	0	0	0	0	0	0.19 0.22 0.24	0.26 0.26 0.24	0.14 0.31 0.28	0.15
	se	0	0	0	0	0	0	0.01 0.01 0.01	0.01 0.02 0.01	0.04 0.02 0.01	0.00
	Diadinoxanthin
	me an	0	0	0	0	0	0	0.79 0.89 0.81	1	0.95 0.93	1.19 1.47 1.18	0.63
	se	0	0	0	0	0	0	0.01 0.02 0.01	0.01 0.03 0.03	0.05 0.04	0	0.01
	Diatoxanthin
	me an	0	0	0	0	0	0	0.28 0.14 0.31	0.03 0.04 0.05	0.14 0.11 0.11	0.08
	se	0	0	0	0	0	0	0	0.02 0.01	0	0.01 0.01	0.01 0.01 0.01	0.00
	Fucoxanthin
	me an	37.66 28.22 40.29	36.9 31.37 38.72	23.03 22.29 24.31	25.48 22.7 25.14	25.19 30.73 25.22	28.96
	se	0.98 0.62 0.86	0.46 0.61 0.73	0.06 0.43 0.3	0.1 0.65 0.11	0.71 1.22 0.16	0.14
	Hex-fucoxanthin
	me an	0	0	0	0	0	0	0.09 0.16 0.13	0.22 0.18 0.19	0.27 0.21 0.32	0.12
	se	0	0	0	0	0	0	0.01 0.03 0.02	0.01 0.01 0.02	0.02 0.01 0.06	0.00
	Prasinoxanthin
	me an	0	0	0	0	0	0	2.27 1.83 2.1	3.63 3.63 3.71	1.33 2.02 1.73	1.52
	se	0	0	0	0	0	0	0.05 0.16 0.06	0.05 0.16 0.03	0.08 0.14 0.16	0.03
	Zeaxanthin
	me an	0	0	0	0	0	0	0.14 0.16 0.16	0	0	0	0.16 0.11 0.09	0.06
	se	0	0	0	0	0	0	0.01 0.01 0.01	0	0	0	0.01 0.01 0.01	0.00

3: Mean proportion of pigments over time on each substrate (Cg: grey concrete, Ds: dolomite Sorel cement, Cw: white concrete)

Table II -

 II 5: Mean proportion of amino acids over time on each substrate (Cg: grey concrete, Ds: dolomite Sorel cement, Cw: white concrete)

	3.4. Principal Component Analysis
				Day 1				Day 7			Day 14	Day 28	Day 35	Global
			Cg	Ds Cw		Cg	Ds Cw	Cg	Ds Cw	Cg	Ds Cw	Cg	Ds Cw	Mean
								Essential amino acids
	Isoleucine
	me an		13.88 2.22 3.47	3.09 4.09 3.58	3.78 2.74 4.18	3.55 3.91 4.66	4.61 3.34 4.57	4.15
	se		8.29 0.11 0.37		0.5 0.37 0.48	0.42 0.13 0.28	0.83 0.06 0.38	0.96 0.06 0.43	0.08
	Leucine
	Ratio me an se		Day 1 2.65 4.58 5.88 0.97 0.19 0.51	Day 7 4.07 6.9 6.11 0.73 0.66 0.63	Day 14 5.45 4.4 6.39 0.79 0.18 0.33	Day 28 5.75 5.65 6.76 1.12 0.09 0.47	6.6 4.74 5.43 Day 35 1.05 0.03 0.04	5.46 0.04
	sugar:protein Lysine	Cg	Ds Cw			Cg	Ds Cw	Cg	Ds Cw	Cg	Ds Cw	Cg	Ds Cw
	mean me an se	4.79 4.26 5.46 2.34 1.42 3.49 0.48 0.23 0.3	5.80 3.90 4.34 5.34 3.17 3.74 0.79 0.55 0.46	7.98 3.99 10.37 8.90 4.17 7.18 4.15 1.62 2.69 2.63 3.33 3.48 3.24 3.1 4.02 8.26 4.38 7.96 3.20 0.53 0.33 0.64 0.41 0.45 0.56 0.82 0.68 0.94 0.04
	se Methionine me an	0.15 0.56 0.39 1.63 0.32	0	1.36 0.37 0.89 0.4 0 0.42	0.65 0.32 0.79 1.04 0.59 1.02	0.36 0.72 0.43 1.58 1.4 1.81 0.81	0.88 0.32 0.53 1 0.88 0.84
	se		1.15 0.13	0		0.13	0	0.13	0.05 0.02 0.01	0.48 0.04 0.24	0.28 0.07 0.25	0.02
	Phenylalanine
	me an		3.51 1.43 2.45	1.71 1.43 3.39	2.99 2.01 3.09	3.12 2.54 3.66	3.57 2.36 3.36	2.67
	se		1.18 0.16 0.29		0.84 0.41 0.3	0.43 0.1 0.24	0.75 0.11 0.4	0.46 0.12 0.52	0.03
	Threonine
	me an		2.3 4.27 3.74	2.94 3.77 4.66	4.11	2	4.1	4.61 4.86 4.68	4.08 4.49 4.32	3.96
	se		0.11 0.68 0.06		0.85 0.3	0.5	0.2	0.5 0.21	0.53 0.09 0.19	0.13 0.15 0.26	0.03
	Valine
	me an		3.83 3.88 4.33	5.6 5.66 4.58	5.39 3.52 5.63	6.84 5.5 6.26	6.19 4.82 3.57	5.04
	se		0.9 0.41 0.36		1.31 0.44 0.27	0.3 0.19 0.32	0.87 0.05 0.42	1.42 0.13 0.89	0.04
	TOTAL
	me an		20.21 19.07 25.80	25.30 25.37 27.32	27.79 18.94 28.04	29.01 28.45 32.61	32.25 24.78 27.70	26.18
	se		0.25 0.41 0.96		0.56 1.39 1.48	2.31 0.81 1.77	2.26 0.67 2.31	1.57 0.27 1.10	1.12
								Non essential amino acids
	Alanine
	me an		6.45 8.29 7.47	7.03 9.45 8.55	8.9 6.75 8.78	9.22 8.46 9.14	8.33 8.03 8.1	8.23
	se		1.26 0.34 0.53		1.82 0.33 0.57	0.2	0.3 0.31	0.97 0.17 0.21	1.51 0.21 0.31	0.04
	Arginine
	me an		0.67 2.21 1.32	7.94 1.7 1.58	2.16 5.53 3.51	2.43 3.04 3.46	4.22 2.65 3.13	3.06
	se		0.47 0.44 0.1		3.54 0.47 0.46	0.05 0.68 0.13	0.86 0.12 0.56	0.21 0.16 0.78	0.07
	Aspartic Acid
	me an		7.4 14.28 9		7.95 10.99 10.91	10.23 8.76 10.75	12.28 9.42 10.99	9.86 9.6 10.17	10.25
	se		0.66 3.42 0.57		2.04 0.55 0.12	0.02 0.38 0.47	0.92 0.29 0.13	1.16 0.3 0.61	0.08
	Cysteine
	me an		0	0.63 0.03	0.43 0.11 0.8	0.64 0.3 0.53	0.34 0.37 0.4	0.13 0.25 0.14	0.35
	se		0	0.1 0.02		0.17 0.06 0.34	0.07 0.09 0.05	0.1 0.04 0.02	0.05 0.06 0.03	0.01
	Glutamic Acid
	me an		15.76 18.19 21.62	17.41 24.47 19.15	25.53 28.58 20.78	15.85 20.59 17.66	18.8 25.59 20.11	20.83
	se		2.9 1.29 2.62		4.1 1.52 2.17	2.57 1.47 1.16	1	0.74 1.28	1.15 1.18 1.06	0.14
	Glycine
	me an		15.39 16.42 16.07	9.75 14.81 12.16	11.97 12.57 10.84	8.21 8.79 8.09	7.17 12.77 11.7	11.80
	se		3.54 0.81 0.94		2.48 0.43 0.22	0.04 0.76 1.09	0.3 0.27 0.51	0.17 0.59 0.54	0.09
	Histidine
	me an		1.59 0.95 2.43	2.13 0.36 0.84	0.88 2.06 0.93	0.92 1.24 1.3	3.15 0.93 1.55	1.37
	se		0.76 0.31 1.31		0.91 0.11 0.33	0.08 0.43 0.04	0.27 0.06 0.08	1.22 0.1 0.19	0.03
	Proline
	me an		2.72	0	1.17	15.79 0.71 8.36	3.19 4.36 6.64	15.24 13.43 10.45	12.68 8.7 12.07	7.70
	se		1.37	0	0.36		9.12 0.41 3.24	0.52 1.36 1.48	2.78 0.34 1.36	4.87 1.41 1.42	0.21
	Serine
	me an		15.36 19.52 15.88	7 11.55 9.48	8.47 12.56 8.02	5.61 5.87 5.05	4.77 6.2	4.8	9.31
	se		1.89 1.88 0.93		2.02 1.05 0.31	0.52 1.14 0.86	0.68 0.25 0.3	0.09 0.21 0.36	0.12
	Tyrosine
	me an		4.52 1.38 1.64	1.41 0.84 1.69	1.11 1.64 2.1	1.82 1.57 2.17	1.78 1.45 2.08	1.75
	se		2.22 0.08 0.37		0.41 0.24 0.49	0.32 0.08 0.17	0.52 0.05 0.22	0.11 0.11 0.38	0.03
	TOTAL
	me an		68.27 80.93 74.20	74.70 74.63 72.68	72.21 81.06 71.96	70.99 71.55 67.38	67.75 75.22 72.30	73.06
	se		3.59 0.41 0.96		0.55 1.39 1.48	2.31 0.81 1.77	2.26 0.67 2.31	1.57 0.27 1.10	0.13

-5). Even if no significant differences were detected between substrates, dolomite Sorel Cement showed a lower proportion of essential amino acids than on the two types of concrete at d14

(Cg: 27.78 ± 2.31; Ds: 18.94 ± 0.91; Cw: 28.04 ± 1.77) and d35 (Cg: 32.25 ± 1.57; Ds: 24.78 ± 0.27; 27.70 ± 1.10

).

  Riera E., Francour P., Hurel C., Lamy D. & Hubas C. Résumé Le premier matériau à base de ciment Sorel n'ayant pas eu une stabilité suffisante dans le milieu marin, un nouveau matériau a été développé à base de ciment blanc, de sable des Dolomites et de cendre volcanique. La composition de ce matériau limite la présence de métaux lourds, d'adjuvants chimiques et a un pH neutre dans le milieu marin. Poursuivant les travaux décrits dans le chapitre 1, la présente étude évalue l'influence de différents matériaux (le béton, le nouveau matériau utilisé pour l'impression des récifs 3D et la roche naturelle) sur les communautés de biofilm et de macrofouling. Le suivi s'est effectué au cours d'une année, dans deux aires marines protégées : la réserve du Larvotto de Monaco en zone hyper-urbanisée et la réserve de Roquebrune Cap Martin en zone urbanisée. Nous avons pu démontrer que la nature du matériau a peu d'influence sur la structure des communautés (biofilm & macrofouling). Cependant, sur les échantillons de béton, la sécrétion du biofilm ainsi que la séquestration de métaux lourds présents dans l'environnement est plus importante que sur les autres matériaux. Cette réponse est davantage significative au sein des communautés échantillonnées dans la réserve de Monaco. Les différences observées entre les matériaux sont probablement liées aux caractéristiques du pH et de la microrugosité. Celles-ci impliquent des sécrétions plus abondantes des communautés de biofilm, ce qui a pour conséquence d'augmenter leur capacité d'absorption des métaux lourds. Cette capacité d'absorption semble s'observer également au sein du macrofouling dans une moindre mesure. La différence entre les deux sites est probablement liée au niveau d'urbanisation de la côte favorisant le lessivage des métaux lourds qui se retrouvent ainsi dans le milieu marin.

	To be submitted
	Authors:
	III. CHAPTER 2: COLONISATION OF ARTIFICIAL REEF
	SUBSTRATES: "THE HABIT DOES NOT MAKE THE
	MONK."

Nous supposons que le matériau est susceptible d'influencer la qualité du biofilm jusqu'au recrutement des macro-organismes aussi bien au niveau de leur structure, de leur sécrétion et de leur capacité à accumuler les métaux lourds présents dans l'environnement ou dans les matériaux eux-mêmes. Nous supposons également que l'ensemble de ces variables seront susceptibles d'être influencées par le site d'échantillonnage.

La structure des communautés du biofilm a été identifiée à l'aide de biomarqueurs pigmentaires extraits par HPLC et par méthode de métabarcoding sur le 16S des procaryotes.

La matrice extracellulaire du biofilm a été analysée en termes de concentrations totales en sucres et en protéines par colorimétrie. La structure des communautés de macrofouling a été analysée par identification taxonomique visuelle. Enfin le contenu en métaux lourds au sein du biofilm, du macrofouling, des matériaux et de la matière organique particulaire a été déterminé par ICP-OES.

  The detection of the elements was carried out on an Optima™ 8000 DV ICP-OES, using corresponding wave length of the targeted elements(As: 193.696 nm, Cd: 228.802 nm, Cr: 267.716 nm, Cu: 324.752 nm, Ni: 231.604 nm, Pb: 220.353 nm, Zn: 206.200 nm). A standard from 0.02 to 10 ppm of the targeted heavy metals was carried out for quantification. Quantification allowed us to raise a comparative study of heavy metals repartition in biofilm and macrofouling depending on their growth on the different substrates. Heavy metals concentrations were compared to data from[START_REF] Seytre | Études préalables à la mise en place de récifs artificiels dans les eaux de la Principauté de Monaco juillet[END_REF], relative to the quality of the water column in Monaco and Roquebrune Cap

	Martin areas.
	2.6. Statistical analyses

All statistical tests and illustrations have been done with the open source software R (3.4.1), using "FactoMineR" (Husson et al. 2016), "vegan" (Oksanen et al. 2017), ade4 (Dray et al. 2018), ggplot2 (Wickham & Winston 2019) and "agricolae" (De Mendiburu 2016) packages.

  CH Criterion 84.20, see: 4.23), the first one determining only two groups was too wide to explain differences between data (CH Criterion 86.92, see: 11.58) (FigureIII-4). The species that explained the main differences between clusters were Oscillatoriophycideae,

	3.2. Structure of the biofilm microbial communities
	3.2.1. Prokaryotic community
	10 643 different OTUs have been sequenced, more than 99% of them were related to Flavobacteriia, Alphaproteobacteria, Gammaproteobacteria, Sphingobacteriia, Cytophagia,
	bacteria, only 76 different OTUs were related to archaea. The archaea were mainly represented Verrucomicrobiae, Clostridia and Cyanobacteria. The first cluster gathered the D14 samples
	by Nitrosopumilus spp. and Candidatus nitrosoarchaeum (respectively: relative abundance of from Roquebrune, characterised by the high relative abundance of Cyanophyceae
	archaea: 53.62% and 23,82%). No differences in archaeal community have been identified (17.97 ± 0.61%). The concrete and rock samples at D14 from Monaco and D21 from
	between substrates, time or sites. (Permutation test for homogeneity of multivariate Roquebrune were grouped in the second cluster and were characterised by the highest relative
	dispersions: p < 0.05). abundance of Alphaproteobacteria (30.50 ± 0.67%). The third cluster grouped the dolomite
	Among the 10 567 different OTUs related to bacteria globally sequenced, the first one samples at D21 from Roquebrune, and all the D28 samples except concrete samples from
	thousand represented 82% were identified . Among these OTUs, the most abundant phylum Monaco. This group showed the highest relative abundance of Clostridia (2.45 ± 0.41%) and
	were the Proteobacteria (relative abundance of bacteria: 40.75 ± 4.63%), Bacteroidetes Verrucomicrobiae (5.10 ± 0.21%). The fourth cluster gathered the dolomite samples at D14
	(34.83 ± 9.23%) and Cyanobacteria (11.67 ± 7.60%), followed by Verrucomicrobia from both sites, all the D21 samples from Monaco, and the concrete samples at D28 from
	Monaco. This cluster corresponded to the highest relative abundance of Flavobacteria
	(29.29 ± 0.83%), Sphingobacteriia (9.93 ± 0.44%), and Cytophagia (8.09 ± 0.30%), and the
	lowest relative abundance of Gammaproteobacteria (9.53 ± 0.21%). The fifth cluster gathered
	all the D07 samples, and was characterised by the highest relative abundance of
	Gammaproteobacteria (16.77 ± 0.84%) and Cyanophyceae (22.63 ± 0.78%) (Figure III-4).
	highest taxonomical identification: R:0.386, p=0.047; Phylum identification: R:0.00249,
	p=0.389). The main differences of bacterial communities were explained by sampling time,
	while the sites explained a slight part of the community's dissimilarities (ANOSIM Bray Curtis
	dissimilarity: Sampling: R: 0.6658, p=0.001; Site: R: 0.118, p=0.002, Substrate: R: 0.04201,
	p=0.056).
	The PCoA has been computed on the bacterial classes that represent more than 1% of

(4.43 ± 1.44%), Planctomycetes (4.11 ± 1.16%), Firmicutes (1.29 ± 1.59%) and Actinobacteria

(1.24 ± 2.5

). Among the Proteobacteria, the Alphaproteobacteria and the Gammaproteobacteria were the most abundant classes, accounting for 24.74 ± 4.32 % and 13.12 ± 3.48 % of the relative abundance of bacteria, respectively. Cyanobacteria were mainly represented by the Oscillatoriophycideae class (10.01 ± 7.24%). Bacteroidetes were mainly represented by the Flavobacteriia class (22.36 ± 5.82%). The most abundant species identified were Cyanobacterium spp. (relative abundance of bacteria: 9.99% ± 7.24) and Flavobacterium spp. (7.41% ± 2.54). On average, no significant differences between substrates have been identified from the finest to the widest identification (ANOSIM Bray Curtis dissimilarity: on the total relative abundance (Figure

. The two first axes explained 43.68 % of the total inertia of the data and have been retained to illustrate the Bray-Curtis dissimilarity between samples. We used the second best Calinski-Harabasz (CH) criterion that identified 5 different clusters (

  dolomite sample from Apr. 2018 and one rock sample from Feb. 2018, where the assemblage showing a slight percentage or even no Dictyotaceae compared to all samples, and were dominated for the dolomite sample by Serpulidae (61.46%) and by Triphoridae on the rock sample (45.50%) The third cluster grouped all the samples of Feb. 2018

	except one rock sample, and showed higher percentage of Rhodomelaceae (23.23 ± 3.88%),
	Serpulidae (16.31 ± 6.39%) and Textulariidae (12.05 ± 2.58%), and lower percentage of
	Dictyotaceae (14.07 ± 3.70%). The fourth cluster gathered the samples of Aug. 2017, with
	higher percentage of Dictyotaceae (77.42 ± 6.32%). The fifth cluster gathered the samples of
	Apr. 2018, determined by higher percentage of Arthrocladiaceae (11.39 ± 3.36%), Cerithiidae
	(10.43 ± 4.49%), Costellariidae (5.02 ± 2.61%), Fasciolariidae (9.19 ± 5.07%), Lithodermataceae
	(7.81 ± 1.79%), high percentage of Rhodomelaceae (22.53 ± 3.38%), and low percentage of
	Dictyotaceae (13.96 ±1.91%) and Textulariidae (0.18 ± 0.11%) (Figure III-9).
	(54,05 ± 6.39%), Rhodomelaceae (7.87.09 ± 2.60%)
	Arthrocladiaceae (5.38 ± 2.28%). Whereas the second cluster grouped Winter and Spring
	season 2018 and was characterized by Serpulidae (12.52 ± 5.25%), Cerithiidae (55.98 ± 8.65%),
	and Textulariidae (2: 1.41 ± 0.59%) (Figure III-9). At Roquebrune, the first two axes explained
	35.95 % of the total inertia of the data We identified 5 different clusters (CH Criterion 84.20,

see: 4.23) (Figure III-9.B). The first cluster gathered the samples of Oct 2017 and one dolomite sample of Aug. 2017, and was characterised by the highest percentage of Peyssonneliaceae (13.00 ± 5.30%) and high percentage of Dictyotaceae (53.36 ± 4.82%). The second cluster grouped two outliers: one

Table IV -

 IV 2: Indexes computed on the artificial reef's modules and evaluation of average values for all the modules

	Fictive model	Dn	SDnz	Topo	Poro	C
	MF01	0.1	0.58	0.83	0	1.51
	MF02	0.11	0.58	0.83	0.28	1.8
	MF03	0.14	0.58	0.86	0.32	1.9
	MF04	0.17	0.6	0.87	0.35	1.99
	MF05	0.2	0.62	0.88	0.4	2.1
	MF06	0.29	0.65	0.91	0.51	2.33
	MF07	0.32	0.66	0.92	0.54	2.36

Table IV -

 IV 3: Index and score of the different combinations of artificial reefs

  The village of the MPA of Cap d'Agde shows the highest score (4.38) with a mean weighted complexity of 2.11 and a structural diversity of 0.27. The ratio of the total volume by the volume occupied has a very low value (8.77E-05). Indeed, the zone occupied by this village is very large.

	Combination	Cw	H'	V	W	S
	AG_COMN	1.38	0.00	0.05	1	2.43
	AG_CR14	1.65	0.00	0.04	1	2.69
	VL_BOSK	2.17	0.00	0.01	2	4.18
	VL_Z3AD	2.11	0.27	8.77E-05	2	4.38

  The index developed for other scales of the arrangement of ARs (i.e. aggregation. village. field) opens the gate to a real evaluation of the ARs according to the habitat structure they provide, both in terms of complexity and heterogeneity. The examples provided give coherent results. An aggregate of COMN modules is less complex than an aggregate of CR14 modules. At the village scale, we can see the interesting effect of the heterogeneity, the village of the Larvotto reserve with BOSK modules still presents a higher complexity index, but compared to the village of the Cap d'Agde that presents two different types of module, this village has no heterogeneity of modules.

  2. Materiel & method 2.1. Substrates of artificial reefs and natural rockThree different substrates used for artificial reefs have been tested: the rock, mainly used for dikes and rockfills; the concrete, mainly used to build classical module of artificial reefs nowadays; and a substrate based on dolomite sand and white cement made by the Boskalis industry and used to build artificial reef with giant 3d print made by D-Shape, this substrate will be named "dolomite". Five cobblestones of each substrate sized 1.5x2x5 cm. The samples have

	been placed in a basket at 1m dept at the Concarneau harbour (N 47°52' 16.395" (+47°52'
	16.395") W 3°54' 52.2354" (-3°54' 52.2354"). Nine of them has been retrieved after one week
	of immersion and six after two weeks of monitoring.
	2.2. Characterization of the surface topography

2.2.1. Surface scanner

Before immersion, each cobblestone was scanned by a surface scanner to digitize its topography. These topographies can take several forms: first a mesh (in format .PLY for Polygon

  Le travail effectué au cours de ces trois années offre des réponses à des besoins fondamentaux dans le domaine des récifs artificiels et permet de proposer l'esquisse d'un cadre scientifique afin d'évaluer leurs caractéristiques intrinsèques (matériaux & structures). En effet, outre sa diversité et son abondance, il est important de déterminer si ce premier maillon du réseau trophique des récifs artificiels est sain et ne séquestre pas de contaminants liés au matériau utilisé pour leur construction. Nous avions émis l'hypothèse que la pollution serait susceptible de provenir du matériau lui-même, mais nos résultats suggèrent finalement qu'au cours de cette première année la stabilité physicochimique des matériaux n'est pas altérée par la bio-érosion. Cependant, nous avons pu montrer que malgré sa stabilité, le béton qui est le matériau le plus utilisé de nos jours pour la 0°, 20°, 30°, 45°, 60°), les biofilms se développant sur des surfaces aux angles droits détiennent une matrice d'EPS plus épaisse et plus robuste face aux perturbations d'un flux laminaire que ceux se développant sur des surfaces lisses ou sur des surfaces dont les angles sont plus aigus ou plus obtus. A première vue, l'aspect lisse de la roche, très acéré de la dolomite, et les microcavités plus larges que présente le béton pourraient confirmer ces précédents résultats. La vérification de cette hypothèse nécessiterait de s'affranchir de la nature chimique bien différente de ces trois matériaux. A ce titre, il est probable que le pH des matériaux joue un rôle dans ces différences. Le béton a un pH très basique (11-13 pH) tandis que le matériau à base de sable de dolomite a un pH proche de celui de la mer (8.2 pH, selon les concepteurs des récifs) ; la roche calcaire composée principalement de carbonate de calcium devrait avoir un pH basique (autour de 9.9 pH). Dans une étude sur l'influence du pH sur les sécrétions du biofilm, il a été démontré qu'un pH bas favorise une structuration des EPS plus dense et homogène qu'un pH neutre. Par ailleurs, la séquestration des métaux lourds par les EPS s'avère plus importante à pH basique qu'à pH acide[START_REF] Comte | Biosorption properties of extracellular polymeric substances (EPS) towards Cd, Cu and Pb for different pH values[END_REF]. L'effet combiné d'une topographie favorable à la sécrétion d'EPS et d'un pH favorisant la séquestration des métaux lourds pourrait expliquer ces résultats sur le béton. De plus amples investigations sur ces différents paramètres sont nécessaires pour vérifier cette hypothèse. Malgré ces questions en suspens, le suivi du biofilm a permis de déceler une probable pollution sur le long terme dans le macrofouling. Il s'agit donc d'un bon indicateur pour valider la qualité d'un matériau utilisé pour un récif artificiel, peu coûteux et facile à mettre en place.

	Les résultats relatifs à la première partie de la thèse (Chap. 1 & 2) sur le suivi comparatif
	du biofouling (biofilm & macrofouling) se développant sur différents matériaux révèlent que
	l'identification simple de la structure des communautés n'est pas un indicateur suffisant pour
	évaluer la qualité d'un matériau.

conception de récifs artificiels ̶ est susceptible de favoriser indirectement la séquestration des métaux lourds présents dans l'environnement. Les mécanismes fins induisant cette séquestration restent encore à élucider. Il est possible que la sécrétion d'exopolymères (EPS) par le biofilm ̶ plus importante sur le béton que sur les autres matériaux étudiés ̶ en soit le vecteur et que ces composés contaminent par la suite le macrofouling (Bhaskar & Bhosle 2006).

La micro-complexité du matériau, étudié dans la deuxième partie du chapitre 3 (Chap. 3. Part.

2), nous donne peut-être quelques éléments d'explication. En effet, si l'on suit la logique de l'étude

de Huang et al. (2018)

sur l'analyse de la microtopographie (de 100 à 200µm) selon un gradient d'impression de vagues angulaires (

  sur les RA afin de proposer des moyens de choisir le matériau, la structure et d'émettre des limitations d'immersion en fonction de leur impact sur le milieu naturel. Un récif artificiel constitue un outil d'ingénierie écologique intéressant à condition qu'il respecte l'environnement. Schéma résumant les différentes étapes de la récupération du model 3D au calcul des paramètres de complexité Annexe 3 : Script R pour le calcul des paramètres de complexité Les scripts présentés ci-dessous peuvent être utilisés pour faire le calcul de différents indices de complexité (D, ik, SDnz, et R) sur les modules numériques des récifs artificiels ou sur les surfaces des matériaux reconstitués par scanner surfacique. Au préalable il est nécessaire d'extraire à partir d'un fichier STL les nuages de points et les normales des modèles comme présenté dans l'Annexe 3.ANNEXE 3.1 : SCRIPT RELATIF AU CHAPITRE 3 PARTIE 1 : ETUDE DE LA COMPLEXITE DES MODULES DE RECIFS ARTIFICIELS # prepare the envrionment setwd("C:/MyFile") # path where are the table with the point clouds and normal initial.wd=getwd() # gives the address where I work list=list.files(initial.wd) # name list of all the tables # libraries library(Rdimtools) # for fractal dimension output=NULL # create an empty object « output » in which all the indexes will be combined M=read.table(paste0(initial.wd,"/",list[i]), h=T, sep=" ") # read each table of the list P=M[,1:3] # extraction of the points from the table N=M[,4:6] # extraction of the normal from the table# processing of Dn outputD=est.boxcount(P, nlevel=100, cut = c(0.1,0.9)) # the result of the function est.boxcount Dn=1-(3-outputD$estdim)# compile the fractal dimension normalized between 0 and 1 # processing of SDnz SDn=as.matrix(apply(N,2,sd)) # processing of the standard deviation on the director cosines SDnz=SD[3] # SD[3] must correspond to the director cosines on the Z axe.# save the data row.names(output)=list # rename the row with the names of the AR modules colnames(output)=c("Dn","SDnz") # rename the columns with the names of the index write.csv2(output,"Complexity_Modules.csv") ANNEXE 3.2 : SCRIPT RELATIF AU CHAPITRE 3 PARTIE 2 : ETUDE DE LA MICROTOPOGRAPHIE # prepare the envrionment setwd("C:/MyFile ") # path where are the table with the point clouds and normal initial.wd=getwd() # gives the address where I work list=list.files(initial.wd) # name list of all the tables

	square <-function(x){
	squared <-x*x
	return(squared)
	}
	# libraries
	library(Rdimtools) # for fractal dimension
	library(seewave) # for rugosity
	# create a function to process the squared of the number

ANNEXES 186

Annexe 1:

### create a loop to process all the indexes in a row for each table ### for (i in 1:length(list)) { cat(paste0("---",Sys.time(),"processing_",list[i]," ---/n")) # to monitor the processing time for each table

.

# compilation of the indexes in the object ''output

'' output=rbind(output,c(Dn,SDnz)

) }

Peu de temps après, Son Altesse Sérénissime le Prince Albert II de Monaco en visite officielle aux Pays-Bas, accompagné de Son Excellence Monsieur Bernard FAUTRIER, Vice-Président de la Fondation Prince Albert II de Monaco, rencontre plusieurs industriels dont les représentants de la Société Boskalis qui présentent le concept de récifs artificiels réalisés avec une imprimante 3D. Le caractère innovant de ces récifs permet à la Société Boskalis de mettre en place dès 2015 un projet pilote à Monaco, coordonné par Madame Jamie LESCINSKI, ingénieur en océanographie, en partenariat avec la Fondation Prince Albert II de Monaco et Madame Jacqueline GAUTIER-DEBERNARDI, Directeur de l'Association Monégasque pour la Protection de la Nature (AMPN), gestionnaire des aires marines protégées de Monaco à qui revient le soin de mettre en oeuvre ce projet dans l'aire marine protégée du Larvotto. L'expertise du Professeur Patrice FRANCOUR (UMR ECOSEAS), spécialiste des populations de poissons et des récifs artificiels a permis d'imaginer le design des récifs en bénéficiant des avantages liés à la technologie de l'impression 3D. Un design complexe, proche de la réalité du milieu naturel, a offert la possibilité de reconstituer les habitats spécifiques d'espèces patrimoniales. Le Professeur Patrice FRANCOUR a par la suite lancé un programme de recherche sur l'étude de la structure des récifs artificiels. Ce programme a été complété par l'étude de la qualité du matériau en collaboration avec les Docteurs Cédric HUBAS et Dominique LAMY (UMR BOREA) à travers le travail de Master 2 et de Doctorat de Mademoiselle Elisabeth RIERA.

© Stéphane Jamme -Les Aquanautes

Abstract

In order to meet some of the prerogatives of the UNEP guidelines for artificial reefs, it seems worthwhile to be concerned about the quality of the substrates used for the construction of artificial reefs. Little comparative monitoring exists to date and does not allow to determine if pollutants are trapped within the communities that develop on these substrates. The present study evaluates the quality of different substrates (concrete, dolomite and rock) over a one-year monitoring from the biofilm communities to the succession of the macrofouling communities in two marine protected area (Larvotto reserve of Monaco and Roquebrune Cap Martin). We have been able to demonstrate that the nature of the substrate has little influence on the structure of communities (biofilm & macrofouling), however it significantly influences the secretion of biofilm as well as the sequestration of heavy metals present in the environment.

Key words : artificial reef substrates, artificial reef colonisation, biofilm community, photosynthetic pigments, metagenomic on prokaryote, biofilm matrix, extracellular polymeric substances, macrofouling community, heavy metal contamination, bio-indicator Abstract Artificial reefs (AR) are often considered as a true ecological engineering solution for restoration and conservation issues. In order to become a real Nature Based Solution, it is necessary to focus on their intrinsic characteristics such as the material used to design them or even their three-dimensional arrangement as relevant characteristics for the settlement of specific communities. In this study, the structural complexity of common single AR modules has been computed using 3D computer aided design (CAD) models. Their structural complexity has been determined by calculating four different variables normalised between 0 and 1: roughness (Topo), porosity (Poro), fractal dimension (Dn) and the standardised deviation of the normal on the vertical plane (Sdnz). Then, the heterogeneity of different kinds of combinations of AR modules (set, group, complex) has been computed with the Shannon index (H') weighted by the volumes of the deployed unit reefs. This study demonstrates that our method is reliable to evaluate the structure of virtually all kinds of artificial reefs, from a given module to any kind of combination.

Keywords: Artificial reef, Complexity structure, 3D CAD model, method

Abstract

The present study proposes to adapt indexes used to determine the complexity of artificial modules to the microscale of the materials used to build artificial reefs. The aims is to be able to relate these complexity parameters to the physiological activity of photosynthetic communities. We have hypothesized that the landscape characteristics of the material are likely to influence the physiology and abundance of photosynthetic organisms in the biofilm.

The use of a surface scanner made it possible to reconstruct a 3D model of the surface of the materials in order to calculate its complexity. We characterize the activity of photosynthetic microorganisms in biofilm communities by Imaging Pam. The indices used at the macroscopic scale are efficient to the study of complexity at the microscopic scale. We have been able to demonstrate that micro-complexity has a positive influence on the abundance of species.

Moreover, the orientation of the surface plays a key role in the conservative adaptation to the incidence of light. The micro-complexity of the material seems to constitute various niches for micro-organisms, which induce a different distribution and activity of the microbial communities within the biofilm.

Roughness "R"

The Topo index was not easy to determine at this finer scale. Then we used a different approximation of the rugosity by taking into account the variations of the continuity of the surface. For this, the "roughness" function of the R "Seewave" package [START_REF] Sueur | Equipment review: Seewave, a free modular tool for sound analysis and synthesis[END_REF] makes it possible to calculate an index easily. This function calculates the integral of the second squared derivative.

EQUATION 11: 𝑟 = ∫ 𝐷 2 𝑥(𝑡) 2 𝑑𝑡 𝑎 𝑏 𝑡: is the x-axis and a and b being the cloud of points.

To enable this function to operate, it is necessary to transform the point cloud into a continuous line in order to calculate its integral. For this, the x values of the points have been rounded to the tenth. Each level of x will therefore have a cloud of points on a two-dimensional axis y z. The curves thus represented can give a roughness index via the package R. The average of all the indices harvested is then considered as the average roughness of the mesh treated with the levels of x. The same operation is repeated by rounding the values of y instead of x. A precise idea of the roughness of the surface can be approximated by averaging between the roughness of the levels of x and levels of y previously calculated.

Fractal dimension

The fractal dimension is calculated for a surface then the fractal dimension of an object in a surface ranges between 1 and 2: 1 is a flat surface and 2 a surface highly folded. We normalized the results between 0 and 1 with the following equation:

Vector dispersion "ik"

At this scale, a previous study highlights the efficiency of the vector dispersion "ik" which measures the uniformity in angles of a surface [START_REF] Carleton | Effects of substratum irregularity on success of coral settlement: quantification by comparative geomorphological techniques[END_REF]) instead of SDnz.

We thus decided to use both indexes to compare them. Mathematically, "ik" estimates vector variance for all normal vectors of individual planar surfaces. It is a value between 0 and 1, where 0 indicates a flat plane and a number closer to 1 indicates a more complex surface, with a highly Accessible via :

RÉFÉRENCES Annexe 2: Extraction des données sur MeshLab et Cloud Compare

https://www.researchgate.net/publication/334262796_An_easy_method_to_assess_3D_underwater_habitat_st ructure_Application_on_Artificial_Reef